The herbicide residue from intensive agricultural activity provokes environmental disturbances and human health injuries. Among the enzymatic disruptor herbicides, mesotrione is able to inhibit 4-hydroxyphenylpyruvate dioxygenase (HPPD), which plays a key role in the carotenoid synthesis. Therefore, enzyme-based sensors are innovative options for monitoring herbicides used in agriculture.

1. 2106 IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015
A Nanobiosensor Based on
4-Hydroxyphenylpyruvate Dioxygenase
Enzyme for Mesotrione Detection
Pâmela Soto Garcia, Alberto Luís Dario Moreau, Jéssica Cristiane Magalhães Ierich, Ana Carolina Araujo Vig,
Akemi Martins Higa, Guedmiller S. Oliveira, Fábio Camargo Abdalla, Moema Hausen, and Fábio L. Leite
Abstract—The herbicide residue from intensive agricultural
activity provokes environmental disturbances and human health
injuries. Among the enzymatic disruptor herbicides, mesotrione
is able to inhibit 4-hydroxyphenylpyruvate dioxygenase (HPPD),
which plays a key role in the carotenoid synthesis. Therefore,
enzyme-based sensors are innovative options for monitoring
herbicides used in agriculture. Compared to the standard sensors,
biosensors have assorted advantages, such as practicality, quick
response, low cost, and high sensitivity. A nanobiosensor was
developed herein based on HPPD for mesotrione detection.
Theoretically, the molecular docking and molecular dynamics
simulation estimated the interacting regions of HPPD with
mesotrione. Experimentally, the atomic force microscope tip func-
tionalization with HPPD immobilized in self-assembled mono-
layers was confirmed by fluorescence microscopy and atomic
force spectroscopy. The cross-linker N-(3-dimethylaminopropyl)-
N -ethylcarbodiimide hydrochloride was responsible for properly
preserving the enzyme on the tip. The nanobiosensor proposed
here was successfully able to detect mesotrione molecules. Such
effectiveness in the development of nanobiosensors promises
reliable, precise, and low-cost techniques, which apply to a broad
range of issues, from ecology to medicine.
Index Terms—AFM, AFS, chemical functionalization,
nanobiosensors, molecular docking, molecular dynamics
simulation, mesotrione, 4-hydroxyphenylpyruvate dioxygenase.
Manuscript received June 3, 2014; revised September 23, 2014 and
October 17, 2014; accepted November 2, 2014. Date of publication
November 20, 2014; date of current version January 29, 2015. This
work was supported in part by CNPq (CNPq/INCT, 573742/2008-1), in part
by FAPESP (FAPESP/INCT, 2008/57859-5, 2007/05089-9, 2010/00463-2,
2010/04599-6, 2013/09746-5, 2013/21958-8, 2011/17840-6, 2014/12082-4),
in part by nBioNet, and in part by CAPES (PNPD/20131505). The associate
editor coordinating the review of this paper and approving it for publication
was Dr. Chang-Soo Kim.
P. S. Garcia, J. C. M. Ierich, A. C. A. Vig, A. M. Higa,
G. S. Oliveira, M. Hausen, and F. L. Leite are with the Nanoneurobiophysics
Research Group, Department of Physics, Chemistry and Mathematics,
Federal University of São Carlos, São Carlos 18052-780, Brazil (e-mail:
pamelasotogarcia@hotmail.com; jcmierich@gmail.com; ana_vig_92@
hotmail.com; akemi.higa@hotmail.com; guedmuller@gmail.com;
moemahausen@gmail.com; fabioleite@ufscar.br).
A. L. D. Moreau is with the Department of Physics, Federal Institute of
Education, Science and Technology of Itapetininga, Itapetininga 18202-000,
Brazil, and also with the Nanoneurobiophysics Research Group, Department
of Physics, Chemistry and Mathematics, Federal University of São Carlos,
São Carlos 18052-780, Brazil (e-mail: aldmoreau@gmail.com).
F. C. Abdalla is with the Laboratory of Structural and Functional Biology,
Department of Biology, Federal University of São Carlos, São Carlos
18052-780, Brazil (e-mail: fabdalla@ufscar.br).
Color versions of one or more of the figures in this paper are available
online at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/JSEN.2014.2371773
I. INTRODUCTION
SENSORS are devices used for detection and measurement
of physical properties [1]. There are many different sorts
of sensors, and the understanding of their mechanisms requires
a multidisciplinary knowledge [2]. When biomolecules are
used to measure relevant biological material, the sensor
is defined as a biosensor [3], [4]. Those biomolecules are
usually immobilized through chemical or physical transducers,
creating a surface that makes possible the direct measurement
of a specific molecule [5], [6]. If the biosensor functions on
the nanometric scale, it is classified as nanobiosensor [7].
