Current
Topics in Medicinal Chemistry
ISSN: 1568-0266
Current Topics
in Medicinal Chemistry
Volume 7, Number 10, 2007
Contents
Small Molecule Inhibition of Protein-Protein
Interaction: An Emerging Paradigm in Drug Design
Guest Editor: Craig W. Lindsley
Editorial Pp. 921
Protein–Protein Interaction Inhibitors:
Small Molecules from Screening Techniques Pp. 922-927
Steven Fletcher and Andrew D. Hamilton
[Abstract]
Scaffolds for Blocking Protein-Protein Interactions
Pp. 928-942
Stefan J. Hershberger, Song-Gil Lee and Jean Chmielewski
[Abstract]
Towards Drugs Targeting Multiple Proteins in a Systems
Biology Approach Pp. 943-951
O. Keskin, A. Gursoy, B. Ma and R. Nussinov
[Abstract]
Small Molecule Protein-Protein Inhibitors for the
p53-MDM2 Interaction Pp. 952-960
Anna S. Dudkina and Craig W. Lindsley
[Abstract]
Small Molecule Inhibition of the Bcl-XL–BH3
Protein-Protein Interaction: Proof-of-Concept of an In
Vivo Chemopotentiator ABT-737 Pp. 961-965
Shaun R. Stauffer
[Abstract]
Small Molecule Inhibitors of the XIAP Protein-Protein
Interaction Pp. 966-971
Hemaka A. Rajapakse
[Abstract]
Disruption of the Keap1-Containing Ubiquitination
Complex as an Antioxidant Therapy Pp. 972-978
Jonathan T. Kern, Mark Hannink and J. Fred Hess
[Abstract]
Computational Approaches in Medicinal Chemistry and
Drug Discovery
Guest Editor: Dr. Fredy Sussman
Editorial Pp. 979
The Search for Drug Leads Targeted to the β-Secretase:
An Example of the Roles of Computer Assisted Approaches in
Drug Discovery Pp. 980-990
M. Carmen Villaverde, Lucía González-Louro
and Fredy Sussman
[Abstract]
Structural Models of Class A G Protein-Coupled Receptors
as a Tool for Drug Design: Insights on Transmembrane Bundle
Plasticity Pp. 991-998
Xavier Deupi, Nicole Dölker, María Luz López-Rodríguez,
Mercedes Campillo and Leonardo Pardo
[Abstract]
Trp/Met/Phe Hot Spots in Protein-Protein Interactions:
Potential Targets in Drug Design Pp. 999-1005
Buyong Ma and Ruth Nussinov
[Abstract]
Ligand Docking and Structure-based Virtual Screening
in Drug Discovery Pp. 1006-1014
Claudio N. Cavasotto and Andrew J.W. Orry
[Abstract]
Medicinal Chemistry and Bioinformatics - Current Trends
in Drugs Discovery with Networks Topological Indices
Pp. 1015-1029
Humberto González-Díaz, Santiago Vilar,
Lourdes Santana and Eugenio Uriarte
[Abstract]
Structure Based Drug Design for HIV Protease: From
Molecular Modeling to Cheminformatics Pp. 1030-1038
Patra Volarath, Robert W. Harrison and Irene T. Weber
[Abstract]
Molecule
of Month
Abstracts
[Back to top]
Editorial
Protein-protein interactions (PPIs) are ubiquitous in biological
systems, with essential functions in key of biological processes
such as cell growth and differentiation, intracellular signaling
and programmed cell death (apoptosis). Due to the pivotal
role of PPIs, protein-protein interfaces have garnered attention
as novel targets for therapeutic intervention in oncology,
neuroscience and antiinfectives. However, the pharmaceutical
industry has long regarded PPIs as intractable targets, which
could only be disrupted by large macromolecules and peptides.
Indeed, PPI targets are considerably more complex than classical
enzyme targets, characterized by well-defined binding pockets
and small molecule substrates, for a number of reasons. First,
the natural protein ligand polypeptides of a PPI do not afford
design opportunities for the development of small molecule
leads and protein surfaces/residues which contribute to the
binding interface are often unknown. Second, small molecule
inhibitors appear to be at a disadvantage as the interacting
protein-protein surfaces are large, featureless and often
contain buried surfaces essential to the PPI. Finally, few
small “drug like” leads have emerged from classical
high-throughput screens aimed at identifying disruptors of
PPIs, and alternative screening techniques are often required.
