DOCSLIB.ORG

Information-Theoretic Bounds of Evolutionary Processes Modeled As a Protein Communication System

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Information-Theoretic Bounds of Evolutionary Processes Modeled As a Protein Communication System INFORMATION-THEORETIC BOUNDS OF EVOLUTIONARY PROCESSES MODELED AS A PROTEIN COMMUNICATION SYSTEM Liuling Gong, Nidhal Bouaynaya∗ and Dan Schonfeld University of Illinois at Chicago, Dept. of Electrical and Computer Engineering, ABSTRACT can be investigated in the context of engineering communica- In this paper, we investigate the information theoretic bounds tion codes. In particular, it is legitimate to ask at what rate of the channel of evolution introduced in [1]. The channel of can the genomic information be transmitted. And what is the evolution is modeled as the iteration of protein communica- average distortion between the transmitted message and the tion channels over time, where the transmitted messages are received message at this rate? Shannon’s channel capacity protein sequences and the encoded message is the DNA. We theorem states that, by properly encoding the source, a com- compute the capacity and the rate-distortion functions of the munication system can transmit information at a rate that is protein communication system for the three domains of life: as close to the channel capacity as one desires with an arbi- Achaea, Prokaryotes and Eukaryotes. We analyze the trade- trarily small transmission error. Conversely, it is not possi- off between the transmission rate and the distortion in noisy ble to reliably transmit at a rate greater than the channel ca- protein communication channels. As expected, comparison pacity. The theorem, however, is not constructive and does of the optimal transmission rate with the channel capacity in- not provide any help in designing such codes. In the case dicates that the biological fidelity does not reach the Shan- of biological communication systems, however, evolution has non optimal distortion. However, the relationship between already designed the code for us. The encoded message is the channel capacity and rate distortion achieved for differ- the DNA sequence. Comparison of the genomic transmis- ent biological domains provides tremendous insight into the sion rate with the channel capacity will reveal whether the ge- dynamics of the evolutionary processes. We rely on these re- nomic code is efficient from an information theoretic perspec- sults to provide a model of protein sequence evolution based tive. However, even if the channel capacity is not exceeded, on the two major evolutionary processes: mutations and un- we are assured that biological communication systems do not equal crossover. rely on codes that produce negligible errors since the level of distortion presented must account for evolutionary processes. Index Terms— Biological communication system; Chan- It is, therefore, interesting to ask ourselves whether biologi- nel capacity; Rate-distortion theory. cal communication systems maintain an optimal balance be- tween the transmission rate and the desired distortion level 1. INTRODUCTION needed to support adaptive evolution. Rate-distortion theory analyzes the optimal tradeoff between the transmission rate, The genetic information storage and transmission apparatus R(D), and distortion, D, in noisy communication channels. resembles engineering communication systems in many ways: Given the fidelity, D, present in biological communication The genomic information is digitally encoded in the DNA. systems, comparison of the genomic transmission rate with By decoding genes into proteins, organisms come into be- the optimal rate R(D) can be used to determine whether or ing. The protein communication system, proposed in [1], not the genomic code achieves the optimal rate-distortion cri- [2] and shown in Fig. 1, is a communication model of the teria. Moreover, by equating the optimal rate R(D) with the genetic information storage and transmission apparatus. The channel capacity, C, we can determine whether the biological protein communication system abstracts a cell as a set of pro- fidelity, D, reaches the Shannon optimum distortion. In this teins and models the process of cell division as an informa- paper, we will only compare the channel capacity and rate tion communication system between protein sets. Using this distortion functions of a single source memoryless protein mathematical model of protein communication, the problem communication system, modelling asexual reproduction. The of a species’ evolution will be represented as the iteration of two-source protein communication system, modelling sexual a communication channel over time. reproduction, is more involved mathematically and will not The genome is viewed as the joint source-channel en- be addressed here. coded message of the protein communication system and hence ∗Nidhal Bouaynaya is currently in the Department of Systems Engineer- ing at