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Role of bioinformatics in drug designing

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Role of bioinformatics in drug designing

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Role of bioinformatics in different steps of drug discovery and drug designing. Various tools and software used in Computer-aided drug designing.

Role of bioinformatics in different steps of drug discovery and drug designing. Various tools and software used in Computer-aided drug designing.

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Role of bioinformatics in drug designing

  1. 1. W Roseybala Devi 19L10921 MSc Bioinformatics, Year-II JSS Academy of Higher Education and Research, Mysore
  2. 2. 1. Understanding Bioinformatics 2. Drug discovery 3. Bioinformatics in Drug design 4. Softwares & Databases used in drug discovery 5. Conclusion 6. References
  3. 3. • The term was first introduced in the 1990s. • Originally, Bioinformatics: the management & analysis of data pertaining to DNA, RNA & protein sequences. • In present, Bioinformatics: creation & advancement of Databases, algorithms, computational and statistical theories to solve formal & practical problems arising from the management and analysis of Biological data. • In the past deacade, devt. in genomics, molecular research technologies & devt in information technologies have combined together to produce a tremendous amount of information related to molecular biology. • Hence, Bioinformatics is the name given to the mathematical and computational approaches used to increase the understanding of biological processes.
  4. 4. Mapping & analyzing DNA & protein sequences Aligning DNA & protein sequences Creating & viewing 3-D models of protein structures
  5. 5. 1. Sequence mapping of biomolecules (DNA, RNA, proteins). 2. Primer designing 3. Prediction of functional gene products. 4. Trace evolutionary trees of genes. 5. Prediction of protein structure. 6. Molecular Modeling of Biomolecules 7. Development of models for the functioning of cells, tissues & organs. 8. Discovery & designing of drugs for medical treatment.
  6. 6. • a substance which has a physiological effect when ingested or otherwise introduced into the body. • all medicines are drugs, whereas not all drugs are medicines. • a medicine imparts a positive medical effect on a patient. • A drug, in contrast to a medicine, can have a positive or negative effect on a patient. • Desirable drug • Bioinformatics facilitate the discovery of such desirable drugs.
  7. 7. • it is the process through which potential new medicines are identified. • In the past, most drugs have been discovered by identifying the active ingredients feom traditional remedies or by serendipitous discoveries. • new approaches helps in understanding how diseases & infections are controlled at the molecular and physiological level and to target specific entities based on this knowledge. • the process of drug discovery involves the identification of candidates, synthesis, characterization, screening and arrays for therapeutic efficacy. • Drug discovery starts with diagnosos of a disease with well characterized symptoms that reduce the quality of life.
  8. 8. • The discovery of new pharmaceutical drugs is one of the preeminent tasks— scientifically, economically, and socially—in biomedical research. • Advances in informatics and computational biology have increased productivity at many stages of the drug discovery pipeline. • Drug discovery has slowed, largely due to the reliance on small molecules as the primary source of novel hypotheses. • Bioinformatics facilitate the discovery of desirable drugs.
  9. 9. Omics Function Databases Genomics Understanding pathogenesis, Identification of disease genes, Discovery of putative drug targets, Patient-centered efficacy and toxicity assessment of drugs/targets. GWAS Catalog GWAS central dbGaP PharmGKB. Transcriptomics Disease mechanisms, Mode of action of compounds, Moving from disease genes to drug targets, Identification/evaluation of drug target candidates, Early prediction of adverse drug target effects. DrugMatrix TG-GATE LINCS 1000 Expression Atlas GEO repository ArrayExpress Proteomics Post-translational process, Protein–protein network interaction, Drug target efficacy and safety evaluation at protein level, Protein toxicology. PRIDE Archive Peptide Atlas ProteomicsDB Human Proteome Map Human Proteome Atlas Metabolomics Novel DTD, Drug target efficacy and safety evaluation at metabolomic level, Metabolic toxicity. Human Metabolome Madison Metabolomics Golm Metabolome Databas MassBank MetaboLights MetabolomeExpress OmicsdataandtheirusesinDrugDiscovery
  10. 10. • Lead optimization aims at enhancing the most promising compounds to improve effectiveness, diminish toxicity, or increase absorption. Drug optimization • A study to test a drug, a procedure, or another medical treatment in animals.The aim of a preclinical study is to collect data in support of the safety of the new treatment. Preclinical trials • A clinical trial is only done when there is good reason to believe that a new test or treatment may improve the care of patients. Clinical trials are research studies that involve people. Clinical trials • Target identification is the process of identifying the direct molecular target.It aimed at finding the efficacy target of a drug/pharmaceutical or other xenobiotic.Target identification • The process involves the application of a range of techniques that aim to demonstrate that drug effects on the target can provide a therapeutic benefit with an acceptable safety window. Target validation • Compound Screening is defined as the identification of compounds that could be promising candidates for drug development, before it advances to the more-costly stages of preclinical and clinical trials. Compound screening
