MOTIVATION: A variety of pocket detection algorithms are now freely or commercially available to the scientific community for the analysis of static protein structures. However, since proteins are dynamic entities, enhancing the capabilities of these programs for the straightforward detection and characterization of cavities taking into account protein conformational ensembles should be valuable for capturing the plasticity of pockets, and therefore allow gaining insight into structure-function relationships. RESULTS: This article describes a new method, called MDpocket, providing a fast, free and open-source tool for tracking small molecule binding sites and gas migration pathways on molecular dynamics (MDs) trajectories or other conformational ensembles. MDpocket is based on the fpocket cavity detection algorithm and a valuable contribution to existing analysis tools. The capabilities of MDpocket are illustrated for three relevant cases: (i) the detection of transient subpockets using an ensemble of crystal structures of HSP90; (ii) the detection of known xenon binding sites and migration pathways in myoglobin; and (iii) the identification of suitable pockets for molecular docking in P38 Map kinase. AVAILABILITY: MDpocket is free and open-source software and can be downloaded at http://fpocket.sourceforge.net. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abstract Classical molecular interaction potentials, in conjunction with other theoretical techniques, are used to analyze the dependence of the binding sites of representative proteins on the bound ligand. It is found that the ligand bound introduces in general small structural perturbations at the binding site of the protein. However, such small structural changes can lead to important alterations in the recognition pattern of the protein. The impact of these findings in docking procedures is discussed. Contact: [email protected]; [email protected] * To whom correspondence should be addressed.

Modesto Orozco, F. J. Luque; POEAMS: program for outliers elimination in ‘anomalous’ multidimensional space, Bioinformatics, Volume 5, Issue 3, 1 July 1989, Pag

A Program for Outliers Elimination in Multidimensional Space (POEMS), which allows the user to eliminate outliers from training spaces as a prior step to any statistical study, is presented. Even though the program can be applied to any scientific field, the characteristics of POEMS makes it particularly suitable for 'series design' on Quantitative Structure-Activity Relationships studies.