Recent Advances in Free Energy Calculations with a Combination of Molecular Mechanics and Continuum Models

By Junmei Wang, Tingjun Hou, Xiaojie Xu. 2006

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Recently, the combination of state-of-the-art molecular mechanical force fields with continuum solvation models enables us to make relatively accurate predictions of both structures and free energies for macromolecules from molecular dynamics trajectories. The first part of this review is focused on the history and basic theory of free energy calculations based on physically effective energy functions. The second part illustrates the applications of free energy calculations on many biological systems, including proteins, DNA, RNA, protein-ligand, protein-protein, protein-nucleic acid complexes, etc. Finally, the prospective and possible strategies to improve the techniques of MM-PBSA and MM-GBSA is discussed. Molecular mechanics (MM), though its theoretical background is not as solid as quantum mechanics (QM), has broad applications in studying biological systems for its simplicity and efficiency. The harmonic function form (Equation 1), which is widely-used in many popular molecular mechanical force fields, describes molecular energy using bond stretching, bond angle bending, torsional angle twisting as well as non-bonded electrostatic and van der Waals interactions. It is well-known that most biological procedures take place in aqueous solutions. Therefore, solvation effect cannot be neglected in studying the structures and interactions of biological systems. There are two basic ways to take the solvent effect into account: with either an explicit water model or an implicit water model. For the first approach, a biological system is usually immersed in a periodical water box; the second approach does not apply water molecules explicitly. Instead, solvation energy and force due to the solvent effect are calculated using some formulas or by solving some equations numerically or analytically. The widely used implicit solvation models include the generalized Born surface area (GBSA) (1-5) and the Poisson-Bolzmann surface area (PBSA) (6-15).

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ad4a6d2767f4d84b777f01131de1ba993c7d26dd

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In Computational Theory and Mathematics

  1. Samuel Genheden
  2. Ulf Ryde
  3. Junmei Wang

In Molecular Biology

  1. Samuel Genheden
  2. Ulf Ryde
  3. Junmei Wang

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