Advanced BioinformaticsLecture 1: Introduction to system biology

ZHU FENGzhufeng@cqu.edu.cn

http://idrb.cqu.edu.cn/Innovative Drug Research Centre in CQU

创新药物研究与生物信息学实验室

1. An introduction

2. How to survive

3. What will be covered

4. Signaling pathway

5. Concluding remarks

Table of Content

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Lecture: ZHU FENG

Major: Bioinformatics and computer-aided drug design

2006-2013: System biology-based drug discovery

1999-2013: Computational simulation on biological system

Please visit http://idrb.cqu.edu.cn/ to download the teaching material

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Introduction to this module

Credits 32

Schedule 10 lectures (week 4th, 6th to 10th, 3 months)

Methods English-teaching & Project-based (3 projects)

1. Biological pathway simulation

2. Computer-aided anti-cancer drug design

3. Disease-causing mutation on drug target

Whether will you pass the exam?

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It depends!

But tell you the way to survive

One long presentation (40%, team work) The organization; Team-work spirit; Achievement ……

One short presentation (20%, personal) Clearance; The organization ……

One project report (40%, individual effort) My observation (1. actively involved in every course; 2. come to this

module on time; 3. creativity; 4. do not just listen, get familiar with the biological side of the topic; 5.good relationship with me ……)

Your ways of putting what you have done in English

Guaranteed!To learn the most-widely used bioinformatics tools

• Basic understanding of the method in each tool(Normally required in a college module)

• Capable of explaining the algorithm to a layperson(so that you are perceived as an expert!)

• Knowing the application range and limitation of each tool(now the real expert!)

To learn through project, focused on application and problem solving• Study of real and recently-emerged biological problems in system biology: 1.

pathways simulation; 2. drug design; 3. drug target mutation

(give you the experience to work for a life-science lab or a pharmaceutical company).

What will be covered?

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“Open-lab” policy:

• Our lab assignments only uses internet tools and downloadable software (which means that you can do the projects “any-time, any-place”)

• No need to show-up in the lab, as long as you submit lab-report on time.

• Project-report submission system at: http://idrb.cqu.edu.cn/

Textbook:

• As most of the topics are not covered by existing textbooks, you are not required to have a textbook. Recommended reference books: Introduction to Bioinformatics. Arthur M. Lesk. 2002. Oxford University Press; ISBN:

0199251967 Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine

Learning). Pierre Baldi, Soren Brunak. 2001. The MIT Press; ISBN: 026202506X Molecular modelling : principles and applications. Andrew R. Leach. Imprint Harlow,

England Most importantly: literature from PubMed (http://www.ncbi.nlm.nih.gov/pubmed)

Lab and Text Book

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Lecture 1: Introduction to system biology (week 4th) An introduction How to survive What will be covered Signaling pathway Concluding remarks

Lecture 2: Cancer pathways and therapeutics (week 6th) The nature of cancer How cancer arises Pathway involved in cancer Cell cycle clock and cancer Molecular target of cancer

Topics covered

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Lecture 3: Protein-protein interaction (week 7th) Protein-protein interaction Interaction representations Method A: Two-hybrid assay Method B: Affinity purification Spoke and matrix models of PPI

Lecture 4: Short presentation A (week 8th) Opening remarks G1: Student 11; Student 12 G2: Student 21; Student 22 G3: Student 31; Student 32 Concluding remarks

Topics covered

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Lecture 5: Signal transduction and simulation (week 9th) Components in signal transduction Growth factor and receptor RTK signal transduction Constructing a pathway model Signaling oncogene & therapeutics

Lecture 6: Pharmacology and drug development (week 10th) Modern drug development Drug & corresponding target Mechanism of drug binding Mechanism of drug action Adrenoceptor cardiac function

Topics covered

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Lecture 7: Computer-aided lead identification (week 11st) Schematic of DOCKing Pharmacophore-based docking INVDOCK Strategy Ligand-based drug design Classification of drugs by SVM

Lecture 8: Short presentation B (week 12nd) Opening remarks G1: Student 13; Student 14 G2: Student 23; Student 24 G3: Student 33; Student 34 Concluding remarks