the University of Arkansas at Little Rock. 1-4244-1198-X/07/$25.00 ©2007 IEEE 1 SSP 2007 Fig. 1. Protein communication system 2. PROTEIN CHANNEL CAPACITY And no information can be obtained at the output after in- finite transmissions. The reason is that, in communications, Assuming a first-order Markov channel, the protein commu- only the initial message is used to convey information and not nication channel is characterized by the probability transition the channel. In bioinformatics, on the other hand, the output matrix, Q = {qi,j }1≤i,j≤20, of the amino acids. In this pa- message captures the information of the channel (i.e. the mu- per, we use two different probability transition matrices: Day- tations) regardless of the initial message. In particular, a par- hoff’s Point Accepted Mutation (PAM) matrices [3], and a ent organism cannot transmit reliably (channel capacity zero) first-order Markov transition probability matrix P [1], [2]. An its genetic information to its offspring of many generations element of a PAM matrix, Mij, gives the probability that the no matter how small the point mutation rate is as long as it aminoacidinrowi will be replaced by the amino acid in col- is not zero. After a long enough time of evolution, the final umn j after a given evolutionary interval which is interpreted distribution of amino acids in offspring only depends on the as the evolutionary distance of PAM matrices. The first-order channel characteristics regardless of the parent organism. It is Markov transition probability matrix P is constructed from also interesting to observe that organisms with lower mutation the genetic code using a point mutation rate α, which rep- rates have higher channel capacity, and therefore their genetic resents the probability of a base interchange of any one nu- information can be reliably transmitted at a higher rate. cleotide and is assumed to be constant over time (see [1] for Having computed the capacity of the protein communica- the computation of P). tion channel, a comparison of the genomic transmission rate The capacity of a channel is the maximum rate at which with the channel capacity will reveal whether the genomic information can be reliably conveyed by the channel. It is code is efficient from an information theoretic perspective. defined as Qjk C I p, Q pjQjk , 3. PROTEIN RATE DISTORTION =maxn ( )=maxn j k log p∈P p∈P k pjQjk (1) The rate distortion function, R(D), is the effective rate at P n {p ∈ Rn p ≥ ∀j p } where = : j 0 ; j j =1 is the which the source produces information subject to the con- set of all probability distributions on the channel input, Q is straint that the receiver can tolerate an average distortion D. I p, Q the probability transition matrix of the channel, and ( ) A distortion matrix with elements ρi,j specifies the distortion is known as the mutual information between the channel in- associated with reproducing the ith source letter by the jth put and output. Evaluation of the channel capacity involves reproducing letter. The rate-distortion function for discrete solution of a convex programming problem. In most cases, memoryless source is defined as analytic solutions cannot be found. Blahut [4] suggested an Q iterative algorithm for computing the channel capacity. jk R(D)= min I(p, Q)= min j k pjQjk log , Figure 2(a) (resp. 2(b)) shows the capacity of the pro- Q∈QD Q∈QD k pjQjk tein communication system as a function of the evolutionary (2) Q {Q ∈ Rn × Rn Q ,Q ≥ distance of PAM matrices (resp. point mutation rate α). As where D = : k jk =1 jk expected, the channel capacity decreases to zero as the evolu- 0,d(Q) ≤ D}, d(Q)= j k pjQjkρjk,andp = {pj} tionary distance or the point mutation rate α increases. This is the probability vector of the channel input. result has different ramifications on bioinformatics than on We define the distortion between a pair of amino acids communication engineering: In engineering, it is interpreted as their distance in the Principal Component Analysis (PCA) as a loss of information after a great number of transmissions. plane obtained from 7 physico-chemical properties (volume, 2 4.5 4 4 3.5 3 3.5 2.5 3 2 1.5 2.5 Channel Capacity Channel Capacity 1 2 0.5 0 1.5 0 200 400 600 800 1000 0 0.02 0.04 0.06 0.08 0.1 0.12 PAM ,k the parameter alfa k (a) (b) Fig. 2. Channel Capacity: (a) Channel capacity v.s. the evolutionary distance of PAM matrices; (b) Channel capacity v.s. the point mutation rate α 3 W R 2 F Y I K 1 L M H V 0 Q E T P −1 C N D Second component −2 A S −3 G −4 −3 −2 −1 0 1 2 3 4 First component Fig. 3. Plot of the amino acids on the first two components of the PCA analysis. The amino acids are labelled by their one-letter standard abbreviations. bulkiness, polarity, PH index, hydrophobicity and surface area). curves of Archaea, Bacteria and Eukaryotes, respectively. At The amino acid data was obtained from [Chapter 2] [5]. The about D ≈ 1.4, the above order switches to result of PCA analysis is shown in Fig 3.
