Virtual screening using molecular simulations

Tianyi Yang, Johnny C. Wu, Chunli Yan, Yuanfeng Wang, Ray Luo, Michael B. Gonzales, Kevin N. Dalby, Pengyu Ren

Research output: Contribution to journalArticle

86 Citations (Scopus)

Abstract

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery.

Original languageEnglish
Pages (from-to)1940-1951
Number of pages12
JournalProteins: Structure, Function and Bioinformatics
Volume79
Issue number6
DOIs
Publication statusPublished - Jun 1 2011
Externally publishedYes

Fingerprint

Mechanics
Free energy
Screening
Molecular mechanics
Glucosidases
Ligands
Blood Coagulation Factors
Cyclin-Dependent Kinases
Urokinase-Type Plasminogen Activator
Entropy
Drug Discovery
Protein Binding
Thrombin
Trypsin
Rigid rotors
Proteins
Phosphotransferases
Binding energy
Permittivity
Throughput

Keywords

  • Alchemical free energy calculation
  • Configurational entropy
  • Dielectric constant
  • MM-GBSA
  • MM-PBSA
  • Molecular mechanics

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology

Cite this

Yang, T., Wu, J. C., Yan, C., Wang, Y., Luo, R., Gonzales, M. B., ... Ren, P. (2011). Virtual screening using molecular simulations. Proteins: Structure, Function and Bioinformatics, 79(6), 1940-1951. https://doi.org/10.1002/prot.23018

Virtual screening using molecular simulations. / Yang, Tianyi; Wu, Johnny C.; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B.; Dalby, Kevin N.; Ren, Pengyu.

In: Proteins: Structure, Function and Bioinformatics, Vol. 79, No. 6, 01.06.2011, p. 1940-1951.

Research output: Contribution to journalArticle

Yang, T, Wu, JC, Yan, C, Wang, Y, Luo, R, Gonzales, MB, Dalby, KN & Ren, P 2011, 'Virtual screening using molecular simulations', Proteins: Structure, Function and Bioinformatics, vol. 79, no. 6, pp. 1940-1951. https://doi.org/10.1002/prot.23018
Yang, Tianyi ; Wu, Johnny C. ; Yan, Chunli ; Wang, Yuanfeng ; Luo, Ray ; Gonzales, Michael B. ; Dalby, Kevin N. ; Ren, Pengyu. / Virtual screening using molecular simulations. In: Proteins: Structure, Function and Bioinformatics. 2011 ; Vol. 79, No. 6. pp. 1940-1951.
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