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Distance Dependent Protein Force Field via Linear Optimization

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Encyclopedia of Optimization

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Introduction

Predicting the structure of a protein from its amino acid sequence is one of the biggest and yet most fundamental problems in computational structural biology. Anfinsen's hypothesis [1] is one of the main approaches used to solve this problem, which says that for a given physiological set of conditions the native structure of a protein corresponds to the global Gibbs free energy minimum. Thus, one needs a force field to calculate the energy of different conformers and pick the one with the lowest energy.

Physics-based force fields consider various types of interactions (for example, van der Waals interactions, hydrogen bonding, electrostatic interactions etc.) occurring at the atomic level of a protein to calculate the energy of a conformer. CHARMM [19], AMBER [5], ECEPP [20], ECEPP/3 [21] and GROMOS [24] are a few examples of the physics-based force fields. On the other hand, knowledge-based force fields use information from databases. Researchers have used the...

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Princeton University, Princeton, USA

    R. Rajgaria, S. R. McAllister & Christodoulos A. Floudas

Authors
  1. R. Rajgaria
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  2. S. R. McAllister
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  3. Christodoulos A. Floudas
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Editor information

Editors and Affiliations

  1. Department of Chemical Engineering, Princeton University, Princeton, NJ, 08544-5263, USA

    Christodoulos A. Floudas

  2. Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, 32611-6595, USA

    Panos M. Pardalos

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© 2008 Springer-Verlag

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Rajgaria, R., McAllister, S.R., Floudas, C.A. (2008). Distance Dependent Protein Force Field via Linear Optimization . In: Floudas, C., Pardalos, P. (eds) Encyclopedia of Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74759-0_135

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