Introduction al. 2008). The continuous use of


The pesticides have facilitated the development and
also expansion of agriculture in world wide. Organophosphate belong to a class
of highly toxic neurotoxins that are commonly used as pesticides and chemical
warfare agent (Surekha Rani et al. 2008).
The continuous use of organophosphate in intensive quantity throughout the
world and their potential neurotoxicity to humans has wind to the development
of various efficient and safety scheme of bioremediation to plenty with their
wide dispersal in the ecosystem (Cho et al. 2002). Enzymatic degradation by
organophosphorus hydrolase (OPH) has received considerable attention. This
attention provides the possibility of both eco friendly and in situ
detoxification (Catherine et al. 2002). The focussing of this study is
organophosphorus hydrolase (OPH, E.C., which catalyzes the hydrolysis
of many organophosphorus compounds and highly reduces the toxicity of organophosphate
pesticide and it can completely mineralize the organophosphate componds.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!

order now

The OPH enzyme was coded by opd gene, were found
in two soil microorganisms namely Pseudomonas diminuta MG and Flavobacterium
sp. (Sethunathan et al. 1998). OPH hydrolyzes a wide range of
organophosphate compounds and the effectiveness of hydrolysis varies
dramatically for differnt compounds like widely used organophosphorus
insecticides methyl parathion, chlorpyrifos, and diazinon are hydrolyzed slowly
than 30 to 1,000 times is the preferred substrate, paraoxon (Cho et al. 2002).
The catalytic rate is reduced due to the unfavorable interaction of these
substrates with the active sites involved in catalysis and structural functions
(Zheng et al. 2013).

A number of enzymes are capable of hydrolysing a
number of organophosphate triesters into less or non-toxic compounds. OPH is
capable of hydrolyzing the P–S bond of phosphonothioate esters. This enzyme are
possible bioremediator because of their ability to decontaminate OP-containing
waters and soils (Zheng et al. 2013). The most thoroughly characterized
phosphotriesterases have been isolated from Flavobacterium sp. ATCC
27551, Pseudomonas diminuta (OPH) and Agrobacterium radiobacter (OpdA)
(Fernanda et al. 2010). These enzymes belong to the binuclear metallohydrolase
family and share high sequence and structural homology. Phosphotriesterases are
highly promiscuous enzymes, hydrolysing a large range of substrates. The
phosphotriester hydrolysis by OPH has been studied extensively (Castro et al. 2016).
In a proposed reaction scheme, based on largely crystal structures with bound
inhibitors, the phosphoryl oxygen of the substrate binds to the ?-metal
ion (Janet et al.2005; Laothanachareo et al. 2008).

In the present research focuses on the interaction
and degradation of chlorpyrifos by OPH enzyme, as this is responsible for
detoxification. The molecular docking study was conducted under FlexX docking
software package.

Materials and methods

Isolation and identification of
organophosphate hydrolase (OPH) producers

potential organophosphate hydrolase
(OPH) producing Pseudomonas stutzeri
MCAS01 (Kavitha et al. 2016) has been used
in this study.

Sequence and template search for
homology modeling

Pseudomonas stutzeri
organophosphate hydrolase (OPH), 3D structures are not available in Protein
Data Bank (PDB) database, the homologous sequences for building the 3D
structure was searched against PDB using NCBI BLAST (Basic Local Alignment
Search Tool) (Altschul et al.1990). The
homologous sequences are ability template structure for homology modeling. The
atomic coordinate report of the template structure was obtained from the PDB
(Berman et al. 2000).

Comparative modeling and model

atomic coordinate file of the template along with the target and template final
sequence alignment file was used to build the model using the automated
homology modeling tool MODELER 9v9 (Eswar et al. 2006).
A bundle of models from the random generation of the starting structure was
calculated and among the generated models, the best model with the least Root
Mean Square Deviation (RMSD) value was selected by superimposing the model with
its template (Maiti et al. 2004). This model
was used for further analysis after subjecting it for energy minimization using
GROMOS of Swiss PDB viewer (Walter et al.1999).
The quality of the generated model was assessed by checking the stereo chemical
parameters using PROCHECK (Laskowski et al. 1993),
Verfiy3D (Bowie et al. 1991; Luthy et al.1992) and ERRAT at SAVES server
(Colovos et al. 1993).

Computational details

                All computations were carried
out on an Intel  Core  i3-3240 @ 3.40GHz capacity  processor 
with  a memory of 8GB RAM running
on windows 7 operating system. Finally docking studies were done using theFlexX
docking software package ( For the improvement and
binding energy calculations, the default settings of FlexX LeadIT were used.

Target proteins and ligands

                Protein structure were
downloaded from PDB (PDB id: 3F4D) (Fig. 2)
(Hawwa et al. 2009) and the ligand structure
were obtained from pubchem (Pubchem CID: 2730) (Fig. 1) and the functional
information of these proteins were retrieved from the Uniprot. Further,
hydrogen atoms, bond orders and formal charges were added using the protein
preparation wizard of the FlexX LeadIT tools as described.

Protein and ligand preparation

                PDB files of proteins and
ligands were prepared using FlexX LeadIT protein and ligand preparation wizard
and then binding pockets were set using the individual wizard. The interactions
of the ligand with the protein residues in the binding site were visualized.



Proteins and ligand interactions were calculated. A
cut-off of 1.5 to 3Å distance between the donor and acceptor were used for the
calculation of hydrogen bonds. All the positive docked sites were generated.




