How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms

Current Opinion in Structural Biology, vol. 86, pp. 102814

Abstract

Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. This has been favored by the exponential growth of computer power and the proliferation of powerful data-driven methods. Here, we briefly review recent advances and applications, and give our perspective on the impact that QM/MM and free-energy methods combined with machine learning-aided algorithms can have on drug design.

Authors 2

1. Giulia Rossetti Aachen Department of Neurology

   RWTH Aachen University · Universitätsklinikum Aachen · Forschungszentrum Jülich · Jülich Supercomputing Centre

   Affiliation as printed

   Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany; Department of Neurology, University Hospital Aachen (UKA), RWTH Aachen University, Aachen, Germany; Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich 52428, Germany. Electronic address: https://twitter.com/G_Rossetti_

   Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany

   Department of Neurology, University Hospital Aachen (UKA), RWTH Aachen University, Aachen, Germany

   Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich 52428, Germany

2. Davide Mandelli corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany. Electronic address: d.mandelli@fz-juelich.de

   Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany