Development of Pharmacophore Models for the Important Off-Target 5-HT2B Receptor

Toxicity is a major cause of attrition in the development of pharmaceuticals, and the off-target effects are a frequent contributor. The 5-HT2B receptor agonism is known to be responsible for a variety of safety concerns including valvular heart disease which was the cause for the withdrawal of several compounds from the market. An early detection of potential binding to this receptor is thus desirable. Herein, we present the identification of key amino acid residues in the active site of 5HT(2B) by molecular dynamics simulations, the development of pharmacophore models and their performance on in-house data, and a structurally highly diverse subset of Enamine REAL labeled for 5-HT2B activity by a machine learning model. These models may be used as filters employed on screening compound sets for the early filtration of compounds with potential 5-HT2B off-target liabilities.

Automated summary

Toxicity, particularly off-target effects, is a major reason for the failure in pharmaceutical development. This study focuses on identifying the key amino acid residues in the active site of 5-HT2B receptor through molecular dynamics simulations. Pharmacophore models were developed and their performance was evaluated on in-house data and a diverse subset of Enamine REAL. Machine learning was used to label the subset for 5-HT2B activity. These models can serve as filters for early detection of compounds with potential 5-HT2B off-target liabilities.