HBAT: a complete package for analysing strong and weak hydrogen bonds in macromolecular crystal structures

The program HBAT is a tool to automate the analysis of potential hydrogen bonds and similar type of weak interactions like halogen bonds and non-canonical interactions in macromolecular structures, available in Brookhaven Protein Database (PDB) file format. HBAT is written using PERL and TK languages. The program generates an MSOFFICE Excel compatible output file for statistical analysis. HBAT identify potential interactions based on geometrical criteria. A series of analysis reports like frequency tables, geometry distribution tables, furcations list are generated. A user friendly GUI offers freedom to select several parameters and options. Graphviz based visualization of hydrogen bond networks in 2D helps to study the cooperativity and anticooperativity geometry in hydrogen bond. HBAT supports post docking interaction analysis between PDB files for any target/receptor (in PDB files) and docked ligands/poses (in SDF). This tool can be implemented in active site interaction analysis, structure based drug design and molecular dynamics simulations.     

FTMove: A Web Server for Detection and Analysis of Cryptic and Allosteric Binding Sites by Mapping Multiple Protein Structures

Protein mapping distributes many copies of different molecular probes on the surface of a target protein in order to determine binding hot spots, regions that are highly preferable for ligand binding. While mapping of X-ray structures by the FTMap server is inherently static, this limitation can be overcome by the simultaneous analysis of multiple structures of the protein. FTMove is an automated web server that implements this approach. From the input of a target protein, by PDB code, the server identifies all structures of the protein available in the PDB, runs mapping on them, and combines the results to form binding hot spots and binding sites. The user may also upload their own protein structures, bypassing the PDB search for similar structures. Output of the server consists of the consensus binding sites and the individual mapping results for each structure - including the number of probes located in each binding site, for each structure. This level of detail allows the users to investigate how the strength of a binding site relates to the protein conformation, other binding sites, and the presence of ligands or mutations. In addition, the structures are clustered on the basis of their binding properties. The use of FTMove is demonstrated by application to 22 proteins with known allosteric binding sites; the orthosteric and allosteric binding sites were identified in all but one case, and the sites were typically ranked among the top five. The FTMove server is publicly available at https://ftmove.bu.edu.     

PISCES: a protein sequence culling server

PISCES is a public server for culling sets of protein sequences from the Protein Data Bank (PDB) by sequence identity and structural quality criteria. PISCES can provide lists culled from the entire PDB or from lists of PDB entries or chains provided by the user. The sequence identities are obtained from PSI-BLAST alignments with position-specific substitution matrices derived from the non-redundant protein sequence database. PISCES therefore provides better lists than servers that use BLAST, which is unable to identify many relationships below 40% sequence identity and often overestimates sequence identity by aligning only well-conserved fragments. PDB sequences are updated weekly. PISCES can also cull non-PDB sequences provided by the user as a list of GenBank identifiers, a FASTA format file, or BLAST/PSI-BLAST output.     

Functional role of C(alpha)-H...O hydrogen bonds between transmembrane alpha-helices in photosystem I

The crystal structure at 2.5A resolution of the membrane-intrinsic, homotrimeric photosystem I (PSI) isolated from the thermophilic cyanobacterium Synechococcus elongatus shows that each monomer is composed of 12 protein subunits of which nine are embedded in the membrane and feature a total of 34 transmembrane alpha-helices (TMH). Hence, PSI provides an ideal case to study "conventional" and C(alpha)-H...O hydrogen bonds between TMH engaged in intra- and intersubunit interactions. Of the total of 75 C(alpha)-H...O hydrogen bonds between TMHs, 72 are intrasubunit and only three are intersubunit. The two largest subunits PsaA and PsaB are each folded into 11 TMHs showing 29 and 24 intrasubunit C(alpha)-H...O hydrogen bonds, respectively, that are not distributed randomly but many of them flank chlorophyll a (Chl a) co-ordinating amino acids, suggesting stabilisation of these structural segments. As major constituent of the trimerisation domain, subunit PsaL is located next to the 3-fold axis relating the three monomers of PSI. PsaL features a unique number of 19 intrasubunit C(alpha)-H...O hydrogen bonds that connect two of its three TMHs but there are no intersubunit C(alpha)-H...O hydrogen bonds between the three PsaL. Of the three intersubunit C(alpha)-H...O hydrogen bonds, two are formed between PsaA and PsaB and one between PsaB and PsaM. The large number of 75 C(alpha)-H...O hydrogen bonds contrasts the 49 conventional hydrogen bonds, indicating that the former and van der Waals contacts determine association and orientation of TMHs in PSI.     

