ArticleJournal of cheminformatics2024
MolScore: a scoring, evaluation and benchmarking framework for generative models in de novo drug design.
Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Multi-objective optimization in the context of generative chemistry.Nature communications · 2026Review
- Deep generative models for 3D structure-based drug design and molecular optimisation: a comprehensive survey.Journal of computer-aided molecular design · 2026Review
- 3DOpt: Benchmark for Automated Design of 3D Molecular Structures across the Periodic Table.Journal of chemical information and modeling · 2026Article
- Scaffold-based evaluation metrics for fair comparison of molecular generators.Journal of cheminformatics · 2026Article
- ANNalog: generation of MedChem-similar molecules.Journal of cheminformatics · 2026Article
- Data-Driven Evaluation for Multicriteria Selection of Covalent Organic Frameworks for Membrane-Based Hydrogen Separation.ACS omega · 2026Article
- Test-Time Training Scaling Laws for Chemical Exploration in Drug Design.Journal of chemical information and modeling · 2025Article
- REINFORCE-ING Chemical Language Models for Drug Discovery.Journal of chemical information and modeling · 2025Article
- Polymorphism Crystal Structure Prediction with Adaptive Space Group Diversity Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- AgentMol: Multi-Model AI System for Automatic Drug-Target Identification and Molecule Development.Methods and protocols · 2025Article
- How evaluation choices distort the outcome of generative drug discovery.Journal of cheminformatics · 2025Article
- Large Language Models for Controllable Multi-property Multi-objective Molecule Optimization.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2025Article
- Multi-Objective Drug Molecule Optimization Based on Tanimoto Crowding Distance and Acceptance Probability.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey.Journal of chemical information and modeling · 2025Review
- CMOMO: a deep multi-objective optimization framework for constrained molecular multi-property optimization.Briefings in bioinformatics · 2025Article
- Identification of nanomolar adenosine ANature communications · 2025Article
- Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry.Chemical Society reviews · 2025Review
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-Directed Molecular Generation.Journal of chemical information and modeling · 2025Article
- ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery.Journal of chemical information and modeling · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Generative models are undergoing rapid research and application to de novo drug design. To facilitate their application and evaluation, we present MolScore. MolScore already contains many drug-design-relevant scoring functions commonly used in benchmarks such as, molecular similarity, molecular docking, predictive models, synthesizability, and more. In addition, providing performance metrics to evaluate generative model performance based on the chemistry generated. With this unification of functionality, MolScore re-implements commonly used benchmarks in the field (such as GuacaMol, MOSES, and MolOpt). Moreover, new benchmarks can be created trivially. We demonstrate this by testing a chemical language model with reinforcement learning on three new tasks of increasing complexity related to the design of 5-HT
Indexed as
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.