SwissSimilarity: A Web Tool for Low to Ultra High Throughput Ligand-Based Virtual Screening.

SwissSimilarity is a new web tool for rapid ligand-based virtual screening of small to unprecedented ultralarge libraries of small molecules. Screenable compounds include drugs, bioactive and commercial molecules, as well as 205 million of virtual compounds readily synthesizable from commercially available synthetic reagents. Predictions can be carried out on-the-fly using six different screening approaches, including 2D molecular fingerprints as well as superpositional and fast nonsuperpositional 3D similarity methodologies. SwissSimilarity is part of a large initiative of the SIB Swiss Institute of Bioinformatics to provide online tools for computer-aided drug design, such as SwissDock, SwissBioisostere or SwissTargetPrediction with which it can interoperate, and is linked to other well-established online tools and databases. User interface and backend have been designed for simplicity and ease of use, to provide proficient virtual screening capabilities to specialists and nonexperts in the field. SwissSimilarity is accessible free of charge or login at http://www.swisssimilarity.ch .

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server.

BACKGROUND: Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting detailed analyses to positions of extremely high or low variability or dubbed important beforehand based on existing knowledge about active sites, interaction surfaces, (de)stabilizing mutations, etc. RESULTS: Our new webserver PsychoProt (freely available without registration at http://psychoprot.epfl.ch or at http://lucianoabriata.altervista.org/psychoprot/index.html ) helps to detect, quantify, and sequence/structure map the biophysical and biochemical traits that shape amino acid preferences throughout a protein as determined by deep-sequencing of saturated mutational libraries or from large alignments of naturally occurring variants. DISCUSSION: We exemplify how PsychoProt helps to (i) unveil protein structure-function relationships from experiments and from alignments that are consistent with structures according to coevolution analysis, (ii) recall global information about structural and functional features and identify hitherto unknown constraints to variation in alignments, and (iii) point at different sources of variation among related experimental datasets or between experimental and alignment-based data. Remarkably, metabolic costs of the amino acids pose strong constraints to variability at protein surfaces in nature but not in the laboratory. This and other differences call for caution when extrapolating results from in vitro experiments to natural scenarios in, for example, studies of protein evolution. CONCLUSION: We show through examples how PsychoProt can be a useful tool for the broad communities of structural biology and molecular evolution, particularly for studies about protein modeling, evolution and design.

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure-based computer-aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand-protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state-of-the-art docking programs.

LipidBuilder: A Framework To Build Realistic Models for Biological Membranes.

The physical and chemical characterization of biological membranes is of fundamental importance for understanding the functional role of lipid bilayers in shaping cells and organelles, steering vesicle trafficking and promoting membrane-protein signaling. Molecular dynamics simulations stand as a powerful tool to probe the properties of membranes at atomistic level. However, the biological membrane is highly complex, and closely mimicking its physiological constitution in silico is not a straightforward task. Here, we present LipidBuilder, a framework for creating and storing models of biologically relevant phospholipid species with acyl tails of heterogeneous composition. LipidBuilder also enables the assembly of these database-stored lipids into realistic bilayers featuring asymmetric distribution on layer leaflets and concentration of given membrane constituents as defined, for example, by lipidomics experiments. The ability of LipidBuilder to assemble robust membrane models was validated by simulating membranes of homogeneous lipid composition for which experimental data are available. Furthermore, taking advantage of the extensive lipid headgroup repertoire, we assembled models of membranes of heterogeneous nature as naturally found in viral (phage PRD1), bacterial (Salmonella enterica, Laurinavicius , S. ; Kakela , R. ; Somerharju , P. ; Bamford , D. H. ; Virology 2004 , 322 , 328 - 336 ) and plant (Chlorella kessleri, Rezanka , T. ; Podojil , M. ; J. Chromatogr. 1989 , 463 , 397 - 408 ) organisms. These realistic membrane models were built using a near-exact lipid composition revealed from analytical chemistry experiments. We suggest LipidBuilder as a useful tool to model biological membranes of near-biological complexity, and as a robust complement to the current efforts to characterize the biophysical properties of biological membrane using molecular simulation.

Reaction Mechanism and Catalytic Fingerprint of Allantoin Racemase.

The stereospecific oxidative decomposition of urate into allantoin is the core of purine catabolism in many organisms. The spontaneous decomposition of upstream intermediates and the nonenzymatic racemization of allantoin lead to an accumulation of (R)-allantoin, because the enzymes converting allantoin into allantoate are specific for the (S) isomer. The enzyme allantoin racemase catalyzes the reversible conversion between the two allantoin enantiomers, thus ensuring the overall efficiency of the catabolic pathway and preventing allantoin accumulation. On the basis of recent crystallographic and biochemical evidence, allantoin racemase has been assigned to the family of cofactor-independent racemases, together with other amino acid racemases. A detailed computational investigation of allantoin racemase has been carried out to complement the available experimental data and to provide atomistic insight into the enzymatic action. Allantoin, the natural substrate of the enzyme, has been investigated at the quantum mechanical level, in order to rationalize its conformational and tautomeric equilibria, playing a key role in protein-ligand recognition and in the following catalytic steps. The reaction mechanism of the enzyme has been elucidated through quantum mechanics/molecular mechanics (QM/MM) calculations. The potential energy surface investigation, carried out at the QM/MM level, revealed a stepwise reaction mechanism. A pair of cysteine residues promotes the stereoinversion of a carbon atom of the ligand without the assistance of cofactors. Electrostatic fingerprint calculations are used to discuss the role of the active site residues in lowering the pKa of the substrate. The planar unprotonated intermediate is compared with the enolic allantoin tautomer observed in the active site of the crystallized enzyme. Finally, the enzymatic catalysis featured by allantoin racemase (AllR) is compared with that of other enzymes belonging to the same family.

Cardiolipin Models for Molecular Simulations of Bacterial and Mitochondrial Membranes.

Present in bacterial and mitochondrial membranes, cardiolipins have a unique dimeric structure, which carries up to two charges (i.e., one per phosphate group) and, under physiological conditions, can be unprotonated or singly protonated. Exhaustive models and characterization of cardiolipins are to date scarce; therefore we propose an ab initio parametrization of cardiolipin species for molecular simulation consistent with commonly used force fields. Molecular dynamics simulations using these models indicate a protonation dependent lipid packing. A peculiar interaction with solvating mono- and divalent cations is also observed. The proposed models will contribute to the study of the assembly of more realistic bacterial and mitochondrial membranes and the investigation of the role of cardiolipins for the biophysical and biochemical properties of membranes and membrane-embedded proteins.