ReviewACS medicinal chemistry letters2023
The Hitchhiker's Guide to Deep Learning Driven Generative Chemistry.
Review in ACS medicinal chemistry letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Multi-objective optimization in the context of generative chemistry.Nature communications · 2026Review
- Geometric Deep Learning-Based Drug Design Models for Small-Molecule Drug Discovery.Molecular informatics · 2026Review
- Generative Chemistry Platform for Small Molecules Targeting RNA: A Case Study for Chemical Optimization.Computational and structural biotechnology journal · 2026Article
- The changing landscape of medicinal chemistry optimization.Nature reviews. Drug discovery · 2025Review
- How many crystal structures do you need to trust your docking results?bioRxiv : the preprint server for biology · 2025Article
- Large language models open new way of AI-assisted molecule design for chemists.Journal of cheminformatics · 2025Article
- Accelerating discovery of bioactive ligands with pharmacophore-informed generative models.Nature communications · 2025Article
- AI meets physics in computational structure-based drug discovery for GPCRs.npj drug discovery · 2025Review
- U-FDL-PPE: a unified federated deep learning framework with privacy-preserving explainability for early and accurate viral disease prediction.Frontiers in radiology · 2025Article
- A systematic review of deep learning chemical language models in recent era.Journal of cheminformatics · 2024Review
- Allostery Illuminated: Harnessing AI and Machine Learning for Drug Discovery.ACS medicinal chemistry letters · 2024Review
- Accelerated chemical science with AI.Digital discovery · 2024Review
- Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: anFrontiers in chemistry · 2024Article
- GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.Journal of chemical information and modeling · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This microperspective covers the most recent research outcomes of artificial intelligence (AI) generated molecular structures from the point of view of the medicinal chemist. The main focus is on studies that include synthesis and experimental
Identifiers
What OpenQuestion holds
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.