ReviewCurrent research in structural biology2022
Structure-based virtual screening for PDL1 dimerizers: Evaluating generic scoring functions.
Review in Current research in structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 12 citations in OpenAlex.
- The Evolution of Machine Learning in Medicinal Chemistry: A Comprehensive Bibliometric Analysis.Current neuropharmacology · 2026Review
- HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors.Journal of cheminformatics · 2025Article
- Rag2Mol: structure-based drug design based on retrieval augmented generation.Briefings in bioinformatics · 2025Article
- An ANI-2 enabled open-source protocol to estimate ligand strain after docking.Journal of computational chemistry · 2025Article
- Inactive-enriched machine-learning models exploiting patent data improve structure-based virtual screening for PDL1 dimerizers.Journal of advanced research · 2025Article
- Multiscale topology-enabled structure-to-sequence transformer for protein-ligand interaction predictions.Nature machine intelligence · 2024Article
- Inhibitors of Immune Checkpoints: Small Molecule- and Peptide-Based Approaches.Journal of personalized medicine · 2024Review
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
- A generalized protein-ligand scoring framework with balanced scoring, docking, ranking and screening powers.Chemical science · 2023Article
- Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader Comparisons.Journal of chemical information and modeling · 2023Article
- Targeted Drug Delivery Systems for Curcumin in Breast Cancer Therapy.International journal of nanomedicine · 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
The interaction between PD1 and its ligand PDL1 has been shown to render tumor cells resistant to apoptosis and promote tumor progression. An innovative mechanism to inhibit the PD1/PDL1 interaction is PDL1 dimerization induced by small-molecule PDL1 binders. Structure-based virtual screening is a promising approach to discovering such small-molecule PD1/PDL1 inhibitors. Here we investigate which type of generic scoring functions is most suitable to tackle this problem. We consider CNN-Score, an ensemble of convolutional neural networks, as the representative of machine-learning scoring functions. We also evaluate Smina, a commonly used classical scoring function, and IFP, a top structural fingerprint similarity scoring function. These three types of scoring functions were evaluated on two test sets sharing the same set of small-molecule PD1/PDL1 inhibitors, but using different types of inactives: either true inactives (molecules with no
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.