Quantitative Structure–Activity Relationship Analysis of Thiophene Derivatives to Explore the Structural Requirements for c-Jun NH 2 -Terminal Kinase 1 Inhibitory Activity

Authors

Ashima Nagpal1,*, Monika Chauhan2
1Department of Pharmacy, G. D. Goenka University, Sohna, Haryana, India
2Department of Pharmacy, Banasthali Vidyapith, Banasthali, Rajasthan, India
*Corresponding Author: Corresponding author: Department of Pharmacy, G. D. Goenka University, Sohna, Haryana, India. Email:[email protected]

Journal of Reports in Pharmaceutical Sciences:Vol. 8, issue 2; 115-23
Published online:Dec 31, 2019
Article type:Research Article
How to Cite:Nagpal A, Chauhan M. Quantitative Structure–Activity Relationship Analysis of Thiophene Derivatives to Explore the Structural Requirements for c-Jun NH 2 -Terminal Kinase 1 Inhibitory Activity. J Rep Pharm Sci. 2019;8(2):e147320. doi: https://doi.org/10.4103/jrptps.jrptps_32_18

Abstract

Background: With an aim to design a validated two‑dimensional quantitative structure–activity relationship (2D QSAR) model, a probe was executed on a series of reported c‑Jun NH2‑terminal kinase‑1 (JNK1) inhibitors, exhibiting selectivity toward JNKs (and not other members of MAPK family). 
Objective: The present work focused on obtaining valuable insights from the structural architecture of the selected compounds and their effects on JNK1 inhibitory activity. The present work deciphers the importance of descriptive variables, namely Verloop L (Subst. 1), Bond Dipole Moment (Subst. 2), LogP (Subst. 1), Balaban Topological index (Subst. 1), and VAMP Total Dipole (whole molecule), in molecules possessing JNK1 inhibitory profile. 
Results: These explanatory variables, obtained after iteratively reducing the data, did not only provide us with the substantial evidence pertaining to the dependence of bioactivity on the structural features of molecules, but also suggested the measures to optimize the selected compounds so as to obtain potent JNK1 inhibitors with good selectivity profile. Based on these distinct descriptors, exhibiting no apparent intercorrelation and manifesting good correlation with biological activity, a 2D QSAR model was generated. 
Conclusion: Robustness of the developed model was evaluated by performing multiple linear regression, partial least square, and artificial neural network studies. The reliability and predictive ability of the developed model was ascertained through the values of standard statistical parameters, such as s = 0.38, F = 97.22, r = 0.95, r2 = 0.90, and r2cv = 0.88, for the training set compounds. The generated model was validated through the test set compounds, as well as by leave one out method. 
 

Highlights

Copyright

© 2019, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

Similar Articles

5
Mar
2018

Applications of Chemometric Methods to Elucidate Physicochemical Requirements for Binding of PTP1B Inhibitors to Its Target

Monika Chauhan,
Sarvesh Paliwal,
Neetika SeemaKesar,
Ashima Nagpal

Chauhan M, Paliwal S, SeemaKesar N, Nagpal A. Applications of Chemometric Methods to Elucidate Physicochemical Requirements for Binding of PTP1B Inhibitors to Its Target. J Rep Pharm Sci. 2018;7(2):e147578. doi:

17
Dec
2021

Quantitative Structure–activity Relationship Modeling of Some Naphthoquinone Derivatives as Inhibitors of Pathogenic Agent IDO1

Sajjad Jazayeri Farsani,
Saeid Asadpour,
Abolfazl Semnani,
Shima Ghanavati Nasab

Jazayeri Farsani S, Asadpour S, Semnani A, Ghanavati Nasab S. Quantitative Structure–activity Relationship Modeling of Some Naphthoquinone Derivatives as Inhibitors of Pathogenic Agent IDO1. J Rep Pharm Sci. 2021;10(2):e146972. doi: https://doi.org/10.4103/jrptps.JRPTPS_124_20

1
Sep
2022

2D-QSAR and docking studies of 4-anilinoquinazoline derivatives as epidermal growth factor receptor tyrosine kinase inhibitors

Mahtab Ghasemi Dogaheh,
Heshmat Ebrahimi,
Fatemeh Yousefbeyk,
saeed ghasemi

Ghasemi Dogaheh M, Ebrahimi H, Yousefbeyk F, ghasemi S. 2D-QSAR and docking studies of 4-anilinoquinazoline derivatives as epidermal growth factor receptor tyrosine kinase inhibitors. koomesh. 2022;24(3):e152750. doi:

31
Mar
2015

QSAR Study on Anti-HIV-1 Activity of 4-Oxo-1,4-dihydroquinoline and 4-Oxo-4H-pyrido[1,2-a]pyrimidine Derivatives Using SW-MLR, Artificial Neural Network and Filtering Methods

Zahra Hajimahdi,
Amin Ranjbar,
Amir Abolfazl Suratgar,
Afshin Zarghi

Hajimahdi Z, Ranjbar A, Abolfazl Suratgar A, Zarghi A. QSAR Study on Anti-HIV-1 Activity of 4-Oxo-1,4-dihydroquinoline and 4-Oxo-4H-pyrido[1,2-a]pyrimidine Derivatives Using SW-MLR, Artificial Neural Network and Filtering Methods. Iran J Pharm Res. 2015;14(Suppl):e125249. doi: https://doi.org/10.22037/ijpr.2015.1714

30
Apr
2017

QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method

Somaye Akbari,
Tannaz Zebardast,
Afshin Zarghi,
Zahra Hajimahdi

Akbari S, Zebardast T, Zarghi A, Hajimahdi Z. QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method. Iran J Pharm Res. 2017;16(2):e125006. doi: https://doi.org/10.22037/ijpr.2017.2107

More by these authors

Ashima NagpalPubMedScholar
Monika ChauhanPubMedScholar
Share
Cited by
Metrics