ArticleChemical science2024
CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training.
Article in Chemical science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Deep learning-guided high-throughput screening and molecular dynamics simulations facilitate the discovery of potential FXIIa inhibitors.Journal of molecular modeling · 2026Article
- Teaching diffusion models physics: reinforcement learning for physically valid diffusion-based docking.Chemical science · 2026Article
- EasyDock 1.3: An Automated Pipeline for Molecular Docking.Journal of chemical information and modeling · 2026Article
- Prioritizing neuroactive ligands using motif-guided virtual discovery and zebrafish profiling.npj drug discovery · 2026Article
- Tightly coupled equivariant flow matching for molecular docking with multimodal physical constraints.Molecular diversity · 2026Article
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- Food-Derived Multi-Target Antihypertensive Peptides: Sources, Mechanisms and AI-Driven Strategies.Foods (Basel, Switzerland) · 2026Review
- Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.Nature protocols · 2026Review
- VsNsbench: evaluating AlphaFold3-embed induced-fit mechanism for enhanced virtual screening.Acta pharmacologica Sinica · 2026Article
- Assessing the factors influencing the quality of pocket-conditioned 3D generative models.Journal of cheminformatics · 2026Article
- CholBindNet as an interpretable neural network for cholesterol-binding site classification.Communications chemistry · 2026Article
- Open-Source Molecular Docking and AI-Augmented Structure-Based Drug Design: Current Workflows, Challenges, and Opportunities.International journal of molecular sciences · 2026Review
- Antiviral drug discovery and development: challenges and future directions.Signal transduction and targeted therapy · 2026Review
- De Novo Generation-Based Design of Potential Computational Hits Targeting the GluN1-GluN2A Receptor.Molecules (Basel, Switzerland) · 2026Article
- CholBindNet: Interpretable Neural Networks for Cholesterol Binding Site Prediction.bioRxiv : the preprint server for biology · 2026Article
- Antibacterial Drug Discovery: Deep Learning Successes and Challenges through the Structural Biology Lens.Computational and structural biotechnology journal · 2026Review
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- The covalent docking software landscape: features and applications in drug design.Briefings in bioinformatics · 2025Review
- SCORCH2: A Generalized Heterogeneous Consensus Model for High-Enrichment Interaction-Based Virtual Screening.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The expertise accumulated in deep neural network-based structure prediction has been widely transferred to the field of protein-ligand binding pose prediction, thus leading to the emergence of a variety of deep learning-guided docking models for predicting protein-ligand binding poses without relying on heavy sampling. However, their prediction accuracy and applicability are still far from satisfactory, partially due to the lack of protein-ligand binding complex data. To this end, we create a large-scale complex dataset containing ∼9 M protein-ligand docking complexes for pre-training, and propose CarsiDock, the first deep learning-guided docking approach that leverages pre-training of millions of predicted protein-ligand complexes. CarsiDock contains two main stages,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.