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Category : Protein Folding

First subject dosed with ZF874, a potential disease-modifying treatment for alpha-1-antitrypsin deficiency – Cambridge Network

AATD is a common genetic disorder, affecting around in 1 in 2000 people in Western countries, where a single mistake in the DNA encoding the protein alpha-1-antitrypsin (A1AT) causes both liver and lung disease.

Nearly all of the cases of AATD are caused by just a single mutation in the A1AT gene, known as the Z mutation. The Z mutation causes most of the A1AT to misfold, forming polymers that stay in the liver instead of being secreted into the blood where it plays a key role in protecting the lungs and other organs from the damaging effects of inflammation explained Jim Huntington, Professor at the University of Cambridge and Founder of Z Factor (pictured). The low levels of correctly-folded A1AT in the lungs results in the development of emphysema in nearly all AATD sufferers. At the same time, accumulation of Z-A1AT polymers in the liver can cause liver disease, sometimes manifesting as liver failure in newborns and more commonly cirrhosis and liver cancer as carriers of this mutation age.

ZF874 was developed with the help of a proprietary crystal structure solved by the Huntington lab. It is a novel compound that acts as a molecular patch for the faulty protein, allowing it to fold correctly, thereby simultaneously relieving the liver burden of polymer accumulation and providing fully-functional Z-A1AT in the circulation to protect the lungs. In mice genetically engineered to express human Z-A1AT in their livers, oral doses of ZF874 were able to substantially increase levels of correctly folded protein in the blood and to completely eliminate accumulation of misfolded protein in the liver.

We are excited to have dosed our first human volunteer with ZF874, said Trevor Baglin, Chief Medical Officer for Z Factor. This trial is designed to allow us to determine how safe and effective it is at raising Z-A1AT levels in humans in a short period of time. We expect to have top-line results for this potentially disease-modifying treatment in subjects carrying the Z mutation by the end of this year.

ZF874 has an excellent safety profile in preclinical toxicology studies and is suitable for oral dosing, ideal for the long-term treatment of patients with AATD, and eventually in the 2-3% of the population carrying a single copy of this mutant gene, who are also at increased risk of both liver and lung disease.

Only one other program targeting Z-A1AT folding is currently in the clinic, from the US pharmaceutical company Vertex (NASDAQ: $VRTX), who expect to report data on a similar time-frame to Z Factor.

The burden of disease caused by the Z-A1AT genetic defect has largely gone under the radar, said David Grainger, Executive Chairman at Z Factor. As many as a third of all emphysema and cirrhosis cases in Western countries, amounting to millions of patients, can trace the origins of their disease to this single error in their DNA. There is a huge unmet clinical need here.

Z Factor was founded in 2015, as a spin-out from the University of Cambridge, armed with the worlds first detailed structure of the Z-A1AT polymer from the Huntington laboratory. Cambridge Enterprise, the commercialisation arm of the University of Cambridge, licensed the technology into Z Factor. Cambridge Enterprise also participated in both the seed round and the Series A round, which was led by Medicxi, with Cambridge Innovation Capital participating.

The funding allowed the team to leverage this window onto the folding defect caused by the Z mutation, working in collaboration with the local out-sourced discovery platform company, RxCelerate, to create ZF874. Entry into the clinic marks a significant step in the development pathway for a drug from concept to approval.

We are one important step closer to delivering a drug that will not only treat the diseases associated with AATD, but that, given prophylactically, may ensure carriers of the Z mutation never develop these diseases in the first place said Huntington.

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These Enzyme-Mimicking Polymers May Have Helped Start Life on Earth – SciTechDaily

The micrograph shows uniform nanoparticles under 10nm in diameter. Credit: Tony Z. Jia, ELSI

Earth-Life Science Institute scientists find that small highly branched polymers that may have formed spontaneously on early Earth can mimic modern biological protein enzyme function. These simple catalytic structures may have helped jump start the origins of life.

Most effort in origins of life research is focused on understanding the prebiotic formation of biological building blocks. However, it is possible early biological evolution relied on different chemical structures and processes, and these were replaced gradually over time by eons of evolution. Recently, chemists Irena Mamajanov, Melina Caudan and Tony Jia at the Earth-Life Science Institute (ELSI) in Japan borrowed ideas from polymer science, drug delivery, and biomimicry to explore this possibility. Surprisingly, they found that even small highly branched polymers could serve as effective catalysts, and these may have helped life get started.

In modern biology, coded protein enzymes do most of the catalytic work in cells. These enzymes are made up of linear polymers of amino acids, which fold up and double-back on themselves to form fixed three-dimensional shapes. These preformed shapes allow them to interact very specifically with the chemicals whose reactions they catalyze. Catalysts help reactions occur much more quickly than they would otherwise, but dont get consumed in the reaction themselves, so a single catalyst molecule can help the same reaction happen many times. In these three-dimensional folded states, most of the structure of the catalyst doesnt directly interact with the chemicals it acts on, and just helps the enzyme structure keep its shape.

Metal sulfide enzymes could have originated from globular metal-sulfide/hyperbranched polymer particles. Credit: Irena Mamajanov, ELSI

In the present work, ELSI researchers studied hyperbranched polymers tree-like structures with a high degree and density of branching which are intrinsically globular without the need for informed folding which is required for modern enzymes. Hyperbranched polymers, like enzymes, are capable of positioning catalysts and reagents, and modulating local chemistry in precise ways.

Most effort in origins of life research is focused on understanding the prebiotic formation of modern biological structures and building blocks. The logic is that these compounds exist now, and thus understanding how they could be made in the environment might help explain how they came to be. However, we only know of one example of life, and we know that life is constantly evolving, meaning that only the most successful variants of organisms survive. Thus it may be reasonable to assume modern organisms may not be very similar to the first organisms, and it is possible prebiotic chemistry and early biological evolution relied on different chemical structures and processes than modern biology to reproduce itself. As an analogy with technological evolution, early cathode-ray TV sets performed more or less the same function as modern high definition displays, but they are fundamentally different technologies. One technology led to the creation of the other in some ways, but it was not necessarily the logical and direct precursor of the other.

If this kind of scaffolding model for biochemical evolution is true, the question becomes what sort of simpler structures, besides those used in contemporary biological systems, might have helped carry out the same sorts of catalytic functions modern life requires? Mamajanov and her team reasoned that hyperbranched polymers might be good candidates.

The team synthesized some of the hyperbranched polymers they studied from chemicals that could reasonably be expected to have been present on early Earth before life began. The team then showed that these polymers could bind small naturally occurring inorganic clusters of atoms known as zinc sulfide nanoparticles. Such nanoparticles are known to be unusually catalytic on their own.

As lead scientist Mamajanov comments, We tried two different types of hyperbranched polymer scaffolds in this study. To make them work, all we needed to do was to mix a zinc chloride solution and a solution of polymer, then add sodium sulfide, and voila, we obtained a stable and effective nanoparticle-based catalyst.

The teams next challenge was to demonstrate that these hyperbranched polymer-nanoparticle hybrids could actually do something interesting and catalytic. They found that these metal sulfide doped polymers that degrade small molecules were especially active in the presence of light, in some cases they catalyzed the reaction by as much as a factor of 20. As Mamajanov says, So far we have only explored two possible scaffolds and only one dopant. Undoubtedly there are many, many more examples of this remaining to be discovered.

The researchers further noted this chemistry may be relevant to an origins of life model known as the Zinc World. According to this model, the first metabolism was driven by photochemical reactions catalyzed by zinc sulfide minerals. They think that with some modifications, such hyperbranched scaffolds could be adjusted to study analogs of iron or molybdenum-containing protein enzymes, including important ones involved in modern biological nitrogen fixation. Mamajanov says, The other question this raises is, assuming life or pre-life used this kind of scaffolding process, why did life ultimately settle upon enzymes? Is there an advantage to using linear polymers over branched ones? How, when and why did this transition occur?

