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. 2008 Aug;48(8):1656-62.
doi: 10.1021/ci8001167. Epub 2008 Aug 2.

MedusaScore: an accurate force field-based scoring function for virtual drug screening

Shuangye Yin  1 , Lada Biedermannova, Jiri Vondrasek, Nikolay V Dokholyan
Affiliations

MedusaScore: an accurate force field-based scoring function for virtual drug screening

Shuangye Yin et al. J Chem Inf Model. 2008 Aug.

Abstract

Virtual screening is becoming an important tool for drug discovery. However, the application of virtual screening has been limited by the lack of accurate scoring functions. Here, we present a novel scoring function, MedusaScore, for evaluating protein-ligand binding. MedusaScore is based on models of physical interactions that include van der Waals, solvation, and hydrogen bonding energies. To ensure the best transferability of the scoring function, we do not use any protein-ligand experimental data for parameter training. We then test the MedusaScore for docking decoy recognition and binding affinity prediction and find superior performance compared to other widely used scoring functions. Statistical analysis indicates that one source of inaccuracy of MedusaScore may arise from the unaccounted entropic loss upon ligand binding, which suggests avenues of approach for further MedusaScore improvement.

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Figures

Figure 1
Figure 1. An example of docking decoy recognition using MedusaScore
The native docking pose (ball-and-stick) for a inhibitor against thermolysin protein (PDB ID: 1tlp) is correctly recognized using MedusaScore from the 100 docking decoys (gray lines) generate by Wang et al. using Autodock.
Figure 2
Figure 2. Scatter plot of the MedusaScore predictions (without VDWR) vs. the experimental dissociation constant pKd for the refined set
The Pearson correlation coefficient is 0.61. The solid line corresponds to a linear regression fit (y = 4.18x - 3.59).
Figure 3
Figure 3. Scatter plot of the MedusaScore vs. the experimental dissociation constant pKd for the core set, categorized based on the number of heavy atoms in the ligand (n)
The prediction accuracy is higher (r = 0.63) for small ligands, than for medium and large sized ligands.
Figure 4
Figure 4. Scatter plot of the MedusaScore vs. the experimental dissociation constant pKd for the core set, categorized based on the number of ligand heavy atoms in contact with protein (nc)
We define a contact when a ligand heavy atom is within 3.5 Å of any protein heavy atom. The prediction accuracy is higher (r = 0.74) for ligands with fewer contacts with the proteins than for those with more extensive contact.
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