(NAS Colloquium) Computational Biomolecular Science

116 Pages·1998·3.72 MB·English

by  Proceedings of the National Academy of Sciences

i
COLLOQUIUM ON
COMPUTATIONAL
BIOMOLECULAR SCIENCE
NATIONAL ACADEMY OF SCIENCES
WASHINGTON, D.C.
1998
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NATIONAL ACADEMY OF SCIENCES ii
NATIONAL ACADEMY OF SCIENCES
Colloquium Series
In 1991, the National Academy of Sciences inaugurated a series of scientific colloquia, five or six of which are scheduled each year under
the guidance of the NAS Council’s Committee on Scientific Programs. Each colloquium addresses a scientific topic of broad and topical
interest, cutting across two or more of the traditional disciplines. Typically two days long, colloquia are international in scope and bring
together leading scientists in the field. Papers from colloquia are published in
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COMPLETED NAS COLLOQUIA iii
COMPLETED NAS COLLOQUIA
(1991 TO PRESENT)
Industrial Ecology Self Defense by Plants: Induction and Signaling Pathways
May 20–21, 1991; Washington, D.C. September 15–17, 1994; Irvine, California
Organizer: C.Kumar N.Patel Organizers: André Jagendorf, Clarence Ryan
Proceedings: February 4, 1992 Proceedings: May 9, 1995
Images of Science: Science of Images Earthquake Prediction
January 13–14, 1992; Washington, D.C. February 10–11, 1995; Irvine, California
Organizer: Albert Crewe Organizer: Leon Knopoff
Proceedings: November 3, 1993 Proceedings: April 30, 1996
Physical Cosmology Quasars and Active Galaxies: High Resolution Radio Imaging
March 27–29, 1992; Irvine, California March 24–25, 1995; Irvine, California
Organizer: David Schramm Organizers: Marshall Cohen, Kenneth Kellerman
Proceedings: June 3, 1993 Proceedings: December 5, 1995
Molecular Recognition Vision: From Photon to Perception
September 10–11, 1992; Washington, D.C. May 21–22, 1995; Irvine, California
Organizer: Ronald Breslow Organizers: John Dowling, Lubert Stryer, and Torsten Wiesel
Proceedings: February 16, 1993 Proceedings: January 23, 1996
Human-Machine Communication by Voice Science, Technology, and the Economy
February 8–9, 1993: Irvine, California October 20–22, 1995; Irvine, California
Organizer: Lawrence Rabiner Organizers: James Heckman, Ariel Pakes, and Kenneth
Proceedings: October 24, 1995 Sokoloff
Changing Human Ecology and Behavior: Effects on Proceedings: November 12, 1996
Infectious Diseases Developmental Biology of Transcription Control
September 27–28, 1993; Washington, D.C. October 25–28, 1995; Irvine, California
Organizer: Bernard Roizman Organizers: Roy Britten, Eric Davidson, and Gary Felsenfeld
Proceedings: March 29, 1994 Proceedings: September 3, 1996
The Tempo and Mode of Evolution Carbon Dioxide and Climate Change
January 27–29, 1994; Irvine, California November 13–15, 1995; Irvine, California
Organizers: Francisco Ayala, Walter Fitch Organizer: Charles Keeling
Proceedings: July 19, 1994 Proceedings: August 5, 1997
Chemical Ecology: The Chemistry of Biotic Interaction Memory: Recording Experience in Cells and Circuits
March 25–26, 1994; Washington, D.C. February 17–20, 1996; Irvine, California
Organizers: Thomas Eisner, Jerrold Meinwald Organizer: Patricia Goldman-Rakic
Proceedings: January 3, 1995 Proceedings: November 26, 1996
Physics: The Opening to Complexity
June 25–27, 1994; Irvine, California
Organizer: Philip Anderson
Proceedings: July 18, 1995
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COMPLETED NAS COLLOQUIA iv
COMPLETED NAS COLLOQUIA
Elliptic Curves and Modular Forms
March 15–17, 1996; Washington, D.C.