Reference: Protoenzymes: The Case of Hyperbranched Polymer-Scaffolded ZnS Nanocrystals by Irena Mamajanov, Melina Caudan and Tony Z. Jia, 13 August 2020, Life.DOI: 10.3390/life10080150

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Protein domain – Wikipedia

Conserved part of a protein

A protein domain is a conserved part of a given protein sequence and tertiary structure that can evolve, function, and exist independently of the rest of the protein chain. Each domain forms a compact three-dimensional structure and often can be independently stable and folded. Many proteins consist of several structural domains. One domain may appear in a variety of different proteins. Molecular evolution uses domains as building blocks and these may be recombined in different arrangements to create proteins with different functions. In general, domains vary in length from between about 50 amino acids up to 250 amino acids in length.[1] The shortest domains, such as zinc fingers, are stabilized by metal ions or disulfide bridges. Domains often form functional units, such as the calcium-binding EF hand domain of calmodulin. Because they are independently stable, domains can be "swapped" by genetic engineering between one protein and another to make chimeric proteins.

The concept of the domain was first proposed in 1973 by Wetlaufer after X-raycrystallographic studies of hen lysozyme[2] and papain[3]and by limited proteolysis studies of immunoglobulins.[4][5] Wetlaufer defined domains as stable units of protein structure that could fold autonomously. In the past domains have been described as units of:

Each definition is valid and will often overlap, i.e. a compact structural domain that is found amongst diverse proteins is likely to fold independently within its structural environment. Nature often brings several domains together to form multidomain and multifunctional proteins with a vast number of possibilities.[9] In a multidomain protein, each domain may fulfill its own function independently, or in a concerted manner with its neighbours. Domains can either serve as modules for building up large assemblies such as virus particles or muscle fibres, or can provide specific catalytic or binding sites as found in enzymes or regulatory proteins.

An appropriate example is pyruvate kinase (see first figure), a glycolytic enzyme that plays an important role in regulating the flux from fructose-1,6-biphosphate to pyruvate. It contains an all- nucleotide binding domain (in blue), an /-substrate binding domain (in grey) and an /-regulatory domain (in olive green),[10] connected by several polypeptide linkers.[11] Each domain in this protein occurs in diverse sets of protein families.[12]

The central /-barrel substrate binding domain is one of the most common enzyme folds. It is seen in many different enzyme families catalysing completely unrelated reactions.[13] The /-barrel is commonly called the TIM barrel named after triose phosphate isomerase, which was the first such structure to be solved.[14] It is currently classified into 26 homologous families in the CATH domain database.[15] The TIM barrel is formed from a sequence of -- motifs closed by the first and last strand hydrogen bonding together, forming an eight stranded barrel. There is debate about the evolutionary origin of this domain. One study has suggestedthat a single ancestral enzyme could have diverged into several families,[16] while another suggests that a stable TIM-barrel structure has evolvedthrough convergent evolution.[17]

The TIM-barrel in pyruvate kinase is 'discontinuous', meaning that more than one segment of the polypeptide is required to form the domain. This is likely to be the result of the insertion of one domain into another during the protein's evolution. It has been shown from known structures that about a quarter of structural domains are discontinuous.[18][19] The inserted -barrel regulatory domain is 'continuous', made up of a single stretch of polypeptide.

The primary structure (string of amino acids) of a protein ultimately encodes its uniquely folded three-dimensional (3D) conformation.[20] The most important factor governing the folding of a protein into 3D structure is the distribution of polar and non-polar side chains.[21] Folding is driven by the burial of hydrophobic side chains into the interior of the molecule so to avoid contact with the aqueous environment. Generally proteins have a core of hydrophobic residues surrounded by a shell of hydrophilic residues. Since the peptide bonds themselves are polar they are neutralised by hydrogen bonding with each other when in the hydrophobic environment. This gives rise to regions of the polypeptide that form regular 3D structural patterns called secondary structure. There are two main types of secondary structure: -helices and -sheets.

Some simple combinations of secondary structure elements have been found to frequently occur in protein structure and are referred to as supersecondary structure or motifs. For example, the -hairpin motif consists of two adjacent antiparallel -strands joined by a small loop. It is present in most antiparallel structures both as an isolated ribbon and as part of more complex -sheets. Another common super-secondary structure is the -- motif, which is frequently used to connect two parallel -strands. The central -helix connects the C-termini of the first strand to the N-termini of the second strand, packing its side chains against the -sheet and therefore shielding the hydrophobic residues of the -strands from the surface.

Covalent association of two domains represents a functional and structural advantage since there is an increase in stability when compared with the same structures non-covalently associated.[22] Other, advantages are the protection of intermediates within inter-domain enzymatic clefts that mayotherwise be unstable in aqueous environments, and a fixed stoichiometric ratio of the enzymatic activity necessary for a sequential set of reactions.[23]

Structural alignment is an important tool for determining domains.

Several motifs pack together to form compact, local, semi-independent units called domains.[6]The overall 3D structure of the polypeptide chain is referred to as the protein's tertiary structure. Domains are the fundamental units of tertiary structure, each domain containing an individual hydrophobic core built from secondary structural units connected by loop regions. The packing of the polypeptide is usually much tighter in the interior than the exterior of the domain producing a solid-like core and a fluid-like surface.[24] Core residues are often conserved in a protein family, whereas the residues in loops are less conserved, unless they are involved in the protein's function. Protein tertiary structure can be divided into four main classes based on the secondary structural content of the domain.[25]

Domains have limits on size.[27] The size of individual structural domains varies from 36 residues in E-selectin to 692 residues in lipoxygenase-1,[18] but the majority, 90%, have fewer than 200 residues[28] with an average of approximately 100 residues.[29] Very short domains, less than 40 residues, are often stabilised by metal ions or disulfide bonds. Larger domains, greater than 300 residues, are likely to consist of multiple hydrophobic cores.[30]

Many proteins have a quaternary structure, which consists of several polypeptide chains that associate into an oligomeric molecule. Each polypeptide chain in such a protein is called a subunit. Hemoglobin, for example, consists of two and two subunits. Each of the four chains has an all- globin fold with a heme pocket.

Domain swapping is a mechanism for forming oligomeric assemblies.[31] In domain swapping, a secondary or tertiary element of a monomeric protein is replaced by the same element of another protein. Domain swapping can range from secondary structure elements to whole structural domains. It also represents a model of evolution for functional adaptation by oligomerisation, e.g. oligomeric enzymes that have their active site at subunit interfaces.[32]

Nature is a tinkerer and not an inventor,[33] new sequences are adapted from pre-existing sequences rather than invented. Domains are the common material used by nature to generate new sequences; they can be thought of as genetically mobile units, referred to as 'modules'. Often, the C and N termini of domains are close together in space, allowing them to easily be "slotted into" parent structures during the process of evolution. Many domain families are found in all three forms of life, Archaea, Bacteria and Eukarya.[34] Protein modules are a subset of protein domains which are found across a range of different proteins with a particularly versatile structure. Examples can be found among extracellular proteins associated with clotting, fibrinolysis, complement, the extracellular matrix, cell surface adhesion molecules and cytokine receptors.[35] Four concrete examples of widespread protein modules are the following domains: SH2, immunoglobulin, fibronectin type 3 and the kringle.[36]

Molecular evolution gives rise to families of related proteins with similar sequence and structure. However, sequence similarities can be extremely low between proteins that share the same structure. Protein structures may be similar because proteins have diverged from a common ancestor. Alternatively, some folds may be more favored than others as they represent stable arrangements of secondary structures and some proteins may converge towards these folds over the course of evolution. There are currently about 110,000 experimentally determined protein 3D structures deposited within the Protein Data Bank (PDB).[37] However, this set contains many identical or very similar structures. All proteins should be classified to structural families to understand their evolutionary relationships. Structural comparisons are best achieved at the domain level. For this reason many algorithms have been developed to automatically assign domains in proteins with known 3D structure; see 'Domain definition from structural co-ordinates'.

The CATH domain database classifies domains into approximately 800 fold families; ten of these folds are highly populated and are referred to as 'super-folds'. Super-folds are defined as folds for which there are at least three structures without significant sequence similarity.[38] The most populated is the /-barrel super-fold, as described previously.

