Resolving protein structure‐function‐binding site relationships from a binding site similarity network perspective

Functional annotation is seldom straightforward with complexities arising due to functional divergence in protein families or functional convergence between non‐homologous protein families, leading to mis‐annotations. An enzyme may contain multiple domains and not all domains may be involved in a given function, adding to the complexity in function annotation. To address this, we use binding site information from bound cognate ligands and catalytic residues, since it can help in resolving fold‐function relationships at a finer level and with higher confidence. A comprehensive database of 2,020 fold‐function‐binding site relationships has been systematically generated. A network‐based approach is employed to capture the complexity in these relationships, from which different types of associations are deciphered, that identify versatile protein folds performing diverse functions, same function associated with multiple folds and one‐to‐one relationships. Binding site similarity networks integrated with fold, function, and ligand similarity information are generated to understand the depth of these relationships. Apart from the observed continuity in the functional site space, network properties of these revealed versatile families with topologically different or dissimilar binding sites and structural families that perform very similar functions. As a case study, subtle changes in the active site of a set of evolutionarily related superfamilies are studied using these networks. Tracing of such similarities in evolutionarily related proteins provide clues into the transition and evolution of protein functions. Insights from this study will be helpful in accurate and reliable functional annotations of uncharacterized proteins, poly‐pharmacology, and designing enzymes with new functional capabilities. Proteins 2017; 85:1319–1335. © 2017 Wiley Periodicals, Inc.     

Identification of common structural features of binding sites in galactose-specific proteins

Galactose-binding proteins characterize an important subgroup of sugar-binding proteins that are involved in a variety of biological processes. Structural studies have shown that the Gal-specific proteins encompass a diverse range of primary and tertiary structures. The binding sites for galactose also seem to vary in different protein-galactose complexes. No common binding site features that are shared by the Gal-specific proteins to achieve ligand specificity are so far known. With the assumption that common recognition principles will exist for common substrate recognition, the present study was undertaken to identify and characterize any unique galactose-binding site signature by analyzing the three-dimensional (3D) structures of 18 protein-galactose complexes. These proteins belong to 7 nonhomologous families; thus, there is no sequence or structural similarity across the families. Within each family, the binding site residues and their relative distances were well conserved, but there were no similarities across families. A novel, yet simple, approach was adopted to characterize the binding site residues by representing their relative spatial dispositions in polar coordinates. A combination of the deduced geometrical features with the structural characteristics, such as solvent accessibility and secondary structure type, furnished a potential galactose-binding site signature. The signature was evaluated by incorporation into the program COTRAN to search for potential galactose-binding sites in proteins that share the same fold as the known galactose-binding proteins. COTRAN is able to detect galactose-binding sites with a very high specificity and sensitivity. The deduced galactose-binding site signature is strongly validated and can be used to search for galactose-binding sites in proteins. PROSITE-type signature sequences have also been inferred for galectin and C-type animal lectin-like fold families of Gal-binding proteins.     

Insilco analysis of functionally important residues in folate receptors

Lack of crystal structure data of folate binding proteins has left so many questions unanswered (for example, important residues in active site, binding domain, important amino acid residues involved in interactions between ligand and receptor). With sequence alignment and PROSITE motif identification, we attempted to answer evolutionarily significant residues that are of functional importance for ligand binding and that form catalytic sites. We have analyzed 46 different FRs and FBP sequences of various organisms obtained from Genbank. Multiple sequence alignment identified 44 highly conserved identical amino acid residues with 10 cysteine residues and 12 motifs including ECSPNLGPW (which might help in the structural stability of FR).     

Predicted metal binding sites for phytoremediation

Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. The objective of the study is to design and analyze metal binding motifs against the genes involved in phytoremediation. This is being done on the basis of certain pre-requisite amino-acid residues known to bind metal ions/metal complexes in medicinal and aromatic plants (MAP''s). Earlier work on MAP''s have shown that heavy metals accumulated by aromatic and medicinal plants do not appear in the essential oil and that some of these species are able to grow in metal contaminated sites. A pattern search against the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases yielded true positives in each case showing the high specificity of the motifs designed for the ions of nickel, lead, molybdenum, manganese, cadmium, zinc, iron, cobalt and xenobiotic compounds. Motifs were also studied against PDB structures. Results of the study suggested the presence of binding sites on the surface of protein molecules involved. PDB structures of proteins were finally predicted for the binding sites functionality in their respective phytoremediation usage. This was further validated through CASTp server to study its physico-chemical properties. Bioinformatics implications would help in designing strategy for developing transgenic plants with increased metal binding capacity. These metal binding factors can be used to restrict metal update by plants. This helps in reducing the possibility of metal movement into the food chain.     

