Development and validation of a docking-based virtual screening platform for the identification of new lactate dehydrogenase inhibitors

Article abstract of DOI:10.3390/molecules20058772

The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is linked to the vitality of tumors in hypoxic conditions. With the aim of identifying new hLDH5 inhibitors, a fully automated docking-based virtual screening platform was developed by considering different protein conformations and the consensus docking strategy. In order to verify the reliability of the reported platform, a small database of about 10,000 compounds was filtered by using this method, and the top-ranked compounds were tested for their hLDH5 inhibition activity. Enzymatic assays revealed that, among the ten selected compounds, two proved to efficiently inhibit enzyme activity with IC₅₀ values in the micromolar range. These results demonstrate the validity of the methodologies we followed, encouraging the application of larger virtual screening studies and further refinements of the platform. Furthermore, the two active compounds herein described may be considered as interesting leads for the development of new and more efficient LDH inhibitors.

Full text of DOI:10.3390/molecules20058772

Molecules 2015, 20, 8772-8790; doi:10.3390/molecules20058772
OPEN ACCESS
molecules
ISSN 1420-3049
www.mdpi.com/journal/molecules
Article
Development and Validation of a Docking-Based Virtual
Screening Platform for the Identification of New Lactate
Dehydrogenase Inhibitors
Carlotta Granchi, Alice Capecchi, Gianluca Del Frate, Adriano Martinelli, Marco Macchia,
Filippo Minutolo and Tiziano Tuccinardi *
Department of Pharmacy, University of Pisa, 56126 Pisa, Italy;
E-Mails: carlotta.granchi@farm.unipi.it (C.G.); alice.capecchi@outlook.it (A.C.);
gianluca.delfrate@sns.it (G.D.F.); adriano.martinelli@farm.unipi.it (A.M.);
marco.macchia@farm.unipi.it (M.M.); filippo.minutolo@farm.unipi.it (F.M.)
* Author to whom correspondence should be addressed; E-Mail: tiziano.tuccinardi@farm.unipi.it;
Tel.: +39-050-221-9595.
Academic Editor: Rino Ragno
Received: 3 March 2015 / Accepted: 11 May 2015 / Published: 15 May 2015
Abstract: The human muscle isoform of lactate dehydrogenase (hLDH5) is one of the key
enzymes of the glycolytic process. It is overexpressed in metastatic cancer cells and is
linked to the vitality of tumors in hypoxic conditions. With the aim of identifying new
hLDH5 inhibitors, a fully automated docking-based virtual screening platform was
developed by considering different protein conformations and the consensus docking
strategy. In order to verify the reliability of the reported platform, a small database of about
10,000 compounds was filtered by using this method, and the top-ranked compounds were
tested for their hLDH5 inhibition activity. Enzymatic assays revealed that, among the ten
selected compounds, two proved to efficiently inhibit enzyme activity with IC50 values in
the micromolar range. These results demonstrate the validity of the methodologies we
followed, encouraging the application of larger virtual screening studies and further
refinements of the platform. Furthermore, the two active compounds herein described
may be considered as interesting leads for the development of new and more efficient
LDH inhibitors.
Keywords: LDH inhibitors; virtual screening; docking