Organizers: Barry Mazur, Karl Rubin
Proceedings: October 14, 1997
Symmetries Throughout the Sciences
May 10–12, 1996; Irvine, California
Organizer: Ernest Henley
Proceedings: December 15, 1996
Genetic Engineering of Viruses and Viral Vectors
June 9–11, 1996; Irvine, California
Organizers: Peter Palese, Bernard Roizman
Proceedings: October 15, 1996
Genetics and the Origin of Species
January 30-February 1, 1997; Irvine, California
Organizers: Francisco Ayala, Walter Fitch
Proceedings: July 22, 1997
The Age of the Universe: Dark Matter and Structure Formation
March 21–23, 1997; Irvine, California
Organizers: David Schramm, P.J.E.Peebles
Proceedings: January 6, 1998
Neuroimaging and Human Brain Function
May 29–31, 1997; Irvine, California
Organizers: Michael Posner, Marcus Raichle
Proceedings: February 3, 1998
Protecting Our Food Supply: The Value of Plant Genome Initiatives
June 2–4, 1997; Irvine, California
Organizers: Michael Freeling, Ronald Phillips, John Axtell
Proceedings: March 5, 1998
Computational Biomolecular Science
September 11–14, 1997; Irvine, California
Organizers: Peter G.Wolynes, Russell Doolittle, J.A.McCammon
Proceedings: May 26, 1998
A Library Approach to Chemistry
October 19–21, 1997; Irvine, California
Organizer: Peter Schultz, Jonathan Ellman
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PROGRAM v
PROGRAM
Computational Biomolecular Science
Thursday, September 11, 1997
Registration and Welcome Reception
Friday, September 12, 1997
Session I 8:45 AM-12:30 PM Chair, Russell Doolittle
Introduction, Peter Wolynes.
Measuring genome evolution. Peer Bork (EMBL, Heidelberg).
Determining biological function from sequence: Building highly specific sequence
motifs for genome analysis. Douglas Brutlag (Stanford).
Experimental studies of protein folding dynamics. William Eaton (NIH).
Coupling the folding of homologous proteins. Ron Elber (Hebrew University).
Session II 2:00 PM-5:30 PM Chair, Andrew McCammon
Photoactive yellow protein: Prototype for the PAS domains of sensors and clocks.
Elizabeth Getzoff (Scripps Research Institute).
Inhomogeneities in genomic sequence composition. Philip Green (Univ.
Washington).
New refinement methods for NOE-distance based NMR structure. Angela
Gronenborn (NIH).
Estimation of evolutionary distances between DNA sequences. Wen-Hsiung Li
(Univ. Texas, Houston).
Comments by Roy Britten
After-dinner Lecture. From slide rule to super computer. Hans Frauenfelder (Los
Alamos).
Saturday, September 13, 1997
Session III 9:00 AM-12:30 PM Chair, Andrew McCammon
Comparing sequence comparison with structure comparison. Michael Levitt
(Stanford).
Structural classification of proteins and its evolutionary implications. Alexey Murzin
(MRC, Cambridge).
Exploring the protein folding funnel landscape-connection to fast folding
experiments. Jose Onuchic (UCSD).
Bridged bimetallic enzymes: A challenge for computational chemistry. Gregory
Petsko (Brandeis).
Session IV 2:00 PM-5:30 PM Chair, Peter Wolynes
Sequence determinants of protein folding and stability. Robert Sauer (MIT).
The evolution of efficient light harvesting in photosynthesis-one goal, many
solutions. Klaus Schulten (Illinois).
Electrostatic steering and ionic tethering in simulations of protein-ligand
interactions. Rebecca Wade (EMBL, Heidelberg).
Computer simulation of enzymatic reactions and other biological process; finding
out what was optimized by evolution. Arieh Warshel (USC).
After-dinner Lecture. Applications of computers in structural biology. Harold
Scheraga (Cornell).
