Ramanathan Sowdhamini

Knowledge-Based Protein Modeling

Knowledge, both from the three-dimensional structures of homologous proteins and from the general analysis of protein structure, is of value in modeling a protein of known sequence but unknown structure. While many models are still constructed at least in part by manual methods on graphics devices, automated procedures have come into greater use. These procedures include those that assemble fragments of structure from other known structures and those that derive coordinates for the model from the satisfaction of restraints placed on atomic positions.

Nanoscale Organization of Hedgehog Is Essential for Long-Range Signaling

Hedgehog (Hh) plays crucial roles in tissue-patterning and activates signaling in Patched (Ptc)-expressing cells. Paracrine signaling requires release and transport over many cell diameters away by a process that requires interaction with heparan sulfate proteoglycans (HSPGs). Here, we examine the organization of functional, fluorescently tagged variants in living cells by using optical imaging, FRET microscopy, and mutational studies guided by bioinformatics prediction. We find that cell-surface Hh forms suboptical oligomers, further concentrated in visible clusters colocalized with HSPGs. Mutation of a conserved Lys in a predicted Hh-protomer interaction interface results in an autocrine signaling-competent Hh isoform--incapable of forming dense nanoscale oligomers, interacting with HSPGs, or paracrine signaling. Thus, Hh exhibits a hierarchical organization from the nanoscale to visible clusters with distinct functions.

Cross genome comparisons of serine proteases in Arabidopsis and rice

BackgroundSerine proteases are one of the largest groups of proteolytic enzymes found across all kingdoms of life and are associated with several essential physiological pathways. The availability of Arabidopsis thaliana and rice (Oryza sativa) genome sequences has permitted the identification and comparison of the repertoire of serine protease-like proteins in the two plant species.ResultsDespite the differences in genome sizes between Arabidopsis and rice, we identified a very similar number of serine protease-like proteins in the two plant species (206 and 222, respectively). Nearly 40% of the above sequences were identified as potential orthologues. Atypical members could be identified in the plant genomes for Deg, Clp, Lon, rhomboid proteases and species-specific members were observed for the highly populated subtilisin and serine carboxypeptidase families suggesting multiple lateral gene transfers. DegP proteases, prolyl oligopeptidases, Clp proteases and rhomboids share a significantly higher percentage orthology between the two genomes indicating substantial evolutionary divergence was set prior to speciation. Single domain architectures and paralogues for several putative subtilisins, serine carboxypeptidases and rhomboids suggest they may have been recruited for additional roles in secondary metabolism with spatial and temporal regulation. The analysis reveals some domain architectures unique to either or both of the plant species and some inactive proteases, like in rhomboids and Clp proteases, which could be involved in chaperone function.ConclusionThe systematic analysis of the serine protease-like proteins in the two plant species has provided some insight into the possible functional associations of previously uncharacterised serine protease-like proteins. Further investigation of these aspects may prove beneficial in our understanding of similar processes in commercially significant crop plant species.

CAMPASS: a database of structurally aligned protein superfamilies

We thank Andrej Sali, John Overington and Mark Johnson for use of the programs COMPARER, JOY and MALIGN, respectively. We thank the anonymous referees for their useful comments. For financial support, RS thanks the Imperial Cancer Research Fund; DFB and HAN Oxford Molecular Ltd; KM HFSP; NS The Wellcome Trust; and RES the MRC.