Molecules 2015, 20
8773
1. Introduction
Human lactate dehydrogenase (hLDH) catalyzes the reduction of pyruvate to lactate (and the
reverse reaction) in the presence of a cofactor (NADH or NAD+). This enzyme may exist as five
functional tetrameric isoforms (hLDH1-5), composed of the various combinations of the two
monomeric subunits: LDH-A and LDH-B. Over the past few years, this enzyme has been increasingly
considered as a potential target for therapeutic agents, including antimalarial and antitumor agents [1].
In particular, hLDH5 (LDH-A4) catalyzes a crucial step in the glycolytic pathway, which is found to be
greatly enhanced in many invasive tumors and, therefore, may determine a sufficient therapeutic
window for perspective therapeutic agents interfering with the peculiar metabolism of cancer cells [2,3].
As a matter of fact, numerous examples of hLDH5 inhibitors have been recently reported [4]. Our
group discovered a new class of N-hydroxyindole-based inhibitors of hLDH5 [5–7], which were
demonstrated to specifically interact with this protein by using a self-referencing external cavity laser
biosensor technology [8]. Then, we have further functionalized these compounds with sugar portions
in order to enhance the uptake by cancer cells, thus exploiting a dual targeting of the Warburg
effect [9,10], by following a strategy that was successfully exploited in many other types of antitumor
agents [11]. Among the various virtual screening (VS) strategies, docking-based VS is one of the most
widely-applied approaches [12]. In the Protein Data Bank [13], some hLDH5 X-ray crystal structures
have been deposited. One of the first published structures described the interaction of oxamate (1,
Figure 1) in the pyruvate binding site [14]; furthermore, other structures have been recently reported,
such as the complex of hLDH5 with a malonic derivative [15] (2, Figure 1) and with (R)-3-(5-amino-
6-((1-phenylethyl)amino)pyrazin-2-yl)-4-chlorobenzoic acid [16] (3, Figure 1). Given the presence of
these deposited structures, a docking-based VS strategy could be profitably applied.
Figure 1. Representative LDH inhibitors deposited in the PDB in complex with hLDH5.
Usually, molecular docking can be defined as an optimization task to identify the ligand conformation
bound to the target with the most favorable binding energy. However, this is a challenging task mainly
due to ligand and protein flexibilities. With regards to the protein flexibility, two different conformational
states of hLDH5 have been reported, a closed and an open conformation [1]; furthermore, different
ligands are able to interact in the presence and/or absence of the NADH co-factor. On these bases, an
ensemble VS docking strategy could be a possible way for identifying new hLDH5 inhibitors. Very
recently, we reported an evaluation study of the consensus docking approach [17]. By using this kind
of approach, one ligand is docked into the target protein by means of different docking procedures.
Then, among the different best-ranked poses (originated by the different docking procedures) the pose
in common with the largest number of docking procedures is considered as the best docking pose.
From a qualitative point of view, previous results highlighted that consensus docking was able to
predict the ligand binding pose better than the single docking evaluation [17]. Furthermore, concerning

Molecules 2015, 20
8774
the VS studies, the results suggested that this approach performed as well as the best available methods
found in the literature, and it was also able to experimentally identify new active molecules. Taking
together all of these data, in the present study, we report the development of a VS platform based on a
mixed ensemble/consensus docking approach.
2. Results and Discussion
An analysis of the various deposited X-ray crystal structures of hLDH5 complexed with ligands
clearly support the hypothesis that there are different binding methods for inhibiting this enzyme. In
2001, Read and co-workers reported the complex between hLDH5 and 1 [14]; in this structure, the
ligand strongly interacted with R169; the enzyme showed a closed conformation, and NADH was
placed in the co-factor binding site. In 2012 Ward and co-workers reported a malonic derivative (2),
which interacted with the closed conformation of hLDH5 by displacing both the substrate and the
NADH co-factor [15]. Finally, in 2013, Fauber and co-workers reported a 2-amino-5-aryl-pyrazine
derivative (3), which interacted with an open conformation of hLDH5 and also showed important
interactions with the NADH co-factor; in fact, in this case, the co-factor was still present in the crystal
structure [16]. On the basis of this analysis, it was possible to assess that hLDH5 inhibitors could
interact with both the closed and the open conformation of the enzyme, either in the presence or in the
absence of the NADH co-factor. Following this hypothesis, four different protein structures were built
for our docking calculations, so that all of the combinations of the open/closed conformation and of the
NADH presence/absence were considered. As mentioned above, we have recently reported a
consensus-docking reliability analysis by using ten docking procedures [17]. However, the main
Achilles’ heel of the consensus docking approach is the long computing time required, so that,
unfortunately, large libraries of compounds require a large amount of CPU time. One of the possible
solutions to this problem could be the reduction of the number of applied docking procedures.
Consequently, in this study, we applied four different docking procedures that corresponded to the
application of four different docking software. In order to validate this approach, an enriched VS
analysis was carried out. To our knowledge, no enriched database consisting of LDH inhibitors and
decoys is presently available in the literature. To build up this database, small molecules for which an
LDH inhibition assay was reported in the literature were analyzed. About 200 compounds were
identified as LDH inhibitors able to interact with the open conformation of the enzyme in the presence
of NADH, and 93 compounds showing an IC50 lower than 15 µM were selected as active LDH
inhibitors [16,18–21]. As regards the choice of decoys, we downloaded all of the decoys included in
the Maximum Unbiased Validation datasets reported by Rohrer and Baumann [22]. A total of 10,000
molecules were randomly selected from the compounds with a molecular weight between 315 and
560 g/mol that corresponded to the molecular weight possessed by the active molecules included in
our dataset. The so-obtained enriched database consisted of 93 active molecules (see Table S1) and
10,000 decoys and was then used to assess the ability of the consensus docking procedure in separating
LDH inhibitors from decoys. The performance evaluation was carried out using well-established
accepted metrics, such as the enrichment factor (EF) and the AUC of the ROC curve. The 10,093
molecules were thus docked into the LDH open conformation in the presence of NADH by using the
four docking procedures and analyzing the consensus docking results. As shown in Table 1, a

