Emerging, Hot Topic: Applications of Computational in-Silico Approach to Investigate the Potential Mechanism of Psychoactive Substances: Khat (catha Edulis) As an Example

Introduction: It is known that addiction of psychoactive substances is largely attributed to their interaction with various transporter and receptors. Multiple computational methods and techniques can be applied to differentiate conformational states and binding interaction of psychostimulants with different transporter to indicate the key functional groups of psychoactive substances for drug addictiveness. Recently studies reported to facilitate the understanding of the mechanism underlining drugs’ addictiveness of various prescribed ADHD drug by using docking and MD simulation^1,2. Multiple computational methods including homology modelling, docking and MD simulation were used to explore the induced addiction of cocaine analog with DAT³.

Methods: This was specifically implemented for the first time by us to investigate the molecular mechanism underlying the potential addiction and toxicity of khat plant (Catha edulis). Khat chewing is a major public health and social problem growing globally. Khat is a controlled substance in some countries, such as Canada, Germany, United Kingdom, and United States, but it is prevalent in Saudi Arabia, Djibouti, Kenya, Uganda, Ethiopia, Somalia and Yemen⁴.

In this regard, we have integrated multiple in silico methods, including homology modeling, molecular docking, pharmacophore modeling and molecular dynamic simulations to study the potential addiction and toxicity of khat. Descriptive 3D database of Khat chemical constituents were constructed and potential molecular interactions of these constituents with respective receptors had been predicted.

Results and conclusions: This poster will discuss the predicted mechanism of khat psychoses, sexual dysfunction and cardiac related disorders. It will highlight the results of our investigation, which revealed that constituents of khat plant showed significant interaction with the 17-β hydroxy steroid dehydrogenase, β-1 adrenergic receptor and dopamine D2 receptor protein respectively.

REFERENCES:

1. Wang, P.; Fu, T.; Zhang, X.; Yang, F.; Zheng, G.; Xue, W.; Chen, Y.; Yao, X.; Zhu, F., Differentiating physicochemical properties between NDRIs and sNRIs clinically important for the treatment of ADHD. Biochimica et Biophysica Acta (BBA)-General Subjects 2017, 1861 (11), 2766-2777.
2. Wang, P.; Zhang, X.; Fu, T.; Li, S.; Li, B.; Xue, W.; Yao, X.; Chen, Y.; Zhu, F., Differentiating physicochemical properties between addictive and nonaddictive ADHD drugs revealed by molecular dynamics simulation studies. ACS chemical neuroscience 2017, 8 (6), 1416-1428.
3. Dahal, R. A.; Pramod, A. B.; Sharma, B.; Krout, D.; Foster, J. D.; Cha, J. H.; Cao, J.; Newman, A. H.; Lever, J. R.; Vaughan, R. A., Computational and biochemical docking of the irreversible cocaine analog RTI 82 directly demonstrates ligand positioning in the dopamine transporter central substrate binding site. Journal of Biological Chemistry 2014, jbc. M114. 571521.
4. Feng, L.-Y.; Battulga, A.; Han, E.; Chung, H.; Li, J.-H., New psychoactive substances of natural origin: a brief review. journal of food and drug analysis 2017, 25 (3), 461-471.