Load more

Recommended publications
  • Lecture 5: Sequence Alignment – Global Alignment
    Sequence Alignment COSC 348: Computing for Bioinformatics • Sequence alignment is a way of arranging two or more sequences of characters to identify regions of similarity – b/c similarities may be a consequence of functional or Lecture 5: evolutionary relationships between these sequences. Sequence Alignment – Global Alignment • Another definition: Procedure for comparing two or more sequences by searching for a series of individual characters that Lubica Benuskova, Ph.D. are in the same order in those sequences – Pair-wise alignment: compare two sequences – Multiple sequence alignment: compare > 2 sequences http://www.cs.otago.ac.nz/cosc348/ 1 2 Similarity versus identity Sequence alignment: example • In the process of evolution, from one generation to the next, and from one species to the next, the amino acid sequences of • Task: align abcdef with somehow similar abdgf an organism's proteins are gradually altered through the action of DNA mutations. For example, the sequence: • Write second sequence below the first one – ALEIRYLRD • could mutate into the sequence: ALEINYLRD abcdef abdgf • in one generation and possibly into AQEINYQRD • Move sequences to give maximum match between them. • over a longer period of evolutionary time. – Note: a hydrophobic amino acid is more likely to stay • Show characters that match using vertical bar. hydrophobic than not, since replacing it with a hydrophilic residue could affect the folding and/or activity of the protein. 3 4 Sequence alignment: example Quantitative global alignments abcdef • We are looking for an alignment, which || – maximizes the number of base-to-base matches; abdgf – if necessary to achieve this goal, inserts gaps in either sequence (a gap means a base-to-nothing match); • In order to maximise the alignment, we insert gap between – the order of bases in each sequence must remain and in lower sequence to allow and to align b d d f preserved and abcdef – gap-to-gap matches are not allowed.
    [Show full text]
  • Novel Bioinformatics Applications for Protein Allergology
    AND ! "#$% &'()* +% + ,-.,-/,0 + 121,..0-10- ! 3 4 33!!3 ,,,1/ !"# $% # $# &'()$ $*+,'-./ $ "Por la ciencia, como por el arte, se va al mismo sitio: a la verdad" Gregorio Marañón Madrid, 19-05-1887 - Madrid, 27-03-1960 List of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I Martínez Barrio, Á., Soeria-Atmadja, D., Nister, A., Gustafsson, M.G., Hammerling, U., Bongcam-Rudloff, E. (2007) EVALLER: a web server for in silico assessment of potential protein allergenicity. Nucleic Acids Research, 35(Web Server issue):W694-700. II Martínez Barrio, Á.∗, Lagercrantz, E.∗, Sperber, G.O., Blomberg, J., Bongcam-Rudloff, E. (2009) Annotation and visualization of endogenous retroviral sequences using the Distributed Annotation System (DAS) and eBioX. BMC Bioinformatics, 10(Suppl 6):S18. III Martínez Barrio, Á., Xu, F., Lagercrantz, E., Bongcam-Rudloff, E. (2009) GeneFinder: In silico positional cloning of trait genes. Manuscript. IV Martínez Barrio, Á., Ekerljung, M., Jern, P., Benachenhou, F., Sperber,
    [Show full text]
  • Testing the Independence Hypothesis of Accepted Mutations for Pairs Of
