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Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding-based methodology.
J Cheminform
January 2025
Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, UK.
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode.
View Article and Find Full Text PDFPharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening.
Chem Sci
November 2024
Department of Chemistry, KAIST 291 Daehak-ro, Yuseong-gu Daejeon 34141 Republic of Korea
As ultra-large-scale virtual screening becomes critical for early-stage drug discovery, highly efficient screening methods are gaining prominence. Deep-learning-based approaches which directly estimate binding affinities without binding conformation have attracted great attention as an alternative solution to molecular docking, but the generalization capability of existing methods in vast chemical space remains uncertain due to restricted training data. Here, we introduce PharmacoNet, the first deep-learning framework for pharmacophore modeling toward ultra-fast virtual screening.
View Article and Find Full Text PDFDecoding the Knacks of Ellagitannin Lead Compounds to Treat Nonalcoholic Fatty Liver Disease using Computer-aided Drug Designing.
Curr Comput Aided Drug Des
October 2024
MOE Key Laboratory of Bio-Intelligent Manufacturing, School of Bioengineering, Dalian University of Technology, Dalian, Liaoning, China.
Background: The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing globally, impacting individuals in Western nations and rapid growing in Asian countries due to sedentary lifestyles; thus, NAFLD has emerged as a significant worldwide health concern. Presently, lifestyle changes represent the primary approach to managing NAFLD.
Methods: This research aimed to identify the potential drug targets for treating NAFLD through comprehensive in silico computational analysis.
Xanthine oxidase inhibitors: Virtual screening and mechanism of inhibition studies.
Int J Biol Macromol
November 2024
College of Food Science and Engineering, Bohai University, Jinzhou 121013, PR China. Electronic address:
Article Synopsis
- Xanthine oxidase (XO) is a crucial enzyme in purine metabolism and is targeted for treating hyperuricemia; the study identifies 22 XO inhibitors to create a 3D-QSAR pharmacophore model.
- Researchers examined 2000 natural compounds using molecular docking and in vitro tests, revealing Diosmetin, Fisetin, and Genistein as effective XO inhibitors with specific inhibition values.
- Analysis indicated that these flavonoids interact with XO via hydrogen bonds and hydrophobic forces, influencing its stability and structure, which is essential for developing new XO inhibitors.
@TOME 3.0: Interfacing Protein Structure Modeling and Ligand Docking.
J Mol Biol
September 2024
A.B.C.I.S, CNRS UMR5048 - INSERM U1054 - Université de Montpellier 29, Rue de Navacelles, 34090 Montpellier Cedex, France. Electronic address:
Knowledge of protein-ligand complexes is essential for efficient drug design. Virtual docking can bring important information on putative complexes but it is still far from being simultaneously fast and accurate. Receptors are flexible and adapt to the incoming small molecules while docking is highly sensitive to small conformational deviations.
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