“School of Cognitive%20Sciences”
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| Paper IPM / Cognitive%20Sciences / 13881 |
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Selective serotonin reuptake inhibitors (SSRIs) are a rationally designed class of antidepressants which act via inhibition of the serotonin transporter (SERT), resulting in increased serotonin concentrations in the synaptic cleft. This group of drugs is thought to be selective for SERT rather than norepinephrine and dopamine transporters (respectively NET and DAT). We used a computational approach to determine the drugs with the highest affinity and selectivity for SERT. We used molecular docking, energy minimization, molecular dynamics simulations and umbrella sampling to estimate the Gibbs binding free energy for each protein-drug complex. Our results qualitatively agree with corresponding experimental data. Among the SSRIs we studied, paroxetine has the highest affinity for SERT and NET, and sertraline for DAT. Our results confirmed the selectivity of this class of drugs for SERT rather than NET and DAT. We found citalopram was the most selective drug for SERT in this class. These results can be used for future studies on designing SSRIs with higher affinity and selectivity.
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