MoMA-LoopSampler: a web server to exhaustively sample protein loop conformations | Zendy

Amélie Barozet | Zendy; Kevin Molloy | Zendy; Marc Vaisset | Zendy; Christophe Za | Zendy; Pierre Fauret | Zendy; Thierry Siméon | Zendy; Juan Cortés | Zendy

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MoMA-LoopSampler: a web server to exhaustively sample protein loop conformations

Author(s) -

Amélie Barozet,

Kevin Molloy,

Marc Vaisset,

Christophe Za,

Pierre Fauret,

Thierry Siméon,

Juan Cortés

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab584

Subject(s) - computer science , web server , loop (graph theory) , sampling (signal processing) , sample (material) , interface (matter) , process (computing) , set (abstract data type) , user interface , data mining , the internet , world wide web , operating system , programming language , computer vision , mathematics , chemistry , filter (signal processing) , chromatography , combinatorics , bubble , maximum bubble pressure method

MoMA-LoopSampler is a sampling method that globally explores the conformational space of flexible protein loops. It combines a large structural library of three-residue fragments and a novel reinforcement-learning-based approach to accelerate the sampling process while maintaining diversity. The method generates a set of statistically likely loop states satisfying geometric constraints, and its ability to sample experimentally observed conformations has been demonstrated. This paper presents a web user interface to MoMA-LoopSampler through the illustration of a typical use-case.

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