**3.4 Undruggable targets and NGS**

As mentioned above, an "Undruggable" target is a term given to sets of proteins that cannot be targeted by a specific treatment, yet they can be exploited for the development of treatments for various diseases.

Among these undruggable targets are non-enzymatic proteins, transcriptional factors, regulatory proteins, and scaffolding proteins [200, 201]. One such undruggable target is the Kristen Rat Sarcoma (KRAS) protein encoding a viral oncogene, detected in non-small cell lung cancer (NSCLC). Recently, KRAS mutations have been successfully targeted using different approaches, such as inhibition of downstream effectors, epigenomic approaches, post-translational modifications, and high-affinity KRAS binders, among others, wherein direct pharmacological inhibition of a *KRAS p.G12C* mutation is deemed possible, thus serving as an effective targeted treatment available for patients with advanced NSCLC [202]. Moreover, other members of the RAS family are deemed as undruggable targets in cancer, and several approaches have been used. Kato et al. have used NGS to evaluate the mutational status of 1937 patients with different cancers, and have observed that over 20% presented *RAS* alterations. Unfortunately, poor overall survival has been observed in spite of various treatment options that are offered; however, a better survival is observed for patients treated using a combined therapy targeting MAPK and non-MAPK pathways [203]. Among other undruggable targets, MYC and TP53 are known to have no enzymatic activities, and are located intracellularly. However, a Phase III trial is undergoing for TP53 using the APR-246 drug for myelodysplastic syndrome, and although there are no current clinical trials for MYC, an anti-MYC compound, OmoMYC, has been validated in multiple preclinical studies [204].

In other efforts, Zhou et al. have proposed the use of neoantigens, collected from patients with gastric cancer, for targeted therapies for gastric cancer disease [181]. In this study, six highly mutated genes along with high frequency HLA alleles have been identified, thus rendering neoantigens of these six genes as possible targets for immunotherapy of gastric cancer [205]. In another study on neuroblastoma, it is reported that a *MYCN* gene can be transformed into a druggable target by targeting different regulators of its pathway, such as β-estradiol and MAPK/ERK [206].

#### **3.5 Drug resistance and NGS**

Using NGS, a new gene was identified in *Acinetobacter baumannii* strain 863 conferring multi-drug resistance to this bacterial pathogen [207]. In another study, an antibiotic resistance signature of 25 genes was differentially expressed in *Staphylococcus aureus* [208]. Furthermore, it was reported that NGS might be successfully used for early identification of mutations related to drug resistance in transplant patients treated for cytomegalovirus [209].

In other studies, metagenomics NGS assays have been used to identify microbial composition and antibiotic resistance in water samples of Puget Sound (Washington State), and have reported that this could serve as a reliable protocol for providing accurate information on bacterial composition and antibiotic resistance in water samples [210]. Leprohon et al. have reviewed all critical information relevant to drug resistance and to resistance mechanism(s) in Leishmania infections generated from NGS analysis [211]. Furthermore, NGS has been successfully used for testing for HIV-1 drug resistance, although such studies are yet to be standardized [212–216]. Likewise, NGS and pyrosequencing have been used to investigate resistance of the *Influenta A* virus to baloxavir [217]. Moreover, NGS has also been used for detection of those *H. pylori* clones that are resistant to levofloxacin [218]. While RNA-seq data have been mined to identify novel fusion genes in gastrointestinal stromal tumor patients with resistance to imatinib [219].

### **4. DrugBank**

Another important set of tools in drug discovery are the collective databases of drugs with detailed information about drugs, including their actions and targets. One such database is DrugBank, launched back in 2006, as it combines various resources offering clinical information, including chemical information about drugs and resources [220]. The main focus of DrugBank is to offer information relavent to mechanistic data, structures, and sequences about drugs and their targets. Furthermore, this resource is capable of providing tools for viewing, sorting, and searching both sequence and structure data [220]. Lately, DrugBank database has been further improved, as it now can offer information about 1467 FDAapproved drugs, 123 biotech drugs, 69 nutraceuticals, 4774 small molecule drugs, and 3116 experimental or unapproved drugs. There is also information related to withdrawn [57] and illicit [188] drugs. Furthermore, it has a higher drug target database for FDA-approved drugs, which includes 1565 non-redundant protein/ DNA targets [221].

Due to its wealth of information, DrugBank has been used for a variety of drug applications, including target prediction [222], *in silico* discovery [223], metabolism prediction [224], docking or screening [225], as well as new uses of old drugs [226]. Additional applications are presented in **Table 3**.

**71**

2006 until 2020.

**Table 3.**

analysis [246–248].

