Virtual compound screening and SAR analysis [Elektronische Ressource] : method development and practical applications in the design of new serine and cysteine protease inhibitors / vorgelegt von Mihiret Tekeste Sisay
163 pages
English

Virtual compound screening and SAR analysis [Elektronische Ressource] : method development and practical applications in the design of new serine and cysteine protease inhibitors / vorgelegt von Mihiret Tekeste Sisay

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163 pages
English
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Virtual compound screening and SAR analysis: method development and practical applications in the design of new serine and cysteine protease inhibitors Dissertation zur Erlangung des Doktorgrades (Dr. rer. nat.) der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn vorgelegt von Mihiret Tekeste Sisay aus Worka/Äthiopien Bonn June 2010 Angefertigt mit Genehmigung der MathematischNaturwissenschaftlichen Fakultät der Rheinischen FriedrichWilhelmsUniversität Bonn 1. Referent: Univ.Prof. Dr. rer. nat. Jürgen Bajorath 2. Referent: Univ.Prof. Dr. rer. nat. Michael Gütschow Tag der Promotion: 01.10.2010 Acknowledgments I would like to express my deepest gratitude and appreciation to my supervisors Prof. Dr. Michael Gütschow and Prof. Dr. Jürgen Bajorath, for their continued guidance, encouragement and support both in my scientific and personal life throughout the course of this work. I am especially indebted to all my colleges and colleges of my supervisors with whom I had successful scientific collaborations especially to Prof. Dr. G. König, Prof. Dr. T. Steinmetzer, Prof. Dr. S. Fustero, Dr. L. Peltason, Dr. M. Stirnberg, Dr. D. Stumpfe, L. Tan, T. J. Crisman, M. Frizler, E. Maurer and S. Hauptmann. I am also grateful to Dr. P. W. Elsinghorst, Dr. H.G. Häcker and Dr. J.

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Publié par
Publié le 01 janvier 2010
Nombre de lectures 22
Langue English
Poids de l'ouvrage 8 Mo

Extrait

Virtual compound screening and SAR
analysis: method development and
practical applications in the design of
new serine and cysteine protease
inhibitors




Dissertation

zur
Erlangung des Doktorgrades (Dr. rer. nat.)
der
Mathematisch-Naturwissenschaftlichen Fakultät
der
Rheinischen Friedrich-Wilhelms-Universität Bonn



vorgelegt von
Mihiret Tekeste Sisay
aus
Worka/Äthiopien


Bonn
June 2010





















Angefertigt mit Genehmigung der MathematischNaturwissenschaftlichen
Fakultät der Rheinischen FriedrichWilhelmsUniversität Bonn


1. Referent: Univ.Prof. Dr. rer. nat. Jürgen Bajorath
2. Referent: Univ.Prof. Dr. rer. nat. Michael Gütschow
Tag der Promotion: 01.10.2010








Acknowledgments
I would like to express my deepest gratitude and appreciation to my
supervisors Prof. Dr. Michael Gütschow and Prof. Dr. Jürgen Bajorath, for
their continued guidance, encouragement and support both in my scientific
and personal life throughout the course of this work.
I am especially indebted to all my colleges and colleges of my
supervisors with whom I had successful scientific collaborations especially
to Prof. Dr. G. König, Prof. Dr. T. Steinmetzer, Prof. Dr. S. Fustero, Dr. L.
Peltason, Dr. M. Stirnberg, Dr. D. Stumpfe, L. Tan, T. J. Crisman, M.
Frizler, E. Maurer and S. Hauptmann. I am also grateful to Dr. P. W.
Elsinghorst, Dr. H.G. Häcker and Dr. J. Batista for their helpful advices
and discussions, and the rest of the members at the research groups of Prof.
M. Gütschow and Prof. J. Bajorath for their friendship and all the good
times I had.
I owe my deepest gratitude to my family for their endless love and am
deeply grateful to Asnake Asegu for his all time encouragement and support.
Especial thanks to Isa Schierstedt and her family for their encouragement
and limitless support particularly to Dr. D. Schierstedt and M. Schierstedt.
Lastly, I offer my regards and blessings to all of those who in one way
or another supported me.

























