Applications of bioinformatics in medicine. Bioinformatics has proven quite useful in medicine as the complete sequencing of the human genome has helped to unlock the genetic contribution for many diseases. Its applications include drug discovery, personalized medicine, preventative medicine, and gene therapy.

1. APPLICATION OF
BIOINFORMATIC TOOLS
INFOODBIO-PEPTIDE
RESEARCH
PRESENTED BY
PRATIK GORDE
(PGFET- 2150109)
PRESENTED TO
DR. C. S. RIAR
& M.TECH (FET IIND SEM.)

2. 2
CONTENT
IntroductiontoTopic
ReviewofLiteratures &Casestudy
Resources&Methods
ScopeofBioinformaticsinFoodResearch
Conclusion
References

3. BIOINFORMATICS?
3
BIOINFORMATICS IS THE
APPLICATION OF TOOLS OF
COMPUTATION AND ANALYSIS TO
THE CAPTURE AND
INTERPRETATION OF COMPLEX
BIOLOGICAL DATA

4. HOW
BIOINFORMATICS
WORKS?
4

5. PROBLEMS IN THE FOOD INDUSTRY THAT
CAN BE SOLVED BYUSING BIOINFORMATICS
TOOLS
Food Allergen
Detection
Ensuring
Quality &
Safety
Electronic Database
Was Established
Which Include The
Chemical Properties
of Various
Compounds Related
To Their Taste And
Flavor
Uncover Bioactive
Peptides
Different Food
Proteins And The
Enzymes Which Help
In The Digestion of
Proteins i.e.
Proteolytic Enzymes
Bioinformatics
Optimize the
quantitative
and
compositional
Parameters of
traditional
operations
Metabolic pathway
construction
The advantage in ability of
desirable microbes to
convert substrates to
organic tailor-made
compounds contributes to
the flavor, structure,
texture, stability, and
safety of the food product.
5
Utilized For Allergen
Diagnostic
Development To
Predict Allergy

6. RESEARCH
GAPANALYSIS
1. BIOINFORMATICS
 BIOLOGY
 CHEMISTRY
 COMPUTER SCIENCE
 INFORMATION ENGINEERING
 MATHEMATICS & STATISTICS
GOLDEN MEAN
OF TWO
TECHNOLOGIES
2. FOOD ENGG. &
TECHNOLOGY
 FOOD PROCESS ENGG.
 FOOD CHEMISTRY
 FOOD NUTRITION
 FOOD MICROBIOLOGY
6
NEED TO STUDY OF
BIOINFORMATICS
TOOLS
TOOLS FOR PRIMARY
SEQUENCE ANALYSIS
TOOLS FOR PHYLOGENETIC
SEQUENCE ANALYSIS
TOOLS FOR STRUCTURE
FUNCTION ANALYSIS
OF PROTEINS

7. Review of
Literature’s
The foundations of Food
Bioinformatics were laid in the
2002 with the application of
computational methods to protein
sequence analysis
7
(2002 – 2022)

8. 8
Application of Bioinformatics in
Food
Author & Year Key findings
1. Detection of Allergen
Lin J. Bruni et.al.(2012)
Techniques of bioinformatics have been utilized for allergen diagnostic
development to predict peanut allergy with the help of machine learning
Jenkins J. A. et.al.(2005)
Homology of prevalent bioinformatics with inclusion of structural
bioinformatics are systematically performed to build up the possible
allergenicity and cross reactivity of proteins
FAO/WHO
(2002)
The utility of such methodologies has incited the WHO to incorporate
sequences similarity search as a feature of the rules for evaluating
allergenicity for food that’s genetically modified
2. Ensuring Quality &
Safety
Dong D. Jones et.al.
(2009)
Bioinformatics is playing an important role in ensuring the quality of the
food while maintaining its safety. Working in relation to molecular
evolution bioinformatics played an essential role in the study of the
evolution of receptors for taste
Dotson C. D. et.al.(2008)
studies being conducted primarily focusing on the taste receptors with the
link between the glucose regulation and bitter taste receptors established
Liu M. Nauta A.
(2008)
study of genetic sequence of lactic acid bacteria played an important role
in uncovering the formation of specific flavoring potential helping in
giving flavor to many fermented foodstuffs