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Computer Science and Engineering: Theses, Computer Science and Engineering, Department of Dissertations, and Student Research 12-2016 TESTING THE INDEPENDENCE HYPOTHESIS OF ACCEPTED MUTATIONS FOR PAIRS OF ADJACENT AMINO ACIDS IN PROTEIN SEQUENCES Jyotsna Ramanan University of Nebraska-Lincoln, [email protected] Follow this and additional works at: http://digitalcommons.unl.edu/computerscidiss Part of the Bioinformatics Commons, and the Computer Engineering Commons Ramanan, Jyotsna, "TESTING THE INDEPENDENCE HYPOTHESIS OF ACCEPTED MUTATIONS FOR PAIRS OF ADJACENT AMINO ACIDS IN PROTEIN SEQUENCES" (2016). Computer Science and Engineering: Theses, Dissertations, and Student Research. 118. http://digitalcommons.unl.edu/computerscidiss/118 This Article is brought to you for free and open access by the Computer Science and Engineering, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Computer Science and Engineering: Theses, Dissertations, and Student Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. TESTING THE INDEPENDENCE HYPOTHESIS OF ACCEPTED MUTATIONS FOR PAIRS OF ADJACENT AMINO ACIDS IN PROTEIN SEQUENCES by Jyotsna Ramanan A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science Major: Computer Science Under the Supervision of Peter Z. Revesz Lincoln, Nebraska December, 2016 TESTING THE INDEPENDENCE HYPOTHESIS OF ACCEPTED MUTATIONS FOR PAIRS OF ADJACENT AMINO ACIDS IN PROTEIN SEQUENCES Jyotsna Ramanan, MS University of Nebraska, 2016 Adviser: Peter Z. Revesz Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are indepen- dent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too.
    [Show full text]
  • A Thesis Entitled Homology-Based Structural Prediction of the Binding
    A Thesis entitled Homology-based Structural Prediction of the Binding Interface Between the Tick-Borne Encephalitis Virus Restriction Factor TRIM79 and the Flavivirus Non-structural 5 Protein. by Heather Piehl Brown Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Biomedical Science _________________________________________ R. Travis Taylor, PhD, Committee Chair _________________________________________ Xiche Hu, PhD, Committee Member _________________________________________ Robert M. Blumenthal, PhD, Committee Member _________________________________________ Amanda Bryant-Friedrich, PhD, Dean College of Graduate Studies The University of Toledo December 2016 Copyright 2016, Heather Piehl Brown This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author. An Abstract of Homology-based Structural Prediction of the Binding Interface Between the Tick-Borne Encephalitis Virus Restriction Factor TRIM79 and the Flavivirus Non-structural 5 Protein. by Heather P. Brown Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Biomedical Sciences The University of Toledo December 2016 The innate immune system of the host is vital for determining the outcome of virulent virus infections. Successful immune responses depend on detecting the specific virus, through interactions of the proteins or genomic material of the virus and host factors. We previously identified a host antiviral protein of the tripartite motif (TRIM) family, TRIM79, which plays a critical role in the antiviral response to flaviviruses. The Flavivirus genus includes many arboviruses that are significant human pathogens, such as tick-borne encephalitis virus (TBEV) and West Nile virus (WNV).
