AIMC Topic: Drug Evaluation, Preclinical

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Risk assessment of supply chain for pharmaceutical excipients with AHP-fuzzy comprehensive evaluation.

Drug development and industrial pharmacy Aug 12, 2015
As the essential components in formulations, pharmaceutical excipients directly affect the safety, efficacy, and stability of drugs. Recently, safety incidents of pharmaceutical excipients posing seriously threats to the patients highlight the necess...
Polysorbates Drug Industry Excipients Fuzzy Logic Drug Evaluation, Preclinical Risk Assessment
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Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

European journal of medicinal chemistry Jul 6, 2015
The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protea...
Molecular Structure Dose-Response Relationship, Drug Drug Evaluation, Preclinical HIV Protease Inhibitors Structure-Activity Relationship HIV Protease Molecular Docking Simulation Support Vector Machine
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Visualization and Interpretation of Support Vector Machine Activity Predictions.

Journal of chemical information and modeling Jun 2, 2015
Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other...
Linear Models Protein Kinase Inhibitors Mitogen-Activated Protein Kinase 14 Receptor, Cannabinoid, CB2 Receptors, Dopamine D2 Humans Drug Evaluation, Preclinical Software Ligands Algorithms Support Vector Machine
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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 Computer Simulation Drug Evaluation, Preclinical 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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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...
Class Ib Phosphatidylinositol 3-Kinase Drug Discovery Bayes Theorem Protein Kinase Inhibitors Phosphoinositide-3 Kinase Inhibitors Drug Evaluation, Preclinical Machine Learning Humans Molecular Docking Simulation
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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...
Drug Evaluation, Preclinical Protein Kinase Inhibitors Molecular Structure Molecular Dynamics Simulation Focal Adhesion Protein-Tyrosine Kinases Humans Molecular Docking Simulation Drug Discovery Artificial Intelligence
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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 Drug Discovery Ligands Molecular Dynamics Simulation Quantitative Structure-Activity Relationship
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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 Ligands Neural Networks, Computer 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 Proteins Machine Learning Drug Evaluation, Preclinical Molecular Docking Simulation
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