000130105 001__ 130105
000130105 005__ 20241125101135.0
000130105 0247_ $$2doi$$a10.1021/acs.jcim.3c01107
000130105 0248_ $$2sideral$$a136502
000130105 037__ $$aART-2023-136502
000130105 041__ $$aeng
000130105 100__ $$0(orcid)0000-0002-1896-7805$$aGalano-Frutos, Juan J.$$uUniversidad de Zaragoza
000130105 245__ $$aCalculation of protein folding thermodynamics using molecular dynamics simulations
000130105 260__ $$c2023
000130105 5060_ $$aAccess copy available to the general public$$fUnrestricted
000130105 5203_ $$aDespite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. However, the challenge of calculating the state functions governing protein folding from first-principles remains unaddressed. We present here a simple approach that allows us to accurately calculate the energetics of protein folding. It is based on computing the energy of the folded and unfolded states at different temperatures using molecular dynamics simulations. From this, two essential quantities (ΔH and ΔCp) are obtained and used to calculate the conformational stability of the protein (ΔG). With this approach, we have successfully calculated the energetics of two- and three-state proteins, representatives of the major structural classes, as well as small stability differences (ΔΔG) due to changes in solution conditions or variations in an amino acid residue.
000130105 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E45-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PDC2021-121341-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-107293GB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2022-141068NB-I00
000130105 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000130105 590__ $$a5.7$$b2023
000130105 592__ $$a1.396$$b2023
000130105 591__ $$aCHEMISTRY, MEDICINAL$$b10 / 72 = 0.139$$c2023$$dQ1$$eT1
000130105 593__ $$aChemical Engineering (miscellaneous)$$c2023$$dQ1
000130105 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b34 / 250 = 0.136$$c2023$$dQ1$$eT1
000130105 593__ $$aLibrary and Information Sciences$$c2023$$dQ1
000130105 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b28 / 170 = 0.165$$c2023$$dQ1$$eT1
000130105 593__ $$aComputer Science Applications$$c2023$$dQ1
000130105 591__ $$aCHEMISTRY, MULTIDISCIPLINARY$$b61 / 231 = 0.264$$c2023$$dQ2$$eT1
000130105 593__ $$aChemistry (miscellaneous)$$c2023$$dQ1
000130105 594__ $$a9.8$$b2023
000130105 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000130105 700__ $$aNerín-Fonz, Francho
000130105 700__ $$0(orcid)0000-0002-2879-9200$$aSancho, Javier$$uUniversidad de Zaragoza
000130105 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000130105 773__ $$g63, 24 (2023), 7791-7806$$pJ. Chem Inf. Model.$$tJournal of Chemical Information and Modeling$$x1549-9596
000130105 8564_ $$s6174248$$uhttps://zaguan.unizar.es/record/130105/files/texto_completo.pdf$$yVersión publicada
000130105 8564_ $$s2988726$$uhttps://zaguan.unizar.es/record/130105/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000130105 909CO $$ooai:zaguan.unizar.es:130105$$particulos$$pdriver
000130105 951__ $$a2024-11-22-12:00:38
000130105 980__ $$aARTICLE