Protein–ligand interactions from a quantum fragmentation perspective: The case of the SARS-CoV-2 main protease interacting with α-ketoamide inhibitors

Abstract

We present a hybrid, multi-method, computational scheme for protein/ligand systems well suited to be used on modern and forthcoming massively parallel computing systems. The scheme relies on a multi-scale polarizable molecular modeling, approach to perform molecular dynamics simulations, and on an efficient Density Functional Theory (DFT) linear scaling method to post-process simulation snapshots. We use this scheme to investigate recent α-ketoamide inhibitors targeting the main protease of the SARS-CoV-2 virus. We assessed the reliability and the coherence of the hybrid scheme, in particular, by checking the ability of MM and DFT to reproduce results from high-end ab initio computations regarding such inhibitors. The DFT approach enables an a posteriori fragmentation of the system and an investigation into the strength of interaction among identified fragment pairs. We show the necessity of accounting for a large set of plausible protease/inhibitor conformations to generate reliable interaction data. Finally, we point out ways to further improve α-ketoamide inhibitors to more strongly interact with particular protease domains neighboring the active site.

Ab initio guided atomistic modelling of nanomaterials on exascale high-performance computing platforms

“…Ligand interactions with nanoparticles can be explored from various configurations, guiding experimental efforts for targeted synthesis. In addition to using complexity reduction frameworks such as QM/MM, linear-scaling DFT can be used to assess the accuracy of MD simulations on-the-fly, targeting systems with thousands of atoms and comparing them with ab initio calculations [49]. This way, materials' (macroscopic) functional properties could be determined by their surface morphology and interatomic bonding.…”

Roadmap on electronic structure codes in the exascale era

“…In this study, MD snapshots were post-processed using BigDFT calculations on systems made up of over 7000 atoms. We have also proposed a sequential multi-scale molecular modeling/quantum mechanical, mMM/QM [19], simulation approach, wherein BigDFT was used to support the accuracy of MD simulations involving over 20 000 atoms, as well as give new insights. For both these studies, we developed representations of the simulation results as interaction graphs showing the details and magnitudes of the interactions (at the residue scale) responsible for the stability of the studied complexes (see figure 3).…”