ReviewRSC medicinal chemistry2022
Recent applications of covalent chemistries in protein-protein interaction inhibitors.
Review in RSC medicinal chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 15 citations in OpenAlex.
- Targeting "undruggable" cancer proteins: pharmacological challenges and emerging strategies.Translational cancer research · 2026Review
- Protein structural dynamics in covalent drug design: insights from irreversible and reversible covalent inhibitors.RSC chemical biology · 2026Review
- Therapeutic Targeting of Protein Lysine and Arginine Methyltransferases: Principles and Strategies for Inhibitor Design.International journal of molecular sciences · 2025Review
- Razing the scaffolding: the elimination of non-catalytic functions of kinases through targeted protein degradation.RSC medicinal chemistry · 2025Review
- Advances in Cellular and Molecular Biology Assays: A Review of Gold Standard Methods.International journal of innovative science and research technology · 2025Article
- Deep learning-based discovery of compounds for blood pressure lowering effects.Scientific reports · 2025Article
- An Antiherpesviral Host-Directed Strategy Based on CDK7 Covalently Binding Drugs: Target-Selective, Picomolar-Dose, Cross-Virus Reactivity.Pharmaceutics · 2024Article
- Computational completion of the Aurora interaction region of N-Myc in the Aurora a kinase complex.Scientific reports · 2023Article
- Molecular Peptide Grafting as a Tool to Create Novel Protein Therapeutics.Molecules (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein-protein interactions (PPIs) are large, often featureless domains whose modulations by small-molecules are challenging. Whilst there are some notable successes, such as the BCL-2 inhibitor venetoclax, the requirement for larger ligands to achieve the desired level of potency and selectivity may result in poor "drug-like" properties. Covalent chemistry is presently enjoying a renaissance. In particular, targeted covalent inhibition (TCI), in which a weakly electrophilic "warhead" is installed onto a protein ligand scaffold, is a powerful strategy to develop potent inhibitors of PPIs that are smaller/more drug-like yet have enhanced affinities by virtue of the reinforcing effect on the existing non-covalent interactions by the resulting protein-ligand covalent bond. Furthermore, the covalent bond delivers sustained inhibition, which may translate into significantly reduced therapeutic dosing. Herein, we discuss recent applications of a spectrum of TCIs, as well as covalent screening strategies, in the discovery of more effective inhibitors of PPIs using the HDM2 and BCL-2 protein families as case studies.
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.