Models of S/pi interactions in protein structures: comparison of the H2S benzene complex with PDB data

S/pi interactions are prevalent in biochemistry and play an important role in protein folding and stabilization. Geometries of cysteine/aromatic interactions found in crystal structures from the Brookhaven Protein Data Bank (PDB) are analyzed and compared with the equilibrium configurations predicted by high-level quantum mechanical results for the H(2)S-benzene complex. A correlation is observed between the energetically favorable configurations on the quantum mechanical potential energy surface of the H(2)S-benzene model and the cysteine/aromatic configurations most frequently found in crystal structures of the PDB. In contrast to some previous PDB analyses, configurations with the sulfur over the aromatic ring are found to be the most important. Our results suggest that accurate quantum computations on models of noncovalent interactions may be helpful in understanding the structures of proteins and other complex systems.     

Specificity of molecular interactions in transient protein-protein interaction interfaces

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of antibody-antigen complexes, the sign is somewhat ambiguous. From the evolutionary perspective, while protease-inhibitors and sig-naling proteins have optimized their interfaces to suit their biological functions, antibody-antigen interactions are the happenstance, implying that antibody-antigen complexes do not show distinctive interaction types. Persistent interaction types such as pi...pi, amide-carbonyl, and hydroxyl-carbonyl interaction, are also investigated. Analyzing the structural orientations of the pi...pi stacking interactions, we find that herringbone shape is a major configuration in transient protein-protein interfaces. This result is different from that of protein core, where parallel-displaced configurations are the major configuration. We also analyze overall trend of amide-carbonyl and hydroxyl-carbonyl interactions. It is noticeable that nearly 82% of the interfaces have at least one hydroxyl-carbonyl interactions.     

Prediction of C alpha-H...O and C alpha-H...pi interactions in proteins using recurrent neural network

In this study, an attempt has been made to develop a method for predicting weak hydrogen bonding interactions, namely, C alpha-H...O and C alpha-H...pi interactions in proteins using artificial neural network. Both standard feed-forward neural network (FNN) and recurrent neural networks (RNN) have been trained and tested using five-fold cross-validation on a non-homologous dataset of 2298 protein chains where no pair of sequences has more than 25% sequence identity. It has been found that the prediction accuracy varies with the separation distance between donor and acceptor residues. The maximum sensitivity achieved with RNN for C alpha-H...O is 51.2% when donor and acceptor residues are four residues apart (i.e. at delta D-A = 4) and for C alpha-H...pi is 82.1% at delta D-A = 3. The performance of RNN is increased by 1-3% for both types of interactions when PSIPRED predicted protein secondary structure is used. Overall, RNN performs better than feed-forward networks at all separation distances between donor-acceptor pair for both types of interactions. Based on the observations, a web server CHpredict (available at http://www.imtech.res.in/raghava/chpredict/) has been developed for predicting donor and acceptor residues in C alpha-H...O and C alpha-H...pi interactions in proteins.     

ProtBuD: a database of biological unit structures of protein families and superfamilies

MOTIVATION: Modeling of protein interactions is often possible from known structures of related complexes. It is often time-consuming to find the most appropriate template. Hypothesized biological units (BUs) often differ from the asymmetric units and it is usually preferable to model from the BUs. RESULTS: ProtBuD is a database of BUs for all structures in the Protein Data Bank (PDB). We use both the PDBs BUs and those from the Protein Quaternary Server. ProtBuD is searchable by PDB entry, the Structural Classification of Proteins (SCOP) designation or pairs of SCOP designations. The database provides the asymmetric and BU contents of related proteins in the PDB as identified in SCOP and Position-Specific Iterated BLAST (PSI-BLAST). The asymmetric unit is different from PDB and/or Protein Quaternary Server (PQS) BUs for 52% of X-ray structures, and the PDB and PQS BUs disagree on 18% of entries. AVAILABILITY: The database is provided as a standalone program and a web server from http://dunbrack.fccc.edu/ProtBuD.php.     

