ArticleJournal of chemical information and modeling2015
Pharmacophore modeling using site-identification by ligand competitive saturation (SILCS) with multiple probe molecules.
Article in Journal of chemical information and modeling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- Drude SILCS-Nucleic: harnessing explicit electronic polarization in targeting RNA and DNA for drug design.Nucleic acids research · 2026Article
- Targeting conserved domains of hypoxia-inducible factors for cancer therapy.The Journal of experimental medicine · 2026Article
- Computational Modeling of PROTAC Ternary Complexes as Ensembles Using SILCS-xTAC.Journal of chemical information and modeling · 2026Article
- Drude SILCS-Nucleic: Harnessing Explicit Electronic Polarization in Targeting RNA and DNA for Drug Design.bioRxiv : the preprint server for biology · 2025Article
- Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation.Journal of chemical information and modeling · 2025Article
- Article
- 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
- Cosolvent Molecular Dynamics Applied to DPP4, DPP8 and DPP9: Reproduction of Important Binding Features and Use in Inhibitor Design.Journal of chemical information and modeling · 2024Article
- Article
- PharmRL: Pharmacophore elucidation with Deep Geometric Reinforcement Learning.Research square · 2024Article
- Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms.The journal of physical chemistry. B · 2024Article
- In silico assessment of biocompatibility and toxicity: molecular docking and dynamics simulation of PMMA-based dental materials for interim prosthetic restorations.Journal of materials science. Materials in medicine · 2024Article
- Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART).Journal of cheminformatics · 2024Article
- Structural and thermodynamic framework for PIEZO1 modulation by small molecules.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- GPU-specific algorithms for improved solute sampling in grand canonical Monte Carlo simulations.Journal of computational chemistry · 2023Article
- Article
- 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
- Nitro-benzylideneoxymorphone, a bifunctional mu and delta opioid receptor ligand with high mu opioid receptor efficacy.Frontiers in pharmacology · 2023Article
- Computer-Aided Drug Design: An Update.Methods in molecular biology (Clifton, N.J.) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues, as SILCS naturally takes both protein flexibility and desolvation effects into account by using full molecular dynamics simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results, as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, reranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design.
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