AIMC Topic: Pharmacophore

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Design and Synthesis of Magnolol Derivatives Using Integrated CNNs and Pharmacophore Approaches for Enhanced Parasiticidal Activity in Aquaculture.

Journal of agricultural and food chemistry Apr 16, 2025
Aquaculture is a rapidly growing sector of global food production, playing a vital role in poverty alleviation, food security, and income generation. However, it faces substantial challenges, particularly due to infections caused by the protozoan , l...
Structure-Activity Relationship Molecular Structure Zebrafish Drug Design Aquaculture Fish Diseases Goldfish Neural Networks, Computer Lignans Animals Ciliophora Infections Pharmacophore Biphenyl Compounds Dinoflagellida Antiprotozoal Agents
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Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

Journal of molecular graphics & modelling Mar 15, 2025
PI3KC2α is a lipid kinase associated with cancer metastasis and thrombosis. In this study, we present a novel computational workflow integrating structure-based pharmacophore modeling, machine learning (ML), and molecular dynamics (MD) simulations to...
Molecular Dynamics Simulation Ligands Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Pharmacophore Drug Discovery Humans Protein Binding Machine Learning Phosphatidylinositol 3-Kinases Molecular Docking Simulation
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In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.

Journal of computer-aided molecular design Dec 31, 2024
Diabetes represents a significant global health challenge associated with substantial healthcare costs and therapeutic complexities. Current diabetes therapies often entail adverse effects, necessitating the exploration of novel agents. Glucokinase (...
Glucokinase Enzyme Activators Molecular Dynamics Simulation Phenylalanine Pharmacophore Machine Learning Computer Simulation Peptides Diabetes Mellitus, Type 2 Hypoglycemic Agents Molecular Docking Simulation Drug Design Humans
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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.

BMC biology Dec 31, 2024
BACKGROUND: Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are ...
Humans Proteins Ligands Binding Sites Pharmacophore Algorithms Drug Design Deep Learning
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Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Molecular diversity Aug 16, 2024
Thymidylate kinase (TMK) is a pivotal enzyme in Mycobacterium tuberculosis (Mtb), crucial for phosphorylating thymidine monophosphate (dTMP) to thymidine diphosphate (dTDP), thereby playing a critical role in DNA biosynthesis. Dysregulation or inhibi...
Nucleoside-Phosphate Kinase Pharmacophore Mycobacterium tuberculosis Enzyme Inhibitors Protein Kinase Inhibitors Machine Learning Antitubercular Agents Molecular Dynamics Simulation Molecular Docking Simulation Protein Binding
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E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.

Computational biology and chemistry Aug 13, 2024
Cryptosporidiosis, a prevalent gastrointestinal illness worldwide, is caused by the protozoan parasite Cryptosporidium parvum. Calcium-dependent protein kinase 1 (CpCDPK1), crucial for the parasite's life cycle, serves as a promising drug target due ...
Molecular Docking Simulation Deep Learning Cryptosporidium parvum Pharmacophore High-Throughput Screening Assays Molecular Structure Antiprotozoal Agents Drug Evaluation, Preclinical Protein Kinase Inhibitors Protein Kinases
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Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.

Physical chemistry chemical physics : PCCP Jun 6, 2024
Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conventional pharmacophore screening approach has limitations in conformation sampling and data mining. He...
Antineoplastic Agents Cell Line, Tumor Drug Repositioning Humans Machine Learning Myeloid Cell Leukemia Sequence 1 Protein Pharmacophore Molecular Dynamics Simulation Quantum Theory Fluvastatin
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Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation.

International journal of biological macromolecules Apr 30, 2024
GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibi...
Protein Kinase Inhibitors Binding Sites Thermodynamics Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Pharmacophore Protein Binding Ligands G-Protein-Coupled Receptor Kinase 5 Chronic Disease Quantitative Structure-Activity Relationship
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Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Molecular diversity Mar 6, 2024
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as col...
Drug Discovery Aurora Kinase A Models, Molecular Ligands Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Humans Pharmacophore Machine Learning
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A pharmacophore-guided deep learning approach for bioactive molecular generation.

Nature communications Oct 6, 2023
The rational design of novel molecules with the desired bioactivity is a critical but challenging task in drug discovery, especially when treating a novel target family or understudied targets. We propose a Pharmacophore-Guided deep learning approach...
Pharmacophore Drug Design Drug Discovery Deep Learning
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