103
Calderone A, Licata L, Cesareni G (2015) VirusMentha: a new resource for virus-host protein
interactions. Nucleic Acids Res 43(Database issue):D588–D592. https://doi.org/10.1093/
nar/gku830
Castilho VVS, Goncalves KCS, Rebello KM, Baptista LPR, Sangenito LS, Santos HLC et al
(2018) Docking simulation between HIV peptidase inhibitors and Trypanosoma cruzi aspartyl
peptidase. BMC Res Notes 11(1):825. https://doi.org/10.1186/s13104-018-3927-z
Centers for Disease Control and Prevention (2013) https://www.cdc.gov/drugresistance/pdf/arthreats-2013-508.pdf
Chanumolu SK, Rout C, Chauhan RS (2012) UniDrug-target: a computational tool to identify
unique drug targets in pathogenic bacteria. PLoS One 7(3):e32833. https://doi.org/10.1371/
journal.pone.0032833
Chavali AK, D’Auria KM, Hewlett EL, Pearson RD, Papin JA (2012) A metabolic network
approach for the identification and prioritization of antimicrobial drug targets. Trends Microbiol
20(3):113–123. https://doi.org/10.1016/j.tim.2011.12.004
Chellasamy SK, Devarajan S (2019) Identification of potential lead molecules for Zika envelope
protein from in silico perspective. Avicenna J Med Biotechnol 11(1):94–103
Cichonska A, Ravikumar B, Parri E, Timonen S, Pahikkala T, Airola A et al (2017) Computationalexperimental approach to drug-target interaction mapping: A case study on kinase inhibitors.
PLoS Comput Biol 13(8):e1005678. https://doi.org/10.1371/journal.pcbi.1005678
De Clercq E, Li G (2016) Approved antiviral drugs over the past 50 years. Clin Microbiol Rev
29(3):695–747. https://doi.org/10.1128/CMR.00102-15
De Maayer P, Chan WY, Rubagotti E, Venter SN, Toth IK, Birch PR et al (2014) Analysis of
the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and
interact with plant, insect and vertebrate hosts. BMC Genomics 15:404. https://doi.
org/10.1186/1471-2164-15-404
de Sarom A, Kumar Jaiswal A, Tiwari S, de Castro Oliveira L, Barh D, Azevedo V et al (2018)
Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive
genomics approaches to control Haemophilus ducreyi, the causative agent of chancroid. J R
Soc Interface 15(142):20180032. https://doi.org/10.1098/rsif.2018.0032
Denning DW, Perlin DS, Muldoon EG, Colombo AL, Chakrabarti A, Richardson MD et al (2017)
Delivering on antimicrobial resistance agenda not possible without improving fungal diagnostic capabilities. Emerg Infect Dis 23(2):177–183. https://doi.org/10.3201/eid2302.152042
Donati C, Hiller NL, Tettelin H, Muzzi A, Croucher NJ, Angiuoli SV et al (2010) Structure
and dynamics of the pan-genome of Streptococcus pneumoniae and closely related species.
Genome Biol 11(10):R107. https://doi.org/10.1186/gb-2010-11-10-r107
Durmus Tekir S, Cakir T, Ardic E, Sayilirbas AS, Konuk G, Konuk M et al (2013) PHISTO:
pathogen- host interaction search tool. Bioinformatics 29(10):1357–1358. https://doi.
org/10.1093/bioinformatics/btt137
Elsheikha HM, McOrist S, Geary TG (2011) Antiparasitic drugs: mechanisms of action and resistance. Essent Vet Parasitol 187:1
Fabregat A, Jupe S, Matthews L, Sidiropoulos K, Gillespie M, Garapati P et al (2018) The
Reactome pathway knowledgebase. Nucleic Acids Res 46(D1):D649–D655. https://doi.
org/10.1093/nar/gkx1132
Fang X, Wallqvist A, Reifman J (2010) Development and analysis of an in vivo- compatible
metabolic network of Mycobacterium tuberculosis. BMC Syst Biol 4:160. https://doi.
org/10.1186/1752-0509-4-160
Gao Z, Li H, Zhang H, Liu X, Kang L, Luo X et al (2008) PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics 9:104. https://doi.
org/10.1186/1471-2105-9-104
Götte M (2012) The distinct contributions of fitness and genetic barrier to the development of antiviral drug resistance. Curr Opin Virol 2(5):644–650. https://doi.org/10.1016/j.coviro.2012.08.004
Guimaraes LC, Florczak-Wyspianska J, de Jesus LB, Viana MV, Silva A, Ramos RT et al (2015)
Inside the pan-genome – methods and software overview. Curr Genomics 16(4):245–252.
