ArticleInternational journal of molecular sciences2021
Quantitative Estimate Index for Early-Stage Screening of Compounds Targeting Protein-Protein Interactions.
Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- IUPAC-GPT: an IUPAC-based large-scale molecular pre-trained model for property prediction and molecule generation.Molecular diversity · 2026Article
- RL-MSVP: Reinforcement Learning and Multi-scale Validation Pipeline Investigating Azole-Fused Pyrimidines as PotentialACS omega · 2025Article
- Integrated molecular and ADME-toxicity profiling identifies PGV-5 and HGV-5 as potential agents to counteract multidrug-resistant (MDR) cancer.Scientific reports · 2025Article
- Diffusion-based generative drug-like molecular editing with chemical natural language.Journal of pharmaceutical analysis · 2025Article
- Interface-aware molecular generative framework for protein-protein interaction modulators.Journal of cheminformatics · 2024Article
- Transformer-Based Molecular Generative Model for Antiviral Drug Design.Journal of chemical information and modeling · 2024Article
- Article
- Design of Cyclic Peptides Targeting Protein-Protein Interactions Using AlphaFold.International journal of molecular sciences · 2023Article
- Generating Potential Protein-Protein Interaction Inhibitor Molecules Based on Physicochemical Properties.Molecules (Basel, Switzerland) · 2023Article
- Fighting Antibiotic Resistance: New Pyrimidine-Clubbed Benzimidazole Derivatives as Potential DHFR Inhibitors.Molecules (Basel, Switzerland) · 2023Article
- Solubility-Aware Protein Binding Peptide Design Using AlphaFold.Biomedicines · 2022Article
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2 authors.
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Abstract
Drug-likeness quantification is useful for screening drug candidates. Quantitative estimates of drug-likeness (QED) are commonly used to assess quantitative drug efficacy but are not suitable for screening compounds targeting protein-protein interactions (PPIs), which have recently gained attention. Therefore, we developed a quantitative estimate index for compounds targeting PPIs (QEPPI), specifically for early-stage screening of PPI-targeting compounds. QEPPI is an extension of the QED method for PPI-targeting drugs that models physicochemical properties based on the information available for drugs/compounds, specifically those reported to act on PPIs. FDA-approved drugs and compounds in iPPI-DB, which comprise PPI inhibitors and stabilizers, were evaluated using QEPPI. The results showed that QEPPI is more suitable than QED for early screening of PPI-targeting compounds. QEPPI was also considered an extended concept of the "Rule-of-Four" (RO4), a PPI inhibitor index. We evaluated the discriminatory performance of QEPPI and RO4 for datasets of PPI-target compounds and FDA-approved drugs using F-score and other indices. The F-scores of RO4 and QEPPI were 0.451 and 0.501, respectively. QEPPI showed better performance and enabled quantification of drug-likeness for early-stage PPI drug discovery. Hence, it can be used as an initial filter to efficiently screen PPI-targeting compounds.
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