Molecular modeling of Acetyl-CoA carboxylase (ACC) from Jatropha curcas and virtual screening for identification of inhibitors

Aim

Acetyl-CoA carboxylase (ACC) is a biotin-dependent enzyme which plays a key role in fatty acid biosynthesis via production of melonyl-CoA as an essential substrate. It is involved in homeostasis of fatty acids inside the system using both up and down regulating mechanisms. Apart from this In silico analysis of its catalytic site and regulatory sites make it a potential target for herbicidal and insecticidal drug targeting. Currently the 3D structure of Acetyl-CoA carboxylase (ACC) from Jatropha curcas has not been solved in Protein Data Bank (PDB). Hence the aim of the present study is to build the 3D structure of Acetyl-CoA carboxylase (ACC) from J. curcas also to perform a virtual screening for the identification of the effective inhibitors using molecular docking studies.

Methods

Homology modeling has been used to determine the 3D structure of Acetyl-CoA carboxylase (ACC) from J. curcas. Structure validation and molecular docking studies has been carried out using Procheck and Molegro Virtual Docker respectively.

Results

Ramachandran Plot confirmed quality of modeled structures along with main chain and side chain parameters. Out of 309 residues in SPDBV model, 244 were in core region 19 residues were in additional allowed region, 2 residues were in generous allowed region and no residues were in disallowed region.

Conclusion

Energy minimization for SPDBV model thermodynamically proved accepted structure with energy of −12,063.024 kJ/mol. The model further can be subjected to pharmacodynamic and pharmacokinetic studies. Molecular docking studies identified few established herbicides which could be promising inhibitors of Acetyl-CoA carboxylase (ACC). Efforts to screen and identify ACC inhibitors using flexible molecular docking resulted in Pinoxaden from Phenylpyrazole class as the most effective inhibitor with rerank = −81.436 and RMSD = 0.31.