228 related articles for article (PubMed ID: 31034213)
1. Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization.
Ustach VD; Lakkaraju SK; Jo S; Yu W; Jiang W; MacKerell AD
J Chem Inf Model; 2019 Jun; 59(6):3018-3035. PubMed ID: 31034213
[TBL] [Abstract][Full Text] [Related]
2. Rapid and accurate estimation of protein-ligand relative binding affinities using site-identification by ligand competitive saturation.
Goel H; Hazel A; Ustach VD; Jo S; Yu W; MacKerell AD
Chem Sci; 2021 Jul; 12(25):8844-8858. PubMed ID: 34257885
[TBL] [Abstract][Full Text] [Related]
3. Inclusion of multiple fragment types in the site identification by ligand competitive saturation (SILCS) approach.
Raman EP; Yu W; Lakkaraju SK; MacKerell AD
J Chem Inf Model; 2013 Dec; 53(12):3384-98. PubMed ID: 24245913
[TBL] [Abstract][Full Text] [Related]
4. Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations.
Mousaei M; Kudaibergenova M; MacKerell AD; Noskov S
J Chem Inf Model; 2020 Dec; 60(12):6489-6501. PubMed ID: 33196188
[TBL] [Abstract][Full Text] [Related]
5. Reproducing crystal binding modes of ligand functional groups using Site-Identification by Ligand Competitive Saturation (SILCS) simulations.
Raman EP; Yu W; Guvench O; Mackerell AD
J Chem Inf Model; 2011 Apr; 51(4):877-96. PubMed ID: 21456594
[TBL] [Abstract][Full Text] [Related]
6. Computational fragment-based binding site identification by ligand competitive saturation.
Guvench O; MacKerell AD
PLoS Comput Biol; 2009 Jul; 5(7):e1000435. PubMed ID: 19593374
[TBL] [Abstract][Full Text] [Related]
7. Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots).
MacKerell AD; Jo S; Lakkaraju SK; Lind C; Yu W
Biochim Biophys Acta Gen Subj; 2020 Apr; 1864(4):129519. PubMed ID: 31911242
[TBL] [Abstract][Full Text] [Related]
8. Site Identification by Ligand Competitive Saturation (SILCS) simulations for fragment-based drug design.
Faller CE; Raman EP; MacKerell AD; Guvench O
Methods Mol Biol; 2015; 1289():75-87. PubMed ID: 25709034
[TBL] [Abstract][Full Text] [Related]
9. 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.
Raman EP; Lakkaraju SK; Denny RA; MacKerell AD
J Comput Chem; 2017 Jun; 38(15):1238-1251. PubMed ID: 27782307
[TBL] [Abstract][Full Text] [Related]
10. Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation.
Yu W; Weber DJ; MacKerell AD
J Chem Theory Comput; 2023 May; 19(10):3007-3021. PubMed ID: 37115781
[TBL] [Abstract][Full Text] [Related]
11. SILCS-RNA: Toward a Structure-Based Drug Design Approach for Targeting RNAs with Small Molecules.
Kognole AA; Hazel A; MacKerell AD
J Chem Theory Comput; 2022 Sep; 18(9):5672-5691. PubMed ID: 35913731
[TBL] [Abstract][Full Text] [Related]
12. Exploring protein-protein interactions using the site-identification by ligand competitive saturation methodology.
Yu W; Jo S; Lakkaraju SK; Weber DJ; MacKerell AD
Proteins; 2019 Apr; 87(4):289-301. PubMed ID: 30582220
[TBL] [Abstract][Full Text] [Related]
13. Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design.
Goel H; Hazel A; Yu W; Jo S; MacKerell AD
New J Chem; 2022 Jan; 46(3):919-932. PubMed ID: 35210743
[TBL] [Abstract][Full Text] [Related]
14. Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling.
Yu W; Lakkaraju SK; Raman EP; MacKerell AD
J Comput Aided Mol Des; 2014 May; 28(5):491-507. PubMed ID: 24610239
[TBL] [Abstract][Full Text] [Related]
15. Pharmacophore modeling using site-identification by ligand competitive saturation (SILCS) with multiple probe molecules.
Yu W; Lakkaraju SK; Raman EP; Fang L; MacKerell AD
J Chem Inf Model; 2015 Feb; 55(2):407-20. PubMed ID: 25622696
[TBL] [Abstract][Full Text] [Related]
16. Computational Characterization of Antibody-Excipient Interactions for Rational Excipient Selection Using the Site Identification by Ligand Competitive Saturation-Biologics Approach.
Jo S; Xu A; Curtis JE; Somani S; MacKerell AD
Mol Pharm; 2020 Nov; 17(11):4323-4333. PubMed ID: 32965126
[TBL] [Abstract][Full Text] [Related]
17. Mapping functional group free energy patterns at protein occluded sites: nuclear receptors and G-protein coupled receptors.
Lakkaraju SK; Yu W; Raman EP; Hershfeld AV; Fang L; Deshpande DA; MacKerell AD
J Chem Inf Model; 2015 Mar; 55(3):700-8. PubMed ID: 25692383
[TBL] [Abstract][Full Text] [Related]
18. Machine learning in computational docking.
Khamis MA; Gomaa W; Ahmed WF
Artif Intell Med; 2015 Mar; 63(3):135-52. PubMed ID: 25724101
[TBL] [Abstract][Full Text] [Related]
19. Site-Specific Fragment Identification Guided by Single-Step Free Energy Perturbation Calculations.
Raman EP; Vanommeslaeghe K; Mackerell AD
J Chem Theory Comput; 2012 Oct; 8(10):3513-3525. PubMed ID: 23144598
[TBL] [Abstract][Full Text] [Related]
20. Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose.
Cleves AE; Jain AN
J Comput Aided Mol Des; 2018 Jul; 32(7):731-757. PubMed ID: 29934750
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
