Computational structure-based screening identifies potential inhibitors of TRIM33α

Discovery of Potent CDK2 Inhibitors Through Structure-Based Virtual Screening and MD Simulation Studies.

Overall, MD1-MD5 demonstrated excellent binding, structural stability, and pharmacokinetic properties, making them strong candidates for future CDK2-targeted anticancer research.

Pharmacophore-based identification and molecular docking of CCR5 inhibitors: insights from dynamic simulations

The integrated computational approach identified ZINC000000867238 as a potent and stable CCR5 inhibitor candidate, warranting further in vitro and in vivo validation as a potential HIV-1 entry blocker.

Computational identification of natural phytochemicals as potential inhibitors of UBE2J1 causing ovarian cancer

Findings highlight Withaferin A as a promising natural inhibitor of UBE2J1 and provide a foundation for future experimental validation aimed at developing targeted therapies against ovarian cancer.

Structure-based discovery of novel ROCK2 inhibitors using integrated virtual screening, molecular dynamics, metadynamics and absolute binding free energy calculations

Structure-based discovery of diphenylpyrazines as disruptors of the Skp2–Cks1 protein–protein interaction: computational insights and biochemical validation

Findings validate the diphenylpyrazine scaffold as a promising chemotype for Skp2–Cks1 inhibition and identify C3 as a strong lead for further optimization.

An Integrated Consensus Machine Learning and Structure-Based Workflow for the Discovery of Novel Tankyrase 1 Inhibitors

The proposed workflow efficiently reduced a large chemical space to a focused set of TNKS1 inhibitor candidates while substantially reducing the experimental screening burden, highlighting the value of integrating consensus ML, SBVS, and experimental validation to accelerate early-stage hit discovery for TNKS1 and other therapeutic targets.