Molecules 2015, 20
8775
consensus docking level of four resulted in an EF of 40.7, which corresponded to 37.5% of the
maximum reachable EF value. With regards to the AUC, it showed a value of 0.84. Focusing the
attention on the active molecules, only 12 out of 93 showed a consensus of four. These results
confirmed that the consensus docking protocol has the disadvantage of generating false negatives.
Table 1. Consensus docking results for the enriched database analysis. EF, enrichment factor.
Consensus Level
Actives
93
Decoys
10,000
1952
177
EF
1.0
1
2
3
75
3.7
43
19.5
40.7
4
12
20
AUC
0.84
The consensus docking results were then compared to those obtained by considering each of the
four docking procedures as an independent evaluation and calculating the AUC and EF values
generated by the docking-based scoring results. As shown in Figure 2, all of the EF and AUC values
obtained for each docking procedure were worse than that obtained for the consensus level of four,
thus suggesting that none of the docking procedures were able to filter the enriched database as
efficiently as the consensus docking approach.
Figure 2. AUC (right plot) and EF (left plot) analysis for the four docking procedures.
The black line indicates the EF and AUC values obtained by applying the consensus
docking strategy.
In order to provide a preliminary experimental VS reliability test, the University of Illinois Marvel
library, a collection of about 10,000 compounds, seemed to be an optimal and accessible set of
compounds to test our procedure, so it was filtered by using this platform (Figure 3). A library of
10,000 molecules can be considered very small with today’s computing power. However, this VS
study was a preliminary analysis, and furthermore, due to the calculation requirements of the consensus
docking procedure, the analysis of this library required a total of about 160,000 docking calculations.

Molecules 2015, 20
8776
The Marvel compounds were thus docked into the four protein structures by using the four different
docking procedures, and the compounds possessing a consensus level of four for at least one protein
structure were further taken into account. The four protein structures were treated as independent of
each other. In this way, compounds that showed a consensus level of four into at least one of the four
protein structures and that bound differently in the four proteins forms were also selected.
Figure 3. Schematic diagram of the virtual screening workflow.
The 30 compounds that showed a consensus level of four were subjected to an MD simulation with
the aim of verifying the stability of the docking pose. To set up the MD simulation protocol, the
complex between hLDH5 and 2 (4AJP [15] PDB code) was used as a test. The ligand-protein complex
was subjected to a total of 2 ns of MD simulation; as shown in Figure 4, after about 500 ps, the system
reached an equilibrium, since the total energy for the last 1.5 ns remained approximately constant. By
analyzing the RMSD of the ligand’s position with respect to the starting structures during the
simulation, we observed an average RMSD of 0.5 Å, whereas with regards to the analysis of the heavy
atoms of the protein, in agreement with the energy analysis after about 500 ps, it showed a stable
RMSD value of about 0.9 Å.
The 30 compounds obtained by the previous VS steps were subjected to MD simulation using the
protocol described above, and all of the ligands that showed an average RMSD value lower than 2 Å
were further considered. The application of an MD time length of 2 ns and the usage of a 2-Å average
RMSD threshold was selected, because these two parameters were profitably used in another
consensus docking VS study [23]. About 70% of the compounds were rejected by using this filter, and
the remaining ten compounds were collected at the University of Illinois in order to submit them to
experimental enzyme inhibition assays. Unfortunately, Compounds VS1, VS2 and VS3 of Table 2
were no longer available; therefore, they were synthesized in our lab.

