000087818 001__ 87818
000087818 005__ 20230519145342.0
000087818 0247_ $$2doi$$a10.1093/bib/bbz146
000087818 0248_ $$2sideral$$a116202
000087818 037__ $$aART-2021-116202
000087818 041__ $$aeng
000087818 100__ $$0(orcid)0000-0002-1896-7805$$aGalano-Frutos, Juan J.
000087818 245__ $$aMolecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when
000087818 260__ $$c2021
000087818 5060_ $$aAccess copy available to the general public$$fUnrestricted
000087818 5203_ $$aThe increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical–chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80–85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore’s law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.
000087818 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E45-17R$$9info:eu-repo/grantAgreement/EUR/INTERREG-POCTEFA/PIREPRED-EFA086/15$$9info:eu-repo/grantAgreement/ES/MINECO/BFU2016-78232-P
000087818 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttp://creativecommons.org/licenses/by-nc/3.0/es/
000087818 590__ $$a13.994$$b2021
000087818 591__ $$aBIOCHEMICAL RESEARCH METHODS$$b3 / 79 = 0.038$$c2021$$dQ1$$eT1
000087818 591__ $$aMATHEMATICAL & COMPUTATIONAL BIOLOGY$$b1 / 57 = 0.018$$c2021$$dQ1$$eT1
000087818 592__ $$a3.032$$b2021
000087818 593__ $$aMolecular Biology$$c2021$$dQ1
000087818 593__ $$aInformation Systems$$c2021$$dQ1
000087818 594__ $$a11.6$$b2021
000087818 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000087818 700__ $$0(orcid)0000-0002-9590-7371$$aGarcía-Cebollada, Helena$$uUniversidad de Zaragoza
000087818 700__ $$0(orcid)0000-0002-2879-9200$$aSancho Sanz, Javier$$uUniversidad de Zaragoza
000087818 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000087818 773__ $$g22, 1 (2021), 3–19$$pBrief. bioinform.$$tBRIEFINGS IN BIOINFORMATICS$$x1467-5463
000087818 8564_ $$s883542$$uhttps://zaguan.unizar.es/record/87818/files/texto_completo.pdf$$yVersión publicada
000087818 8564_ $$s2584160$$uhttps://zaguan.unizar.es/record/87818/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000087818 909CO $$ooai:zaguan.unizar.es:87818$$particulos$$pdriver
000087818 951__ $$a2023-05-18-13:16:20
000087818 980__ $$aARTICLE