Affiliation:
1. Department of Health Sciences, Santa Cruz State University, Ilhéus, Bahia, Brazil
2. Bahiana School of Medicine and Public Health - Salvador - Bahia - Brazil.
3. SENAI CIMATEC University Center – Salvador – Bahia - Brazil.
4. Federal University of Bahia School of Medicine – Salvador – Bahia – Brazil.
5. Medical Doctor, UniFTC Medical School - Salvador - Bahia - Brazil.
Abstract
Abstract
Introduction
Graves' disease (GD), an autoimmune disorder characterized by hyperthyroidism and the production of autoantibodies targeting the thyroid-stimulating hormone receptor (TSHR), poses a considerable challenge in clinical management. Antithyroid medications block thyroid hormone synthesis and are usually the first-line treatment. In recent years, the advent of computational molecule design has offered a promising avenue for the development of novel therapeutic strategies tailored to specific molecular targets. Despite the substantial progress made in silico molecule design for targeting the TSHR in GD, several critical gaps persist in the current literature.
Objective
To provide an in silico design of hybrid molecule targeting the TSHR.
Method
In silico hybridization of rituximab (RTX) and methimazole (MMZ) was performed through a comprehensive workflow: structural bioinformatics analysis, virtual screening and hybrid molecule design, molecular dynamics simulations, machine learning-based analysis, pharmacokinetic modeling and safety assessment, free energy calculations, in silico mutation analysis, data analysis and visualization.
Result
In silico approach identified a novel hybrid molecule candidate with promising potential for the treatment of GD. The designed molecule exhibited favorable characteristics in terms of binding affinity, selectivity, absorption, distribution, metabolism, excretion and toxicity profiles, and potential safety.
Conclusion
The designed molecule, derived from MMZ and RTX, exhibited promising characteristics in silico. The hybrid molecule demonstrated favorable binding affinity and selectivity towards the TSHR through virtual screening and molecular dynamics simulations.
Publisher
Research Square Platform LLC