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Quantum descriptors for biological macromolecules from linear-scaling electronic structure methods.

Jana Khandogin·Darrin M York
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Abstract

The characterization of electrostatic and chemical properties at the surface of biological macromolecules is of interest in elucidating the fundamental biological structure-function relationships as well as in problems of rational drug design. This paper presents a set of macromolecular quantum descriptors for the characterization of biological macromolecules in solution that can be obtained with modest computational cost from linear-scaling semi-empirical quantum/solvation methods. The descriptors discussed include: solvent-polarized electrostatic surface potential maps, equilibrated atomic charges, Fukui reactivity indices, approximate local hardness maps, and relative proton potentials. These properties are applied to study the conformational dependence of the electrostatic surface potential of the solvated phosphate-binding protein mutant (T141D), the regioselectivity of the zinc finger domains of HIV-1 nucleocapsid (NC) protein, and the order of pKa values of acidic residues in turkey ovomucoid third domain (OMTKY3) and of the zinc-binding residues in the carboxyl terminal zinc finger of NC. In all cases, insight beyond that obtainable from purely classical models is gained and can be used to rationalize the experimental observations. The macromolecular quantum descriptors presented here greatly extend the arsenal of tools for macromolecular characterization and offer promise in applications to modern structure-based drug design.

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Computational BiologyModels, MolecularMultiprotein ComplexesNucleocapsid ProteinsPeptidesPhosphate-Binding ProteinsProtein Structure, QuaternaryProtein Structure, TertiaryProtonsQuantum TheorySolutionsStatic ElectricityStructure-Activity RelationshipTrypsin Inhibitor, Kazal PancreaticJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, P.H.S.

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Jana Khandogin, Darrin M York. 2004-09-01. Quantum descriptors for biological macromolecules from linear-scaling electronic structure methods.. https://doi.org/10.1002/prot.20171

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