History and background
Motivation
Pathogenic bacteria are dynamically evolving organisms that are capable of causing infections in a large variety of hosts, including humans, animals, plants, and insects. The discovery and deployment of antibiotics had a massive impact on modern medicine (…) Unfortunately, antibiotics are a victim of their own success since their broad availability, low cost and tremendous effectiveness has led to their overuse in hospitals and agricultural settings. This has created ideal conditions for the selection and spread of antimicrobial resistant microorganisms. (Pletzer & Hancock 2016)
Drug and multi-drug resistant (MDR) strains are emerging with increasing frequency and rendering ineffective many conventional antibiotic treatments.
Recent statistics from the Centers of Disease Control and Prevention (CDC) indicate that, each year, at least 2 million people become infected with
antibiotic-resistant bacteria in the USA and 23,000 people die as a direct result of these infections (http://www.cdc.gov/drugresistance/). Therefore,
researchers are searching for alternative antimicrobial agents with different mechanisms of action. This is the case of the antimicrobial peptides (AMP).
Antimicrobial Peptides (AMP)
AMP are short-length peptides (between 15 and 30 amino acids), the majority of which are cationic, amphipathic, gene-encoded and directed to the cell membrane. AMP are part of the innate immune system of animals and plants, but can also be found in bacteria and fungi. AMP have been recognized as promising candidates for replacing classical antibiotics due to their multiple mechanisms of action and low specificity in terms of molecular targets, which reduces the chance of acquired resistance. (Jorge et al. 2012)
Recent studies have also demonstrated that peptides can be used in conjunction with antibiotics, antifungals, or other antimicrobial compounds, which leads to enhanced activity (i.e. synergistic effects). Lowering antibiotic concentrations helps to reduce expenses, toxic side effects, and the spread of antimicrobial resistance. Synergy with peptides can also enhance the activity of antibiotics against multidrug resistant strains. (Pletzer et al. 2016)
Bioinformatics for Antimicrobial Combinations
Bioinformatics approaches, such as network reconstructions, may help to profile the results of combination studies and, in particular, the added value of
including AMP in antimicrobial drugs. Pharmacological networks are commonly used to map the data resulting of combination studies, and help to explore new
combinations at the global scale. Previous works on drug-drug interaction (DDI) and pharmacokinetics reconstructions have shown that text mining tools can
relieve part of this manual workload while preserving annotation quality (Percha & Altman 2013). Scientific manuscripts may be automatically annotated,
prioritised, and filtered according to the directives of human experts and with the support of natural language processing tools and domain-specific
controlled vocabulary.