The majority of proteins, two-thirds in unicellular organisms and more than 80% in metazoa, are multidomain proteins.[39] However, other studies concluded that 40% of prokaryotic proteins consist of multiple domains while eukaryotes have approximately 65% multi-domain proteins.[40]

Many domains in eukaryotic multidomain proteins can be found as independent proteins in prokaryotes,[41] suggesting that domains in multidomain proteins have once existed as independent proteins. For example, vertebrates have a multi-enzyme polypeptide containing the GAR synthetase, AIR synthetase and GAR transformylase domains (GARs-AIRs-GARt; GAR: glycinamide ribonucleotide synthetase/transferase; AIR: aminoimidazole ribonucleotide synthetase). In insects, the polypeptide appears as GARs-(AIRs)2-GARt, in yeast GARs-AIRs is encoded separately from GARt, and in bacteria each domain is encoded separately.[42]

Multidomain proteins are likely to have emerged from selective pressure during evolution to create new functions. Various proteins have diverged from common ancestors by different combinations and associations of domains. Modular units frequently move about, within and between biological systems through mechanisms of genetic shuffling:

The simplest multidomain organization seen in proteins is that of a single domain repeated in tandem.[46] The domains may interact with each other (domain-domain interaction) or remain isolated, like beads on string. The giant 30,000 residue muscle protein titin comprises about 120 fibronectin-III-type and Ig-type domains.[47] In the serine proteases, a gene duplication event has led to the formation of a two -barrel domain enzyme.[48] The repeats have diverged so widely that there is no obvious sequence similarity between them. The active site is located at a cleft between the two -barrel domains, in which functionally important residues are contributed from each domain. Genetically engineered mutants of the chymotrypsin serine protease were shown to have some proteinase activity even though their active site residues were abolished and it has therefore been postulated that the duplication event enhanced the enzyme's activity.[48]

Modules frequently display different connectivity relationships, as illustrated by the kinesins and ABC transporters. The kinesin motor domain can be at either end of a polypeptide chain that includes a coiled-coil region and a cargo domain.[49] ABC transporters are built with up to four domains consisting of two unrelated modules, ATP-binding cassette and an integral membrane module, arranged in various combinations.

Not only do domains recombine, but there are many examples of a domain having been inserted into another. Sequence or structural similarities to otherdomains demonstrate that homologues of inserted and parent domains can exist independently. An example is that of the 'fingers' inserted into the 'palm' domain within the polymerases of the Pol I family.[50] Since a domain can be inserted into another, there should always be at least one continuous domain in a multidomain protein. This is the main difference between definitions of structural domains and evolutionary/functional domains. An evolutionary domain will be limited to one or two connections between domains, whereas structural domains can have unlimited connections, within a given criterion of the existence of a common core. Several structural domains could be assigned to an evolutionary domain.

A superdomain consists of two or more conserved domains of nominally independent origin, but subsequently inherited as a single structural/functional unit.[51] This combined superdomain can occur in diverse proteins that are not related by gene duplication alone. An example of a superdomain is the protein tyrosine phosphataseC2 domain pair in PTEN, tensin, auxilin and the membrane protein TPTE2. This superdomain is found in proteins in animals, plants and fungi. A key feature of the PTP-C2 superdomain is amino acid residue conservation in the domain interface.

Protein folding - the unsolved problem: Since the seminal work of Anfinsen in the early 1960s,[20] the goal to completely understand the mechanism by which a polypeptide rapidly folds into its stable native conformation remains elusive. Many experimental folding studies have contributed much to our understanding, but the principles that govern protein folding are still based on those discovered in the very first studies of folding. Anfinsen showed that the native state of a protein is thermodynamically stable, the conformation being at a global minimum of its free energy.

Folding is a directed search of conformational space allowing the protein to fold on a biologically feasible time scale. The Levinthal paradox states that if an averaged sized protein would sample all possible conformations before finding the one with the lowest energy, the whole process would take billions of years.[52] Proteins typically fold within 0.1 and 1000 seconds. Therefore, the protein folding process must be directed some way through a specific folding pathway. The forcesthat direct this search are likely to be a combination of local and global influences whose effects are felt at various stages of the reaction.[53]

Advances in experimental and theoretical studies have shown that folding can be viewed in terms of energy landscapes,[54][55] where folding kinetics is considered as a progressive organisation of an ensemble of partially folded structures through which a protein passes on its way to the folded structure. This has been described in terms of a folding funnel, in which an unfolded protein has a large number of conformational states available and there are fewer states available to the folded protein. A funnel implies that for protein folding there is a decrease in energy and loss of entropy with increasing tertiary structure formation. The local roughness of the funnel reflects kinetic traps, corresponding to the accumulation of misfolded intermediates. A folding chain progresses toward lower intra-chain free-energies by increasing its compactness. The chain's conformational options become increasingly narrowed ultimately toward one native structure.

The organisation of large proteins by structural domains represents an advantage for protein folding, with each domain being able to individually fold, accelerating the folding process and reducing a potentially large combination of residue interactions. Furthermore, given the observed random distribution of hydrophobic residues in proteins,[56] domain formation appears to be the optimal solution for a large protein to bury its hydrophobic residues while keeping the hydrophilic residues at the surface.[57][58]

However, the role of inter-domain interactions in protein folding and in energetics of stabilisation of the native structure, probably differs for each protein. In T4 lysozyme, the influence of one domain on the other is so strong that the entire molecule is resistant to proteolytic cleavage. In this case, folding is a sequential process where the C-terminal domain is required to fold independently in an early step, and the other domain requires the presence of the folded C-terminal domain for folding and stabilisation.[59]

It has been found that the folding of an isolated domain can take place at the same rate or sometimes faster than that of the integrated domain,[60] suggesting that unfavourable interactions with the rest of the protein can occur during folding. Several arguments suggest that the slowest step in the folding of large proteins is the pairing of the folded domains.[30] This is either because the domains are not folded entirely correctly or because the small adjustments required for their interaction are energetically unfavourable,[61] such as the removal of water from the domain interface.

Protein domain dynamics play a key role in a multitude of molecular recognition and signaling processes.Protein domains, connected by intrinsically disordered flexible linker domains, induce long-range allostery via protein domain dynamics.The resultant dynamic modes cannot be generally predicted from static structures of either the entire protein or individual domains. They can however be inferred by comparing different structures of a protein (as in Database of Molecular Motions). They can also be suggested by sampling in extensive molecular dynamics trajectories[62] and principal component analysis,[63] or they can be directly observed using spectra[64][65]measured by neutron spin echo spectroscopy.

The importance of domains as structural building blocks and elements of evolution has brought about many automated methods for their identification and classification in proteins of known structure. Automatic procedures for reliable domain assignment is essential for the generation of the domain databases, especially as the number of known protein structures is increasing. Although the boundaries of a domain can be determined by visual inspection, construction of an automated method is not straightforward. Problems occur when faced with domains that are discontinuous or highly associated.[66] The fact that there is no standard definition of what a domain really is has meant that domain assignments have varied enormously, with each researcher using a unique set of criteria.[67]

A structural domain is a compact, globular sub-structure with more interactions within it than with the rest of the protein.[68]Therefore, a structural domain can be determined by two visual characteristics: its compactness and its extent of isolation.[69] Measures of local compactness in proteins have been used in many of the early methods of domain assignment[70][71][72][73] and in several of the more recent methods.[28][74][75][76][77]

One of the first algorithms[70] used a C-C distance map together with a hierarchical clustering routine that considered proteins as several small segments, 10 residues in length. The initial segments were clustered one after another based on inter-segment distances; segments with the shortest distances were clustered and considered as single segments thereafter. The stepwise clustering finally included the full protein. Go[73] also exploited the fact that inter-domain distances are normally larger than intra-domain distances; all possible C-C distances were represented as diagonal plots in which there were distinct patterns for helices, extended strands and combinations of secondary structures.

The method by Sowdhamini and Blundell clusters secondary structures in a protein based on their C-C distances and identifies domains from the pattern intheir dendrograms.[66] As the procedure does not consider the protein as a continuous chain of amino acids there are no problems in treating discontinuous domains. Specific nodes in these dendrograms are identified as tertiary structural clusters of the protein, these include both super-secondary structures and domains. The DOMAK algorithm is used to create the 3Dee domain database.[75] It calculates a 'split value' from the number of each type of contact when the protein is divided arbitrarily into two parts. This split value islarge when the two parts of the structure are distinct.