Topics covered

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Lecture 9: Drug resistant & cancerous mutation (week 13rd)• Differential drug efficacy• Pharmacogenetics• Pharmacogenetic response• Drug resistance mutation• Prediction of drug resistance

Lecture 10: Examination and presentation (week 14th)• Opening remarks• G1: Biological pathway simulation• G2: Computer-aided drug design• G3: Cancerous mutations on targets• Concluding remarks

Topics covered

Signal

Receptor (sensor)

Transduction Cascade

Targets

Response Altered

Metabolism

MetabolicEnzyme

Gene Regulator Cytoskeletal Protein

Altered Gene Expression

Altered Cell Shape or Motility

Generic signaling pathway

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Integrated circuit of the cell

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EGFR-ERK/MAPK Signaling Pathways

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EGFR MET PDGFR

C.L. Sawyers. Nature. 449(7165):993-996 (2007)

Z. Chen. Journal of Medicinal Chemistry. 54(10):3650-3660 (2011)

Cancer growth

Single target drug

EGFR MET PDGFR

Cancer growth stop

Multi-target drug

Gleevec: “Time magazine” reported as the “magic bullet” for anti-caner, which is a typical multi-target drug for Abl, Kit, Arg, PDGFR

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Signaling

Synergy effect (1+1>2) on system level

Therapeutic effect

Pharmacodynamic combination

Pharmacokinetic combination

Anti-counteractive Complementary Facilitating

Potentiative

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Cisplatin：DNA adduct, DNA

damage, Cancer cell apoptosis

Trastuzumab：Anti-HER2 antibody

Anti-counteractivesynergistic effectDNA repair

Anti-anti-caner

Synergy effect:Pietras et al. Oncogene 1998Le et al. J. Biol. Chem. 2005Lee et al. Cancer Res. 2002

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Complex can enhance the interaction between 5-FU and TSDrug-drug interaction

Complementary

S. Loi. Journal of Clinical Oncology. 31(7):860-867 (2013)

Methotrexate (MTX) – 5-FU CombinationAnticancer

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突厥蔷薇Rosa damascena Anti-HIV active

ingradentKaempferol

AIDS-058145

Synergy EffectFakruddin et al. Clin. Exp. Immunol. (2004)

Human T cell exposed to gp120Up regulate

RANKL

Up regulate HIV Transcription

AIDS-058145Inhibit HIV

protease substrate

KaempferolDirect

inhibit HIV protease

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EGFR pathway net work (cancer related)

ERK’s activation dynamics will directly affect the cell proliferation and

differentiation, and push tumor genesis. Therefore, the understanding of

EGFR-ERK pathway will understand how cancer signaling is proceed and

developed.

Quantitative study not qualitative

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1. Single protein ODE equation concentration (time)

3. Sensitivity analysis, multi-targets synergy effect

2. Soleving the equations together

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EGF binding to EGF receptor

EGF∙EGFR dimerization

Reaction rate producing EGF∙EGFR

Reaction rate consuming EGF∙EGFR

Determine the change in the concentration of EGF∙EGFR over time

Examples

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Parameters

Gene expression level for different disease

Gene expression level for individual

Kinetic data for protein-protein interaction

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Model Validation 1：EGFR L858R/T790M mutation in lung cancer significantly hamper EGFR-Cbl

interaction (Kf), therefore reduce EGFR endocytosis, and lead to the elongation of

EGFR-ERK signal in lung cancer cell.

Kf

Oncogene, 26 (2007), pp. 6968–6978

Is quantitative study reliable?

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Model Validation 2：The initial concentration of EGF in cancer cell line PC12 is 50ng/ml, transient activation of ERK (peaks within 5 min and decays within 30–60 min) Nat. Cell Biol., 7 (2011), pp. 365–373

Biophys. J., 87 (2009), pp. L01–L02Protein phosphatase 2A (PP2A, from 0.005 to 0.01 μM) that differ by 2-folds show little effect on the change of maximal amount of active ERK but substantially affect the duration of ERK activation

Is quantitative study reliable?

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Enjoy more on the next lecture

1. Biological pathway simulation

2. Computer-aided anti-cancer drug design

3. Disease-causing mutation on drug target

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Any questions? Thank you!