ArticleMachine learning: science and technology2021
PASSer: Prediction of Allosteric Sites Server.
Article in Machine learning: science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature.Frontiers in medicine · 2025Pooled it
- Uncovering hidden druggable sites: computational approaches to allosteric and cryptic pocket discovery-from molecular dynamics to AI.Journal of computer-aided molecular design · 2026Review
- RinPy, a Python Package for Residue Interaction Network Model to Analyze Protein Structures and Predict Ligand Binding Sites.Journal of chemical information and modeling · 2026Article
- Breaking glycolysis: allosteric hotspots for multi-target drug repurposing.Journal of computer-aided molecular design · 2026Article
- AI-Driven Design of Miniproteins as Potential Allosteric Modulators.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Interrelational Proteomic Sequence Features Enhance Predictive Modeling: Application to COVID-19 Severity.Biomedicines · 2026Article
- Resistance to Allosteric Inhibitors.Journal of molecular biology · 2025Review
- STINGAllo: a web server for high-throughput prediction of allosteric site-forming residues using internal protein nanoenvironment descriptors.Briefings in bioinformatics · 2025Article
- DeepAllo: allosteric site prediction using protein language model (pLM) with multitask learning.Bioinformatics (Oxford, England) · 2025Article
- AlloBench: A Data Set Pipeline for the Development and Benchmarking of Allosteric Site Prediction Tools.ACS omega · 2025Article
- Role of artificial intelligence in revolutionizing drug discovery.Fundamental research · 2025Review
- Decoding allosteric landscapes: computational methodologies for enzyme modulation and drug discovery.RSC chemical biology · 2025Review
- Allosteric modulation of Plasmodium falciparum Isoleucyl tRNA synthetase by South African natural compounds.PloS one · 2025Article
- Protein allosteric site identification using machine learning and per amino acid residue reported internal protein nanoenvironment descriptors.Computational and structural biotechnology journal · 2024Article
- MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model.Journal of cheminformatics · 2024Article
- Favipiravir Analogues as Inhibitors of SARS-CoV-2 RNA-Dependent RNA Polymerase, Combined Quantum Chemical Modeling, Quantitative Structure-Property Relationship, and Molecular Docking Study.Molecules (Basel, Switzerland) · 2024Article
- PASSerRank: Prediction of allosteric sites with learning to rank.Journal of computational chemistry · 2023Article
- Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variant Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms.Journal of chemical information and modeling · 2023Article
- PASSer: fast and accurate prediction of protein allosteric sites.Nucleic acids research · 2023Article
- Combining structural and coevolution information to unveil allosteric sites.Chemical science · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Allostery is considered important in regulating protein's activity. Drug development depends on the understanding of allosteric mechanisms, especially the identification of allosteric sites, which is a prerequisite in drug discovery and design. Many computational methods have been developed for allosteric site prediction using pocket features and protein dynamics. Here, we present an ensemble learning method, consisting of eXtreme gradient boosting (XGBoost) and graph convolutional neural network (GCNN), to predict allosteric sites. Our model can learn physical properties and topology without any
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.