EvaluationMaster: A GUI Tool for Structure-Based Virtual Screening Evaluation Analysis and Decision-Making Support.

Structure-based virtual screening (SBVS) plays an indispensable role in the early phases of drug discovery, utilizing computational docking techniques to predict interactions between molecules and biological targets. During the SBVS process, selecting appropriate target structures and screening algorithms is crucial, as these choices significantly shape the outcomes. Typically, such selections require researchers to be proficient with multiple algorithms and familiar with evaluation and analysis processes, complicating their tasks.

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations.

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method.

Identification and assessment of new PIM2 inhibitors for treating hematologic cancers: A combined approach of energy-based virtual screening and machine learning evaluation.

PIM2, part of the PIM kinase family along with PIM1 and PIM3, is often overexpressed in hematologic cancers, fueling tumor growth. Despite its significance, there are no approved drugs targeting it. In response to this challenge, we devised a thorough virtual screening workflow for discovering novel PIM2 inhibitors.

Discovery of potential WEE1 inhibitors via hybrid virtual screening.

G/M cell cycle checkpoint protein WEE1 kinase is a promising target for inhibiting tumor growth. Although various WEE1 inhibitors have entered clinical investigations, their therapeutic efficacy and safety profile remain unsatisfactory. In this study, we employed a comprehensive virtual screening workflow, which included Schrödinger-Glide molecular docking at different precision levels, as well as the utilization of tools such as MM/GBSA and Deepdock to predict the binding affinity between targets and ligands, in order to identify potential WEE1 inhibitors.

Discovery of novel 2H-chromene-3-carbonyl derivatives as selective estrogen receptor degraders (SERDs): Design, synthesis and biological evaluation.

Selective estrogen receptor degraders (SERDs) not only block ERα activity but degrade this receptor at the same time and are effective in relapsed ERα positive breast cancer patients who have accepted other endocrine therapies. Herein, through scaffold hopping of coumarin skeleton, a series of 2H-chromene-3-carbonyl-based SERDs with phenyl acrylic acid group as the side chain were designed and synthesized. Compound XH04 containing 7-hydroxy-2H-chromene-3-carbonyl skeleton exhibited the most potent activities in 2D (IC = 0.