AIMC Topic: Drug Evaluation, Preclinical

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Systematic artifacts in support vector regression-based compound potency prediction revealed by statistical and activity landscape analysis.

PloS one Mar 5, 2015
Support vector machines are a popular machine learning method for many classification tasks in biology and chemistry. In addition, the support vector regression (SVR) variant is widely used for numerical property predictions. In chemoinformatics and ...
Drug Evaluation, Preclinical Artifacts Support Vector Machine Humans Structure-Activity Relationship Drug Discovery
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Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors.

Molecular diversity Aug 1, 2025
PI3Kγ is a lipid kinase that is expressed primarily in leukocytes and plays a significant role in tumors, inflammation, and autoimmune diseases. Consequently, considerable attention has been given to the development of pharmacological inhibitors of P...
Molecular Docking Simulation Humans Phosphoinositide-3 Kinase Inhibitors Drug Evaluation, Preclinical Machine Learning Class Ib Phosphatidylinositol 3-Kinase Drug Discovery Protein Kinase Inhibitors Bayes Theorem
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In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

Computational biology and chemistry Aug 1, 2025
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...
Humans Artificial Intelligence Protein Kinase Inhibitors Molecular Structure Molecular Docking Simulation Molecular Dynamics Simulation Drug Discovery Focal Adhesion Protein-Tyrosine Kinases Drug Evaluation, Preclinical
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On the application of artificial intelligence in virtual screening.

Expert opinion on drug discovery Jul 1, 2025
INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative tool in drug discovery, particularly in virtual screening (VS), a crucial initial step in identifying potential drug candidates. This article highlights the significance of AI...
Humans Artificial Intelligence Molecular Docking Simulation Drug Evaluation, Preclinical Ligands Quantitative Structure-Activity Relationship Drug Discovery Molecular Dynamics Simulation
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Advancements in Ligand-Based Virtual Screening through the Synergistic Integration of Graph Neural Networks and Expert-Crafted Descriptors.

Journal of chemical information and modeling May 26, 2025
The fusion of traditional chemical descriptors with graph neural networks (GNNs) offers a compelling strategy for enhancing ligand-based virtual screening methodologies. A comprehensive evaluation revealed that the benefits derived from this integrat...
Neural Networks, Computer Drug Discovery Ligands Graph Neural Networks Drug Evaluation, Preclinical
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Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening.

Journal of chemical information and modeling May 26, 2025
Physics-based docking methods have long been the cornerstone of structure-based virtual screening (VS). However, the emergence of machine learning (ML)-based docking approaches has opened new possibilities for enhancing VS technologies. In this study...
Protein Conformation Proteins Machine Learning Drug Evaluation, Preclinical Molecular Docking Simulation
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Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening.

Molecules (Basel, Switzerland) May 8, 2025
Butyrylcholinesterase (BChE), plays a critical role in alleviating the symptoms of Alzheimer's disease (AD) by regulating acetylcholine levels, emerging as an attractive target for AD treatment. This study employed a quantitative structure-activity r...
Molecular Docking Simulation Drug Discovery Protein Binding Humans Machine Learning Drug Evaluation, Preclinical Alzheimer Disease Ligands Neuroprotective Agents Molecular Dynamics Simulation Butyrylcholinesterase Cholinesterase Inhibitors Quantitative Structure-Activity Relationship
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Bioactivity predictions and virtual screening using machine learning predictive model.

Journal of biomolecular structure & dynamics May 1, 2025
Recently, there has been significant attention on machine learning algorithms for predictive modeling. Prediction models for enzyme inhibitors are limited, and it is essential to account for chemical biases while developing them. The lack of repeatab...
Dipeptidyl-Peptidase IV Inhibitors Humans Molecular Dynamics Simulation Machine Learning Drug Evaluation, Preclinical Molecular Docking Simulation Algorithms Dipeptidyl Peptidase 4 Drug Discovery
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Increase Docking Score Screening Power by Simple Fusion With CNNscore.

Journal of computational chemistry Mar 5, 2025
Scoring functions (SFs) of molecular docking is a vital component of structure-based virtual screening (SBVS). Traditional SFs yield their inherent shortage for idealized approximations and simplifications predicting the binding affinity. Complementa...
Ligands Protein Kinase Inhibitors Deep Learning Neural Networks, Computer Drug Evaluation, Preclinical Molecular Docking Simulation Humans
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COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.

Journal of computational chemistry Jan 15, 2025
Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachidonic acid into prostaglandins. The overexpression of enzyme is associated with conditions such as cancer, arthritis, and Alzheimer's disease (AD), wh...
Drug Evaluation, Preclinical Cyclooxygenase 2 Inhibitors Cyclooxygenase 2 Machine Learning Molecular Structure Workflow Humans
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