𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Protonation free energy levels in complex molecular systems

✍ Scribed by Jan M. Antosiewicz


Publisher
Wiley (John Wiley & Sons)
Year
2008
Tongue
English
Weight
210 KB
Volume
89
Category
Article
ISSN
0006-3525

No coin nor oath required. For personal study only.

✦ Synopsis


Abstract

All proteins, nucleic acids, and other biomolecules contain residues capable of exchanging protons with their environment. These proton transfer phenomena lead to pH sensitivity of many molecular processes underlying biological phenomena. In the course of biological evolution, Nature has invented some mechanisms to use pH gradients to regulate biomolecular processes inside cells or in interstitial fluids. Therefore, an ability to model protonation equilibria in molecular systems accurately would be of enormous value for our understanding of biological processes and for possible rational influence on them, like in developing pH dependent drugs to treat particular diseases. This work presents a derivation, by thermodynamic and statistical mechanical methods, of an expression for the free energy of a complex molecular system at arbitrary ionization state of its titratable residues. This constitutes one of the elements of modeling protonation equilibria. Starting from a consideration of a simple acid–base equilibrium of a model compound with a single tritratable group, we arrive at an expression which is of general validity for complex systems. The only approximation used in this derivation is the postulating that the interaction energy between any pair of titratable sites does not depend on the protonation states of all the remaining ionizable groups. © 2007 Wiley Periodicals, Inc. Biopolymers 89: 262–269, 2008.

This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at [email protected]


📜 SIMILAR VOLUMES


Free energy of proton binding in protein
✍ Douglas Poland 📂 Article 📅 2003 🏛 Wiley (John Wiley & Sons) 🌐 English ⚖ 214 KB

## Abstract In this article we use literature data on the titration of denatured ribonuclease to test the accuracy of proton‐binding distributions obtained using our recent approach employing moments. We find that using only the local slope of the titration curve at a small number of points (five,

ORAC: A molecular dynamics simulation pr
✍ Simone Marsili; Giorgio Federico Signorini; Riccardo Chelli; Massimo Marchi; Pie 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 165 KB

## Abstract We present the new release of the ORAC engine (Procacci et al., Comput Chem 1997, **18**, 1834), a FORTRAN suite to simulate complex biosystems at the atomistic level. The previous release of the ORAC code included multiple time steps integration, smooth particle mesh Ewald method, cons

Proton transfer in phenol–amine complexe
✍ Shinji Aono; Shigeki Kato 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 396 KB

## Abstract Free energy profiles for the proton transfer reactions in hydrogen‐bonded complex of phenol with trimethylamine in methyl chloride solvent are studied with the reference interaction site model self‐consistent field method. The reactions in both the electronic ground and excited states a

A scalable parallel Monte Carlo method f
✍ Malek O. Khan; Gareth Kennedy; Derek Y. C. Chan 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 234 KB

## Abstract We present a method of parallelizing flat histogram Monte Carlo simulations, which give the free energy of a molecular system as an output. In the serial version, a constant probability distribution, as a function of any system parameter, is calculated by updating an external potential

Efficient use of nonequilibrium measurem
✍ F. Marty Ytreberg; Daniel M. Zuckerman 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 802 KB

## Abstract A promising method for calculating free energy differences __ΔF__ is to generate nonequilibrium data via “fast‐growth” simulations or by experiments—and then use Jarzynski's equality. However, a difficulty with using Jarzynski's equality is that __ΔF__ estimates converge very slowly and