New approaches to protein docking [Elektronische Ressource] / von Oliver Kohlbacher

Sujets

• Biologie

Informations

• Publié par: universitat_des_saarlandes
• Publié le: 01 janvier 2004
• Nombre de lectures: 39
• Langue: English
• Poids de l'ouvrage: 3 Mo

Extrait

New approaches to protein docking
Dissertation zur Erlangung des Grades
Doktor der Ingenieurwissenschaften (Dr.-Ing.)
der Naturwissenschaftlich-Technischen Fakulta¨t I
der Universita¨t des Saarlandes
von
Oliver Kohlbacher
Saarbru¨cken
12. Januar 2001Datum des Kolloquiums: 12. Januar 2000
Dekan der technischen Fakulta¨t:
Professor Dr. Rainer Schulze-Pillot-Ziemen
Gutachter:
Professor Dr. Hans-Peter Lenhof, Universita¨t des Saarlandes, Saarbru¨cken
Professor Dr. Kurt Mehlhorn, MPI fu¨r Informatik, Saarbru¨cken
2nigh
oring.
Biology
Y
w
to
y
no

l
w
for
d
biologist,
r
erimen
.
ears
st
y
and
things
x
v
in
our
a
,
to
p
as
in
"
m
our

tak

three
.
then,
n
the
so
es
is
all

die
k
start
y
In


ro
wn
deserv
otics
of

eing
an
it
e
ork
partly
a
ute
it
applications
b
i
Y
bio
exp
rese
ts
hemistry
e
o
ou
.
y
h
and
.
one
t
t,
is
electricit
w
go
digital,
o
e
and

the
part
!
I
h
th
g
b
orlds.
but
ou

o
use
er.
ful.

