Biology subjects

R, P.

Publications and source records attributed to R, P..

5 recordsLinked to original sources

bioRxiv2021

M-CAMP™: A cloud-based web platform with a novel approach for species-level classification of 16S rRNA microbiome sequences

The M-CAMP (Microbiome Computational Analysis for Multiomic Profiling) Cloud Platform was designed to provide users with an easy-to-use web interface to access best in class microbiome analysis tools. This interface allows bench scientists to conduct bioinformatic analysis on their samples and then download publication-ready graphics and reports. The core pipeline of the platform is the 16S-seq taxonomic classification algorithm which provides species-level classification of Illumina 16s sequencing. This algorithm uses a novel approach combining alignment and kmer based taxonomic classification methodologies to produce a highly accurate and comprehensive profile. Additionally, a comprehensive proprietary database combining reference sequences from multiple sources was curated and contains 18056 unique V3-V4 sequences covering 11527 species. The M-CAMP 16S taxonomic classification algorithm was validated on 52 sequencing samples from both public and in-house standard sample mixtures with known fractions. Compared to current popular public classification algorithms, our classification algorithm provides the most accurate species-level classification of 16S rRNA sequencing data.

bioinformatics↗

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↗

bioRxiv2020

Rational design of protein-specific folding modifiers

Protein folding can go wrong in vivo and in vitro, with significant consequences for the living cell and the pharmaceutical industry, respectively. Here we propose a general design principle for constructing small peptide-based protein-specific folding modifiers. We construct a xenonucleus, which is a pre-folded peptide that resembles the folding nucleus of a protein, and demonstrate its activity on the folding of ubiquitin. Using stopped-flow kinetics, NMR spectroscopy, Forster Resonance Energy transfer, single-molecule force measurements, and molecular dynamics simulations, we show that the ubiquitin xenonucleus can act as an effective decoy for the native folding nucleus. It can make the refolding faster by 33 {+/-} 5% at 3 M GdnHCl. In principle, our approach provides a general method for constructing specific, genetically encodable, folding modifiers for any protein which has a well-defined contiguous folding nucleus.

biophysics↗