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Develop and test a solvent accessible surface area-based model in conformational entropy calculations.

Junmei Wang1, Tingjun Hou

  • 1Department of Biochemistry, The University of Texas Southwestern Medical Center , 5323 Harry Hines Blvd., Dallas, Texas 75390, USA. junmei.wang@utsouthwestern.edu

Journal of Chemical Information and Modeling
|April 14, 2012
PubMed
Summary
This summary is machine-generated.

A new weighted solvent accessible surface area (WSAS) method efficiently estimates conformational entropy for molecular mechanics Poisson-Boltzmann/generalized Born surface area (MM-PB/GBSA) calculations. This fast approach achieves comparable accuracy to normal-mode analysis (NMA), accelerating drug design.

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Area of Science:

  • Computational Chemistry
  • Drug Design
  • Molecular Modeling

Background:

  • Accurate calculation of protein-ligand binding free energies is crucial for modern drug design.
  • MM-PBSA and MM-GBSA methods are popular for binding free energy calculations.
  • Conformational entropy, often computed via computationally intensive normal-mode analysis (NMA), is essential for absolute binding free energy calculations in MM-PB/GBSA methods, posing a significant bottleneck.

Purpose of the Study:

  • To develop a computationally efficient approach for estimating molecular conformational entropy.
  • To replace the bottleneck of normal-mode analysis (NMA) in MM-PB/GBSA calculations with a faster method.
  • To evaluate the performance of the new method in predicting binding free energies and conformational entropy changes.

Main Methods:

  • Developed a novel method estimating conformational entropy based on solvent accessible surface area (SAS) and buried SAS (BSAS) calculations.
  • The weighted solvent accessible surface area (WSAS) model incorporates atomic contributions, weighted by surface area type and a general parameter k.
  • Parametrized the WSAS model using small molecules with known conformational entropies and validated it against NMA across various molecular systems and binding energy calculations.

Main Results:

  • The WSAS method demonstrated good correlations with NMA for conformational entropy (TΔS) in protein/nucleic acid systems (R²=0.56) and upon binding (R²=0.67).
  • High correlations were also observed for decoy sets (mean R²=0.73) and binding free energy predictions (mean R² ranging from 0.40 to 0.51).
  • WSAS-based scoring functions achieved prediction performance comparable to NMA-based functions, with mean errors around 1.2-1.4 kcal/mol, notably without requiring structural minimization.

Conclusions:

  • The developed WSAS method provides a computationally efficient and accurate alternative to NMA for estimating conformational entropy in MM-PB/GBSA calculations.
  • WSAS-based scoring functions show comparable predictive power to NMA-based methods for binding free energy calculations.
  • The WSAS approach is highly suitable for applications requiring high throughput, such as high throughput screening, molecular docking, and rational protein design, due to its computational efficiency.