Organometallic compounds are increasingly used as molecular scaffolds in drug development projects; their structural and electronic properties offering novel opportunities in protein-ligand complementarities. Interestingly, while protein-ligand dockings have long become a spearhead in computer assisted drug design, no benchmarking nor optimization have been done for their use with organometallic compounds. Pursuing our efforts to model metal mediated recognition processes, we herein present a systematic study of the capabilities of the program GOLD to predict the interactions of protein with organometallic compounds. The study focuses on inert systems for which no alteration of the first coordination sphere of the metal occurs upon binding. Several scaffolds are used as test systems with different docking schemes and scoring functions. We conclude that ChemScore is the most robust scoring function with ASP and ChemPLP providing with good results too and GoldScore slightly underperforming. This study shows that current state-of-the-art protein-ligand docking techniques are reliable for the docking of inert organometallic compounds binding to protein. © 2013 Wiley Periodicals, Inc. Organometallic compounds are increasingly used as molecular scaffolds in drug development projects. In this study, the predictiveness of protein-ligand docking programs for the binding of inert organometallic scaffolds with protein receptors is investigated. Using the software GOLD as an illustrative case, scoring functions, preprocessing calculations, and flexibility schemes are tested. The work shows that actual methodologies are efficient for such systems without requiring major improvements. Copyright © 2013 Wiley Periodicals, Inc.
|Journal||Journal of Computational Chemistry|
|Publication status||Published - 30 Jan 2014|
- computational bioinorganics
- drug design
- kinase inhibition
- protein-ligand dockings