9. 9
Application of Bioinformatics
in Food
Author & Year Key findings
3. Uncover Bioactive
Peptides
Dziuba J. Minkiewicz P.
et.al.(2002)
Simultaneous evaluation of different food proteins and the enzymes
which help in the digestion of proteins i.e. proteolytic enzymes
bioinformatics can help in bringing the major change in bioactive peptide
research.
Lacroix I. M. et.al.
(2012)
The protein sequences from UniProtKB, SwissProt and TreMBL database
can be obtained for determining the occurring frequency of bioactive
peptide crypt in primary structures of food proteins.
Chibuike C. Udenigwe
et.al.(2014)
Bioinformatics developed software's are used to generate profiles for
in silico peptides resulted from the stimulation of proteolytic specificities
of various enzymes
4. Microbial informatics
Alkema W, Boekhorst
et.al.(2016)
Sequence-based prediction of microbial functionality with access to
databases that integrate data from genomics, systems biology,
phenotypes and ‘biomarkers’ for functionality in specific taxa will help
in predicting the eff‫ٴ‬ects of microorganisms on food.
Gry J. Black et.al.(2007)
Complete genome-scale metabolic models together with algorithms such
as flux balance analysis allow the in silico simulation of growth of the
organism under the metabolic restrictions provided by the substrate
availability in the medium.
Cont…

10. UNDERSTANDINGBIOINFORMATICS
THROUGH
#CASESTUDY
10
Agricultural Bioinformatics, DOI 10.1007/978-81-322-1880-7_7, Springer India 2014
OF
DETECTION OF ALLERGEN
IN PEANUT (ARA H1)
Venkatesh Kandula et.al.(2014)

11. #Case study
11
Scientific name -Arachis hypogaea
Most Allergenic Protein- Ara H1 (Cupin)
Symptoms Can Include: Skin reactions, Itching
or tingling in or around the Mouth and throat.
DETECTION OF ALLERGEN IN PEANUT (ARA H1)

12. #Case study
12
Allergen Protein family
MW
(kDa) References
Ara h 1 Cupin: 7S vicilin-like globulins 64.0 Burks et.al. (1995)
Ara h 2 Prolamin: 2S albumin, conglutin
17.0 Kleber-Janke et.al. (1999)
Ara h 3 Cupin: legumin-like (11S globin,
glycinin)
59.0 Rabjohn et.al. (1999)
Ara h 4 Cupin: legumin-like (11S globin,
glycinin)
37.0 Kleber-Janke et.al. (1999)
Ara h 5 Profilin 15.0 Kleber-Janke et.al. (1999)
Ara h 6 Prolamin: 2S albumin, conglutin 15.0 Kleber-Janke et.al. (1999)
Ara h7 Prolamin: 2S albumin, conglutin 15.0 Kleber-Janke et.al. (1999)
Ara h 8 Pathogenesis-related protein,PR-10 17.0 Mittag et.al. (2004)
Ara h 9
Prolamin: nonspecificlipid-transfer
protein 9.8 Krause et.al. (2009)
Ara h10 Oleosin 16.0 Pons et.al. (1998, 2002)
Table 2.2 Peanut Allergens

13. #Case study
13
Defatted
Peanut
Protein
Conc.
Amino Acid
Profile
Amino Acid
Sequence
Allergen
Identificati
on
Structure &
Stability
Amino Acid
Profile
Amino Acid
Sequence
RAW PEANUT PROTEIN STANDARDISE &
PURIFIED PEANUT
PROTEIN DATA
MODELING & SIMULATION
FOOD
ENGG.
&
TECH.
BIOINFORMATICS
MAJOR REQUIREMENTS
1. Tool For Sequence Analysis
2. Tools For Structure & Function Analysis
3. Tools For Modeling & Simulation

14. #Case study
14
Allergen Protein family
MW
(kDa)
Length of the Protein
sequence (amino acids)
Full-length FASTA alignment in
three databases (% sequence
identity)
Ara h 1 Cupin: 7S vicilin-like
globulins
64.0 228 86.207 %
Ara h 2 Prolamin: 2S albumin,
conglutin
17.0
210 89.306 %
Ara h 3
Cupin: legumin-like
(11S globin, glycinin)
59.0 140 91.567 %
Ara h 4
Cupin: legumin-like
(11S globin, glycinin)
37.0 150 88.567 %
Table 2.3 Results of Major allergens’ study
Venkatesh Kandula et.al.(2014)

15. BIOINFORMATIC
TOOLS
15

16. BIOINFORMATIC
TOOLS
There are numerous Tools &
Databases which are beneficial to
Complete Research in the areas of
life sciences. These tools and
databases are the Backbones of
Emerging Genetic And Proteomic
Research. Based on analysis of a
particular area in life science.
1. Tools For Primary
Sequence Analysis
2. Tools for phylogenetic
sequence analysis
3. Tools for structure &
function analysis of
proteins
4. Genomic
Databases
16

