Cristian Micheletti1, Henri Orland. 1. SISSA, CNR-INFM Democritos and Italian Institute of Technology, Via Beirut 2-4, 34014 Trieste, Italy. michelet@sissa.it
Abstract
MOTIVATION: The steady growth of the number of available protein structures has constantly motivated the development of new algorithms for detecting structural correspondences in proteins. Detecting structural equivalences in two or more proteins is computationally demanding as it typically entails the exploration of the combinatorial space of all possible amino acid pairings in the parent proteins. The search is often aided by the introduction of various constraints such as considering protein fragments, rather than single amino acids, and/or seeking only sequential correspondences in the given proteins. An additional challenge is represented by the difficulty of associating to a given alignment, a reliable a priori measure of its statistical significance. RESULTS: Here, we present and discuss MISTRAL (Multiple STRuctural ALignment), a novel strategy for multiple protein alignment based on the minimization of an energy function over the low-dimensional space of the relative rotations and translations of the molecules. The energy minimization avoids combinatorial searches and returns pairwise alignment scores for which a reliable a priori statistical significance can be given. AVAILABILITY: MISTRAL is freely available for academic users as a standalone program and as a web service at http://ipht.cea.fr/protein.php.
MOTIVATION: The steady growth of the number of available protein structures has constantly motivated the development of new algorithms for detecting structural correspondences in proteins. Detecting structural equivalences in two or more proteins is computationally demanding as it typically entails the exploration of the combinatorial space of all possible amino acid pairings in the parent proteins. The search is often aided by the introduction of various constraints such as considering protein fragments, rather than single amino acids, and/or seeking only sequential correspondences in the given proteins. An additional challenge is represented by the difficulty of associating to a given alignment, a reliable a priori measure of its statistical significance. RESULTS: Here, we present and discuss MISTRAL (Multiple STRuctural ALignment), a novel strategy for multiple protein alignment based on the minimization of an energy function over the low-dimensional space of the relative rotations and translations of the molecules. The energy minimization avoids combinatorial searches and returns pairwise alignment scores for which a reliable a priori statistical significance can be given. AVAILABILITY: MISTRAL is freely available for academic users as a standalone program and as a web service at http://ipht.cea.fr/protein.php.
Authors: Steven Molinarolo; Sora Lee; Lilia Leisle; John D Lueck; Daniele Granata; Vincenzo Carnevale; Christopher A Ahern Journal: J Biol Chem Date: 2018-01-25 Impact factor: 5.157
Authors: Calem J Bendell; Shalon Liu; Tristan Aumentado-Armstrong; Bogdan Istrate; Paul T Cernek; Samuel Khan; Sergiu Picioreanu; Michael Zhao; Robert A Murgita Journal: BMC Bioinformatics Date: 2014-03-24 Impact factor: 3.169