The method of Wodak and Janin[78] was based on the calculated interface areas between two chain segments repeatedly cleaved at various residue positions. Interface areas were calculated by comparing surface areas of the cleaved segments with that of the native structure. Potential domain boundaries can be identified at a site where the interface area was at a minimum. Other methods have used measures of solvent accessibility to calculate compactness.[28][79][80]

The PUU algorithm[19] incorporates a harmonic model used to approximate inter-domain dynamics. The underlying physical concept is that many rigid interactions will occur within each domain and loose interactions will occur between domains. This algorithm is used to define domains in the FSSP domain database.[74]

Swindells (1995) developed a method, DETECTIVE, for identification of domains in protein structures based on the idea that domains have a hydrophobicinterior. Deficiencies were found to occur when hydrophobic cores from different domains continue through the interface region.

RigidFinder is a novel method for identification of protein rigid blocks (domains and loops) from two different conformations. Rigid blocks are defined as blocks where all inter residue distances are conserved across conformations.

The method RIBFIND developed by Pandurangan and Topf identifies rigid bodies in protein structures by performing spacial clustering of secondary structural elements in proteins.[81] The RIBFIND rigid bodies have been used to flexibly fit protein structures into cryo electron microscopy density maps.[82]

A general method to identify dynamical domains, that is proteinregions that behave approximately as rigid units in the course ofstructural fluctuations, has been introduced by Potestio et al.[62] and, among other applications was also usedto compare the consistency of the dynamics-based domainsubdivisions with standard structure-based ones. The method,termed PiSQRD, is publicly available in the form of a webserver.[83] The latter allows users to optimally subdivide single-chainor multimeric proteins into quasi-rigid domains[62][83] based on the collective modes of fluctuation of the system. By default thelatter are calculated through an elastic network model;[84]alternatively pre-calculated essential dynamical spaces can beuploaded by the user.

A large fraction of domains are of unknown function. Adomain of unknown function(DUF) is aprotein domainthat has no characterized function. These families have been collected together in thePfamdatabase using the prefix DUF followed by a number, with examples beingDUF2992andDUF1220. There are now over 3,000 DUF families within the Pfam database representing over 20% of known families.[86]

This article incorporates text and figures from George, R. A. (2002) "Predicting Structural Domains in Proteins" Thesis, University College London, which were contributed by its author.

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Protein domain - Wikipedia

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A computer’s all you need: Folding@Home joins the race to find a COVID-19 cure – The Stanford Daily

Today, you just need a computer Thats all you need. You dont need to have a fancy computer [or a] super modern computer. Anything will do, said Anton Thynell, head of collaboration and communication at [emailprotected]

Founded by chemistry, structural biology and computer science professor Vijay Pande in 2000 at Stanford, the global computing research community [emailprotected] (FAH) is now joining the race to find a cure for COVID-19. Volunteers from across the globe are downloading the FAH software, which is accessible to everyone, to run simulations of protein-folding in the background of their computer. The simultaneous running of these simulations contributes to researchers efforts to find treatments to certain diseases, illnesses and COVID-19.

[emailprotected] was originally a computing project that studied and simulated biomolecular systems. In 2006, collaborators from Stanford University joined the project and later increased computing performance to a level that rivaled that of a supercomputer.

Upon downloading the FAH software, volunteers are given specific proteins to run simulations on. They then can start folding by running their extra CPU power a part of the computer that operates instructions and later, they upload the results. The word folding comes from the process that proteins undergo when they are created. During that process, protein molecules transform from a long chain of amino acids to a complex shape (it folds up). The resulting structure allows researchers to understand the proteins properties and functions.

The FAH community aims to apply their professional knowledge along with volunteers computing power to understand the role of proteins dynamics in their function and dysfunction, and to aid in the design of new proteins and therapeutics. It is established as the worlds fastest supercomputer according to Ethan Zuo, president of [emailprotected] a group of volunteers who contribute to the [emailprotected] research project.

Thynell, who joined the [emailprotected] community in 2013, said that since COVID-19 began, he and his team have created a separate project that relied on the [emailprotected] concept to understand SARS-CoV-2.

[COVID-19] was really an all-hands-on-deck situation, Thynell said. I stopped working at my regular job and started full-time at [emailprotected] We grew our community [to] about 150 times [our past size] in three months. Thats where we are today.

Thynell broke down the process and importance of understanding protein dynamics when trying to find treatments or solutions to diseases, pandemics and more.

Most of the time, when youre studying biology, you look at proteins as a fixed structure, but theyre actually moving around, Thynell said.And there are tons of reactions happening in our cell structure all the time. So these proteins are actually like small machines We wanted to understand more about the virus and hopefully find some hidden pockets. Its like a treasure map, and sometimes you find a treasure.

These hidden pockets can open up for a certain period of time and you can look at them at potential[ly] druggable sites, which is very interesting for developing therapeutics, he added.

Zuo added that [emailprotected] is helping researchers study spike proteins, a type of protein that is part of the SARS-CoV-2 and allows the coronavirus to enter host cells. Zuo states that using extra computing power to run simulations of the virus can speed up the process of studying how these proteins work, which can then help researchers find ways to manipulate them using medicine.

When you download our software from our website and you have Wi-Fi or internet, you connect with our servers and download the small work unit thats a small part of a large simulation and your computer starts crunching away at it, Thynell said. You can decide how much computing power you want to dedicate or when you want to start. Its all up to you.

Recently, Zuo has been very active in volunteering for the [emailprotected] COVID-19 project. He leaves his computer on 24 hours a day so that it can build computational models to help identify sites of the spike protein that researchers can target through a therapeutic antibody.

[When] school shut down, everyone was doing online learning, Zuo said. When doing online learning, I realized that everyone is using their computers for a large fraction of the day [but] not 100% of their computing potential is used. So I decided to [help] put that extra compute power to good use Even though [emailprotected] is the worlds largest supercomputer, a surprising number of people dont know about [it].

By reaching out to more people, youll make the supercomputer more powerful [in] finding a cure for COVID-19 more quickly and gain knowledge more effectively, he added.

Recently, [emailprotected] has been working with COVID Moonshotan organization aiming to develop inexpensive patent-free therapeutics for COVID-19 to identify key compounds that may stop the main viral protease (Mpro),an enzyme that breaks down proteins of COVID-19. As of now, over 800 compounds have been simulated and tested. Volunteers are actively participating in weekly sprints in which they donate their computing power to crunching work units to collect and generate new designs for proteins. Additionally, researchers are constantly discovering new things about the virus and are actively publishing them on their home website.

To see and measure progress within [emailprotected] teams, volunteers are able to collect individual points for their contributions, which are displayed on a universal leaderboard. Depending on the computation power and system, certain amounts of points may also be awarded to teams, which puts them higher on the leaderboard.

According to Thynell, the leaderboard also shows what communities are participating in folding; these include tech companies such as Google, Reddit, Linus, NVIDIA and Intel. Global teams include China [emailprotected] Power, Overclockers Australia and TSC Russia.

What was really interesting is that [emailprotected] is global, Thynell said. We have people contributing from every part of the world. And its really amazing to see a global community coming together and fighting the virus, with the spare computing power of your home computer. That has been really nice to see.

Contact Rachel Jiang at racheljiang310 at

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A computer's all you need: Folding@Home joins the race to find a COVID-19 cure - The Stanford Daily

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Scientists discover protein linked to depression and brain disorders – The Irish Times

Earlier diagnosis and better treatments for people with depression and certain brain disorders may be possible following a research breakthrough involving Belfast-based scientists.

They have found how a specific protein plays a crucial role in the generation of neurons the nerve cells that relay electrical signals it the brain. This was made possible by focusing on a specific time and location during brain development, and how its disruption can lead to intellectual disability and depression in adults.

A research team led by Queens University Belfast (QUB) in collaboration with the Centre for Regenerative Therapies at Dresden University in Germany have published their findings in the journal Genes & Development.

It is expected this breakthrough will have a major impact on our fundamental understanding of brain development and lead to earlier diagnosis and better treatments for people with certain brain disorders, said Dr Vijay Tiwari, who is based at the Wellcome-Wolfson Institute for Experimental Medicine at QUB.

Our study reveals the key role this protein plays during the birth of probably one of the most important cells in our body the neuron.

Brain development is a highly complex process that involves generating various types of cells at defined time points and locations during embryonic development, he explained. Any kind of interference during these processes is known to cause diseases including a range of intellectual disabilities.

