“The scientific discovery appears first as the hypothesis of an analogy ; and science tends to become independent of the hypothesis.”
~ William Kingdon Clifford
As you may know, the number and severity of diseases are rapidly increasing day by day resulting in high morbidity and mortality rates. Most of these diseases do not have a definitively beneficial therapy and are potentially life-threatening.
Drug discovery in simple term means the process of identification of chemical entities that has a potentiality of becoming a therapeutic agent. A desirable drug is that which reduces the symptoms efficaciously without causing serious side effects to the patient and should be affordable as well as profitable for the drug company. It is a complex, time consuming (about 15 years), and high-risk process which demands technological expertise and human resource, and requires a strict following of rules and guidelines for clinical testing and manufacturing of new drugs before it comes to market. No wonder why pharmaceutical companies shell out millions of dollars to introduce a drug on the shelf of the market. Bioinformatics came into play and made a positive impact on the drug designing process, by accelerating the drug target identification, screening, and refinement along with the characterization of side effects and predicting the drug resistance.
STEPS IN DRUG DEVELOPMENT AND ROLE OF BIOINFORMATICS AND SOFTWARE TOOLS
The process of Drug discovery involves three main steps which are- Target identification, Validation, and lead optimization, followed by pre-clinical and intensive clinical trials and subsequent pharmacovigilance for drug safety.
1. Target Identification
Prediction and identification of clinically appropriate molecular targets or biologically active candidates (such as receptors, proteins, enzymes, DNA, or RNA which are prominently involved in a disease process) for drug intervention, and mining and warehousing the correlated data is considered to be one of the major thirsts of bioinformatics approach.
Computational methods for target identification :
- Molecular docking : A technique is used for the prediction of intermolecular complex structures and best orientation of ligand forming complex with overall minimum energy, which can be visualized using various tools such as PyMol, RasMol, etc. We can also predict the affinity between the drug target (biomolecules or receptors) and the potential drug candidate. The technique requires the structure of protein/receptor of interest, which is determined by X-ray crystallography or NMR spectroscopy. A score-based result is generated by a scoring function based on a docking algorithm that identifies which drug candidate fits best to the target site.
- Molecular dynamic simulation : It is a computer simulation method that calculates the behavior of molecular systems with time and gives information about the molecule’s structure and microscopic interaction between them. It is commonly used to determine the docking of ligands, predict the structure of the lipid layer and protein.
- Proteomics : It is a large-scale comprehensive study that involves modification or variation of proteins and their respective interacting partners or networks and subsequently elucidates their cellular processes. Bioinformatics tools help to appropriately store and analyze this large data. The combined approach of bioinformatics and proteomics are used in clinically crucial discoveries and identifications such as candidate biomarkers, bacterial antigens targeted by the immune response, immunohistochemistry markers, etc.
Some software is used in pre-clinical trials for randomization to plan the design study and to remove bias. In clinical trials software like electronic data capture, remote data capture, and electronic case report form (eCRF) is used for data storing purposes, and software such as E-Clinical, Oracle clinical is used for management and statistical analysis of data. The safety of drugs after marketing is monitored using safety software like Oracle Argus or ARISg.
NOTE: Most important drug target databases include – DrugBank, therapeutic target, STITCH, SuperTarget.
Pharmacogenomics Information resources for drug designing and development purposes include- PharmGKB, CYP allele nomenclature, FDA genomic marker table, HapMap project, dbSNP home Page, Pharmacogenomics education program.
2. Target Validation
After a potential drug target is discovered we need to establish a strong association between the putative target and interested disease, a process called target validation which helps to moderate failures in clinical testing and approval phases. Since there is a huge availability of potential targets, bioinformatics tools are developed and used for selecting a short number of genes or the drug targets having the strongest association with the disease.
Databases and computational tools used :
- Gene logic : A leading integrated genomics company that provides a comprehensive genomic reference database and solutions for scientific laboratory-based information management. For example, it generates a shortlist of targets expressed in diseases using its large database of tumor and normal gene expression, which can be a screen for functional target validation. It also provides us the information of differential expression pattern of the target, it’s level of expression in various types of diseases, and expression levels of proteins involved in specific pathways.
- Immusol : This technology allows fast in-vivo target validation for safety and efficiency in various disease models using siRNA vectors that are introduced into cultured tumor cells which results in the expression of RNAi used for the validation process.
- Aptamers : Aptamers are synthetic nucleic acid ligands, which bind the active binding site to which a small molecule of drug binds and inactivates the specific functional epitope on protein, thus mimicking the effect of the drug molecule. Also, it can differentiate various post-translational modifications by inactivating the stable protein.
3. Lead Identification Process
This is a complex process of drug discovery where the chemical structure of the confirmed target is optimized to produce a pre-clinical drug candidate, which is done by modifying the primary and secondary structure of the compound. This step uses recent computational methods and innovation which modifies related compounds to give a lead candidate.
CONCLUDING THOUGHTS
Huge demand for increasing the efficacy and efficiency of drug discovery and development has prompted researchers to explore more innovative and novel ways to produce promising new products along with the aid of bioinformatics and computational tools. Though bioinformatics and pharmacogenomics are still in their initial phase and presently facing some hurdles, they are displaying enough potential to help the drug development process in near future. As of now, we can only anticipate that the future will bring more rapid technological changes for the new level of drug discovery.
Written by : Rifat Aara , 3rd year B.Tech Biotechnology
Crescent Bioinformatics Association 
Well explained. Keep it up Rifat.
LikeLiked by 1 person
Good article
LikeLiked by 1 person
Good work !
LikeLiked by 1 person
Great!!
LikeLiked by 1 person