Design and combinatorial library generation of 1H 1,4 benzodiazepine 2,5 diones as photosystem-II inhibitors: A public QSAR approach

Banjare, Purusottam; Singh, Jagadish; Roy, Partha Pratim

doi:10.1016/j.bjbas.2017.04.003

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…Promotion of genetically modified crops for the fulfillment of food and crop demand of increasing population around the globe by the agrochemical companies are thoroughly changing the face of agriculture in recent era . But limited extension of agricultural lands still encourages the indiscriminate applications of agrochemicals for plant protection and increasing production yields . Some of the other applications include slowing the spread of insects, to maintain lawns, highways and recreational areas, various human diseases transmitted by insects of apart from agrochemical .…”

Section: Introductionmentioning

confidence: 99%

Acute Rat and Mouse Oral Toxicity Determination of Anticholinesterase Inhibitor Carbamate Pesticides: A QSTR Approach

Roy

Banjare

Verma

et al. 2019

Molecular Informatics

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The toxic potentials of carbamates to human and non target organisms are of public concern in relation to society and ecosystem for their unregulated and indiscriminate use. No computational study was found on rat and mouse oral toxicity for carbamate pesticides. In this context, carbamate pesticides were collected from ChemIDplus databases for the modeling study. A series of local QSTR model for both rat and mouse oral toxicity of carbamate derivatives were developed according to OECD principle from 2D descriptors by using Genetic Algorithm (GA) as feature selection chemometric tools using QSARINS software. All the models indicate the importance of auto correlation descriptors related to charge, I-State, atom type E state for fragment À OÀ in relation to acute mammalian toxicity. Reliability of predictions of the models was verified by applicability domain (AD) and prediction reliability index. Finally developed models were applied to unknown carbamate pesticides to evaluate their predictions and AD. The toxic nature of the prioritized compounds with structural alerts were commented in a consensus way. Additional toxicity-toxicity relationship studies (QTTR) between these two responses with similar findings promoted further application of QTTR models in absence of one response. These findings may help the scientific community in prioritizing potentially hazardous pesticides of carbamate and related classes.

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Section: Introductionmentioning

confidence: 99%

Acute Rat and Mouse Oral Toxicity Determination of Anticholinesterase Inhibitor Carbamate Pesticides: A QSTR Approach

Roy

Banjare

Verma

et al. 2019

Molecular Informatics

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“…Amphetamines[15,37,55,67,68] Cathinones[39,53,54,[69][70][71][72] Benzidiazepines[6,7,52,65,[73][74][75] Synthetic Cannabinoids[49,52,58,70,76] O Fentanyls[64,77] 2.2. Computational Procedure2.2.1.…”

mentioning

confidence: 99%

Evaluation of Density Functional Theory-Generated Data for Infrared Spectroscopy of Novel Psychoactive Substances Using Unsupervised Learning

dos Santos,

Bruni

2024

Psychoactives

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Novel psychoactive substances (NPSs) are compounds plotted to modify the chemical structures of prohibited substances, offering alternatives for consumption and evading legislation. The prompt emergence of these substances presents challenges in health concerns and forensic assessment because of the lack of analytical standards. A viable alternative for establishing these standards involves leveraging in silico methods to acquire spectroscopic data. This study assesses the efficacy of utilizing infrared spectroscopy (IRS) data derived from density functional theory (DFT) for analyzing NPSs. Various functionals were employed to generate infrared spectra for five distinct NPS categories including the following: amphetamines, benzodiazepines, synthetic cannabinoids, cathinones, and fentanyls. PRISMA software was conceived to rationalize data management. Unsupervised learning techniques, including Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE), were utilized to refine the assessment process. Our findings reveal no significant disparities among the different functionals used to generate infrared spectra data. Additionally, the application of unsupervised learning demonstrated adequate segregation of NPSs within their respective groups. In conclusion, integrating theoretical data and dimension reduction techniques proves to be a powerful strategy for evaluating the spectroscopic characteristics of NPSs. This underscores the potential of this combined methodology as a diagnostic tool for distinguishing IR spectra across various NPS groups, facilitating the evaluation of newly unknown compounds.

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First report on exploration of structural features of natural compounds (NPACT database) for anti-breast cancer activity (MCF-7): QSAR-based virtual screening, molecular docking, ADMET, MD simulation, and DFT studies

Banjare,

Murmu,

Pandey

et al. 2024

In Silico Pharmacol.

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Design and combinatorial library generation of 1H 1,4 benzodiazepine 2,5 diones as photosystem-II inhibitors: A public QSAR approach

Cited by 3 publications

References 37 publications

Acute Rat and Mouse Oral Toxicity Determination of Anticholinesterase Inhibitor Carbamate Pesticides: A QSTR Approach

Acute Rat and Mouse Oral Toxicity Determination of Anticholinesterase Inhibitor Carbamate Pesticides: A QSTR Approach

Evaluation of Density Functional Theory-Generated Data for Infrared Spectroscopy of Novel Psychoactive Substances Using Unsupervised Learning

First report on exploration of structural features of natural compounds (NPACT database) for anti-breast cancer activity (MCF-7): QSAR-based virtual screening, molecular docking, ADMET, MD simulation, and DFT studies

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