Three dimensional pharmacophore modeling of Alpha-synuclein aggregation inhibitors

سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 482

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شناسه ملی سند علمی:

CBC14_024

تاریخ نمایه سازی: 7 اسفند 1396

چکیده مقاله:

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that is characterized by thedeposition of misfolded α-synuclein (α-Syn) asamyloid fibrils in the various region of thebrain.Therefore, preventing this process may provide an effective therapeutic approach for treatment ofPD. Several experimental methods have beensuggested for inhibition of α-Syn aggregation. In the presentstudy, pharmacophore modeling as a computational method was selected for reduction of time and cost.The pharmacophore concept has been proven to be extremely successful, not only in rationalizingstructure-activity relationships, but also by its large impact on developing the appropriate 3D-tools forefficient virtual screening. Several experimental data from various types of compounds for structure–activity relationships were collected.The structure of compounds was optimized and chemical featurebased on pharmacophore models of α-Syn aggregation inhibitors have been developed with theLigandscout Program package. Our results suggest that the best pharmacophore model for α-Synaggregation inhibitors contain three hydrogen bonds acceptor and two hydrogenbonds donor features with0.75 score. The best pharmacophore model was validated using database of a test set consist of 48 activeand inactive compounds. This well-validated model will use for 3D-query in virtual screening to identifypotential hits from database.

نویسندگان

S.S Jafarypour

Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran

S Gharaghani

Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran

A.A Saboury

Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran

A.A Meratan

Department of Biological Sciences, Institute of Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran