ArticleNature communications2024
In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Automated pharmacophore hypothesis generator for SILCS-Pharm: ph4gen.Journal of computer-aided molecular design · 2026Article
- Targeting the RNA-Binding Site of SARS-CoV-2 NSP13 by FRASE-bot in CACHE Challenge #2.Journal of chemical information and modeling · 2026Article
- The Last Mile Problem: A Critical Assessment of Physics-Based and AI Tools for Small Molecule Binding Prediction in Virtual Screening.Journal of chemical information and modeling · 2026Article
- Generative AI in structure-based drug discovery.BMC biology · 2026Review
- Leveraging large language models for literature-driven prioritization of protein binding pockets.Bioinformatics (Oxford, England) · 2025Article
- The Diverse Functions of the Calcium- and Integrin-Binding Protein Family.International journal of molecular sciences · 2025Review
- In silico fragment-based discovery of CIB1-directed anti-tumor agents by FRASE-bot.Nature communications · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
Chemical probes are an indispensable tool for translating biological discoveries into new therapies, though are increasingly difficult to identify since novel therapeutic targets are often hard-to-drug proteins. We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets. FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE). The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments. A neural network model is used to retain fragments with the highest likelihood of being native binders. The seeded fragments then inform ultra-large-scale virtual screening of commercially available compounds. We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1), a promising drug target implicated in triple negative breast cancer. FRASE-based virtual screening identifies a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay) showing specific cell-killing activity in CIB1-dependent cancer cells, but not in CIB1-depletion-insensitive cells.
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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.