performed a similar study and estimated that 4479 genes can be drugged or are
druggable out of total 20,300 annotated protein-coding genes as per Ensembl
version 73 (https://www.ensembl.org/) covering *22% of total. They reported that
there could be 2282 genes more than earlier reports of the druggable human genome [22].
Systems biology approaches have been used for decades for predicting target
genes in case of infectious diseases [2], studying systems approaches, e.g., metabolic control analysis (MCA) and flux balance analysis (FBA). Systems genetics
approaches have also been used for identification of novel disease genes in rat and
human [23]. Molecular networks information can be used for improving drug
discovery projects at several stages from target identification utilizing information
of existing data about drug–target association [24]. Metabolic and signaling pathway [25] and genome-wide association are studied in detail for identification of new
target proteins and their interactions [26]. Genome-led methods provide a new
pathway or a class of protein(s) as target.
Pharmacophore designed from ligands of a target protein can be looked for
assessing binding site similarity for the proteins of same family as well as it can be
used to compare binding site similarity for proteins from different families of
proteins for selectivity. In recent times, several highly selective inhibitors of such
protein(s) have been found to assess the multitarget activity. For example, c-Abl
inhibitor imatinib [27] was approved as drug for chronic myeloid leukemia, but its
clinical utility is widened after finding that it has shown significant activity against
several other important targets, e.g., tyrosine-protein kinase kit (c-KIT or CD117).
Similarly, sorafenib affects tumor proliferation and tumor angiogenesis pathways
due to its multikinase inhibitory activity [28]. Sunitinib is also approved for being a
multiprotein kinase inhibitor with similar effects as sorafenib [28].
1.3 Starting of Structure-Based Drug Design
One of the successful stories of the structure-based drug design started in the early
eighties with purine nucleoside phosphorylase (PNP), targeted as a salvage enzyme
important to inhibit, so that T-cell-mediated activation of immune system is suppressed. PNP is an important enzyme involved in purine salvage and catabolism
[29]. Inactivity of PNP has been found to show adverse effect on T-cell proliferation
[30]. Human PNP, a homotrimer with each subunit of molecular weight 97 kD,
shows substrate specificity for guanine, inosine, and other 6-oxypurines analogs,
while bacterial PNP shows specificity for adenine [30] also. PNP active site consists
of three binding subsites: purine-binding site (Fig. 1, shown in cyan), hydrophobic
site (or ribose-binding site, Fig. 1, shown in blue), and phosphate-binding site
(Fig. 1, colored purple) [31]. In attempt to design potent PNP inhibitors, considering the features of three subsites of PNP binding site and three-dimensional
structure of PNP as starting point, an iterative process of modeling inhibitor-bound
structure, conformational search using Monte Carlo method followed by energy
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
113
druggable out of total 20,300 annotated protein-coding genes as per Ensembl
version 73 (https://www.ensembl.org/) covering *22% of total. They reported that
there could be 2282 genes more than earlier reports of the druggable human genome [22].
Systems biology approaches have been used for decades for predicting target
genes in case of infectious diseases [2], studying systems approaches, e.g., metabolic control analysis (MCA) and flux balance analysis (FBA). Systems genetics
approaches have also been used for identification of novel disease genes in rat and
human [23]. Molecular networks information can be used for improving drug
discovery projects at several stages from target identification utilizing information
of existing data about drug–target association [24]. Metabolic and signaling pathway [25] and genome-wide association are studied in detail for identification of new
target proteins and their interactions [26]. Genome-led methods provide a new
pathway or a class of protein(s) as target.
Pharmacophore designed from ligands of a target protein can be looked for
assessing binding site similarity for the proteins of same family as well as it can be
used to compare binding site similarity for proteins from different families of
proteins for selectivity. In recent times, several highly selective inhibitors of such
protein(s) have been found to assess the multitarget activity. For example, c-Abl
inhibitor imatinib [27] was approved as drug for chronic myeloid leukemia, but its
clinical utility is widened after finding that it has shown significant activity against
several other important targets, e.g., tyrosine-protein kinase kit (c-KIT or CD117).
Similarly, sorafenib affects tumor proliferation and tumor angiogenesis pathways
due to its multikinase inhibitory activity [28]. Sunitinib is also approved for being a
multiprotein kinase inhibitor with similar effects as sorafenib [28].
1.3 Starting of Structure-Based Drug Design
One of the successful stories of the structure-based drug design started in the early
eighties with purine nucleoside phosphorylase (PNP), targeted as a salvage enzyme
important to inhibit, so that T-cell-mediated activation of immune system is suppressed. PNP is an important enzyme involved in purine salvage and catabolism
[29]. Inactivity of PNP has been found to show adverse effect on T-cell proliferation
[30]. Human PNP, a homotrimer with each subunit of molecular weight 97 kD,
shows substrate specificity for guanine, inosine, and other 6-oxypurines analogs,
while bacterial PNP shows specificity for adenine [30] also. PNP active site consists
of three binding subsites: purine-binding site (Fig. 1, shown in cyan), hydrophobic
site (or ribose-binding site, Fig. 1, shown in blue), and phosphate-binding site
(Fig. 1, colored purple) [31]. In attempt to design potent PNP inhibitors, considering the features of three subsites of PNP binding site and three-dimensional
structure of PNP as starting point, an iterative process of modeling inhibitor-bound
structure, conformational search using Monte Carlo method followed by energy
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
113