STIFDB2: An Updated Version of Plant Stress-Responsive TranscrIption Factor DataBase with Additional Stress Signals, Stress-Responsive Transcription Factor Binding Sites and Stress-Responsive Genes in Arabidopsis and Rice

Understanding the principles of abiotic and biotic stress responses, tolerance and adaptation remains important in plant physiology research to develop better varieties of crop plants. Better understanding of plant stress response mechanisms and application of knowledge derived from integrated experimental and bioinformatics approaches are gaining importance. Earlier, we showed that compiling a database of stress-responsive transcription factors and their corresponding target binding sites in the form of Hidden Markov models at promoter, untranslated and upstream regions of stress-up-regulated genes from expression analysis can help in elucidating various aspects of the stress response in Arabidopsis. In addition to the extensive content in the first version, STIFDB2 is now updated with 15 stress signals, 31 transcription factors and 5,984 stress-responsive genes from three species (Arabidopsis thaliana, Oryza sativa subsp. japonica and Oryza sativa subsp. indica). We have employed an integrated biocuration and genomic data mining approach to characterize the data set of transcription factors and consensus binding sites from literature mining and stress-responsive genes from the Gene Expression Omnibus. STIFDB2 currently has 38,798 associations of stress signals, stress-responsive genes and transcription factor binding sites predicted using the Stress-responsive Transcription Factor (STIF) algorithm, along with various functional annotation data. As a unique plant stress regulatory genomics data platform, STIFDB2 can be utilized for targeted as well as high-throughput experimental and computational studies to unravel principles of the stress regulome in dicots and gramineae. STIFDB2 is available from the URL: http://caps.ncbs.res.in/stifdb2

100 ns Molecular Dynamics Simulations to Study Intramolecular Conformational Changes in Bax

Abstract Bax is a pro-apoptotic member of the widely studied Bcl-2 family of apoptotic proteins. Its function is regulated by anti-apoptotic members of the same family. Bcl-xL is one such member, which plays a key role in inhibiting the function of Bax. Recent experimental evidences suggest that intra-molecular conformational changes in the all-helical fold of Bax are necessary for it to be amenable to regulation by Bcl-xL, principal among these being proposed interactions between the N-terminus and α5, α6 (transmembrane TM1.1 and TM1.2) of Bax. The present study is a detailed molecular dynamics investigation of Bax in an aqueous environment, in order to better understand the nature of intra-molecular conformational changes it undergoes before it translocates and inserts into the mitochondrial membrane. A distinct movement of the N-terminal end is observed in a 100ns production run of Bax. Fluctuations across domains are compared for simulations in full-length and deletion mutants of Bax. A series of hydrogen bonding patterns across N-terminal region and α7,8 (BH2 domain) is observed during the simulations. BH2 domain, in turn, acquires new hydrogen bond interactions with TM1 helices. The analysis further revealed other hydrogen bond interactions, across crucial domains in Bax, which are mediated by water molecules across the length of simulation. The structural alliance between N-terminal region and BH2 domain suggests a structural transition cascade leading to the dislocation of TM helices away from hydrophobic interactions that normally prevail with the BH3 domain in the cytosolic form of Bax.

A database of globular protein structural domains: clustering of representative family members into similar folds

BACKGROUND A database of globular domains, derived from a non-redundant set of proteins, is useful for the sequence analysis of aligned domains, for structural comparisons, for understanding domain stability and flexibility and for fold recognition procedures. Domains are defined by the program DIAL and classified structurally using the procedure SEA. RESULTS The DIAL-derived domain database (DDBASE) consists of 436 protein chains involving 695 protein domains. Of these, 206 are alpha-class, 191 are beta-class and 294 alpha and beta class. The domains, 63% from multidomain proteins and 73% less than 150 residues in length, were clustered automatically using both single-link cluster analysis and hierarchical clustering to give a quantitative estimate of similarity in the domain-fold space. CONCLUSIONS Highly populated and well described folds (doubly wound alpha/beta, singly wound alpha/beta barrels, globins alpha, large Greek-key beta and flavin-binding alpha/beta) are recognized at a SEA cut-off score of 0.55 in single-link clustering and at 0.65 in hierarchical clustering, although functionally related families are usually clearly distinguished at more stringent values.

