Biology subjects

Arulanandam, C. D.

Publications and source records attributed to Arulanandam, C. D..

4 recordsLinked to original sources

bioRxiv2021

In Silico: Mutagenicity and carcinogenicity prediction of Sugar substitutes

Sugar substitutes are mostly artificial, man-made industrial products used as additives in food and beverages. Most of these substances flow through the digestive tract and food chains to become emerging organic contaminants in various abiotic and biotic environmental media. Here, we predict the mutagenicity and carcinogenicity of commonly used sugar substitutes using the in silico based methods. The simplified molecular-input line-entry system (SMILES) of sugar substitutes were obtained from the PubChem database for the toxicity predictions. Here, sixteen sugar substitutes tested out of these four compounds Glucin (GLU), and 5-nitro-2-propoxyaniline (P-4000), SCL, Ace were predicted as mutagens by using in silico tools such as LAZAR, pKCSM, and Toxtree. Based on the predicted results GLU and P-4000 were predicted as carcinogenic sugar substitutes.

bioengineering↗

bioRxiv2021

Raspberry pi: Assessments of emerging organic chemicals by the predictive in silico methods

Phthalic acid esters (PAEs) and bisphenols are used as plasticizers worldwide. During plastic production, use, deposition, and recycling these compounds contaminate the environment and affect environmental health. In this study, we investigated the toxicity of plasticizers by using in silico tools. None of the test compounds were found to be hERG blockers in multiclass predictions as evaluated by the Pred-hERG 4.1 tool. Among all tested compounds in Pred-Skin 2.0, only BBP, BCP, DBP, diethyl phthalate (DEP), DMP, DNHP, DNPP, DPP, DTDP, DUP, and ODP were non-skin sensitizers. Our results demonstrate that in silico tools provide a reliable, fast, and economic way to explore the toxicological effects of EOCs.

pharmacology and toxicology↗

bioRxiv2021

Repurposing of an Antifungal Drug against Gastrointestinal Stromal Tumors

Drug discovery is an important research area to improve human health. Currently, treatment of gastrointestinal stromal tumors (GISTs) is unsuccessful due to drug-resistance, hence, there is a demand for alternatives. Often, there is limited time available for toxicological assessments and a lack of safer drugs. It is possible to identify new drugs from existing approved drugs possessing another purpose in the clinical lines. In this study, virtual screening of some Food and Drug Administration (FDA-USA) approved and available antifungal and antineoplastic drugs were performed against GISTs based on docking affinity of human platelet-derived growth factor receptor alpha (PDGFRA) with these drugs to identify a suitable PDGFRA inhibitor for saving the time required for toxicity screening. The protein and ligand-binding affinity were investigated for five FDA approved antineoplastic and thirty-six antifungal drugs against PDGFRA using the AutoDock (AD) and AutoDock Vina (ADV) software. Based on docking score and inhibition constant (Ki), Itraconazole was predicted as a better PDGFRA inhibitor among all the computationally tested drugs.

cancer biology↗

bioRxiv2021

In silico approach on drug repurposing - Antimalarial drugs against HIV-1 protease

Acquired Immunodeficiency Syndrome (AIDS), belonging to the retrovirus family is one of the most devastating contagious diseases of this century. Most of the available approved drugs are small molecules which are used in antiretroviral therapy (ART) that trigger the therapeutic response through binding to a targeted protein, HIV-1 protease (PR). This protein represents the most important antiretroviral drug target due to its key role in viral development inhibition. Computational tools using computer-aided technologies have proven useful in accelerating the drug discovery. In this study we evaluated selected FDA (USA) approved antimalarial drugs against HIV-1 protease to find a potential inhibitor candidate for HIV-1 PR (PDB 6DJ1). Binding affinities and Ki inhibition constant of an AutoDock 4.2 study suggest that of all assessed antimalarial agents, Lumefantrine (LUM) would be a most promising HIV-1 PR inhibitor.

bioinformatics↗