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Current
Pharmaceutical Design
ISSN: 1381-6128
Current Pharmaceutical Design
Volume 12, Number 17, 2006
Contents
Computational Applications in Medicinal Chemistry
Executive Editor: Stefano Moro
Editorial Pp. 2065-2066
Large-Scale Prediction of Protein Structure and Function from
Sequence Pp. 2067-2086
S.C.E. Tosatto and S. Toppo
[Abstract]
Structural Biology and Drug Discovery Pp.
2087-2097
G. Scapin
[Abstract]
Molecular Descriptors and Methods for Ligand Based
Virtual High Throughput Screening in Drug Discovery Pp.
2099-2110
A. Pozzan
[Abstract]
Recent Developments of the Chemistry Development Kit (CDK)
-An Open-Source Java Library for Chemo- and Bioinformatics
Pp. 2111-2120
C. Steinbeck, C. Hoppe, S. Kuhn, M. Floris, R.
Guha and E.L. Willighagen
[Abstract]
Development, Validation, and Applications of Anisotropic
Polarizable Molecular Mechanics to Study Ligand and Drug Receptor
Interactions Pp. 2121-2158
N. Gresh
[Abstract]
In Silico Approaches Towards the Understanding
of the Structure Function Relationships in Metabotropic Glutamate
Receptors (mGluRs) and other Family C GPRCs Pp. 2159-2173
G. Costantino
[Abstract]
Ligand-Based Homology Modeling as Attractive Tool
to Inspect GPCR Structural Plasticity Pp. 2175-2185
S. Moro, F. Deflorian, M. Bacilieri and G. Spalluto
[Abstract]
Abstracts
[Back
to top]
Editorial
Computational Applications in Medicinal Chemistry
The very foundations of drug discovery research are being
rapidly transformed by high throughput systems, automated
assays, robotics and advanced computational applications in
medicinal chemistry. Costs are dropping, the time to complete
a cycle of discovery and compound characterization is lessening,
and all the while the ability to assess a compound's possible
therapeutic role is improving. Indeed, the drive to increase
the speed and efficiency of drug discovery, from hit identification
all the way through to the creation of development candidates
has seen huge investments by major pharmaceutical companies
in many new technologies, with the primary aim of synthesizing
more compounds and screening them faster; all at reduced cost
per compound or assay.
Nowadays, computational medicinal chemistry brings together
the most powerful concepts in modern chemistry, biology and
pharmacology, linking medicinal chemistry with genomics and
proteomics.
However, following our experience, both ligand-based and structure-based
approaches to drug discovery in the absence, but probably
also in the presence, of the real 3D-structures require a
multidisciplinary approach, where molecular models represent
a structural context to efficiently integrate experimental
data and inferences derived from molecular biological, biophysical,
bioinformatic, pharmacological and organic chemical methods.
Although not always achievable, the success of a synergistic
effect among these disciplines is highly dependent on the
experimental design. Synergy is best achieved when mutations
are structurally interpretable, structural hypotheses are
experimentally testable, ligands are well characterized pharmacologically,
and the necessary chemical modifications of the ligands are
feasible.
The present edition opens with the interesting report by Silvio
Tosatto and Stefano Toppo [1] on the large scale prediction
of protein structure and function from primary sequence obtained
by the state of art chemioinformatics methodologies. This
is an instance of a likely future contribution of bioinformatics
research towards an improvement in the druggable target structure
and function prediction.
Giovanna Scapin [2] recalls the crucial role of macromolecular
crystallography in structural determination and structural-based
drug design (SBDD) approach. This process has been aided by
recent technological innovations such as high-throughput crystallization,
high performance synchrotron beamlines, and new methods in
structural bioinformatics and computational chemistry prompted
by the structural genomics effort.
Alfonso Pozzan [3] updates the role of molecular descriptors
and methods for ligand based virtual high throughput screening
in drug discovery.
Christoph Steinbeck, Christian Hoppe, Stefan Kuhn, Matteo
Floris, Rajarshi Guha and Egon L. Willighagen [4] deal with
the potentiality of Java applications in molecular informatics.
The Authors outline the perspective to develop chemoinformatics
tools, such as Chemistry Development Kit (CDK), with the aim
to speed up the drug discovery process.
Nohad Gresh [5] reports about the development, validation,
and applications of anisotropic polarizable molecular mechanics
to study ligand and drug-receptor interactions. In fact, considering
molecular docking one of the most useful application in structural-based
drug design (SBDD) approach, a correct representation of intermolecular
interaction energies is necessary for reliable drug-receptor
docking studies.
