Biological insights from topology independent comparison of protein 3D structures

Creative destruction: New protein folds from old

Mechanisms of emergence and divergence of protein folds pose central questions in biological sciences. Incremental mutation and stepwise adaptation explain relationships between topologically similar protein folds. However, the universe of folds is diverse and riotous, suggesting more potent and creative forces are at play. Sequence and structure similarity are observed between distinct folds, indicating that proteins with distinct folds may share common ancestry. We found evidence of common ancestry between three distinct β-barrel folds: Scr kinase family homology (SH3), oligonucleotide/oligosaccharide-binding (OB), and cradle loop barrel (CLB). The data suggest a mechanism of fold evolution that interconverts SH3, OB, and CLB. This mechanism, which we call creative destruction, can be generalized to explain many examples of fold evolution including circular permutation. In creative destruction, an open reading frame duplicates or otherwise merges with another to produce a fused polypeptide. A merger forces two ancestral domains into a new sequence and spatial context. The fused polypeptide can explore folding landscapes that are inaccessible to either of the independent ancestral domains. However, the folding landscapes of the fused polypeptide are not fully independent of those of the ancestral domains. Creative destruction is thus partially conservative; a daughter fold inherits some motifs from ancestral folds. After merger and refolding, adaptive processes such as mutation and loss of extraneous segments optimize the new daughter fold. This model has application in disease states characterized by genetic instability. Fused proteins observed in cancer cells are likely to experience remodeled folding landscapes and realize altered folds, conferring new or altered functions.

AllerCatPro 2.0: a web server for predicting protein allergenicity potential

Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg.

Fold Evolution before LUCA: Common Ancestry of SH3 Domains and OB Domains

SH3 and OB are the simplest, oldest, and most common protein domains within the translation system. SH3 and OB domains are β-barrels that are structurally similar but are topologically distinct. To transform an OB domain to a SH3 domain, β-strands must be permuted in a multistep and evolutionarily implausible mechanism. Here, we explored relationships between SH3 and OB domains of ribosomal proteins, initiation, and elongation factors using a combined sequence- and structure-based approach. We detect a common core of SH3 and OB domains, as a region of significant structure and sequence similarity. The common core contains four β-strands and a loop, but omits the fifth β-strand, which is variable and is absent from some OB and SH3 domain proteins. The structure of the common core immediately suggests a simple permutation mechanism for interconversion between SH3 and OB domains, which appear to share an ancestor. The OB domain was formed by duplication and adaptation of the SH3 domain core, or vice versa, in a simple and probable transformation. By employing the folding algorithm AlphaFold2, we demonstrated that an ancestral reconstruction of a permuted SH3 sequence folds into an OB structure, and an ancestral reconstruction of a permuted OB sequence folds into a SH3 structure. The tandem SH3 and OB domains in the universal ribosomal protein uL2 share a common ancestor, suggesting that the divergence of these two domains occurred before the last universal common ancestor.

The miRISC component AGO2 has multiple binding sites for Nup358 SUMO-interacting motif

Micro-RNA mediated suppression of mRNA translation represents a major regulatory mode of post-transcriptional gene expression. Recently, the nucleoporin Nup358 was shown to interact with AGO protein, a key component of miRNA-induced silencing complex (miRISC), and facilitate the coupling of miRISC with target mRNA. Previous results suggested that SUMO-interacting motifs (SIMs) present on Nup358 mediate interaction with AGO protein. Here we show that Nup358-SIM has multiple interacting regions on AGO2, specifically within the N, PAZ and MID domains, with an affinity comparable to SIM-SUMO1 interaction. The study also unraveled specific residues involved in the interaction of AGO2 with miRNA-loading components such as Dicer and HSP90. Collectively, the results support the conclusion that multiple SIMs contribute to the association of Nup358 with AGO2.

Methods for Molecular Modelling of Protein Complexes

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes.

Topology-independent and global protein structure alignment through an FFT-based algorithm

MOTIVATION

Protein structure alignment is one of the fundamental problems in computational structure biology. A variety of algorithms have been developed to address this important issue in the past decade. However, due to their heuristic nature, current structure alignment methods may suffer from suboptimal alignment and/or over-fragmentation and thus lead to a biologically wrong alignment in some cases. To overcome these limitations, we have developed an accurate topology-independent and global structure alignment method through an FFT-based exhaustive search algorithm, which is referred to as FTAlign.