A nanobiosensor is obtained by the functionalization of
Atomic Force Microscope (AFM) tips and canmeasure forces
at an atomic scale [8], [9]; the application of those tips
on the development of nanobiosensors is known as Atomic
Force Spectroscopy (AFS) [10]. To build a functionalized
AFM tip requires the chemical modification of its surface.
Such procedure provides three essential benefits: (i) a high
sensitivity device; (ii) detections at the molecular level; and
(iii) simulation of a mimetic microenvironment [11], [12].
The functionalization process requires a previous study of
the set of molecules involved, while the availability of the
active site and substrate orientation are important parameters
for the AFM measurements [11], [13], [14]. In this context,
computer simulation is an easy and economical approach to
estimate intermolecular interactions. Therefore, the combina-
tion of theoretical and experimental methodologies provides
both macro and micro scale perspectives to the experiments.
Herbicides act on specific metabolic pathways in plants,
as inhibitors of the synthesis of carotenoids and amino acids.
This triggers photosynthesis failure, which leads to plant
starvation and death [15]. Herbicides have a deep impact on
human health and the environment, and the monitoring of such
agrochemicals in order to minimize their impact and invite
the development of alternative weed control procedures in
intensive agriculture is crucial. Plants and animals can share
targets of homoplasic molecules, and the metabolization of
herbicide molecules can generate secondary metabolics. These
can be more harmful than the herbicide itself, in addition to
the surfactant products that compose the herbicide formula,
which have been shown to be extremely toxic to animals by
ingestion, inhalation or contact [16]. Among assorted herbicide
types, few act by inhibiting specific enzymes. This type of
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2. GARCIA et al.: NANOBIOSENSOR BASED ON 4-HPPD ENZYME 2107
Fig. 1. Conversion of HPP to homogentisate, catalyzed by HPPD enzyme
(depicted on green elipse) at the tyrosine pathway [adapted from literature 21].
inhibition process is a reaction between a molecule and an
enzyme, which forms a complex that blocks the enzyme
function [16], [17].
The tyrosine catabolism is a common process in
plants and animals and requires key enzymes, such as
4-Hydroxyphenylpyruvate dioxygenase (HPPD) that catalyze
Hydroxyphenylpyruvate (HPP) to homogentisate (Fig. 1),
which participate in the energetic metabolism [18]–[20].
In animals, the lack of such conversion can adversely affect
different metabolic pathways and cause severe metabolic
disorders, such as Tyrosinemia and Hawkisinuria [18].
In plants, the inhibition of this sequence of metabolic events
leads to lower levels of chlorophyll and carotenoids. The
latter protect the chlorophyll from excess light. Because
of those inhibitory events and the fact that weeds grow
much more quickly than the economic plant of interest, the
herbicide causes leaves of the plant to blanch and, in a couple
of weeks, causes all photosynthesis to cease [21].
Several herbicides promote HPPD inhibition. Among them,
the triketone herbicide mesotrione (C14H13NO7S) is used
on pre- and post-emergency crops. After application, it is
absorbed by leaves and roots and is readily translocated to
the plant vascular system [22]–[24]. The HPPD inhibitors are
considered low risk pesticides.
Therefore, to contribute to advances in this research
field, a nanobiosensor based on AFM functionalized tips
was developed using the techniques of AFS and AFM [3],
[7], [11], [25] to perform mesotrione detection through the
inhibition of the target enzyme, HPPD. In our research,
the development of nanobiosensors focus on the study of
neurodegenerative diseases and on agrochemical detection,
especially enzymatic inhibitor herbicides [15], [26]–[29].
Mesotrione identification by an AFM tip nanobiosensor
functionalized with HPPD, studied hereunder controlled
parameters, can improve the application of biotechnology
to environmental safety. All techniques and methodologies
developed in this paper can be adapted to detect other
potential contaminants, such as pesticides and trace metals
that can harm the environment.
