Literature DB >> 30289133

Assessing the capability of in silico mutation protocols for predicting the finite temperature conformation of amino acids.

Rodrigo Ochoa1, Miguel A Soler, Alessandro Laio, Pilar Cossio.   

Abstract

Mutation protocols are a key tool in computational biophysics for modelling unknown side chain conformations. In particular, these protocols are used to generate the starting structures for molecular dynamics simulations. The accuracy of the initial side chain and backbone placement is crucial to obtain a stable and quickly converging simulation. In this work, we assessed the performance of several mutation protocols in predicting the most probable conformer observed in finite temperature molecular dynamics simulations for a set of protein-peptide crystals differing only by single-point mutations in the peptide sequence. Our results show that several programs which predict well the crystal conformations fail to predict the most probable finite temperature configuration. Methods relying on backbone-dependent rotamer libraries have, in general, a better performance, but even the best protocol fails in predicting approximately 30% of the mutations.

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Year:  2018        PMID: 30289133     DOI: 10.1039/c8cp03826k

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  9 in total

1.  Computational Evolution Protocol for Peptide Design.

Authors:  Rodrigo Ochoa; Miguel A Soler; Ivan Gladich; Anna Battisti; Nikola Minovski; Alex Rodriguez; Sara Fortuna; Pilar Cossio; Alessandro Laio
Journal:  Methods Mol Biol       Date:  2022

2.  Protocol for iterative optimization of modified peptides bound to protein targets.

Authors:  Rodrigo Ochoa; Pilar Cossio; Thomas Fox
Journal:  J Comput Aided Mol Des       Date:  2022-10-19       Impact factor: 4.179

3.  Multiple-Allele MHC Class II Epitope Engineering by a Molecular Dynamics-Based Evolution Protocol.

Authors:  Rodrigo Ochoa; Victoria Alves Santos Lunardelli; Daniela Santoro Rosa; Alessandro Laio; Pilar Cossio
Journal:  Front Immunol       Date:  2022-04-27       Impact factor: 8.786

4.  Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors.

Authors:  Abimbola Feyisara Adedeji Olulana; Miguel A Soler; Martina Lotteri; Hendrik Vondracek; Loredana Casalis; Daniela Marasco; Matteo Castronovo; Sara Fortuna
Journal:  Int J Mol Sci       Date:  2021-01-15       Impact factor: 5.923

Review 5.  Evolution of the Automatic Rhodopsin Modeling (ARM) Protocol.

Authors:  Laura Pedraza-González; Luca De Vico; Massimo Olivucci; Leonardo Barneschi; Daniele Padula
Journal:  Top Curr Chem (Cham)       Date:  2022-03-15

6.  KEAP1 Cancer Mutants: A Large-Scale Molecular Dynamics Study of Protein Stability.

Authors:  Carter J Wilson; Megan Chang; Mikko Karttunen; Wing-Yiu Choy
Journal:  Int J Mol Sci       Date:  2021-05-20       Impact factor: 5.923

7.  Impact of Structural Observables From Simulations to Predict the Effect of Single-Point Mutations in MHC Class II Peptide Binders.

Authors:  Rodrigo Ochoa; Roman A Laskowski; Janet M Thornton; Pilar Cossio
Journal:  Front Mol Biosci       Date:  2021-03-30

8.  In silico assessment of human Calprotectin subunits (S100A8/A9) in presence of sodium and calcium ions using Molecular Dynamics simulation approach.

Authors:  Nematollah Gheibi; Mohammad Ghorbani; Hanifeh Shariatifar; Alireza Farasat
Journal:  PLoS One       Date:  2019-10-17       Impact factor: 3.240

9.  Effects of unsaturated fatty acids (Arachidonic/Oleic Acids) on stability and structural properties of Calprotectin using molecular docking and molecular dynamics simulation approach.

Authors:  Nematollah Gheibi; Mohamad Ghorbani; Hanifeh Shariatifar; Alireza Farasat
Journal:  PLoS One       Date:  2020-03-26       Impact factor: 3.240

  9 in total

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