Molecules 2015, 20
8777
Figure 4. Analysis of the MD simulation of Compound 1 complexed with hLDH5: (A)
total energy of the system vs. time; (B) RMSD of the ligand from the starting model
structure during the simulation; (C) RMSD of the heavy atoms of the protein from the
starting model structure during the simulation.
The synthesis of the first two compounds, VS1 and VS2 (Scheme 1), started from commercially
available p-aminobenzoic acid 4, which was subjected to a classical Fischer esterification in methanol
with catalytic sulfuric acid to protect the carboxylic acid group for the next reaction steps. The
resulting methyl ester 5 was then reacted with neat 2-iodoethanol to alkylate the aniline group with a
2-hydroxyethyl chain. Finally, the methyl ester group of Compound 6 was hydrolyzed under basic
aqueous conditions to give the desired Compound VS1. Intermediate 5 was also condensed with
p-toluenesulfonyl chloride in the presence of 4-(dimethylamino)pyridine (DMAP) and pyridine to
produce sulfonamide 7, whose saponification yielded Compound VS2.
H
N
H
H2N
H2N
N
HO
HO
a
b
c
OH
OCH3
OCH3
OH
O
O
O
O
4
5
6
VS1
d
H3C
H3C
H
H
N
N
c
S
S
O
O
O
O
OCH3
OH
O
O
7
VS2
Reagents and conditions: (a) MeOH, concentrated H2SO4, reflux, 48 h; (b) 2-iodoethanol, neat, 90 °C, 6 h;
(c) aq. LiOH 2 N, THF/MeOH 1:1, RT, 48 h; (d) p-toluenesulfonyl chloride, pyridine, catalytic
4-(dimethylamino)pyridine (DMAP), CH2Cl2, 0 °C to RT, 17 h.
Scheme 1. Synthesis of compounds VS1 and VS2.

Molecules 2015, 20
8778
An intramolecular cyclization of commercially available 2-amino-1-phenylethanol 8 in the presence
of N,N-carbonyldiimidazole (CDI) and imidazole gave the oxazolinone 9 (Scheme 2), which was then
N-alkylated with sodium hydride and tert-butyl bromoacetate. Standard deprotection of the tert-butyl
ester of Compound 10 with trifluoroacetic acid afforded the desired Compound VS3.
O
O
O
CH3
CH3
CH3
O
OH
NH
N
N
*
O
O
O
O
O
HO
*
*
*
NH2
c
a
b
8
9
10
VS3
Reagents and conditions: a, N,N-carbonyldiimidazole (CDI), imidazole, CH2Cl2, RT, 20 h; b, NaH, tert-butyl
bromoacetate, dry DMF, RT, 4 h; c, CF3COOH, CH2Cl2, RT, 26 h.
Scheme 2. Synthesis of compound VS3.
The ten compounds were then subjected to hLDH5 inhibition assays together with reference
inhibitor galloflavin, oxamic acid [24], N-hydroxyindole-based compounds NHI-1 and NHI-2 [25],
which were used as positive controls. As shown in Table 2, two out of the ten tested compounds
showed appreciable LDH inhibitory activities (VS6 and VS8), with IC50 values of about 250 µM. It is
worth noting that Compound VS6 was derived from the closed LDH conformation without the NADH
co-factor, whereas Compound VS8 was derived from the open LDH conformation in the presence of
NADH. The docking scores obtained for the ten compounds were also used to rank them; however,
none of the four scoring results were able to correctly rank-order the ten final compounds.
Table 2. Structure and activity of the tested compounds.
Structure
hLDH5, IC50 (µM)
VS1
VS2
>500
>500
>500
>500
VS3
VS4