II. MATERIALS AND METHODS
A. Molecular Docking Parameters
The initial crystallography structure of the HPPD was
obtained from the online repository Protein Data Bank (PDB),
ID: 3ISQ [30]. The PDB file was prepared for the dock-
ing calculations. All missing residues were completed, and
the molecular structure was energy-minimized. Eight Mole-
cular Dockings were used to determine the HPPD affinity
regions with mesotrione by means of the AutoDock Tools,
version 1.5.6 [31]. The grid boxes had two different sizes, in
Angstrom (Å): grid boxes 1, 3, 5 and 7 had dimensions of
x = 56, y = 56 and z = 126, and grid boxes 2, 4, 6 and
8 dimensions were x = 68, y = 66 and z = 66, following the
protocol used by Franca et al. [32]. This last group was an
attempt of creating smaller boxes and obtaining more precise
results. The Lamarckian Genetic Algorithm (LGA) was used
to fit the mesotrione molecule in the HPPD, which was set
as a rigid structure, in a total of 100 runs for each docking.
The program was also set to calculate the internal electrostatic
energy. The RMSD Cluster Tolerance was adjusted to a limit
of 2.0 Å.
B. Molecular Dynamics Simulation
From the eight Molecular Dockings obtained previously,
four systems were chosen based on their final scored energies
and cluster conformations on which to perform Molecular
Dynamics (MD). Nanoscale Molecular Dynamics – NAMD
version 2.9 [33] and Visual Molecular Dynamics – VMD
version 1.9.1 [34] were used to prepare the systems under
study. The main goal was to rearrange the atoms to minimize
and equilibrate the molecule energetically. The first step was
to balance the negative charge of the system. The final charge
was 9.66340 e−6 C. The next step was the minimization
of the system’s energies conducted in 100000 steps, total-
ing 200 ps. The temperature adjustments were performed in
the NVT ensemble, at 298 K and 1.0 atm, using a Langevin
thermostat. The cut-off distance of 16 Å was the sameused in
Oliveira et al. [35]. The equilibration of the systems followed
the minimization, with certain modified parameters in the NpT
ensemble. Pressure and temperature were controlled using the
Langevin method at 1 atm and 310 K. The cut-off distance
of 12 Å was needed for accurate interaction contacts over the
trajectory. The electrostatic interactions were calculated with
the Particle Mesh Ewald (PME).
C. Experimental Procedure – Materials
According to Orry and Abagyan, (2012) [36], the
homology protocol established a minimum of 25% sequence
similarity between two molecules. In this case, the similarity
between human and plant HPPD is 33% as performed on
the BLAST online platform [37]. Therefore, our model
presents a moderate similarity that is feasible for use in
the mesotrione herbicide detection process. In addition,
only the pure human HPPD enzyme was available for
purchase, while the plant one is commercially restricted.
Consequently, in order to evaluate the nanobiosensor
behavior, the study was conducted using the human enzyme.

3. 2108 IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015
The pure human HPPD enzyme was acquired from Acris
Antibodies, Inc. (San Diego, CA), NCBI NP_001165464. The
enzyme was received lyophilized, and prior to experiments,
it was reconstituted in Mili-Q water. The mesotrione
agrochemical was purchased from Chem Service (West
Chester, PA) and diluted in pure-grade acetone, purchased
from Qhemis, Hexis Científica S/A (Indaiatuba, SP). The
following pure-grade materials were purchased from Sigma-
Aldrich (St. Louis, MO): monobasic sodium phosphate,
dibasic sodium phosphate, sodium chloride, triethy-
lamine (TEA), 3-aminopropyltriethoxysilane (APTES), and
N-(3-Dimethylaminopropyl)-N -ethylcarbodiimide hydrochlo-
ride (EDC). The glutaraldehyde (GLU) (as a 25% aqueous
solution) was purchased from Nuclear, CAQ (Diadema, SP),
and the Casein (CAS) was obtained from skimmed milk
powder. The fluorochrome used was fluorescamine
(C17H10O4; Sigma-Aldrich, USA). The AFM tips used were
triangular silicon nitride tips from NanoWorld-Innovative
Technologies (Switzerland), model PNP-TR-20. The cantilever
used had the following specifications: overall thickness:
600 nm, length: 200 μm, width: 2 × 28 μm, resonance
frequency: 17 kHz, spring constant (k): 0.08 N/m, radius:
<10 nm, coating (detector side): Cr/Au. The substrate
used was a muscovite mica from Ted Pella. The Atomic
Force Microscope was Veeco Multimode V with PicoForce
mode coupled with a fluid cell. The AFM software was
NanoScope 7.0, and the Origin 6 software was used
for statistical analysis. To obtain force curves, the AFM
Veeco Multimode V with PicoForce mode package was used,
in contact mode and in a liquid environment, using a fluid cell.
To use this fluid cell, it was necessary to build a system on the
AFM using a syringe with in and out pipes. The fluorescence
microscope used to characterize the functionalized AFM tips
was a Leica DM 4000b, coupled with a digitalization image
system by a Leica DFC310 FX camera, and the software
Leica FIM (Fluorescence Intensity Manager).
