Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0

J Comput Aided Mol Des. 2019 Dec;33(12):1083-1094. doi: 10.1007/s10822-019-00222-y. Epub 2019 Sep 10.


Computational prediction of protein-ligand interactions is a useful approach that aids the drug discovery process. Two major tasks of computational approaches are to predict the docking pose of a compound in a known binding pocket and to rank compounds in a library according to their predicted binding affinities. There are many computational tools developed in the past decades both in academia and industry. To objectively assess the performance of existing tools, the community has held a blind assessment of computational predictions, the Drug Design Data Resource Grand Challenge. This round, Grand Challenge 4 (GC4), focused on two targets, protein beta-secretase 1 (BACE-1) and cathepsin S (CatS). We participated in GC4 in both BACE-1 and CatS challenges using our molecular surface-based virtual screening method, PL-PatchSurfer2.0. A unique feature of PL-PatchSurfer2.0 is that it uses the three-dimensional Zernike descriptor, a mathematical moment-based shape descriptor, to quantify local shape complementarity between a ligand and a receptor, which properly incorporates molecular flexibility and provides stable affinity assessment for a bound ligand-receptor complex. Since PL-PatchSurfer2.0 does not explicitly build a bound pose of a ligand, we used an external docking program, such as AutoDock Vina, to provide an ensemble of poses, which were then evaluated by PL-PatchSurfer2.0. Here, we provide an overview of our method and report the performance in GC4.

Keywords: BACE-1; CatS; D3R Grand Challenge; PL-PatchSurfer; Protein–ligand interaction; Virtual screening.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Amyloid Precursor Protein Secretases / chemistry*
  • Amyloid Precursor Protein Secretases / genetics
  • Aspartic Acid Endopeptidases / chemistry*
  • Aspartic Acid Endopeptidases / genetics
  • Binding Sites / genetics
  • Computer-Aided Design
  • Crystallography, X-Ray
  • Drug Design
  • Drug Discovery
  • Intracellular Signaling Peptides and Proteins / chemistry*
  • Intracellular Signaling Peptides and Proteins / genetics
  • Ligands
  • Molecular Docking Simulation*
  • Nuclear Proteins / chemistry*
  • Nuclear Proteins / genetics
  • Protein Binding / genetics*
  • Protein Conformation
  • Proteins / chemistry
  • Proteins / genetics
  • Structure-Activity Relationship
  • Thermodynamics


  • Intracellular Signaling Peptides and Proteins
  • Ligands
  • Nuclear Proteins
  • PIMREG protein, human
  • Proteins
  • Amyloid Precursor Protein Secretases
  • Aspartic Acid Endopeptidases
  • BACE1 protein, human