Sequence analysis

organophosphate hydrolase enzyme producing bacterial strain was identified as Pseudomonas stutzeri through 16s rRNA
gene sequence analysis (Kavitha et al. 2016).
Sequenced amplicon has been submitted to NCBI database and accession number was
obtained KT757902. The organophousphorus
hydrolase gene (opd) was sequenced and submitted to the NCBI and the accession
number was MG739657. Based on the above information the organophosphate
hydrolase sequences were retrieved from PDB for homology modeling. The BLASTP
search for target sequences of organophosphate hydrolase from P. stutzeri against the PDB database
resulted that crystal structure of organophosphate hydrolase was got.


Homology modeling

The 3D structure of organophosphate hydrolase from Pseudomonas stutzeri was developed by
the X-ray structure. Modeler 9v9 was used to develop the 3D structure by
providing the alignment file, template file, and target file. The alignment
file was adjusted by taking into the account of overlap between the secondary
structure elements of the template and the predicted secondary structure
profile of the sequence. Further, considering the parameter provided for a
number of the model to be calculated as five, modeler provided five initial models
of cellulose by using random generation and by applying spatial resistance.
These generated models were superimposed with a template structure to reveal
the degree of modeled structure with the template by calculating the Root Mean
Square Deviation (RMSD). The modeled and energy minimized structure of
organophosphate hydrolase from P.
stutzeri was shown in cartoon representation with group color using rasmol
visualization tool (Fig. 2).


orientation and interaction

orientation of ligand is important for acceptor binding activity. Clearly,
binding orientation of chlorpyrifos model compounds inside the organophosphate
hydrolase highly varied
as can be seen from Fig. 4, which suggested the performance of organophosphate
hydrolase in catalysis
for the degradation of chlorpyrifos model compounds was different. The
interaction energies were analyzed in detail (Table 1).
When making comparisons between these complexes, the most noticeable difference
was the interaction energy. Their interaction energy changed 1 in a wide range.
This means that H-bonds were an alternative way to determine the interaction of
hydrolase with
chlorpyrifos. Hydrophobic interaction seemed to be a more important factor for
the binding of organophosphate hydrolase to chlorpyrifos model compounds than
H-bonds, because all chlorpyrifos model compounds formed hydrophobic
interactions with organophosphate hydrolase (Fig. 3).
We observed local differences in the types of amino acid residues participated
in hydrophobic interactions. These results showed that hydrophobic interactions
were necessary for the binding of organophosphate
hydrolase to
chlorpyrifos model compounds, and thus were potentially important to
chlorpyrifos degradation.



technology is becoming more and more attractive for environmental remediation
due to its environmentally friendly nature. An organophosphate hydrolase-based
application for chlorpyrifos pesticide degradation is a good example (Singh, 2009). To increase the chlorpyrifos-degrading
efficiency of organophosphate hydrolase, previous studies investigated the
impact of substrate structure on organophosphate hydrolase-mediated oxidation
rate, the stability of bacterial organophosphate hydrolase, using chlorpyrifos
as a model compounds (Fernanda et al. 2010). The chlorpyrifos-degrading efficiency
of organophosphate hydrolase was largely related to the properties of enzyme
and substrates, such as their binding property. The stability and catalytic
activities of organophosphate hydrolase was potentially influenced by the
binding modes between it and its substrates. However, the detailed interaction
mechanism between organophosphate hydrolase and chlorpyrifos is still unclear,
limiting organophosphate hydrolase application in chlorpyrifos degradation to
some extent. Thus, the illustration of interaction between organophosphate
hydrolase and chlorpyrifos model compounds is important. Molecular simulations
such as molecular docking have proved to be a robust technology for the analyses
of intermolecular interactions (Ramalha et al. 2016).
This article performed an investigation of the molecular basis of
organophosphate hydrolase for chlorpyrifos degradation, using molecular
docking. We showed that the present protocol was capable of giving a molecular
insight into the interaction of organophosphate hydrolase with chlorpyrifos
model compounds, and in this way we found several rules that may be important
to chlorpyrifos degradation, this also states by Jin et al. (2015) Molecular Dynamics
Simulations of Acylpeptide Hydrolase Bound to Chlorpyrifosmethyl Oxon and
Dichlorvos. It was showed
that chlorpyrifos model compounds bound to organophosphate hydrolase by a wide
range of interaction energies. Therefore, we proposed that H-bonds were
alternative, but hydrophobic contacts were necessary to the interaction of
organophosphate hydrolase with chlorpyrifos model compounds or chlorpyrifos
this also confirmed by Castro et al. (2016).
Mean backbone RMSD values for different complexes varied (Lima et al. 2016). It not only meant stable behavior of these
complexes, but also indicated that the stability was different between various


extended binding analysis was done after docking the Chlorpyrifos against the
targeted protein. The models created by docking compounds against target
proteins were analyzed and the interactions, hydrogen bonds and distance. Chlorpyrifos
efficiently binds to the target protein organophosphate hydrolase with the
formation of three hydrogen bonds with residues Asp53, Lys54 and yielded a
binding affinity of -5.9124 kcal/mol. Therefore, the present study provides dynamic and structural information on
the interaction mechanism between organophosphate hydrolase and chlorpyrifos,
being useful to develop new organophosphate hydrolase with high
chlorpyrifos-degrading ability for the prevention of pollution in the soil and  provide an ecofriendly environment.