D. Experimental Procedure – Solution Preparation
The solutions were prepared as described: HPPD was
prepared using a dilution of 0.1 mg of enzyme in 5 mL
of Mili-Q, then stored in small aliquots (300μL) at
approximately −20 °C; mesotrione was prepared by a
dilution of 0.0333 gin 50 mL of acetone PA ACS; phosphate
buffered saline (PBS) was prepared with monobasic sodium
phosphate, dibasic sodium phosphate and sodium chloride.
The PBS solution buffer was at pH 7.2; PBS solution
with HPPD was prepared with a solution of PBS solution
buffer and HPPD enzyme (100 μL of enzyme in 5 mL of
PBS solution buffer); EDC with HPPD was prepared by
diluting 0.0013 g of EDC in 1 mL Mili-Q water, and 20 μL
of this solution was added to 150 μL of HPPD enzyme in
solution; casein solution was prepared by diluting 0.02 g of
skimmed milk powder in 1 mL of Mili-Q water.
E. Experimental Procedure – Methodologies for Nanobiosen-
sor Assembly and Immobilization of Target Molecules
Based on Silva et al., 2013 [15] and Moreau, 2005 [38],
the tip functionalization method used for the immobilization
of the HPPD enzyme by linker molecules was performed
using two distinct approaches. The first approach used APTES,
TEA and GLU, and the second approach used APTES, TEA,
EDC and CAS. The procedure described in this paper was
related to the second method, once the first method was
not successful in the HPPD attachment to an AFM tip. The
procedure steps can be summarized as follows: (i) the AFM
tips were cleaned for 20 min using U.V. (240 nm, ProCleaner,
Bioforce); (ii) the tips were exposed to the APTES and
TEA vapors (40 μl) during 45 min in a reaction chamber
(previously cleaned with nitrogen steam); (iii) the tips were
immersed in a solution containing HPPD and EDC for 2 h at
4 °C; (iv) three baths were prepared with fresh CAS solution
in Mili-Q water; (v) the AFM tips were immersed in the
CAS solution and were incubated during 1 h at 37 °C; and
(vi) a PBS bath solution injected in the AFM fluid cell for
measurements.
The substrate preparation procedure, which is made on
muscovite mica, was performed as follows: (i) the mica was
cleaved with adhesive tape and cleaned in UV light (240 nm,
ProCleaner, Bioforce) for 20 min; (ii) in a reaction chamber,
cleaned with nitrogen, the mica was exposed to APTES and
TEA at a ratio of 1:1 for 45 min; (iii) 200 μL of GLU was
deposited on the mica surface for 10 minutes; (iv) after three
Mili-Q baths, the herbicide mesotrione was added to the mica
surface, during 25 min in a nitrogen chamber; (iv) the mica
was immersed in a CAS solution at 37 °C during 1 h and then
immersed in a Mili-Q bath; and (v) the mica was immersed
in a PBS bath before being transferred to the AFM magnetic
holder for measurements.
F. Experimental Procedure – Atomic Force Spectroscopy
After the tip functionalization and mica placement in the
AFM apparatus, the laser beam was adjusted and the tip
approached to the mica surface. The injected solutions and
the software Nanoscope Analysis were previously adjusted
to carry out the force measurements. The nanobiosensor
experiments were performed in two steps: (i) nanobiosensor
measurement, using a PBS buffer solution injected in the
fluid cell, and (ii) system inhibition, injecting PBS buffer
with HPPD enzyme in the fluid cell. When this solution with
enzyme is injected in the system, it attaches to the herbicide at
the mica surface, avoiding the HPPD on the tip and interacting
with the sample, as shown in Fig. 2. This space can interact
with the HPPD on the tip, providing adhesion force values.
The data were obtained from adhesion force measurements of
the enzyme-herbicide interaction, performed on 10 different
substrate regions.
G. Experimental Procedure – Tip Characterization Using
Fluorescence Microscopy
The fluorochrome-HPPD conjugation was measured as fol-
lows: the functionalized tip was immersed for 5 min in
fluorescamine-dimethyl sulfoxide solution; afterwards, the set
was bathed three times in Mili-Q water. The fluorescent images
were obtained digitally and the software Leica Image Analysis
was used for processing and editing the images.

4. GARCIA et al.: NANOBIOSENSOR BASED ON 4-HPPD ENZYME 2109
Fig. 2. (a) Herbicide-enzyme interaction; (b) enzyme being injected on the
system; (c) enzyme-enzyme interaction and (d) enzyme-free spaces where
there is no interaction with the herbicide molecules over the mica substrate.
