ArticleChemical science2021
DeepFrag: a deep convolutional neural network for fragment-based lead optimization.
Article in Chemical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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The trial behind it
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Who cites it
44 citing papers in PubMed.
- Computational identification of potential inhibitors for chikungunya virus nsP2pro.Royal Society open science · 2026Article
- RelAgent: a multi-agent solution for molecular relationship grounding.Bioinformatics (Oxford, England) · 2026Article
- Deep generative models for 3D structure-based drug design and molecular optimisation: a comprehensive survey.Journal of computer-aided molecular design · 2026Review
- Unlocking the potential of marine natural product fragments for rational anticancer drug design: a computational approach.Scientific reports · 2026Article
- MolMod: a molecular modification platform for molecular property optimization via fragment-based generation.Molecular diversity · 2026Article
- Generative AI in structure-based drug discovery.BMC biology · 2026Review
- Precision fragment addition: domain-specific DeepFrag2 models for smarter lead optimization.Digital discovery · 2026Article
- Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.Advanced drug delivery reviews · 2026Review
- An effective fragment-based dual conditional diffusion framework for molecular generation.Briefings in bioinformatics · 2026Article
- Artificial intelligence for coordinating vaccine design, antiviral discovery, and real-world monitoring in the era of emerging and endemic viral threats.Frontiers in pharmacology · 2026Review
- Structure-based design of anticancer drugs based on β-elemene: Research foundations and development potential.Journal of pharmaceutical analysis · 2025Review
- Progress of AI-Driven Drug-Target Interaction Prediction and Lead Optimization.International journal of molecular sciences · 2025Review
- Leveraging artificial intelligence and machine learning in kinase inhibitor development: advances, challenges, and future prospects.RSC medicinal chemistry · 2025Review
- PepLand: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids.Briefings in bioinformatics · 2025Article
- A 3D pocket-aware lead optimization model with knowledge guidance and its application for discovery of new glutaminyl cyclase inhibitors.Briefings in bioinformatics · 2025Article
- Bridging chemical space and biological efficacy: advances and challenges in applying generative models in structural modification of natural products.Natural products and bioprospecting · 2025Review
- Moldrug algorithm for an automated ligand binding site exploration by 3D aware molecular enumerations.Journal of cheminformatics · 2025Article
- Active learning driven prioritisation of compounds from on-demand libraries targeting the SARS-CoV-2 main protease.Digital discovery · 2025Article
- Interpretable adenylation domain specificity prediction using protein language models.bioRxiv : the preprint server for biology · 2025Article
- Design of RNA Polymerase Inhibitors as Therapeutics for Tuberculous Meningitis.Infectious disorders drug targets · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Machine learning has been increasingly applied to the field of computer-aided drug discovery in recent years, leading to notable advances in binding-affinity prediction, virtual screening, and QSAR. Surprisingly, it is less often applied to lead optimization, the process of identifying chemical fragments that might be added to a known ligand to improve its binding affinity. We here describe a deep convolutional neural network that predicts appropriate fragments given the structure of a receptor/ligand complex. In an independent benchmark of known ligands with missing (deleted) fragments, our DeepFrag model selected the known (correct) fragment from a set over 6500 about 58% of the time. Even when the known/correct fragment was not selected, the top fragment was often chemically similar and may well represent a valid substitution. We release our trained DeepFrag model and associated software under the terms of the Apache License, Version 2.0.
Identifiers
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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.