ArticleScientific reports2021
Identification of novel inhibitors of Keap1/Nrf2 by a promising method combining protein-protein interaction-oriented library and machine learning.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 20 citations in OpenAlex.
- The Evolution of Machine Learning in Medicinal Chemistry: A Comprehensive Bibliometric Analysis.Current neuropharmacology · 2026Review
- Integrated strategy for screening direct Keap1-Nrf2 PPI inhibitors from traditional Chinese medicine: a case study of Achyranthis bidentatae Radix.Journal of computer-aided molecular design · 2025Article
- Hybridisation of in silico and in vitro bioassays for studying the activation of Nrf2 by natural compounds.Scientific reports · 2024Article
- Application of Fluorescence- and Bioluminescence-Based Biosensors in Cancer Drug Discovery.Biosensors · 2024Review
- Article
- Generating Potential Protein-Protein Interaction Inhibitor Molecules Based on Physicochemical Properties.Molecules (Basel, Switzerland) · 2023Article
- The Complex Genetic and Epigenetic Regulation of the Nrf2 Pathways: A Review.Antioxidants (Basel, Switzerland) · 2023Review
- KEAP1-NRF2 protein-protein interaction inhibitors: Design, pharmacological properties and therapeutic potential.Medicinal research reviews · 2023Review
- Manipulating autophagic degradation in human diseases: from mechanisms to interventions.Life medicine · 2022Review
- DLiP-PPI library: An integrated chemical database of small-to-medium-sized molecules targeting protein-protein interactions.Frontiers in chemistry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein-protein interactions (PPIs) are prospective but challenging targets for drug discovery, because screening using traditional small-molecule libraries often fails to identify hits. Recently, we developed a PPI-oriented library comprising 12,593 small-to-medium-sized newly synthesized molecules. This study validates a promising combined method using PPI-oriented library and ligand-based virtual screening (LBVS) to discover novel PPI inhibitory compounds for Kelch-like ECH-associated protein 1 (Keap1) and nuclear factor erythroid 2-related factor 2 (Nrf2). We performed LBVS with two random forest models against our PPI library and the following time-resolved fluorescence resonance energy transfer (TR-FRET) assays of 620 compounds identified 15 specific hit compounds. The high hit rates for the entire PPI library (estimated 0.56-1.3%) and the LBVS (maximum 5.4%) compared to a conventional screening library showed the utility of the library and the efficiency of LBVS. All the hit compounds possessed novel structures with Tanimoto similarity ≤ 0.26 to known Keap1/Nrf2 inhibitors and aqueous solubility (AlogP < 5). Reasonable binding modes were predicted using 3D alignment of five hit compounds and a Keap1/Nrf2 peptide crystal structure. Our results represent a new, efficient method combining the PPI library and LBVS to identify novel PPI inhibitory ligands with expanded chemical space.
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.