Do We Build Similar Molecules for Comorbid Diseases? Tevarud in Drug Design, an Analysis for Depression and Inflammation

Abstract

Tevarud designates two poets coincidently writing a same verse in the Ottoman Divan literature. This study aims to analyze the structural similarity of molecules independently designed for inflammation and depression to determine if coincidentally we are building similar molecules for comorbid diseases. For this purpose, a molecule library was first constituted with structures that were developed as anti-inflammatory (AI) and antidepressant (AD) agents these last decades. Then, the similarity of the structures was determined by calculating the Tanimoto and Cosine similarity coefficients for each AD/AI pair. The highest scores were obtained for two theophylline derivatives: AD17 (for which some AI activity was found to be mentioned) and AI42. The study also pointed out the similarity of some AD coumarins with some AI flavonoids interestingly found to be highly similar to some AI coumarins and AD flavonoids, respectively. Thus, our investigation demonstrated that structures independently developed as AD and AI derivatives can present extremely high structural similarity, a finding that can suggest mechanistic interconnection for these comorbid diseases and also guide for the design of novel bioactive compounds.

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“…e average Tanimoto similarity index calculated from PubchemFP, SubFP, and KRFP is 0.335, 0.372, and 0.165, respectively. A lower Tanimoto similarity index means a more diverse dataset [56]. So, the chemical diversity of our modeling set is significant.…”

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“…A lower Tanimoto similarity index means a more diverse data set. 44,45 The heat map of the normalized Tanimoto similarity index is shown in Fig. 8(a).…”