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Proposing Institution

LRZ
Project Manager

Dr. Nils Otto vor dem Gentschen Felde
Boltzmannstraße 1
85748 Garching
Abstract
It project is to develop high fidelity, computationally based, predictive mechanistic models of biomedical systems which can be applied in support of drug discovery and personalised medicine utilizing today’s top-level computational infrastructure. This proposal focuses on molecular medicine, for which we want to investigate its robust application within a computing infrastructure of the highest performance. Therefore, this project will not only advance the particular fields in focus, but will lead to improved and novel insights for the operation of HPC machines at unprecedented levels, thereby serving as a lighthouse model for other domains.The theme of the project is gaining insight into the binding properties of proteins which represent key classes of drug target in important disease cases. We will focus on two distinct target classes; G-protein-coupled receptors (GPCRs) and immunological complexes, including peptide-major histocompatibility complex (pMHC) and T-cell receptor-pMHC (TCR-pMHC) studies. The computational objective is to quantitatively predict the binding affinities and residence times of ligands to GPCRs, peptides to MHC, pMHCs to TCR, together with the residence time of peptide in MHC. Our investigations will share a common methodology, namely application of ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) for binding affinity calculations, as well as new approaches to enhance sampling and for estimation of off-rates for the first time, in an extension of the BAC workflow environment.

Impressum, Conny Wendler