Adriana Maggi DOCENTE DI BIOTECNOLOGIE FARMACOLOGICHE CORSO DI LAUREA SPECIALISTICA IN BIOTECNOLOGIE DEL FARMACO AA 201

1. Adriana Maggi DOCENTE DI BIOTECNOLOGIE FARMACOLOGICHE CORSO DI LAUREA SPECIALISTICA IN BIOTECNOLOGIE DEL FARMACO AA 2011/2012 Lezione 5 Bioinformatica nel processo di drug discovery

2. Bioinformatics in the drug discovery process Alessandro Villa Center of Excellence on Neurodegenerative DiseasesDepartment of Pharmacological SciencesUniversity of Milan

3. Bioinformatics Bioinformatics is about finding and interpreting biological data using informatic tools, with the goal of enabling and accelerating biological research

4. Bioinformatics spans a wide range of activities - Data capture - Automatedrecordingofexperimentalresults - Data storage - Visualizationofraw data and analyticalresults - Access to data using a multitudeofdatabases and querytools

5. Workflow Experimental Design Sample collection and analysis Human based Data collection, filtering, and input Computer aided Data analysis Output results

6. Critical analysis of the results Definitely human based

7. Bioinformatics is web-centric Most academic groups and many companies make computing tools and data available on the web Most of them are free based on the contribution of worldwide researchers

8. Focus on Bioinformatics strategies for disease gene identification

9. Traditional Methods of Drug Discovery natural (plant-derived) treatment for illness ↓ isolation of active compound (small, organic)

10. synthesis of compound ↓ manipulation of structure to get better drug (greater efficacy, fewer side effects)

11. Modern Methods of Drug Discovery • What’s different? • Drug discovery process begins • with a disease (rather than a treatment) • Use disease model to pinpoint relevant genetic/biological components (i.e. possible drug targets)

12. Defining genetic disease Genetic disorders are caused by abnormalities in the genetic material Abnormalities can range from a small mutation in a single gene to the addition or subtraction of an entire chromosome or set of chromosomes. In general, four types of genetic disorders can be distinguished

13. Monogenetic Monogenetic (also called Mendelian or single gene) disorders are caused by a mutation in one particular pair of gene. A mutated gene can result in a mutated protein, which can no longer carry out its normal function. Over 10,000 human diseases are known to be caused by defects in single genes, affecting about 1% of the population as a whole. Monogenetic disorders often have simple and predictable inheritance patterns.

14. Monogenetic disorders Thalassaemia Sickle cell anemia Haemophilia Cystic Fibrosis Tay sachs disease Fragile X syndrome Huntington's disease

15. Polygenic Polygenic disorders are due to mutations in multiple genes in combination with external factors, such as lifestyle and environment Heritability presents the contritution of genetic factors in the formation of multiple gene diseases. Higher heritability is generally interpreted as a larger contribution of genes. Examples of polygenic diseases include coronary heart disease, diabetes, hypertension, and peptic ulcers. At present, there are still many difficulties in prenatal diagnosis for multiple-gene diseases, however, as technology develops, prenatal diagnosis for common multiple-gene diseases will be available in the near future.

16. Polygenic disorders Type 1 diabetes Multiple sclerosis Autism Asthma Celiac disease

17. Chromosomal Abnormalities in the chromosomal number or structure, e.g. (partial) deletion, extra copies, breakage, and (partial) rearrangements, can result in disease.

18. Chromosomal Down syndrome Klinefelter's syndrome Prader–Willi syndrome Turner syndrome

19. Mitochondrial Mitochondria, like the cell nucleus, contains DNA (mtDNA), which is the biggest difference between mitochondria and other sub-units. mtDNA is only inherited from the mother and exhibits higher mutation rate than that of nuclear DNA as well as low repair capacity. Mitochondrial diseases have threshold effects. That means mitochondrial diseases could occur only if the abnormal mtDNA exceeds the threshold. Although sometimes diseases would not happen in the female carriers, for their underthreshold abnormal mtDNA or certain nuclear effects, mutant mtDNA can also be passed from generation to generation.

20. Mitochondrial disorders Kearns-Sayre syndrome Chronic progressive external ophthalmoplegia Mitochondrial encephalomyopathy with lactic acidosis Leigh syndrome

21. Gene identification/findingofinheriteddisease Every gene has a specific task Identification of disease genes is similar to finding genes responsible for normal functions The mutation may be within a gene/protein or within a regulatory part of the genome that, e.g., affects the amount of protein being produced. The mutation changes the protein, which alters the way the task is usually performed DISEASE

22. Gene identification/findingofinheriteddisease Timeline 1983 – Invention of Polymerase Chain Reaction (PCR) technique by Kary Mullis 1989 – the National Center for Human Genome Research is created 1990 – the Human Genome Project (HGP) starts to map and sequence human DNA 1996 – the DNA sequence of the first eukaryotic genome (S. Cerevisiae) is completed 2002 – the mouse genome sequence is completed 2003 – the human genome sequence is completed Now – the genome sequences are still frequently updated with new and rearranged sequences, and some parts are still missing.

23. Gene identification/findingofinheriteddisease We have a huge amount of genetic data in place. And now? Find a candidate gene!

24. Candidate gene definition A candidate gene is a gene that is suspected to be involved in a genetic disease It is located in a chromosome region suspected of being involved in the expression of a trait such as a disease, whose protein product suggests that it could be the gene in question.