Characterization of surface binding sites in glycoside hydrolases: A computational study

Structural properties of carbohydrate surface binding sites (SBSs) were investigated with computational methods. Eighty‐five SBSs of 44 enzymes in 119 Protein Data Bank (PDB) files were collected as a dataset. On the basis of SBSs shape, they were divided into 3 categories: flat surfaces, clefts, and cavities (types A, B, and C, respectively). Ligand varieties showed the correlation between shape of SBSs and ligands size. To reduce cut‐off differences in each SBSs with different ligand size, molecular docking were performed. Molecular docking results were used to refine SBSs classification and binding sites cut‐off. Docking results predicted putative ligands positions and displayed dependence of the ligands binding mode to the structural type of SBSs. Physicochemical properties of SBSs were calculated for all docking results with YASARA Structure. The results showed that all SBSs are hydrophilic, while their charges could vary and depended to ligand size and defined cut‐off. Surface binding sites type B had highest average values of solvent accessible surface area. Analysis of interactions showed that hydrophobic interactions occur more than hydrogen bonds, which is related to the presence of aromatic residues and carbohydrates interactions.     

Protein function annotation by local binding site surface similarity

Hundreds of protein crystal structures exist for proteins whose function cannot be confidently determined from sequence similarity. Surflex‐PSIM, a previously reported surface‐based protein similarity algorithm, provides an alternative method for hypothesizing function for such proteins. The method now supports fully automatic binding site detection and is fast enough to screen comprehensive databases of protein binding sites. The binding site detection methodology was validated on apo/holo cognate protein pairs, correctly identifying 91% of ligand binding sites in holo structures and 88% in apo structures where corresponding sites existed. For correctly detected apo binding sites, the cognate holo site was the most similar binding site 87% of the time. PSIM was used to screen a set of proteins that had poorly characterized functions at the time of crystallization, but were later biochemically annotated. Using a fully automated protocol, this set of 8 proteins was screened against ～60,000 ligand binding sites from the PDB. PSIM correctly identified functional matches that predated query protein biochemical annotation for five out of the eight query proteins. A panel of 12 currently unannotated proteins was also screened, resulting in a large number of statistically significant binding site matches, some of which suggest likely functions for the podorly characterized proteins. Proteins 2014; 82:679–694. © 2013 Wiley Periodicals, Inc.     

Structure and function of the AAA+ nucleotide binding pocket

Members of the diverse superfamily of AAA+ proteins are molecular machines responsible for a wide range of essential cellular processes. In this review we summarise structural and functional data surrounding the nucleotide binding pocket of these versatile complexes. Protein Data Bank (PDB) structures of closely related AAA+ ATPase are overlaid and biologically relevant motifs are displayed. Interactions between protomers are illustrated on the basis of oligomeric structures of each AAA+ subgroup. The possible role of conserved motifs in the nucleotide binding pocket is assessed with regard to ATP binding and hydrolysis, oligomerisation and inter-subunit communication. Our comparison indicates that in particular the roles of the arginine finger and sensor 2 residues differ subtly between AAA+ subgroups, potentially providing a means for functional diversification.     

Studies on the inference of protein binding regions across fold space based on structural similarities

The emerging picture of a continuous protein fold space highlights the existence of non obvious structural similarities between proteins with apparent different topologies. The identification of structure resemblances across fold space and the analysis of similar recognition regions may be a valuable source of information towards protein structure-based functional characterization. In this work, we use non-sequential structural alignment methods (ns-SAs) to identify structural similarities between protein pairs independently of their SCOP hierarchy, and we calculate the significance of binding region conservation using the interacting residues overlap in the ns-SA. We cluster the binding inferences for each family to distinguish already known family binding regions from putative new ones. Our methodology exploits the enormous amount of data available in the PDB to identify binding region similarities within protein families and to propose putative binding regions. Our results indicate that there is a plethora of structurally common binding regions among proteins, independently of current fold classifications. We obtain a 6- to 8-fold enrichment of novel binding regions, and identify binding inferences for 728 protein families that so far lack binding information in the PDB. We explore binding mode analogies between ligands from commonly clustered binding regions to investigate the utility of our methodology. A comprehensive analysis of the obtained binding inferences may help in the functional characterization of protein recognition and assist rational engineering. The data obtained in this work is available in the download link at www.scowlp.org.     

Towards a structural classification of phosphate binding sites in protein-nucleotide complexes: an automated all-against-all structural comparison using geometric matching

A method is described for the rapid comparison of protein binding sites using geometric matching to detect similar three-dimensional structure. The geometric matching detects common atomic features through identification of the maximum common sub-graph or clique. These features are not necessarily evident from sequence or from global structural similarity giving additional insight into molecular recognition not evident from current sequence or structural classification schemes. Here we use the method to produce an all-against-all comparison of phosphate binding sites in a number of different nucleotide phosphate-binding proteins. The similarity search is combined with clustering of similar sites to allow a preliminary structural classification. Clustering by site similarity produces a classification of binding sites for the 476 representative local environments producing ten main clusters representing half of the representative environments. The similarities make sense in terms of both structural and functional classification schemes. The ten main clusters represent a very limited number of unique structural binding motifs for phosphate. These are the structural P-loop, di-nucleotide binding motif [FAD/NAD(P)-binding and Rossman-like fold] and FAD-binding motif. Similar classification schemes for nucleotide binding proteins have also been arrived at independently by others using different methods.     

