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Article: In silico concurrent multisite pH titration in proteins

TitleIn silico concurrent multisite pH titration in proteins
Authors
Issue Date2014
Citation
Journal of Computational Chemistry, 2014, v. 35, p. 1491-1498 How to Cite?
AbstractThe concurrent proton binding at multiple sites in macromolecules such as proteins and nucleic acids is an important yet challenging problem in biochemistry. We develop an efficient generalized Hamiltonian approach to attack this issue. Based on the previously developed generalized-ensemble methods, an effective potential energy is constructed which combines the contributions of all (relevant) protonation states of the molecule. The effective potential preserves important phase regions of all states and, thus, allows efficient sampling of these regions in one simulation. The need for intermediate states in alchemical free energy simulations is greatly reduced. Free energy differences between different protonation states can be determined accurately and enable one to construct the grand canonical partition function. Therefore, the complicated concurrent multisite proton titration process of protein molecules can be satisfactorily simulated. Application of this method to the simulation of the pKa of Glu49, Asp50, and C-terminus of bovine pancreatic trypsin inhibitor shows reasonably good agreement with published experimental work. This method provides an unprecedented vivid picture of how different protonation states change their relative population upon pH titration. We believe that the method will be very useful in deciphering the molecular mechanism of pH-dependent biomolecular processes in terms of a detailed atomistic description.
Persistent Identifierhttp://hdl.handle.net/10722/200499
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHu, Hen_US
dc.contributor.authorShen, Len_US
dc.date.accessioned2014-08-21T06:48:45Z-
dc.date.available2014-08-21T06:48:45Z-
dc.date.issued2014en_US
dc.identifier.citationJournal of Computational Chemistry, 2014, v. 35, p. 1491-1498en_US
dc.identifier.urihttp://hdl.handle.net/10722/200499-
dc.description.abstractThe concurrent proton binding at multiple sites in macromolecules such as proteins and nucleic acids is an important yet challenging problem in biochemistry. We develop an efficient generalized Hamiltonian approach to attack this issue. Based on the previously developed generalized-ensemble methods, an effective potential energy is constructed which combines the contributions of all (relevant) protonation states of the molecule. The effective potential preserves important phase regions of all states and, thus, allows efficient sampling of these regions in one simulation. The need for intermediate states in alchemical free energy simulations is greatly reduced. Free energy differences between different protonation states can be determined accurately and enable one to construct the grand canonical partition function. Therefore, the complicated concurrent multisite proton titration process of protein molecules can be satisfactorily simulated. Application of this method to the simulation of the pKa of Glu49, Asp50, and C-terminus of bovine pancreatic trypsin inhibitor shows reasonably good agreement with published experimental work. This method provides an unprecedented vivid picture of how different protonation states change their relative population upon pH titration. We believe that the method will be very useful in deciphering the molecular mechanism of pH-dependent biomolecular processes in terms of a detailed atomistic description.en_US
dc.languageengen_US
dc.relation.ispartofJournal of Computational Chemistryen_US
dc.titleIn silico concurrent multisite pH titration in proteinsen_US
dc.typeArticleen_US
dc.identifier.emailHu, H: haohu@hku.hken_US
dc.identifier.emailShen, L: shenl@hku.hken_US
dc.identifier.authorityHu, H=rp00707en_US
dc.identifier.doi10.1002/jcc.23645en_US
dc.identifier.pmid24889139-
dc.identifier.hkuros234701en_US
dc.identifier.volume35en_US
dc.identifier.spage1491en_US
dc.identifier.epage1498en_US
dc.identifier.isiWOS:000338119200003-

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