Dedicated to my parents
ለአባቴ፡ተከሥተ፡ሲሳይ
ለእናቴ፡አበበች፡በቀለ






ለሚያደርግልኝ፡ሁሉ፡እግዚአብሔር፡የተመሰገነ፡ይሁን።










Abstract
Virtual screening is an important tool in drug discovery that uses different
computational methods to screen chemical databases for the identification of
possible drug candidates. Most virtual screening methodologies are knowledge
driven where the availability of information on either the nature of the target
binding pocket or the type of ligand that is expect to bind is essential. In this
regard, the information contained in Xray crystal structures of proteinligand
complexes provides a detailed insight into the interactions between the protein
and the ligand and opens the opportunity for further understanding of drug
action and structure activity relationships at molecular level. Proteinligand
interaction information can be utilized to introduce targetspecific interaction
based constraints in the design of focused combinatorial libraries. Furthermore,
such information can also be directly transformed into structural interaction
fingerprints and can be applied in virtual screening to analyze docking studies or
filter compounds. However, the integration of proteinligand interaction
information into twodimensional compound similarity searching is not fully
explored. Therefore, novel methods are still required to efficiently utilize
proteinligand interaction information in twodimensional ligand similarity
searching. Furthermore, application of proteinligand interaction information in
the interpretation of SARs at the ligand level needs further exploration. Thus,
utilization of threedimensional protein ligand interaction information in virtual
screening and SAR analysis was the major aim of this thesis. The thesis is
presented in two major parts. In the first part, utilization of threedimensional
proteinligand interaction information for the development of a new hybrid
virtual screening method and analysis of the nature of SARs in analog series at
molecular level is presented.
A new virtual screening hybrid methodology, termed the interaction
annotated structural features, was introduced that assigns energybased scores to
twodimensional substructures based on threedimensional proteinligand
interaction information and utilize interactionannotated features in virtual
screening. Database molecules containing annotated fragments were assigned
cumulative scores that serve as a measure of similarity to active reference
compounds. In benchmark calculations on different highthroughput screening
i

data sets, the hybrid approach mostly performed better than conventional
fragmentbased twodimensional fingerprint similarity searching and three
dimensional docking calculations.
On the other hand, to better understand how SAR discontinuity detected
at the ligand level is reflected by threedimensional proteinligand interaction
information, different compound series in combinatorial analog graphs were
analyzed and substitution patterns that introduce activity cliffs were determined.
The identified SAR determinants were then studied on the basis of three
dimensional ligandtarget Xray crystal complexes to enable a structural
interpretation of SAR discontinuity and underlying activity cliffs. The analysis
showed that many discontinuous SAR features extracted from combinatorial
analog graphs can be directly associated with experimental threedimensional
receptorligand interactions. However, this was not always possible and some
substitution site patterns that introduce significant SAR discontinuity in analog
series cannot be explained in structural terms.
The second part of the thesis is focused on the application of different
virtual screening methods for the identification of new cysteine and membrane
bound serine proteases inhibitors. In addition, molecular modeling studies were
also applied to analyze the binding mode of cyclic peptide inhibitors.
Two major virtual screening campaigns were carried out to identify
cathepsin K, cathepsin S and matriptase2 inhibitors. While cathepsins K and S
are cysteine proteases, matriptase2 is a newly identified type II membrane
bound serine protease. These proteases are considered to be important current
pharmaceutical targets due to their involvement in bone resorption, immune
response and iron metabolism, respectively.
The first virtual screening application was focused at identification of
dual cathepsin K and S inhibitors using a ligandbased compound mapping
algorithm. By testing only 10 candidate compounds selected from a source
database containing ~3.7 million molecules, two inhibitors of cathepsin K and S
with new scaffolds were identified. Both inhibitors did not contain an
electrophilic “warhead” that usually is present in most of the previously
reported covalently interacting cathepsin inhibitors.
In a second study, through structurebased virtual screening in
combination with similarity searching and knowledgebased compound design,
two Nprotected dipeptide amides containing a 4amidinobenzylamide were
identified as the first small molecule inhibitors of matriptase2 with K values of i
170 nM and 460 nM, respectively. An inhibitor of the closely related protease,
matriptase1 (K = 220 nM) with more than 50fold selectivity over matriptase2 i
was also identified.
ii

These newly identified inhibitors of the above proteases provide starting
points for further chemical exploration of noncovalent cathepsins K and S
inhibitors and nonpeptidic matriptase2 inhibitors.
Finally, three new cyanobacterial peptides, brunsvicamides AC, were
identified as selective inhibitors of human leukocyte elastase (HLE) through
enzymebased screening assays. Further molecular modeling studies were
performed to analyze the possible binding mode of the cyclic peptides. The
results showed that the cyclic peptides bind into the active site of HLE by
forming several putative intermolecular interactions and mimicking an
experimentally determined binding mode of a similar cyclic peptide.

iii
Contents
1 General introduction 1

2 Integration of protein-ligand interaction information into
9 2D substructures for virtual screening
2.1 Introduction 9
2.1.1 Proteinligand interactions 10
2.1.2 Structural fingerprints 11
2.1.3 Similarity searching 13
2.2 Methodology 14
2.2.1 Data set 16
2.2.2 Atombased scoring of proteinligand interaction 18
2.2.3 Feature annotation 19
2.2.4 Calculations 19
2.3 Results and Discussion 20
2.3.1 The Interaction Annotated Structural Features 20
(IASF) method
2.3.2 Analysis o

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