Despite these significant challenges, progress has been made
and small molecule disruptors of PPIs have been discovered.
In large part, recent success in this field has been due to
the pioneering work of Clarkson and Wells and the discovery
of “hot spots”. Hot spots are small, high affinity
regions at the protein-protein interface of many PPIs and
can account for the majority (>80%) of the binding energy.
As a result, disruptors of PPIs do not need to mimic the entire
protein binding surface, but rather a smaller subset of key
residues, suggesting small molecules can disrupt PPIs. There
are now reports of a staggering diversity of small molecule
chemotypes that disrupt PPIs and the concept of ‘privileged
structures’, usually associated with GPCR ligands, can
now be easily applied to small molecule PPIs.
This issue contains a collection of reviews that describe
state-of -the art screening techniques, medicinal chemistry
strategies and case studies for various protein-protein targets.
The authors have included the background biology needed to
understand the target rationale and then have moved on to
the screening paradigm, lead discovery and drug optimization
stages as appropriate. The reader will find introductory reviews
describing PPI chemotypes, screening techniques and system
biology approaches followed by case studies on such important
PPI targets as p53/HDM2, XIAP, Bcl-XL–BH3
and Nrf2-Keap1. I hope that this Issue serves to inspire and
inform researchers interested in protein-protein interactions
and accelerates scientific discovery in this arena.
Craig W. Lindsley
Departments of Pharmacology and Chemistry
Vanderbilt Medical Center
RRB 804
Nashville, TN 37232-6600
USA
[Back to top]
Protein–Protein Interaction Inhibitors: Small
Molecules from Screening Techniques
Steven Fletcher and Andrew D. Hamilton
Protein–protein interactions play crucial roles in a
number of biological processes, and, as such, their disruption
is becoming an area of intense research. Despite the many
challenges associated with the development of protein–protein
interaction inhibitors, such as the large and relatively featureless
interfacial areas involved, there has been considerable success
in recent years. Importantly, through the existence of protein
“hot spots”, some of this success takes the form
of small molecule inhibitors that have been identified from
a variety of screening techniques.
[Back to top]
Scaffolds for Blocking Protein-Protein Interactions
Stefan J. Hershberger, Song-Gil Lee and Jean Chmielewski
Due to the pivotal roles that protein-protein interactions
play in a plethora of biological processes, the design of
therapeutic agents targeting these interactions has become
an attractive and important area of research. The development
of such agents is faced with a variety of challenges. Nevertheless,
considerable progress has been made in the design of proteomimetics
capable of disrupting protein-protein interactions. Those
inhibitors based on molecular scaffold designs hold considerable
interest because of the ease of variation in regard to their
displayed functionality. In particular, protein surface mimetics,
α-helical
mimetics, β-sheet/β-strand
mimetics, as well as β-turn
mimetics have successfully modulated protein-protein interactions
involved in such diseases as cancer and HIV. In this review,
current progress in the development of molecular scaffolds
designed for the disruption of protein-protein interactions
will be discussed with an emphasis on those active against
biological targets.
[Back to top]
Towards Drugs Targeting Multiple Proteins in a Systems
Biology Approach
O. Keskin, A. Gursoy, B. Ma and R. Nussinov
Protein-protein interactions are increasingly becoming drug
targets. This is understandable, since they are crucial at
all levels of cellular expression and growth. In practice,
targeting specific disease-related interactions has proven
difficult, with success varying with specific complexes. Here,
we take a Systems Biology approach to targeting protein-protein
interactions. Below, we first briefly review drug discovery
targeted at protein-protein interactions; we classify protein-protein
complexes with respect to their types of interactions and
their roles in cellular function and as being targets in drug
design; we describe the properties of the interfaces as related
to drug design, focusing on hot spots and surface cavities;
and finally, in particular, we cast the interactions into
the cellular network system, highlighting the challenge of
partially targeting multiple interactions in the networks
as compared to hitting a specific protein-protein interaction
target. The challenge we now face is how to pick the targets
and how to improve the efficiency of designed partially-specific
multi-target drugs that would block parallel pathways in the
network.
