ArticleACS central science2018
Chemical Space Expansion of Bromodomain Ligands Guided by in Silico Virtual Couplings (AutoCouple).
Article in ACS central science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 37 citations in OpenAlex.
- Selective CBP/EP300 Bromodomain Inhibitors: Novel Epigenetic Tools to Counter TNF-α-Driven Inflammation.JACS Au · 2025Article
- The physics-AI dialogue in drug design.RSC medicinal chemistry · 2025Review
- Article
- ChemoDOTS: a web server to design chemistry-driven focused libraries.Nucleic acids research · 2024Article
- Recent Advances in Automated Structure-Based De Novo Drug Design.Journal of chemical information and modeling · 2024Review
- Discovery and Characterization of Active CBP/EP300 Degraders Targeting the HAT Domain.ACS medicinal chemistry letters · 2024Article
- ASD2023: towards the integrating landscapes of allosteric knowledgebase.Nucleic acids research · 2024Article
- Hitting a Moving Target: Simulation and Crystallography Study of ATAD2 Bromodomain Blockers.ACS medicinal chemistry letters · 2020Article
- CReM: chemically reasonable mutations framework for structure generation.Journal of cheminformatics · 2020Article
- Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots).Biochimica et biophysica acta. General subjects · 2020Article
- Binding mode information improves fragment docking.Journal of cheminformatics · 2019Article
- Binding Motifs in the CBP Bromodomain: An Analysis of 20 Crystal Structures of Complexes with Small Molecules.ACS medicinal chemistry letters · 2018Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Expanding the chemical space and simultaneously ensuring synthetic accessibility is of upmost importance, not only for the discovery of effective binders for novel protein classes but, more importantly, for the development of compounds against hard-to-drug proteins. Here, we present AutoCouple, a de novo approach to computational ligand design focused on the diversity-oriented generation of chemical entities via virtual couplings. In a benchmark application, chemically diverse compounds with low-nanomolar potency for the CBP bromodomain and high selectivity against the BRD4(1) bromodomain were achieved by the synthesis of about 50 derivatives of the original fragment. The binding mode was confirmed by X-ray crystallography, target engagement in cells was demonstrated, and antiproliferative activity was showcased in three cancer cell lines. These results reveal AutoCouple as a useful in silico coupling method to expand the chemical space in hit optimization campaigns resulting in potent, selective, and cell permeable bromodomain ligands.
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.