Shape-based Machine Learning Models for the Potential Novel COVID-19 Protease Inhibitors Assisted by Molecular Dynamics Simulation

Abstract

<jats:sec> <jats:title>Background:</jats:title> <jats:p> The vast geographical expansion of novel coronavirus and an increasing number of COVID-19 affected cases has overwhelmed health and public health services. AI and ML algorithms have extended its major role in tracking the disease patterns, and in identifying possible treatment of disease.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective:</jats:title> <jats:p>To identify potential COVID-19 protease inhibitor through shape-based Machine Learning assisted by Molecular docking and Molecular Dynamics simulation.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods:</jats:title> <jats:p>31 repurposed compounds have been selected targeting coronavirus protease (6LU7) and a machine learning approach was employed to generate shape-based molecules starting from 3D shape to pharmacophoric features of its seed compound. Ligand-Receptor docking was performed with Optimized Potential for Liquid Simulations (OPLS3) algorithms to identify high-affinity compounds from the list of selected candidates for 6LU7. This compound was subjected to Molecular Dynamic Simulations followed by ADMET studies and other analysis.</jats:p> </jats:sec> <jats:sec> <jats:title>Results:</jats:title> <jats:p>Shape-based Machine learning reported Remdesivir, Valrubicin, Aprepitant, and Fulvestrant and a novel therapeutic compound as the best therapeutic agents with the highest affinity for its target protein. Among the best shape-based compounds, the novel theoretical compound was not indexed in any chemical databases (PubChem, Zinc, or ChEMBL). Hence, the novel compound was named 'nCorvEMBS'. Further, toxicity analysis showed nCorv-EMBS to be efficacious that can be qualified as a 6LU7 inhibitor in COVID-19.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion:</jats:title> <jats:p> An effective ACE-II, GAK, AAK1, and protease 3C blockers that can serve a novel therapeutic approach to block the binding and attachment of COVID-19 protein (PDB ID: 6LU7) to the host cell and thus inhibit the infection at AT2 Lung cells. The novel theoretical compound nCorv-EMBS herein proposed stands as a promising inhibitor that can be extended for entering phases of clinical trials for COVID-19 treatment.</jats:p> </jats:sec>

A Systematic Review on the Contribution of Artificial Intelligence in the Development of Medicines for COVID-2019

“…Ligand-Receptor Docking was performed with Optimized Potential for Liquid Simulations (OPLS) algorithms to identify high affinity compounds. The selected drug candidates were subjected to Molecular Dynamic Simulations followed by absorption, distribution, metabolism, and excretion-toxicity in pharmacokinetics (ADMET) studies (AdmetSAR and Swiss ADME software explained various ADMET properties) and other analyses [ 34 ].…”

“…Overall, diverse new repurposed drugs against the treatment of COVID-2019 were suggested in this systematic review through AI techniques [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ], such as: valrubicin, aprepitant, dihydroergotamine, * bivalirudin, eltrombopag, eribulin, fulvestrant, idarubicin, ivermectin, ledipasvir, lifitegrast, nystatin, regorafenib, trypan blue, vitamin E, ruxolitinib, nafcillin, nabumetone, octacosanol, cinametic acid, trabectedin, lauric acid, acorbyl palmitrate, palmidrol, salmeterol, simvastatin, guaifenesin, verteporfin, metergoline, rescinnamine, leuprolide, lusutrombopag, telotristat, fostamatinib, tofacitinib, etoricoxib, ziprasidone, interferon-gamma; cyclosporine, zidovudine, methotrexate, artemisinin, glycyrrhizin acid, quinine, suramin, albuterol, ciprofloxacin, spirapril, lisinopril, and captopril. …”

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

“…More importantly, the most potent compounds presented nanomolar concentration levels for a half-maximal inhibitory. Nayarisseri et al [ 122 ] proposed a shape-based ML method, which generates the 3D shaped pharmacophoric features of the seed compound. Furthermore, molecular docking was performed with optimized potential for liquid simulations (OPLS) algorithms to recognize high affinity compounds targeting M pro .…”

“…They also found a novel compound ‘nCorv-EMBS’, which is not included in public chemical databases (PubChem, ZINC or ChEMBL) so far. The results of toxicity analysis suggested nCorv-EMBS was valuable to further research as the main protease inhibitor in COVID-19 [ 122 ].…”

Repurposing anticancer drugs for the management of COVID-19

“…Based on computational hierarchical virtual screening, recently Wang showed that valrubicin alongside with other drugs, such as lopinavir and carfilzomib inhibits the main protease of SARS-CoV-2 ( Wang, 2020 ). Moreover, another report based on a machine learning simulation has recently shown that valrubicin is a potential COVID-19 protease inhibitor ( Khandelwal et al 2020 ). However, no considerations on the effective doses have been modeled: the clinical use as an agent for systemic administration is not validated, being approved only as a topic solution, and any speculation for the design of clinical trials should account for the adverse safety profile of this chemotherapeutic.…”