STIFDB—Arabidopsis Stress Responsive Transcription Factor DataBase

Elucidating the key players of molecular mechanism that mediate the complex stress-responses in plants system is an important step to develop improved variety of stress tolerant crops. Understanding the effects of different types of biotic and abiotic stress is a rapidly emerging domain in the area of plant research to develop better, stress tolerant plants. Information about the transcription factors, transcription factor binding sites, function annotation of proteins coded by genes expressed during abiotic stress (for example: drought, cold, salinity, excess light, abscisic acid, and oxidative stress) response will provide better understanding of this phenomenon. STIFDB is a database of abiotic stress responsive genes and their predicted abiotic transcription factor binding sites in Arabidopsis thaliana. We integrated 2269 genes upregulated in different stress related microarray experiments and surveyed their 1000 bp and 100 bp upstream regions and 5′UTR regions using the STIF algorithm and identified putative abiotic stress responsive transcription factor binding sites, which are compiled in the STIFDB database. STIFDB provides extensive information about various stress responsive genes and stress inducible transcription factors of Arabidopsis thaliana. STIFDB will be a useful resource for researchers to understand the abiotic stress regulome and transcriptome of this important model plant system.

Genome-wide survey of prokaryotic serine proteases: Analysis of distribution and domain architectures of five serine protease families in prokaryotes

BackgroundSerine proteases are one of the most abundant groups of proteolytic enzymes found in all the kingdoms of life. While studies have established significant roles for many prokaryotic serine proteases in several physiological processes, such as those associated with metabolism, cell signalling, defense response and development, functional associations for a large number of prokaryotic serine proteases are relatively unknown. Current analysis is aimed at understanding the distribution and probable biological functions of the select serine proteases encoded in representative prokaryotic organisms.ResultsA total of 966 putative serine proteases, belonging to five families, were identified in the 91 prokaryotic genomes using various sensitive sequence search techniques. Phylogenetic analysis reveals several species-specific clusters of serine proteases suggesting their possible involvement in organism-specific functions. Atypical phylogenetic associations suggest an important role for lateral gene transfer events in facilitating the widespread distribution of the serine proteases in the prokaryotes. Domain organisations of the gene products were analysed, employing sensitive sequence search methods, to infer their probable biological functions. Trypsin, subtilisin and Lon protease families account for a significant proportion of the multi-domain representatives, while the D-Ala-D-Ala carboxypeptidase and the Clp protease families are mostly single-domain polypeptides in prokaryotes. Regulatory domains for protein interaction, signalling, pathogenesis, cell adhesion etc. were found tethered to the serine protease domains. Some domain combinations (such as S1-PDZ; LON-AAA-S16 etc.) were found to be widespread in the prokaryotic lineages suggesting a critical role in prokaryotes.ConclusionDomain architectures of many serine proteases and their homologues identified in prokaryotes are very different from those observed in eukaryotes, suggesting distinct roles for serine proteases in prokaryotes. Many domain combinations were found unique to specific prokaryotic species, suggesting functional specialisation in various cellular and physiological processes.

Comparative genomics of odorant binding proteins in Anopheles gambiae, Aedes aegypti and Culex quinquefasciatus.

About 1 million people in the world die each year from diseases spread by mosquitoes, and understanding the mechanism of host identification by the mosquitoes through olfaction is at stake. The role of odorant binding proteins (OBPs) in the primary molecular events of olfaction in mosquitoes is becoming an important focus of biological research in this area. Here, we present a comprehensive comparative genomics study of OBPs in the three disease-transmitting mosquito species Anopheles gambiae, Aedes aegypti, and Culex quinquefasciatus starting with the identification of 110 new OBPs in these three genomes. We have characterized their genomic distribution and orthologous and phylogenetic relationships. The diversity and expansion observed with respect to the Aedes and Culex genomes suggests that the OBP gene family acquired functional diversity concurrently with functional constraints posed on these two species. Sequences with unique features have been characterized such as the “two-domain OBPs” (previously known as Atypical OBPs) and “MinusC OBPs” in mosquito genomes. The extensive comparative genomics featured in this work hence provides useful primary insights into the role of OBPs in the molecular adaptations of mosquito olfactory system and could provide more clues for the identification of potential targets for insect repellants and attractants.