Abstract
Computational drug design is increasingly becoming important with new and unforeseen diseases like COVID-19. In this study, we present a new computational de novo drug design and repurposing method and applied it to find plausible drug candidates for the receptor binding domain (RBD) of SARS-CoV-2 (COVID-19). Our study comprises three steps: atom-by-atom generation of new molecules around a receptor, structural similarity mapping to existing approved and investigational drugs, and validation of their binding strengths to the viral spike proteins based on rigorous all-atom, explicit-water well-tempered metadynamics free energy calculations. By choosing the receptor binding domain of the viral spike protein, we showed that some of our new molecules and some of the repurposable drugs have stronger binding to RBD than hACE2. To validate our approach, we also calculated the free energy of hACE2 and RBD, and found it to be in an excellent agreement with experiments. These pool of drugs will allow strategic repurposing against COVID-19 for a particular prevailing conditions.
Keywords: Covid-19; Spike protein; de Novo drug design; docking; free energy; human ACE2; molecular dynamics; repurposing therapeutics; well-tempered metadynamics.
【저자키워드】 COVID-19, docking, molecular dynamics, Spike protein, free energy, de Novo drug design, human ACE2, repurposing therapeutics, well-tempered metadynamics., 【초록키워드】 SARS-CoV-2, spike, drug design, drugs, drug, docking, molecular dynamics, Spike protein, hACE2, free energy, Receptor binding domain, Metadynamics, Free energy calculations, human ACE2, Viral, RBD, receptor, molecular, disease, binding, Spike proteins, similarity, viral spike protein, drug candidate, viral spike proteins, de novo, approach, approved, applied, calculated, conditions, experiments, increasingly, 【제목키워드】 SARS-CoV-2, spike, repurposing, drug, Spike protein, validation,