Tunneling Group, Biotechnology Center, Silesian University of Technology, Krzywoustego St. 8, 44-100 Gliwice, Poland.
Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 26 Plocka St., 01-138 Warsaw, Poland.
Genes (Basel). 2024 Mar 6;15(3):340. doi: 10.3390/genes15030340.
In the rapidly advancing field of bioinformatics, the development and application of computational tools to predict the effects of single nucleotide variants (SNVs) are shedding light on the molecular mechanisms underlying disorders. Also, they hold promise for guiding therapeutic interventions and personalized medicine strategies in the future. A comprehensive understanding of the impact of SNVs in the gene on alpha-1 antitrypsin (AAT) protein structure and function requires integrating bioinformatic approaches. Here, we provide a guide for clinicians to navigate through the field of computational analyses which can be applied to describe a novel genetic variant. Predicting the clinical significance of variation allows clinicians to tailor treatment options for individuals with alpha-1 antitrypsin deficiency (AATD) and related conditions, ultimately improving the patient's outcome and quality of life. This paper explores the various bioinformatic methodologies and cutting-edge approaches dedicated to the assessment of molecular variants of genes and their product proteins using and AAT as an example.
在快速发展的生物信息学领域,开发和应用计算工具来预测单核苷酸变异 (SNV) 的影响,揭示了疾病背后的分子机制。此外,它们还有望为未来的治疗干预和个性化医学策略提供指导。全面了解 SNV 对基因中 alpha-1 抗胰蛋白酶 (AAT) 蛋白结构和功能的影响,需要整合生物信息学方法。在这里,我们为临床医生提供了一个指南,帮助他们了解可以应用于描述新型遗传变异的计算分析领域。预测变异的临床意义,可以让临床医生为 alpha-1 抗胰蛋白酶缺乏症 (AATD) 和相关疾病的个体定制治疗方案,最终改善患者的预后和生活质量。本文探讨了各种生物信息学方法和最先进的方法,专门用于评估基因及其产物蛋白的分子变异,以 AAT 为例。