Adila Nazli, Jingyi Qiu, Ziyi Tang and Yun He* Pages 464 - 501 ( 38 )
Background: With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.
Methods: In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.
Results: Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.
Conclusion: The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.
Antibacterial, omics, machine learning, bioinformatics, drug target, bacterial cytological profiling.