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InteractoMIX is a suite of computational tools designed to exploit interactomics information at different levels ranging from genome-wide interactomes to their atomic 3D structural details. Interactomix is the result of a combined effort from the Structural Bioinformatics Lab at the University Pompeu Fabra headed by Prof Baldo Oliva and the Bioinsilico dot org lab headed by Narcis Fernandez-Fuentes. Currently, Interactomix integrates 11 of the most advanced computations tools to study interactomic data at different levels of resolution and thus addressing both the questions of: what proteins interact and how do these proteins interact. More information is available in the publication describing the method and on the help pages.

V-D²OCK is a web application designed to derive structural models of protein complexes using data-driven docking.The method relies on the binding sites prediction made by VORFFIP, including a subsequent refining step: V-PATCH, novel to this work. The information is then used by PatchDock to dock the protein monomers and the docking space is then clustered using Gromacs to reduce redundancy. Users can choose among 3 different scoring functions to rank the structural models. More information is available in the publication describing the method and on the help pages of the web-server

Frag'R'Us is a web application designed to sample alternative protein backbone conformations in loop regions using the geometrical constrains of smotifs (as defined in this publication). The remodeling of short fragment(s) of the protein backbone is required to accommodate new function(s), fine-tune binding specificities or change/create novel protein interactions. Frag'r'Us therefore is a tool to seed the search of suitable fragments or smotifs. More information is available here and here and on the help pages of the web-server

Multi-VORFFIP is a web server to predict functional sites in protein. Muti-VORFFIP represents an evolution of our currrent server VORFFIP but extended on line the prediction of protein-binding sites but also peptide-, DNA-, and RNA-binding sites. Under benchmarking conditions Multi-VORFFIP performed at the comparable level when compared to current methodologies. Moreover, Multi-VORFFIP predicts multiple binding sites in the same protein with high accuracy and selectivity. Multi-VORFFIP is interface by a powerful molecular viewer that allows users to simultaneously visualize all predicted binding sites in the context of the protein structures. More information is available on the paper describing the method and on the help pages of the web-server

VORFFIP is a web server to predict protein binding sites in protein structures. VORFFIP makes use of several residue features including structural, energetic, evolutionary and crystallographic B-factors information and a new definition of residue environment by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensembler. More information is available on the paper describing the method and on the web-server

PCRPi-W is a web server to chart hot spots in protein structures. Several are the features that characterize the residues that are part of a hot spot. These can be broadly grouped in three categories: energy, structural, and evolutionary-based (e.g. sequence conservation). PCRPi-W combines a set of seven different measures that account for energetic, structural, and evolutionary-based information into an unique probabilistic framework by using Bayesian Networks. More information is available on the paper describing the method and on the web-server

ArchPred is a knwoledge-based loop structure prediction method. The algorithm selects candidate loop fragments from a regularly updated loop library (Search Space) by matching the length, the types of bracing secondary structures of the query and by satisfying the geometrical restraints imposed by the stem residues. Subsequently, candidate loops are inserted in the query protein framework where their side chains are rebuilt and their fit is assessed by the RMSD of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed [phi/psi] main chain dihedral angle propensities.

M4T, Multiple Mapping Method with Multiple Templates, is a fully automated comparative protein structure modeling server. The novelty of M4T resides in two of its major modules, Multiple Templates (MT) and Multiple Mapping Method (MMM). The MT module of M4T selects and optimally combines the sequences of multiple template structures through an iterative clustering approach that takes into account the 'unique' contribution of each template, its sequence similarity to other template sequences and to the target sequences, and the crystal resolution. MMM module is a sequence-to-structure alignment method that is aimed at improving the alignment accuracy, especially at lower sequence identity levels.