Nature of the protein universe.
Ontology highlight
ABSTRACT:
SUBMITTER: Levitt M
PROVIDER: S-EPMC2698892 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Metagenomics sequencing projects have dramatically increased our knowledge of the protein universe and provided over one-half of currently known protein sequences; they have also introduced a much broader phylogenetic diversity into the protein databases. The full analysis of metagenomic datasets is only beginning, but it has already led to the discovery of thousands of new protein families, likely representing novel functions specific to given environments. At the same time, a deeper analysis of such novel families, including experimental structure determination of some representatives, suggests that most of them represent distant homologs of already characterized protein families, and thus most of the protein diversity present in the new environments are due to functional divergence of the known protein families rather than the emergence of new ones.
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Project description:To explore protein space from a global perspective, we consider 9,710 SCOP (Structural Classification of Proteins) domains with up to 70% sequence identity and present all similarities among them as networks: In the "domain network," nodes represent domains, and edges connect domains that share "motifs," i.e., significantly sized segments of similar sequence and structure. We explore the dependence of the network on the thresholds that define the evolutionary relatedness of the domains. At excessively strict thresholds the network falls apart completely; for very lax thresholds, there are network paths between virtually all domains. Interestingly, at intermediate thresholds the network constitutes two regions that can be described as "continuous" versus "discrete." The continuous region comprises a large connected component, dominated by domains with alternating alpha and beta elements, and the discrete region includes the rest of the domains in isolated islands, each generally corresponding to a fold. We also construct the "motif network," in which nodes represent recurring motifs, and edges connect motifs that appear in the same domain. This network also features a large and highly connected component of motifs that originate from domains with alternating alpha/beta elements (and some all-alpha domains), and smaller isolated islands. Indeed, the motif network suggests that nature reuses such motifs extensively. The networks suggest evolutionary paths between domains and give hints about protein evolution and the underlying biophysics. They provide natural means of organizing protein space, and could be useful for the development of strategies for protein search and design.
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Project description:A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix-loop-helix-loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95?°C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5?Å. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering.
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Project description:Protein structural diversity encompasses a finite set of architectural designs. Embedded in these topologies are evolutionary histories that we here uncover using cladistic principles and measurements of protein-fold usage and sharing. The reconstructed phylogenies are inherently rooted and depict histories of protein and proteome diversification. Proteome phylogenies showed two monophyletic sister-groups delimiting Bacteria and Archaea, and a topology rooted in Eucarya. This suggests three dramatic evolutionary events and a common ancestor with a eukaryotic-like, gene-rich, and relatively modern organization. Conversely, a general phylogeny of protein architectures showed that structural classes of globular proteins appeared early in evolution and in defined order, the alpha/beta class being the first. Although most ancestral folds shared a common architecture of barrels or interleaved beta-sheets and alpha-helices, many were clearly derived, such as polyhedral folds in the all-alpha class and beta-sandwiches, beta-propellers, and beta-prisms in all-beta proteins. We also describe transformation pathways of architectures that are prevalently used in nature. For example, beta-barrels with increased curl and stagger were favored evolutionary outcomes in the all-beta class. Interestingly, we found cases where structural change followed the alpha-to-beta tendency uncovered in the tree of architectures. Lastly, we traced the total number of enzymatic functions associated with folds in the trees and show that there is a general link between structure and enzymatic function.
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Project description:The genome projects have unearthed an enormous diversity of genes of unknown function that are still awaiting biological and biochemical characterization. These genes, as most others, can be grouped into families based on sequence similarity. The PFAM database currently contains over 2,200 such families, referred to as domains of unknown function (DUF). In a coordinated effort, the four large-scale centers of the NIH Protein Structure Initiative have determined the first three-dimensional structures for more than 250 of these DUF families. Analysis of the first 248 reveals that about two thirds of the DUF families likely represent very divergent branches of already known and well-characterized families, which allows hypotheses to be formulated about their biological function. The remainder can be formally categorized as new folds, although about one third of these show significant substructure similarity to previously characterized folds. These results infer that, despite the enormous increase in the number and the diversity of new genes being uncovered, the fold space of the proteins they encode is gradually becoming saturated. The previously unexplored sectors of the protein universe appear to be primarily shaped by extreme diversification of known protein families, which then enables organisms to evolve new functions and adapt to particular niches and habitats. Notwithstanding, these DUF families still constitute the richest source for discovery of the remaining protein folds and topologies.
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Project description:Proteins are involved in almost all functions in a living cell, and functions of proteins are realized by their tertiary structures. Obtaining a global perspective of the variety and distribution of protein structures lays a foundation for our understanding of the building principle of protein structures. In light of the rapid accumulation of low-resolution structure data from electron tomography and cryo-electron microscopy, here we map and classify three-dimensional (3D) surface shapes of proteins into a similarity space. Surface shapes of proteins were represented with 3D Zernike descriptors, mathematical moment-based invariants, which have previously been demonstrated effective for biomolecular structure similarity search. In addition to single chains of proteins, we have also analyzed the shape space occupied by protein complexes. From the mapping, we have obtained various new insights into the relationship between shapes, main-chain folds, and complex formation. The unique view obtained from shape mapping opens up new ways to understand design principles, functions, and evolution of proteins.
| S-EPMC6481876 | biostudies-literature
Project description:Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ?600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.
| S-EPMC5127300 | biostudies-literature
Project description:It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.
| S-EPMC2973819 | biostudies-literature
Project description:One of the goals of structural genomics is to obtain a structural representative of almost every fold in nature. A recent estimate suggests that 70%-80% of soluble protein domains identified in the first 1000 genome sequences should be covered by about 25,000 structures-a reasonably achievable goal. As no current estimates exist for the number of membrane protein families, however, it is not possible to know whether family coverage is a realistic goal for membrane proteins. Here we find that virtually all polytopic helical membrane protein families are present in the already known sequences so we can make an estimate of the total number of families. We find that only approximately 700 polytopic membrane protein families account for 80% of structured residues and approximately 1700 cover 90% of structured residues. While apparently a finite and reachable goal, we estimate that it will likely take more than three decades to obtain the structures needed for 90% residue coverage, if current trends continue.
| S-EPMC2242558 | biostudies-literature
Project description:BACKGROUND: The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its "dark matter". RESULTS: Here we suggest that true size of "dark matter" is much larger than stated by current definitions. We propose an approach to reducing the size of "dark matter" by identifying and subtracting regions in protein sequences that are not likely to contain any domain. CONCLUSIONS: Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of "dark matter"; however, its absolute size increases substantially with the growth of sequence data.
| S-EPMC3557196 | biostudies-literature