    [Show full text]
  • Bioinformatics Scoring Matrices
    Bioinformatics Scoring Matrices David Gilbert Bioinformatics Research Centre www.brc.dcs.gla.ac.uk Department of Computing Science, University of Glasgow Scoring Matrices • Learning Objectives – To explain the requirement for a scoring system reflecting possible biological relationships – To describe the development of PAM scoring matrices – To describe the development of BLOSUM scoring matrices (c) David Gilbert 2008 Scoring matrices 2 Scoring Matrices • Database search to identify homologous sequences based on similarity scores • Ignore position of symbols when scoring • Similarity scores are additive over positions on each sequence to enable DP • Scores for each possible pairing, e.g. proteins composed of 20 amino acids, 20 x 20 scoring matrix (c) David Gilbert 2008 Scoring matrices 3 Scoring Matrices • Scoring matrix should reflect – Degree of biological relationship between the amino-acids or nucleotides – The probability that two AA’s occur in homologous positions in sequences that share a common ancestor • Or that one sequence is the ancestor of the other • Scoring schemes based on physico-chemical properties also proposed (c) David Gilbert 2008 Scoring matrices 4 Scoring Matrices • Use of Identity – Unequal AA’s score zero, equal AA’s score 1. Overall score can then be normalised by length of sequences to provide percentage identity • Use of Genetic Code – How many mutations required in NA’s to transform one AA to another • Phe (Codes UUU & UUC) to Asn (AAU, AAC) • Use of AA Classification – Similarity based on properties such
    [Show full text]
  • Oxidising Bacteria (SAOB)
    Computational and Comparative Investigations of Syntrophic Acetate- oxidising Bacteria (SAOB) Genome-guided analysis of metabolic capacities and energy conserving systems Shahid Manzoor Faculty of Veterinary Medicine and Animal Science Department of Animal Breeding and Genetics Uppsala Doctoral Thesis Swedish University of Agricultural Sciences Uppsala 2014 Acta Universitatis agriculturae Sueciae 2014:56 Cover: Bioinformatics helping the constructed biogas reactors to run efficiently. (photo: (Shahid Manzoor) ISSN 1652-6880 ISBN (print version) 978-91-576-8060-0 ISBN (electronic version) 978-91-576-8061-7 © 2014 Shahid Manzoor, Uppsala Print: SLU Service/Repro, Uppsala 2014 Computational and Comparative Investigations of Syntrophic Acetate-oxidising Bacteria (SAOB) – Genome-guided analysis of metabolic capacities and energy conserving systems. Abstract Today’s main energy sources are the fossil fuels petroleum, coal and natural gas, which are depleting rapidly and are major contributors to global warming. Methane is produced during anaerobic biodegradation of wastes and residues and can serve as an alternative energy source with reduced greenhouse gas emissions. In the anaerobic biodegradation process acetate is a major precursor and degradation can occur through two different pathways: aceticlastic methanogenesis and syntrophic acetate oxidation combined with hydrogenotrophic methanogenesis. Bioinformatics is critical for modern biological research, because different bioinformatics approaches, such as genome sequencing, de novo assembly
    [Show full text]
  • Lecture 10: Local Alignment and Substitution Matrices 10.1
    CPS260/BGT204.1 Algorithms in Computational Biology September 30, 2003 Lecture 10: Local Alignment and Substitution Matrices Lecturer: Pankaj K. Agarwal Scribe: Madhuwanti Vaidya So far we have seen global alignment, where entire sequences are matched. There are two other variations of global alignment. 10.1 Semiglobal alignment In semiglobal alignment we do not pay penalty for end gaps. These are gaps that appear before the first letter of the sequence or after the last letter of the sequence. They are also called leading and trailing gaps, respectively. If one of the sequences is significantly shorter than the other, then semiglobal alignment is preferrable. Example Consider two sequences - C A G C A C T T G G A T T C T C G G and C A G C G T G G. They can be aligned in many ways: C A G C A − C T T G G A T T C T C G G C A G C A C T T G G A T T C T C G G − − − C A G C G T G G − − − − − − − C A G C − − − − − G − T − − − − G G Alignment 1 Alignment 2 Figure 10.1: Semi-global alignment We want to choose the Alignment1 over Alignment2 as Alignment2 fragments the second sequence, which is not what we are looking for. Giving Alignment1 a better score as compared to Alignment2 is done by not paying a penalty for the trailing and leading gaps. ¢¡¤£¦¥¨§ © ©¥ ¡£§© © Trailing Gaps Suppose we have two sequences , and and is the shorter ¥§©¥ © ©¥"! of the 2 sequences.
