IDENTIFICATION OF POSSIBLE MOLECULAR TARGETS OF POTENTIAL ANTI-PARKINSON DRUGS BY PREDICTING THEIR BINDING AFFINITIES USING MOLECULAR DOCKING TECHNIQUE

Maguemga Homsi Chanceline Dorice; Navneet Khurana; Neha Sharma; Gopal L Khatik

doi:10.22159/ajpcr.2018.v11s2.28512

Authors

Maguemga Homsi Chanceline Dorice Department of Pharmaceutical Chemistry & Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara â€“ 144 411, Punjab, India.
Navneet Khurana Department of Pharmaceutical Chemistry & Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara â€“ 144 411, Punjab, India.
Neha Sharma Department of Pharmaceutical Chemistry & Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara â€“ 144 411, Punjab, India.
Gopal L Khatik Department of Pharmaceutical Chemistry & Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara â€“ 144 411, Punjab, India.

DOI:

https://doi.org/10.22159/ajpcr.2018.v11s2.28512

Keywords:

Anti-Parkinson, Mechanism, Molecular docking, Autodock Vina

Abstract

Objective: Mechanistic study of newly reported anti-Parkinson agents by molecular docking to predict possible target.

Methods: Structures of newer drugs known anti-Parkinson agents were drawn using ChemBioDraw 2D software. Thereafter, they were converted to 3D structures using ChemBioDraw 3D software in which they were subjected to energy minimization using the MM2 method and then saved as PDB extension files, which can be accessed using the AutoDock Vina (ADT) interface. ADT 1.5.6 software version was used for molecular docking study.

Results: Various molecular targets were selected (D2/D3, D2, A2A, and MAO-B) and studied for Pardoprunox, Istradefylline, Rasagiline, and Bromocriptine. Pardoprunox, Istradefylline, and Bromocriptine had more affinity with their corresponding receptor with âˆ’6.9, âˆ’8.5, and âˆ’9.4 kcal/mol binding affinity, respectively, except Rasagiline, who has less affinity with its corresponding receptor (âˆ’6.4kcal/mol) and shown better affinity with 3pbl receptor (âˆ’6.7 kcal/mol).

Conclusion: Pardoprunox, Istradefylline, and Bromocriptine were found to act on D2/D3 (3pbl), A2A (3pwh), and D2 (4yyw), respectively, whereas Rasagiline found to be act on D2/D3 (3pbl) receptor. The results help in prediction of mechanism and interaction to various Parkinson's disease targets.

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References

Lotharius J, Brundin P. Pathogenesis of Parkinsonâ€™s disease: Dopamine, vesicles and Î±-synuclein. Nat Rev Neurosci 2002;3:932-42.

Kapoor SK, Banerjee AK. Prevalence of common neurological diseases in a rural community of India. Indian J Community Med 1989;14:171.

Gourie-Devi M, Gururaj G, Satishchandra P. Neuroepidemiology in India: Development during three decades. Natl Inst Mental Health 1999;17:379-88.

Gourie-Devi M, Gururaj SP, Satishchandra P. Bangalore urban and rural neurological survey. Report to Indian Council of Medical Research; 1995.

Hirsch EC, Hunot S. Neuroinflammation in Parkinsonâ€™s disease: A target for neuroprotection? Lancet Neurol 2009;8:382-97.

Priyadarshi A, Khuder SA, Schaub EA, Priyadarshi SS. Environmental risk factors and Parkinsonâ€™s disease: A metaanalysis. Environ Res 2001;86:122-7.

Huang Z, Fuente-Fernandezr D, Stoessi AJ. Etiology of Parkinsonâ€™s disease. Can J Neurol Sci 2003;30:10-8.

Bharucha NE, Bharucha EP, Dastur, HD, Schoenberg BS. Pilot survey of the prevalence of neurologic disorders in the Parsi community of Bombay. Am J Prev Med 1987;3:293-9.

Gelb DJ, Oliver E, Gilman S. Diagnostic criteria for Parkinson disease. Arch Neurol 1999;56:33-9.

Calne DB. Treatment of Parkinsonâ€™s disease. N Engl J Med 1993;329:1021-7.

Dawson TM, Dawson VL. Molecular pathways of neurodegeneration in Parkinsonâ€™s disease. Science 2003;302:819-22.

Dong X, Liu T, Xu S, Zhu L, Zhang P, Cheng A, et al. The relevance of ABCA1 R219K polymorphisms and serum ABCA1 receptor concentration to Parkinsonâ€™s disease pathogenesis and classification: A case-control study. Genes Genomics 2016;38:243-50.

Pourcher E, Fernandez HH, Stacy M, Mori A, Ballerini R, Chaikin P.Istradefylline for Parkinsonâ€™s disease patients experiencing motor fluctuations: Results of the KW-6002-US-018 study. Parkinsonism Relat Disord 2012;18:178-84.

Chaurasiya S, Kaur P, Nayak SK, Khatik GL. Virtual screening for identification of novel potent EGFR inhibitors through AutoDock Vina molecular modeling software. J Chem Pharm Res 2016;8:353-60.

Kaur P, Khatik GL. Identification of novel 5-styryl- 1,2,4-oxadiazole/ Triazole derivatives as the potential antiandrogens. Through molecular docking study. Int J Pharm Pharm Sci 2016;8:72-7.

Kaur K, Kaur P, Mittal A, Nayak SK, Khatik GL. Design and molecular docking studies of novel antimicrobial peptides using Autodock molecular docking software. Asian J Pharm Clin Res 2017;10:28-31.

Bhardwaj S, Khatik GL, Kaur P, Nayak SK. Computer aided drug design through molecular docking: Identification of selective COX-2 inhibitors as potential NSAIDs. J Pharm Res 2017;11:604-8.

Trott O, Olson AJ. Autodock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 2010;31:455-61.

PDB 2vz2, 3pbl, 4yyw, and 3pwh Were. Available from: http://www. rcsb.org/pdb/explore.do?pdbId. [Last accessed on 2017 Oct 05; 2017 Oct 17].

Energy Minimizations were Performed MM2 Interface Program on ChemBio3D Ultra 12.0, and Structures were Drawn by ChemBioDraw Ultra 12.0. Cambridge: Cambridge Soft; 1985.