ArticleJournal of chemical information and modeling2021
DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Computational identification of potential inhibitors for chikungunya virus nsP2pro.Royal Society open science · 2026Article
- Article
- MolPIF: a parameter interpolation flow model for molecule generation.Bioinformatics (Oxford, England) · 2026Article
- Precision fragment addition: domain-specific DeepFrag2 models for smarter lead optimization.Digital discovery · 2026Article
- A 3D pocket-aware lead optimization model with knowledge guidance and its application for discovery of new glutaminyl cyclase inhibitors.Briefings in bioinformatics · 2025Article
- Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches.npj drug discovery · 2025Review
- Simulation- and AI-directed optimization of 4,6-substituted 1,3,5-triazin-2(1Computational and structural biotechnology journal · 2024Article
- MolModa: accessible and secure molecular docking in a web browser.Nucleic acids research · 2024Article
- Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening.Journal of chemical information and modeling · 2024Article
- Recent Deep Learning Applications to Structure-Based Drug Design.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Fragment-based drug discovery-the importance of high-quality molecule libraries.Molecular oncology · 2022Review
- Implementation of an AI-assisted fragment-generator in an open-source platform.RSC medicinal chemistry · 2022Article
- Prot2Prot: a deep learning model for rapid, photorealistic macromolecular visualization.Journal of computer-aided molecular design · 2022Article
- FPocketWeb: protein pocket hunting in a web browser.Journal of cheminformatics · 2022Article
- Open-Source Browser-Based Tools for Structure-Based Computer-Aided Drug Discovery.Molecules (Basel, Switzerland) · 2022Review
- BINANA 2: Characterizing Receptor/Ligand Interactions in Python and JavaScript.Journal of chemical information and modeling · 2022Article
- Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations.RSC advances · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Lead optimization, a critical step in early stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve properties such as binding affinity. We recently developed DeepFrag, a deep-learning model capable of recommending such modifications. Though a powerful hypothesis-generating tool, DeepFrag is currently implemented in Python and so requires a certain degree of computational expertise. To encourage broader adoption, we have created the DeepFrag browser app, which provides a user-friendly graphical user interface that runs the DeepFrag model in users' web browsers. The browser app does not require users to upload their molecular structures to a third-party server, nor does it require the separate installation of any third-party software. We are hopeful that the app will be a useful tool for both researchers and students. It can be accessed free of charge, without registration, at http://durrantlab.com/deepfrag. The source code is also available at http://git.durrantlab.com/jdurrant/deepfrag-app, released under the terms of the open-source Apache License, Version 2.0.
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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.