Current Projects

    Coarse-grained free energy landscapes for protein conformational changes [J. Chem. Phys. (2015) 143(24): 243153].

    Landscape

    Figure: Human serum albumin
    (a) The % of variance captured by PCA (b) free energy landscape (c) Visualization of PC1 (d) Visualization of PC2

    Abstract: In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes.

    The Use of Experimental Structures to Model Protein Dynamics [Meth. Mol. Biol. (2014) 1215: 213-236.]

    PCA

    Figure: HIV-1 protease.
    (a) Cartoon representation of HIV-1 protease structure with each monomer in red and blue. (b) Visualization of the first three PCs of HIV-1 protease visualized on the structures, derived from a set of 329 structures.

    Abstract: The number of solved protein structures submitted in the Protein Data Bank (PDB) has increased dramatically in recent years. For some specific proteins, this number is very high-for example, there are over 550 solved structures for HIV-1 protease, one protein that is essential for the life cycle of human immunodeficiency virus (HIV) which causes acquired immunodeficiency syndrome (AIDS) in humans. The large number of structures for the same protein and its variants include a sample of different conformational states of the protein. A rich set of structures solved experimentally for the same protein has information buried within the dataset that can explain the functional dynamics and structural mechanism of the protein. To extract the dynamics information and functional mechanism from the experimental structures, we discuss two methods: Principal Component Analysis (PCA) and Elastic Network Models (ENM). PCA is a widely used statistical dimensionality reduction technique to classify and visualize high-dimensional data. On the other hand, ENMs are well-established simple biophysical method for modeling the functionally important global motions of proteins. This chapter covers the basics of these two. Moreover, an improved ENM version that utilizes the variations found within a given set of structures for a protein is described. As a practical example, we have extracted the functional dynamics and mechanism of HIV-1 protease dimeric structure by using a set of 329 PDB structures of this protein.

    An analysis of conformational changes upon RNA-protein binding. [Proc. 5th ACM Conf. on Bioinf., Comp. Biol. and Health Inf. (2014) 592-593.]

    escet

    Figure: ATP-dependent RNA helicase DDX48.
    (a) Error-scaled internal distance change matrices between RNA-bound and unbound forms of DDX48. Red (blue) indicates increase (decrease) in internal distance. (b) Superimposition of bound (violet) and unbound (green) forms of DDX48 showing flexible, invariant and interface residues.

    Abstract: Multiple sequence alignments become biologically meaningful only if conserved and functionally important residues and secondary structural elements preserved can be identified at equivalent positions. This is particularly important for transmembrane proteins like G-protein coupled receptors (GPCRs) with seven transmembrane helices. TM-MOTIF is a software package and an effective alignment viewer to identify and display conserved motifs and amino acid substitutions (AAS) at each position of the aligned set of homologous sequences of GPCRs. The key feature of the package is to display the predicted membrane topology for seven transmembrane helices in seven colours (VIBGYOR colouring scheme) and to map the identified motifs on its respective helices /loop regions. It is an interactive package which provides options to the user to submit query or pre-aligned set of GPCR sequences to align with a reference sequence, like rhodopsin, whose structure has been solved experimentally. It also provides the possibility to identify the nearest homologue from the available inbuilt GPCR or Olfactory Receptor cluster dataset whose association is already known for its receptor type. The tool is available for download from the DOR homepage

    Previous Projects

    DOCKSCORE: A scoring scheme for scoring docked poses of protein-protein complexes. [PLoS ONE (2014) 9(2): e80255].

    DockScore

    Abstract: Molecular interactions are studied computationally using the approach named as Molecular Docking, which employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. We have proposed a rigorous scoring scheme called 'DockScore' which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. Currently the Sowdhamini Lab has made the algorithm available to the public as a web-server: DOCKSCORE Server

    DOR: a Database of Olfactory Receptors from selected eukaryotic genomes. [Bioinf. & Biol. Insights (2014) 8: 147-158.]

    DockScore

    Abstract: The database of olfactory receptors (DOR) is a repository that provides sequence and structural information on ORs of selected organisms (such as Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Homo sapiens). Users can download OR sequences, study predicted membrane topology, and obtain cross-genome sequence alignments and phylogeny, including three-dimensional (3D) structural models of 100 selected ORs and their predicted dimer interfaces. The database can be accessed from http://caps.ncbs.res.in/DOR. Such a database should be helpful in designing experiments on point mutations to probe into the possible dimerization modes of ORs and to even understand the evolutionary changes between different receptors.

    TM-MOTIF: An alignment viewer for transmembrane regions and motifs in G-Protein Coupled Receptors (GPCRs). [Bioinformation (2011) 7(5): 214-221.]

    tmmotif

    Abstract: Multiple sequence alignments become biologically meaningful only if conserved and functionally important residues and secondary structural elements preserved can be identified at equivalent positions. This is particularly important for transmembrane proteins like G-protein coupled receptors (GPCRs) with seven transmembrane helices. TM-MOTIF is a software package and an effective alignment viewer to identify and display conserved motifs and amino acid substitutions (AAS) at each position of the aligned set of homologous sequences of GPCRs. The key feature of the package is to display the predicted membrane topology for seven transmembrane helices in seven colours (VIBGYOR colouring scheme) and to map the identified motifs on its respective helices /loop regions. It is an interactive package which provides options to the user to submit query or pre-aligned set of GPCR sequences to align with a reference sequence, like rhodopsin, whose structure has been solved experimentally. It also provides the possibility to identify the nearest homologue from the available inbuilt GPCR or Olfactory Receptor cluster dataset whose association is already known for its receptor type. The tool is available for download from the DOR homepage