Title: SYNERGY CHEMICALS RESEARCH COMPUTING RESEARCH
SUPPORT THE EFFECT OF MOLECULAR SIZE ON ACTIVITIES AND DERIVATIVE AS INHIBITORS
curcumin glutathione S-transferase
With drug design is an iterative process that starts
with a compound menjukkan important biologically active properties and ends
with either optimize the activity profile of molecules and chemical synthesis.
This process can be run if chemists hypothesized a connection with the chemical
structure of a molecule with biological activity. Without detailed knowledge of
biochemical processes will be taken based on the hypothesis strukutur similarities
as well as differences in active and inactive molecules. Alternatives to be
able to optimize the compounds in which dpat diskriptor molecules are easily
predictable nature is used to indicate the nature of computing is used to
indicate the chemical synthesis of compounds useful.
Make an idea become a reality it requires a
sacrifice and the cost is also not small. One is if we are going to make the
drug from a chemical compound to cost about US $ 800 million (DiMasi et al,
2003). A huge cost, especially if linked to the ability of the economy of a
developing country like Indonesia. Effective and efficient strategies
economically indispensable to make Indonesia also observed in drug discovery.
One way that can be used is to use the computer as a
tool in drug discovery. Computing power increases exponentially is an
opportunity to develop simulations and calculations in designing the drug.
Computers provide in silico methods as complementary methods of in vitro and in
vivo commonly used in the drug discovery process. Terminology in silico,
analogue of in vitro and in vivo, referring to the use of computers in the
study of drug discovery.
Reasons pulled using computers is cost efficiency.
With the existence of a computer equipped with an application or software that
supports computational chemistry, computational medicinal chemists experienced
a compound can show three-dimensional (3D) and perform a comparison with other
compounds already known to have high activity. Based on the comparison of 3D is
equipped with the similarity calculation and energy can provide an overview
sections and groups of potential that can be developed from the compounds in
curcumin. Then various derivatives and analogues synthesized in silico or drawn
according to the requirements of computer applications used hereinafter
referred to as the hypothetical compound.
Effect of molecular size on the activity of curcumin
and its derivatives as inhibitors of glutathione S-transferase (GST).
Quantitative structure-activity relationship (QSAR) of curcumin and its derivatives
as inhibitors of glutathione S-transferase (GST) has been studied by using
atomic net charge as a predictor, but the influence of molecular size is not
taken into account in the study. The size of the molecule is closely related to
the steric parameter (Es) which is one of the parameters in QSAR analysis
methods Hänsch. However, the flexibility of conformational changes of drug
molecules and receptor molecules also play a role in the penetration ability of
molecules to the enzyme active site. Therefore, it is necessary to study the
effect of molecular size on the activity of curcumin and its derivatives as
inhibitors of GST.
The purpose of this study was to determine the
effect of molecular size on the activity of the compounds curcumin derivatives
as inhibitors of GST. This research uses molecular size of molecules in the
form of surface area and volume of a molecule which is obtained by using
computational chemistry approaches as independent variables, and the
concentration of inhibitor (curcumin and its derivatives) which produces 50%
inhibition of GST activity (IC50) as the dependent variable.
The size of the molecule as a representation of
steric parameter (Es) is relatively no effect on the activity of curcumin and
its derivatives as inhibitors of GST compared with the electronic parameters.
The relationship between the size of the molecules of curcumin and its
derivatives with activity as an inhibitor of GST tend to quadratic. Optimal
curcumin and its derivatives as inhibitors of GST on compounds that have a
molecular surface area of between 410-460 A2 and or have a molecular volume
between 350-400 A3.
In this case the computer helps to reduce the amount
of the proposed compound rationally and are expected to be more effective and
help to study the interaction of the drug with its target, even the possibility
of the toxic nature of these compounds and their metabolites. Within one year,
Indonesia has to import a tool for structure elucidation extremely rare and
even if there was often not in a usable condition. Tools and even then the
average is only able to report the synthesis of 3 simple compounds. So the role
of computers in this case for developing countries, especially in Indonesia can
be optimized.
There are two methods in computational chemistry
complementary in the use of computers as a tool for drug discovery, namely:
a. Based compound known to bind to a target or
so-called ligands, ligand-based drug designi (LBDD). LBDD utilize information
physicochemical properties of the active compounds as the basis for designing
new compounds. Three methods are commonly used LBDD pharmacophore discovery and
quantitative structure-activity relationship or quantative structure-activity
relationship (QSAR or QSAR), and docking studies. Pharmacophore discovery is
the method of searching for common ground physicochemical properties, among
others, electronic properties, hydrophobic and steric of compounds that are
reported on, and then built a 3D part which combines properties of clusters as
well as parts of a compound believed to be responsible for its activity
(pharmacophore). The QSAR combines statistics with the physicochemical
properties of compounds that can be calculated with the help of computers in
order to derive an equation that can be used to predict the activity of a
compound. If the QSAR equation has been produced then we can design a compound
with specific activities and provide such predictions on scientists to
synthesize the compound synthesis.
b. Based on the structure of both the target either
the enzyme or receptor that is responsible for the toxicity and activity of a
compound in the body or target structure based drug design, structure-based
drug design (SBDD). The structure of the target protein can be modeled from
data obtained crystal structure as well as the results of the analysis of
nuclear magnetic resonance (NMR) and data genomics (bioinformatics). SBDD uses
information from the structure of the target protein for the active side of the
protein that binds to compounds. Based on the prediction of the active
compounds can be designed that are expected to bind to the target protein and
has a biological activity.
With memanfaatan information on the structure and
physicochemical properties of the target ligand interactions can be conducted
screening test compounds which are known active (ligand) in the prediction of
the active protein. Based on information obtained new compound designed to
expect better than existing compounds. It is also used to study the interaction
of the ligand with its target protein. One disadvantage docking studies to
study protein interactions are assuming rigid structure, which does not
facilitate the induced-fit effects of protein interaction with ligand. The
flexibility of proteins and their interaction with a compound can be analyzed
by applying the Molecular Dynamics (MD) simulations are seeing changes in the
structure of a compound over time based on certain parameters.
The main problem for the use of this computer is the
existence of adequate computational chemistry applications and complete. One
application of adequate computational chemistry to drug discovery is the
Molecular Operating Environment (MOE) developed Chemical Computing Group. MOE
addition to offering complete facilities are also user-friendly so suitable for
use in learning. Only computational chemistry applications are user-friendly so
that is usually expensive cost efficiency reasons no longer relevant. For
information, license fees for academic use (non-commercial) of approximately US
$ 2,000 per year. However, in this era of a growing number of applications
based on open source computational chemistry as well as offering free academic
license (Geldenhuys et al., 2006). It's just that these applications are often
not user-friendly and requires the ability to use a better computer, such as
master LINUX-based operating system and command line editor default each
application. Besides being user-friendly, these applications often focus on a
single topic that is not complete enough to use in a comprehensive manner.
With a variety of data synthesis and testing
activities that have been done many researchers who have published both in
Indonesia and internationally as well as protein structure data can be easily
accessed, participated in drug discovery effectively and efficiently by
utilizing CADD is one opportunity that is worth considering for the occupied
more Further.
References:
DiMasi, J.A., et al (2003) The price of innovation:
new estimates of drug development costs. J. Health. Econ., 22, 151-185
Geldenhuys, W,J., et al (2006) Optimizing the use of
open-source software applications in drug discovery. DDT, 11 (3/4), 127-132
Pranowo, Harno .D, 2004, Kimia Komputasi, Pusat
Kimia Komputasi Indonesia- Austria UGM : Yogyakarta
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