Výsledky vyhledávání - "Madhulata Kumari"

Development of a deep learning-based quantitative structure-activity relationship model to identify potential inhibitors against the 3C-like protease of SARS-CoV-2

Autor: Madhulata, Kumari, Naidu, Subbarao

Publikováno v: Future medicinal chemistry. 14(21)

bBackground:/bIn the recent COVID-19 pandemic, SARS-CoV-2 infection spread worldwide. The 3C-like protease (3CLpro) is a promising drug target for SARS-CoV-2.bResults:/bWe constructed a deep learning-based convolutional neural network-quantitative st

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::615fdf542e76cb4ac4df6851288cef55
https://pubmed.ncbi.nlm.nih.gov/36177879

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Identification of novel multitarget antitubercular inhibitors against mycobacterial peptidoglycan biosynthetic Mur enzymes by structure-based virtual screening

Autor: Madhulata Kumari, Naidu Subbarao

Publikováno v: Journal of Biomolecular Structure and Dynamics. 40:8185-8196

Current therapeutic strategies for several diseases, including Mycobacterium tuberculosis infection, have evolved from an initial single-target treatment to a multitarget one. A multitarget antitubercular drugs targeting different mycobacterial prote

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f124c813f5e3056080c41912b01ed206
https://doi.org/10.1080/07391102.2021.1908913

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A hybrid resampling algorithms SMOTE and ENN based deep learning models for identification of Marburg virus inhibitors

Autor: Madhulata Kumari, Naidu Subbarao

Publikováno v: Future medicinal chemistry. 14(10)

Background: Marburg virus (MARV) is a sporadic outbreak of a zoonotic disease that causes lethal hemorrhagic fever in humans. We propose a deep learning model with resampling techniques and predict the inhibitory activity of MARV from unknown compoun

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f34e766ea4b696c52d6d16871cc3008d
https://pubmed.ncbi.nlm.nih.gov/35393862

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A genetic programming-based approach to identify potential inhibitors of serine protease of Mycobacterium tuberculosis

Autor: Madhulata Kumari, Naidu Subbarao, Neeraj Tiwari

Publikováno v: Future Medicinal Chemistry. 12:147-159

Aim: We applied genetic programming approaches to understand the impact of descriptors on inhibitory effects of serine protease inhibitors of Mycobacterium tuberculosis ( Mtb) and the discovery of new inhibitors as drug candidates. Materials & method

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4cc100f62642d99b6e853f2c373f6aa6
https://doi.org/10.4155/fmc-2018-0560

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Virtual screening to identify novel potential inhibitors for Glutamine synthetase of Mycobacterium tuberculosis

Autor: Madhulata Kumari, Naidu Subbarao

Publikováno v: Journal of Biomolecular Structure and Dynamics. 38:5062-5080

Glutamine synthetase (GS) of Mycobacterium tuberculosis (Mtb) is an essential enzyme which is involved in nitrogen metabolism and cell wall synthesis. It is involved in the inhibition of phagosome-lysosome fusion by preventing acidification. Targetin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::35645c96f80b9f7367ab4ec31aa502df
https://doi.org/10.1080/07391102.2019.1695670

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Origin, domestication, and spread

Autor: Madhulata Kumari, Roshni Joshi, A.K. Jain, Nikhil Malhotra

Nature provides an infinite variety of plant species which includes number of neglected and underutilized crops that have been pushed into forgetfulness by the predominant ‘major’ cereals. Millets and pseudo-cereals belong to such category having

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::433f7031eaafe55d2518913c294b7284
https://doi.org/10.1016/b978-0-12-820089-6.00004-5

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