Among these brain cell types, neurons are the working unit of the brain, designed to transmit information to other nerve cells and various tissues in the body, such as the muscles as well as storage of memory in our brain, he added.

While the field has rapidly advanced, the mechanisms creating the birth of neurons from their mother cells, called neural stem cells, in time and space during development has not been well understood until now.

To conduct their study, the researchers looked at brain samples to closely determine the development of various cell types within the brain.

The study showed how the presence of a specific protein (called Phf21b), within a defined time window of brain development and in a specific location in the brain, signals the birth of neurons from neural stem cells in the right place and at the right time, said Dr Tiwari, who is a molecular biologist working in neuroscience.

The researchers found that removal of Phf21b stopped production of neurons from neural stem cells and led to severe defects in brain development. They also found the importance of this protein, in particular in the folding of DNA in cells going on to form neurons.

Understanding how a cell type in the brain is born at a specific point and in a specific place during development is crucial in our understanding how neurological issues arise later in life. We hope this discovery will pave the way for earlier diagnosis, earlier interventions and better treatment for people with a brain disorder, such as depression, he said.

Their research suggested screening for certain genetic variants would enable earlier diagnosis, in contrast to a scenario where depression in adults is not usually detected until a person is seriously depressed.

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Scientists discover protein linked to depression and brain disorders - The Irish Times

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Europe Protein A Resins Market Research, Recent Trends and Growth Forecast 2025 – CueReport

A Research study on Europe Protein A Resins Market analyzes and offers ideas of exhaustive research on ancient and recent Europe Protein A Resins market size. Along with the estimated future possibilities of the market and emerging trends in the Europe Protein A Resins market.

Rapid expansion of biotechnology and pharmaceutical companies will spur protein A resins market growth. Also, rising funding for protein-based research will augment the market growth. However, availability of alternatives such as crystallization, ultrafiltration, capillary electrophoresis and high pressure folding for purification methods may restrain the industry growth in forthcoming years.

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Europe Protein A Resins MarketSize Estimated To Exceed USD 232.0 Million By 2026. Growing demand for chromatography for purification and discovery of biological entities will escalate the adoption of Protein A resins in Europe over the analysis timeframe. Owing to improved, cost-effective and widely accepted component for purification of biological samples, protein A resins are widely used in chromatography technique. Furthermore, increasing product approvals of monoclonal antibodies from regulatory bodies to cater the increasing demand for immunotherapy will further fuel the industry growth.

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Demand for protein A resins in biopharmaceutical companies will progress at 8.4% CAGR during the projection period. Growing demand for drug development coupled with increase research and development spending will augment the segment share. With rising adoption by biotechnology industries for protein A resins for antibody production, will offer profitable growth in the forecast timeframe.

Antibody purification application segment accounted for more than 77% revenue share in 2019. With rising incidence of chronic diseases such as rheumatoid arthritis, protein A resin kits are developed for purification of antibodies for structural and diagnostic studies. They are also used as molecular probes for research and development activities. Monoclonal antibodies exhibit remarkable results in the management of chronic conditions such as cancer and rheumatoid arthritis. Thus, wide applications and benefits of antibodies will render a lucrative potential for protein A resins market growth in the forthcoming years.

Agarose-based matrix segment is estimated to grow at 8.3% CAGR over the forecast timeframe. Suitable resolution, favorable pH conditions and high flow rate drives the segment growth over the forecast time period. The benefits of using agarose-based matrix include excellent biocompatibility, considerable mechanical resistance, and hydrophobic nature that significantly contribute to product preference, thus increasing segmental growth.

Europe protein A resins industry was led by Germany protein A resins market in 2019 and is estimated to show a positive trend throughout the projection period. UK protein A resins business is forecasted to proceed at more than 7.5% CAGR across the forecast timeframe. Increasing number of pharmaceutical industry and presence of major market players in the country will influence market growth in the future. Furthermore, expanding applications of immunotherapy will augment the UK protein A resins business growth in future.

Recombinant protein A resins market held more than USD 80 million revenue size in 2019. Recombinant protein A is generally formulated in E.coli and functioning is same as that of natural protein A resins. When other sources of production offer less non-specific binding, recombinant protein A resins are generally preferred. Thus, higher inclination towards recombinant protein A resins owing to its advantages will augment the segmental growth.

Major market players in Europe protein A resins market are Thermo Fisher Scientific, EMD Millipore, GE Healthcare, and Bio-Rad Laboratories among other industry participants. These market players are undertaking strategies such as technology advancements and inorganic growth strategies to strengthen their market presence and company expansion. For instance, in June 2018, Purolite introduced advanced protein A agarose resin. The new-generation resins, Praesto Jetted A50 shows improved performance aimed at widening their product and customer base.

A Pin-point overview of TOC of Europe Protein A Resins Market are:

Overview and Scope of Europe Protein A Resins Market

Europe Protein A Resins Market Insights

Industry analysis - Porter's Five Force

Company Profiles

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Europe Protein A Resins Market Research, Recent Trends and Growth Forecast 2025 - CueReport

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A math problem stumped experts for 50 years. This grad student from Maine solved it in days – The Boston Globe

The problem had to do with proving whether the Conway knot was something called slice, an important concept in knot theory that well get to a little later. Of all the many thousands of knots with 12 or fewer crossings, mathematicians had been able to determine the sliceness of all but one: the Conway knot. For more than 50 years, the knot stubbornly resisted every attempt to untangle its secret, along the way achieving a kind of mythical status. A sculpture of it even adorns a gate at the University of Cambridges Isaac Newton Institute for Mathematical Sciences.

Then, two years ago, a little-known graduate student named Lisa Piccirillo, who grew up in Maine, learned about the knot problem while attending a math conference. A speaker mentioned the Conway knot during a discussion about the challenges of studying knot theory. For example, the speaker said, we still dont know whether this 11-crossing knot is slice.

Thats ridiculous, Piccirillo thought while she listened. This is 2018. We should be able to do that. A week later, she produced a proof that stunned the math world.


Knot theory is a sub-specialty of a field of mathematics known as topology, which is concerned with the study of spaces. Whats it used for? The answer one memorizes is that topology is useful for understanding DNA and protein folding, Piccirillo tells me in May as we sit wearing masks and maintaining a good 10 feet of distance in an outdoor courtyard not far from where she lives in Harvard Square. Apparently these things are very long and they like to stick to themselves, so they get all knotted up.

When topologists think of knots, however, they dont imagine a length of rope with a gnarled twist in the middle. To them, a knot is more like an extension cord in which the two ends have been plugged together and the whole thing has been tossed onto the floor in a mess of crisscrosses. Its essentially a closed loop with various places where the loop crosses over itself.

Now lets take one of these knots and think for a moment about the space in which it exists. That space has a fourth dimension, such as time, and to a topologist, our knot is a kind of sphere that sits within it. Topologists see spheres everywhere, but in a specialized way: A circle is a one-dimensional sphere, while the skin surrounding an orange is a two-dimensional sphere. And here is where minds tend to get blown: If we were to take that whole orange and glue it to another one, topologists would see the resulting object as a three-dimensional sphere, one that could be viewed as the skin of a four-dimensional orange. Dont worry if you are unable to conjure such a higher-dimension image for yourself. There are only a couple hundred specialists doing this work in the world, and not even all of them can.

Piccirillo, who graduated from Boston College in 2013, was already well on her way to joining the ranks of those specialists when, in the summer of 2018, the speaker at the math conference said something that would change the trajectory of her career.

The speaker showed a slide depicting the Conway knot and explained that mathematicians had long suspected that the knot was not, in fact, slice, but no one had been able to prove it. So what does it mean for a knot to be slice? Lets return for a moment to that four-dimensional orange. Inside of it there are disks think of them as the surface of a plate. If a three-dimensional knot, like Conways, can bound such a disk, then the knot is slice. If it cannot, then it is not slice.

Topologists use mathematical tools called invariants to try to determine sliceness, but for half a century, those tools had been unable to help them prove the prevailing belief that the Conway knot wasnt slice. Sitting in that lecture hall two years ago, however, Piccirillo sensed right away that the techniques she was using in a different area of topology might help these invariants better apply to the Conway knot problem. I immediately knew that some work that I was doing for totally other reasons could at least try to answer this question, she says. She started on the problem the very next day.


