Design of Novel Selective Serotonin Reuptake Inhibitors Using Computational Modeling Studies

Svanholm, L. E. H.; Torrence, I. S.; Nguyen, T. Q.; Siegel, J. B.

doi:10.1101/2022.10.10.511679

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bioRxiv · 10.1101/2022.10.10.511679

Design of Novel Selective Serotonin Reuptake Inhibitors Using Computational Modeling Studies

Svanholm, L. E. H.·Torrence, I. S.·Nguyen, T. Q.·Siegel, J. B.

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Abstract

Low levels of serotonin in the human brain have been associated with a variety of disorders including depression and anxiety. Selective serotonin reuptake inhibitors (SSRIs) are currently being prescribed to treat such conditions and examples of already marketed drugs include paroxetine, fluvoxamine, sertraline, and citalopram. Nevertheless, side effects such as nausea and drowsiness have been reported for these pharmaceuticals emphasizing the need for continuous development of new and improved lead molecules. In this study, chemical intuition and computational modeling were employed to propose two novel SSRI drug candidates with higher binding affinities to the ts3 human serotonin transporter (hSERT) than currently known SSRIs. Lastly, a homology analysis determined that Macaca fascicularis is a suitable model organism for future preclinical studies.

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Svanholm, L. E. H., Torrence, I. S., Nguyen, T. Q., Siegel, J. B.. 2022-10-13. Design of Novel Selective Serotonin Reuptake Inhibitors Using Computational Modeling Studies. https://doi.org/10.1101/2022.10.10.511679

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