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LIST OF ATTENDEES vi
LIST OF ATTENDEES
Computational Biomolecular Science
Robert K.Adair, Yale University Zaida Luthey-Schultem, University of Ilinois
Paul A.Bash, Argone National Laboratory Jeffry D.Madura, University of South Alabama
R.L.Bernstein, San Francisco State University J.Andrew McCammon, University of California, San Diego
Paul Beroza, CombiChem Inc. Gregory Mooser, University of Southern California, School of
Peer Bork, European Molecular Biology Laboratory Dentistry
David A.Brant, University of California Victor Munoz, National Institutes of Health
Roy J.Britten, California Institute of Technology Alexey G.Murzin, Centre for Protein Engineering
Thomas C.Bruice, University of California, Santa Barbara Craig Nevill-Manning, Stanford University
Douglas Brutlag, Stanford University Medical School Louis Noodleman, The Scripps Research Institute
Aloke Chatterjee. Lawrence Berkeley National Laboratory Hugh Nymeyer, University of California, San Diego
Jiangang Chen, University of California, Los Angeles Jose N.Onuchic, University of California, San Diego
Margaret S.Cheung, University of California, San Diego Jean-Luc Pellequer, The Scripps Research Institute
Julian D.Cole, Rensselaer Polytechnic Institute Gregory A.Petsko, Brandeis University
Kumari Devulapalle, University of Southern California, School Mike Potter, University of California, San Diego
of Dentistry Vijay S.Reddy, The Scripps Research Institute
Russel F.Doolittle, University of California, San Diego Carolina M.Reyes, University of California, San Francisco
William Eaton, National Institutes of Health Ron Elber, Hebrew Roy Riblet, Medical Biology Institute
University Andrey Rzhetsky, Columbia University
Adrien Elcock, University of California, San Diego Suzanne B.Sandmeyer, University of California, Irvine
Hans Frauenfelder, Los Alamos National Laboratory Robert Sauer, Massachusetts Institute of Technology
Anthony Gamst, University of California, San Diego Harold Scheraga, Cornell University
Robert Gerber, University of California, Irvine Rebecca K.Schmidt, Australian National University
Elizabeth D.Getzoff, Scripps Research Institute Klaus Schulten, University of Illinois
Raveh Gill-More, Compugen Ltd. Soheil Shams, BioDiscovery
Adam Godzik, The Scripps Research Institute Sylvia Spengler, Lawrence Berkeley National Laboratory
Jill E.Gready, Australian National University Tim Springer, Center for Blood Research
Phillip Green, University of Washington T.P.Straatsma, Pacific Northwest National Laboratory
Angela M.Gronenborn, National Institutes of Health Ivan Suthsland, Sun Microsystems Laboratories
William Grundy, University of California. San Diego Mounir Tarek, National Institute of Standards and Technology
Volkhard Helms, University of California San Diego Douglas Tobias, University of California, Irvine
Dennis Kibler, University of California, Irvine Chandra S.Verma, University of York
Robert Konecny, The Scripps Research Institute Rebecca Wade, European Molecular Biology Laboratory
Kristin Korethe, Smith Kline Beecham Frederic Y.M.Wan, University of California, Irvine
Leslie A.Kuhn, Michigan State University Arieh Warshel, University of Southern California
Donald Kyle, Scios Inc. Stephen H.White, University of California, Irvine
Peter W.Langhoff, San Diego Supercomputer Center Peter Wolynes, National Institutes of Health
Michael Levitt, Stanford University, School of Medicine Willy Wriggers, University of Illinois at Urbana-Champaign
Jian Li, The Scripps Research Institute William V.Wright University of North Carolina
Wen-Hsiung Li, University of Texas Thomas Wu, Stanford University
E.N.Lightfoot, University of Wisconsin Qiang Zhenq, Scios Inc.
