Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints

BMC Bioinformatics. 2017 Jul 18;18(1):343. doi: 10.1186/s12859-017-1750-5.

Abstract

Background: In structure-based drug design, binding affinity prediction remains as a challenging goal for current scoring functions. Development of target-biased scoring functions provides a new possibility for tackling this problem, but this approach is also associated with certain technical difficulties. We previously reported the Knowledge-Guided Scoring (KGS) method as an alternative approach (BMC Bioinformatics, 2010, 11, 193-208). The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding data of an appropriate reference complex, so the error in binding affinity prediction can be reduced effectively.

Results: In this study, we have developed an upgraded version, i.e. KGS2, by employing 3D protein-ligand interaction fingerprints in reference selection. KGS2 was evaluated in combination with four scoring functions (X-Score, ChemPLP, ASP, and GoldScore) on five drug targets (HIV-1 protease, carbonic anhydrase 2, beta-secretase 1, beta-trypsin, and checkpoint kinase 1). In the in situ scoring test, considerable improvements were observed in most cases after application of KGS2. Besides, the performance of KGS2 was always better than KGS in all cases. In the more challenging molecular docking test, application of KGS2 also led to improved structure-activity relationship in some cases.

Conclusions: KGS2 can be applied as a convenient "add-on" to current scoring functions without the need to re-engineer them, and its application is not limited to certain target proteins as customized scoring functions. As an interpolation method, its accuracy in principle can be improved further with the increasing knowledge of protein-ligand complex structures and binding affinity data. We expect that KGS2 will become a practical tool for enhancing the performance of current scoring functions in binding affinity prediction. The KGS2 software is available upon contacting the authors.

Keywords: Interaction fingerprints; Protein-ligand binding affinity; Scoring function; Structure-based drug design.

MeSH terms

  • Amyloid Precursor Protein Secretases / chemistry
  • Amyloid Precursor Protein Secretases / metabolism
  • Carbonic Anhydrase II / chemistry
  • Carbonic Anhydrase II / metabolism
  • Checkpoint Kinase 1 / chemistry
  • Checkpoint Kinase 1 / metabolism
  • Computational Biology / methods*
  • HIV Protease / chemistry
  • HIV Protease / metabolism
  • Humans
  • Ligands*
  • Molecular Docking Simulation
  • Pharmaceutical Preparations / chemistry
  • Pharmaceutical Preparations / metabolism
  • Protein Binding
  • Proteins / chemistry*
  • Proteins / metabolism*
  • Software

Substances

  • Ligands
  • Pharmaceutical Preparations
  • Proteins
  • Checkpoint Kinase 1
  • Amyloid Precursor Protein Secretases
  • HIV Protease
  • p16 protease, Human immunodeficiency virus 1
  • Carbonic Anhydrase II