Molecules 2015, 20
8779
Table 2. Cont.
Structure
hLDH5, IC50 (µM)
VS5
VS6
>500
245.7 ± 10.8
>500
VS7
VS8
VS9
268.6 ± 58.1
>500
>500
VS10
galloflavin
91.7 ± 10.7
oxamic acid
NHI-1
97.7 ± 11.2
51.7 ± 4.2
CF3
O
NHI-2
10.8 ± 3.5
N
O
OH
As shown in Figure 5A, Compound VS6 occupied the NADH binding site; the N-phenylacetamide
portion of the molecule showed two H-bonds with D52 and G97 and lipophilic interactions with V26,
V51, V53, A96, I116, F119 and I120. The isopropyl group was exposed to the solvent and did not

Molecules 2015, 20
8780
show important interactions, whereas the benzyl carbamate portion of the molecule showed a
lipophilic interaction with V31 and two H-bonds with the backbone of G29 and G97. Differently from
VS6, Compound VS8 occupied the substrate binding region of the enzyme (Figure 5B); the 3,5
dinitrobenzene portion of the molecule showed three H-bonds with R169 and T248 and lipophilic
interactions with V241. The amide portion did not show important interactions, whereas the
methyl-2-phenylacetate fragment showed one H-bond with the nitrogen backbone of Q100 and
lipophilic interactions with L109 and P139.
Figure 5. Minimized average structures of Compounds VS6 (A) and VS8 (B) docked into hLDH5.
Among these two newly-identified LDH inhibitors, VS8 appeared to be the most promising
compound, because it occupies the substrate binding region and interacts with key residues, such as
T248 and R169. In order to suggest possible modifications to the VS8 structure for optimizing its
activity, this compound was subjected to fragmental scanning by using the BROOD software [26].
This software is capable of identifying bioisosteric replacements for a query fragment, but it can
also identify fragments with progressively less similarity to the original molecular fragment. The
3,5-dinitrobenzene portion of the molecule, which was shown to effectively interact with the substrate
binding site of the enzyme, was thus subjected to a fragmental scanning. Starting from a database of
about one million fragments, those that showed a possible interaction into the protein binding cavity
(see the Materials and Methods Section for details) were considered, and the corresponding molecules
were processed with consensus docking/MD screening analysis. Table 3 shows the filtered compounds
obtained by using this procedure.
Table 3. Potential new active LDH inhibitors.

Molecules 2015, 20
8781
Table 3. Cont.
R
VS8a
VS8b
VS8c
OH
N
N
O
N
H
The analysis highlighted that the substitution of one of the two nitro groups with a carboxylic
(VS8c) or an acetic substituent (VS8a and VS8b) could improve the activity. The acetic portion of
compounds VS8a and VS8b showed a strong ionic interaction with R169 and a secondary H-bond
with T248, whereas the hydroxyl group of VS8a and the methoxy substituent of VS8b maintained the
H-bond interaction with the nitrogen backbone of T248 (Figure 6A). With regards to the rest of their
structures, these molecules showed a disposition very similar to that observed for VS8. A similar
analysis could also be done for Compound VS8c; as shown in Figure 6B, the carboxylic substituent
showed a strong ionic interaction with R169; the imidazopyridine nucleus maintained the two H-bonds
with the hydroxyl and the nitrogen backbone of T248, whereas the rest of the molecule showed a
disposition very similar to that observed for VS8.
Figure 6. Minimized average structures of compounds VS8b (A) and VS8c (B) docked into hLDH5.
3. Experimental Section
3.1. Molecular Modeling
Input generation: In the Protein Data Bank [13] are deposited X-ray crystal structures of hLDH5 in
the open and closed conformation. In particular, the structure of hLDH5 complexed with Compound 2
(4AJP [15] PDB code) corresponded to a closed conformation of the enzyme and did not show NADH
co-factor; the hLDH5 complexed with 1 (1I10 [14] PDB code) showed a closed conformation and the
presence of NADH, whereas the hLDH5 complexed with 3 (4M49 [16] PDB code) showed an open
conformation of the enzyme and was crystallized in the presence of NADH. For these reasons, for the
closed hLDH5 conformation in the absence and presence of NADH, 4AJP and 1I10 were used,