Jennifer H.Y.Liu, University of California
Hartmut Luecke, University of California, Irvine
Jia Luo, University of California, Santa Barbara
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TABLE OF CONTENTS vii
PROCEEDINGS OF THE NATIONAL
ACADEMY OF SCIENCES OF THE
UNITED STATES OF AMERICA
Table of Contents
Papers from a National Academy of Sciences Colloquium on Computational Biomolecular Science
Computational biomolecular science 5848
Peter G.Wolynes
Measuring genome evolution 5849–5856
Martijn A.Huynen and Peer Bork
SMART, a simple modular architecture research tool: Identification of signaling domains 5857–5864
Jörg Schultz, Frank Milpetz, Peer Bork, and Chris P.Ponting
Highly specific protein sequence motifs for genome analysis 5865–5871
Craig G.Nevill-Manning, Thomas D.Wu, and Douglas L.Brutlag
A statistical mechanical model for β-hairpin kinetics 5872–5879
Victor Munoz, Eric R.Henry, James Hofrichter, and William A.Eaton
Coupling the folding of homologous proteins 5880–5883
Chen Keasar, Dror Tobi, Ron Elber, and Jeff Skolnick
Photoactive yellow protein: A structural prototype for the three-dimensional fold of the PAS 5884–5890
domain superfamily
Jean-Luc Pellequer. Karen A.Wager-Smith, Steve A.Kay, and Elizabeth D.Getzoff
New methods of structure refinement for macromolecular structure determination by NMR 5891–5898
G.Marius Clore and Angela M.Gronenborn
Estimation of evolutionary distances under stationary and nonstationary models of nucleotide 5899–5905
substitution
Xun Gu and Wen-Hsiung Li
Precise sequence complementarity between yeast chromosome ends and two classes of just- 5906–5912
subtelomeric sequences
Roy J.Britten
A unified statistical framework for sequence comparison and structure comparison 5913–5920
Michael Levitt and Mark Gerstein
Folding funnels and frustration in off-lattice minimalist protein landscapes 5921–5928
Hugh Nymeyer, Angel E.García, and José Nelson Onuchic
Optimizing the stability of single-chain proteins by linker length and composition mutagenesis 5929–5934
Clifford R.Robinson and Robert T.Sauer
Architecture and mechanism of the light-harvesting apparatus of purple bacteria 5935–5941
Xiche Hu, Ana Damjanovi , Thorsten Ritz, and Klaus Schulten
Electrostatic steering and ionic tethering in enzyme-ligand binding: Insights from simulations 5942–5949
Rebecca C.Wade, Razif R.Gabdoulline, Susanna K.Lüdemann, and Valère Lounnas
Computer simulations of enzyme catalysis: Finding out what has been optimized by evolution 5950–5955
Arieh Warshel and Jan Florián
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COMPUTATIONAL BIOMOLECULAR SCIENCE 5848
Proc. Natl. Acad. Sci. USA
Vol. 95. p. 5848, May 1998
Colloquium Paper
This paper is the introduction to the following papers, which were presented at the colloquium “Computational Biomolecular
Science,” organized by Russell Doolittle, J.Andrew McCammon, and Peter G.Wolynes, held September 11–13, 1997, sponsored by the
National Academy of Sciences at the Arnold and Mabel Beckman Center in Irvine, CA.
Computational biomolecular science
PETER G.WOLYNES
School of Chemical Sciences, University of Illinois, Urbana-Champaign, Urbana, IL 61801
In this century, the study of the molecules of life has transformed the practice of biology as a whole. Molecular thinking now influences
the research agenda for scientists studying both the behavior of individual cells and organisms, and the relationships between organisms as in
natural history. Even ecology and anthropology are being influenced by this molecular revolution. It is impressive that this transformation has,
to a large extent, been made possible by simply identifying (with very clever strategies!) active biological molecules and cataloging their
information content through their sequences. One result of all this activity is that raw data about life at the molecular level have become
abundant, but understanding its biological meaning remains, in many if not most respects, perplexing. Fortunately, just at this stage, new
approaches to understanding the connection between biomolecular sequence and physiological behavior are coming forward. Computation,
theory, and novel experimental approaches that utilize the combinatorial power of the genetic code allow us to begin to understand
biomolecular function from both the bottom-up atomistic point-of-view of the physical sciences and the top-down view usually associated with
the evolutionary perspective.
The goal of this colloquium was to bring together some of the workers from different scientific disciplines who are approaching these
problems by using quantitative methods. Because computation plays such a large part in exploiting the information content of sequence data,
the conference was entitled “Computational Biomolecular Science,” although some of the essential input of new experiments to this emerging
discipline was covered too.
From the bottom-up perspective, the first event to consider on the road from sequence to the biological behavior of an organism is the
folding of a linear polymer into a three-dimensional structure. Once a molecule is properly folded, a variety of motions still go on in the folded
state. It is through these motions that the biological molecule can function. These dynamical aspects represent complex problems in chemistry
and physics. But it is the aptness with which these functions are carried out that at last determines whether the organism containing that
molecule can survive in the struggle with other organisms. Quantitatively understanding molecular behavior sufficiently well for understanding
this final biological goal requires much work from both the theoreticians and the experimentalists.
