ArticleProteins2019
Exploring protein-protein interactions using the site-identification by ligand competitive saturation methodology.
Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- Proteolysis Targeting Chimera (PROTAC) Linkerology Enhances the CDK-Degradation Selectivity Profile of a Multi-CDK Inhibitor: Discovery of Potent, Anti-Leukemic CDK9 Degraders.ACS pharmacology & translational science · 2026Article
- Computational Modeling of PROTAC Ternary Complexes as Ensembles Using SILCS-xTAC.Journal of chemical information and modeling · 2026Article
- Emerging Technologies and Integrated Interdisciplinary Strategies for Mitigating Protein Aggregation in Therapeutic Formulations.Pharmaceutical research · 2026Review
- Investigating the Interaction between Excipients and Monoclonal Antibodies PGT121 and N49P9.6-FR-LS: A Comprehensive Analysis.Molecular pharmaceutics · 2025Article
- Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation.Journal of chemical information and modeling · 2025Article
- Modeling Ligand Binding Site Water Networks with Site Identification by Ligand Competitive Saturation: Impact on Ligand Binding Orientations and Relative Binding Affinities.Journal of chemical theory and computation · 2024Article
- Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms.The journal of physical chemistry. B · 2024Article
- Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.Chemical reviews · 2024Review
- GPU-specific algorithms for improved solute sampling in grand canonical Monte Carlo simulations.Journal of computational chemistry · 2023Article
- Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation.Journal of chemical theory and computation · 2023Article
- Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction.Molecular pharmaceutics · 2023Article
- Computer-Aided Drug Design: An Update.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Docking-based long timescale simulation of cell-size protein systems at atomic resolution.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties.Chemistry (Basel, Switzerland) · 2022Article
- Mapping the binding sites of challenging drug targets.Current opinion in structural biology · 2022Review
- Efficient link prediction in the protein-protein interaction network using topological information in a generative adversarial network machine learning model.BMC bioinformatics · 2022Article
- Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design.New journal of chemistry = Nouveau journal de chimie · 2022Article
- Towards design of drugs and delivery systems with the Martini coarse-grained model.QRB discovery · 2022Review
- Rapid and accurate estimation of protein-ligand relative binding affinities using site-identification by ligand competitive saturation.Chemical science · 2021Article
- Toward Biotherapeutics Formulation Composition Engineering using Site-Identification by Ligand Competitive Saturation (SILCS).Journal of pharmaceutical sciences · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Protein docking methods are powerful computational tools to study protein-protein interactions (PPI). While a significant number of docking algorithms have been developed, they are usually based on rigid protein models or with limited considerations of protein flexibility and the desolvation effect is rarely considered in docking energy functions, which may lower the accuracy of the predictions. To address these issues, we introduce a PPI energy function based on the site-identification by ligand competitive saturation (SILCS) framework and utilize the fast Fourier transform (FFT) correlation approach. The free energy content of the SILCS FragMaps represent an alternative to traditional energy grids and they can be efficiently utilized to guide FFT-based protein docking. Application of the approach to eight diverse test cases, including seven from Protein Docking Benchmark 5.0, showed the PPI prediction using SILCS approach (SILCS-PPI) to be competitive with several commonly used protein docking methods indicating that the method has the ability to both qualitatively and quantitatively inform the prediction of PPI. Results show the utility of the SILCS-PPI docking approach for determination of probability distributions of PPI interactions over the surface of both partner proteins, allowing for identification of alternate binding poses. Such binding poses are confirmed by experimental crystal contacts in our test cases. While more computationally demanding than available PPI docking technologies, we anticipate that the SILCS-PPI docking approach will offer an alternative methodology for improved evaluation of PPIs that could be used in a variety of fields from systems biology to excipient design for biologics-based drugs.
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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.