https://doi.org/10.2174/1389202916666150423002311
4 In Silico Approaches for Prioritizing Drug Targets in Pathogens
Calderone A, Licata L, Cesareni G (2015) VirusMentha: a new resource for virus-host protein
interactions. Nucleic Acids Res 43(Database issue):D588–D592. https://doi.org/10.1093/
nar/gku830
Castilho VVS, Goncalves KCS, Rebello KM, Baptista LPR, Sangenito LS, Santos HLC et al
(2018) Docking simulation between HIV peptidase inhibitors and Trypanosoma cruzi aspartyl
peptidase. BMC Res Notes 11(1):825. https://doi.org/10.1186/s13104-018-3927-z
Centers for Disease Control and Prevention (2013) https://www.cdc.gov/drugresistance/pdf/arthreats-2013-508.pdf
Chanumolu SK, Rout C, Chauhan RS (2012) UniDrug-target: a computational tool to identify
unique drug targets in pathogenic bacteria. PLoS One 7(3):e32833. https://doi.org/10.1371/
journal.pone.0032833
Chavali AK, D’Auria KM, Hewlett EL, Pearson RD, Papin JA (2012) A metabolic network
approach for the identification and prioritization of antimicrobial drug targets. Trends Microbiol
20(3):113–123. https://doi.org/10.1016/j.tim.2011.12.004
Chellasamy SK, Devarajan S (2019) Identification of potential lead molecules for Zika envelope
protein from in silico perspective. Avicenna J Med Biotechnol 11(1):94–103
Cichonska A, Ravikumar B, Parri E, Timonen S, Pahikkala T, Airola A et al (2017) Computationalexperimental approach to drug-target interaction mapping: A case study on kinase inhibitors.
PLoS Comput Biol 13(8):e1005678. https://doi.org/10.1371/journal.pcbi.1005678
De Clercq E, Li G (2016) Approved antiviral drugs over the past 50 years. Clin Microbiol Rev
29(3):695–747. https://doi.org/10.1128/CMR.00102-15
De Maayer P, Chan WY, Rubagotti E, Venter SN, Toth IK, Birch PR et al (2014) Analysis of
the Pantoea ananatis pan-genome reveals factors underlying its ability to colonize and
interact with plant, insect and vertebrate hosts. BMC Genomics 15:404. https://doi.
org/10.1186/1471-2164-15-404
de Sarom A, Kumar Jaiswal A, Tiwari S, de Castro Oliveira L, Barh D, Azevedo V et al (2018)
Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive
genomics approaches to control Haemophilus ducreyi, the causative agent of chancroid. J R
Soc Interface 15(142):20180032. https://doi.org/10.1098/rsif.2018.0032
Denning DW, Perlin DS, Muldoon EG, Colombo AL, Chakrabarti A, Richardson MD et al (2017)
Delivering on antimicrobial resistance agenda not possible without improving fungal diagnostic capabilities. Emerg Infect Dis 23(2):177–183. https://doi.org/10.3201/eid2302.152042
Donati C, Hiller NL, Tettelin H, Muzzi A, Croucher NJ, Angiuoli SV et al (2010) Structure
and dynamics of the pan-genome of Streptococcus pneumoniae and closely related species.
Genome Biol 11(10):R107. https://doi.org/10.1186/gb-2010-11-10-r107
Durmus Tekir S, Cakir T, Ardic E, Sayilirbas AS, Konuk G, Konuk M et al (2013) PHISTO:
pathogen- host interaction search tool. Bioinformatics 29(10):1357–1358. https://doi.
org/10.1093/bioinformatics/btt137
Elsheikha HM, McOrist S, Geary TG (2011) Antiparasitic drugs: mechanisms of action and resistance. Essent Vet Parasitol 187:1
Fabregat A, Jupe S, Matthews L, Sidiropoulos K, Gillespie M, Garapati P et al (2018) The
Reactome pathway knowledgebase. Nucleic Acids Res 46(D1):D649–D655. https://doi.
org/10.1093/nar/gkx1132
Fang X, Wallqvist A, Reifman J (2010) Development and analysis of an in vivo- compatible
metabolic network of Mycobacterium tuberculosis. BMC Syst Biol 4:160. https://doi.
org/10.1186/1752-0509-4-160
Gao Z, Li H, Zhang H, Liu X, Kang L, Luo X et al (2008) PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics 9:104. https://doi.
org/10.1186/1471-2105-9-104
Götte M (2012) The distinct contributions of fitness and genetic barrier to the development of antiviral drug resistance. Curr Opin Virol 2(5):644–650. https://doi.org/10.1016/j.coviro.2012.08.004
Guimaraes LC, Florczak-Wyspianska J, de Jesus LB, Viana MV, Silva A, Ramos RT et al (2015)
Inside the pan-genome – methods and software overview. Curr Genomics 16(4):245–252.
https://doi.org/10.2174/1389202916666150423002311
4 In Silico Approaches for Prioritizing Drug Targets in Pathogens