Fig. 3. Four mesotrione molecules (in green) docked to the different
regions on the HPPD molecular structure in order to run MD simulation.
Two cofactors are presented, Sodium and Chloride ions (in black and purple,
respectively). The total energies (E values in kJ.mol−1) are represented for
each mesotrione position. The inset above shows structural formula of the
mesotrione.
III. RESULTS AND DISCUSSION
A. System Energy
The immobilization and stability of biomolecular systems
on functionalized AFM tips is one concern in the design of
sensitive and selective biosensors [7], [15], [29]. As mentioned
before, HPPD (PDB code: 3ISQ) [30] was chosen to act as
a biologic sensor. To evaluate its behavior in an aqueous
solution, computational simulations (Molecular Docking and
Molecular Dynamics - MD simulation) were performed to
monitor the HPPD fluctuations such as its interaction energies
with mesotrione herbicide. The most favorable docked
positions scored are shown in Fig. 3. Four different confor-
mations of the mesotrione on binding regions of the HPPD
were considered. By running MD simulations, the systems
TABLE I
INHIBITION COEFFICIENT (Ki) AND REFERENCE RMSD, AND TOTAL
ENERGIES (ET) FOR EACH SYSTEM OF THE MOLECULAR DOCKING
CALCULATIONS AFTER 5 ns OF MD SIMULATION
were energy minimized and energy equilibrated, in order to
analyze the fluctuations and mobility of the mesotrione-HPPD
set in aqueous solution. The electrostatic and van der Waals
interactions were estimated and calculated. The results after
5 ns of MD simulation and the average energies are listed in
Table I.
Energetically, the most interactive region of the HPPD
enzyme was found in system 4, but this result cannot be
directly related to experimental ones because the orientation
of the HPPD on the tip must be considered, which depends on
the arrangement of multiple enzymes together. The goal of this
computational analysis is to provide an atomistic perspective
on the binding regions of HPPD with mesotrione.
The parameters of inhibition coefficient (Ki) and root mean
square deviation (RMSD) were analyzed using Molecular
Docking calculations for scoring HPPD binding sites with
mesotrione. According to Franca et al. [32], the concentration
of the herbicide required to inhibit an enzyme activity is
expected to be lower for the most favorable binding region.
In Table I, mesotrione has the lowest inhibition coefficient and
favorable interaction energies for systems 5 and 8. For these
systems, the adhesion force for mesotrione was higher. The
analysis of the Ki revealed that the inhibition coefficient was
high for systems 1 and 2; as a result, the clusters formed by
these systems were not suitable for biosensor requirements.
Additionally, the RMSD results revealed a large value for
systems 1, 2 and 5 (5.99 Å, 4.16 Å and 3.37 Å, respectively)
and a low value for system 8 (1.71 Å). Therefore, system 8 is
more interactive than the other ones, and the experimental
force curve obtained with the AFM is strong when the HPPD
is oriented to the substrate similar to system 8.
B. Root Mean Square Deviation – Protein Stability
Fig. 4 shows the computed RMSD for the 4 evaluated
systems. The HPPD structural fluctuations were monitored
during 5 ns of MD simulation in the presence of mesotrione
molecules. As shown, all systems have similar average
RMSD: 1.5 Å. The fluctuations can be attributed to the salt
bridges and hydrogen bonds formed and broken over time.
According to Franca et al. [32], charged amino acids such as
ARG, LYS, ASP and GLU located on the border can induce
new hydrogen bonds between water molecules and HPPD,
causing small structural fluctuations. The amino acids that

5. 2110 IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015
Fig. 4. Structural fluctuation of the HPPD at the presence of mesotrione
herbicide during 5 ns.
TABLE II
NUMBER OF SALT BRIDGES AND HYDROGEN BONDS FORMED AFTER
5 ns OF MD SIMULATION
contribute more hydrogen bonds were ASP, GLU and LYS,
while CYS, ILE and TRP do not have relevant contributions
to the total number of hydrogen bonds during the MD
simulation. Moreover, during all simulations, salt bridge
numbers from the HPPD were almost the same, and HPPD
structure was preserved. As shown in Table II, the number
of salt bridges remained constant during the MD simulation;
thus, the enzymatic structure was not affected by the solvent.
As a result, no effect was observed at the loops and side
chains, which have high RMSD values, and no denaturation
was detected on the HPPD enzyme structure.
