Molecular
Recognition
Molecular Recognition by b-Cyclodextrin
Derivatives: FEP vs MM/PBSA Study Pp. 605-611
I. Beà, E. Cervelló, P.A. Kollman and C. Jaime
The Linear Interaction Energy Method for
Predicting Ligand Binding Free Energies Pp. 613-626
Johan Åqvist and John Marelius
Comparative Binding Energy (COMBINE)
Analysis of Human Neutrophil Elastase Inhibition by Pyridone-containing
Trifluoromethylketones Pp. 627-642
Carmen Cuevas, Manuel Pastor, Carlos Pérez and Federico Gago
Automatic Procedures for Protein Design
Pp. 643-659
Alfonso Jaramillo, Lorenz Wernisch,
Stephanie Héry and Shoshana J. Wodak
An Evolutionary Approach for Structure-based
Design of Natural and Non-natural
Peptidic Ligands Pp. 661-673
Nicolas Budin, Shaheen Ahmed, Nicolas Majeux
and Amedeo Caflisch
Conformation and Dynamics of Normal and
Damaged DNA Pp. 675-706
Edward L. Rachofsky, J. B. Alexander Ross and Roman Osman
High-speed Molecular Mechanics Searches for
Optimal DNA Interaction Sites Pp. 707-717
Ingrid Lafontaine and Richard Lavery
BindingDB: A Web-Accessible Molecular
Recognition Database Pp. 719-725
Xi Chen, Ming Liu and Michael K. Gilson
Gene Assessment and Sample Classification
for Gene Expression Data Using a Genetic Algorithm/k-nearest Neighbor
Method Pp. 727-739
Leping Li, Thomas A. Darden, Clarice R.
Weinberg, A. J. Levine and Lee G.
Pedersen
[Back to top] Molecular Recognition by b-Cyclodextrin
Derivatives: FEP vs MM/PBSA Study
I. Beà, E. Cervelló, P.A. Kollman and C. Jaime
The complexation
of p-tert-butylphenyl p-tert-butylbenzoate, N-(p-tert-butylphenyl)-p-tert-butylbenzamide
and a bisadamantyl-phosphate derivative with a b-cyclodextrin
derivative formed by two cyclodextrin units linked by a disulfide bridge on one
of the C6 atoms have been studied by computational methods (free energy
perturbation (FEP) and Molecular Mechanics/Poisson Bolzmann Surface Area
(MM/PBSA)). The calculated relative free energies of the amide and ester are in
good agreement with experiment only for MM/PBSA and not for FEP. Only MM/PBSA
was applied to the bisadamantyl-phosphate complex and its calculated
association free energy was calculated to be similar to that of the ester,
which is consistent with the experimental tendencies.
[Back to top] The Linear Interaction Energy Method for Predicting Ligand Binding Free Energies
Johan Åqvist and John Marelius
An overview of the
simplified linear interaction energy (LIE) method for calculation of ligand
binding free energies is given. This method is based on force field estimations
of the receptor-ligand interactions and thermal conformational sampling. A
notable feature is that the binding energetics can be predicted by considering
only the intermolecular interactions between the ligand and receptor. The
approximations behind this approach are examined and different parametrizations
of the model are discussed. In general, LIE type of methods appears
particularly useful for computational drug lead optimization.
