Latest Research in Physics-Informed Ligand Bioactivity Prediction

Top Research Topics in Physics-Informed Ligand Bioactivity Prediction

• Computational Drug Discovery Methods — 13 papers
• Machine Learning — 3 papers
• Biomolecules — 2 papers
• Quantitative Methods — 1 papers
• Metabolomics and Mass Spectrometry Studies — 1 papers
• Origins and Evolution of Life — 1 papers
• Artificial Intelligence — 1 papers
• Social and Information Networks — 1 papers
• Retinal Development and Disorders — 1 papers
• Chronic Lymphocytic Leukemia Research — 1 papers

Highest-Cited Papers

1. CGA-DTA: interaction-conditioned graph topology and cross-graph attention for drug--target affinity prediction
2. HelixDTA: Dual-Branch Sequence–Structure Learning with Complete Target Structures for Robust and Interpretable Drug–Target Affinity Prediction
3. GPCR Ligand Bioactivity Prediction with Physics-Informed Dual-State Query Learning
4. Decoding Molecular Binding Equilibria through Uncertainty-Aware Memory Retrieval
5. Multimodal molecular representation learning via text retrieval augmentation
6. MoaNet: Learning Protein–Ligand Mechanism of Action from Transcriptional Profiles and Sequence Information
7. Pre-training with Graph Transformers
8. Docking-score landscapes shape active-learning performance across Vina, Glide, and SILCS
9. A Task-Adaptive Multimodal Pretrained Framework for Antibiotic Virtual Screening with Joint Activity and Cytotoxicity Prediction
10. Deep3DCCS: Geometry-Driven Collision Cross Section Prediction from Multi-View Molecular Projection Tensors
11. Mechanochemical Transduction at the Protocellular Interface: A Refinement of the Energetic Coupling Between Mechanical Agitation and Vesicle Cannibalism
12. Agentic BAIM-LLM Evaluation (ABLE): Benchmarking LLM Use of Protein Design Tools
13. Omega-N: Interpretable Structural Node Descriptors and Their Applicability Domain
14. MAIDTA: an interpretable attention-based multi-modal model for drug-target affinity prediction
15. Artificial intelligence-guided engineering of precision ocular therapeutics
16. Chemical and geometric representation fidelity improves drug--target affinity prediction
17. ProbeMatchDTI: Probe-Driven Multi-Scale Biochemical Pattern Matching for Drug-Target Interaction Prediction
18. Discovery of novel acridine based inhibitors of Bruton’s tyrosine kinase (BTK) via pharmacophore modeling and machine learning-driven virtual screening followed by molecular dynamic studies
19. Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules
20. PCIM-DTA: Pairwise Conditional Interaction Modeling for Drug–Target Affinity Prediction under Cold-Start Scenarios

Sub-Regions

• Computational Drug Discovery Methods — 8 papers
• Quantitative Methods — 7 papers
• Metabolomics and Mass Spectrometry Studies — 5 papers
• Computational Drug Discovery Methods — 3 papers
• Artificial Intelligence — 2 papers
• Machine Learning — 2 papers