In Silico docking, molecular dynamics and binding energy insights into the bolinaquinone-clathrin terminal domain binding site

Molecules

Volumn 19, Issue 5, 2014, Pages 6609-6622

  Abdel Hamid, Mohammed K ^a   McCluskey, Adam ^a  

^a UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

Bolinaquinone; Clathrin terminal domain; Flexible docking; Linear interaction energy

Indexed keywords

BOLINAQUINONE; CLATHRIN; SESQUITERPENE;

ANTAGONISTS AND INHIBITORS; BINDING SITE; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; DRUG DESIGN; METABOLISM; MOLECULAR DYNAMICS; PROTEIN TERTIARY STRUCTURE; STATIC ELECTRICITY;

BINDING SITES; CLATHRIN; COMPUTER SIMULATION; DRUG DESIGN; MODELS, MOLECULAR; MOLECULAR DYNAMICS SIMULATION; PROTEIN STRUCTURE, TERTIARY; SESQUITERPENES; STATIC ELECTRICITY;

EID: 84901425609     PISSN: None     EISSN: 14203049     Source Type: Journal    
DOI: 10.3390/molecules19056609     Document Type: Article

References (28)

1. Traub L.M. Tickets to ride: Selecting cargo for clathrin-regulated internalization. Nat. Rev. Mol. Cell Biol. 2009, 10, 583-596.
2. Von Kleist L.; Stahlschmidt W.; Bulut H.; Gromova K.; Puchkov D.; Robertson M.J.; MacGregor K.A.; Tomilin N.; Pechstein A.; Chau N.; et al. Role of the clathrin terminal domain in regulating coated pit dynamics revealed by small molecule inhibition. Cell 2011, 146, 471-484.
3. Miyauchi K.; Kim Y.; Latinovic O.; Morozov V.; Melikyan G.B. HIV enters cells via endocytosis and dynamin-dependent fusion with endosomes. Cell 2009, 137, 433-444.
4. Boettner D.R.; Chi R.J.; Lemmon S.K. Lessons from yeast for clathrin-mediated endocytosis. Nat. Cell Biol. 2011, 14, 2-10.
5. Saffarian S.; Cocucci E.; Kirchhausen T. Distinct dynamics of endocytic clathrin-coated pits and coated plaques. PLoS Biol. 2009, 7, e1000191.
6. Ohmori K.; Endo Y.; Yoshida Y.; Ohata H.; Taya Y.; Enari M. Monomeric but not trimeric clathrin heavy chain regulates p53-mediated transcription. Oncogene 2007, 27, 2215-2227.
7. Ohata H.; Ota N.; Shirouzu M.; Yokoyama S.; Yokota J.; Taya Y.; Enari M. Identification of a Function-Specific Mutation of Clathrin Heavy Chain (CHC) Required for p53 transactivation. J. Mol. Biol. 2009, 394, 460-471.
8. Endo Y.; Sugiyama A.; Li S.-A.; Ohmori K.; Ohata H.; Yoshida Y.; Shibuya M.; Takei K.; Enari M.; Taya Y. Regulation of clathrin-mediated endocytosis by p53. Gene Cell. 2008, 13, 375-386.
9. Nicot A.S.; Toussaint A.; Tosch V.; Kretz C.; Wallgren-Pettersson C.; Iwarsson E.; Kingston H.; Garnier J.M.; Biancalana V.; Oldfors A.; et al. Mutations in amphiphysin 2 (BIN1) disrupt interaction with dynamin 2 and cause autosomal recessive centronuclear myopathy. Nat. Genet. 2007, 39, 1134-1139.
10. MacGregor K.A.; Robertson M.J.; Young K.A.; von Kleist L.; Stahlschmidt W.; Whiting A.; Chau N.; Robinson P.J.; Haucke V.; McCluskey A. Development of 1, 8-naphthalimides as clathrin inhibitors. J. Med. Chem. 2013, 57, 131-143.
11. Margarucci L.; Monti M.C.; Fontanella B.; Riccio R.; Casapullo A. Chemical proteomics reveals bolinaquinone as a clathrin-mediated endocytosis inhibitor. Mol. BioSys. 2011, 7, 480-485.