Table II shows the number of salt bridges and hydrogen
bonds at the beginning (0 to 2.5 ns) and at the end
(2.5 to 5.0 ns) of the simulation. Both initial and late patterns
presented similarities, which consequently revealed that the
position of the mesotrione has no influence on the HPPD
enzyme structure. Finally, the computational results showed
that HPPD is stable enough to be used as a biosensor and
has specific interactive regions to mesotrione.
C. Support of Tip Functionalization by
Fluorescent Labeling
According to literature [39], fluorescence microscopy (FM)
is usedto confirm the AFM tip functionalization. The
combination of AFM and other techniques, such as confocal
laser scanning microscopy and fluorescent imaging, provides a
better understanding of biological studies, enlarging the possi-
bilities of investigation and giving more detailed information.
Fig. 5. The AFM tips observed by two microscopy techniques: bright
field (a, c) and fluorescent mode (b, d). The same tip is observed in
both techniques for the nonfunctionalized-control group (a, b) and for the
functionalized one (c, d). The tips functionalized with HPPD and conjugated
with fluorescamine (Si/HPPD-F) presented intense blue fluorescence while the
nonfunctionalized ones remained dark in fluorescent mode (b). This qualitative
result confirmed the HPPD presence on tips.
TABLE III
ADHESION FORCE (AF) OBTAINED WITH AFS EXPERIMENTS FOR
CONTROL (600 ADHESION FORCE CYCLES)
They may become important tools in medicine, detecting
diseases in early stages [40]. In this paper, the use of FM
to detect HPPD confirmed the AFM tip functionalization.
The images obtained by FM showed that the methodology
was effective in attaching the biomolecule to the tip (Fig. 5).
Furthermore, other studies [41] suggest functionalization
evaluation by confocal microscopy and mediated by indirect
fluorescent labeling to be an effective tool to scan and detect
all labeling distribution on the tip surface at higher resolution.
D. Mesotrione Detection by AFM Tip Nanobiosensor
The first experimental data were obtained from control
tips, organized as follows: (type 1) clean tips, without any
functionalization; (type 2) tips functionalized with APTES and
TEA; (type 3) tips functionalized with APTES, TEA, EDC
and CAS. These three control tips were used to perform force
measurements in the AFM liquid cell, over the sample with
the herbicide. The obtained adhesion force data were lower
than expected, at values around 0.4 nN for measurements in
solution [42], [43].
The force measurement characterizations of all control tips
were used as parameters for the nanobiosensor according to
the values shown in Table III. The type 2 tips showed high
adhesion values, most likely due to the interaction between the

6. GARCIA et al.: NANOBIOSENSOR BASED ON 4-HPPD ENZYME 2111
Fig. 6. Representative histograms for the sets of measurements to the
Nanobiosensor (AFnb) and System Inhibition (AFsi). The adjustment was
performed by Gauss curve.
APTES and the herbicide. Compared to those with APTES, the
type 3 tips showed lower values because CAS favors the inhi-
bition of the active sites of APTES, as recently reported [44].
Limanskii [45] also performed a functionalization on silicon
nitride AFM probes, using APTES vapors. In that work, the
use of the linking agent Disuccinimidyl suberate (DSS) was
followed by albumin attachment. The model proposed by
Limanskii [45] and the one presented here share the use of
APTES vapors to successfully induce modifications on the tip.
The nanobiosensor, developed through the functionaliza-
tion of the HPPD enzyme on APTES, TEA, EDC and
CAS, is expected to present a higher value of adhesion
compared to the control tests, specifically detecting the her-
bicide mesotrione. The results presented here are in agree-
ment with our previous experiments using nanobiosensors
with diclofop, atrazine and metsulfuron-methyl agrochem-
icals [15], [26], [28]. The high adhesion values that were
obtained confirm the effectiveness of the functionalization
method under aqueous conditions. Therefore, the protocol
established for the nanobiosensors is straightforward and can
be applied to assorted detections.
After obtaining the control data, the nanobiosensors were
developed and tested. First, a functionalization methodology
with APTES, TEA, GLU, and HPPD was tested (data not
shown). However, this functionalization was not efficient and
did not provide good adhesion force values, which led to the
conclusion that the biomolecule HPPD did not link properly
on GLU, and the active sites were most likely not in favorable
positions to link to the substrate.
Fig. 6 shows that the adhesion values ranged approximately
1.5 nN and reached a recover of 63% to the nanobiosensor
and 35% to the system inhibition. These values are included
in Table IV. Although the frequency changed, the adhesion
force remained the same, as expected. According to the
proposed model, the system was probably inhibited due to
HPPD linkage on mesotrione (Fig. 2d).
