BIL 511 – Nesnesel Tasarım ve Programlama
Yasemin Seren Demiray
PRINCIPLES OF DOCKING: AN OVERVIEW OF
Ø Docking Algorithms
Ø BiGGER: Predicting Protein Interactions
Ø Prediction of Protein Complexes by an NMR
Ø Scheduling of Receiving and Shipping Trucks in Cross-Docking
Ø ASPDock :Using Atomic Solvation Parameters Model
Ø A fast protein-ligand docking algorithm
Ø Protein-Protein Docking based on Best-First Search Algorithm
Ø Efficient Combinatorial Library Docking Using Recursive Algorithm
Different types of molecular docking methods are used
to study molecular recognition. Using known structures,
molecular docking aims to predict the binding mode and
binding affinity of a complex formed by two or more
One of the important type of molecular dockings is
protein-ligand docking because of its applications in modern
structure-based drug design for many diseases. Protein-
protein interactions play important roles in many biological
processes such as signal transduction, cell regulation, and
other macromolecular assemblies.
In this paper, we review the followings for
predicting protein interactions, structure
prediction of protein complexes:
flexible ligand docking
Due to the difficulties and economic cost of the
experimental methods for determining the structures
of complexes, computational methods such as
molecular docking are desired for predicting putative
binding modes and affinities.
There are two main aspects of a docking
algorithm; scoring or measuring the quality of any
given docked complex, and searching for the highest
scoring or a pool of high quality docking
In addition to this, docking is a term used for
computational schemes that attempt to find the best
matching between two molecules: a receptor and a
ligand. The molecular docking problem can be defined
as follows: Given the atomic coordinates of two
molecules, predict their correct bound association.
Here we attempt to look back on what has been
achieved and to suggest what might be tried in the next
BIGGER: PREDICTING PROTEIN INTERACTIONS
Soft docking is a computationally efficient and
automated docking algorithm which can be used
to predict the mode of binding between two
proteins using the three dimensional structures of
the unbound molecules.
BiGGER (Bimolecular Complex Generation with
Global Evaluation and Ranking) is a software
package where the method is implemented.
BIGGER: PREDICTING PROTEIN INTERACTIO
The docking procedure has two modules.
First module is BoGIE (Boolean Geometric
Interaction Evaluation), a grid-like search algorithm
to generate a population of docked geometries with
maximal surface matching and favorable
intermolecular amino acid contacts.
Second module is the putative binding modes
which are evaluated according to a set of
PREDICTION OF PROTEIN COMPLEXES BY AN NMR
Protein–Protein Docking Problems (PPD
problem) can be formulated as follows:
The 3D structure of two proteins A and B forms a
protein complex AB, the 3D structure of the
complex AB is computed and a variant of the PPD
problem where the input consists of the tertiary
structures of A and B plus an unassigned
experimental 1H-NMR spectrum of the protein
PREDICTION OF PROTEIN COMPLEXES BY AN NMR
One of the important results is that the use
of NMR data can improve the reliability and
accuracy of docking predictions, another is the
new method still needs a more extensive
validation with experimental data.
SCHEDULING OF RECEIVING AND SHIPPING TRUCKS IN CROSS-DOCKING SYSTEMS
Cross-docking system is transferring items directly from
receiving trucks to shipping trucks without being held in
storage at warehouse. An imperialistic competitive algorithm
(ICA) is developed to use in system.
In addition to this, cross-docking system is used to
handle high volume of items in a short time.
As a result of this, cost reduces with decreasing
inventory and efficiency improves by increasing customer
responsiveness and better control of distribution operation.
ASPDOCK :USING ATOMIC SOLVATION PARAMETERS MODEL
One of the most improved docking algorithms is based on Fast
Fourier Transform (FFT) which are widely used and have made great
success. Because they can search 6D space in a very fast way.
Atomic Solvation Parameters (ASP) model is used to calculate
the binding free energy of protein complexes. An FFT-based algorithm
is studied to calculate ASP scores of protein complexes and develop
an ASP-based protein-protein docking method (ASPDock).
We have observed from the results of the ASPDock that it is
more accurate and physical than the pure shape complementarily in
describing the feature of protein docking.
A FAST PROTEIN-LIGAND DOCKING ALGORITHM
At the present day, drug discovery is a
contemporary issue to find improved drugs for human
diseases. Working on hydrogen bond matching and
surface shape complementarity, a fast docking
algorithm (H-DOCK) was developed for this aim. The
aim of the docking procedure in H-DOCK is to
maximize the intermolecular hydrogen bonding and to
avoid large steric hindrance between protein and
A FAST PROTEIN-LIGAND DOCKING ALGORITHM
The flowchart of the H-DOCK algorithm is
PROTEIN-PROTEIN DOCKING BASED ON BEST-FIRST SEARCH
Protein-protein docking method developed
based on Best-First search algorithm which is
used for imitating protein-protein interactions.
The method consists of two stages:
The first stage is that performs a rigid search on
the unbound proteins.
Second stage is searching alternately on rigid and
flexible degrees of freedom starting from multiple
configurations from the rigid search.
EFFICIENT COMBINATORIAL LIBRARY DOCKING USING RECURS
In this method how the structure of combinatorial
libraries can be exploited to speed up docking
predictions were studied using incremental construction
method implemented in the docking software FLEXX.
Because of the relating ligands within the dataset
structurally, to be generated a minimal tree structure
representing the whole ligand dataset and to be
speeded up conformational searching based on
clustering similar molecules. In both cases, the derived
hierarchy of molecules can then be used in an
incremental construction docking method.
Because of the protein flexibility, which has only been
addressed recently because of the difficulty resulting from the
enormous degrees of freedom and the limitation of the
computing power, computational molecular docking problem is
far from being solved.
Nevertheless, despite the drawbacks in each docking
strategy, significant progress has been made. Algorithms have
been remarkably successful especially in addressing the
protein–protein docking problem.
Computational generation of protein structures and the
docking of modeled protein structures with potential interacting
partners will have great impact on the life sciences.
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