Gabriele Costantino [6] introduces the role of in silico approaches
towards the understanding of the structure-function relationships
in metabotropic glutamate receptors (mGluRs) and other family
C GPRCs. The present review will discuss the evolution of
our perception in family C GPCRs structure and function as
emerged from the critical comparison of in silico methods
with molecular biology and crystallographic experiments
Francesca Deflorian, Magdalena Bacilieri, Giampiero Spalluto
and myself [7], address the concept of receptor multi-conformational
state applied to G-protein coupled receptors (GPCRs). Particularly,
we define ligand-based homology modeling as new approach to
simulate the reorganization of the receptor induced by the
ligand binding. Finally, we discuss its possible application
in new GPCR ligand discovery.
References
[1] Tosatto SCE, Toppo S. Large-Scale Prediction of Protein
Structure and Function from Sequence. Curr Pharm Design 2006;
12(17): 2067-2086.
[2] Scapin G. Structural Biology and Drug Discovery. Curr
Pharm Design 2006; 12(17): 2087-2097.
[3] Pozzan A. Molecular Descriptors and Methods for Ligand
Based Virtual High Throughput Screening in Drug Discovery.
Curr Pharm Design 2006; 12(17): 2099-2110.
[4] Steinbeck C, Hoppe C, Kuhn S, Floris M, Guha R, Willighagen
EL. Recent Developments of the Chemistry Development Kit (CDK)
- An Open-Source Java Library for Chemo- and Bioinformatics.
Curr Pharm Design 2006; 12(17): 2111-2120.
[5] Gresh N. Development, Validation, and Applications of
Anisotropic Polarizable Molecular Mechanics to Study Ligand
and Drug-Receptor Interactions. Curr Pharm Design 2006; 12(17):
2121-2158.
[6] Costantino G. In Silico Approaches Towards the
Understanding of the Structure-Function Relationships in Metabotropic
Glutamate Receptors (mGluRs) and other Family C GPRCs. Curr
Pharm Design 2006; 12(17): 2159-2173.
[7] Moro S, Deflorian F, Bacilieri M, Spalluto G. Ligand-Based
Homology Modeling as Attractive Tool to Inspect GPCR Structural
Plasticity. Curr Pharm Design 2006; 12(17): 2175-2185.
Stefano Moro
Molecular Modeling Section
Dipartimento di Scienze Farmaceutiche
Università di Padova
Via Marzolo 5, I-35131 Padova
Italy
E-mail: stefano.moro@unipd.it
[Back to top]
Large-Scale Prediction of Protein Structure
and Function from Sequence
S.C.E. Tosatto and S. Toppo
The identification of novel drug targets from
genomic data involves the large-scale analysis of many protein
sequences. Methods for automated structure and function prediction
are an essential tool for this purpose. In this review we
concentrate on the recent developments in the field of protein
structure prediction and how these can be used to gain hints
about the function of proteins. The current state-of-the-art
is highlighted through recent community-wide experiments aimed
at comparing different approaches. For structure prediction
this allows the identification of key improvements to increase
the crucial sequence to structure alignment needed for accurate
models. Function prediction is a rapidly maturing field that
is still being benchmarked. Definitions for protein function
are presented and available methods, mostly concentrating
on functional site descriptors and structural motifs, presented.
[Back to top]
Structural Biology and Drug Discovery
G. Scapin
In the past few years macromolecular crystallography has become
a standard technique used by many pharmaceutical and biotechnology
companies. This methodology offers details of protein-ligand
interactions at levels of resolution virtually unmatched by
any other technique, and this approach holds the promise of
novel, more effective, safer and cheaper drugs. Although crystallography
remains a laborious and rather expensive technique, remarkable
advances in structure determination and structure based drug
design (SBDD) have been made in recent years. This process
has been aided by recent technological innovations such as
high-throughput crystallization, high performance synchrotron
beamlines, and new methods in structural bioinformatics and
computational chemistry prompted by the structural genomics
effort. As a consequence of the increased availability of
structural data, the use of structure-based information has
expanded from simple protein-ligand interaction analysis to
include other aspects of the drug discovery process like target
selection and initial lead discovery that used to be almost
the exclusive property of biology and chemistry. This review
will cover recent examples to illustrate how macromolecular
crystallography has evolved and how structural information
is now being used in the different stages of the drug discovery
process. Advantages and shortcomings of the methodology will
also be discussed.
[Back to top]
Molecular Descriptors and Methods for Ligand Based
Virtual High Throughput Screening in Drug Discovery
A. Pozzan
The aim of virtual high throughput screening is the identification
of biologically relevant molecules amongst either tangible
or virtual (large) collections of compounds. Amongst the various
virtual screening approaches, those that are ligand based
are becoming very popular due to the possibility to screen
millions of molecules in a timely way. Descriptors and methods
are briefly introduced and reviewed with more emphasis for
those approaches that are based on fingerprint descriptors
and that seems to be more utilized during the drug discovery
process.
