Current
Computer-Aided Drug Design
ISSN: 1573-4099
Current Computer-Aided
Drug Design
Volume 3, Number 1, March 2007
Contents
The Rational Design of Bacterial Toxin Inhibitors
Pp. 1-12
Graeme C. Clark, Ajit K. Basak and Richard W. Titball
[Abstract] [Full
text article]
Aerosol Drug Delivery Optimization by Computational
Methods for the Characterization of Total and Regional Deposition
of Therapeutic Aerosols in the Respiratory System
Pp. 13-32
Imre Balásházy, Bálint Alföldy,
Andrea J. Molnár, Werner Hofmann, István and
Erika Kis
[Abstract] [Full
text article]
Acceleration of the Drug Discovery Process: A Combinatorial
Approach Using NMR Spectroscopy and Virtual Screening
Pp. 33-49
Xavier Morelli and Alan C. Rigby
[Abstract] [Full
text article]
Inhibitors of Protein-Protein Interactions as Potential
Drugs Pp. 51-58
Alexander V. Veselovsky and Alexander I. Archakov
[Abstract] [Full
text article]
Substructural Analysis in Drug Discovery
Pp. 59-67
Hugo O. Villar, Mark R. Hansen and Richard Kho
[Abstract] [Full
text article]
Computational Approaches for Fragment Optimization
Pp. 69-83
Eric Vangrevelinghe and Simon Rüdisser
[Abstract] [Full
text article]
Abstracts
[Back to top]
The Rational Design of Bacterial Toxin Inhibitors
Graeme C. Clark, Ajit K. Basak and Richard W. Titball
[Full
text article]
Protein toxins play key roles in many infectious diseases
of humans which are caused by bacteria. In some cases the
toxin alone is directly responsible for the majority of the
symptoms of the disease (e.g. tetanus, anthrax, diphtheria).
In others the toxin is one of an arsenal of virulence factors
which allow the bacterium to cause disease. Antibiotics are
currently the mainstay for the treatment of bacterial infections.
However, increasing levels of antibiotic resistance and the
indiscreet nature of antibiotic therapy are limitations. Prior
to the availability of antibiotics, antisera against toxins
were often used to treat bacterial disease. Nowadays, animal-sourced
products, such as antisera, are generally not acceptable for
use in humans. Against the background there is an increasing
interest in the development of low molecular weight inhibitors
of toxins for the treatment of disease. For some toxins, like
anthrax toxin, botulinum toxin and shigella toxin, low molecular
weight inhibitors demonstrate proof of principle of this concept.
For most other toxins the design and development of inhibitors
is now a very real prospect; the crystal structures of many
toxins are available, and in most cases the identity of the
substrate or receptor is known. This article describes in
detail the rational design of bacterial toxin inhibitors.
[Back to top]
Aerosol Drug Delivery Optimization by Computational
Methods for the Characterization of Total and Regional Deposition
of Therapeutic Aerosols in the Respiratory System
Imre Balásházy, Bálint Alföldy,
Andrea J. Molnár, Werner Hofmann, István and
Erika Kis
[Full
text article]
The intake of medicines in form of aerosols is becoming increasingly
popular, especially in the treatment of different lung diseases
and allergies. In addition, there is a great interest to utilize
the inhalation pathway for systemic therapy. Hence, determination
of the required local distribution of inhaled therapeutic
aerosols within the respiratory system is a key issue of modern
aerosol drug design. In general, deposition characteristics
of inhaled particles depend on the properties of the aerosols,
the breathing mode and the geometry of the airways. All three
parameters must be analyzed for the optimal design of therapeutic
aerosols. A recommended way of drug inhalation may differ
for various illnesses and patients. There are two different
modeling directions for the description of deposition characteristics
of inhaled drugs in the respiratory system. One way is the
application of lung deposition models for the determination
of total, regional and airway generation-specific deposition,
and the other way is the usage of computational fluid dynamics
techniques for the characterization of local deposition patterns,
which, at present, cannot be applied to the whole respiratory
system. This computational fluid dynamics approaches will
be analyzed in another study. This work describes the general
background of aerosol drug delivery optimization, summarizes
previous important studies in the field, and provides a comprehensive
discussion about numerical lung modeling and the salient features
of the newest models and techniques. In the last part, the
stochastic lung deposition model is applied to determine the
optimal particle size and breathing technique for bronchial
and pulmonary drug delivery.
[Back to top]
Acceleration of the Drug Discovery Process: A Combinatorial
Approach Using NMR Spectroscopy and Virtual Screening
Xavier Morelli and Alan C. Rigby
[Full
text article]
The continued implementation of NMR-based approaches in hit-through-lead
drug discovery in academic and corporate settings is founded
upon NMR applications that assess structure activity relationships.