RESULTS

Our FTAlign algorithm was extensively tested on six commonly used datasets and compared with seven state-of-the-art structure alignment approaches, TMalign, DeepAlign, Kpax, 3DCOMB, MICAN, SPalignNS and CLICK. It was shown that FTAlign outperformed the other methods in reproducing manually curated alignments and obtained a high success rate of 96.7 and 90.0% on two gold-standard benchmarks, MALIDUP and MALISAM, respectively. Moreover, FTAlign also achieved the overall best performance in terms of biologically meaningful structure overlap (SO) and TMscore on both the sequential alignment test sets including MALIDUP, MALISAM and 64 difficult cases from HOMSTRAD, and the non-sequential sets including MALIDUP-NS, MALISAM-NS, 199 topology-different cases, where FTAlign especially showed more advantage for non-sequential alignment. Despite its global search feature, FTAlign is also computationally efficient and can normally complete a pairwise alignment within one second.

AVAILABILITY AND IMPLEMENTATION

http://huanglab.phys.hust.edu.cn/ftalign/.

FiRES: A computational method for the de novo identification of internal structure similarity in proteins

Internal structure similarity in proteins can be observed at the domain and subdomain levels. From an evolutionary perspective, structurally similar elements may arise divergently by gene duplication and fusion events but may also be the product of convergent evolution under physicochemical constraints. The characterization of proteins that contain repeated structural elements has implications for many fields of protein science including protein domain evolution, structure classification, structure prediction, and protein engineering. FiRES (Find Repeated Elements in Structure) is an algorithm that relies on a topology-independent structure alignment method to identify repeating elements in protein structure. FiRES was tested against two hand curated databases of protein repeats: MALIDUP, for very divergent duplicated domains; and RepeatsDB for short tandem repeats. The performance of FiRES was compared to that of lalign, RADAR, HHrepID, CE-symm, ReUPred, and Swelfe. FiRES was the method that most accurately detected proteins either with duplicated domains (accuracy = 0.86) or with multiple repeated units (accuracy = 0.92). FiRES is a new methodology for the discovery of proteins containing structurally similar elements. The FiRES web server is publicly available at http://fires.ifc.unam.mx. The scripts, results, and benchmarks from this study can be downloaded from https://github.com/Claualvarez/fires.

Elastic continuum stiffness of contractile tail sheaths from molecular dynamics simulations

Contractile tails are key components of the biological nanomachinery involved in cell membrane puncturing, where they provide a means to deliver molecules and ions inside cells. Two intriguing examples of contractile tails are those from bacteriophage T4 and R2-pyocin. Although the two systems are different in terms of biological activity, they share a fascinatingly similar injection mechanism, during which the tail sheaths of both systems contract from a so-called extended state to around half of their length (the contracted state), accompanied by release of elastic energy originally stored in the sheath. Despite the great prevalence and biomedical importance of contractile delivery systems, many fundamental details of their injection machinery and dynamics are still unknown. In this work, we calculate the bending and torsional stiffness constants of a helical tail sheath strand of bacteriophage T4 and R2-pyocin, in both extended and contracted states, using molecular dynamics simulations of about one-sixth of the entire sheath. Differences in stiffness constants between the two systems are rationalized by comparing their all-atom monomer structures, changes in sheath architecture on contraction, and differences in interstrand interactions. The calculated coefficients indicate that the T4 strand is stiffer for both bending and torsion than the corresponding R2-pyocin strands in both extended and contracted conformations. The sheath strands also have greater stiffness in the contracted state for both systems. As the main application of this study, we describe how the stiffness constants can be incorporated in a model to simulate the dynamics of contractile nanoinjection machineries.

