Theoretical Modeling and Systemic Analysis of Various Active Dipeptides and Analogues with 3D-QSAR Methods

Author(s): Guanghui Tang, Cheng Chen, Yuping Zhang, Ya Zhang, Yuanqiang Wang*, Zhihua Lin*.

Journal Name: Letters in Drug Design & Discovery

Volume 15 , Issue 9 , 2018

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Graphical Abstract:


Background: Dipeptides and their analogs have multiple biological functions, such as bitter taste, angiotensin-converting enzyme (ACE) inhibition, etc. That design and modification of dipeptides guided by theoretical models are of great significance for research and development on drug, especially in discovery and optimization of lead compound, which can reduce the experimental expenditure and improve the hit rate.

Methods: We used conventional 3D-QSAR methods, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA), and Topomer CoMFA to construct Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) models for four catalogues of dipeptides and their derivatives, which were bitter-tasting dipeptides, ACE-inhibitory dipeptides, anti-cryptococcal and anti-microtubule dipeptide derivatives. The CoMFA and CoMSIA models based on a training set were optimized through varying the force fields and their combination. Topomer CoMFA experientially completed identification and alignment of pose of the fragments.

Results and Conclusion: We have achieved theoretical 3D-QSAR models with good reliability of prediction for correspondingly novel samples, which had good statistically significance with excellent cross-validated correlation coefficients (Q2 >0.5) and conventional correlation coefficients (R2 >0.9). The counter maps from the CoMFA and CoMSIA models could provide the direct information about contributions of the force fields for activity, aiding the design and modification of novel bioactive dipeptides and by which relationships between bitter dipeptides with ACEinhibitory dipeptides were explored briefly and a set of novel anti-cryptococcal dipeptide derivatives with predicted activities were designed. Topomer CoMFA models for bitter dipeptides, ACEinhibitory dipeptides and anti-cryptococcal dipeptidomimetics were ideal, proved the above results and could provide a tool for virtual screening.

Keywords: ACE inhibition, anti-cryptococcal, anti-microtubule, bitter-tasting, dipeptide, 3D-QSAR.

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Article Details

Year: 2018
Page: [988 - 1001]
Pages: 14
DOI: 10.2174/1570180814666171027162400
Price: $58

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