AIMC Topic: Drug Evaluation, Preclinical

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Experimental design strategy: weak reinforcement leads to increased hit rates and enhanced chemical diversity.

Journal of chemical information and modeling May 14, 2015
High Throughput Screening (HTS) is a common approach in life sciences to discover chemical matter that modulates a biological target or phenotype. However, low assay throughput, reagents cost, or a flowchart that can deal with only a limited number o...
Machine Learning Algorithms Drug Evaluation, Preclinical Computer Simulation Bayes Theorem
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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 Humans Support Vector Machine Drug Discovery Structure-Activity Relationship
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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...
Artificial Intelligence Molecular Docking Simulation Humans 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...
Drug Discovery Drug Evaluation, Preclinical Neural Networks, Computer Ligands Graph Neural Networks
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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 Machine Learning Proteins Molecular Docking Simulation Drug Evaluation, Preclinical
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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...
Humans Machine Learning Molecular Docking Simulation Butyrylcholinesterase Drug Evaluation, Preclinical Cholinesterase Inhibitors Neuroprotective Agents Alzheimer Disease Quantitative Structure-Activity Relationship Molecular Dynamics Simulation Ligands Drug Discovery Protein Binding
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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...
Drug Evaluation, Preclinical Dipeptidyl Peptidase 4 Dipeptidyl-Peptidase IV Inhibitors Drug Discovery Molecular Dynamics Simulation Algorithms Molecular Docking Simulation Humans Machine Learning
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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...
Protein Kinase Inhibitors Neural Networks, Computer Molecular Docking Simulation Drug Evaluation, Preclinical Ligands Deep Learning 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...
Cyclooxygenase 2 Drug Evaluation, Preclinical Cyclooxygenase 2 Inhibitors Humans Molecular Structure Workflow Machine Learning
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An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

Protein science : a publication of the Protein Society Jun 1, 2024
The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a...
Humans Machine Learning Cyclin-Dependent Kinase 8 Protein Kinase Inhibitors Molecular Docking Simulation Small Molecule Libraries Drug Evaluation, Preclinical
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