12. De Guzman F.S.; Copp B.R.; Mayne C.L.; Concepcion G.P.; Mangalindan G.C.; Barrows L.R.; Ireland C.M. Bolinaquinone: A novel cytotoxic sesquiterpene hydroxyquinone from a Philippine Dysidea sponge. J. Org. Chem. 1998, 63, 8042-8044.
13. Morris G.M.; Huey R.; Lindstrom W.; Sanner M.F.; Belew R.K.; Goodsell D.S.; Olson A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comp. Chem. 2009, 30, 2785-2791.
14. Koska J.R.; Spassov V.Z.; Maynard A.J.; Yan L.; Austin N.; Flook P.K.; Venkatachalam C.M. Fully automated molecular mechanics based induced fit protein-ligand docking method. J. Chem. Inf. Mod. 2008, 48, 1965-1973.
15. Spassov V.Z.; Yan L.; Flook P.K. The dominant role of side-chain backbone interactions in structural realization of amino acid code. ChiRotor: A side-chain prediction algorithm based on side-chain backbone interactions. Prot. Sci. 2007, 16, 494-506.
16. Diller D.J.; Merz K.M. High throughput docking for library design and library prioritization. Proteins 2001, 43, 113-124.
17. Wu G.; Robertson D.H.; Brooks C.L.; Vieth M. Detailed analysis of grid-based molecular docking: A case study of CDOCKER-A CHARMm-based MD docking algorithm. J. Comp. Chem. 2003, 24, 1549-1562.
18. Pronk S.; Páll S.; Schulz R.; Larsson P.; Bjelkmar P.; Apostolov R.; Shirts M.R.; Smith J.C.; Kasson P.M.; van der Spoel D.; et al. GROMACS 4.5: A high-Throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 2013, 29, 845-854.
19. Schuttelkopf A.W.; van Aalten D.M.F. PRODRG: A tool for high-Throughput crystallography of protein-ligand complexes. Acta Cryst. Sect. D 2004, 60, 1355-1363.
20. Lemkul J.A.; Allen W.J.; Bevan D.R. Practical considerations for building GROMOScompatible small-molecule topologies. J. Chem. Inf. Model. 2010, 50, 2221-2235.
21. Carlsson J.; Boukharta L.; Åqvist J. Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase. J. Med. Chem. 2008, 51, 2648-2656.
22. Åqvist J.; Medina C.; Samuelsson J.-E. A new method for predicting binding affinity in computer-Aided drug design. Prot. Eng. 1994, 7, 385-391.
23. Gutiérrez-de-Terán H.; Åqvist J. Linear interaction energy: Method and applications in drug design. In Computational Drug Discovery and Design; Baron R., Ed.; Springer: New York, NY, USA, 2012; Volume 819, pp. 305-323.
24. Nicola G.; Smith C.A.; Abagyan R. New method for the assessment of all drug-like pockets across a structural genome. J. Comput. Biol. 2008, 15, 231-240.
25. Stehn J.R.; Haass N.K.; Bonello T.; Desouza M.; Kottyan G.; Treutlein H.; Zeng J.; Nascimento P.R.B.B.; Sequeira V.B.; Butler T.L.; et al. A novel class of anti cancer compounds which target the actin cytoskeleton of tumor cells. Can. Res. 2013, 73, 5169-5182.
26. Odell L.R.; Howan D.; Gordon C.P.; Robertson M.J.; Chau N.; Mariana A.; Whiting A.E.; Abagyan R.; Daniel J.A.; Gorgani N.N.; et al. The pthaladyns: GTP competitive inhibitors of dynamin I and II GTPase derived from virtual screening. J. Med. Chem. 2010, 53, 5267-5280.
27. Cheng T.; Li Q.; Zhou Z.; Wang Y.; Bryant S.H. Structure-based virtual screening for drug discovery: A problem-centric review. AAPS J. 2012, 14, 133-141.
28. Cavasotto C.N.; Orry A.J. Ligand docking and structure-based virtual screening in drug discovery. Curr. Top. Med. Chem. 2007, 7, 1006-1014.