Dados do Resumo

Título

In Silico assembly of a chimeric receptor for oncolytic adenoviruses

Introdução

In recent years, cancer treatments such as immune checkpoint inhibition and CAR-T cell therapies have become state-of-the-art. These immunotherapies enhance the body's immune response against cancer. Due to rapid technological advances in molecular biology and genetics, virotherapy, the use of viruses to treat cancer, has also improved. Genetic editing now offers vast possibilities for designing viruses specifically to target and destroy cancer cells.

Objetivo

This work aims to explore how to assemble an oncolytic virus receptor using in silico tools. The goal is to provide a theoretical framework for constructing a customizable receptor capable of targeting cancer cells, thus contributing to the advancement of virotherapy as a cancer treatment.

Métodos

We employed computational tools to model and evaluate two potential oncolytic virus receptors. First, using crystallography data, we constructed initial receptor models with AlphaFold 2. These models were then validated with VERIFY 3D, PROCHECK, and ProSa to assess their structural stability and functionality. Simulations were performed using GROMACS software to analyze the behavior of the receptor models in aqueous environments that mimic physiological conditions. Additionally, Free-Energy Landscape (FEL) analysis was used to determine the accessibility of the receptor's binding interaction surface when in its lowest energy state. Using these in silico methods provided a deep understanding of the molecular characteristics and stability of the constructs under different conditions.

Resultados

The two constructed receptor models showed promising results. Structural validation using VERIFY 3D, PROCHECK, and ProSa indicated that both models exhibited robust and stable characteristics suitable for practical application. GROMACS simulations demonstrated that the receptor models maintained their integrity and flexibility in conditions simulating the physiological environment, with no significant structural collapse observed. Free-Energy Landscape analysis further confirmed that the receptor's interaction surface remained exposed and solvent-accessible, suggesting that these models could effectively bind to their targets in vivo. The findings support the potential for creating highly customizable and stable oncolytic virus receptors using sequence data and computational tools.

Conclusões

This study demonstrates the feasibility of designing robust and stable oncolytic virus receptors using in silico tools and sequence data. The results provide a proof of concept for constructing customizable receptors for virotherapy, enhancing the precision and effectiveness of viral therapies against cancer. Further experimental validation is needed, but this approach opens new avenues for personalized cancer treatments using engineered viruses.

Financiador do resumo

CNPQ

Palavras Chave

Biologia Sintética; imunologia; Bioinformática