Molecules 2015, 20
8782
respectively, and for the open hLDH5 conformation in the presence of NADH, the 4M49 structure was
used. As there were no deposited structures of the open hLDH5 conformation in the absence of NADH
co-factor, we generated this structure removing the NADH molecule from the 4M49 structure. For the
protein input structures containing NADH, the substrate binding region corresponded to the docking
binding site, whereas for the two protein input structures that did not show NADH, the docking
binding site corresponded to the fusion of the substrate and co-factor binding site. The Marvel library,
a unique collection of over 10,000 compounds stored in the Department of Chemistry at University of
Illinois, Urbana-Champaign, was processed by means of the LigPrep software [27], which performs a
series of steps that perform conversions, apply corrections to the structures, eliminate unwanted
structures and optimize the structures. The so-obtained database was then subjected to the consensus
docking calculations into the four hLDH5 structures.
Docking procedures: For all docking analyses, only the best-scored pose was taken into account.
AUTODOCK 4.2.3: AUTODOCK Tools utilities [28] were used in order to identify the torsion
angles in the ligands, to add the solvent model and assign the Gasteiger atomic charges to proteins and
ligands. The regions of interest used by AUTODOCK [29] were defined by considering the reference
ligand as the central group of a grid box of 10 Å in the x, y and z directions. A grid spacing of 0.375 Å
and a distance-dependent function of the dielectric constant were used for the energetic map
calculations. By using the Lamarckian genetic algorithm, the docked compounds were subjected to 20
runs of the AUTODOCK search using 2,500,000 steps of energy evaluation and the default values of
the other parameters.
DOCK 6.5: The molecular surface of the binding site was calculated by means of the MS program [30],
generating the Connolly surface with a probe with a radius of 1.4 Å. The points of the surface and the
vectors normal to it were used by the Sphgen program in order to build a set of spheres, with radii
varying from 1.4–4 Å that describe, from a stereoelectronic point of view, the negative image of the site.
Spheres within a radius of 10 Å from the reference ligand were used to represent the site. For each ligand,
DOCK 6.5 calculated 500 orientations; among them, the best grid scored was taken into consideration.
The grid-based score is based on the non-bonded terms of the molecular mechanic force field.
GLIDE 5.0: The binding site was defined by a rectangular box of 10 Å in the x, y and z directions
centered on the ligand. The possibility of imposing a maximum number of atoms a ligand may have if
it were to be docked was deactivated, so that all of the ligands were docked independently from the
number of their atoms, whereas the GLIDE [31] defaults were used for all other parameters. The
docking analysis was carried out using the standard precision (SP) methods.
GOLD 5.1: The region of interest for the docking studies was defined in such a manner that it
contained all residues that stayed within 10 Å from the ligand in the X-ray structures; the “allow early
termination” command was deactivated, while the possibility for the ligand to flip ring corners was
activated. For all other parameters, GOLD [32] defaults were used, and the ligands were subjected to
30 genetic algorithm runs by applying the ChemPLP fitness functions.
Consensus docking evaluation: By applying the four docking software, four different binding
dispositions (best-scored docking pose) resulted from the docking of each ligand into each protein
binding site. The RMSD of each of these docking poses against the remaining three was evaluated by
using the rms_analysis software of the GOLD suite. On this basis, for each ligand docked into each
protein binding site, a 4 × 4 matrix was generated reporting the RMSD results. By using an in-house