MATRAS: A program for protein 3D structure comparison

The recent accumulation of large amounts of 3D structural data warrants a sensitive and automatic method to compare and classify these structures. We developed a web server for comparing protein 3D structures using the program Matras (http://biunit.aist-nara.ac.jp/matras). An advantage of Matras is its structure similarity score, which is defined as the log-odds of the probabilities, similar to Dayhoff's substitution model of amino acids. This score is designed to detect evolutionarily related (homologous) structural similarities. Our web server has three main services. The first one is a pairwise 3D alignment, which is simply align two structures. A user can assign structures by either inputting PDB codes or by uploading PDB format files in the local machine. The second service is a multiple 3D alignment, which compares several protein structures. This program employs the progressive alignment algorithm, in which pairwise 3D alignments are assembled in the proper order. The third service is a 3D library search, which compares one query structure against a large number of library structures. We hope this server provides useful tools for insights into protein 3D structures.     

PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB)

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). The previous version of PDB-REPRDB provided 48 representative sets, whose similarity criteria were predetermined, on the WWW. The current version is designed so that the user may obtain a quick selection of representative chains from PDB. The selection of representative chains can be dynamically configured according to the user's requirement. The WWW interface provides a large degree of freedom in setting parameters, such as cut-off scores of sequence and structural similarity. One can obtain a representative list and classification data of protein chains from the system. The current database includes 20 457 protein chains from PDB entries (August 6, 2000). The system for PDB-REPRDB is available at the Parallel Protein Information Analysis system (PAPIA) WWW server (http://www.rwcp.or.jp/papia/).     

STRUCLA: a WWW meta-server for protein structure comparison and evolutionary classification

MOTIVATION: Evolutionary relationships of proteins have long been derived from the alignment of protein sequences. But from the view of function, most restraints of evolutionary divergence operate at the level of tertiary structure. It has been demonstrated that quantitative measures of dissimilarity in families of structurally similar proteins can be applied to the construction of trees from a comparison of their three-dimensional structures. However, no convenient tool is publicly available to carry out such analyses. RESULTS: We developed STRUCLA (STRUcture CLAssification), a WWW tool for generation of trees based on evolutionary distances inferred from protein structures according to various methods. The server takes as an input a list of PDB files or the initial alignment of protein coordinates provided by the user (for instance exported from SWISS PDB VIEWER). The user specifies the distance cutoff and selects the distance measures. The server returns series of unrooted trees in the NEXUS format and corresponding distance matrices, as well as a consensus tree. The results can be used as an alternative and a complement to a fixed hierarchy of current protein structure databases. It can complement sequence-based phylogenetic analysis in the 'twilight zone of homology', where amino acid sequences are too diverged to provide reliable relationships.     

HOMCOS: an updated server to search and model complex 3D structures

The HOMCOS server (http://homcos.pdbj.org) was updated for both searching and modeling the 3D complexes for all molecules in the PDB. As compared to the previous HOMCOS server, the current server targets all of the molecules in the PDB including proteins, nucleic acids, small compounds and metal ions. Their binding relationships are stored in the database. Five services are available for users. For the services “Modeling a Homo Protein Multimer” and “Modeling a Hetero Protein Multimer”, a user can input one or two proteins as the queries, while for the service “Protein-Compound Complex”, a user can input one chemical compound and one protein. The server searches similar molecules by BLAST and KCOMBU. Based on each similar complex found, a simple sequence-replaced model is quickly generated by replacing the residue names and numbers with those of the query protein. A target compound is flexibly superimposed onto the template compound using the program fkcombu. If monomeric 3D structures are input as the query, then template-based docking can be performed. For the service “Searching Contact Molecules for a Query Protein”, a user inputs one protein sequence as the query, and then the server searches for its homologous proteins in PDB and summarizes their contacting molecules as the predicted contacting molecules. The results are summarized in “Summary Bars” or “Site Table”display. The latter shows the results as a one-site-one-row table, which is useful for annotating the effects of mutations. The service “Searching Contact Molecules for a Query Compound” is also available.     

