Mechanistic QSAR analysis to predict the binding affinity of diverse heterocycles as selective cannabinoid 2 receptor inhibitor

Abstract

CB2R are fascinating targets for neuropathic pain and mood disorders because of their improved biological characteristics. Experimental data on 1296 cannabinoid-2 receptor inhibitors with different structural properties were used to develop a QSAR model following OECD guidelines. This study selected the best-predicted model (80:20 splitting ratio) with fitting parameters, such as R²:0.78; F:623.6, Internal validation parameters, such as Q²_Loo:0.78; CCCcv: 0.87 and external validation parameters, such as R²_ext:0.77; Q²_F1:0.7730; Q²_F2:0.7730; Q²_F3:0.76; CCC_ext:0.87. Following this, another QSAR model was developed by using a 50:50 split ratio for thetraining and the prediction sets, which were then swapped to evaluate the robustness of the built QSAR model by the 50:50 ratio, which also gives a deeper understanding of the chemical space. In addition, we have confirmed the QSAR result with pharmacophore modelling, and supported by molecular docking, MD simulation, MMGBSA and ADME studies. Thus, this work may enable cannabinoid 2 receptor inhibsitor development.

GRAPHICAL ABSTRACT

KEYWORDS:

• Cannabinoid 2 receptor
• QSAR
• GA-MLR
• pharmacophore modeling
• Molecular dynamic simulation
• MMGBSA

Acknowledgments

The author, Rahul D. Jawarkar, acknowledges and is grateful to the esteemed Shri Yogendraji Gode Sir, President of the Dr. Rajendra Gode Institute of Pharmacy in Amravati, for his support during the whole study process. The author is grateful to Paola Gramatica and her colleagues for providing a complimentary copy of QSARINS 2.2.4. Rahul D. Jawarkar: conceptualization, editing and formal analysis: Magdi E.A. Zaki, Sami A Al-Hussain and Rahul d. Jawarkar, Conceptualization, editing and review, Abdullah Yahya Abdullah Alzahrani. Long Chiau Ming. Gehan M. Elossaily: Formal Analysis, editing and Review. Summya Rashid, Abdul Samad, Suraj Mali: Formal Analysis, editing and Review.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All the data available on this manuscript.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-RG23013).