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1. BIOINFORMATICS IN DRUG DISCOVERY By KAUSHAL KUMAR SAHU Assistant Professor (Ad Hoc) Department of Biotechnology Govt. Digvijay Autonomous P. G. College Raj-Nandgaon ( C. G. )

2. SYNOPSIS INTRODUCTION A PERFECT THERAPEUTIC DRUG DRUG DISCOVERY- HISTORY MODERN DRUG DISCOVERY BIOINFORATICS IN DRUG DISCOVERY DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY ECONOMICS OF DRUG DISCOVERY CONCLUSION REFERENCES

3. INTRODUCTION A drug can be defined as “a substance intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease…or as a component of a medication ”. Drug discovery is the process of discovering and designing drugs. This process is very important, involving analyzing the causes of the diseases and finding ways to tackle them .   This process is so long and expensive that it might cost millions of dollars and take a dozen years; and the accuracy of identification of targets is not good enough, which in turn delays the process .  

4. Bioinformatics is generally defined as the research, development & application of computational tools and approaches for expanding the use of biological, medical and health data, including those to acquire, store, organize, archive, analyze and visualize such data. It can explore the causes of diseases at the molecular level, explain the phenomena of the diseases from the angle of the gene and make use of computer techniques, and enhance the accuracy of the results so as to reduce the cost and time.

5.   A PERFECT THERAPEUTIC DRUG Drug is defined as all natural and artificially made chemicals that produce desired effects in the living organisms when administered by the most favoured route. What makes a chemical compound acting as pharmaceutically active agent ? • High affinity towards the target • Selectivity with respect to the target • High bioavailability und low toxicity

6. HISTORY The discovery of drugs historically has been serendipitous (Ratti & Trist, 2001). For most of its history, drug discovery has been a product of trial and error. Long before the pharmaceutical industry existed, drugs were discovered by accident and their uses passed down by verbal and written records (Ratti & Trist, 2001). According to Boa (2003), “Throughout history people have found by trial and error which berries, roots and barks could be used for medicinal purposes to alleviate symptoms of illness”. For example, the Willow bark, which contains salicin, was used as a fever reducer .

7. MODERN DRUG DISCOVERY Drug discovery is the process of discovering and designing drugs, which includes target identification, target validation, lead identification, lead optimization and introduction of the new drugs to the public.

8. BIOINFORMATICS IN DRUG DISCOVERY Bioinformatics is a booming subject combining biology with computer science. It can explore the causes of diseases at the molecular level, explain the phenomena of the diseases from the angle of the gene and enhance the accuracy of the results so as to reduce the cost and time . In recent years, we have seen an explosion in the amount of biological information that is available. It appears that the ability to generate vast quantities of data has surpassed the ability to use this data meaningfully. All marketed drugs today target only about 500 gene products. The elucidation of the human genome which has an estimated 30,000 to 40,000 genes, presents immense new opportunities for drug discovery and simultaneously creates a potential bottleneck regarding the choice of targets to support the drug discovery pipeline.

9. DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS The processes of designing a new drug using bioinformatics tools have open a new area of research. In order to design a new drug one need to follow the following path . Identify Target Disease • Study Interesting Compounds • Detect the Molecular Bases for Disease • Refinement of compounds • Quantitative Structure Activity Relationships ( QSAR) • Solubility of Molecule • Drug Testing

10. BIOINFORMATICS IN COPUTER-AIDED DRUG DISCOVERY Homology modeling Most drug targets are proteins, so it is important to know their 3-D structure. Homology modeling relies on the identification of one or more known protein structures. Modeller is a well-known tool in homology modeling, and the Swiss-Model Repository is a database of protein structures created with homology modeling.

11. Interaction networks Docking is a method used to identify the fit between a receptor and a potential ligand. . The goal of protein-ligand docking is to predict the position and orientation of a ligand (a small molecule) when it is bound to a protein receptor or enzyme . The following are the protein-ligand docking software’s: i) Gold (http://www.ccdc.cam.ac.uk/products/life_sciences/gold). ii) AutoDock (http://autodock.scripps.edu/). iii) Dock (http://dock.compbio.ucsf.edu/). iv) ZDock (http://zlab.bu.edu/zdock/). v) Docking server: http://www.dockingserver.com/web.

12. Virtual high-throughput screening (vHTS) Pharmaceutical companies are always searching for new leads to develop into drug compounds. One search method is virtual high-throughput screening (vHTS). In vHTS, protein targets are screened against databases of small-molecule compounds to see which molecules bind strongly to the target.

13. Drug lead optimization When a promising lead candidate has been found in a drug discovery program, the next step is to optimize the structure and properties of the potential drug. This usually involves a series of modifications to the primary structure and secondary structure of the compound. Lead optimization tools such as WABE offer a rational approach to drug design that can reduce the time and expense of searching for related compounds

14. Drug bioavailability and bioactivity Most drug candidates fail in clinical trials after many years of research and millions of dollars have been spent on them. And most fail because of toxicity or problems with metabolism. The key characteristics for drugs are: absorption, distribution, metabolism, excretion, toxicity (ADMET) and efficacy—in other words bioavailability and bioactivity. Although these properties are usually measured in the lab, they can also be predicted in advance with bioinformatics such as C2-ADME, TOPKAT, CLOGP, DrugMatrix, AbSolv, Bioprint, GastroPlus etc.

15. ECONOMICS OF DRUG DISCOVERY

16. CONCLUSION The drug discovery process is a long and expensive one. It starts from target identification, after that, validates the targets and identifies the drug candidates.   Due to the limitation of throughput, accuracy and cost, experimental techniques cannot be applied widely, therefore, in recent times the drug discovery process has shifted to bioinformatic approaches such as homology modeling, protein-ligand interactions, vHTS etc. Bioinformatic approach has been of great importance to develop fast and accurate target identification and prediction method for the discovery and enhance the accuracy of the results so as to reduce the cost and time

17. REFERENCES 1. Bioinformatics and drug discovery- Richard S. Larson 2. Bioinformatics- R.C. Rastogi 3. Modern drug discovery process: An in silico approach V. Srinivasa Rao and K. Srinivas* Department of Computer Science and Engineering, V.R Siddhartha Engineering College, Kanuru, Vijayawada-520 007, India. 4. Bioinformatics- SABU M. THAMPI Assistant Professor Dept. of CSE LBS College of Engineering Kasaragod, Kerala