TESE: generating specific protein structure test set ensembles

TESE is a web server for the generation of test sets of protein sequences and structures fulfilling a number of different criteria. At least three different use cases can be envisaged: (i) benchmarking of novel methods; (ii) test sets tailored for special needs and (iii) extending available datasets. The CATH structure classification is used to control structural/sequence redundancy and a variety of structural quality parameters can be used to interactively select protein subsets with specific characteristics, e.g. all X-ray structures of alpha-helical repeat proteins with more than 120 residues and resolution <2.0 A. The output includes FASTA-formatted sequences, PDB files and a clickable HTML index file containing images of the selected proteins. Multiple subsets for cross-validation are also supported. AVAILABILITY: The TESE server is available for non-commercial use at URL: http://protein.bio.unipd.it/tese/.     

N-H...O, O-H...O, and C-H...O hydrogen bonds in protein-ligand complexes: strong and weak interactions in molecular recognition

The characteristics of N-H...O, O-H...O, and C-H...O hydrogen bonds are examined in a group of 28 high-resolution crystal structures of protein-ligand complexes from the Protein Data Bank and compared with interactions found in small-molecule crystal structures from the Cambridge Structural Database. It is found that both strong and weak hydrogen bonds are involved in ligand binding. Because of the prevalence of multifurcation, the restrictive geometrical criteria set up for hydrogen bonds in small-molecule crystal structures may need to be relaxed in macromolecular structures. For example, there are definite deviations from linearity for the hydrogen bonds in protein-ligand complexes. The formation of C-H...O hydrogen bonds is influenced by the activation of the C(alpha)-H atoms and by the flexibility of the side-chain atoms. In contrast to small-molecule structures, anticooperative geometries are common in the macromolecular structures studied here, and there is a gradual lengthening as the extent of furcation increases. C-H...O bonds formed by Gly, Phe, and Tyr residues are noteworthy. The numbers of hydrogen bond donors and acceptors agree with Lipinski's "rule of five" that predicts drug-like properties. Hydrogen bonds formed by water are also seen to be relevant in ligand binding. Ligand C-H...O(w) interactions are abundant when compared to N-H...O(w) and O-H...O(w). This suggests that ligands prefer to use their stronger hydrogen bond capabilities for use with the protein residues, leaving the weaker interactions to bind with water. In summary, the interplay between strong and weak interactions in ligand binding possibly leads to a satisfactory enthalpy-entropy balance. The implications of these results to crystallographic refinement and molecular dynamics software are discussed.     

PIBASE: a comprehensive database of structurally defined protein interfaces

MOTIVATION: In recent years, the Protein Data Bank (PDB) has experienced rapid growth. To maximize the utility of the high resolution protein-protein interaction data stored in the PDB, we have developed PIBASE, a comprehensive relational database of structurally defined interfaces between pairs of protein domains. It is composed of binary interfaces extracted from structures in the PDB and the Probable Quaternary Structure server using domain assignments from the Structural Classification of Proteins and CATH fold classification systems. RESULTS: PIBASE currently contains 158,915 interacting domain pairs between 105,061 domains from 2125 SCOP families. A diverse set of geometric, physiochemical and topologic properties are calculated for each complex, its domains, interfaces and binding sites. A subset of the interface properties are used to remove interface redundancy within PDB entries, resulting in 20,912 distinct domain-domain interfaces. The complexes are grouped into 989 topological classes based on their patterns of domain-domain contacts. The binary interfaces and their corresponding binding sites are categorized into 18,755 and 30,975 topological classes, respectively, based on the topology of secondary structure elements. The utility of the database is illustrated by outlining several current applications. AVAILABILITY: The database is accessible via the world wide web at http://salilab.org/pibase SUPPLEMENTARY INFORMATION: http://salilab.org/pibase/suppinfo.html.     