A very recent application of NMR spectroscopy to these discovery
initiatives involves fraganomics, in which NMR is used to
iteratively “guide” the assembly of several weakly
interacting fragments or small molecules through chemical
links. Moreover, several groups have recently reported the
potential of integrating NMR spectroscopy with in silico,
virtual screens of large chemical repositories possessing
diverse collections of small molecules. Importantly an improved
understanding of the intermolecular forces that mediate protein-protein/
protein-ligand interactions has been integral to improving
these virtual screening approaches, resulting in the identification
of novel ligands for several therapeutic targets. Recent success
of these structure-based discovery initiatives in targeting
protein-protein interactions that are responsible for the
non-covalent assembly and/or regulation of macromolecular
complexes and are a critical paradigm in many disease pathologies
will be discussed. The atomic details of these requisite interactions
are the cornerstone of NMR and crystallographic “structure-guided”,
drug discovery initiatives aimed at disrupting complex formation.
This review will predominantly focus on the recent advances
in structure based computational screening approaches, highlighting
the successful integration of in silico virtual screens
with NMR-based techniques. The application of this powerful,
combinatorial approach for the evaluation of well-characterized
target space as well as its application to unique chemical
space such as the protein-protein interaction inhibition (2P2I)
that has recently been shown to be tractable to small molecule
intervention will be discussed.
[Back to top]
Inhibitors of Protein-Protein Interactions as Potential
Drugs
Alexander V. Veselovsky and Alexander I. Archakov
[Full
text article]
Protein-protein interactions play a crucial role in numerous
vital cell functions. However proteinprotein interactions
are also responsible for pathological formation of protein
aggregates, which determine the development of several diseases.
The key role of protein-protein interactions for manifestation
of numerous cell functions attracts much attention to protein
complexes as perspective drug targets. So design or discovery
of small molecules that would regulate protein-protein interactions
represents great pharmacological interest. The recent progress
in understanding of mechanism protein-protein interaction,
including role of flexibility of protein-protein interfaces,
thermodynamic of complex formation, discovery of small molecules
modifying protein-protein interactions, the advantages and
limitation of protein-protein inhibitors as potential drugs
are discussed in this review.
[Back to top]
Substructural Analysis in Drug Discovery
Hugo O. Villar, Mark R. Hansen and Richard Kho
[Full
text article]
The dominant paradigm in drug discovery emphasizes techniques
that generate large amounts of data. What was possible by
simple inspection in the past, nowadays cannot be effectively
achieved without the aid of informatics techniques. In this
context substructural analysis techniques are increasing their
role in the organization and management of information generated.
Advances in the field of substructure analysis have expanded
the applicability of substructural analysis in multiple fronts
in early lead discovery and optimization. It can be applied
beyond the management of information, including compound library
design and virtual screening to structure activity relationships.
The relationships between chemical substructures and drug-like
properties also aid in developing more robust rationales for
fragment-based approaches for lead discovery, predictive toxicology,
and elucidation of pharmacokinetic properties.A review of
recent developments in substructure analysis in a broad range
of areas in drug discovery is presented. The focus is on the
application of substructural analysis in computational chemistry
for drug design and the methods used to identify substructures
in a chemical database, as well as their relation to fragment-based
drug discovery. The discussion shows the benefits of substructural
analysis to the drug discovery process and gives impetus to
further advancement of substructure analysis techniques.
[Back to top]
Computational Approaches for Fragment Optimization
Eric Vangrevelinghe and Simon Rüdisser
[Full
text article]
Fragment based screening has become a valuable tool to complement
traditional lead finding methods like high throughput screening
in drug discovery. Fragments are low molecular mass compounds
and are usually screened using high sensitivity biophysical
methods which are suitable for the detection of weakly binding
ligands. Because fragments have a low affinity, efficient
methods to improve their affinity are required. Structure
based methods, i.e. methods which make use of a three
dimensional structure of the protein have been applied in
most of the cases for fragment optimization programs which
are reported in the literature. De novo design, combinatorial
docking and interactive optimization fell in this category
and belong to the computer-aided drug design field. While
de novo design is a computational method where a
ligand is build completely de novo, combinatorial
docking is applied to evaluate easily accessible or physically
existing compound libraries around a previously identified
core and interactive optimization alternates computational,
biological and structural experiments to progress towards
a drug. The principles, advantages, drawbacks of the different
methods are being discussed together with examples of applications
taken from the literature. At the end of the article we define
a new metric to express the efficiency of optimization and
show that small molecular molecules, i.e. fragments
with a molecular mass below 250 Da, tend to be more easily
optimized than larger molecules, thus reinforcing the interest
of the fragment approach in the drug discovery process.
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