Simulations of mutant p53 DNA binding domains reveal a novel druggable pocket

The DNA binding domain (DBD) of the tumor suppressor p53 is the site of several oncogenic mutations. A subset of these mutations lowers the unfolding temperature of the DBD. Unfolding leads to the exposure of a hydrophobic β-strand and nucleates aggregation which results in pathologies through loss of function and dominant negative/gain of function effects. Inspired by the hypothesis that structural changes that are associated with events initiating unfolding in DBD are likely to present opportunities for inhibition, we investigate the dynamics of the wild type (WT) and some aggregating mutants through extensive all atom explicit solvent MD simulations. Simulations reveal differential conformational sampling between the WT and the mutants of a turn region (S6-S7) that is contiguous to a known aggregation-prone region (APR). The conformational properties of the S6-S7 turn appear to be modulated by a network of interacting residues. We speculate that changes that take place in this network as a result of the mutational stress result in the events that destabilize the DBD and initiate unfolding. These perturbations also result in the emergence of a novel pocket that appears to have druggable characteristics. FDA approved drugs are computationally screened against this pocket.

AppA: a web server for analysis, comparison, and visualization of contact residues and interfacial waters of antibody-antigen structures and models

The study of contact residues and interfacial waters of antibody–antigen (Ab-Ag) structures could help in understanding the principles of antibody–antigen interactions as well as provide guidance for designing antibodies with improved affinities. Given the rapid pace with which new antibody–antigen structures are deposited in the protein databank (PDB), it is crucial to have computational tools to analyze contact residues and interfacial waters, and investigate them at different levels. In this study, we have developed AppA, a web server that can be used to analyze and compare 3D structures of contact residues and interfacial waters of antibody–antigen complexes. To the best of our knowledge, this is the first web server for antibody–antigen structures equipped with the capability for dissecting the contributions of interfacial water molecules, hydrogen bonds, hydrophobic interactions, van der Waals interactions and ionic interactions at the antibody–antigen interface, and for comparing the structures and conformations of contact residues. Various examples showcase the utility of AppA for such analyses and comparisons that could help in the understanding of antibody–antigen interactions and suggest mutations of contact residues to improve affinities of antibodies. The AppA web server is freely accessible at http://mspc.bii.a-star.edu.sg/minhn/appa.html.

The three-dimensional structure of an H-superfamily conotoxin reveals a granulin fold arising from a common ICK cysteine framework

Venomous marine cone snails produce peptide toxins (conotoxins) that bind ion channels and receptors with high specificity and therefore are important pharmacological tools. Conotoxins contain conserved cysteine residues that form disulfide bonds that stabilize their structures. To gain structural insight into the large, yet poorly characterized conotoxin H-superfamily, we used NMR and CD spectroscopy along with MS-based analyses to investigate H-Vc7.2 from Conus victoriae, a peptide with a VI/VII cysteine framework. This framework has Cys^I-Cys^IV/Cys^II-Cys^V/Cys^III-Cys^VI connectivities, which have invariably been associated with the inhibitor cystine knot (ICK) fold. However, the solution structure of recombinantly expressed and purified H-Vc7.2 revealed that although it displays the expected cysteine connectivities, H-Vc7.2 adopts a different fold consisting of two stacked β-hairpins with opposing β-strands connected by two parallel disulfide bonds, a structure homologous to the N-terminal region of the human granulin protein. Using structural comparisons, we subsequently identified several toxins and nontoxin proteins with this "mini-granulin" fold. These findings raise fundamental questions concerning sequence-structure relationships within peptides and proteins and the key determinants that specify a given fold.

Non-sequential protein structure alignment by conformational space annealing and local refinement

Protein structure alignment is an important tool for studying evolutionary biology and protein modeling. A tool which intensively searches for the globally optimal non-sequential alignments is rarely found. We propose ALIGN-CSA which shows improvement in scores, such as DALI-score, SP-score, SO-score and TM-score over the benchmark set including 286 cases. We performed benchmarking of existing popular alignment scoring functions, where the dependence of the search algorithm was effectively eliminated by using ALIGN-CSA. For the benchmarking, we set the minimum block size to 4 to prevent much fragmented alignments where the biological relevance of small alignment blocks is hard to interpret. With this condition, globally optimal alignments were searched by ALIGN-CSA using the four scoring functions listed above, and TM-score is found to be the most effective in generating alignments with longer match lengths and smaller RMSD values. However, DALI-score is the most effective in generating alignments similar to the manually curated reference alignments, which implies that DALI-score is more biologically relevant score. Due to the high demand on computational resources of ALIGN-CSA, we also propose a relatively fast local refinement method, which can control the minimum block size and whether to allow the reverse alignment. ALIGN-CSA can be used to obtain much improved alignment at the cost of relatively more extensive computation. For faster alignment, we propose a refinement protocol that improves the score of a given alignment obtained by various external tools. All programs are available from http://lee.kias.re.kr.

