**4.2 Phenotype-based HTS-aided repurposing**

There are various unexplored targets and pathways within the complexity of the microbial intracellular mechanisms along with the identified targets. The drugs for repurposing may be screened for known off-target, on-target, and unknown targets using HTS (**Figure 3**). Mechanism-based biochemical assays may be carried out for known off-target and on-target screening of drugs employing specific proteins such as enzymes in the assay. However, the unknown off-target screening can be carried out through phenotype cell-based HTS assays, so that the multiple targets can be screened to conclude the efficacy of repurposed drug related to its pharmacodynamic status, heterogeneity, biomarker readout, membrane permeability, and cytotoxicity. Further, the phenotype-based assays may be carried out using two-dimension (2D) and three-dimension (3D) approaches. The 2D approach is a traditional cellbased HTS that is carried out on cultured cells propagated in 2D on plastic surfaces

optimized for cell culture. Anti-infective screening for drug repurposing traditionally utilizes a 2D cell-based HTS approach. However, this approach is not suitable for accessing the drug resistance status in antimicrobials. Thus, for drug repurposing or discovery, bioengineered 3D cell culture technology that closely resembles the in vivo cell environment is now being pursued [15].

#### **4.3 'Omics-based drug repurposing**

Omics technology comprises various approaches such as genomics, transcriptomic, proteomics, and metabolomics. The genomics and transcriptomic approaches analyze the gene pattern and mRNA sequence of a pathogen before and after exposure to a drug under consideration for repurposing. The study of the gene expression at the transcription level helps researchers to predict possible metabolic pathways of microorganisms, genomic mutation leading to drug resistance, and potential targets. Further, large-scale microbial gene expression studies may be carried out using advanced microchip technology. The proteomic approach evaluates the overall protein expression profile of the entire organism pre- and post-exposure to an antimicrobial agent under various environmental conditions. It helps identify drugs that may be repurposed for plausible new targets with the least chances of resistance and novel mechanism of action. In contrast, metabolomics involves the analyses of metabolites, and biological/molecular substrates present in a pathogen at a particular time interval. Further, exometabolomics, also known as "metabolic footprint" measures charged or polar molecules being consumed or released by an organism as a secondary metabolite. Sound knowledge of metabolomics can predict the alternative mechanism or pathway during drug resistance, and synergy in combination therapy. Hence, 'omics technologies have transformed the anti-infective drug discovery by generating an unparallel amount of data on potential antimicrobial targets and their resistance from the array of biological libraries. The unique signature (characteristics) of a disease and its co-relationship with a drug can be derivatized using 'omics technologies and drug databases, respectively, such as CARD (Comprehensive Antibiotic Research Database), ARDB (Antibiotic Resistance Genes Database), and NDARO (National Database of Antibiotic-Resistant Organisms) [16].

#### **4.4 Drug-disease biological pathway analysis**

Traditionally, computer-aided approaches were mainly aimed toward target and drug molecules involving structure-based drug design. However, it has also been employed toward the assessment of biological pathways, and mechanisms of drugs through network systems to formulate the correlation between drugs and disease pathways for possible drug repositioning. The scientific data over the drug-disease pathways network may be designed using various databases such as NCBI, MMDB, GEO, and PubChem. Using this approach, Yang et al. generated three networkbased systems between cardiovascular diseases, diabetes mellitus, and neoplasms to establish the drug-disease biological pathway correlation and to predict possible drugs for repositioning. Similarly, Pan et al. studied 16 FDA-approved drugs for possible drug repurposing by using a drug-disease pathway-based approach. Their approach involved the analysis of the drug, protein, and corresponding gene target with affected gene expression level after drug treatment [17, 18].

#### **4.5 Poly-pharmacology-based drug repurposing**

The "single drug, single target" approach is an oversimplified disease mechanism which is in fact, a complex sub-network of the underlying distorted *Trends in Molecular Aspects and Therapeutic Applications of Drug Repurposing for Infectious… DOI: http://dx.doi.org/10.5772/intechopen.100858*

physiological pathway within the interactome. In contrast, network pharmacology considers disease a casual mechanism within the "diseasome cluster" and treats by identifying the synergistic co-targets leading to reduced dose and side effects of the drug. Similarly, "polypharmacology" is the concept of designing or utilizing pharmaceutical agents that can synergistically act on multiple targets or disease pathways. Thus, the drugs which are poly targeting allow a broader impact not only in the early stages of drug discovery but in drug repositioning as well. Various polypharmacology- and network pharmacology-based databases have been published which are employed to develop polypharmacology-based drug repurposing predictions. Polypharmacology apart from the concept also incorporates the use of computational fingerprinting such as structure-based polypharmacology and ligand-based polypharmacology similar to SBDD and LBDD [19, 20].

#### **4.6 Serendipity**

"Serendipity," a term used by medical writers for almost 50 years, was originally coined in 1754 by Horace Walpole in an allusion to an ancient oriental legend of the "Three Princes of Serendip." Today serendipity means, "discoveries not purposely searched for" [21]. However, this term has become one of the methods for discoveries. A thorough survey (via social media platforms) based on medical questions and answers can form a database for the serendipity approach in drug repurposing. This approach can be best understood by various examples where patients taking medication "A" for a specific ailment but suffering from comorbidities have claimed to have found relief from the comorbid disease as well. For example, a patient taking hydrochlorothiazide prescribed for hypertension found relief in kidney stones. However, there is a logical scientific connection between the two conditions. Hydrochlorothiazide is an antihypertensive drug that functions through its diuretic properties (increased urine production and flow) leading to either dissolution or removal of small kidney stones. Similarly, a second example is of a 41-year-old woman with depression and psoriasis and was under treatment for depression with sertraline. She noticed that with sertraline her psoriatic lesions started disappearing. However, scientifically these two conditions are also correlated as psoriasis being an autoimmune disorder having a direct impact on psychosocial factors leading to depression and periodical inflammatory lesions. The main limitations of this method can be questioned in terms of its credibility as these databases are just an output of a questionnaire where other factors such as lifestyle change and environmental factors too might have played an important role. However, the conclusions may be evaluated using drug-disease pathway analysis and other drug repurposing strategies [22].

### **5. Challenges in drug repurposing**

Traditional drug discovery is a time-consuming (10–17 years) process that bears failure risk and huge investment. In this regard, drug repurposing strategy has a lower rate of failure and is found to be safe in early preclinical and clinical trials, thus reducing the cost and time spent during formulation development, safety, and efficacy studies. However, the major challenges in drug repurposing could be (i) untoward side effects due to higher dose of the nonantibiotic drug repurposed for infectious diseases to show the required therapeutic effect and (ii) variation in the pharmacokinetic profile of the drug after off-target repurposing.