[Back to top]
Small Molecule Protein-Protein Inhibitors for the
p53-MDM2 Interaction
Anna S. Dudkina and Craig W. Lindsley
This article describes recent progress in the development
of small molecule protein-protein inhibitors of the p53-MDM2
(purine double minute 2, or HDM2 for the human congener) protein-protein
interaction, with special attention to the diversity of chemotypes
reported to disrupt this protein-protein interaction. In >50%
of all human cancers, the tumor supressor 53 KDa phospho-protein
p53 is either mutated or deleted. The discovery that MDM2
(HDM2) negatively regulates p53 and therefore inhibits the
tumor-supressor activity of p53 has instigated numerous drug
discovery campaigns aimed at disrupting this protein-protein
interaction as a potential cancer therapy. Once regarded as
intractable targets disrupted by only large macromolecules,
protein-protein interactions (PPI) are now mainstream targets
due in large part to the intensive effort applied to the study
of p53 and the surprising diversity of small molecules (peptides,
natural products, terphenyl and other α-helix
mimetics, chalcones, piperidines, piperazines, fused indoles,
isoindolinones, spiro-oxindoles, cis-imidazolines
(nutlins), quinolinol and benzodiazepines) capable of disrupting
the p53-HDM2 PPI. In addition, drug discovery researchers
have employed a number of screening approaches and technologies
to identify SMPPIs of the p53-HDM2 interaction, and these
discovery paradigms will be dicussed. This review will detail
the biology of the p53-MDM2 interaction, the major classes
of SMPPIs and key medicinal chemistry and in vitro/in
vivo biological data reported through October 2006.
[Back to top]
Small Molecule Inhibition of the Bcl-XL–BH3
Protein-Protein Interaction: Proof-of-Concept of an In
Vivo Chemopotentiator ABT-737
Shaun R. Stauffer
The Bcl-2 family of anti-apoptotic proteins are key regulators
of programmed cell death. Bcl-2 and its closely related Bcl-XL
counterpart are one of several pro-survival proteins which
can share up to four highly conserved domains known as the
BH1, BH2, BH3 and BH4 domains. These domains form the basis
of a well defined groove whereupon a heterodimeric protein-protein
interaction can occur with pro-apoptotic BH3 proteins such
as Bad, Bid and Bim. Extensive evidence clearly indicates
a strong correlation between neoplastic progression and deregulation
of apoptotic pathways. Overexpression of Bcl-XL
is associated with tumor progression, poor prognosis and resistance
to chemotherapy. Antagonism of Bcl-XL
is therefore viewed as a means to mimic the endogenous apoptotic
pathways initiated by Bad, Bid and other pro-apoptotic proteins.
Several successful approaches to block the Bcl-XL-BH3
binding groove have been reported but only recently have proteomimetics
been found which could prove to be clinically useful as new
anticancer agents capable of overcoming apoptosis resistance.
ABT-737 is an example of one of the first small-molecule inhibitors
of Bcl-2/XL
proteins shown to be efficacious in vivo, causing
complete regression in small-cell lung carcinoma tumour xenografts
in mice. This review will focus on the recent advances surrounding
the non-peptidic Bcl-2/XL
inhibitor ABT-737 developed by Abbot laboratories and highlight
the key structural characteristics found within this unique
BH3 alpha-helical mimetic.
[Back to top]
Small Molecule Inhibitors of the XIAP Protein-Protein
Interaction
Hemaka A. Rajapakse
The X-linked inhibitor of apoptosis proteins (XIAP) is thought
to play a key role in the unchecked proliferation of cancer
cells by interfering with the signaling cascade leading to
cell death. The structure and mechanism of XIAP has been widely
investigated and characterized over the past few years, to
the point where this may be the best understood apoptosis
protein inhibitor. As a result, XIAP is viewed as an attractive
target for the treatment of cancer. To date, several research
groups have reported on the discovery of small molecule inhibitors
of this protein. This review focuses on the discovery and
optimization of these leads.