25. Disease genes identification in complex disorders Complex disorders are multifactorial and many such diseases, like heart and vascular disease are quite common. Five steps are applicable to research of a complex disease:

26. I. Establish that the disease is indeed (partially ) caused by genetic factors To prove that the candidate is in fact a gene, demonstration of a genetic mutation is needed. Mutation analysis can be done by direct sequencing. Changes in the splicing process of the gene may be missed when screening protein-coding DNA sequences only, but are detectable at the RNA level using RT-PCR. With RT-PCR and related methods it is possible to evaluate whether the spatio-temporal gene expression pattern is compatible with the phenotype of interest. Final proof may require the examination of the effect of induced mutation in model organisms.

27. Mutation analysis

28. II. Perform segregation analysis on individual pedigree to determine the type of inheritance. Inheritance can vary from Mendelian to polygenic, depending on penetrance and environment. The mode of inheritance determines the linkage analysis methods applicable (next step).

29. Segregation analysis E.g. Genetic Association Interaction Analysis Software (GAIA) http://www.bbu.cf.ac.uk/html/research/biostats.htm

30. III. Perform linkage analysis to map susceptibility loci Genetic linkage analysis is a statistical method that is used to associate functionality of genes to their location on chromosomes.  The main idea is that markers which are found in vicinity on the chromosome have a tendency to stick together when passed on to offsprings.  Thus, if some disease is often passed to offsprings along with specific markers, then it can be concluded that the gene(s) which are responsible for the disease are located close on the chromosome to these markers. Parametric, useful for Mendelian traits; Non parametric, useful for complex diseases.

31. Pedigree Analysis Software E.g. MERLIN http://www.sph.umich.edu/csg/abecasis/Merlin/index.html

32. IV. Fine mapping of the susceptibility gene by population-association studies After using linkage to get an idea where disease genes may be located, use association to try to better locate the gene. Association allows to test candidate genes, or very small genetic regions, to see if they are associated with the phenotype in study. These tests can result in the location of a risk gene. Association studies require the use of DNA from many individuals. However, association studies do not use families. Rather, they look at DNA from affected individuals compared to DNA of controls (non-affected individuals who do not have to be relatives.)

33. V. Elucidation of the DNA sequences/genes Confirm their molecular and biochemical action and involvement. Relatively easy in case of Mendelian disorders, because the disease is due to a single change. In complex disorders the susceptibility is often modelled as a quantitative trait locus (QTL)

34. In silico positional cloning Once the critical region for a genetic disease has been determined by linkage analysis, population-association, etc., the human genome sequence can be used to identify positional candidate disease genes. Genome browsers, biological databases, and other bioinformatics tools all contribute to the gene finding strategy.

35. Bioinformatics approach to disease gene identification The release of genomic sequences, full-lenght cDNA sequences, expressed sequence tags (ESTs), and large-scale expression micro-array data of human and model organisms (e.g. Mus Musculus) offer invaluable resources for studying genetic diseases. This huge amount of data is stored in numerous different databases, thus making the use of high performance computing an essential tool for decoding the information contained in these databases.

36. DNA Data Bank of Japan http://www.ddbj.nig.ac.jp/index-e.html

37. European Molecular Biology Laboratory database http://www.ensembl.org/

38. GenBank http://www.ncbi.nlm.nih.gov/genbank/

39. First Step To search for all genes between two genetic markers on the chromosome under study Essential is a proper description of the location of genes and other annotations like regulatory elements Databases and computational tools have been developed to identify all genes on the human genome sequence. None is perfect and genes may be missed, or false genes may be annotated  manual evaluation is necessary or.. Multiple sequence analyses on different databases should be performed

40. USCS Genome Browser http://genome.ucsc.edu/

41. Second Step Functional cloning and candidate gene selection We identified all the genes between the genetic markers In theory, every gene within the disease critical region can cause the disease. When the critical region is large, or the gene density is high, positional candidates are many. Strategies: • There may be already a suspicion on the biochemical/pathogenic background of the disease • If a genetic disorder affects e.g. the liver, select only genes expressed in liver • For known genes, the knowledge in literature can be used to select the candidate genes • Genes located within the critical disease region that have a functional similarity to genes involved in related diseases are good candidates

42. The Gene Ontology project is a major bioinformatics initiative with the aim of standardizing the representation of gene and gene product attributes across species and databases. The project provides a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data from GO Consortium members, as well as tools to access and process this data.

43. Database for Annotation, Visualization and Integrated Discovery http://david.abcc.ncifcrf.gov/home.jsp Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. (2009) Nat Protoc. 4(1):44 -57.

47. Further, knowledge of model organisms makes comparative candidate selection possible This situation applies when a gene is known, which causes a similar phenotype in other species. Transfer of knowledge by phenotype is strightforward in Mus Musculus, being evolutionarily close to humans

48. This grid, called Oxford grid, shows the relationship between human and mouse chromosomes. Chromosome location of either of the species often predicts the chromosome location in the other species.

49. When none of the known genes has mutations, it is possible to try to find new genes in the critical region. Comparative genome analysis of related species present us with a wealth of opportunities for studying evolution and gene/protein function. Homology-based function-prediction transfers information from known genes/proteins to unknow sequences and remains the primary method to determine the function of a new gene Example of homology-based methods are Basic Local Alignment Search Tool (BLAST) Evolutionary annotation database (EVOLA)

50. BLAST http://blast.ncbi.nlm.nih.gov/