4.5 Article

Insights from Free-Energy Calculations: Protein Conformational Equilibrium, Driving Forces, and Ligand-Binding Modes

Journal

BIOPHYSICAL JOURNAL
Volume 103, Issue 2, Pages 342-351

Publisher

CELL PRESS
DOI: 10.1016/j.bpj.2012.05.046

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Funding

  1. National Science Foundation [MCB-0919586]
  2. University of California, Riverside
  3. National Institutes of Health [5R44GM075350]
  4. Direct For Biological Sciences [0919586] Funding Source: National Science Foundation
  5. Div Of Molecular and Cellular Bioscience [0919586] Funding Source: National Science Foundation

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Accurate free-energy calculations provide mechanistic insights into molecular recognition and conformational equilibrium. In this work, we performed free-energy calculations to study the thermodynamic properties of different states of molecular systems in their equilibrium basin, and obtained accurate absolute binding free-energy calculations for protein-ligand binding using a newly developed M2 algorithm. We used a range of Asp-Phe-Gly (DFG)-in/out p38 alpha mitogen-activated protein kinase inhibitors as our test cases. We also focused on the flexible DFG motif, which is closely connected to kinase activation and inhibitor binding. Our calculations explain the coexistence of DFG-in and DFG-out states of the loop and reveal different components (e. g., configurational entropy and enthalpy) that stabilize the apo p38 alpha conformations. To study novel ligand-binding modes and the key driving forces behind them, we computed the absolute binding free energies of 30 p38 alpha inhibitors, including analogs with unavailable experimental structures. The calculations revealed multiple stable, complex conformations and changes in p38 alpha and inhibitor conformations, as well as balance in several energetic terms and configurational entropy loss. The results provide relevant physics that can aid in designing inhibitors and understanding protein conformational equilibrium. Our approach is fast for use with proteins that contain flexible regions for structure-based drug design.

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