[Back to top]
Disruption of the Keap1-Containing Ubiquitination
Complex as an Antioxidant Therapy
Jonathan T. Kern, Mark Hannink and J. Fred Hess
The transcription of antioxidant response element (ARE)–containing
cytoprotective genes has been proposed as a means to combat
oxidative stress–related disorders, such as cancer and
Parkinson’s disease. Transactivation of the ARE requires
the transcription factor nuclear factor erythroid 2-related
factor 2 (Nrf2). Cellular levels of Nrf2 protein are regulated
by the Kelch-like ECH-associated protein 1 (Keap1), a substrate
adaptor protein for the ubiquitin ligase machinery and subsequent
proteasomal degradation. Recently, detailed studies have elucidated
the structure and interactions of the Keap1-containing ubiquitin
ligase complex. Here, we propose that small molecule modulation
of Keap1 protein:protein interactions may permit Nrf2’s
nuclear accumulation and the transcription of ARE-dependent
genes to enhance cellular resistance to oxidative insult.
[Back to top]
Editorial
The present CTMC issue entitled ‘Computational Approaches
in Medicinal Chemistry and Drug Discovery’, covers a
wide range of methodologies and applications that are having
an increasing impact in the search for drug leads both in
academic and pharmaceutical industry settings. These reviews
deal with the wide gamut of methodologies used in this field
ranging from the application of QSAR based techniques (see
contributions by González-Diaz et al. and
Volarath et al.) to receptor based binding predictions
of Cavasotto and Orry, Villaverde et al. and Volarath et
al. The latter algorithms have spanned the Structure-Based
Virtual Screening (SBVS) of novel protein ligands, an in
silico technique that can be used successfully in synergy
with the wet lab High Throughput Screening protocols (HTS),
in the search for drug leads with novel chemical moieties,
as shown by Cavasotto and Orry. It is worth noticing that
the computer assisted methods presented here could also have
a bearing on a large number of disciplines (including proteomics)
assisted and supported by the use of QSAR protocols based
on topological indexes (see review by González-Diaz
et al.).
The drug targets are also well represented. They include the
HIV-1 PR protease (see review by Volarath et al.),
arguably the most successful receptor based rational lead
design endeavor in the history of drug discovery. As it is
well known, drugs based on inhibitors of this enzyme have
made a huge impact in the life span and quality of life of
AIDS patients. The experience gathered for an enzymatic target
could be employed in targeting other enzymes of the same family.
That has been the case of β-secretase
(a member of the same protease family as the HIV-1 protease)
which is crucial for the development of amyloid plaques in
the brain of Alzheimer diseased patients. Although the inhibitor
sequence specificities are quite different for both enzymes,
similar kinds of isosteres, as those employed for HIV-1 PR,
are currently being used for the design of β-secretase
inhibitors. Based on our current involvement in a β-secretase
inhibitor discovery program we reviewed this burgeoning field
in the light of computer assisted approaches on drug discovery
(see review by Villaverde et al.).
No review issue on computer assisted drug design could be
complete without a chapter on G-coupled protein receptors
(GCPRs), one of the largest protein families whose functioning
is activated by a wide range of external signals (odor, light,
etc) as well as internal signals (ions, hormones, neurotransmitters,
etc). These proteins are the target of about 40% of the prescribed
drugs and of around 25% of the top-selling drugs. GPCRs interact
with an extraordinary diversity of ligands by means of their
extracellular domains and/or the extracellular part of the
transmembrane (TM) segment. Each receptor subfamily has developed
specific sequence motifs to adjust the structural characteristics
of its cognate ligands to a common set of conformational rearrangements
of the TM segments near the G protein binding domains during
the activation process. This adaptation has been achieved
during evolution by customizing a preserved 7TM scaffold through
conformational plasticity. Deupi et al.
have contributed to this issue a review on this subject that
helps to explain the functional versatility of these molecules.
A large number of diseases can be explained nowadays in terms
of protein aggregation. These include degenerative CNS diseases,
some types of diabetes, etc. The group headed by Nussinov
has been at the forefront of the computer assisted study of
protein-protein interactions and has contributed many new
insights to this field. In this issue Ma and Nussinov review
their seminal work on the detection of residues that constitute
hot spots for protein interaction and aggregation, a crucial
issue in the design of drugs targeted against the formation
of plaques that are thought to be the causal source of these
diseases.
