In-silico analysis of the structure and binding site features of an α-expansin protein from mountain papaya fruit (VpEXPA2), through molecular modeling, docking, and dynamics simulation studies
- 549 Downloads
Fruit softening is associated to cell wall modifications produced by a set of hydrolytic enzymes and proteins. Expansins are proteins with no catalytic activity, which have been associated with several processes during plant growth and development. A role for expansins has been proposed during softening of fruits, and many fruit-specific expansins have been identified in a variety of species. A 3D model for VpEXPA2, an α-expansin involved in softening of Vasconcellea pubescens fruit, was built for the first time by comparative modeling strategy. The model was validated and refined by molecular dynamics simulation. The VpEXPA2 model shows a cellulose binding domain with a β-sandwich structure, and a catalytic domain with a similar structure to the catalytic core of endoglucanase V (EGV) from Humicola insolens, formed by six β-strands with interconnected loops. VpEXPA2 protein contains essential structural moieties related to the catalytic mechanism of EGV, such as the conserved HFD motif. Nevertheless, changes in the catalytic environment are observed in the protein model, influencing its mode of action. The lack of catalytic activity of this expansin and its preference for cellulose are discussed in light of the structural information obtained from the VpEXPA2 protein model, regarding the distance between critical amino acid residues. Finally, the VpEXPA2 model improves our understanding on the mechanism of action of α-expansins on plant cell walls during softening of V. pubescens fruit.
KeywordsExpansin Homology modeling Molecular docking Molecular dynamics simulation Vasconcellea pubescens
L. Morales-Quintana acknowledges CONICYT for a doctoral fellowship. This work has been supported by Initiation FONDECYT grant N° 11100481 and CONICYT Anillo ACT-1110 project.
- 20.MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL Jr, Evanseck J, Field M, Fischer JS, Gao J, Guo H, Ha S, Joseph D, Kuchnir L, Kuczera K, Lau FTK, Mattos C, Michnick S, Ngo T, Nguyen DT, Prodhom B, Roux B, Schlenkrich M, Smith J, Stote R, Straub J, Watanabe M, Wiorkiewicz-Kuczera J, Yin D, Karplus M (1992) Self-consistent parameterization of biomolecules for molecular modeling and condensed phase simulations. FASEB J 6:A143Google Scholar
- 21.Schlenkrich M, Brickmann J, MacKerell AD Jr, Karplus M (1996) In: Roux B, Merz KM (eds) A molecular perspective from computation and experiment. Birkhauser, Boston, pp 31–81Google Scholar
- 26.Trott O, Olson AJ (2010) AutoDockVina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. J Comput Chem 31:455–461Google Scholar
- 27.Vanommeslaeghe K, Hatcher E, Acharya C, Kundu S, Zhong S, Shim J, Darian E, Guvench O, Lopes P, Vorobyov I, MacKerell AD Jr (2010) CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force field. J Comput Chem 31:671–690Google Scholar