Ratna R. Thangudu

Inferred Biomolecular Interaction Server—a web server to analyze and predict protein interacting partners and binding sites

IBIS is the NCBI Inferred Biomolecular Interaction Server. This server organizes, analyzes and predicts interaction partners and locations of binding sites in proteins. IBIS provides annotations for different types of binding partners (protein, chemical, nucleic acid and peptides), and facilitates the mapping of a comprehensive biomolecular interaction network for a given protein query. IBIS reports interactions observed in experimentally determined structural complexes of a given protein, and at the same time IBIS infers binding sites/interacting partners by inspecting protein complexes formed by homologous proteins. Similar binding sites are clustered together based on their sequence and structure conservation. To emphasize biologically relevant binding sites, several algorithms are used for verification in terms of evolutionary conservation, biological importance of binding partners, size and stability of interfaces, as well as evidence from the published literature. IBIS is updated regularly and is freely accessible via http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.html.

IBIS (Inferred Biomolecular Interaction Server) reports, predicts and integrates multiple types of conserved interactions for proteins

We have recently developed the Inferred Biomolecular Interaction Server (IBIS) and database, which reports, predicts and integrates different types of interaction partners and locations of binding sites in proteins based on the analysis of homologous structural complexes. Here, we highlight several new IBIS features and options. The servers webpage is now redesigned to allow users easier access to data for different interaction types. An entry page is added to give a quick summary of available results and to now accept protein sequence accessions. To elucidate the formation of protein complexes, not just binary interactions, IBIS currently presents an expandable interaction network. Previously, IBIS provided annotations for four different types of binding partners: proteins, small molecules, nucleic acids and peptides; in the current version a new protein–ion interaction type has been added. Several options provide easy downloads of IBIS data for all Protein Data Bank (PDB) protein chains and the results for each query. In this study, we show that about one-third of all RefSeq sequences can be annotated with IBIS interaction partners and binding sites. The IBIS server is available at http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi and updated biweekly.

Analysis on conservation of disulphide bonds and their structural features in homologous protein domain families

BackgroundDisulphide bridges are well known to play key roles in stability, folding and functions of proteins. Introduction or deletion of disulphides by site-directed mutagenesis have produced varying effects on stability and folding depending upon the protein and location of disulphide in the 3-D structure. Given the lack of complete understanding it is worthwhile to learn from an analysis of extent of conservation of disulphides in homologous proteins. We have also addressed the question of what structural interactions replaces a disulphide in a homologue in another homologue.ResultsUsing a dataset involving 34,752 pairwise comparisons of homologous protein domains corresponding to 300 protein domain families of known 3-D structures, we provide a comprehensive analysis of extent of conservation of disulphide bridges and their structural features. We report that only 54% of all the disulphide bonds compared between the homologous pairs are conserved, even if, a small fraction of the non-conserved disulphides do include cytoplasmic proteins. Also, only about one fourth of the distinct disulphides are conserved in all the members in protein families. We note that while conservation of disulphide is common in many families, disulphide bond mutations are quite prevalent. Interestingly, we note that there is no clear relationship between sequence identity between two homologous proteins and disulphide bond conservation. Our analysis on structural features at the sites where cysteines forming disulphide in one homologue are replaced by non-Cys residues show that the elimination of a disulphide in a homologue need not always result in stabilizing interactions between equivalent residues.ConclusionWe observe that in the homologous proteins, disulphide bonds are conserved only to a modest extent. Very interestingly, we note that extent of conservation of disulphide in homologous proteins is unrelated to the overall sequence identity between homologues. The non-conserved disulphides are often associated with variable structural features that were recruited to be associated with differentiation or specialisation of protein function.

Crystal structure of a feruloyl esterase belonging to the tannase family: A disulfide bond near a catalytic triad

Feruloyl esterase (FAE) catalyzes the hydrolysis of the ferulic and diferulic acids present in plant cell wall polysaccharides, and tannase catalyzes the hydrolysis of tannins to release gallic acid. The fungal tannase family in the ESTHER database contains various enzymes, including FAEs and tannases. Despite the importance of FAEs and tannases in bioindustrial applications, three‐dimensional structures of the fungal tannase family members have been unknown. Here, we determined the crystal structure of FAE B from Aspergillus oryzae (AoFaeB), which belongs to the fungal tannase family, at 1.5 Å resolution. AoFaeB consists of a catalytic α/β‐hydrolase fold domain and a large lid domain, and the latter has a novel fold. To estimate probable binding models of substrates in AoFaeB, an automated docking analysis was performed. In the active site pocket of AoFaeB, residues responsible for the substrate specificity of the FAE activity were identified. The catalytic triad of AoFaeB comprises Ser203, Asp417, and His457, and the serine and histidine residues are directly connected by a disulfide bond of the neighboring cysteine residues, Cys202 and Cys458. This structural feature, the “CS‐D‐HC motif,” is unprecedented in serine hydrolases. A mutational analysis indicated that the novel structural motif plays essential roles in the function of the active site. Proteins 2014; 82:2857–2867.

