Virtual screening of compounds for the development of thyroid hormone analogues for potential application in cardiac regeneration
José de Anchieta de Oliveira Filho, Elton José Ferreira Chaves, Pedro Geraldo Pascutti, Enéas Ricardo de Morais Gomes

TL;DR
This paper uses virtual screening to find compounds that could activate a thyroid hormone receptor linked to heart cell regeneration.
Contribution
A novel multi-scale computational framework for identifying TRα agonists with potential cardiac regenerative applications.
Findings
A virtual screening pipeline identified eight candidate compounds from 412 million in ZINC15.
Two compounds, including Cetraxate, showed interaction energies and reactivity patterns similar to T3.
The framework integrates MM, QM, QM/MM, and Fukui function analysis for ligand evaluation.
Abstract
Cardiovascular diseases remain the leading global cause of mortality, largely due to the limited regenerative capacity of adult cardiac tissue. Thyroid hormones, particularly tri-iodothyronine (T3), have been shown to stimulate cardiomyocyte proliferation through activation of the thyroid hormone receptor alpha (TRα), making this receptor a promising therapeutic target. Here we report a hierarchical and consensus, multi-level virtual screening pipeline integrating Molecular Mechanics (MM), Quantum Mechanics (QM), hybrid QM/MM calculations, and reactivity analysis based on the Fukui function to identify novel TRα agonists. Starting from 412 million compounds in the ZINC15 database, physicochemical filtering, validated pharmacophore matching, and docking guided by ROC curve optimization yielded 568 candidates, from which eight compounds were selected through chemically guided visual…
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Taxonomy
TopicsThyroid Disorders and Treatments · GDF15 and Related Biomarkers · Machine Learning in Bioinformatics
