ArticleJournal of computer-aided molecular design2019
Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies.
Article in Journal of computer-aided molecular design, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The Human Omnibus of Targetable Pockets.Journal of cheminformatics · 2025Article
- Role of Small Non-Coding RNA in Gram-Negative Bacteria: New Insights and Comprehensive Review of Mechanisms, Functions, and Potential Applications.Molecular biotechnology · 2025Review
- Databases of ligand-binding pockets and protein-ligand interactions.Computational and structural biotechnology journal · 2024Review
- Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning.Journal of cheminformatics · 2024Article
- Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023Review
- SiteFerret: Beyond Simple Pocket Identification in Proteins.Journal of chemical theory and computation · 2023Article
- CAT-Site: Predicting Protein Binding Sites Using a Convolutional Neural Network.Pharmaceutics · 2022Article
- Targeting protein conformations with small molecules to control protein complexes.Trends in biochemical sciences · 2022Review
- Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking.Journal of molecular liquids · 2022Article
- Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions.Briefings in bioinformatics · 2022Review
- CAVIAR: a method for automatic cavity detection, description and decomposition into subcavities.Journal of computer-aided molecular design · 2021Article
- A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0.International journal of molecular sciences · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the current "genomic era" the number of identified genes is growing exponentially. However, the biological function of a large number of the corresponding proteins is still unknown. Recognition of small molecule ligands (e.g., substrates, inhibitors, allosteric regulators, etc.) is pivotal for protein functions in the vast majority of the cases and knowledge of the region where these processes take place is essential for protein function prediction and drug design. In this regard, computational methods represent essential tools to tackle this problem. A significant number of software tools have been developed in the last few years which exploit either protein sequence information, structure information or both. This review describes the most recent developments in protein function recognition and binding site prediction, in terms of both freely-available and commercial solutions and tools, detailing the main characteristics of the considered tools and providing a comparative analysis of their performance.
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31628659What 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.