Protein-ligand interactions are crucial for many important biological processes and thus the selective inhibition of disease relevant protein interactions is one of the major strategies for drug design in pharmaceutical industry. In this context computer-based methods are routinely used to screen large compound libraries for the identification of potential drug candidates. Thus many sampling and scoring methods have been developed for this purpose over the last two decades, which perform very well for classical drug design applications, namely predicting the binding of non-covalently bound ligands to specific target proteins [1-4]. Nevertheless, these approaches experience considerable limitations for e.g the correct prediction of covalently-bound ligands or ligands bound to metal-containing binding sites as these methods are based on classical mechanics-based models. On the other hand, as CPU-time requirements have become less critical during the last years, the use of QM and especially QM/MM methods has become feasible in computer-aided drug design [6], which can lead to improvements in the accuracy of the calculations. We will present several case studies, which show how QM/MM methods can be efficiently used for drug design and how the use of QM-based approaches can improve the accuracy of protein-ligand-binding predictions considerably. References: [1] Song SM, Lim SJ, Tong JC, Brief. Bioinform. 10(5) (2009) 579. [2] Huang X, Grinter SZ, Zou X, Phys. Chem. Chem. Phys. 12(40) (2012) 12899. [3] Hartmann C, Antes I, and Lengauer T, Proteins 74(3) (2009) 712. [4] Antes I, Proteins 78(5) (2010) 1084. [5] Xu M, Lill MA, Drug. Discov. Today. Technol. 10(3) (2013) e411.

Prediction of protein-ligand binding using QM/MM-based methods

251st National Meeting (2016)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.