ArticleChemical science2023
A flexible data-free framework for structure-based
Article in Chemical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Application of Reinforcement Learning Techniques in De Novo Drug Design: A Systematic Literature Review.Health science reports · 2026Article
- AI-guided competitive docking for virtual screening and compound efficacy prediction.npj drug discovery · 2026Article
- Metalloprotein-Based Nanomedicines: Design Strategies, Functional Mechanisms, and Biomedical Applications.International journal of molecular sciences · 2026Review
- Structural Model of the Oncostatin M (OSM)-OSMRβ-gp130 Ternary Complex Reveals Pathways of Allosteric Communication in OSM Signaling.Current medicinal chemistry · 2026Article
- Incorporating targeted protein structure in deep learning methods for molecule generation in computational drug design.Chemical science · 2025Review
- Artificial intelligence in bioinformatics: a survey.Briefings in bioinformatics · 2025Review
- A Novel Multi-Tiered Hybrid Virtual Screening Pipeline for the Discovery of WDR5-MLL1 Interaction Disruptors in Precision Cancer Therapy.ACS omega · 2025Article
- Investigate the potential inhibitors of sphingosine kinase 1 (SphK1) with molecular dynamics and artificial intelligence drug design methods.Journal of molecular modeling · 2025Article
- Artificial Intelligence in Molecular Optimization: Current Paradigms and Future Frontiers.International journal of molecular sciences · 2025Review
- A structure-based framework for selective inhibitor design and optimization.Communications biology · 2025Article
- MolEM: a unified generative framework for molecular graphs and sequential orders.Briefings in bioinformatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Contemporary structure-based molecular generative methods have demonstrated their potential to model the geometric and energetic complementarity between ligands and receptors, thereby facilitating the design of molecules with favorable binding affinity and target specificity. Despite the introduction of deep generative models for molecular generation, the atom-wise generation paradigm that partially contradicts chemical intuition limits the validity and synthetic accessibility of the generated molecules. Additionally, the dependence of deep learning models on large-scale structural data has hindered their adaptability across different targets. To overcome these challenges, we present a novel search-based framework, 3D-MCTS, for structure-based
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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.