Fredy Sussman
Departamento de Química Orgánica,
Facultad de Química,
Universidad de Santiago de Compostela,
15782-Santiago de Compostela,
Spain
[Back to top]
The Search for Drug Leads Targeted to the β-Secretase:
An Example of the Roles of Computer Assisted Approaches in
Drug Discovery
M. Carmen Villaverde, Lucía González-Louro
and Fredy Sussman
The inhibition of β-secretase
has become a very promising approach to control the onset
and progression of Alzheimer’s disease due to its involvement
in the generation of amyloid plaques. The main goal of the
many drug discovery projects targeting this enzyme is the
identification of highly specific, non-peptidic compounds
with low molecular weight, characteristics that are desirable
for drug leads with low toxicity that have to transverse the
blood brain barrier. We describe the main approaches used
in the discovery of novel inhibitors, including substrate
specificity, target structure based design, and high throughput
screening (HTS), both in vitro and in silico.
We place special emphasis in the receptor based design and
in silico HTS, two strategies that make wide use
of computer assisted tools. To exemplify the usefulness and
versatility of computer tools in this endeavor we use the
computer generated ‘enzyme’s binding site cast’
to rationalize qualitatively some salient structural features
of known β-secretase
second generation inhibitors, and for guiding the review of
many of the ligands whose complexes with the enzyme have been
studied by X-ray crystallography. We discuss the use made
by other authors of molecular modelling for the understanding
of the very special characteristics of ligand binding to β-secretase
and for the design of new inhibitors. Finally, we review the
quest for non-peptidic inhibitors that has led to the use
of HTS in vitro and in silico. The screening
of extensive libraries resulted in a few low affinity compounds
that do not fit into the key S1/S1’ pockets, indicating
that this is not an easy target to block.
[Back to top]
Structural Models of Class A G Protein-Coupled Receptors
as a Tool for Drug Design: Insights on Transmembrane Bundle
Plasticity
Xavier Deupi, Nicole Dölker, María Luz López-Rodríguez,
Mercedes Campillo and Leonardo Pardo
G protein-coupled receptors (GPCRs) interact with an extraordinary
diversity of ligands by means of their extracellular domains
and/or the extracellular part of the transmembrane (TM) segments.
Each receptor subfamily has developed specific sequence motifs
to adjust the structural characteristics of its cognate ligands
to a common set of conformational rearrangements of the TM
segments near the G protein binding domains during the activation
process. Thus, GPCRs have fulfilled this adaptation during
their evolution by customizing a preserved 7TM scaffold through
conformational plasticity. We use this term to describe
the structural differences near the binding site crevices
among different receptor subfamilies, responsible for the
selective recognition of diverse ligands among different receptor
subfamilies. By comparing the sequence of rhodopsin at specific
key regions of the TM bundle with the sequences of other GPCRs
we have found that the extracellular region of TMs 2 and 3
provides a remarkable example of conformational plasticity
within Class A GPCRs. Thus, rhodopsin-based molecular models
need to include the plasticity of the binding sites among
GPCR families, since the “quality” of these homology
models is intimately linked with the success in the processes
of rational drug-design or virtual screening of chemical databases.
[Back to top]
Trp/Met/Phe Hot Spots in Protein-Protein Interactions:
Potential Targets in Drug Design
Buyong Ma and Ruth Nussinov
Protein-protein interactions are crucial to biological functions.
Consequently, designing drugs to control protein-protein interactions
is receiving increasing attention. Protein structures can
associate in different ways. Analysis of the structures of
protein-protein complexes using amino acid sequence order-independent
multiple structural comparison algorithms, led us to conclude
that the amino acids Trp, Met, and Phe are important for protein-protein
interactions. Hence, in principle, drug design targeting the
Trp/Met/Phe should modulate protein functions effectively.
Several clusters of the Trp/Met/Phe residues are involved
in the p53 protein-protein interactions. The best example
in this regard is the Phe19/Trp23 of p53, which binds to transcriptional
factors and to the MDM2 protein. In the HIV related proteins,
the Trp/Met/Phe residues have roles in the dimerization of
the transcriptase (p51/p66) and in cell-fusion processes,
including the gp120-CD4 interaction and the gp41 six-helix
bundle formation. Trp/Met/Phe residues are preferred in 'normal'
functional protein-protein interactions and they also appear
to be exploited in amyloid formation, especially the phenylalanine.
