Pharmacophore

Integrating pharmacophore model and deep learning for activity prediction of molecules with BRCA1 gene.

Journal of bioinformatics and computational biology 38567386

In this paper, we propose a novel approach for predicting the activity/inactivity of molecules with the BRCA1 gene by combining pharmacophore modeling and deep learning techniques. Initially, we generated 3D pharmacophore fingerprints using a pharmac...

Deep Learning Drug Discovery Genes, BRCA1 Pharmacophore Reproducibility of Results

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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 38446372

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...

Aurora Kinase A Drug Discovery Humans Ligands Machine Learning Models, Molecular Pharmacophore Protein Kinase Inhibitors Quantitative Structure-Activity Relationship

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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 38780456

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 Fluvastatin Humans Machine Learning Molecular Dynamics Simulation Myeloid Cell Leukemia Sequence 1 Protein Pharmacophore Quantum Theory

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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 38697440

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...

Binding Sites Chronic Disease G-Protein-Coupled Receptor Kinase 5 Humans Ligands Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Pharmacophore Protein Binding Protein Kinase Inhibitors Quantitative Structure-Activity Relationship Thermodynamics

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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 39191165

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 ...

Antiprotozoal Agents Cryptosporidium parvum Deep Learning Drug Evaluation, Preclinical High-Throughput Screening Assays Molecular Docking Simulation Molecular Structure Pharmacophore Protein Kinase Inhibitors Protein Kinases

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Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

Molecular diversity 39152354

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...

Antitubercular Agents Enzyme Inhibitors Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Mycobacterium tuberculosis Nucleoside-Phosphate Kinase Pharmacophore Protein Binding Protein Kinase Inhibitors

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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 39739078

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 (...

Computer Simulation Diabetes Mellitus, Type 2 Drug Design Enzyme Activators Glucokinase Humans Hypoglycemic Agents Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Peptides Pharmacophore Phenylalanine

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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.

BMC biology 39736736

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 ...

Algorithms Binding Sites Deep Learning Drug Design Humans Ligands Pharmacophore Proteins

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Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

Molecular informatics 39976334

The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the development of various aggressive cancers, particularly breast cancer. Discovering novel HER2 inhibitors is crucial for expanding therapeutic options for HER...

Antineoplastic Agents Drug Discovery Humans Machine Learning Molecular Docking Simulation Pharmacophore Protein Kinase Inhibitors Quantitative Structure-Activity Relationship Receptor, ErbB-2

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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 40112531

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...

Drug Discovery Humans Ligands Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Pharmacophore Phosphatidylinositol 3-Kinases Phosphoinositide-3 Kinase Inhibitors Protein Binding Protein Kinase Inhibitors

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Explore the latest research on artificial intelligence and machine learning in medicine.

Integrating pharmacophore model and deep learning for activity prediction of molecules with BRCA1 gene.

Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.

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.

E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.

Identification of mycobacterial Thymidylate kinase inhibitors: a comprehensive pharmacophore, machine learning, molecular docking, and molecular dynamics simulation studies.

In silico design of dehydrophenylalanine containing peptide activators of glucokinase using pharmacophore modelling, molecular dynamics and machine learning: implications in type 2 diabetes.

PharmRL: pharmacophore elucidation with deep geometric reinforcement learning.

Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

Computational discovery of novel PI3KC2α inhibitors using structure-based pharmacophore modeling, machine learning and molecular dynamic simulation.

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