Precision Protein Engineering for Endodontic Applications: A Computational Approach

Abstract

Protein-Sol and PSIPRED are crucial resources for developing endodontic research and treatment plans. Effective antimicrobial peptides and immune modulators can be designed more easily thanks to PSIPRED's assistance in predicting protein secondary structures related to immune responses or bacterial resistance within the root canal. Its predictions derived from machine learning aid in maximizing protein function and stability in the intricate oral environment. However, Protein-Sol offers essential information about protein solubility, guaranteeing the effective administration of biologics for endodontic treatment, infection management, and tissue regeneration. Protein-Sol helps customize therapeutic proteins to stay accessible and effective within the pulp tissue or root canal by comparing exposed and buried residues. Furthermore, the design of targeted therapeutics is further guided by the visualization of energy and charge heat maps, accessible surface areas, and ionizable groups. These work together to improve the creation of biocompatible and efficient biomaterials, which improves root canal therapy results, infection prevention, and endodontic tissue reconstruction.