The top-down interpretation of molecular data appears to proceed quite differently. Avoiding the complexity of molecular theory, the
evolutionary perspective takes inheritance, perhaps the most self-evident aspect of “living” things, as its central concept. Comparing sequences
between different organisms then provides clues to their molecular function. In this study, dominant use is made of features of molecules that
do not change an organism’s fitness, thus allowing markers of inheritance to be reliably assigned. In a sense then the nonfunctional parts of a
molecule’s structure and dynamics are the most useful to the phylogenetically inclined scientist. Convergent evolution is hard to establish by
such studies but is critically important to those who wonder whether, from the atomistic perspective, there are indeed general themes to the
scheme of life. Despite its sometimes “life as a blackbox” character, the top-down viewpoint has achieved a myriad of successes in the practical
applications of biomolecular science.
A gap exists between the two different vantage points of looking at biomolecular information, but there are a surprising number of
common concepts. In understanding the folding, motions, and function of biological molecules, for example, a powerful new viewpoint that
describes the entire energy landscape of a biomoiecule in a statistical fashion is proving essential. Understanding and differentiating between
those parts of the energetics and dynamics that are biologically significant and those that can be thought of as random noise is the hallmark of
this approach. Similarly, in the comparative top-down approach to understanding sequence data, a tremendous amount of statistical thinking
must be done to understand whether a perceptible similarity between two sequences really means the molecules have comparable function or
structure or whether the similarity is just an accident. Just as in energy landscape theory, extracting signal from noise is the crucial point to
understanding molecular evolution. Such frankly statistical viewpoints must also be brought together when planning modern molecular biology
experiments that now begin to allow the study of a huge number of variants of a biomoiecule in the laboratory simultaneously at one time.
It became apparent in the meeting that, apart from the general common interest in biomolecules and the common but general theoretical
concepts based on statistics, there were many specific problems where the top-down and bottom-up viewpoints can profitably be merged For
example, surveys of genomes reveal widespread structural themes that may be clues to folding thermodynamics and kinetic folding routes. For
the atomists, several studies show how the structures of specific sequences can be predicted if knowledge of the sequences of many widely
different but evolutionary related molecules is available. On the other hand, for the evolutionist, an a priori knowledge of structural and
energetic patterns in molecules leads to refined algorithms for comparing sequences to obtain reliable phylogenies. Also, convergent evolution
can be recognized if both comparative and physical studies are available for proteins in the same family. This breaks evolutionary explanation
out of the mold of sophisticated Kipling “just-so” stories into the quantitative mode, most prized by natural scientists.
The papers in this colloquium give a partial snapshot of computational biomolecular science today. The organizers of the meeting,
J.A.McCammon, R.F.Doolittle, and I, hope these papers give the readers of the Proceedings an idea of what is going on in a branch of science
that is destined to grow much larger in the coming years.
© 1998 by The National Academy of Sciences 0027–8424/98/955848–1$2.00/0
PNAS is available online at http://www.pnas.org.
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MEASURING GENOME EVOLUTION 5849
Proc. Natl. Acad. Sci. USA
Vol. 95, pp. 5849–5856, May 1998
Colloquium Paper
This paper was presented at the colloquium “Computational Biomolecular Science,” organized by Russell Doolittle, J.Andrew
McCammon, and Peter G.Wolynes, held September 11–13, 1997, sponsored by the National Academy of Sciences at the Arnold and Mabel
Beckman Center in Irvine CA.
Measuring genome evolution
(ortholog/synteny/comptuer analysis/horizontal gene transfer)
MARTIJN A.HUYNEN* AND PEER BORK
European Molecular Biology Laboratory, Meyerhofstrasse 1, 69012 Heidelberg. Germany, and Max-Delbrück-Centrum for Molecular
Medicine, 13122 Berlin-Buch. Germany
ABSTRACT The determination of complete genome sequences provides us with an opportunity to describe and analyze evolution
at the comprehensive level of genomes. Here we compare nine genomes with respect to their protein coding genes at two levels: (i) we
compare genomes as “bags of genes” and measure the fraction of orthologs shared between genomes and (ii) we quantify correlations
between genes with respect to their relative positions in genomes. Distances between the genomes are related to their divergence times,
measured as the number of amino acid substitutions per site in a set of 34 orthologous genes that are shared among all the genomes
compared. We establish a hierarchy of rates at which genomes have changed during evolution. Protein sequence identity is the most
conserved, followed by the complement of genes within the genome. Next is the degree of conservation of the order of genes, whereas
gene regulation appears to evolve at the highest rate. Finally, we show that some genomes are more highly organized than others: they
show a higher degree of the clustering of genes that have orthologs in other genomes.