Native and modeled disulfide bonds in proteins: knowledge-based approaches toward structure prediction of disulfide-rich polypeptides

Structure prediction and three‐dimensional modeling of disulfide‐rich systems are challenging due to the limited number of such folds in the structural databank. We exploit the stereochemical compatibility of substructures in known protein structures to accomodate disulfide bonds in predicting the structures of disulfide‐rich polypeptides directly from disulfide connectivity pattern and amino acid sequence in the absence of structural homologs and any other structural information. This knowledge‐based approach is illustrated using structure prediction of 40 nonredundant bioactive disulfide‐rich polypeptides such as toxins, growth factors, and endothelins available in the structural databank. The polypeptide conformation could be predicted in 35 out of 40 nonredundant entries (87%). Nonhomologous templates could be identified and models could be obtained within 2 Å deviation from the query in 29 peptides (72%). This procedure can be accessed from the World Wide Web (http://www.ncbs.res.in/∼faculty/mini/dsdbase/dsdbase.html). Proteins 2005.

Knowledge-based annotation of small molecule binding sites in proteins

BackgroundThe study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapidly increasing structural data, it is essential to improve the tools that enable large scale binding site prediction with greater emphasis on their biological validity.ResultsWe have developed a new method for the annotation of protein-small molecule binding sites, using inference by homology, which allows us to extend annotation onto protein sequences without experimental data available. To ensure biological relevance of binding sites, our method clusters similar binding sites found in homologous protein structures based on their sequence and structure conservation. Binding sites which appear evolutionarily conserved among non-redundant sets of homologous proteins are given higher priority. After binding sites are clustered, position specific score matrices (PSSMs) are constructed from the corresponding binding site alignments. Together with other measures, the PSSMs are subsequently used to rank binding sites to assess how well they match the query and to better gauge their biological relevance. The method also facilitates a succinct and informative representation of observed and inferred binding sites from homologs with known three-dimensional structures, thereby providing the means to analyze conservation and diversity of binding modes. Furthermore, the chemical properties of small molecules bound to the inferred binding sites can be used as a starting point in small molecule virtual screening. The method was validated by comparison to other binding site prediction methods and to a collection of manually curated binding site annotations. We show that our method achieves a sensitivity of 72% at predicting biologically relevant binding sites and can accurately discriminate those sites that bind biological small molecules from non-biological ones.ConclusionsA new algorithm has been developed to predict binding sites with high accuracy in terms of their biological validity. It also provides a common platform for function prediction, knowledge-based docking and for small molecule virtual screening. The method can be applied even for a query sequence without structure. The method is available at http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi.

Homology inference of protein-protein interactions via conserved binding sites.

The coverage and reliability of protein-protein interactions determined by high-throughput experiments still needs to be improved, especially for higher organisms, therefore the question persists, how interactions can be verified and predicted by computational approaches using available data on protein structural complexes. Recently we developed an approach called IBIS (Inferred Biomolecular Interaction Server) to predict and annotate protein-protein binding sites and interaction partners, which is based on the assumption that the structural location and sequence patterns of protein-protein binding sites are conserved between close homologs. In this study first we confirmed high accuracy of our method and found that its accuracy depends critically on the usage of all available data on structures of homologous complexes, compared to the approaches where only a non-redundant set of complexes is employed. Second we showed that there exists a trade-off between specificity and sensitivity if we employ in the prediction only evolutionarily conserved binding site clusters or clusters supported by only one observation (singletons). Finally we addressed the question of identifying the biologically relevant interactions using the homology inference approach and demonstrated that a large majority of crystal packing interactions can be correctly identified and filtered by our algorithm. At the same time, about half of biological interfaces that are not present in the protein crystallographic asymmetric unit can be reconstructed by IBIS from homologous complexes without the prior knowledge of crystal parameters of the query protein.

Analycys: A database for conservation and conformation of disulphide bonds in homologous protein domains

Disulphide bonds in proteins are known to play diverse roles ranging from folding to structure to function. Thorough knowledge of the conservation status and structural state of the disulphide bonds will help in understanding of the differences in homologous proteins. Here we present a database for the analysis of conservation and conformation of disulphide bonds in SCOP structural families. This database has a wide range of applications including mapping of disulphide bond mutation patterns, identification of disulphide bonds important for folding and stabilization, modeling of protein tertiary structures and in protein engineering. The database can be accessed at: http://bioinformatics.univ‐reunion.fr/analycys/. Proteins 2007.

Mutations in DNA-binding loop of NFAT5 transcription factor produce unique outcomes on protein-DNA binding and dynamics.

The nuclear factor of activated T cells 5 (NFAT5 or TonEBP) is a Rel family transcriptional activator and is activated by hypertonic conditions. Several studies point to a possible connection between nuclear translocation and DNA binding; however, the mechanism of NFAT5 nuclear translocation and the effect of DNA binding on retaining NFAT5 in the nucleus are largely unknown. Recent experiments showed that different mutations introduced in the DNA-binding loop and dimerization interface were important for DNA binding and some of them decreased the nuclear–cytoplasm ratio of NFAT5. To understand the mechanisms of these mutations, we model their effect on protein dynamics and DNA binding. We show that the NFAT5 complex without DNA is much more flexible than the complex with DNA. Moreover, DNA binding considerably stabilizes the overall dimeric complex and the NFAT5 dimer is only marginally stable in the absence of DNA. Two sets of NFAT5 mutations from the same DNA-binding loop are found to have different mechanisms of specific and nonspecific binding to DNA. The R217A/E223A/R226A (R293A/E299A/R302A using isoform c numbering) mutant is characterized by significantly compromised binding to DNA and higher complex flexibility. On the contrary, the T222D (T298D in isoform c) mutation, a potential phosphomimetic mutation, makes the overall complex more rigid and does not significantly affect the DNA binding. Therefore, the reduced nuclear–cytoplasm ratio of NFAT5 can be attributed to reduced binding to DNA for the triple mutant, while the T222D mutant suggests an additional mechanism at work.