    [Show full text]
  • 2-PAM Matrices
    3/28/20 Bioinformatics II: PAM matrices Dr Manaf A Guma University of Anbar- college of applied science-Heet. Department of chemistry 1 Before we start, what is the difference between point mutation and frameshift mutation? • Point mutation is an alteration of a single nucleotide in a gene whereas frameshift mutation involves one or more nucleotide changes of a particular gene. • Point mutations are mainly nucleotide substitutions, which lead to silent, missense or nonsense mutations. Frameshift mutations occur by insertion or deletion of nucleotides. 2 1 3/28/20 Define? • Nonsense Mutations: the alteration of a nucleotide in a particular codon may introduce a stop codon to the gene. This stops the translation of the protein at halfway of the complete protein. • Silent mutations, a single base pair has changed in a particular codon, the same amino acid is coded by the altered codon as well. • Missense mutations, once the alteration occurs in a particular codon by a nucleotide substitution, the codon is altered in such a way to code a different amino acid. 3 Point accepted mutation 4 2 3/28/20 PAM matrices: Background and concepts • How the PAM work? 1. Only mutations are allowed. 2. Sites evolve independently. 3. Evolution at each site occurs according to a Markov equation. • It follows Markov process.? How? 5 5 What is Markov concept? • Markov process: • (The substitution is independent from their past history!). • Meaning: • Next mutation depends only on current state and is independent of previous mutations. • It is derived from global alignment. do you remember? 6 3 3/28/20 What are PAM matrices ? • Point accepted mutation matrix known as a PAM.
    [Show full text]
  • Pairwise Alignment
    Chap. 2 Pairwise alignment • The most basic sequence analysis question: if two sequences are related? • Key Issues: 1. What alignment should be considered? 2. What score system to rank alignments? 3. What algorithm to find optimal (or good) scoring alignments? 4. What statistical method to evaluate the significance? 2.1 Introduction 1 Introduction 2 2.1 Introduction 3 The scoring model • Evolutionary force that can shape molecular (protein, DNA) sequences: mutation (substitution, insertion/deletion or indel), selection (positive, negative, neutral). • If total log-likelihood score (measuring relatedness) of an alignment is a sum of terms for each aligned pair of residues (plus terms for each gap), intuitively, we expect identities and conservative substitutions to be more likely in real alignments than we expect by chance (positive score); and vice versa. 2.2 The Scoring model 4 Substitution matrices (for un-gapped global alignment) • For unrelated or random model R, odds ratio of “match model” M and unrelated or random model R, : p ∏ xi yi p(x, y | M ) px y = i = ∏ i i p(x, y | R) q q q q ∏ xi ∏ y j i xi yi i j • For log-odds ratio score S(x, y) = ∑ s(xi , yi ) i pab where s(a,b) = log qaqb 2.2 The scoring model 5 Chemical Properties of Amino Acids Match +3 and mismatch = -1 may be good enough for DNA, but not for proteins: e.g. leucine is much more likely to be replaced by an isoleucine than by a glutamate. Introduction 6 Introduction Taylor W.R. (1986) Bioinformatics7 Introduction 8 Gap penalties • Linear penalty score for a gap of length g γ (g) = −gd • Or affine score γ (g) = −d − (g −1)e where d is the gap-open penalty and e is the gap extension penalty.
