Languages for Systems Biology Luca Cardelli Microsoft Research Cambridge UK http://www.luca.demon.co.uk/BioComputing.htm http://research.microsoft.com/bioinfo Languages for Systems Biology

Structural Architecture Eukaryotic Cell (10~100 trillion in human body) Nuclear membrane Mitochondria Membranes everywhere Golgi Vesicles E.R. Plasma membrane (<10% of all membranes) 2/19/2019

Functional Architecture Regulation Abstract Machines of Molecular Biology Gene Machine Biochemical Networks - The Protein Machine Gene Regulatory Networks - The Gene Machine Transport Networks - The Membrane Machine Nucleotides Makes proteins, where/when/howmuch Holds genome(s), confines regulators Signals conditions and events Directs membrane construction and protein embedding Model Integration Different time and space scales P Q Holds receptors, actuators hosts reactions Protein Machine Machine Membrane Implements fusion, fission Aminoacids Phospholipids Phospholipids Metabolism, Propulsion Signal Processing Molecular Transport Confinement Storage Bulk Transport 2/19/2019

1: The Protein Machine Pretty close to the atoms. On/Off switches cf. BioCalculus [Kitano&Nagasaki], k-calculus [Danos&Laneve] On/Off switches Each protein has a structure of binary switches and binding sites. But not all may be always accessible. Inaccessible Protein Inaccessible Binding Sites Switching of accessible switches. - May cause other switches and binding sites to become (in)accessible. - May be triggered or inhibited by nearby specific proteins in specific states. Binding on accessible sites. May cause other switches and binding sites to become (in)accessible. - May be triggered or inhibited by nearby specific proteins in specific states. 2/19/2019

Molecular Interaction Maps http://www.cds.caltech.edu/~hsauro/index.htm The p53-Mdm2 and DNA Repair Regulatory Network JDesigner Taken from Kurt W. Kohn 2/19/2019

“External Choice” The phage lambda switch 2. The Gene Machine Pretty far from the atoms. cf. Hybrid Petri Nets [Matsuno, Doi, Nagasaki, Miyano] Positive Regulation Negative Regulation Transcription Input Output1 Output2 Input Output Coding region Gene (Stretch of DNA) “External Choice” The phage lambda switch Regulatory region Regulation of a gene (positive and negative) influences transcription. The regulatory region has precise DNA sequences, but not meant for coding proteins: meant for binding regulators. Transcription produces molecules (RNA or, through RNA, proteins) that bind to regulatory region of other genes (or that are end-products). Human (and mammalian) Genome Size 3Gbp (Giga base pairs) 750MB @ 4bp/Byte (CD) Non-repetitive: 1Gbp 250MB In genes: 320Mbp 80MB Coding: 160Mbp 40MB Protein-coding genes: 30,000-40,000 M.Genitalium (smallest true organism) 580,073bp 145KB (eBook) E.Coli (bacteria): 4Mbp 1MB (floppy) Yeast (eukarya): 12Mbp 3MB (MP3 song) Wheat 17Gbp 4.25GB (DVD) 2/19/2019

Gene Regulatory Networks http://strc.herts.ac.uk/bio/maria/NetBuilder/ Taken from Eric H Davidson Or And Gate Amplify Sum DNA Begin coding region NetBuilder 2/19/2019

The Membrane Machine P Q P Q Very far from the atoms. Drip Mate Mito Bud R One case Arbitrary subsystem Mate Mito Zero case Fusion Fission Mito: special cases P Pino Phago R Arbitrary subsystem Zero case One case Exo Endo Q Endo: special cases Fusion Fission 2/19/2019

Membrane Transport Algorithms LDL-Cholesterol Degradation Protein Production and Secretion Viral Replication Taken from MCB p.730 2/19/2019

Equations => Notations => Languages How to model a system Mathematical modeling: Formal (e.g. differential equations). Dynamic (but increasingly difficult to analyze). Non scalable. Non “visual”. => Alterantive notations in biology: Too informal. Too static. Non scalable. Exceeding capabilities of traditional mathematical modeling. => “Programming” languages for biology: Formal, Dynamic Scalable, Analyzable Visual (with some effort). 2/19/2019

Road Ahead Identifying the architecture Modeling the system Physics, Chemistry, Biology, Informatics: Principles of Operation Modeling the system Scalable, compositional, integrated descriptions A common framework (stochastic process calculi) Analyzing the model Exploiting techniques unique to computing Perturbing, predicting, engineering Model Integration “The data are accumulating and the computers are humming, what we are lacking are the words, the grammar and the syntax of a new language…” D. Bray (TIBS 22(9):325-326, 1997) “Although the road ahead is long and winding, it leads to a future where biology and medicine are transformed into precision engineering.” Hiroaki Kitano. 2/19/2019