ArticleInternational journal of molecular sciences2014
PL-PatchSurfer: a novel molecular local surface-based method for exploring protein-ligand interactions.
Article in International journal of molecular sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Edge-aware GAT-based protein binding sites prediction.PLoS computational biology · 2026Article
- PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors.Journal of cheminformatics · 2026Article
- SHREC 2025: Protein surface shape retrieval including electrostatic potential.Computers & graphics · 2025Article
- Using AlphaFold and Symmetrical Docking to Predict Protein-Protein Interactions for Exploring Potential Crystallization Conditions.Proteins · 2025Article
- Article
- Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches.Frontiers in molecular biosciences · 2023Article
- Classification of Protein-Binding Sites Using a Spherical Convolutional Neural Network.Journal of chemical information and modeling · 2022Article
- Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0.Journal of computer-aided molecular design · 2019Article
- Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.BMC bioinformatics · 2018Article
- An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes.Scientific reports · 2017Article
- DeCAF-Discrimination, Comparison, Alignment Tool for 2D PHarmacophores.Molecules (Basel, Switzerland) · 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
- CSAR Benchmark Exercise 2013: Evaluation of Results from a Combined Computational Protein Design, Docking, and Scoring/Ranking Challenge.Journal of chemical information and modeling · 2016Article
- Combined Approach of Patch-Surfer and PL-PatchSurfer for Protein-Ligand Binding Prediction in CSAR 2013 and 2014.Journal of chemical information and modeling · 2016Article
- A pose prediction approach based on ligand 3D shape similarity.Journal of computer-aided molecular design · 2016Article
- PDID: database of molecular-level putative protein-drug interactions in the structural human proteome.Bioinformatics (Oxford, England) · 2016Article
- PatchSurfers: Two methods for local molecular property-based binding ligand prediction.Methods (San Diego, Calif.) · 2016Article
- Three-dimensional compound comparison methods and their application in drug discovery.Molecules (Basel, Switzerland) · 2015Review
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5 authors.
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Abstract
Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given protein based on their structural complementarity. Compared to other protein and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Here we developed a novel method named PL-PatchSurfer (Protein-Ligand PatchSurfer). PL-PatchSurfer represents the protein binding pocket and the ligand molecular surface as a combination of segmented surface patches. Each patch is characterized by its geometrical shape and the electrostatic potential, which are represented using the 3D Zernike descriptor (3DZD). We first tested PL-PatchSurfer on binding ligand prediction and found it outperformed the pocket-similarity based ligand prediction program. We then optimized the search algorithm of PL-PatchSurfer using the PDBbind dataset. Finally, we explored the utility of applying PL-PatchSurfer to a larger and more diverse dataset and showed that PL-PatchSurfer was able to provide a high early enrichment for most of the targets. To the best of our knowledge, PL-PatchSurfer is the first surface patch-based method that treats ligand complementarity at protein binding sites. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets.
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