ChemInform Abstract: Evolution of Graph Theory‐Based QSAR Methods and Their Applications to the Search for New Antibacterial Agents

Abstract

Resistance of bacteria to current antibiotics has increased worldwide, being one of the leading unresolved situa- tions in public health. Due to negligence regarding the treatment of community-acquired diseases, even healthcare facili- ties have been highly impacted by an emerging problem: nosocomial infections. Moreover, infectious diseases, including nosocomial infections, have been found to depend on multiple pathogenicity factors, confirming the need to discover of multi-target antibacterial agents. Drug discovery is a very complex, expensive, and time-consuming process. In this sense, Quantitative Structure-Activity Relationships (QSAR) methods have become complementary tools for medicinal chemis- try, permitting the efficient screening of potential drugs, and consequently, rationalizing the organic synthesis as well as the biological evaluation of compounds. In the consolidation of QSAR methods as important components of chemoinfor- matics, the use of mathematical chemistry, and more specifically, the use of graph-theoretical approaches has played a vi- tal role. Here, we focus our attention on the evolution of QSAR methods, citing the most relevant works devoted to the development of promising graph-theoretical approaches in the last 8 years, and their applications to the prediction of anti- bacterial activities of chemicals against pathogens causing both community-acquired and nosocomial infections.