17. 17
Table 3.1 Tools used in Bioinformatics for Sequence Analysis
Classification of
tools
Tool’s Description Reference
1. Tools for primary
sequence analysis
HMMER
Using this tool homologousprotein sequences can
be searched from the databases.
R. D. Finn et.al.(2011)
ClustalOmega
Multiple sequence alignment may be
performed using thisprogram.
F. Sievers et.al.(2011)
2. Tools for phylogenetic
sequence analysis
JStree
An open- source library forediting phylogenetic
tress.
A. Boc et.al (2012)
Jalview
An alignment editor whichis based on refining the
alignment.
A.M. Waterhouse
et.al.(2009)
3. Tools for structure-
function analysis of
proteins
CATH
A semi-automatic tool for the categorized
organizationof proteins.
I. Sillitoe et.al.(2013)
RaptorX
Prediction of protein structure based on either a
single or multi-templatethreading.
M. Källberg et.al.(2012)
SMART
A Simple Modular Architecture Retrieval Tool,
describes multiple information about protein- query.
T. Doerks et.al.(2009)

18. 18
Table 3.2 Tools used in Bioinformatics for Protein Database
Databases Description Reference
GenBank
Member of International Nucleotide SequenceDatabase (INSD) and is a
nucleotide sequence resource.
D.A. Benson et.al.(2012)
Rfam Collection of RNA families, represented by multiple sequence alignments. S. W. Burge et.al.(2013)
European
Nucleotide
Archive
Captures and presents related to experimental workflows that are based
around nucleotidesequencing.
R. Elanchezhian
et.al.(2017)
Prosite
Provides information on protein families, conserved domains and active sites of
theproteins.
C.J. Sigrist et.al.(2013)
Pfam Collection of protein families. R. D. Finn et.al. (2014)
Ensembl Contains annotated genomes of eukaryotes. P. Flicek et.al. (2013)
Medherb Database for medicinally important herbs. M.I. Rajoka et.al. (2014)

19. 19
Tools For Modeling & Simulation
Software Year of publishing Organization
AutoDock Vina 2010 The Scripps Research Institute
AADS 2011 IIT-Delhi
EADock 2007 Swiss Institute of Bioinformatics
ParDOCK 2007 IIT-Delhi
Peanut allergen
Ara h1
Protein data
bank

20. SCOPEOF
BIOINFORMATICS
INFOODINDUSTRY
20
BIOINFORMATICS
Food
Quality &
Safety
Food
Processing
Optimization
Microbial
Study in
Fermentation
GMO Food
Improvement
Detection
of Bioactive
Peptides
Crop mgmt.
&
improvement
Waste
management

21. Refine the food
production
Detection of
Severe Food
Allergens
Food taste &
Flavour
Metabolite
production and
biomass
2
1
Reconstruction of
Metabolic Pathways
SCOPEOF BIOINFORMATICS
INFOODINDUSTRY

22. FUTUREOFBIOINFORMATICSINFOODINDUSTRY
Computer Science
Advance Biology &
Chemistry
54%
20%
14%
12%
Physics, Mathematics &
statistics
Food Science & Technology
22
2030
Alkema W. et.al. (2016)

23. 23
Summary

24. 24
The latest technological advances in proteomics and metabolomics
combined with suitable software and tools provide the opportunity
to explore and decipher the composition of food, their micro
constituents, nutritive value, chemistry, and biology of food.
Efficiently handle huge amounts of data that are generated from
various projects, making bioinformatics an important area in the food
industry.
Bioinformatics influence on nutrition and food science will generate a
unified area of research where both nutritional benefit and
traditional food values become parts of an extended life science
driving towards enhanced quality of life.
CONCLUSION

25. REFERENCES
25
• Udenigwe CC (2014) Bioinformatics approaches prospects and challenges of food
bioactive peptide research. Trends Food Sci Technology 36: 137-143.
• Can T (2014) Introduction to bioinformatics. Methods Mol Biology 1107: 51-71.
• Ugawa S, Minami Y, Guo W, Saishin Y, Takatsuji K, et al. (1998) Receptor that leaves a sour
taste in the mouth. Nature 395: 555-556.
• Chandrashekar J, Mueller KL, Hoon MA, Adler E, Feng L, et al. (2000) T2Rs function as
bitter taste receptors. Cell 100: 703-711.
• Matsunami H, Montmayeur JP, Buck LB (2000) A family of candidate taste receptors in
human and mouse. Nature 404: 601-604.
• Max M, Shanker YG, Huang L, Rong M, Liu Z, et al. (2001) Tas1r3, encoding a new
candidate taste receptor, is a

26. REFERENCES
26
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Cont….

27. 27
ANY QUESTIONS?

28. 28
Thank you…