    [Show full text]
  • PHAT: a Transmembrane-Specific Substitution Matrix
    Vol. 16 no. 9 2000 BIOINFORMATICS Pages 760–766 PHAT: a transmembrane-specific substitution matrix Pauline C. Ng 1, Jorja G. Henikoff 2 and Steven Henikoff 2,∗ 1Department of Bioengineering, University of Washington, Seattle, WA 98195, USA and 2Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, Seattle, WA 98109-1024, USA Received on February 23, 2000; revised on April 14, 2000; accepted on April 18, 2000 −1 Abstract sij = λ ln(qij/(pi p j )) where λ is a scaling factor, qij’s Motivation: Database searching algorithms for proteins are target or observed frequencies of amino acid pairs use scoring matrices based on average protein properties, taken from alignments and pi ’s are the background fre- and thus are dominated by globular proteins. However, quencies (Altschul, 1991). The widespread use of database since transmembrane regions of a protein are in a searching and other protein alignment tools in modern distinctly different environment than globular proteins, biology underscores the importance of using substitution one would expect generalized substitution matrices to be matrices that most accurately resemble biological reality. inappropriate for transmembrane regions. The point accepted mutation (PAM) and blocks sub- Results: We present the PHAT (predicted hydrophobic stitution matrices (BLOSUM) are the two most popular and transmembrane) matrix, which significantly outper- matrix series (Dayhoff, 1978; Henikoff and Henikoff, forms generalized matrices and a previously published 1992). The PAM matrix is computed by counting muta- transmembrane matrix in searches with transmembrane tions between closely related sequences and an inferred queries. We conclude that a better matrix can be con- common ancestral sequence to obtain PAM 1 target structed by using background frequencies characteristic frequencies.
    [Show full text]
  • Substitution Matrices E S V U
    C E N Introduction to bioinformatics T R E 2007 F B O I R O I I N N Lecture 8 T F E O G R R M A A T T I I V C Substitution Matrices E S V U C E N T R E F O R I N T E G R A T I V E B I O I N F O R M A T I C S V U [1] Substitution matrices – Sequence analysis 2006 Sequence Analysis Finding relationships between genes and gene products of different species, including those at large evolutionary distances C E N T R E F O R I N T E G R A T I V E B I O I N F O R M A T I C S V U [2] Substitution matrices – Sequence analysis 2006 Archaea Domain Archaea is mostly composed of cells that live in extreme environments. While they are able to live elsewhere, they are usually not found there because outside of extreme environments they are competitively excluded by other organisms. Species of the domain Archaea are •not inhibited by antibiotics, •lack peptidoglycan in their cell wall (unlike bacteria, which have this sugar/polypeptide compound), •and can have branched carbon chains in their membrane lipids of the phospholipid bilayer. C E N T R E F O R I N T E G R A T I V E B I O I N F O R M A T I C S V U [3] Substitution matrices – Sequence analysis 2006 Archaea (Cnt.) • It is believed that Archaea are very similar to prokaryotes (e.g.
    [Show full text]
  • Mutational Effects on Protein Structure and Function
    Thesis: 2009-10-7 14:17 — i(1) Link¨oping studies in science and technology Dissertation No. 1271 Mutational effects on protein structure and function Jonas Carlsson Department of Physics, Chemistry and Biology Link¨oping university SE-581 83 Link¨oping, Sweden Link¨oping 2009 Thesis: 2009-10-7 14:17 — ii(2) The cover picture shows the model structure of steroid 21-hydroxylase with bound heme co-factor in red and bound steroid ligand progesterone in green. Mutations with varying clinical disease phenotype, found in human patients, are indicated in the structure with the following color coding: red corresponds to SW, blue to SV and yellow to NC. During the course of the research underlying this thesis, Jonas Carlsson was enrolled in Forum Scientium, a multidisciplinary doctoral programme at Link¨oping University, Sweden. Copyright c Jonas Carlsson 2009, unless otherwise noted. All rights reserved. Mutational effects on protein structure and function ISBN 978-91-7393-539-5 ISSN 0345-7524 Printed by LiU-Tryck, Link¨oping, Sweden 2009 Thesis: 2009-10-7 14:17 — iii(3) Abstract In this thesis several important proteins are investigated from a structural per- spective. Some of the proteins are disease related while other have important but not completely characterised functions. The techniques used are general as demonstrated by applications on metabolic proteins (CYP21, CYP11B1, IAPP, ADH3), regulatory proteins (p53, GDNF) and a transporter protein (ANTR1). When the protein CYP21 (steroid 21-hydroxylase) is deficient it causes CAH (congenital adrenal hyperplasia). For this protein, there are about 60 known mu- tations with characterised clinical phenotypes.
    [Show full text]