99
bioinformatics approaches (metabolic modelling, enzyme regulation based strategy,
and enzyme regulation based strategy) and 64 metabolic enzymes targets were identified (Kaltdorf et al. 2016).
Protein targets can also be predicted by the host pathogen interactions caused in
the process of infection. Such an approach was applied by Remmele et al., where
the protein-protein interaction network of human Aspergillus fumigatus and human
Candida albicans was determined based on yeast and human intraspecies networks
(Remmele et al. 2015). The reconstruction of the metabolic network provided several novel host pathogen interaction candidates, for instance, the anti-fungal host
protein APP and the Candida virulence factor PLB (Remmele et  al. 2015)
(Table 4.5).
Table 4.5 Different in silico methods geared towards the studies of drug targets
Organism
Disease
Methods applied for
analysis
Outcome
Reference
Entamoeba
histolytica
Amoebiasis
MOLREP; REFMAC
5.5; COOT; PyMOL;
MOLPROBITY; DS
suite 4.0; AutoDock
Vina Tools; Gromacs
5.1.4 suite; PRODRG;
MM –PBSA
Identified the active
site of Entamoeba
histolytica Arginase
(EhArg); novel
drugs from the drug
library
Malik et al.
(2019)
Candida albicans Fungal
infections
SWISSMODEL
server; ERRAT;
PROCHECK;
AutoDock Tools;
Accelrys DS (ver.
2.5.5); Chem- Axon
Marvin Sketch
5.3.735; Avogadro
v1.1.1; Accelrys DS
3D model of the C.
albicans FBA-II as
the target against
azole resistant
fungal pathogens
Semenyuta
et al. (2019)
Mycobacterium
tuberculosis
Tuberculosis
Metabolic pathways
(KEGG; Clustal
Omega; Blastp;
DEG); AutoDock v
4.2.6; AutoDock Tools
5 proteins as
potential drug
target
Uddin et al.
(2019)
Staphylococcus
aureus
Infectious
diseases
caused by
methicillinresistant
Molecular modelling,
Mesh Ewald (PME)
method; GROMACS;
Nanoplexes as a
promising delivery
system to combat
MRSA infections
Hassan
et al. (2019)
(continued)
4 In Silico Approaches for Prioritizing Drug Targets in Pathogens