Allosteric binding sites in Rab11 for potential drug candidates

Rab11 is an important protein subfamily in the RabGTPase family. These proteins physiologically function as key regulators of intracellular membrane trafficking processes. Pathologically, Rab11 proteins are implicated in many diseases including cancers, neurodegenerative diseases and type 2 diabetes. Although they are medically important, no previous study has found Rab11 allosteric binding sites where potential drug candidates can bind to. In this study, by employing multiple clustering approaches integrating principal component analysis, independent component analysis and locally linear embedding, we performed structural analyses of Rab11 and identified eight representative structures. Using these representatives to perform binding site mapping and virtual screening, we identified two novel binding sites in Rab11 and small molecules that can preferentially bind to different conformations of these sites with high affinities. After identifying the binding sites and the residue interaction networks in the representatives, we computationally showed that these binding sites may allosterically regulate Rab11, as these sites communicate with switch 2 region that binds to GTP/GDP. These two allosteric binding sites in Rab11 are also similar to two allosteric pockets in Ras that we discovered previously.

De novo main-chain modeling for EM maps using MAINMAST

An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4-5 Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map. The method directly traces the protein's main-chain and identifies Cα positions as tree-graph structures in the EM map. MAINMAST performs significantly better than existing software in building global protein structure models on data sets of 40 simulated density maps at 5 Å resolution and 30 experimentally determined maps at 2.6-4.8 Å resolution. In another benchmark of building missing fragments in protein models for EM maps, MAINMAST builds fragments of 11-161 residues long with an average RMSD of 2.68 Å.

Structural analysis of protein tyrosine phosphatase 1B reveals potentially druggable allosteric binding sites

Catalytic proteins such as human protein tyrosine phosphatase 1B (PTP1B), with conserved and highly polar active sites, warrant the discovery of druggable nonactive sites, such as allosteric sites, and potentially, therapeutic small molecules that can bind to these sites. Catalyzing the dephosphorylation of numerous substrates, PTP1B is physiologically important in intracellular signal transduction pathways in diverse cell types and tissues. Aberrant PTP1B is associated with obesity, diabetes, cancers, and neurodegenerative disorders. Utilizing clustering methods (based on root mean square deviation, principal component analysis, nonnegative matrix factorization, and independent component analysis), we have examined multiple PTP1B structures. Using the resulting representative structures in different conformational states, we determined consensus clustroids and used them to identify both known and novel binding sites, some of which are potentially allosteric. We report several lead compounds that could potentially bind to the novel PTP1B binding sites and can be further optimized. Considering the possibility for drug repurposing, we discovered homologous binding sites in other proteins, with ligands that could potentially bind to the novel PTP1B binding sites.

Discovery of Rab1 binding sites using an ensemble of clustering methods

Targeting non-native-ligand binding sites for potential investigative and therapeutic applications is an attractive strategy in proteins that share common native ligands, as in Rab1 protein. Rab1 is a subfamily member of Rab proteins, which are members of Ras GTPase superfamily. All Ras GTPase superfamily members bind to native ligands GTP and GDP, that switch on and off the proteins, respectively. Rab1 is physiologically essential for autophagy and transport between endoplasmic reticulum and Golgi apparatus. Pathologically, Rab1 is implicated in human cancers, a neurodegenerative disease, cardiomyopathy, and bacteria-caused infectious diseases. We have performed structural analyses on Rab1 protein using a unique ensemble of clustering methods, including multi-step principal component analysis, non-negative matrix factorization, and independent component analysis, to better identify representative Rab1 proteins than the application of a single clustering method alone does. We then used the identified representative Rab1 structures, resolved in multiple ligand states, to map their known and novel binding sites. We report here at least a novel binding site on Rab1, involving Rab1-specific residues that could be further explored for the rational design and development of investigative probes and/or therapeutic small molecules against the Rab1 protein. Proteins 2017; 85:859-871. © 2016 Wiley Periodicals, Inc.

