Madhulata Kumari

发表

3D QSAR, pharmacophore and molecular docking studies of known inhibitors and designing of novel inhibitors for M18 aspartyl aminopeptidase of Plasmodium falciparum

N. Subbarao, Madhulata Kumari, S. Chandra, 2016, BMC Structural Biology.

High Throughput Virtual Screening to Identify Novel natural product Inhibitors for MethionyltRNA-Synthetase of Brucella melitensis

N. Subbarao, Madhulata Kumari, S. Chandra, 2017, Bioinformation.

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

N. Subbarao, Madhulata Kumari, 2019, Journal of biomolecular structure & dynamics.

Virtual Screening of EGFR Tyrosine Kinase Inhibitors Associated with Non-Small Cell Lung Cancer from Phytochemical Data Set

H. Joshi, Madhulata Kumari, S. Chandra, 2016 .

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

N. Subbarao, Madhulata Kumari, Neeraj Tiwari, 2020, Future medicinal chemistry.

Exploring the interaction mechanism between potential inhibitor and multi-target Mur enzymes of mycobacterium tuberculosis using molecular docking, molecular dynamics simulation, principal component analysis, free energy landscape, dynamic cross-correlation matrices, vector movements, and binding fr

N. Subbarao, Madhulata Kumari, Ruhar Singh, 2021, Journal of biomolecular structure & dynamics.

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

N. Subbarao, Madhulata Kumari, 2021, Journal of biomolecular structure & dynamics.

Discovery of multi-target mur enzymes inhibitors with anti-mycobacterial activity through a Scaffold approach

N. Subbarao, M. Waseem, Madhulata Kumari, 2022, Journal of biomolecular structure & dynamics.

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

N. Subbarao, Madhulata Kumari, 2022, Future medicinal chemistry.

Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases

N. Subbarao, Madhulata Kumari, 2021, Computers in Biology and Medicine.

In silico prediction of anti-malarial hit molecules based on machine learning methods

Subhash Chandra, Madhulata Kumari, Madhulata Kumari, 2015, Int. J. Comput. Biol. Drug Des..

Origin, domestication, and spread

Ajai Kumar Jain, Madhulata Kumari, Nikhil Malhotra, 2021 .