ArticleMolecules (Basel, Switzerland)2018
Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches.
Article in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 18 citations in OpenAlex.
- Structure-guided computational insecticide discovery targetingJournal of biomolecular structure & dynamics · 2024Article
- New Acetamide-Sulfonamide-Containing Scaffolds: Antiurease Activity Screening, Structure-Activity Relationship, Kinetics Mechanism, Molecular Docking, and MD Simulation Studies.Molecules (Basel, Switzerland) · 2023Article
- Exploring the potential of propanamide-sulfonamide based drug conjugates as dual inhibitors of urease and cyclooxygenase-2: biological and theirFrontiers in chemistry · 2023Article
- Mechanistic Analysis of Chemically Diverse Bromodomain-4 Inhibitors Using Balanced QSAR Analysis and Supported by X-ray Resolved Crystal Structures.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors.Frontiers in chemistry · 2022Article
- Identification of novel bacterial urease inhibitors through molecular shape and structure based virtual screening approaches.RSC advances · 2020Article
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r²), leave-one-out (LOO) cross validated correlation coefficient (q²), bootstrapping, and Fisher's randomization test. The highly reliable and predictive CoMFA (q² = 0.569, r² = 0.979) and CoMSIA (q² = 0.500, r² = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein's active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds.
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