Nup358 binds to AGO proteins through its SUMO-interacting motifs and promotes the association of target mRNA with miRISC

MicroRNA (miRNA)-guided mRNA repression, mediated by the miRNA-induced silencing complex (miRISC), is an important component of post-transcriptional gene silencing. However, how miRISC identifies the target mRNA in vivo is not well understood. Here, we show that the nucleoporin Nup358 plays an important role in this process. Nup358 localizes to the nuclear pore complex and to the cytoplasmic annulate lamellae (AL), and these structures dynamically associate with two mRNP granules: processing bodies (P bodies) and stress granules (SGs). Nup358 depletion disrupts P bodies and concomitantly impairs the miRNA pathway. Furthermore, Nup358 interacts with AGO and GW182 proteins and promotes the association of target mRNA with miRISC A well-characterized SUMO-interacting motif (SIM) in Nup358 is sufficient for Nup358 to directly bind to AGO proteins. Moreover, AGO and PIWI proteins interact with SIMs derived from other SUMO-binding proteins. Our study indicates that Nup358-AGO interaction is important for miRNA-mediated gene silencing and identifies SIM as a new interacting motif for the AGO family of proteins. The findings also support a model wherein the coupling of miRISC with the target mRNA could occur at AL, specialized domains within the ER, and at the nuclear envelope.

Topology independent comparison of RNA 3D structures using the CLICK algorithm

RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA-protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html.

Molecular Mechanism Underlying ATP-Induced Conformational Changes in the Nucleoprotein Filament of Mycobacterium smegmatis RecA

RecA plays a central role in bacterial DNA repair, homologous recombination, and restoration of stalled replication forks by virtue of its active extended nucleoprotein filament. Binding of ATP and its subsequent recognition by the carboxamide group of a highly conserved glutamine (Gln196 in MsRecA) have been implicated in the formation of active RecA nucleoprotein filaments. Although the mechanism of ATP-dependent structural transitions in RecA has been proposed on the basis of low-resolution electron microscopic reconstructions, the precise sequence of events that constitute these transitions is poorly understood. On the basis of biochemical and crystallographic analyses of MsRecA variants carrying mutations in highly conserved Gln196 and Arg198 residues, we propose that the disposition of the interprotomer interface is the structural basis of allosteric activation of RecA. Furthermore, this study accounts for the contributions of several conserved amino acids to ATP hydrolysis and to the transition from collapsed to extended filament forms in Mycobacterium smegmatis RecA (MsRecA). In addition to their role in the inactive compressed state, the study reveals a role for Gln196 and Arg198 along with Phe219 in ATP hydrolysis in the active extended nucleoprotein filament. Finally, our data suggest that the primary, but not secondary, nucleotide binding site in MsRecA isomerizes into the ATP binding site present in the extended nucleoprotein filament.

Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic

MOTIVATION

The three dimensional tertiary structure of a protein at near atomic level resolution provides insight alluding to its function and evolution. As protein structure decides its functionality, similarity in structure usually implies similarity in function. As such, structure alignment techniques are often useful in the classifications of protein function. Given the rapidly growing rate of new, experimentally determined structures being made available from repositories such as the Protein Data Bank, fast and accurate computational structure comparison tools are required. This paper presents SPalignNS, a non-sequential protein structure alignment tool using a novel asymmetrical greedy search technique.

RESULTS

The performance of SPalignNS was evaluated against existing sequential and non-sequential structure alignment methods by performing trials with commonly used datasets. These benchmark datasets used to gauge alignment accuracy include (i) 9538 pairwise alignments implied by the HOMSTRAD database of homologous proteins; (ii) a subset of 64 difficult alignments from set (i) that have low structure similarity; (iii) 199 pairwise alignments of proteins with similar structure but different topology; and (iv) a subset of 20 pairwise alignments from the RIPC set. SPalignNS is shown to achieve greater alignment accuracy (lower or comparable root-mean squared distance with increased structure overlap coverage) for all datasets, and the highest agreement with reference alignments from the challenging dataset (iv) above, when compared with both sequentially constrained alignments and other non-sequential alignments.

AVAILABILITY AND IMPLEMENTATION

SPalignNS was implemented in C++. The source code, binary executable, and a web server version is freely available at: http://sparks-lab.org

CONTACT

yaoqi.zhou@griffith.edu.au.

