Can an optimization/scoring procedure in ligand-protein docking be employed to probe drug-resistant mutations in proteins?
A simple ligand-protein structural optimization and binding evaluation procedure has been routinely used in high-speed ligand-protein docking studies. In this work, we examine whether such an optimization/scoring procedure is useful in indicating possible drug-resistant mutations in proteins. Crystal structures of three wild-type enzymes (HIV-1 protease, HIV-1 reverse transcriptase, and Mycobacterium tuberculosis H37Rv enoyl-ACP reductase) complexed to a variety of inhibitors are studied. Mutations are introduced into these structures by using the molecular modeling software, SYBYL. Structural optimization and scoring of a mutant complex is conducted by a procedure similar to that used in a recent docking study (Wang et al., 1999). The computed results are compared with observed drug resistance data and the profile of nonresistant mutations. Most mutations studied show an energy change in the same direction as those indicated by observed resistance data. 50% of the polar to polar or nonpolar to nonpolar mutations are found to correlate qualitatively with observed drug resistance data. Van der Waals interactions account for most of these changes, which is in agreement with conclusions from structural studies. Substantially larger deviations are found between computed results and observed data for most polar to nonpolar or nonpolar to polar mutations, which result from deficiency in modelling and scoring ligand-protein interactions in our procedure. Our results suggest that an optimization/docking scoring procedure is useful for qualitatively probing polar to polar or nonpolar to nonpolar resistant mutations in addition to its application in screening active compounds. More accurate description of ligand-protein interactions and the use of methods such as free energy perturbation and Poisson-Boltzmann may be needed to further improve the quality of prediction.
Chen
Y Z
YZ
Department of Computational Science, National University of Singapore, Lower Kent Ridge Road, Singapore 119260. yzchen@cz3.nus.edu.sg
Gu
X L
XL
Cao
Z W
ZW
D003198:Computer Simulation; D018360:Crystallography, X-Ray; D024881:Drug Resistance, Bacterial / Q000235:genetics*; D024882:Drug Resistance, Viral / Q000235:genetics*; D004735:Energy Transfer; D050753:Enoyl-(Acyl-Carrier-Protein) Reductase (NADH); D016333:HIV Protease / Q000737:chemistry* / Q000235:genetics; D017320:HIV Protease Inhibitors / Q000737:chemistry*; D054303:HIV Reverse Transcriptase / Q000737:chemistry* / Q000235:genetics; D015497:HIV-1 / Q000201:enzymology; D006801:Humans; D057927:Hydrophobic and Hydrophilic Interactions; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D016296:Mutagenesis; D009169:Mycobacterium tuberculosis / Q000201:enzymology; D010088:Oxidoreductases / Q000737:chemistry* / Q000235:genetics; D011487:Protein Conformation; D018894:Reverse Transcriptase Inhibitors / Q000737:chemistry*
D017320:HIV Protease Inhibitors; D008024:Ligands; D018894:Reverse Transcriptase Inhibitors; D010088:Oxidoreductases; D050753:Enoyl-(Acyl-Carrier-Protein) Reductase (NADH); D054303:HIV Reverse Transcriptase; D016333:HIV Protease