dc.description.abstract | This investigation presents novel computer graphical and computational schemes for
solving the challenges of computer-aided drug design (CADD). The application of the
energy minimum to enhance the docking performance of CADD is discussed in terms
of three aspects, geometry, energy and activity. American CDC research reports
reveal that an increasing incurrence of disease, resulting in a requirement to
accelerate drug discovery. However, commercialization of a new drug is extremely
complicated. The most significant challenge is the docking procedure in CADD
according to previous literature. This study applies the energy minimum theorem to
solve the objection. A geometry search is performed and compared with four types in
classification of receptors. This work attempts to improve the speed of computer
simulations of protein folding of protein, and proposes an improved genetic algorithm
to accelerate the binding site search; second, we focused on energy theme.
Lyapunov’s stability theorem is adopted to decrease the number of binding sites, thus
enhancing the docking performance in computer simulation examples. The knot
insertion and modifying weights of NURBS curves are utilized to accelerate the
molecular docking system in order to obtain the shortest response route. Finally,
various drug-ligand interaction models are employed to compute docking simulation,
and energy minimum theorem is used to judge the approach global energy minimum
area and docking stability. Various molecular activities are derived at each binding
site, and the contribution of every bond and non-bond’s in the force field is observed.
As a benchmark is reference for testing docking performances, the error tolerance of
computer simulation examples is compared with the X-ray and RMSD experiment
standard, and the values obtained by Michel, David, Denical and Abraham’s researches performance. This investigation develops the AMBER force field and
Ullman’s algorithm to support the computer simulation environments. The
significance of the eigenvalue λ is analyzed at each protein folding, and this study
performance has increased by 25 percents compared with various binding sites.
Additionally, the protein folding and various bond forces in drug-ligand interaction
model are discussed s. Comparing four optimal geometry search methods and referred
to Pegg and Camila the two been published paper in benchmark of drug docking
database, the improved genetic algorithms are specified to undertake the search
binding site and docking, and the global minimum search and the arithmetic
convergence time of 1.16hr is achieved. Analytical results indicate that the improved
genetic algorithm is better than traditions random methods in terms of processing the
geometry graphics operation.
Previous published investigations have employed the WebDeGrator system to
establish molecular computer modeling for the docking process. This study
demonstrates examples in protein folding kinetics and drug docking computations,
and successfully applies the Lyapunov function and molecular dynamics to help
determine the system stability. Optimal solutions, molecular docking and protein
folding kinetics are also discussed herein. This work integrates various research fields
to find advanced and novel solutions to problems in bioinformatics. The combination
of biology, information, system, and chemistry will be a powerful CADD strategy in
the future. | en_US |