[Back to top]
Recent Developments of the Chemistry Development Kit
(CDK) -An Open-Source Java Library for Chemo- and Bioinformatics
C. Steinbeck, C. Hoppe, S. Kuhn, M. Floris, R.
Guha and E.L. Willighagen
The Chemistry Development Kit (CDK) provides methods for common
tasks in mole¬cular informatics, including 2D and 3D rendering
of chemical structures, I/O routines, SMILES parsing and generation,
ring searches, isomorphism checking, structure diagram generation,
etc. Implemented in Java, it is used both for server-side
computational ser¬vices, possibly equipped with a web
interface, as well as for applications and client-side applets.
This article introduces the CDK's new QSAR capabilities and
the recently in¬troduced interface to statistical software.
[Back to top]
Development, Validation, and Applications of Anisotropic
Polarizable Molecular Mechanics to Study Ligand and Drug Receptor
Interactions
N. Gresh
A correct representation of intermolecular interaction
energies is necessary for reliable drug-receptor docking studies.
While ab initio quantum chemistry with extended basis sets
is the most accurate tool for that purpose, its use is precluded
for very large molecular complexes. This constitutes the incentive
for the development of accurate molecular mechanics potentials,
in which the first-order electrostatic, and the second-order
polarization energy contributions, are of essential importance.
In this paper, we review the most important steps in the development
of anisotropic, polarizable molecular mechanics (APMM) procedures.
Among these, we illustrate validation tests of the ab initio-grounded,
polarizable molecular mechanics potential, SIBFA (Sum of Interactions
Between Fragments Ab initio computed). These are done by comparisons
with parallel quantum-chemical (QC) results on representative
multiply hydrogen-bonded complexes and polycoordinated complexes
of one, or of two, divalent metal cations. For both kinds
of complexes, the need to reproduce the non-additivity of
the QC interaction energies is emphasized. One difficulty
arises upon handling flexible molecules, due to the need to
account simultaneously and consistently for the onset of inter-
and intra-molecular polarization and charge-transfer effects.
A new approach in the context of SIBFA was recently developed
towards this aim, and tested in two cases of conformation-dependent
cation-ligand interaction energies. The first relates to the
complexes formed between the mecapto-carboxamide anion, an
essential building-block of several Zn-metalloenzyme inhibitors,
and Zn(II). The second relates to the complexes of the tetra-anionic
pyrophosphate anion, a key building-block of ATP and GTP,
with one or two divalent Zn(II) cations used as a probe. In
the domain of applications, two recent studies are then presented.
The first is the docking of the captopril drug to the active
site of the binuclear Zn(II)- β-lactamase
enzyme. The second is the complex of a non-hydrolyzable analog
of ATP with the active site of a binuclear Mg(II)-dependent
kinase. An extension to an open-shell cation, Cu(II), is finally
presented. The encouraging results presented in this review
show that APMM procedures could be used in large-scale studies
of ligand and drug-receptor interactions.
[Back to top]
In Silico Approaches Towards the Understanding
of the Structure Function Relationships in Metabotropic Glutamate
Receptors (mGluRs) and other Family C GPRCs
G. Costantino
Family C of the superfamily of G-protein coupled receptors
is a growing family of heptahelical receptors, which includes,
among others, metabotropic glutamate receptors (mGluRs) and
GABA(B) receptors. A common feature of all the members of
family C is a structural architecture much more complex than
any other GPCRs. Computational studies, including homology
modeling, pharmacophore definitions and molecular dynamics
simulations have constantly flanked experimental approaches
in the understanding of the receptor functioning. The present
review will discuss the evolution of our perception in family
C GPCRs structure and function as emerged from the critical
comparison of in silico methods with molecular biology
and crystallographic experiments.
[Back to top]
Ligand-Based Homology Modeling as Attractive Tool
to Inspect GPCR Structural Plasticity
S. Moro, F. Deflorian, M. Bacilieri and G. Spalluto
G protein-coupled receptors (GPCRs) represent the largest
family known of signal-transducing molecules. They convey
signals for light and many extracellular regulatory molecules.
GPCRs have been found to be dysfunctional/dysregulated in
a growing number of human diseases and they have been estimated
to be the targets of more than 40% of the drugs used in clinical
medicine today. The crystal structure of rhodopsin provides
the first three-dimensional GPCR information, which now supports
homology modeling studies and structure-based drug design
approaches. Here, we review our recent work on adenosine receptors,
a family of GPCRs and, in particular, on A3
adenosine receptor subtype antagonists. We will focus on an
alternative approach to computationally explore the multi-conformational
space of the antagonist-like state of the human A3
receptor. We define ligand-based homology modeling as new
approach to simulate the reorganization of the receptor induced
by the ligand binding. The success of this approach is due
to the synergic interaction between theory and experiment.
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