Skip to Main content Skip to Navigation
Journal articles

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

Amélie Barozet 1 Kevin Molloy 2 Marc Vaisset 3 Christophe Zanon 3 Pierre Fauret 3 Thierry Siméon 1 Juan Cortés 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes
3 LAAS-I2C - Service Instrumentation Conception Caractérisation
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : 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. Availability: MoMA-LoopSampler is freely available at: https://moma.laas.fr/applications/LoopSampler/ We recommend users to create an account, but anonymous access is possible. In most cases, jobs are completed within a few minutes. The waiting time may increase depending on the server load, but it very rarely exceeds an hour. For users requiring more intensive use, binaries can be provided upon request. Supplementary information Supplementary data are available at Bioinformatics online.
Complete list of metadata

https://hal.laas.fr/hal-03326493
Contributor : Juan Cortés Connect in order to contact the contributor
Submitted on : Thursday, August 26, 2021 - 9:52:36 AM
Last modification on : Wednesday, January 5, 2022 - 3:50:12 AM
Long-term archiving on: : Saturday, November 27, 2021 - 6:20:06 PM

Identifiers

Citation

Amélie Barozet, Kevin Molloy, Marc Vaisset, Christophe Zanon, Pierre Fauret, et al.. MoMA-LoopSampler: A web server to exhaustively sample protein loop conformations. Bioinformatics, Oxford University Press (OUP), 2022, 38 (2), pp.552-553. ⟨10.1093/bioinformatics/btab584⟩. ⟨hal-03326493⟩

Share

Metrics

Les métriques sont temporairement indisponibles