Recent efforts for drug identification from phytochemicals against SARS-CoV-2: Exploration of the chemical space to identify druggable leads

Abstract

Nature, which remains a central drug discovery pool, is always looked upon to find a putative druggable lead. The natural products and phytochemical derived from plants are essential during a global health crisis. This class represents one of the most practical and promising approaches to decrease pandemic's intensity owing to their therapeutic potential. The present manuscript is therefore kept forth to give the researchers updated information on undergoing research in allied areas of natural product-based drug discovery, particularly for Covid-19 disease. The study briefly shreds evidence from in vitro and in silico researches done so far to find a lead molecule against Covid-19. Following this, we exhaustively explored the concept of chemical space and molecular similarity parameters for the drug discovery about the lead(s) generated from in silico -based studies. The comparison was drawn using FDA-approved anti-infective agents during 2015–2020 using key descriptors to evaluate druglike properties. The outcomes of results were further corroborated using Molecular Dynamics studies which suggested the outcomes in alignment with chemical space ranking. In a nutshell, current research work aims to provide a holistic strategic approach to drug design, keeping in view the identified phytochemicals against Covid-19.

Phytochemicals from Leucas zeylanica Targeting Main Protease of SARS-CoV-2: Chemical Profiles, Molecular Docking, and Molecular Dynamics Simulations

“…Our analysis indicated that most of the identified phytocompounds derived from the aerial parts of L. zeylanica followed Lipinski’s RO5. Furthermore, it was reported that, the antiviral drugs approved by the FDA in the last five years involve a molecular weight of 513.97, hydrogen bond donors of 2.95, and hydrogen bond acceptors of 9.13 [ 23 ]. The targeted natural compounds are also within the reported criteria, indicating that these compounds may be evaluated as potential drug molecules.…”

“…In silico studies were conducted on a broad spectrum for a plethora of medicinal plants and a huge number of compounds were screened. This not only helped indicate the potentiality of natural plant compounds but also reduced the number of tedious and costly wet-laboratory experiments [ 23 ]. Therefore, in our current study, we endeavored to assess the roles of phytoconstituents identified from Leucas zeylanica, a medicinal plant belonging to the Lamiaceae family, in the management of COVID-19 infection by employing computational biology approaches.…”

A review on computational approaches that support the researches on traditional Chinese medicines (TCM) against COVID-19

“…This method utilizes the neighborhood behavior principle, which suggests that close-proximity compounds have similar chemical properties, so chemical space maps can relate to structural-activity relationship (SAR) studies. Joshi et al conceptualized the key druggable parameters of chemical space and analyzed molecular similarity on already identified phytochemicals in COVID-19 ( Joshi et al, 2021 ). Chemical space exploration using key parameters including MW, TPSA, number of rotational bonds (nROTB), hydrogen bond donors (nHBDon) and acceptors (nHBAcc), and partition coefficient (AlogP) using Platform for Unified Molecular Analysis (PUMA) online server ( Gonzalez-Medina and Medina-Franco, 2017 ).…”

A concise review of mushrooms antiviral and immunomodulatory properties that may combat against COVID-19

“…Some popular plants, including cinnamon, pepper, olive, black nightshade, hawthorn, passion fruit, and grapes, were shown to have ACE2 inhibitory action and have been intensively explored with in silico, pre-clinical, and clinical models. Alkaloids, flavonols, flavonones, terpenes, limonoids, lignans, terpenoids, tannins, phenolic acids, and fatty acids are all examples of ACE2 inhibitors found in plant extracts ( da Silva Antonio et al, 2020 ; Cheke et al, 2021 ; Abubakar et al, 2021 ; Joshi et al, 2021 ).…”