Observation of a unique pattern of bifurcated hydrogen bonds in the crystal structures of the N-glycoprotein linkage region models

Elucidation of the intra- and intermolecular carbohydrate-protein interactions would greatly contribute toward obtaining a better understanding of the structure-function correlations of the protein-linked glycans. The weak interactions involving C-H...O have recently been attracting immense attention in the domain of biomolecular recognition. However, there has been no report so far on the occurrence of C-H...O hydrogen bonds in the crystal structures of models and analogs of N-glycoproteins. We present herein an analysis of C-H...O interactions in the crystal structures of all N-glycoprotein linkage region models and analogs. The study reveals a cooperative network of bifurcated hydrogen bonds consisting of N-H...O and C-H...O interactions seen uniquely for the models. The cooperative network consists of two antiparallel chains of bifurcated hydrogen bonds, one involving N1-H, C2'-H and O1' of the aglycon moiety and the other involving N2-H, C1-H and O1' of the sugar. Such bifurcated hydrogen bonds between the core glycan and protein are likely to play an important role in the folding and stabilization of proteins.     

VarSite: Disease variants and protein structure

VarSite is a web server mapping known disease‐associated variants from UniProt and ClinVar, together with natural variants from gnomAD, onto protein 3D structures in the Protein Data Bank. The analyses are primarily image‐based and provide both an overview for each human protein, as well as a report for any specific variant of interest. The information can be useful in assessing whether a given variant might be pathogenic or benign. The structural annotations for each position in the protein include protein secondary structure, interactions with ligand, metal, DNA/RNA, or other protein, and various measures of a given variant's possible impact on the protein's function. The 3D locations of the disease‐associated variants can be viewed interactively via the 3dmol.js JavaScript viewer, as well as in RasMol and PyMOL. Users can search for specific variants, or sets of variants, by providing the DNA coordinates of the base change(s) of interest. Additionally, various agglomerative analyses are given, such as the mapping of disease and natural variants onto specific Pfam or CATH domains. The server is freely accessible to all at: https://www.ebi.ac.uk/thornton-srv/databases/VarSite .     

Evaluation of C-H cdots,three dots,centered O hydrogen bonds in native and misfolded proteins

Non-traditional C-H cdots, three dots, centered Y hydrogen bonds, in which a carbon atom acts as the hydrogen donor and an electronegative atom Y (Y=N, O or S) acts as the acceptor, have been reported in proteins, but their importance in protein structures is not well established. Here, we present the results of three computational tests that examine the significance of C-H cdots, three dots, centered Y bonds involving the C(alpha) in proteins. First, we compared the number of C(alpha)-H cdots, three dots, centered Y bonds in native structures with two sets of compact, energy-minimized decoy structures. The decoy structures contain about as many C(alpha)-H cdots, three dots, centered Y bonds as the native structures, indicating that the constraints of chain connectivity and compactness can lead to incidental formation of C(alpha)-H cdots, three dots, centered Y bonds. Secondly, we examined whether short C(alpha)-H cdots, three dots, centered Y bonds have a tendency to be linear, as is expected for a cohesive hydrogen-bonding interaction. The native structures do show this trend, but so does one of the decoy sets, suggesting that this criterion is also not sufficient to indicate a stabilizing interaction. Finally, we examined the preference for C(alpha)-H cdots, three dots, centered Y bond donors to be near to strong hydrogen bond acceptors. In the native proteins, the alpha protons attract strong acceptors like oxygen atoms more than weak acceptors. In contrast, hydrogen bond donors in the decoy structures do not distinguish between strong and weak acceptors. Thus, any individual C(alpha)-H cdots, three dots, centered Y bond may be fortuitous and occur due to the polypeptide connectivity and compactness. Taken collectively, however, C(alpha)-H cdots, three dots, centered Y bonds provide a weakly cohesive force that stabilizes proteins.     

PDBsum extras: SARS‐CoV‐2 and AlphaFold models

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.