ArticleProteins2010
Real-time ligand binding pocket database search using local surface descriptors.
Article in Proteins, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- SHREC 2025: Protein surface shape retrieval including electrostatic potential.Computers & graphics · 2025Article
- Article
- ContactPFP: Protein function prediction using predicted contact information.Frontiers in bioinformatics · 2022Article
- ZEAL: protein structure alignment based on shape similarity.Bioinformatics (Oxford, England) · 2021Article
- Quantitative Description of Surface Complementarity of Antibody-Antigen Interfaces.Frontiers in molecular biosciences · 2021Article
- 2D Zernike polynomial expansion: Finding the protein-protein binding regions.Computational and structural biotechnology journal · 2021Article
- Quantitative Characterization of Binding Pockets and Binding Complementarity by Means of Zernike Descriptors.Journal of chemical information and modeling · 2020Article
- Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0.Journal of computer-aided molecular design · 2019Article
- Three-Dimensional Krawtchouk Descriptors for Protein Local Surface Shape Comparison.Pattern recognition · 2019Article
- A Novel Geometry-Based Approach to Infer Protein Interface Similarity.Scientific reports · 2018Article
- Large-scale computational drug repositioning to find treatments for rare diseases.NPJ systems biology and applications · 2018Article
- Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery.Frontiers in chemistry · 2018Review
- Protein 3D Structure and Electron Microscopy Map Retrieval Using 3D-SURFER2.0 and EM-SURFER.Current protocols in bioinformatics · 2017Article
- Discovery of Nicotinamide Adenine Dinucleotide Binding Proteins in the Escherichia coli Proteome Using a Combined Energetic- and Structural-Bioinformatics-Based Approach.Journal of proteome research · 2017Article
- PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation.Journal of chemical information and modeling · 2016Article
- DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.Journal of medicinal chemistry · 2016Article
- PatchSurfers: Two methods for local molecular property-based binding ligand prediction.Methods (San Diego, Calif.) · 2016Article
- Considerations of Protein Subpockets in Fragment-Based Drug Design.Chemical biology & drug design · 2016Article
- Navigating 3D electron microscopy maps with EM-SURFER.BMC bioinformatics · 2015Article
- Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0.Bioinformatics (Oxford, England) · 2015Article
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Authors and funding
3 authors.
Funding
Abstract
Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.
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