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.     

Evolution of binding sites for zinc and calcium ions playing structural roles

The geometry of metal coordination by proteins is well understood, but the evolution of metal binding sites has been less studied. Here we present a study on a small number of well-documented structural calcium and zinc binding sites, concerning how the geometry diverges between relatives, how often nonrelatives converge towards the same structure, and how often these metal binding sites are lost in the course of evolution. Both calcium and zinc binding site structure is observed to be conserved; structural differences between those atoms directly involved in metal binding in related proteins are typically less than 0.5 A root mean square deviation, even in distant relatives. Structural templates representing these conserved calcium and zinc binding sites were used to search the Protein Data Bank for cases where unrelated proteins have converged upon the same residue selection and geometry for metal binding. This allowed us to identify six "archetypal" metal binding site structures: two archetypal zinc binding sites, both of which had independently evolved on a large number of occasions, and four diverse archetypal calcium binding sites, where each had evolved independently on only a handful of occasions. We found that it was common for distant relatives of metal-binding proteins to lack metal-binding capacity. This occurred for 13 of the 18 metal binding sites we studied, even though in some of these cases the original metal had been classified as "essential for protein folding." For most of the calcium binding sites studied (seven out of eleven cases), the lack of metal binding in relatives was due to point mutation of the metal-binding residues, whilst for zinc binding sites, lack of metal binding in relatives always involved more extensive changes, with loss of secondary structural elements or loops around the binding site.     

Surface‐based protein binding pocket similarity

Protein similarity comparisons may be made on a local or global basis and may consider sequence information or differing levels of structural information. We present a local three‐dimensional method that compares protein binding site surfaces in full atomic detail. The approach is based on the morphological similarity method which has been widely applied for global comparison of small molecules. We apply the method to all‐by‐all comparisons two sets of human protein kinases, a very diverse set of ATP‐bound proteins from multiple species, and three heterogeneous benchmark protein binding site data sets. Cases of disagreement between sequence‐based similarity and binding site similarity yield informative examples. Where sequence similarity is very low, high pocket similarity can reliably identify important binding motifs. Where sequence similarity is very high, significant differences in pocket similarity are related to ligand binding specificity and similarity. Local protein binding pocket similarity provides qualitatively complementary information to other approaches, and it can yield quantitative information in support of functional annotation. Proteins 2011; © 2011 Wiley‐Liss, Inc.     

Comparison analysis of primary ligand‐binding sites in seven‐helix membrane proteins

Seven‐helix transmembrane proteins, including the G‐protein‐coupled receptors (GPCRs), mediate a broad range of fundamental cellular activities through binding to a wide range of ligands. Understanding the structural basis for the ligand‐binding selectivity of these proteins is of significance to their structure‐based drug design. Comparison analysis of proteins' ligand‐binding sites provides a useful way to study their structure‐activity relationships. Various computational methods have been developed for the binding‐site comparison of soluble proteins. In this work, we applied this approach to the analysis of the primary ligand‐binding sites of 92 seven‐helix transmembrane proteins. Results of the studies confirmed that the binding site of bacterial rhodopsins is indeed different from all GPCRs. In the latter group, further comparison of the binding sites indicated a group of residues that could be responsible for ligand‐binding selectivity and important for structure‐based drug design. Furthermore, unexpected binding‐site dissimilarities were observed among adrenergic and adenosine receptors, suggesting that the percentage of the overall sequence identity between a target protein and a template protein alone is not sufficient for selecting the best template for homology modeling of seven‐helix membrane proteins. These results provided novel insight into the structural basis of ligand‐binding selectivity of seven‐helix membrane proteins and are of practical use to the computational modeling of these proteins. © 2010 Wiley Periodicals, Inc. Biopolymers 95: 31–38, 2011.     

Partner-specific prediction of RNA-binding residues in proteins: A critical assessment

RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are “specific”, that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are “non-RNA specific.” Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both.     

