From Genome to Drugs: New Approaches in Antimicrobial Discovery

Abstract

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a “big-data era” that improves target selection and lead compound identification in a cost-effective and shortened timeline.

Integrating diverse layers of omic data to identify novel drug targets in Listeria monocytogenes

“…In this sense, Target-Pathogen (http://target.sbg.qb.fcen.uba.ar) is a unique resource that combines structural druggability datasets, essentiality analysis, metabolic context, genomic and expression data to rank proteins according to their potential to be used as novel targets. Previous reports from our and other groups have selected and prioritized molecular targets of several relevant pathogens such as Mycobacterium tuberculosis (Defelipe et al, 2016), Klebsiella pneumoniae (Ramos et al, 2018;Serral et al, 2021, Serral et al, 2022, Bartonella bacilliformis (Farfán-López et al, 2020), Trypanosoma cruzi (Osorio-Méndez andCevallos, 2018;Coutinho et al, 2021) and Schistosoma mansoni (Lobo-Silva et al, 2020) using Target-Pathogen.…”

From drugs to targets: Reverse engineering the virtual screening process on a proteomic scale

“…Currently, it is accepted that the identification of appropriate targets is a critical step in the design of new drugs. In the postgenomic era, integrative computational approaches facilitate the identification and prioritization of candidate targets (Serral et al, 2021). Target-Pathogen (http://target.sbg.…”

Computer-Based Identification of Potential Druggable Targets in Multidrug-Resistant Acinetobacter baumannii: A Combined In Silico, In Vitro and In Vivo Study

“…This is based on the utilization of vast available OMICS datasets of different microbes, which offer an increased number of opportunities for drug discovery against resistant pathogens. Subtractive proteomics, metabolic pathways analysis and structural bioinformatics approaches are now employed for the development of new drugs and combating antimicrobial resistance, acting as a complement to conventional approaches [ 10 ].…”

“…Subtractive proteomics, the approach used in the current study, allows for the selection of vital proteins related to the pathogen while absent in the host, followed by checking the presence of drug molecules with possible binding affinity to these proteins in a channel known as “druggability”. These proteins are then regarded as putative drug targets [ 10 ]. These drug targets are also checked for cytoplasmic localization in addition to conservation to ensure their use in the control of multiple strains of A. baumannii .…”