Extended Abstract
Background and Aim: Recombinant protein production frequently encounters limitations due to structural instability and misfolding. The rational design of amino acid mutations via computational screening offers a potent alternative to empirical trial-and-error approaches. Despite the growing global reliance on computational biology, a comprehensive Persian summarizing these analytical servers remains unavailable. Therefore, this study aimed to evaluate, and categorize advanced bioinformatics tools tailored for predicting mutation impacts on protein stability and validating the resulting three-dimensional structures.
Materials and Methods: In this study, Google Scholar, PubMed, and Scopus databases were searched to retrieve relevant articles published between 1971 and 2023. The search strategy utilized keywords including "bioinformatics methods", "stability", "mutation", and "predictive databases". Furthermore, protein stability prediction tools (such as PoPMuSiC, HotMuSiC, DUET, SDM, mCSM, CUPSAT, DDGun, STRUM, and I-Mutant) and 3D structure validation servers (including I-TASSER, QMEAN, Phyre2, PROCHECK, ProSA, and ERRAT) were analyzed and compared regarding their algorithms, functions, and features.
Results: The comparative screening revealed that mutation-based stability tools accurately quantify changes in melting temperature (ΔTm) and free energy of stability (ΔΔG). Following modeling, validation servers facilitate the selection of the most stable 3D model by evaluating stereochemical quality, model accuracy, and structural errors. The finalized model can serve as a reference structure for gene construct design and experimental validation.
Conclusion: Utilizing in silico bioinformatics toolkits in structural biology drastically minimizes wet-lab screening times and experimental costs. By providing accurate mathematical modeling of structural thermodynamics, these predictive servers facilitate the design of highly stable recombinant proteins, establishing a robust foundation for targeted advancements in industrial and medical biotechnology.