Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1038/s41559-021-01519-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
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 PDFDrug-target binding affinity prediction based on power graph and word2vec.
BMC Med Genomics
January 2025
School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, Hubei, China.
Background: Drug and protein targets affect the physiological functions and metabolic effects of the body through bonding reactions, and accurate prediction of drug-protein target interactions is crucial for drug development. In order to shorten the drug development cycle and reduce costs, machine learning methods are gradually playing an important role in the field of drug-target interactions.
Results: Compared with other methods, regression-based drug target affinity is more representative of the binding ability.
A Deep Learning and PSSM Profile Approach for Accurate SNARE Protein Prediction.
Methods Mol Biol
January 2025
AIBioMed Research Group, Taipei Medical University, Taipei, Taiwan.
SNARE proteins play a pivotal role in membrane fusion and various cellular processes. Accurate identification of SNARE proteins is crucial for elucidating their functions in both health and disease contexts. This chapter presents a novel approach employing multiscan convolutional neural networks (CNNs) combined with position-specific scoring matrix (PSSM) profiles to accurately recognize SNARE proteins.
View Article and Find Full Text PDFMolecular Dynamics Simulation for Membrane Fusion.
Methods Mol Biol
January 2025
Department of Cancer and Cell Biology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
The soluble N-ethylmaleimide sensitive factor attachment protein receptor (SNARE) protein complex drives membrane fusion, and this process is further aided by accessory proteins, including complexin and α-synuclein. To understand the molecular mechanism underlying membrane fusion, we introduce an all-atom molecular dynamics (MD) simulation method. This method is used to understand and predict the conformations of protein and lipids, membrane geometry, and their interaction at femtosecond precision, by describing complex chemical systems with atomic models.
View Article and Find Full Text PDFPrecision Prediction of Alzheimer's Disease: Integrating Mitochondrial Energy Metabolism and Immunological Insights.
J Mol Neurosci
January 2025
Department of Biophysics, School of Life Sciences, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, is characterized by mitochondrial dysfunction and immune dysregulation. This study is aimed at developing a risk prediction model for AD by integrating multi-omics data and exploring the interplay between mitochondrial energy metabolism-related genes (MEMRGs) and immune cell dynamics. We integrated four GEO datasets (GSE132903, GSE29378, GSE33000, GSE5281) for differential gene expression analysis, functional enrichment, and weighted gene co-expression network analysis (WGCNA).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!