Molecular evolution usually is studied at the level of single genes. With the determination of genome sequences we have an opportunity to
study it at a higher, comprehensive level, that of complete genomes. This leads to the pertinent question: how can genomic information be used
to obtain useful information concerning genome evolution? The goal of this paper is to create baseline expectations for measures of genome
distances that are based on gene content. By describing some general patterns one also can identify the exceptions. Measuring evolution at the
level of complete genomes is pertinent as it is, after all, the principal level for natural selection. Furthermore, it is intermediate to levels at
which evolution has long been studied: namely, the molecular level in genes and genotypes, and the organismal level in the fossil record. The
genome in principle contains all of the information necessary to bridge the gap between genotype and phenotype. For example, by-knowing the
functions of the genes in a genome of a species we can postulate a model for its complete metabolism. However, we have to be careful not to
overstate our expectations. The situation might turn out to be analogous to that of proteins, for which, in principle, all information necessary to
determine three-dimensional structures in the form of amino acid sequences is known, yet we remain unable to predict their tertiary structures.
Genomes can be analyzed and compared for various features: e.g., nucleotide content, compositional biases of leading and lagging strands
in replication (e.g., in Escherichia coli) (1), dinucleotide frequencies (2), the occurrence of repeats (e.g., in virulence genes of Haemophilus
influenzae: ref. 3), RNA structures, coding densities, protein coding genes, operons, the size distribution of gene families (4), etc. They also can
be compared at a variety of levels: a first-order level where we regard the genome as a “bag of genes” without taking account of interactions
between the various components, and a second-order level that considers whether properties of genomes are cross-correlated (e.g., the absence
of certain polynucleotides together with the presence of restriction enzymes that specifically cut these polynucleotides; ref. 5). In this paper we
focus on first- and second-order patterns in protein coding regions in genomes. Specifically we measure: (i) the fraction of orthologous
sequences between genomes, (ii) the conservation of gene order between genomes, and (iii) the spatial clustering of genes in one genome that
have an ortholog in another genome. We correlate these measures with the divergence time between the genomes compared. It is not our goal
to define new distance measures to construct phylogenetic trees. Rather it is to analyze the conservation and differentiation of patterns between
genomes, to show how we can extract useful information from these, and to analyze at what relative time scales they change. The analyses are
done on the first nine sequenced Archaea and Bacteria that were publicly available: H.influenzae (6), Mycoplasma genitalium (7),
Synechocystis sp. PCC 6803 (8), Methanococcus jannaschii (9), Mycoplasma pneumoniae (10), E.coli (1), Methanobacterium
thermoautotrophicum (11), Helicobacter pylori (12), and Bacillus subtilis (13). Although the total number of publicly available genome
sequences is growing rapidly, the trends that we observe should remain largely unchanged with the comparison of new species, given the
diverse range of evolutionary distances of the species compared in this paper.
Methodological Issues in Comparisons of Genomes
Identification of Orthologous Genes. Defining orthology. In comparing the genes of different genomes it is important that we avoid
comparisons of “apples and pears”: i.e., that we are able to identify which genes correspond to each other in the various genomes. Fitch (14)
introduced the term “orthologs” for genes whose independent evolution reflects a speciation event rather than a gene duplication event. “Where
the homology is the result of gene duplication so that both copies have descended side by side during the history of an organism, (for example,
alpha and beta hemoglobin) the genes should be called paralogous (para=in parallel). Where the homology is the result of speciation so that the
history of the gene reflects the history of the species (for example, alpha hemoglobin in man and mouse) the genes should be called orthologous
(ortho=exact)” (14). Note that orthology and paralogy are
*To whom reprint requests should be addressed at: European Molecular Biology Laboratory, Meyerhofstrasse 1,69012 Heidelberg.
Germany, e-mail: