**6. Conclusion**

*Drug Repurposing - Hypothesis, Molecular Aspects and Therapeutic Applications*

learning method and semi-supervised learning method [32].

In this method the interaction in between drug and its target is determined. To accomplish this, we may fix the drugs on certain bead and allowing reaction of washing cell lysate extracts with drugs [44]. It is also possible to carry out highthroughput screening based direct-binding assays to test drugs against certain kinases [45]. Cell based screening examine the evidence of autophagy, apoptosis or inhibition of proliferation in proper cell culture environment of different cancer cells [46–48]. Also, genetic expression study of drugs based on cell line can help in

Physical collection of approved drugs to carry out experimental repositioning screens is challenging task. Smaller digital libraries containing information of approved drugs or drugs with expired patents are available to serve drug repurposing like Enzi Life Sciences, Prestwick, Spectrum and many other like National Institute of Health's Chemical Genomics Center (NCGC) [49]. It may happen that drug get failed in clinical trials because of lack of effectiveness (efficacy) but not due to toxicity represent good candidate for drug repositioning. There is some web

**4.2 Biological experimental approaches**

It might be apparent that identifying specific drugs with pleiotropic effects is easy task but the execution is a complex. Following methods work well to repositioning of drug with the help of existing data, reducing the time of investigation, helping to reduce unnecessary animal experiments and regulatory obligations.

Although high through put screening (HTS) and many assay techniques available, it is difficult to predict drug and target interaction and its subsequence consequences [31]. Every drug bind with variety of targets but most of them attach with proteins that present in the form of receptors, ion channels, enzymes, antigen and transcriptional factors [32]. To screen the drugs interaction with every of this target is not possible and also it consumes lots of time and money. Certain computational approaches are available that able to screen thousands of test drug molecule with many targets within short time period. The selection of drug and its possible targets are based on similarities based on structure, its protein binding and typical side effects that drugs produce [33–35]. Many molecular docking software are available that predict binding of drug molecule within active site of the target and able to predict the three-dimensional interaction at atomic level. In this approach it is necessary to discover protein structures of both normal and disease condition to target it in proper way else binding of drug with normal protein structure may lead to side effects. Computational approach needs lots of information that can be derived from various databases and webservers like DrugBank [36], E medstore [37], KEGG: Kyoto Encyclopedia of Genes and Genomes [38], SuperTarget and Manually Annotated Targets and Drugs Online Resource (MATADOR) [39], Potential Drug Target Database (PDTD) [40], ZINC [41], CancerDR [42] and many others. Computational models broadly categorized in to network based model that working based on the principles of multiple target optimal intervention (MTOI) [43], Drug side-effect similarity-based method [35] and machine learning-based model that further categorized into supervised

**4. Methods for drug repurposing**

**4.1 Computational methods**

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drug repurposing.

**5. Drug repurposing database**

The process of drug repurposing or repositioning help the Pharmaceutical companies in terms saving capital expenditure and decrease efforts of scientific community from long drug discovery and development process that pass through much experimental and regulatory task. Drug repositioning works well for those drug molecules for which disease targets are not get altered over a period of time. All the drug repositioning hypothesis will not transferred to successful outcome. It was happened with bevacizumab (Avastin), a kinase inhibitor drug that failed to prove its efficacy during phase- III of clinical trial in gastric cancer therapy although it has good efficacy against colon, rectal, brain, lung and kidney cancer by targeting vascular endothelial growth factor (VEGF) and decreasing the blood supply to the tumor that required for tumor growth and metastasis [51, 52]. Similar thing happened for sunitinib, a kinase inhibitor where it has proven its efficacy in certain cancers while unable to show same in other cancers [53]. It is significant to consider the unique drug indication during repositioning with proper justification for risk and benefits ratio. Any cytotoxic anti-cancer drug may not be an ideal drug for cardiovascular disorder in same dose, as it may kill many normal cells with high proliferation index. But it can be utilized at low doses for drug repurposing with less side effects as in the case of methotrexate at 10–20 mg per week for rheumatoid arthritis due to its anti-inflammatory property. Although, there are many obstacles present on the path of drug repurposing now, but future will bring more advancement in the technologies with the help of combinatorial chemistry, virtual screening, data mining and artificial intelligence that raise the success rates. At the last, we hope that all these scientific advancements translated into clinical setting to improve oncotherapy and reduce the burden of cancer related mortality in the world.