Piccirillo, who is 29, grew up in Greenwood, Maine, a town with a population of less than 900. She was an excellent student and her mom taught middle school math, but there was little in her interests to suggest that she would become a world-class mathematician.

I was an overachiever, she says. I rode dressage. I was very active in the youth group at my church. I did drama. I was in band. I did everything. Which is another way of saying that she wasnt one of those math prodigies whos programming computers and building algorithms at age 4.

When Piccirillo arrived on campus for her first year at Boston College in 2009, she was as interested in theater and other subjects as she was math. During a calculus class that year, though, she made a connection with professor J. Elisenda Grigsby. (Disclosure: I am the editor of Boston Colleges alumni magazine.)

Piccirillo stood out, even if she lacked a certain polish, Grigsby recalls. Golden-child mathematicians usually went to math camp when they were in high school and had been groomed from a young age, she says. That wasnt Piccirillos background, but I felt a kinship to her.

She really encouraged me, Piccirillo says of Grigsby. Eli really pushed me into trying another math class, and then liking the next class. I had already started on a progression. By her senior year, she was taking graduate-level topology courses. After graduating in 2013, she chose to pursue her doctorate at the University of Texas because of the universitys excellent topology program and its reputation as a great place for female math students. In 2014, just 28.9 percent of math and science doctorates were awarded to women, according to the National Science Foundation, but at Texas, something like 40 percent of graduate math students were women.

By and large, Piccirillo has felt welcomed and encouraged as a female mathematician. But now and again, things happen, she tells me. For example, in grad school, I would receive notes in my department mailbox commenting on my appearance.

Overall, Piccirillo excelled during her six years at the University of Texas, finding both strong mentorship and a supportive research community. The time coincided with her deepening connection to the math itself. She loved to turn problems over in her mind, thinking about how one higher-dimension shape might be manipulated to resemble an entirely different one. It was thrilling, creative work, as much about aesthetic as arriving at a particular result. When you perform a calculation, sometimes theres really clever tricks you can use or some ways that you can be an actual human and not a computer in the performing of the calculation, Piccirillo says. But when you make a logical argument thats entirely yours.

Outside of her studies, Piccirillo liked to make beautiful things. She carved wooden spoons for a while, as well as large-scale woodcut prints of fish and vegetables. She and her roommate, Wiley Jennings, built a dining room table together. For a while, she was obsessed with buying and repairing 70s Japanese motorcycles.

She has a very, very strong sense of aesthetic, says James Farre, a friend of Piccirillos from the University of Texas who specializes in geometry and is a postdoc at Yale. At Piccirillos level, math that people like is often thought of and talked about as beautiful or deep.

The day after hearing about the Conway knot problem, Piccirillo, then 27, sat down at her desk and began looking for a solution. Because much of her graduate work involved building pairs of knots that were different but shared some 4-D properties, she already knew that any two knots that share the same 4-D space also share sliceness theyre either both slice or both not slice. Since her goal was to prove that the Conway knot wasnt slice, her first step was come up with an entirely different knot with the same four-dimensional space, she explains. Then Ill try to show that the other knot isnt slice.

She spent spare time over the next several days hand-sketching and manipulating configurations of the 4-D space occupied by the Conway knot. I didnt allow myself to work on it during the day, she told Quanta Magazine earlier this year, because I didnt consider it to be real math. I thought it was, like, my homework.

The next step was to try to prove that the knot she drew was not slice. There are lots of tools already in the literature for doing that, she says. She would feed the knot iterations into a computer, and based on the data of the knot, maybe based on how its crossings look or other data that you can pull from the knot, the algorithm spits out an integer. In less than a week, Piccirillo had created a knot that hit the sweet spot: It had the same 4-D properties as the Conway knot, and it was found by the algorithm to be not slice.

She had suddenly succeeded where countless mathematicians had failed for five decades. She had solved the Conway knot problem.


Not long after the breakthrough, Piccirillo attended a meeting with the Cameron Gordon, a University of Texas math professor. When she mentioned her solution, Gordon was skeptical. He asked Piccirillo to walk him through the steps. Then he made me write it down, like all up on the board, she recalls, and then he got very excited and started yelling.

Piccirillo submitted her solution to the Annals of Mathematics, and the prestigious math journal agreed to publish her paper. When I asked James Farre, the Yale postdoc, to explain the significance of having a paper published in the Annals he laughed for several seconds. Its head and shoulders the most important and influential journal in mathematics, he says. Thats why Im laughing. Its amazing and its so cool!

By the time Piccirillos paper appeared in the journal about a year later, word of her solution had already spread throughout the math world. After graduating from UT in 2019, Piccirillo started her postdoctoral work at Brandeis. The last time I saw her was in January, says Wiley Jennings, her roommate in Austin, who recently completed a doctorate at Stanford. She was out at a faculty visit here at Stanford. To be invited, as someone who has done one year or less [of postdoc study] just finished their PhD essentially I mean, thats insane. Its unheard of . . . I think thats when I first got a hint that like, Oh my gosh, shes really a hotshot.

Postdoc positions typically run for three or four years, but Piccirillo found herself in high demand. In July, she started a new tenure-track position as an assistant professor at MIT. Its been a whirlwind, and I wondered how her life has changed. The practical answer is not too much, she says. She still teaches undergrads and conducts her research. She acknowledges, though, that there sometimes is a feeling of pressure, based on what shes already accomplished. In practice, math for everyone is about trying to prove simple statements and failing, basically all of the time. So, she says, Im having to relearn how to be OK with the fact that most of the time Im failing to prove really simple stuff when Im feeling the weight of these expectations.

When I ask her about her goals, Piccirillo says one of her priorities is to help grow and broaden the mathematics community. There certainly are many young women, people of color, non-heterosexual, or non-gender binary people who feel put at an arms length by the institution of mathematics, she says. Its really important to me to help mitigate that in any small ways I can. One important way to do that, she continues, is to help shatter the myth of the math prodigy.

When universities organize math conferences, she says, they should avoid inviting speakers who give talks where they go really fast and they try to show you how smart they are and how hard their research is. Thats not good for anyone, but its especially not good for young people or people who are feeling maybe like they dont belong here. What those people in the audience dont know, she says, is that nobody else really understands it either.

You dont have to be really smart whatever that means to be a successful mathematician, Piccirillo says. Theres this idea that mathematicians are geniuses. A lot of them seem to be child prodigies that do these Olympiads. In fact, you dont have to come from that background at all to be very good at math and most mathematicians, including many of the really great ones, dont come from that sort of background.

And as Piccirillo herself proves, some of them even go on to produce work that alters the course of mathematics.


John Wolfson is the editor of Boston College Magazine. Follow him on Twitter @johnwolfson and send comments to

A math problem stumped experts for 50 years. This grad student from Maine solved it in days - The Boston Globe

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Rogue Waves: Freaks of Nature Studied with Math and Lasers – Inside Science News Service

The elusive waves, once thought to be myths, are explained by the same math that's found in a wide range of settings.

(Inside Science) -- During Columbus third voyage to the Americas, as his six-ship fleet sailed around the southern tip of Trinidad, an island just off the coast of Venezuela, they encountered a freak wave taller than the ships mast. The wave hoisted the ships up to its peak before dropping them down into a huge trough. Columbus would later name the passageway Boca del Serpiente -- Mouth of the Serpent -- for the ferocity of its waters.

Once regarded as myths or pieces of folklore, rogue waves can spike out of nowhere and dissipate just moments later, terrifying sailors and sinking ships. Half a millennium would pass after Columbus encounter before the first rogue wave was measured by a scientific instrument. On New Years Day of 1995, the Draupner oil platform perched in the North Sea off the coast of Norway spotted a wave 84 feet tall -- more than twice the height of its neighboring waves.

Like stock market crashes and devastating earthquakes, the study of rogue waves has been plagued by the scarcity of data.

The Draupner wave was the first time that a rogue wave was actually observed by a scientific instrument; before that it was all just people telling about it. But if we want to learn more about these waves, well need to obtain better statistics and more data, said Tobias Grafke, a physicist from the University of Warwick in the U.K. He is an author of a paper published in the journal Physical Review X that explored the probabilities of rogue waves from a statistical perspective.

