Mitigating chronic granulomatous disease (CGD) through mutational analysis and de novo drug design targeting the CYBA gene through different approaches

Chronic Granulomatous Disease (CGD) is a rare genetic immunodeficiency disorder that arises from mutations in genes responsible for encoding the NADPH oxidase complex, including the CYBA. Such genetic alterations impair the production of reactive oxygen species (ROS), which culminates in impaired microbial eradication, recurrent infections, and the formation of granulomas. This study aimed to conduct an in silico mutational analysis of the CYBA gene and design a novel therapeutic candidate to mitigate Chronic Granulomatous disease. The FASTA sequence of the protein Cytochrome b-245 light chain was retrieved from the UniProt. Mutational analysis was performed using BLASTp and UniProt to identify and confirm the possible mutations. AlphaFold server 3 was utilized to generate the mutated 3D structure of the CYBA protein. The pharmacokinetics and toxicity profiles performed using ADMET AI and ProToxII indicated that the drug compound is nontoxic with medium solubility. Finally, the molecular dynamics simulation studies were carried out using the OpenMM engine with the AMBER force field. The mutated protein structure was validated and assessed for quality using Ramachandran and ERRAT analysis which showed a quality factor of 98.5 according to ERRAT and 98.6 % of residues within favorable regions. For drug design, the ELEA-3D tool was utilized to synthesize the 20 ligands against the targeted protein from which the best one was selected based on a confidence score of 81.23 %. The molecular docking and interaction analysis was carried out utilizing HDock yielding a docking score of −165.5 and Ligplot+ and Discovery studio. The quality, validity, interaction analysis, and non-toxicity nature of the designed drug compound suggest it is a promising candidate for Chronic Granulomatous disease.