Architecture of the sugar binding sites in carbohydrate binding proteins-a computer modeling study

Different sugars, Gal, GalNAc and Man were docked at the monosaccharide binding sites of Erythrina corallodenron (EcorL), peanut lectin (PNA), Lathyrus ochrus (LOLI), and pea lectin (PSL). To study the lectin-carbohydrate interactions, in the complexes, the hydroxymethyl group in Man and Gal favors, gg and gt conformations respectively, and is the dominant recognition determination. The monosaccharide binding site in lectins that are specific to Gal/GalNAc is wider due to the additional amino acid residues in loop D as compared to that in lectins specific to Man/Glc, and affects the hydrogen bonds of the sugar involving residues from loop D, but not its orientation in the binding site. The invariant amino acid residues Asp from loop A, and Asn and an aromatic residue (Phe or Tyr) in loop C provides the basic architecture to recognize the common features in C4 epimers. The invariant Gly in loop B together with one or two residues in the variable region of loop D/A holds the sugar tightly at both ends. Loss of any one of these hydrogen bonds leads to weak interaction. While the subtle variations in the sequence and conformation of peptide fragment that resulted due to the size and location of gaps present in amino acid sequence in the neighborhood of the sugar binding site of loop D/A seems to discriminate the binding of sugars which differ at C4 atom (galacto and gluco configurations). The variations at loop B are important in discriminating Gal and GalNAc binding. The present study thus provides a structural basis for the observed specificities of legume lectins which uses the same four invariant residues for binding. These studies also bring out the information that is important for the design/engineering of proteins with the desired carbohydrate specificity.     

Exploiting 3D structural templates for detection of metal-binding sites in protein structures

High throughput structural genomics efforts have been making the structures of proteins available even before their function has been fully characterized. Therefore, methods that exploit the structural knowledge to provide evidence about the functions of proteins would be useful. Such methods would be needed to complement the sequence-based function annotation approaches. The current study describes generation of 3D-structural motifs for metal-binding sites from the known metalloproteins. It then scans all the available protein structures in the PDB database for putative metal-binding sites. Our analysis predicted more than 1000 novel metal-binding sites in proteins using three-residue templates, and more than 150 novel metal-binding sites using four-residue templates. Prediction of metal-binding site in a yeast protein YDR533c led to the hypothesis that it might function as metal-dependent amidopeptidase. The structural motifs identified by our method present novel metal-binding sites that reveal newer mechanisms for a few well-known proteins.     

Hidden partners: Using cross‐docking calculations to predict binding sites for proteins with multiple interactions

Protein‐protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein‐protein interactions. Cross‐docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross‐docking simulations of 358 proteins with 2 different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity‐sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross‐docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, that is, partners not included in the original cross‐docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.     

A putative ATP binding protein influences the fidelity of branchpoint recognition in yeast splicing

We previously described a dominant suppressor of the splicing defect conferred by an A----C intron branchpoint mutation in S. cerevisiae. Suppression occurs by increasing the frequency with which the mutant branchpoint is utilized. We have now cloned the genomic region encoding the prp16-1 suppressor function and have demonstrated that PRP16 is essential for viability. A 1071 amino acid open reading frame contains sequence motifs characteristic of an NTP binding fold and further similarities to a superfamily of proteins that includes members with demonstrated RNA-dependent ATPase activity. A single nucleotide change necessary to confer the prp16-1 suppressor phenotype results in a Tyr----Asp substitution near the "A site" consensus for NTP binding proteins. We propose that PRP16 is an excellent candidate for mediating one of the many ATP-requiring steps of spliceosome assembly and that accuracy of branchpoint recognition may be coupled to ATP binding and/or hydrolysis.     

Nucleotide binding architecture for secreted cytotoxic endoribonucleases

Vertebrate secreted RNases are small cationic protein endowed with an endoribonuclease activity that belong to the RNase A superfamily and display diverse cytotoxic activities. In an effort to unravel their mechanism of action, we have analysed their nucleotide binding recognition patterns. General shared features with other nucleotide binding proteins were deduced from overall statistics on the available structure complexes at the Protein Data Bank and compared with the particularities of selected representative endoribonuclease families. Results were compared with other endoribonuclease representative families and with the overall protein–nucleotide interaction features. Preferred amino acids and atom types involved in pair bonding interactions were identified, defining the spatial motives for phosphate, base and ribose building blocks. Together with the conserved catalytic triad at the active site, variability was observed for secondary binding subsites that may contribute to the proper substrate alignment and could explain the distinct substrate preference patterns. Highly conserved binding patterns were identified for the pyrimidine and purine subsites at the main and secondary base subsites. Particular substitution could be ascribed to specific adenine or guanine specificities. Distribution of evolutionary conserved residues were compared to search for the structure determinants that underlie their diverse catalytic efficiency and those that may account for putative physiological substrate targets or other non-catalytic biological activities that contribute to the antipathogen role of the RNases involved in the host defence system. A side by side comparison with another endoribonuclease superfamily of secreted cytotoxic proteins, the microbial RNases, was carried on to analyse the common features and peculiarities that rule their substrate recognition. The data provides the structural basis for the development of applied therapies targeting cellular nucleotide polymers.