AIMC Topic: Ligands

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Structural stability-guided scaffold hopping and computational modeling of tankyrase inhibitors targeting colorectal cancer.

PloS one Sep 19, 2025
Colorectal cancer is one of the leading causes of cancer-related deaths worldwide, mainly due to aberrant Wnt/β-catenin signaling resulting from APC mutations. Tankyrase is a key regulator of this pathway and plays a crucial role in stabilizing AXIN,...
Humans Colorectal Neoplasms Tankyrases Ligands Enzyme Inhibitors Molecular Docking Simulation Antineoplastic Agents
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PyaiVS unifies AI workflows to accelerate ligand discovery and yields ABCG2 inhibitors.

European journal of medicinal chemistry Sep 17, 2025
Developing optimized AI models for virtual screening requires coordinated selection of algorithms, molecular representations, and data splitting strategies, yet lacks integrated tools. We present PyaiVS, a Python package that integrates nine machine ...
Humans Dose-Response Relationship, Drug Machine Learning Neoplasm Proteins Molecular Docking Simulation Drug Discovery Antineoplastic Agents Structure-Activity Relationship Molecular Structure Ligands ATP Binding Cassette Transporter, Subfamily G, Member 2 Workflow
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Integrating Machine Learning into Free Energy Perturbation Workflows.

Journal of chemical information and modeling Sep 17, 2025
Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein-ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup proc...
Thermodynamics Workflow Ligands Drug Discovery Proteins Drug Design Humans Machine Learning
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Machine Learning Navigated Allosteric Network to Unveil Biased Allosteric Modulation of GPCRs.

Journal of chemical theory and computation Sep 16, 2025
Biased allosteric modulators (BAMs) offer a promising avenue for developing safer and more selective therapeutics for G protein-coupled receptors (GPCRs). However, their molecular mechanisms remain unclear due to the complex combination of biased and...
Allosteric Regulation Machine Learning Receptors, G-Protein-Coupled Molecular Dynamics Simulation Ligands Humans
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Bioactivity Deep Learning for Complex Structure-Free Compound-Protein Interaction Prediction.

Journal of chemical information and modeling Sep 16, 2025
Protein-ligand binding affinity assessment plays a pivotal role in virtual drug screening, yet conventional data-driven approaches rely heavily on limited protein-ligand crystal structures. Structure-free compound-protein interaction (CPI) methods ha...
Deep Learning Protein Binding Drug Discovery Ligands Proteins Drug Evaluation, Preclinical
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HitScreen: A Sequence-Based Drug Virtual Screening Approach Using Data Augmentation and Protein Language Models.

Journal of chemical information and modeling Sep 16, 2025
Sequence-based drug-target interaction (DTI) prediction is an effective approach for identifying potential drug candidates without relying on three-dimensional protein structures. However, current sequence-based methods often suffer from limited gene...
Deep Learning Drug Evaluation, Preclinical Ligands Proteins Models, Molecular
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MolAI: A Deep Learning Framework for Data-Driven Molecular Descriptor Generation and Advanced Drug Discovery Applications.

Journal of chemical information and modeling Sep 15, 2025
This study introduces MolAI, a robust deep learning model designed for data-driven molecular descriptor generation. Utilizing a vast training data set of 221 million unique compounds, MolAI employs an autoencoder neural machine translation model to g...
Deep Learning Structure-Activity Relationship Ligands Neural Networks, Computer Drug Discovery
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BIOPTIC B1 Ultra-High-Throughput Virtual Screening System Discovers LRRK2 Ligands in Vast Chemical Space.

Journal of chemical information and modeling Sep 12, 2025
The rapid expansion of chemical space presents significant challenges in identifying novel ligands for drug targets. Here, we introduce BIOPTIC B1, an ultra-high-throughput ligand-based virtual screening system capable of rapidly evaluating multi-bil...
Small Molecule Libraries Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 User-Computer Interface Humans Ligands Drug Discovery High-Throughput Screening Assays
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MOLECULE: Molecular-dynamics and Optimized deep Learning for Entropy-regularized Classification and Uncertainty-aware Ligand Evaluation.

Journal of chemical theory and computation Sep 11, 2025
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' pred...
Entropy Uncertainty Ligands Protein Kinase Inhibitors Drug Discovery Deep Learning Molecular Dynamics Simulation
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All That Glitters Is Not Gold: Importance of Rigorous Evaluation of Proteochemometric Models.

Journal of chemical information and modeling Sep 3, 2025
Proteochemometric models (PCMs) are used in computational drug discovery to employ both protein and ligand representations jointly for bioactivity prediction. While machine learning (ML) and deep learning (DL) have come to dominate PCMs, often servin...
Ligands Deep Learning Machine Learning Proteins Drug Discovery
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