In Silico Approach for the Identification of Potential Targets and Specific Antimicrobials for Streptococcus mutans

摘要

Tooth decay affects most of the population in developed countries. The multifactorial etiology of the disease includes multiple bacterial species, S. mutans is the main pathogen associated with the disease. This bacterium adheres to the tooth surface and allows the colonization of other microorganisms resulting in dental biofilm. Several therapeutic agents are available to treat or prevent tooth decay, but none, with the exception of fluoride, has significantly influenced the disease’s global burden. Moreover, the probable development of resistance of microorganisms to existing antibacterial agents and the scarcity of good antimicrobial agents motivates this effort for innovation. The detailed knowledge obtained in recent years on the S. mutans allowed the identification of potential targets in this microorganism, enabling the development of specific drugs to combat tooth decay. Thus, the identification of potential targets in these pathogens is the first step in the discovery process of new therapeutic agents. Currently, the experimental assays used for this purpose are expensive and time consuming. In contrast, bioinformatics methods to predict drug targets are cheap, quick and workaday in the biotechnology. This article will review the potential drug targets in S. mutans, as well as the bioinformatics methods used to identify these targets and effective drugs for specific pharmacological treatment of dental caries.