It's a very localized phenomenon that comes out of nowhere. I mean, you can just put certain measurement points somewhere and hope that a rogue wave would come by, but it's very, very rare, said Hadas Frostig, a physicist from Boston University not involved in Grafkes paper.

Moreover, rogue waves are so strong that they often destroy the instruments trying to measure them, said Grafke.

Due to the difficulty of collecting real-world data -- even a team of satellites would probably struggle to spot the fleeting, unpredictable waves -- researchers have mostly studied rogue waves in wave pools, dialing in specific conditions that might generate a rogue wave.

An in-lab rogue wave experiment by researchers from the University of Oxford and the University of Edinburgh. [Credit: Ton van den Bremer and Mark McAllister at the University of Oxford.]

Scientists think rogue waves can be generated via two main mechanisms. In the first, waves of different wavelengths, peaking at the same spot, combine to build a massive wave. Because each of their amplitudes simply adds up to form the final height of the rogue wave, it is referred to as a linear process. In contrast, the second mechanism is nonlinear and has to do with how waves with different wavelengths interact and exchange energy with each other. (Check out this infographic by Quanta Magazine that explains the difference between the two concepts.)

A rogue wave can be built linearly or nonlinearly, or a combination of both.

Depending on how a wave model is set up, the relative importance of the two mechanisms is different. What we want is a theory that can predict the probability of these waves and the way they evolve given the state of the ocean, said Grafke. In other words, a model that can predict rogue waves based on the ocean condition without having to predetermine the significance for each mechanism.

Grafke and his colleagues developed a model based on mathematical concepts called solitons and instantons. Solitons are solitary excitations in a field, such as single, short pulses of light; instantons are mathematical devices for interpreting rare events in systems where random processes are present.

According to Amin Chabchoub, who studies environmental fluid mechanics at the University of Sydney in Australia and was not involved in the paper, the model is unique in its approach to predicting the occurrence of rogue waves independent of the formation mechanism.

The study of waves is rarely limited to a single medium. (For example, we have previously covered how a phenomenon called excitable waves plays a role in vastly different systems such as wildfires and heart arrhythmia.)

Since 2007, researchers have begun studying rogue waves in systems where the abundance of data is not a problem because the waves can be easily generated in huge numbers with existing technologies. Theses waves also happen to be much, much faster: light.

Once people started studying rogue waves, it spurred this whole field where people are asking what kind of physics gives rise to these very rare, very extreme events, said Frostig, who recently published a paper in the journal Optica that used laser systems to study rogue waves.

Using optical systems, scientists can generate the immense amount of data required to gauge the probabilities of rogue waves arising under different mechanisms. They have observed that optical rogue waves occur more frequently than would be expected if the waves formation were governed by Gaussian statistics, commonly known as a bell curve.

According to Frostig, rogue wave experiments in optical systems have primarily been focusing on how light waves of different wavelengths interact with each other to generate an extreme event. She and her colleagues discovered these mechanisms alone cannot account for the frequency of rogue waves present in their system. In this relatively young field, new results often create more questions than they answer.

Optical rogue waves do not play a significant role in fiber optics systems like those that bring internet to homes and offices, because the fibers are designed to prevent signals of different frequencies interfering with each other. Nor will ocean rogue wave models likely become a practical solution for safeguarding sailors anytime soon.

But the study of rogue waves and the statistics that govern them is not limited to the ocean or fiber optics. For example, speckle patterns -- the graininess of a laser when it is projected on a surface -- is related to optical rogue waves and has applications in imaging techniques.

Rogue waves also share a mathematical framework with other systems -- some of which arent even waves. Protein folding, disease transmission and even some animal population estimation techniques all display similar statistical characteristics as rogue waves.

The underlying math itself is very general, and it tells you how a system evolves around the probability of an extremely rare event, things like extreme shocks in acoustics systems, extreme voltage vortices and models for turbulence, said Grafke. It doesn't need to be a rogue wave.

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Rogue Waves: Freaks of Nature Studied with Math and Lasers - Inside Science News Service

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Power To The Tenth Power – IT Jungle

August 17, 2020Timothy Prickett Morgan

This is one of my favorite times of the year, with the Hot Chips symposium usually underway this week at Stanford University and all the vendors big and small trotting out their, well, hottest chippery. In this case, hot means extremely interesting but it often means burning shedloads of watts as well. But this is the time that the chip architects show off what they have been working on for four or five years and what has already been in production in recent months or will be in the coming months.

IBM tends to jump the gun a bit with its Power processors, and is doing so a little more than usual with the Power10 processor, which we frankly had hoped would be available later this year rather than later next year. But none of that matters. What does matter is that Power9 is giving customers plenty of headroom in compute at the moment and that Power10 will, thanks to the innovative engineering that Big Blue has come up with, be well worth the wait.

This is the kind of processor complex and system architecture that we have been waiting to see arrive for a long, long time. And we will be getting into the details of that architecture in the coming weeks after IBMs presentation is done at Hot Chips this week. In the meantime, IBM talked with us about how Power10 extends the lead that the Power architecture has over X86 and Arm alternatives for enterprise systems and we are going to focus on that ahead of the Power10 preview and talk to the top brass at Big Blue about how they had better start thinking about systems differently and get people to start thinking about them differently and then invest in IBMs own technology and build the best damned public cloud in the world based on it. We are talking about a moonshot-class investment the likes of which we have not seen out of IBM since it invested $100 million to create the BlueGene protein folding supercomputer back in 1999 to break through the petaflops performance barrier.

So without further ado, here is the wafer of Power10 chips that have come back as early silicon from the fabs at Samsun Electronics, IBMs manufacturing partner:

The research alliance that IBM set up with Samsung, Applied Materials, AMD, GlobalFoundries, and others many years ago has contributed tweaks to the 7 nanometer process that Samsung is using to make the Power10 chips, according to IBM, which is not just using Samsungs plain vanilla 7 nanometer etching, which is called V1 and which uses extreme ultraviolet (EUV) lithography techniques. (Similar to the ones that GlobalFoundries, the former AMD fab cut loose several years ago, was working on for Power10 when it decided in August 2018 to spike the whole 7 nanometer effort, and importantly both flavors of 7 nanometer using regular lithography and using EUV were killed off. Thus driving IBM into Samsungs waiting arms as a foundry partner for the Power10 chips. (Intel and Taiwan Semiconductor Manufacturing Corp were not going to get the deals, that is for sure.)

Samsung started building its V1 fab back in February 2018 and invested $6 billion in the effort in the first two years and has probably spend a few billion dollars more this year. Back in April 2019, Samsung said it was going to invest $115 billion between then and 2030 to build up its foundry both for its own use and for others like IBM. And it is about the safest bet that IBM has outside of GlobalFoundries when it comes to picking a fab partner, given its long history of collaboration with Samsung and the latter companys desire to boost its merchant foundry credentials. Everybody including Intel had better hope Samsung gets good at this, because there are not enough deep pockets otherwise to allay all of the risk as we move from 7 nanometers down to 5 nanometers down to 3 nanometers looking ahead in the current decade.

We are not at liberty to say much about Power10 as we go to press for the Monday issue of The Four Hundred, but we will do a series of follow-up stories to drill down into different aspects of the machines, which we have been prebriefed about under embargo for later today. Here is one thing that IBM did allow us to share with you:

I have only seen the core count of the Power10 chip detailed in a few internal roadmaps, and all of them said that Power10 would have 48 cores. This made logical sense, given that Power8 maxxed out at 12 cores and Power9 maxxed out at 24 skinny cores (or 12 fat ones) across the same 96 threads per die, mostly enabled from the shrink from 22 nanometers with Power8 to 14 nanometers with Power9. It was logical to assume that with the shrink to 7 nanometers that the core count could double up again.

What we now know from the roadmap above is that with the shrink to 7 nanometers, IBM gutted the core design and started with a clean slate to maximize the new 7 nanometer process something that we suspect it was not planning to do with the GlobalFoundries 7 nanometer process and crammed 16 fat cores or 32 skinny cores on a die. Only 15 fat cores or 30 skinny cores are activated to help improve the yield on the chips, assuming that at least 1 in 16 of the cores will be a dud on the new 7 nanometer process, as IBM and Samsung are assuming. At some point, when the yields on the V1 process improve, IBM could activate that latent 16th core and there is an instant performance upgrade for those using a newer stepping of the Power10 chip. The gutting of the microarchitecture is what has allowed IBM to boost the core count from 12 to 16 per chip moving from Power9 to Power10, which is considerably more than expected.