General overview on structure prediction of twilight-zone proteins

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

Structure- and context-based analysis of the GxGYxYP family reveals a new putative class of glycoside hydrolase

Background

Gut microbiome metagenomics has revealed many protein families and domains found largely or exclusively in that environment. Proteins containing the GxGYxYP domain are over-represented in the gut microbiota, and are found in Polysaccharide Utilization Loci in the gut symbiont Bacteroides thetaiotaomicron, suggesting their involvement in polysaccharide metabolism, but little else is known of the function of this domain.

Results

Genomic context and domain architecture analyses support a role for the GxGYxYP domain in carbohydrate metabolism. Sparse occurrences in eukaryotes are the result of lateral gene transfer. The structure of the GxGYxYP domain-containing protein encoded by the BT2193 locus reveals two structural domains, the first composed of three divergent repeats with no recognisable homology to previously solved structures, the second a more familiar seven-stranded β/α barrel. Structure-based analyses including conservation mapping localise a presumed functional site to a cleft between the two domains of BT2193. Matching to a catalytic site template from a GH9 cellulase and other analyses point to a putative catalytic triad composed of Glu272, Asp331 and Asp333.

Conclusions

We suggest that GxGYxYP-containing proteins constitute a novel glycoside hydrolase family of as yet unknown specificity.

Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins

Residue depth accurately measures burial and parameterizes local protein environment. Depth is the distance of any atom/residue to the closest bulk water. We consider the non-bulk waters to occupy cavities, whose volumes are determined using a Voronoi procedure. Our estimation of cavity sizes is statistically superior to estimates made by CASTp and VOIDOO, and on par with McVol over a data set of 40 cavities. Our calculated cavity volumes correlated best with the experimentally determined destabilization of 34 mutants from five proteins. Some of the cavities identified are capable of binding small molecule ligands. In this study, we have enhanced our depth-based predictions of binding sites by including evolutionary information. We have demonstrated that on a database (LigASite) of ∼200 proteins, we perform on par with ConCavity and better than MetaPocket 2.0. Our predictions, while less sensitive, are more specific and precise. Finally, we use depth (and other features) to predict pK_as of GLU, ASP, LYS and HIS residues. Our results produce an average error of just <1 pH unit over 60 predictions. Our simple empirical method is statistically on par with two and superior to three other methods while inferior to only one. The DEPTH server (http://mspc.bii.a-star.edu.sg/depth/) is an ideal tool for rapid yet accurate structural analyses of protein structures.

Detection of spatial correlations in protein structures and molecular complexes

Protein structures are frequently related by spectacular and often surprising similarities. Structural correlations among protein chains are routinely detected by various structure-matching techniques, but the comparison of oligomers and molecular complexes is largely uncharted territory. Here we solve the structure-matching problem for oligomers and large molecular aggregates, including the largest molecular complexes known today. We provide several challenging examples that cannot be handled by conventional structure-matching techniques and we report on a number of remarkable correlations. The examples cover the cell-puncturing device of bacteriophage T4, the secretion system of P. aeruginosa, members of the dehydrogenase family, DNA clamps, ferredoxin iron-storage cages, and virus capsids.

CLICK--topology-independent comparison of biomolecular 3D structures

Our server, CLICK: http://mspc.bii.a-star.edu.sg/click, is capable of superimposing the 3D structures of any pair of biomolecules (proteins, DNA, RNA, etc.). The server makes use of the Cartesian coordinates of the molecules with the option of using other structural features such as secondary structure, solvent accessible surface area and residue depth to guide the alignment. CLICK first looks for cliques of points (3-7 residues) that are structurally similar in the pair of structures to be aligned. Using these local similarities, a one-to-one equivalence is charted between the residues of the two structures. A least square fit then superimposes the two structures. Our method is especially powerful in establishing protein relationships by detecting similarities in structural subdomains, domains and topological variants. CLICK has been extensively benchmarked and compared with other popular methods for protein and RNA structural alignments. In most cases, CLICK alignments were statistically significantly better in terms of structure overlap. The method also recognizes conformational changes that may have occurred in structural domains or subdomains in one structure with respect to the other. For this purpose, the server produces complementary alignments to maximize the extent of detectable similarity. Various examples showcase the utility of our web server.