  11. 11. • Bioinformatic analysis accelerate drug target identification and drug candidate screening and refinement,and facilitate characterization of side effects and predict drug resistance. • uses high-throughput molecular data in comparison between patients, animal disease models, cancer cell lines & normal controls. • Key objective: i. to connect disease symptoms to genetic mutation, epigenetic modification & other environmental factors modulation of gene expression. ii. to identify drug targets that can either restore cellular function or eliminate malfunctioning cells. iii. predict or refine drug candidate to achieve the designed therapeutic results and minimize side effects. iv. access the impact on environmental health & the potential of drug resistance.
  12. 12. Role of Bioinformatics in drug discovery Steps in Drug discovery Role of Bioinformatics Target identification bioinformatics plays a key role in the exploitation of genomic, transcriptomic, and proteomic data to gain insights into the molecular mechanisms that underlie disease and to identify potential drug targets. Target validation rational and efficient mining of the information that integrates knowledge about genes and proteins is necessary for linking targets to biological function. Structural information from raw sequence data, helps in identification or design of target- specific ligands. (Gene logic, Immusol, Aptamers} Compound Screening rational index of drug desirability (Idd) in phenotypic screening. virtual high-throughput screening:protein targets are screened against databases of small-molecule compounds to see which molecules bind strongly to the target. ZINC is a good example of a vHTS compound library Drug optimization screening of compound libraries.chemical structure of a confirmed hit is extensively optimized to produce a preclinical drug candidate. (Comprehensive medicinal chemistry, Drug bankPharmaGKB) Pre-clinical and trials Big Data Management (BDM)solve the current data storagevarious clinical Data.management tools and software available in the market are clinical conductor CTMS (by Bio-Optronics), Clindex, Ascend (by Biopharm).
  13. 13. • The drug discovery process ends when one lead compound is found for a drug candidate, and the process of drug development starts. • Drug design is the inventive process of finding new medications based on the knowledge of a biological target.
  14. 14. Bioinformatics and drug designing approaches Approaches Role of Bioinformatics Ligand-based approach 3D quantitative structure activity relationships (3D QSAR) and pharmacophore modeling are the most important and widely used tools in ligand based drug design. They can provide predictive models suitable for lead identification and optimization Target-based approaches • essential genes (well annotated genome). Essential genes are often highly conserved and can be revealed by genomic comparisons between pathogens and their phylogenetic relatives. • to check if such essential genes have homologues in the host. If they do, then inhibiting such essential genes in the pathogen • to minimize the chance of pathogen developing drug resistance. Finding pathogenecity is and bioinformaticians have created database facilitate the identification pathogenicity islands as drug targets. De novo approaches UCSF, DOCK, FLOG, GOLD, LEGEND18, LUDI19, SPROUT20, GRID Structure Based Drug designing Homology modeling. MODELLERSwissModel RAMPCOMPOSER
  15. 15. • A compilation of software, databases & web services dirctly related to drug discovery are found at http://click2drug.org/ maintained by Swiss Institute. click2drug.org
  16. 16. • many software packages are powerful and free and supported by well known institutions. ChEMBL & SwissSidechain Databases UCSF Chimera software tool 3D visualization SwissSimilarity virtual screening SwissBioisostere for ligand design SwissTargetPrediction webserver to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity SwissSideChain Database for studying, modeling or viualizing non-natural amino acids SwissDock for docking drug candidates (small molecules) on proteins
  17. 17.  Novel approaches in Bioinformatics and development of software packages and databases have expanded our views to the biological system, just as the microscopes and telescopes have extended our views of patterns we have never seen before.  Drug discovery, drug development and commercialization are complicated processes. Bioinformatics tools availability have made positive effect on overall process and they can accelerate various steps of drug designing, and reduce the cost and over all time.
  18. 18. 1. Xia X. (2017). Bioinformatics and Drug Discovery. Current topics in medicinal chemistry, 17(15), 1709–1726. https://doi.org/10.2174/1568026617666161116143440 2. Parul Kumar. Bioinformatics: History, Coverage, Components and Applications. BiologyDicsussions. https://www.biologydiscussion.com/biodiversity/bioinformatics/bioinformatics-history-coverage-components-and-applications/11294 3. Romano JD, Tatonetti NP. Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives. Front Genet. 2019;10:368. Published 2019 Apr 30. doi:10.3389/fgene.2019.00368 4. Ségalat, Laurent. (2007). Loss-of-function genetic diseases and the concept of pharmaceutical targets. Orphanet journal of rare diseases. 2. 30. 10.1186/1750-1172-2-30. 5. Paananen J, Fortino V. An omics perspective on drug target discovery platforms [published online ahead of print, 2019 Nov 27]. Brief Bioinform. 2019;bbz122. doi:10.1093/bib/bbz122 6. Gill, S. K., Christopher, A. F., Gupta, V., & Bansal, P. (2016). Emerging role of bioinformatics tools and software in evolution of clinical research. Perspectives in clinical research, 7(3), 115–122. https://doi.org/10.4103/2229-3485.184782 7. Acharya, C., Coop, A., Polli, J. E., & Mackerell, A. D., Jr (2011). Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach. Current computer-aided drug design, 7(1), 10–22. https://doi.org/10.2174/157340911793743547

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