The method was evaluated by measuring the nanobiosensor
force value, which was two times higher than with the
control tips. This finding implies that the HPPD was properly
TABLE IV
ADHESION FORCE (AF) OBTAINED WITH AFS EXPERIMENTS FOR
NANOBIOSENSOR AND INHIBITION
orientated on the tip due to the EDC cross-linker, probably
exposing the interaction sites to mesotrione molecules.
All data sets presented demonstrate that the nanobiosensor
developed here was effective for mesotrione detection. The
inhibition parameter is very informative as it verified the
fidelity by the characterizing approach, while the FM directly
confirmed the functionalization. The promising results
obtained by our research group [7], [15], [29], [46] bring
forward insights to the study of intermolecular detections.
IV. CONCLUSION
The combination of theoretical and experimental studies
identified possible regions where the herbicide mesotrione
interacts on the HPPD molecular structure. Additionally,
the AFM adhesion measurements showed the accuracy of
the functionalized HPPD nanobiosensor, which was also
corroborated by the FM tip labeling. The next step of our
investigation is to compare the results from human HPPD with
the plant HPPD because the latter is more directly affected by
mesotrione molecules. Finally, the originality of the biosensor
proposed in this paper is based on AFS categorical detection
of herbicides for environmental monitoring.
ACKNOWLEDGMENTS
The authors of this paper would like to thank
M. Castilho de Almeida Moura for the tip drawings
using Corel Draw. They acknowledge the Post-Graduation
Program of Biotechnology and Environment Monitoring of
the Federal University of São Carlos, Sorocaba.
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Pâmela Soto Garcia was born in Sorocaba, Brazil,
in 1984. From 2006 to 2007, she performed under-
graduate research at the Biomonitoring Laboratory,
Faculty of Technology at Sorocaba (FATEC-SO),
Sorocaba. In 2008, at her second undergraduate
research at the Dante Pazzanese Institute, São Paulo,
Brazil, she studied devices for medical applications.
She received the B.S. degree in health technology
from FATEC-SO, in 2008. In 2009, she studied
microbiology in public health at the Adolfo Lutz
Institute, São Paulo. She received the M.Sc. degree
in biotechnology and environmental monitoring from the Federal University
of São Carlos (UFScar), Sorocaba, in 2014. Since 2012, she has developed
atomic force microscopy (AFM) tips nanobiosensors, and is a specialist in
AFM and Nanotechnology with the Nanoneurobiophysics Research Group,
UFScar, where she is currently pursuing the Ph.D. degree in nanobiosensors.
Alberto Luís Dario Moreau was born in São Paulo,
Brazil, in 1977. He received the B.S. degree in
physics, and the M.Sc. and Ph.D. degrees from the
State University of Campinas, Campinas, Brazil, in
2003, 2005, and 2011, respectively. He is currently
a Professor and Coordinator of the Basic Physics
Laboratory at the Federal Institute of Education,
Science and Technology, Itapetininga, Brazil. Since
2013, he has been with the Nanoneurobiophysichs
Research Group, Federal University of São Carlos,
Sorocaba, and has experience in biophysics with an
emphasis on functionalization and immobilization of biomaterials surfaces and
interfaces, force spectroscopy with atomic force microscopy (AFM), AFM
topographic analysis of biomaterials, carbon nanotubes and graphene, and
biosensors in semiconductor platforms.

8. GARCIA et al.: NANOBIOSENSOR BASED ON 4-HPPD ENZYME 2113
Jéssica Cristiane Magalhães Ierich was born in
Sorocaba, Brazil, in 1991. She received the degree in
technology on biomedical systems from the Faculty
of Technology at Sorocaba, Sorocaba, in 2011, and
the M.S. degree in biotechnology and environmental
monitoring from the Federal University of São Car-
los (UFSCar), Sorocaba, in 2014. In 2012, she had
the opportunity to study 3-D structures of proteins
using homology modeling and molecular dynam-
ics simulation. Also, she has studied enzymatic
inhibition process by herbicides for nanobiosensors
applications. She is currently pursuing the bachelor’s degree in biological
sciences and the Ph.D. degree at UFSCar. Her Ph.D. study is focused on the
description of antigen-antibody interaction by means of computational and
theoretical approaches.
