ArticleJournal of chemical information and modeling2010
Protein pockets: inventory, shape, and comparison.
Article in Journal of chemical information and modeling, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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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.
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Who cites it
38 citing papers in PubMed.
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- Gp8 mediates adsorption of bacteriophage vB_VpP_jzsmvpa to the host Vibrio parahaemolyticus.Antonie van Leeuwenhoek · 2026Article
- Novel Thermostable α-Amylase from Bacillus subtilis: Molecular Characterization, Optimization, and Docking-Based Substrate Profiling.The protein journal · 2026Article
- Specific and potent inhibition of steroid hormone pre-receptor regulator AKR1C2 by perfluorooctanoic acid: Implications for androgen metabolism.The Journal of steroid biochemistry and molecular biology · 2025Article
- Tri-chalcone suppressed breast cancer cell proliferation and induced apoptosis through intrinsic and extrinsic pathways.Naunyn-Schmiedeberg's archives of pharmacology · 2024Article
- Article
- Protein Structure Inspired Drug Discovery.bioRxiv : the preprint server for biology · 2024Article
- SiteFerret: Beyond Simple Pocket Identification in Proteins.Journal of chemical theory and computation · 2023Article
- Overcoming phenotypic switching: targeting protein-protein interactions in cancer.Exploration of targeted anti-tumor therapy · 2023Review
- Large-Scale Ligand Perturbations of the Protein Conformational Landscape Reveal State-Specific Interaction Hotspots.Journal of medicinal chemistry · 2022Article
- Genome-wide identification, comprehensive characterization of transcription factors, cis-regulatory elements, protein homology, and protein interaction network of DREB gene family inFrontiers in plant science · 2022Article
- Molecular docking-based computational platform for high-throughput virtual screening.CCF transactions on high performance computing · 2022Article
- Discovery of Novel Cyclic Salt Bridge in Thermophilic Bacterial Protease and Study of its Sequence and Structure.Applied biochemistry and biotechnology · 2021Article
- Therapeutic Potential of Novel Mastoparan-Chitosan Nanoconstructs Against Clinical MDRInternational journal of nanomedicine · 2021Article
- Article
- An enumerative algorithm for de novo design of proteins with diverse pocket structures.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Binding site matching in rational drug design: algorithms and applications.Briefings in bioinformatics · 2019Review
- High-Performance Analysis of Biomolecular Containers to Measure Small-Molecule Transport, Transbilayer Lipid Diffusion, and Protein Cavities.Journal of chemical information and modeling · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The shape of the protein surface dictates what interactions are possible with other macromolecules, but defining discrete pockets or possible interaction sites remains difficult. First, there is the problem of defining the extent of the pocket. Second, one has to characterize the shape of each pocket. Third, one needs to make quantitative comparisons between pockets on different proteins. An elegant solution to these problems is to sort all surface and solvent points by travel depth and then collect a hierarchical tree of pockets. The connectivity of the tree is determined via the deepest saddle points between each pair of neighboring pockets. The resulting pocket surfaces tessellate the entire protein surface, producing a complete inventory of pockets. This method of identifying pockets also allows one to easily compute important shape metrics, including the problematic pocket volume, surface area, and mouth size. Pockets are also annotated with their lining residue lists and polarity and with other residue-based properties. Using this tree and the various shape metrics pockets can be merged, grouped, or filtered for further analysis. Since this method includes the entire surface, it guarantees that any pocket of interest will be found among the output pockets, unlike all previous methods of pocket identification. The resulting hierarchy of pockets is easy to visualize and aids users in higher level analysis. Comparison of pockets is done by using the shape metrics, avoiding the complex shape alignment problem. Example applications show that the method facilitates pocket comparison along mutational or time-dependent series. Pockets from families of proteins can be examined using multiple pocket tree alignments to see how ligand binding sites or how other pockets have changed with evolution. Our method is called CLIPPERS for complete liberal inventory of protein pockets elucidating and reporting on shape.
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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.