124 related articles for article (PubMed ID: 29768914)
1. Exploring Cryptic Pockets Formation in Targets of Pharmaceutical Interest with SWISH.
Comitani F; Gervasio FL
J Chem Theory Comput; 2018 Jun; 14(6):3321-3331. PubMed ID: 29768914
[TBL] [Abstract][Full Text] [Related]
2. Understanding Cryptic Pocket Formation in Protein Targets by Enhanced Sampling Simulations.
Oleinikovas V; Saladino G; Cossins BP; Gervasio FL
J Am Chem Soc; 2016 Nov; 138(43):14257-14263. PubMed ID: 27726386
[TBL] [Abstract][Full Text] [Related]
3. SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein-Protein Interfaces.
Borsatto A; Gianquinto E; Rizzi V; Gervasio FL
J Chem Theory Comput; 2024 Apr; 20(8):3335-3348. PubMed ID: 38563746
[TBL] [Abstract][Full Text] [Related]
4. Small Glycols Discover Cryptic Pockets on Proteins for Fragment-Based Approaches.
Bansia H; Mahanta P; Yennawar NH; Ramakumar S
J Chem Inf Model; 2021 Mar; 61(3):1322-1333. PubMed ID: 33570386
[TBL] [Abstract][Full Text] [Related]
5. Niemann-Pick type C disease: a QM/MM study of conformational changes in cholesterol in the NPC1(NTD) and NPC2 binding pockets.
Elghobashi-Meinhardt N
Biochemistry; 2014 Oct; 53(41):6603-14. PubMed ID: 25251378
[TBL] [Abstract][Full Text] [Related]
6. Exploring protein kinase conformation using swarm-enhanced sampling molecular dynamics.
Atzori A; Bruce NJ; Burusco KK; Wroblowski B; Bonnet P; Bryce RA
J Chem Inf Model; 2014 Oct; 54(10):2764-75. PubMed ID: 25178116
[TBL] [Abstract][Full Text] [Related]
7. Investigating Cryptic Binding Sites by Molecular Dynamics Simulations.
Kuzmanic A; Bowman GR; Juarez-Jimenez J; Michel J; Gervasio FL
Acc Chem Res; 2020 Mar; 53(3):654-661. PubMed ID: 32134250
[TBL] [Abstract][Full Text] [Related]
8. Exploring the structural origins of cryptic sites on proteins.
Beglov D; Hall DR; Wakefield AE; Luo L; Allen KN; Kozakov D; Whitty A; Vajda S
Proc Natl Acad Sci U S A; 2018 Apr; 115(15):E3416-E3425. PubMed ID: 29581267
[TBL] [Abstract][Full Text] [Related]
9. CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites.
Cimermancic P; Weinkam P; Rettenmaier TJ; Bichmann L; Keedy DA; Woldeyes RA; Schneidman-Duhovny D; Demerdash ON; Mitchell JC; Wells JA; Fraser JS; Sali A
J Mol Biol; 2016 Feb; 428(4):709-719. PubMed ID: 26854760
[TBL] [Abstract][Full Text] [Related]
10. Cosolvent-Enhanced Sampling and Unbiased Identification of Cryptic Pockets Suitable for Structure-Based Drug Design.
Schmidt D; Boehm M; McClendon CL; Torella R; Gohlke H
J Chem Theory Comput; 2019 May; 15(5):3331-3343. PubMed ID: 30998331
[TBL] [Abstract][Full Text] [Related]
11. Rapid identification of ligand-binding sites by using an assignment-free NMR approach.
Kodama Y; Takeuchi K; Shimba N; Ishikawa K; Suzuki E; Shimada I; Takahashi H
J Med Chem; 2013 Nov; 56(22):9342-50. PubMed ID: 24171460
[TBL] [Abstract][Full Text] [Related]
12. PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations.
Martinez-Rosell G; Lovera S; Sands ZA; De Fabritiis G
J Chem Inf Model; 2020 Apr; 60(4):2314-2324. PubMed ID: 32175736
[TBL] [Abstract][Full Text] [Related]
13. Identification of Potential Small Molecule Binding Pockets in p38α MAP Kinase.
Gomez-Gutierrez P; Rubio-Martinez J; Perez JJ
J Chem Inf Model; 2017 Oct; 57(10):2566-2574. PubMed ID: 28872880
[TBL] [Abstract][Full Text] [Related]
14. Identification of a Novel Inhibitory Allosteric Site in p38α.
Gomez-Gutierrez P; Campos PM; Vega M; Perez JJ
PLoS One; 2016; 11(11):e0167379. PubMed ID: 27898710
[TBL] [Abstract][Full Text] [Related]
15. Cryptic Pockets Repository through Pocket Dynamics Tracking and Metadynamics on Essential Dynamics Space: Applications to Mcl-1.
Benabderrahmane M; Bureau R; Voisin-Chiret AS; Santos JSO
J Chem Inf Model; 2021 Nov; 61(11):5581-5588. PubMed ID: 34748701
[TBL] [Abstract][Full Text] [Related]
16. Kinase in motion: insights into the dynamic nature of p38α by high-pressure NMR spectroscopic studies.
Nielsen G; Jonker HR; Vajpai N; Grzesiek S; Schwalbe H
Chembiochem; 2013 Sep; 14(14):1799-806. PubMed ID: 23843149
[TBL] [Abstract][Full Text] [Related]
17. Cryptic binding sites on proteins: definition, detection, and druggability.
Vajda S; Beglov D; Wakefield AE; Egbert M; Whitty A
Curr Opin Chem Biol; 2018 Jun; 44():1-8. PubMed ID: 29800865
[TBL] [Abstract][Full Text] [Related]
18. 3D matched pairs: integrating ligand- and structure-based knowledge for ligand design and receptor annotation.
Posy SL; Claus BL; Pokross ME; Johnson SR
J Chem Inf Model; 2013 Jul; 53(7):1576-88. PubMed ID: 23809058
[TBL] [Abstract][Full Text] [Related]
19. Computational studies of the cholesterol transport between NPC2 and the N-terminal domain of NPC1 (NPC1(NTD)).
Estiu G; Khatri N; Wiest O
Biochemistry; 2013 Oct; 52(39):6879-91. PubMed ID: 24001314
[TBL] [Abstract][Full Text] [Related]
20. Accelerated Ligand-Mapping Molecular Dynamics Simulations for the Detection of Recalcitrant Cryptic Pockets and Occluded Binding Sites.
Tze-Yang Ng J; Tan YS
J Chem Theory Comput; 2022 Mar; 18(3):1969-1981. PubMed ID: 35175753
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]