Modeling van der Waals interactions between proteins and inorganic surfaces from time-dependent density functional theory calculations

Literature Information

Publication Date 2011-07-25
DOI 10.1039/C1CP20719A
Impact Factor 3.676
Authors

Micael J. T. Oliveira, Miguel A. L. Marques


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Abstract

In this work we show how the ab initio determination of van der Waals coefficients within time-dependent density functional theory can be used to build efficient and accurate atomistic models that describe the long-range interactions of proteins with other proteins and of proteins with semi-conducting surfaces. The model parameters are fitted so that they reproduce the ab initio van der Waals coefficients of amino acids and dipeptides. We then assess the quality of our results by comparing ab initio van der Waals coefficients for larger peptides with the coefficients yielded by the models. The different sets of parameters can be easily incorporated in current empirical force field methods, thus providing an essential ingredient for molecular dynamics simulations of proteins close to surfaces.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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