Biomedical Engineering Reference
In-Depth Information
their best relative position. However, the correct representation of electrostatic and
non-electrostatic energies as well as entropic contributions in the overall scoring cost
function is not fully established.We target both the configurational as well as the ener-
getic surface analysis, since the optimal protein-ligand interaction is not determined
solely by one or the other but by a complex interplay between energetic stabilization
and configuration selection. The initial parameterization will be done on systems for
which the real positions of ligand and protein are known from experimental results
in the Protein Data Bank (PDB) [28].
Tools such as Nimrod greatly facilitate carrying out procedures such as described,
as they can manage the rather large set of individual calculations that one would like
to do to obtain the most accurate and thorough results. Furthermore, apart from exist-
ing parameter sweeping and objective parameter optimization facilities in Nimrod
/
G
and Nimrod
/
O, recently an interactive subjective optimization algorithm was imple-
mented into the Nimrod Toolkit (
Nimrod/OI
). An objective cost function can thus
be applied to monitor the energetics associated with the protein-ligand interaction
in any particular molecular configuration of the ligand docked into the protein, and
a subjective cost function to monitor the steric and overall configuration details in
terms of special parameters. The subjective optimization procedure needs direct user
intervention and decisions, and therefore, requires the use of a visualization tool, for
which we plan to invoke our QMView [8] molecular computation and analysis tool.
As such, our particular docking protocol requires executing two major com-
putational chemistry or biophysics packages: The GAMESS software, which was
discussed earlier, has just to be the invoked once for each ligand structure, to obtain
its hydrogen positions and atomic charge distribution. Then, the adaptive Poisson-
Boltzmann solver (APBS) [29, 30], a code for biomolecular dielectric continuum
solvation calculations, computes the electrostatic energies of protein, ligand, and
protein-ligand complex in solution for each of their relevant positions, from which
the corresponding binding energies can be determined. However, particularly due to
the complexity of protein structures, a variety of auxiliary tools is also required, to
prepare, manipulate, and analyze the docking calculations such as those to access
the protein data, to set up the GAMESS and APBS input files, to bring the quantum
chemical results into the right format, to assign the molecular force field, to estimate
non-electrostatic contributions, and to visualize the results. A principal methodology
to automate this overall procedure will be introduced in the next chapter.
22.5 COMPUTATIONAL CHEMISTRY WORKFLOW ENVIRONMENTS
Although Nimrod plan files allow the user to construct basic pipelines, there is a
considerable interest in the ability to combine more than one computational code,
to build flexible, complex, and reusable workflows for high-throughput studies on
significant numbers of molecules or with a variety of methods. Recently, we have
begun to develop a “computational chemistry prototyping environment,” which would
enable researchers to design computational experiments which span multiple com-
putational and analytical models, and in the process, to store, access, transfer, and
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