Ana Carolina Araujo Vig was born in São Paulo,
Brazil, in 1992. She is currently pursuing the bach-
elor’s degree in chemistry at the Federal University
of São Carlos (UFSCar), Sorocaba, Brazil. In 2010,
she began teaching Chemistry for private students,
preparatory courses at Corporative University, and
tutoring at Aprendiz Reinforcement School. She also
tutored the students of UFSCar coursing Physics I
in 2012. In 2011, she joined the GNN Research
Group, functionalizing atomic force microscopy tips
for the study of nanobiosensors. Currently, she has a
Scientific Initiation in Theoretical and Computational Chemistry, studying the
IgG antibody, specially its binding site, and its relation to multiple sclerosis.
Akemi Martins Higa is currently pursuing the
bachelor’s degree in biological sciences from the
Federal University of São Carlos (UFSCar), Soro-
caba, Brazil. She was born in São Paulo, Brazil, in
1992. She joined the GNN Research Group in 2012,
studying the immobilization of enzymes on atomic
force microscopy tips. Since 2013, she has studied
the development of quantum dots functionalization
techniques to cover them with biomolecules, such
as antibodies and antigens. The main purpose of her
studies with the group is to develop a nanobiosensor
that promotes an accurate and early diagnosis for multiple sclerosis disease.
Guedmiller S. Oliveira received the B.S. and M.S.
degrees in physical chemistry from the Federal Uni-
versity of Uberlândia, Uberlândia, Brazil, in 2006
and 2009, respectively, and the Ph.D. degree in
physical chemistry from the Federal University of
São Carlos (UFSCar), Sorocaba, Brazil, in 2013.
Since 2007, he has worked with computer simulation
providing an atomistic point of view for experi-
mental procedures. His expertise lies on quantum
mechanics theory, molecular dynamics simulation,
and it combines results from experimental and theo-
retical analysis through statistical thermodynamics to improve comprehension
of the macromolecular phenomena. He currently holds a post-doctoral position
with UFSCar.
Fábio Camargo Abdalla received the bachelor’s
degree in biological sciences from São Paulo State
University, Rio Claro, Brazil, in 1996, the mas-
ter’s degree in biological sciences with a minor in
molecular cellular biology from São Paulo State
University and the University of Utrecht, Utrecht,
The Netherlands, in 1999, the Ph.D. degree in bio-
logical sciences with a minor in molecular cellular
biology from São Paulo State University and Keele
University, Keele, U.K., in 2002, and the Post-
Doctoral degree from São Paulo State University, in
2006. He is currently a Professor with the Federal University of São Carlos,
Sorocaba, Brazil. He has experience in cell and molecular biology with an
emphasis on structural and functional biology and chemical ecology.
Moema Hausen was born in Rio de Janeiro, Brazil,
in 1977. She received the Ph.D. degree from the
State University of Rio de Janeiro, Rio de Janeiro,
in 2009. After three years performing her first
post-doctoral assistance at the Brazilian Center for
Physics Research, Rio de Janeiro, she is currently
involved in a second one, at the Biotechnology
and Environmental Monitoring Post-Graduation Pro-
gram, Federal University of São Carlos, Sorocaba,
Brazil. In 2000, she started in biomedical scientific
laboring in the following themes—cell biology, his-
tology, protozoology, transmission, and assorted state-of-the-art microscopy
techniques, such as the scanning electron, transmission electron, fluorescence,
and confocal ones. Her main goals actually are the application of high-end
microscopy techniques to integrated approaches on materials and biological
sciences.
Fábio L. Leite was born in Itanhaem, Brazil.
He received the B.Sc. degree in physics from São
Paulo State University, Rio Claro, Brazil, in 2000,
and the M.Sc. and Ph.D. degrees in materials science
and engineering from the University of São Paulo,
São Carlos, Brazil, in 2002 and 2006, respec-
tively. From 2007 to 2008, he was a Post-Doctoral
Researcher with the Alan Graham MacDiarmid
Institute of Innovation and Business, Embrapa Agri-
cultural Instrumentation (Embrapa), São Carlos,
with Dr. O. N. de Oliveira, Jr., Dr. L. H. C. Mattoso
(Embrapa), and A. G. MacDiarmid, and was a recipient of the University of
Pennsylvania Nobel Prize in Chemistry in 2000. His efforts at the MacDiarmid
Institute focused on conducting polymers, nanosensors, and atomic force
microscopy (AFM) with environmental applications. Since 2009, he has been
an Assistant Professor and a Researcher with the Federal University of
São Carlos, Sorocaba, Brazil, and the Head of the Nanoneurobiophysics
Research Group. He has authored over 50 published papers, five books,
10 book chapters, and holds two patents. His research interests are related
to the development of nanobiosensors using AFM and computational nano-
technological for application in the studies of a variety neurodegenerative and
autoimmune diseases.