Výsledky vyhledávání - "Subhash M. Agarwal"

Akademický článek

Machine Learning, Molecular Docking, and Dynamics-Based Computational Identification of Potential Inhibitors against Lung Cancer

Autor: Agneesh Pratim Das, Puniti Mathur, Subhash M. Agarwal

Publikováno v: ACS Omega, Vol 9, Iss 4, Pp 4528-4539 (2024)

Externí odkaz: https://doaj.org/article/cf3ed1727b6e468da9298f5be942e20e

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Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach

Autor: Subhash M. Agarwal, Prajwal Nandekar, Ravi Saini

Publikováno v: RSC advances. 12(26)

Double mutated epidermal growth factor receptor is a clinically important target for addressing drug resistance in lung cancer treatment. Therefore, discovering new inhibitors against the T790M/L858R (TMLR) resistant mutation is ongoing globally. In

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f024416385a72ecf17bf2c95ef8cc579
https://pubmed.ncbi.nlm.nih.gov/35754875

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Meta-Analysis of 49 SNPs Covering 25,446 Cases and 41,106 Controls Identifies Polymorphisms in Hormone Regulation and DNA Repair Genes Associated with Increased Endometrial Cancer Risk

Autor: Agneesh Pratim Das, Nisha Chaudhary, Shrishty Tyagi, Subhash M. Agarwal

Publikováno v: Genes; Volume 14; Issue 3; Pages: 741

Endometrial cancer (EC) is among the most common gynecological disorders globally. As single nucleotide polymorphisms (SNPs) play an important role in the causation of EC, therefore, a comprehensive meta-analysis of 49 SNPs covering 25,446 cases and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05f2cbe1ab760f41c201d038acbe52dd
https://doi.org/10.3390/genes14030741

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A comprehensive meta-analysis of non-coding polymorphisms associated with precancerous lesions and cervical cancer

Autor: Agneesh Pratim Das, Sandeep Saini, Subhash M. Agarwal

Publikováno v: Genomics. 114(3)

To study the risk of polymorphisms present in the non-coding regions of genes related with cervical cancer.The PubMed database was extensively searched using text-mining techniques to identify literature containing the association of single nucleotid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0271339adddb8775d20455dd35abad7a
https://pubmed.ncbi.nlm.nih.gov/35227837

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Akademický článek

QSAR-based models for designing quinazoline/imidazothiazoles/pyrazolopyrimidines based inhibitors against wild and mutant EGFR.

Autor: Jagat Singh Chauhan, Sandeep Kumar Dhanda, Deepak Singla, Open Source Drug Discovery Consortium, Subhash M Agarwal, Gajendra P S Raghava

Publikováno v: PLoS ONE, Vol 9, Iss 7, p e101079 (2014)

Overexpression of EGFR is responsible for causing a number of cancers, including lung cancer as it activates various downstream signaling pathways. Thus, it is important to control EGFR function in order to treat the cancer patients. It is well estab

Externí odkaz: https://doaj.org/article/e7de3fb6c3244acc963798844644b989

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Prioritization and Meta-analysis of regulatory SNPs identified IL6, TGFB1, TLR9 and MMP7 as significantly associated with cervical cancer

Autor: Agneesh Pratim Das, Meenu Chopra, Subhash M. Agarwal

Publikováno v: Cytokine. 157

Cervical cancer is a leading women cancer globally with respect to both incidence and mortality. Its increased risk has been linked with HPV infection and genetic variations like single nucleotide polymorphisms (SNPs). Although, studies have been pub

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cebbbda965c924b238f40259a4875af1
https://pubmed.ncbi.nlm.nih.gov/35810505

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Akademický článek

The dynamics of stress p53-Mdm2 network regulated by p300 and HDAC1.

Autor: Akshit Arora, Saurav Gera, Tanuj Maheshwari, Dhwani Raghav, Md Jahoor Alam, R K Brojen Singh, Subhash M Agarwal

Publikováno v: PLoS ONE, Vol 8, Iss 2, p e52736 (2013)

We construct a stress p53-Mdm2-p300-HDAC1 regulatory network that is activated and stabilised by two regulatory proteins, p300 and HDAC1. Different activation levels of [Formula: see text] observed due to these regulators during stress condition have

Externí odkaz: https://doaj.org/article/b4b5a54d627b4b078ed95e3045fbfa3d

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