Computer-Aided Approaches to De Novo Design of drug candidates targeting the SARS-CoV-2 Spike protein bound to angiotensin converting enzyme 2 (ACE2)

24 March 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

In this study a computer-aided approach to de novo design of chemical entities with drug-like properties against the SARS-CoV-2 Spike protein bound to ACE2 is presented. A structure-based de novo drug design tool LIGANN was used to produce complementary ligand shapes to the SARS-CoV-2 Spike protein (6M0J). The obtained ligand structures - potential drug candidates – were optimized and virtually screened. Hit ligands were considered all that showed initial binding energy scores ≤ -9.0 kcal.mol-1 for the protein. These compounds were tested for drug-likeness (Lipinski’s rule and BOILED Permeation Predictive Model). All satisfying the criteria were re-optimized (geometry & frequencies) at the HF-3c33 level of theory and virtually screened against 6M0J. Molecular dynamics (MD) simulations were used to assess the structural stability of selected 6M0J/novel compound complexes. Synthetic pathways for selected compounds from commercially available starting materials are proposed.

Keywords

drug design
computer assisted design
SARS-CoV-2 Spike protein
SARS-CoV-2
drug-likeness
virtual screening
In silico screening
Molecular docking computations
computatinal drug screening
Molecular Dynamic Simulations
novel inhibitors
de novo design

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.