**5. NGS in SARS-CoV-2 drug discovery**

*Microarrays and NGS for Drug Discovery DOI: http://dx.doi.org/10.5772/intechopen.96657*

Virtual drug screening Repositioning

Drug-target identification

Molecular docking and simulation studies

Drug metabolism prediction

Drug screening/ discovery

resistance

Molecular docking, drug

Molecular docking, molecular dynamic simulation

Multi regulatory pathways construction

Pharmacological drug mechanism

*Applications of the DrugBank database.*

Although **Table 3** presents only a few studies employing the DrugBank database, a PubMed search for DrugBank has identified at least 505 published articles, from

**Type of application Drug tested Disease Reference(s)**

Rheumatoid arthritis [227]

SARS-CoV-2 M pro [228]

SARS-CoV-2 [231]

SARS-CoV-2 [233]

Pancreatic cancer [237]

Cervical cancer [242]

SARS-CoV-2 [238, 239]

[229]

[230]

[232]

[235]

[236]

hM2 allosteric modulation

Events

Carbapenems *Acinetobacter baumannii*

Seniors' Metabolism of Medications and Avoiding Adverse Drug

OXA class enzymes

Treatment of resistant

depression

metastasis

Aloperine Cardiovascular disease [241]

Traditional Chinese medicine derived from *Trachelospermum* 

Mitoxantrone, Leucovorin, Birinapant, and Dynasore

*jasminoides*

Dequalinium

proteins

ACE2

depression

proteases

related genes

Drug repositioning Drugs that target genes

Drug repurposing Drugs that inhibit

Drug screening Drugs targeting immune-

Drugs related to P450 cytochrome enzymes

All drugs correlated to viral

Approve drug libraries for

in pathways for treating

Pharmacological analysis JianPi Fu Recipe Colon cancer LoVo cells

Pivotal Drugs for pancreatic cancer

*In silico* screening Glycoprotein inhibitors SARS-CoV-2 [234]

Drug repurposing Hypertension [240]

As infections with the SARS-CoV-2 virus have become more aggressive, there is an urgent need for evaluating different drugs that may contribute to a better and effective treatment of this infection. The majority of drugs used for SARS-CoV-2 treatment are drugs currently in use for treatment of other diseases [243–245], and these have been evaluated for their efficacy using computational drug discovery

### *Microarrays and NGS for Drug Discovery DOI: http://dx.doi.org/10.5772/intechopen.96657*

*Drug Design - Novel Advances in the Omics Field and Applications*

transplant patients treated for cytomegalovirus [209].

tinal stromal tumor patients with resistance to imatinib [219].

and MAPK/ERK [206].

**4. DrugBank**

DNA targets [221].

Additional applications are presented in **Table 3**.

**3.5 Drug resistance and NGS**

In other efforts, Zhou et al. have proposed the use of neoantigens, collected from patients with gastric cancer, for targeted therapies for gastric cancer disease [181]. In this study, six highly mutated genes along with high frequency HLA alleles have been identified, thus rendering neoantigens of these six genes as possible targets for immunotherapy of gastric cancer [205]. In another study on neuroblastoma, it is reported that a *MYCN* gene can be transformed into a druggable target by targeting different regulators of its pathway, such as β-estradiol

Using NGS, a new gene was identified in *Acinetobacter baumannii* strain 863 conferring multi-drug resistance to this bacterial pathogen [207]. In another study, an antibiotic resistance signature of 25 genes was differentially expressed in *Staphylococcus aureus* [208]. Furthermore, it was reported that NGS might be successfully used for early identification of mutations related to drug resistance in

In other studies, metagenomics NGS assays have been used to identify micro-

Another important set of tools in drug discovery are the collective databases of drugs with detailed information about drugs, including their actions and targets. One such database is DrugBank, launched back in 2006, as it combines various resources offering clinical information, including chemical information about drugs and resources [220]. The main focus of DrugBank is to offer information relavent to mechanistic data, structures, and sequences about drugs and their targets. Furthermore, this resource is capable of providing tools for viewing, sorting, and searching both sequence and structure data [220]. Lately, DrugBank database has been further improved, as it now can offer information about 1467 FDAapproved drugs, 123 biotech drugs, 69 nutraceuticals, 4774 small molecule drugs, and 3116 experimental or unapproved drugs. There is also information related to withdrawn [57] and illicit [188] drugs. Furthermore, it has a higher drug target database for FDA-approved drugs, which includes 1565 non-redundant protein/

Due to its wealth of information, DrugBank has been used for a variety of drug applications, including target prediction [222], *in silico* discovery [223], metabolism prediction [224], docking or screening [225], as well as new uses of old drugs [226].

bial composition and antibiotic resistance in water samples of Puget Sound (Washington State), and have reported that this could serve as a reliable protocol for providing accurate information on bacterial composition and antibiotic resistance in water samples [210]. Leprohon et al. have reviewed all critical information relevant to drug resistance and to resistance mechanism(s) in Leishmania infections generated from NGS analysis [211]. Furthermore, NGS has been successfully used for testing for HIV-1 drug resistance, although such studies are yet to be standardized [212–216]. Likewise, NGS and pyrosequencing have been used to investigate resistance of the *Influenta A* virus to baloxavir [217]. Moreover, NGS has also been used for detection of those *H. pylori* clones that are resistant to levofloxacin [218]. While RNA-seq data have been mined to identify novel fusion genes in gastrointes-

**70**


#### **Table 3.**

*Applications of the DrugBank database.*

Although **Table 3** presents only a few studies employing the DrugBank database, a PubMed search for DrugBank has identified at least 505 published articles, from 2006 until 2020.