Comparison of binding propensity and amyloid formation preference
reveals that apart from Lysine, Isoleucine is the least structurally
conserved in protein binding sites and has a high propensity
in sequences forming amyloids. Thus, this may suggest that
nature tends to avoid Ile conservation in protein-protein
interaction to avoid amyloid formation. In this regards, Trp/Met/Phe
as well as Ile may be targeted to modulate protein-protein
interaction.
[Back to top]
Ligand Docking and Structure-based Virtual Screening
in Drug Discovery
Claudio N. Cavasotto and Andrew J.W. Orry
Ligand-docking—based methods are starting to play a
critical role in lead discovery and optimization, thus resulting
in new ‘drug-candidates’. They offer the possibility
to go beyond the pool of existing active compounds, and thus
find novel chemotypes. A brief tutorial on ligand docking
and structure-based virtual screening is presented highlighting
current problems and limitations, together with the most recent
methodological and algorithmic developments in the field.
Recent successful applications of docking-based tools for
hit discovery, lead optimization and target-biased library
design are also presented. Special consideration is devoted
to ongoing efforts to account for protein flexibility in structure-based
virtual screening.
[Back to top]
Medicinal Chemistry and Bioinformatics - Current Trends
in Drugs Discovery with Networks Topological Indices
Humberto González-Díaz, Santiago Vilar,
Lourdes Santana and Eugenio Uriarte
The numerical encoding of chemical structure with Topological
Indices (TIs) is currently growing in importance in Medicinal
Chemistry and Bioinformatics. This approach allows the rapid
collection, annotation, retrieval, comparison and mining of
chemical structures within large databases. TIs can subsequently
be used to seek quantitative structure-activity relationships
(QSAR), which are models connecting chemical structure with
biological activity. In the early 1990´s, there was
an explosion in the introduction and definition of new TIs.
The Handbook of Molecular Descriptors by Todeschini
and Consonni lists more than 1500 of these indices. At the
end of the last century, researchers produced a large number
of TIs with essentially the same advantages and/or disadvantages.
Consequently, many researchers abandoned the definition of
TIs for a time. In our opinion, one of the problems associated
with TIs is that researchers aimed their efforts only at the
codification of chemical connectivity for small-sized drugs.
As a consequence, recently it seems that we have arrived at
“Fukuyama´s End of History in TIs definition”.
In the work described here, we review and comment on the “quo
vadis” and challenges in the definition of TIs
as we enter the new century. Emphasis is placed on new chiral
TIs (CTIs), flexible TIs for unifying QSAR models with multiple
targets, topographic indices (TPGIs), TIs for DNA and protein
sequences, TIs for 2D RNA structures, TPGIs and drug-protein
or drug-RNA quantitative structure-binding relationship (QSBR)
studies, TIs to encode protein surface information and TIs
for protein interaction networks (PINs).
[Back to top]
Structure Based Drug Design for HIV Protease: From
Molecular Modeling to Cheminformatics
Patra Volarath, Robert W. Harrison and Irene T. Weber
Significant progress over the past decade in virtual representations
of molecules and their physicochemical properties has produced
new drugs from virtual screening of the structures of single
protein molecules by conventional modeling methods. The development
of clinical antiviral drugs from structural data for HIV protease
has been a major success in structure based drug design. Techniques
for virtual screening involve the ranking of the affinity
of potential ligands for the target site on a protein. Two
main alternatives have been developed: modeling of the target
protein with a series of related ligand molecules, and docking
molecules from a database to the target protein site. The
computational speed and prediction accuracy will depend on
the representation of the molecular structure and chemistry,
the search or simulation algorithm, and the scoring function
to rank the ligands. Moreover, the general challenges in modern
computational drug design arise from the profusion of data,
including whole genomes of DNA, protein structures, chemical
libraries, affinity and pharmacological data. Therefore, software
tools are being developed to manage and integrate diverse
data, and extract and visualize meaningful relationships.
Current areas of research include the development of searchable
chemical databases, which requires new algorithms to represent
molecules and search for structurally or chemically similar
molecules, and the incorporation of machine learning techniques
for data mining to improve the accuracy of predictions. Examples
will be presented for the virtual screening of drugs that
target HIV protease.
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