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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