ArticleFrontiers in molecular biosciences2022
PASSer2.0: Accurate Prediction of Protein Allosteric Sites Through Automated Machine Learning.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- A systematic evaluation of protein allosteric site prediction tools with independent datasets.Journal of computer-aided molecular design · 2026Article
- AI-Driven Design of Miniproteins as Potential Allosteric Modulators.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Derivatives of the Cashew Nut Shell Liquid as Ligands ofACS omega · 2025Article
- Novel in silico Evidence of Bisphenol A as a Neuroinflammatory Modulator through the cGAS-STING-NLRP3 Pathway.Neurotoxicity research · 2025Article
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- 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
- Decoding allosteric landscapes: computational methodologies for enzyme modulation and drug discovery.RSC chemical biology · 2025Review
- 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
- The value of protein allostery in rational anticancer drug design: an update.Expert opinion on drug discovery · 2024Review
- Reinforcing Tunnel Network Exploration in Proteins Using Gaussian Accelerated Molecular Dynamics.Journal of chemical information and modeling · 2024Article
- Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking.International journal of molecular sciences · 2024Article
- PASSerRank: Prediction of allosteric sites with learning to rank.Journal of computational chemistry · 2023Article
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- 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
- AlphaFold, allosteric, and orthosteric drug discovery: Ways forward.Drug discovery today · 2023Review
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Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Allostery is a fundamental process in regulating protein activities. The discovery, design, and development of allosteric drugs demand better identification of allosteric sites. Several computational methods have been developed previously to predict allosteric sites using static pocket features and protein dynamics. Here, we define a baseline model for allosteric site prediction and present a computational model using automated machine learning. Our model, PASSer2.0, advanced the previous results and performed well across multiple indicators with 82.7% of allosteric pockets appearing among the top three positions. The trained machine learning model has been integrated with the Protein Allosteric Sites Server (PASSer) to facilitate allosteric drug discovery.
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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.