With Power10, IBM is cutting down on the number of chips it is making, which will also help lower costs but it also calls into question whether there will be a single-core or even dual-core variant aimed specifically at smaller IBM i shops. (We will fight that battle later.)

Rather than having three different chip implementations a half skinny chip and a full skinny chip for machines with one or two sockets and a full fat chip for big NUMA iron as it did with Power8 and Power9, IBM moving to a single chip with fat cores and putting one or two of them into a socket to get 30 cores or 60 cores into a socket. This is a much more aggressive strategy, and interestingly, either the single-chip module (SCM) or dual-chip module (DCM) variants of the Power10 chip can be run in SMT4 (four threads per core) or SMT8 (eight threads per core) mode. This mode is not switchable by users, but by IBM at the time it packages up the processor. In the past, to get 24 cores meant running in SMT4 mode, or four threads per core, and not all systems had this capability. This was just a funny way of isolating threads and caches to lower the core count and therefore enterprise software licenses for SMT8 customers, but it also meant raising the per-socket price on software running on the 24-core Power9 variant for software that was priced based on cores and not sockets. It would be useful if IBM could make this SMT level settable at system boot, but it is hard-coded into the processor microcode that customers cannot change because of the software pricing issue mentioned above.

We strongly suspect that IBM never intended to do a monolithic Power10 die with 48 cores on it, but rather a 7 nanometer shrink of the 24-core Nimbus part with some tweaks and then put two of them into a single socket to create a throughput monster. With the Power10 chip as it will be delivered, IBM can, in theory once yields improve, provide customers with 33 percent more cores and, if history is any guide, somewhere around 3X the raw throughput at the 4 GHz design point that IBM has used for Power chips since the Power7 way back in 2010. (The Power6 had a 5 GHz design point, which was quite impressive but not sustainable because Dennard scaling and Moores Law scaling were running out of steam.)

We cant say a lot about it right now, but this memory clustering technology, and indeed the whole memory subsystem of the Power10 chip, is the killer technology with Power10. IBM will be able to do things that other architectures simply cannot, with multi-petabyte memory clustering and sharing across large numbers of Power10 systems.

And that is why IBM has to be the one to invest in building and using these systems, to demonstrate their capabilities, and to make sure Power10 systems are available on the IBM Cloud on Day One of their launch and in huge numbers, not in prototype and proofs of concept onesies and twosies here and there around a dozen or so cloud regions. This is not about drinking the Kool-Aid, which is easy enough, but eating your own dog food first, as we say in this IT business. IBM has to move its own apps to its own cloud running on Power10 iron and be the case study that others can learn from and benefit from.

Theres plenty of time between now and the end of 2021 to make that happen, and IBM i customers as well as those running AIX and Linux should all be invited to come along for the ride.

Power Systems Slump Is Not As Bad As It Looks

The Path Truly Opens To Alternate Power CPUs, But Is It Enough?

Powers Of Ten

What Open Sourcing Powers ISA Means For IBM i Shops

IBMs Plan For Etching Power10 And Later Chips

The Road Ahead For Power Is Paved With Bandwidth

IBM Puts Future Power Chip Stakes In The Ground

What Will IBM i Do With A Power10 Processor?

Samsung Joins The OpenPower Consortium Party

Read more here:
Power To The Tenth Power - IT Jungle

Recommendation and review posted by Alexandra Lee Anderson

After COVID-19, capital will be different, stronger and more conscious –

VentureCrowd executive director and Maarbani Consulting managing director. Source: supplied.

Lets talk about sushi. I love the stuff. High protein, low fat, minimalist Japanese perfection. Its great with soy, pickled ginger and a sprinkle of microplastic.

Oh, you didnt know? Let me explain.

The modern lightweight shopping bag was invented by Swedish engineer Sten Gustaf Thulin in the early-1960s (stay with me, the connection is coming). Thulin developed and patented a method of forming a one-piece bag by folding, welding and die-cutting a flat tube of plastic for the packaging company Celloplast.

Nowadays, nearly 1 trillion plastic bags are consumed worldwide every year thats over 1 million per minute. Needless to say, the lifetime value of a plastic bag customer is a rock-solid metric, and a bunch of investors are making a ship-load of cash from this little beauty.

Convenient, cheap, disposable and, as it turns out, delicious.

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You see, most plastic trash in the oceans flows from land. Once at sea, sunlight, wind and wave action break down plastic waste into small particles called microplastics. They are less than 5 millimetres in length the size of a sesame seed and have been found in municipal drinking water systems, drifting through the air and in the seafood we eat.

Ah, the circle of life.

In just one generation, we went from being plastic-free pause for effect to a level of reliance on plastic that results in 12 million tonnes of plastic entering our oceans every year. Thats a full rubbish truck every minute.

But, whatever. Were all making money, right?

Oh, Thulin. Insert facepalm. As my mother would say, Im not angry, Im just disappointed.

The new reality is that the global investment landscape is changing.

A new generation of investors is awakening and they dont want plastic in their sushi. Backed by the largest intergenerational transfer of wealth in modern history, this group is demanding the opportunity to support companies that fund more sustainable futures and solve real-world problems.

In the post-COVID-19 world, capital will be different, stronger, and more conscious.

Even before the pandemic changed our everyday lives, companies contributing to climate change were being called to account as Australia experienced its worst bushfire season on record.

Investors alarmed at the impact of companies damaging the environment have begun to look at the impact of their own investments, and whether those investments are aligned with their values. When people began to dig a little deeper and uncovered where their money was going, the floodgates opened.

In January, Ethical Super saw its net inflow increase by five timescompared to January of 2019, with the fund citing increased awareness of climate change as the reason behind the rise in growth.

The changes are not just being seen in retail investment.

Recently, over half of Woodside Petroleums investors backed motionsfor the company to commit to hard targets for the reduction of its greenhouse gas emissions. As more people realised that the power to choose is in their hands, the shift towards more ethical investments began.

At the same time, the impact of the pandemic has caused many aspects of globalisation to come to a screeching halt accelerating the pace of transformation for industries across the world. In times like these, innovation flourishes.

Uber, Airbnb and WhatsApp were all founded during the 2009 global financial crisis, underling that some of the biggest disruptive opportunities arise during major economic downturns.

Square Peg co-founder Paul Bassat concurs: Every time theres been a major crisis, weve seen this burst of innovation occur where theres a combination of problems needing to be solved as a result, as well as people having a chance to think differently about their career and their lives.

In the midst of the global pandemic, the Australian venture capital sector actually grew. The KPMG Venture Pulse Q1 2020 report found that investment in Australian startups reached a record high of $US944.7 million ($1,314 billion) in H1 2020.

Clearly VC firms are grasping at the opportunities. But they are not the only ones able to reap the potential benefits.

Changes to Australian legislation in 2017 has seen the creation of investment opportunities for retail investors that were previously only available to high-net-worth individuals or sophisticated investors.

If they meet the criteria, these investors are able to invest up to $10,000 in private companies launching fundraises of up to $5 million; cementing the fact that startup investment is no longer just for VCs and angel investors.

Investors have generally been motivated by two things: the opportunity to back the companies changing the world, and the outsized returns of startup investment.

As we move towards a post-COVID world, investments also need to be good for the planet.

As a new generation of investors increasingly begin to focus on the positive impacts their funding decisions can make on the world, startups will need to prove their social and environmental credentials as well as their ability to disrupt and grow.

When they do that, investors will follow and we can all enjoy sushi again, without the microplastic.

NOW READ: Eco-deodorant, accessible rock climbing and interior design: Meet the entrepreneurs taking part in The Good Incubator

NOW READ: After being made redundant on maternity leave, this founder launched her own watch brand and raised $15,000 in six minutes

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Thats our job at SmartCompany: to keep you informed with the news, interviews and analysis you need to manage your way through this unprecedented crisis.

Now, theres a way you can help us keep doing this: by becoming a SmartCompany supporter.

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After COVID-19, capital will be different, stronger and more conscious -

Recommendation and review posted by Alexandra Lee Anderson

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