102
4.8 Conclusion and Future Prospective
Many approaches have been used for the identification of drug targets in pathogens.
In the last two decades with the advent of the new sequencing platforms, drug discovery has observed a shift from the traditional approaches to rational drug target
identification and target driven lead compounds discovery. One strategy that has
been applied to identify new targets is the prediction of epitopes that culminates in
the proposition of vaccines formed by multiple selected epitopes. The bioinformatics analyses, the discovery of potential drug targets became a rapid and less expensive way. Not only the software but also the compounds databases became important
tools in the process of drug target prioritization, making them imperative of frequent
updates be made. It is logical to believe that in the coming year’s specific drug discovery against antimicrobial resistance will increasingly benefit from large scale
informatics, modelling, and simulations.
References
Ammari MG, Gresham CR, McCarthy FM, Nanduri B (2016) HPIDB 2.0: a curated database for
host-pathogen interactions. Database (Oxford) 2016. https://doi.org/10.1093/database/baw103
Andes D, Pascual A, Marchetti O (2009) Antifungal therapeutic drug monitoring: established and
emerging indications. Antimicrob Agents Chemother 53(1):24–34. https://doi.org/10.1128/
AAC.00705-08
Balouiri M, Sadiki M, Ibnsouda SK (2016) Methods for in vitro evaluating antimicrobial activity:
a review. J Pharm Anal 6(2):71–79. https://doi.org/10.1016/j.jpha.2015.11.005
Barh D, Tiwari S, Jain N, Ali A, Santos AR, Misra AN et al (2011) In silico subtractive genomics
for target identification in human bacterial pathogens. Drug Dev Res 72(2):162–177. https://
doi.org/10.1002/ddr.20413
Barnes RA, White PL, Bygrave C, Evans N, Healy B, Kell J (2009) Clinical impact of enhanced
diagnosis of invasive fungal disease in high-risk haematology and stem cell transplant patients.
J Clin Pathol 62(1):64–69. https://doi.org/10.1136/jcp.2008.058354
Becattini S, Taur Y, Pamer EG (2016) Antibiotic-induced changes in the intestinal microbiota and
disease. Trends Mol Med 22(6):458–478. https://doi.org/10.1016/j.molmed.2016.04.003
Bleves S, Dunger I, Walter MC, Frangoulidis D, Kastenmuller G, Voulhoux R et al (2014)
HoPaCI-DB: host-Pseudomonas and Coxiella interaction database. Nucleic Acids Res
42(Database issue):D671–D676. https://doi.org/10.1093/nar/gkt925
Bragg RR, Meyburgh CM, Lee JY, Coetzee M (2018) Potential treatment options in a postantibiotic era. Adv Exp Med Biol 1052:51–61. https://doi.org/10.1007/978-981-10-7572-8_5
Brandl K, Plitas G, Mihu CN, Ubeda C, Jia T, Fleisher M et al (2008) Vancomycin-resistant enterococci exploit antibiotic-induced innate immune deficits. Nature 455(7214):804–807. https://
doi.org/10.1038/nature07250
Brown GD, Denning DW, Gow NAR, Levitz SM, Netea MG, White TC (2012) Hidden killers: human fungal infections. Science Translational Medicine 4(165):165rv113. https://doi.
org/10.1126/scitranslmed.3004404
Bruno A, Costantino G, Sartori L, Radi M (2017) The in silico drug discovery toolbox: applications in lead discovery and optimization. Curr Med Chem 26:3838–3873. https://doi.org/1
0.2174/0929867324666171107101035
M. Santana et al.
4.8 Conclusion and Future Prospective
Many approaches have been used for the identification of drug targets in pathogens.
In the last two decades with the advent of the new sequencing platforms, drug discovery has observed a shift from the traditional approaches to rational drug target
identification and target driven lead compounds discovery. One strategy that has
been applied to identify new targets is the prediction of epitopes that culminates in
the proposition of vaccines formed by multiple selected epitopes. The bioinformatics analyses, the discovery of potential drug targets became a rapid and less expensive way. Not only the software but also the compounds databases became important
tools in the process of drug target prioritization, making them imperative of frequent
updates be made. It is logical to believe that in the coming year’s specific drug discovery against antimicrobial resistance will increasingly benefit from large scale
informatics, modelling, and simulations.
References
Ammari MG, Gresham CR, McCarthy FM, Nanduri B (2016) HPIDB 2.0: a curated database for
host-pathogen interactions. Database (Oxford) 2016. https://doi.org/10.1093/database/baw103
Andes D, Pascual A, Marchetti O (2009) Antifungal therapeutic drug monitoring: established and
emerging indications. Antimicrob Agents Chemother 53(1):24–34. https://doi.org/10.1128/
AAC.00705-08
Balouiri M, Sadiki M, Ibnsouda SK (2016) Methods for in vitro evaluating antimicrobial activity:
a review. J Pharm Anal 6(2):71–79. https://doi.org/10.1016/j.jpha.2015.11.005
Barh D, Tiwari S, Jain N, Ali A, Santos AR, Misra AN et al (2011) In silico subtractive genomics
for target identification in human bacterial pathogens. Drug Dev Res 72(2):162–177. https://
doi.org/10.1002/ddr.20413
Barnes RA, White PL, Bygrave C, Evans N, Healy B, Kell J (2009) Clinical impact of enhanced
diagnosis of invasive fungal disease in high-risk haematology and stem cell transplant patients.
J Clin Pathol 62(1):64–69. https://doi.org/10.1136/jcp.2008.058354
Becattini S, Taur Y, Pamer EG (2016) Antibiotic-induced changes in the intestinal microbiota and
disease. Trends Mol Med 22(6):458–478. https://doi.org/10.1016/j.molmed.2016.04.003
Bleves S, Dunger I, Walter MC, Frangoulidis D, Kastenmuller G, Voulhoux R et al (2014)
HoPaCI-DB: host-Pseudomonas and Coxiella interaction database. Nucleic Acids Res
42(Database issue):D671–D676. https://doi.org/10.1093/nar/gkt925
Bragg RR, Meyburgh CM, Lee JY, Coetzee M (2018) Potential treatment options in a postantibiotic era. Adv Exp Med Biol 1052:51–61. https://doi.org/10.1007/978-981-10-7572-8_5
Brandl K, Plitas G, Mihu CN, Ubeda C, Jia T, Fleisher M et al (2008) Vancomycin-resistant enterococci exploit antibiotic-induced innate immune deficits. Nature 455(7214):804–807. https://
doi.org/10.1038/nature07250
Brown GD, Denning DW, Gow NAR, Levitz SM, Netea MG, White TC (2012) Hidden killers: human fungal infections. Science Translational Medicine 4(165):165rv113. https://doi.
org/10.1126/scitranslmed.3004404
Bruno A, Costantino G, Sartori L, Radi M (2017) The in silico drug discovery toolbox: applications in lead discovery and optimization. Curr Med Chem 26:3838–3873. https://doi.org/1
0.2174/0929867324666171107101035
M. Santana et al.