ArticleJournal of computational chemistry2017
Estimation of relative free energies of binding using pre-computed ensembles based on the single-step free energy perturbation and the site-identification by Ligand competitive saturation approaches.
Article in Journal of computational chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Review
- CDK2 Allosteric Modulators: The New Route in the Design of New Drugs as Anticancer and Non-hormonal Contraceptives.Current medicinal chemistry · 2025Review
- Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms.The journal of physical chemistry. B · 2024Article
- Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction.Molecular pharmaceutics · 2023Article
- Nitro-benzylideneoxymorphone, a bifunctional mu and delta opioid receptor ligand with high mu opioid receptor efficacy.Frontiers in pharmacology · 2023Article
- hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties.Chemistry (Basel, Switzerland) · 2022Article
- Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.1].Living journal of computational molecular science · 2022Article
- Insights into substrate recognition and specificity for IgG by Endoglycosidase S2.PLoS computational biology · 2021Article
- Functional Group Distributions, Partition Coefficients, and Resistance Factors in Lipid Bilayers Using Site Identification by Ligand Competitive Saturation.Journal of chemical theory and computation · 2021Article
- Toward Biotherapeutics Formulation Composition Engineering using Site-Identification by Ligand Competitive Saturation (SILCS).Journal of pharmaceutical sciences · 2021Article
- Computational Characterization of Antibody-Excipient Interactions for Rational Excipient Selection Using the Site Identification by Ligand Competitive Saturation-Biologics Approach.Molecular pharmaceutics · 2020Article
- Repulsive Soft-Core Potentials for Efficient Alchemical Free Energy Calculations.Journal of chemical theory and computation · 2020Article
- Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots).Biochimica et biophysica acta. General subjects · 2020Article
- Optimization of Protein-Ligand Electrostatic Interactions Using an Alchemical Free-Energy Method.Journal of chemical theory and computation · 2019Article
- Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization.Journal of chemical information and modeling · 2019Article
- Review
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4 authors.
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Abstract
Accurate and rapid estimation of relative binding affinities of ligand-protein complexes is a requirement of computational methods for their effective use in rational ligand design. Of the approaches commonly used, free energy perturbation (FEP) methods are considered one of the most accurate, although they require significant computational resources. Accordingly, it is desirable to have alternative methods of similar accuracy but greater computational efficiency to facilitate ligand design. In the present study relative free energies of binding are estimated for one or two non-hydrogen atom changes in compounds targeting the proteins ACK1 and p38 MAP kinase using three methods. The methods include standard FEP, single-step free energy perturbation (SSFEP) and the site-identification by ligand competitive saturation (SILCS) ligand grid free energy (LGFE) approach. Results show the SSFEP and SILCS LGFE methods to be competitive with or better than the FEP results for the studied systems, with SILCS LGFE giving the best agreement with experimental results. This is supported by additional comparisons with published FEP data on p38 MAP kinase inhibitors. While both the SSFEP and SILCS LGFE approaches require a significant upfront computational investment, they offer a 1000-fold computational savings over FEP for calculating the relative affinities of ligand modifications once those pre-computations are complete. An illustrative example of the potential application of these methods in the context of screening large numbers of transformations is presented. Thus, the SSFEP and SILCS LGFE approaches represent viable alternatives for actively driving ligand design during drug discovery and development. © 2016 Wiley Periodicals, Inc.
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