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Review
. 2018;16(6):865-880.
doi: 10.2174/1570159X15666171128145423.

Computer-aided Drug Design Applied to Parkinson Targets

Affiliations
Review

Computer-aided Drug Design Applied to Parkinson Targets

Hamilton M Ishiki et al. Curr Neuropharmacol. 2018.

Abstract

Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by debilitating motor deficits, as well as autonomic problems, cognitive declines, changes in affect and sleep disturbances. Although the scientific community has performed great efforts in the study of PD, and from the most diverse points of view, the disease remains incurable. The exact mechanism underlying its progression is unclear, but oxidative stress, mitochondrial dysfunction and inflammation are thought to play major roles in the etiology.

Objective: Current pharmacological therapies for the treatment of Parkinson's disease are mostly inadequate, and new therapeutic agents are much needed.

Methods: In this review, recent advances in computer-aided drug design for the rational design of new compounds against Parkinson disease; using methods such as Quantitative Structure-Activity Relationships (QSAR), molecular docking, molecular dynamics and pharmacophore modeling are discussed.

Results: In this review, four targets were selected: the enzyme monoamine oxidase, dopamine agonists, acetylcholine receptors, and adenosine receptors.

Conclusion: Computer aided-drug design enables the creation of theoretical models that can be used in a large database to virtually screen for and identify novel candidate molecules.

Keywords: Parkinson's disease; QSAR; acetylcholine receptors; and adenosine receptors; dopamine agonists; monoamine oxidase..

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Figures

Fig. (1)
Fig. (1)
Molecular structures of the derivatives used in the 3D QSAR studies.
Fig. (2)
Fig. (2)
Molecular structure of the dopamine D2 receptor derivatives.
Fig. (3)
Fig. (3)
Compound 5 with descriptors derived from the best QSAR-4D model.
Fig. (4)
Fig. (4)
The structure of 3-[[(aryloxy)alkyl]piperidinyl]-1,2-benzis- oxazole derivatives.
Fig. (5)
Fig. (5)
Mechanism of action of the selective nigral toxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP).
Fig. (6)
Fig. (6)
Chemical structure of phenyl alkylamines derivatives.
Fig. (7)
Fig. (7)
Chemical structure of coumarin derivatives.
Fig. (8
Fig. (8
a). Chemical structures of (A) nicotinoid agonists, (B) phenylpyrrolidine derivatives, (C) isonicotine derivatives and (D) 3-aminomethylpyridine derivatives.
Fig. (8c)
Fig. (8c)
Chemical structures of (A) arecolone and (B) isoarecolone derivatives.
Fig. (8b)
Fig. (8b)
Chemical structures of (A) pyridyloxymethylpyrrolidine derivatives, (B) pyridyloxymethylazetidine derivatives and (C) phenoxymethylazacyclic derivatives.
Fig. (8d)
Fig. (8d)
Chemical structures of nitrogen polycyclic derivatives.
Fig. (9)
Fig. (9)
Structures of (A) (R)-epibatidine, and (B) compound 29 employed as templates for the alignment step.
Fig. (10)
Fig. (10)
Adenosine receptors.
Fig. (11)
Fig. (11)
Structures of (A) pyrimidine and triazine derivatives (X=C/N), model I; (B) pyrazolo[3,4-d]pyrimidines, pyrrolo[2,3- d]pyrimidines, triazolo[4,5-d]pyrimidines and 6-arylpurines derivatives (X=C/N and Y=C/N), model II and (C) thieno[3,2-d]pyrimidines derivatives, model III.
Fig. (12)
Fig. (12)
Structures of 4-arylthieno [3, 2-d] pyrimidine derivatives.

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