Abstract
Serotonin (5-hydroxytryptamine, 5-HT) receptors are neuromodulator neurotransmitter receptors which when activated trigger a signal transduction cascade within cells resulting in cell-cell communication. 5-hydroxytryptamine receptor 2B (5-HT2B) is a subtype of the seven members of 5-hydroxytrytamine receptors family which is the largest member of the super family of 7-transmembrane G-protein coupled receptors (GPCRs). Not only do 5-HT receptors play physiological roles in the cardiovascular system, gastrointestinal and endocrine function as well as the central nervous system, but they also play a role in behavioral functions. In particular 5-HT2B receptor is widely spread with regards to its distribution throughout bodily tissues and is expressed at high levels in the lungs, peripheral tissues, liver, kidneys and prostate, just to name a few. Hence 5-HT2B participates in multiple biological functions including CNS regulation, regulation of gastrointestinal motality, cardiovascular regulation and 5-HT transport system regulation. While 5-HT2B is a viable drug target and has therapeutic indications for treating obesity, psychosis, Parkinson’s disease etc. there is a growing concern regarding adverse drug reactions, specifically valvulopathy associated with 5-HT2B agonists. Due to the sequence homology experienced by 5-HT2 subtypes there is also a concern regarding the off-target effects of 5-HT2A and 5-HT2C agonists. The concepts of sensitivity and subtype selectivity are of paramount importance and now can be tackled with the aid of in silico studies, especially cheminformatics, to develop models to predict valvulopathy associated toxicity of drug candidates prior to clinical trials. This review has highlighted three in silico approaches thus far that have been successful in either predicting 5-HT2B toxicity of molecules or identifying important interactions between 5-HT2B and drug molecules that bring about valvulopathy related toxicities.
Keywords: 5-hydroxytryptamine (serotonin) receptor 2B, valvular heart disease, G protein-coupled receptors, in silico, cheminformatics, quantitative structure–activity relationship, homology modeling, molecular docking, molecular dynamics, virtual screening.