[Back to top] Comparative
Binding Energy (COMBINE) Analysis of Human Neutrophil Elastase Inhibition by
Pyridone-containing Trifluoromethylketones
Carmen Cuevas, Manuel Pastor, Carlos Pérez and Federico Gago
The complexes of
human neutrophil elastase with a series of 40 N3-substituted
trifluoromethylketone-based pyridone inhibitors have been modelled. The series
spans three orders of magnitude in inhibition constants despite the fact that
it was originally developed in an attempt to improve the oral activity of a
lead compound. Ligand-receptor interaction energies calculated using molecular
mechanics did not correlate well with the experimental activities. A good
correlation with activity was found, however, when a COMBINE analysis of the
same data was carried out, which allowed a quantitative interpretation of the
modelled complexes. The essence of this method is to partition the
ligand-receptor interaction energies into individual residue-based van der
Waals and electrostatic contributions, and to subject the resulting energy
matrix to partial least squares analysis. Incorporation of two additional
descriptors representing the electrostatic energy contributions to the partial
desolvation of both the receptor and the ligands improved the QSAR model, as
did the replacement of the distance-dependent electrostatic contributions with
solvent-screened electrostatic interactions calculated by numerically solving
the Poisson-Boltzmann equation. The model was validated both internally
(cross-validation) and externally, using a set of twelve
6-phenyl-pyridopyrimidine analogs. The analysis reveals the subtle interplay of
binding forces which occurs within the enzyme active site and provides
objective information that can be interpreted in the light of the receptor
structure. This information, gained from a series of real compounds, can be
easily translated into 3D real or virtual database queries in the search for
more active derivatives.
[Back to top] Automatic Procedures for Protein Design
Alfonso Jaramillo, Lorenz Wernisch,
Stephanie Héry and Shoshana J. Wodak
This review
describes computational procedures for deriving the amino acid sequences that
are compatible with a given protein backbone structure. Such procedures can be
used to gain insight into the constraints imposed by the 3D structure of the
protein sequence, or to design proteins that are likely to adopt a given
backbone conformation. We start by presenting a short overview of the various
types of approaches to protein design developed over more than a decade. This
is followed by a more detailed presentation of a recently developed sequence
selection procedure DESIGNER. This latter presentation illustrates the basic
principles underlying this type of procedures, described what they may teach us
when applied to small proteins, and highlights issues that need to be addressed
in order to go forward.
[Back to top] An Evolutionary Approach for
Structure-based Design of Natural and
Non-natural Peptidic Ligands
Nicolas Budin, Shaheen Ahmed, Nicolas Majeux
and Amedeo Caflisch
A new
computational approach (PEP) is presented for the structure-based design of
linear polymeric ligands consisting of any type of amino acid. Ligands are
grown from a seed by iteratively adding amino acids to the growing construct.
The search in chemical space is performed by a build-up approach which employs
all of the residues of a user-defined library. At every growing step, a genetic
algorithm is used for conformational optimization of the last added monomer
inside the binding site of a rigid target protein. The binding energy with
electrostatic solvation is evaluated to select sequences for further growing.
PEP is tested on the peptide substrate binding site of the insulin receptor
tyrosine kinase and farnesyltransferase. In both test cases, the peptides
designed by PEP correspond to the sequence motifs of known substrates. For
tyrosine kinase, tyrosine residues are suggested at position P and P+2. While
the tyrosine at P is in agreement with the experimental data, the one at P+2 is
a prediction which awaits experimental validation. For farnesyltransferase, it
is shown that electrostatic solvation is necessary for the correct design of
peptidic inhibitors.
[Back to top] Conformation and Dynamics of Normal and Damaged DNA
Edward L. Rachofsky, J. B. Alexander Ross and Roman Osman
The genetic
information that determines the structure and function of living organisms is
encoded in the nucleotide sequence of double-stranded DNA molecules. Despite an
apparent structural homogeneity displayed by DNA, subtle local variations in
structure and dynamics are functionally significant. Short sequences exhibit
specificity for regulatory and catalytic proteins, which mediate fundamental
processes necessary to the survival of the cell. However, the molecular basis
for specific recognition is still incompletely understood. The "indirect
readout" mechanism suggests that the relative propensity of DNA to undergo
structural deformations induced by the protein contributes to specific
protein-DNA recognition. Although the hypothesis was originally formulated to
explain recognition of specific nucleic acid sequences by DNA-binding proteins,
it may have particular application to the recognition of DNA damage, because
damaged sites in DNA have different equilibrium structure and dynamics from
undamaged DNA. In this work, we review the approaches that we took to
investigate the questions of sequence- and damage-dependent structure and
dynamics of DNA.