The
e
trouble

with
o
biology
w
is
Biologists
that,
e
if
lot
y

ou
b
ha
able
v
slug
e
through.
to
's
\
– Donald KnuthAcknowledgements
The work on this thesis was carried out during the years 1996–2000 at the Max-Planck-
Institut fu¨r Informatik in the group of Prof. Dr. Kurt Mehlhorn under the supervision of
Prof. Dr. Hans-Peter Lenhof.
Prof. Dr. Hans-Peter Lenhof kindled my interest in Bioinformatics and gave me the freedom
to do research in those areas that fascinated me most. Our discussions, although sometimes
heated, were always fruitful and forced me to get to the very bottom of many problems.
The implementation of BALL is unthinkable without the help of all the people who con-
tributed code and ideas. Nicolas Boghossian had significant impact on the design of the library
core and contributed lots of code for the kernel. Heiko Klein implemented the largest part of
the visualization. Dr. Peter Mu¨ller brought in his experience in the field of molecular dynamics
simulations. Andreas Burchardt implemented parts of the NMR code. Upon Andreas Moll fell
the ungrateful work of testing and debugging. Stefan Strobel implemented the difficult part
of molecular surface calculations. Andreas Hildebrandt implemented the NMR visualization.
The more sophisticated parts of the solvation code were implemented by Andreas Kerzmann,
who also set up the BALL web server. Last, but not least, Prof. Dr. Hans-Peter Lenhof not only
contributed code for structure mapping and force field calculations, but also initiated the whole
project and kept everyone motivated.
Ernst Althaus implemented the branch-&-cut-algorithm and was coauthor of the paper on
flexible docking. He had the patience to explain to me some of the finer details of polyhedral
theory.
The Rechnerbetriebsgruppe had to suffer from this work as well. Jo¨rg Herrmann, Wolfram
Wagner, Bernd Fa¨rber, Uwe Brahm, Thomas Hirtz, and Roland Berberich solved numerous of
my hardware- and software-related problems even at night and during weekends. Christoph
AClodo managed to track down and resolve several errors in the LT X code of this thesis.E
I am also grateful to my “WG” (Holger, Michael, Christian) for nearly six years of enjoy-
able coexistence and for the flat, the evenings, and quite some bottles of wine we shared. Last,
but certainly not least, I wish to thank Andreas for his patience, his understanding, and his
support while I wrote this thesis.Abstract
In the first part of this work, we propose new methods for protein docking. First, we present two ap-
proaches to protein docking with flexible side chains. The first approach is a fast greedy heuristic, while
the second is a branch-&-cut algorithm that yields optimal solutions. For a test set of protease-inhibitor
complexes, both approaches correctly predict the true complex structure. Another problem in protein
docking is the prediction of the binding free energy, which is the the final step of many protein docking
algorithms. Therefore, we propose a new approach that avoids the expensive and difficult calculation of
the binding free energy and, instead, employs a scoring function that is based on the similarity of the
proton nuclear magnetic resonance spectra of the tentative complexes with the experimental spectrum.
Using this method, we could even predict the structure of a very difficult protein-peptide complex that
could not be solved using any energy-based scoring functions.
The second part of this work presents BALL (Biochemical ALgorithms Library), a framework for
Rapid Application Development in the field of Molecular Modeling. BALL provides an extensive set
of data structures as well as classes for Molecular Mechanics, advanced solvation methods, comparison
and analysis of protein structures, file import/export, NMR shift prediction, and visualization. BALL
has been carefully designed to be robust, easy to use, and open to extensions. Especially its extensibility,
which results from an object-oriented and generic programming approach, distinguishes it from other
software packages.
Kurzzusammenfassung
Der erste Teil dieser Arbeit bescha¨ftigt sich mit neuen Ansa¨tzen zum Proteindocking. Zuna¨chst stellen
wir zwei Ansa¨tze zum Proteindocking mit flexiblen Seitenketten vor. Der erste Ansatz beruht auf einer
schnellen, gierigen Heuristik, wa¨hrend der zweite Ansatz auf branch-&-cut-Techniken beruht und das
Problem optimal lo¨sen kann. Beide Ansa¨tze sind in der Lage die korrekte Komplexstruktur fu¨r einen
Satz von Testbeispielen (bestehend aus Protease-Inhibitor-Komplexen) vorherzusagen. Ein weiteres,
gro¨sstenteils ungelo¨stes, Problem ist der letzte Schritt vieler Protein-Docking-Algorithmen, die Vorher-
sage der freien Bindungsenthalpie. Daher schlagen wir eine neue Methode vor, die die schwierige und
aufwa¨ndige Berechnung der freien Bindungsenthalpie vermeidet. Statt dessen wird eine Bewertungs-
¨funktion eingesetzt, die auf der Ahnlichkeit der Protonen-Kernresonanzspektren der potentiellen Kom-
plexstrukturen mit dem experimentellen Spektrum beruht. Mit dieser Methode konnten wir sogar die
korrekte Struktur eines Protein-Peptid-Komplexes vorhersagen, an dessen Vorhersage energiebasierte
Bewertungsfunktionen scheitern.
Der zweite Teil der Arbeit stellt BALL (Biochemical ALgorithms Library) vor, ein Rahmenwerk
zur schnellen Anwendungsentwicklung im Bereich Molecular Modeling. BALL stellt eine Vielzahl von
Datenstrukturen und Algorithmen fu¨r die Felder Moleku¨lmechanik, Vergleich und Analyse von Protein-
strukturen, Datei-Import und -Export, NMR-Shiftvorhersage und Visualisierung zur Verfu¨gung. Beim
Entwurf von BALL wurde auf Robustheit, einfache Benutzbarkeit und Erweiterbarkeit Wert gelegt.
Von existierenden Software-Paketen hebt es sich vor allem durch seine Erweiterbarkeit ab, die auf der
konsequenten Anwendung von objektorientierter und generischer Programmierung beruht.Contents
Part I – Introduction 1
Part II – Protein Docking 7
1 Biochemistry – the Basics 9
1.1 Atoms and Molecules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2 Amino Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.3 Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.4 Nucleic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.5 Interatomic Forces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.5.1 Nonbonded interactions . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.5.2 Molecular Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2 Introduction 19
2.1 Rigid Body Docking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 Docking and Protein Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3 Combining NMR Data and Docking Algorithms . . . . . . . . . . . . . . . . . 23
3 Semi-Flexible Docking 25
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2 The Docking Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.1 Rigid Docking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.2 Side Chain Demangling . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.3 The Multi-Greedy Method . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2.4 The Branch-&-Cut Algorithm . . . . . . . . . . . . . . . . . . . . . . 30
3.2.5 Energetic Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4 Protein Docking and NMR 45
4.1 Nuclear Magnetic Resonance Spectroscopy . . . . . . . . . . . . . . . . . . . 45
4.1.1