We describe a
statistical thermodynamic model that relates DNA configurational flexibility to
sequence-specific protein-DNA binding. The model provides a theoretical basis
for interpreting experimental measurements of DNA dynamics. We describe results
from MCSCF calculations of the excited states of 2-aminopurine (2AP), which
provide the theoretical basis for the intramolecular mechanism of quenching as
well as the effect of environment on this process. We then describe our
investigations of the effect of stacking, base pairing, and base dynamics on
the fluorescence of 2-AP in model systems, which allow us to develop the
relationships between steady-state and time-resolved fluorescence parameters on
the one hand and local structural and dynamic properties of DNA on the other
hand. Finally, we describe the application of the experimental approach to
study the conformational heterogeneity of DNA abasic sites, a commonly
occurring type of DNA damage. We demonstrate the power of the experimental
algorithm to characterize the physical differences between undamaged and
damaged DNA, as well as the effects of nucleic acid sequence in both of these
contexts. Thus, the work described herein comprises a combination of
theoretical and experimental approaches to the problem of sequence- and
damage-dependent DNA deformation.
[Back to top] High-speed Molecular Mechanics Searches for Optimal DNA Interaction
Sites
Ingrid Lafontaine and Richard Lavery
We have recently
developed a theoretical means of studying the mechanical and interaction
properties of nucleic acids as a function of their base sequence. This
approach, termed ADAPT, can be used to obtain the physical properties of
millions of base sequences with only modest computational expense. ADAPT is
based on a multi-copy algorithm using special nucleotides ("lexides")
containing all four standard bases whose contribution to the energy of the
molecule can be varied. We present here a deeper study of the energy minima
which occur in the multi-dimensional space defined by these variable sequences.
We also present an extension of the approach termed "gene threading"
which enables us to scan genomic sequence data in an attempt to locate
preferential binding sites. This technique is illustrated for the case of
TATA-box protein binding. ADAPT enables us to demonstrate that, for this
protein, DNA deformation alone explains a large part of the experimentally
observed consensus binding sequence.
[Back to top]
BindingDB: A Web-Accessible Molecular Recognition Database
Xi Chen, Ming Liu and Michael K. Gilson
This paper
presents an initial description of the BindingDB, a public web-accessible
database of measured binding affinities for various molecular types
(http://www.bindingdb.org). The BindingDB allows queries based upon a range of
criteria, including chemical similarity or substructure, sequence homology,
numerical criteria (e.g. DGo<
5 kcal/mol) and reactant names (e.g. "lysozyme"). Principles of
Human-Computer Interactions are being employed in creating the query interface
and user-feedback is being solicited. The data specification includes
significant experimental detail. A full dictionary has been created for
isothermal titration calorimetry data in consultation with experimentalists and
data dictionaries for enzyme-inhibition and other measurement techniques are
being developed. Currently, the BindingDB contains several data sets of broad
interest, such as antigen-antibody binding and cyclodextrin/small-molecule
binding. However, it is anticipated that online deposition by experimentalists
will ultimately contribute a larger flow of data. We are actively developing
software and file specifications to facilitate such deposition.
[Back to top]
Gene Assessment and Sample Classification for Gene Expression Data Usinga
Genetic Algorithm/k-nearest Neighbor Method
Leping Li, Thomas A. Darden, Clarice R. Weinberg,
A. J. Levine and Lee G. Pedersen
Recent tools that analyze microarray expression data have exploited correlation-based approaches such as clustering analysis. We describe a new method for assessing the importance of genes for sample classification based on expression data. Our approach combines a genetic algorithm (GA) and the k-nearest neighbor (KNN) method to identify genes that jointly can discriminate between two types of samples (e.g. normal vs. tumor). First, many such subsets of differentially expressed genes are obtained independently using the GA. Then, the overall frequency with which genes were selected is used to deduce the relative importance of genes for sample classification. Sample heterogeneity is accommodated; that is, the method should be robust against the existence of distinct subtypes. We applied GA/KNN to expression data from normal versus tumor tissue from human colon. Two distinct clusters were observed when the 50 most frequently selected genes were used to classify all of the samples in the data sets studied and the majority of samples were classified correctly. Identification of a set of differentially expressed genes could aid in tumor diagnosis and could also serve to identify disease subtypes that may benefit from distinct clinical approaches to treatment.