Molecules 2015, 20
8783
program, these results were clustered, so that among the four results, all of the similar docking poses
were clustered together. As a clustering algorithm, we used the complete-linkage method, which is an
agglomerative type of hierarchical clustering. This method starts considering each element in a cluster
of its own. The clusters are then sequentially combined into larger ones, until all elements are in the
same cluster. At each step, the two clusters separated by the shortest distance are combined. We
selected an RMSD clustering threshold of 2.0 Å, therefore, the so-obtained clusters contained the
group of poses that are less than 2.0 Å away from all others poses belonging to the same cluster. All of
the ligands showing a consensus level of four were taken into account.
Database generation: The 18 Maximum Unbiased Validation datasets of decoys were prefiltered by
selecting only compounds with a molecular weight between 315 and 560 g/mol. The retained compounds
belonging to the different datasets were collected in a unique decoy dataset of 167,320 molecules, and
10,000 of them were randomly chosen for the enriched dataset evaluation analysis. The database was
then enriched with 93 known active LDH inhibitors and subjected to the four docking procedures
described above.
Virtual screening evaluation: The VS results were assessed through the use of the enrichment factor
(EF) and the area under curve (AUC) of the receiver operator characteristic (ROC) curve. The EF
measures the enrichment of the method compared with random selection:
EF = [tp/(tp + fn)](NCtot/NC)
where tp is the number of known active ligands retrieved (true positives); fn is the number of known
active ligands discarded during the VS filtering (false negatives); NCtot is the total number of
compounds of the database; NC is the total number of molecules obtained by the VS protocol [33].
The EF1%, EF5% and EF10% indicate the EF values retaining the 1%, 5% and 10% of the whole
database. The maximum value that can be reach is 100 (EF1%), 20 (EF5%) and 10 (EF10%); therefore, all
of the evaluated EF results were reported as the percentage of these values. The AUC is the area under
the ROC curve; an AUC of 0.5 corresponds to a random discrimination between actives and decoys,
whereas an AUC very close to 1.0 corresponds to an ideal case, in which all of the known true actives
are ranked before all of the decoys.
Molecular dynamics simulations: All simulations were performed using AMBER 11 [34]. The
complexes were placed in a rectangular parallelepiped water-box, an explicit solvent model for water
(TIP3P) was used; the complexes were solvated with a 10-Å water cap. Chlorine ions were added as
counterions to neutralize the system. Prior to MD simulations, two steps of minimization were carried
out using the same procedure described above. Particle mesh Ewald electrostatics and periodic
boundary conditions were used in the simulation [35]. The MD trajectories were run using the
minimized structures as the starting conformations. The time step of the simulations was 2.0 fs with a
cutoff of 10 Å for the non-bonded interaction, and SHAKE was employed to keep all bonds involving
hydrogen atoms rigid. Constant-volume periodic boundary MD was carried out for 300 ps, during
which the temperature was raised from 0 to 300 K. Then, 1.7 ns of constant pressure periodic boundary
MD was carried out at 300 K by using the Langevin thermostat to maintain the temperature of our
system constant. General Amber force field (GAFF) parameters were assigned to the ligands, while
partial charges were calculated using the AM1-BCC method. The MD trajectories were analyzed by
using the Ptraj suite of AMBER 11. The ligand’s disposition was monitored, and by using the docking

Molecules 2015, 20
8784
result as a reference pose, all of the ligands that showed an average RMSD greater than 2 Å with
respect to the reference disposition were discarded.
3.2. Chemistry
3.2.1. General
Commercially available chemicals were purchased from Sigma-Aldrich or Alfa Aesar and used
without further purification. Proton (1H) and carbon (13C) NMR spectra were obtained with a Bruker
Avance III 400 MHz spectrometer. Chemical shifts (δ) are reported in parts per million downfield
from tetramethylsilane and referenced from solvent references. Chromatographic separations were
performed on silica gel columns by flash chromatography (Kieselgel 60, 0.040–0.063 mm; Merck).
Reactions were followed by thin-layer chromatography (TLC) on Aldrich aluminum silica gel (F254)
sheets that were visualized under a UV lamp. Evaporation was performed in vacuo (rotating evaporator).
Sodium sulfate was always used as the drying agent. Yields refer to isolated and purified products.
3.2.2. Synthetic Procedures
Methyl 4-aminobenzoate (5): Commercially available 4-aminobenzoic acid 4 (500 mg, 3.65 mmol)
was dissolved in 12.5 mL of methanol, followed by a dropwise addition of sulfuric acid (0.02 mL), and
the mixture was refluxed for 48 h. The reaction mixture was cooled to room temperature, and after
evaporation of the solvent, the mixture was diluted with water and extracted with EtOAc. The organic
phase was dried and concentrated to afford a crude reaction product, which was subjected to flash
column chromatography (n-hexane/EtOAc 7:3) providing the desired Compound 5 as a white
crystalline solid (499 mg, 3.30 mmol, 90% yield). 1H-NMR (CDCl3): 3.85 (s, 3H), 6.64 (AAʹXXʹ, 2H,
JAX = 8.8 Hz, JAAʹ/XXʹ = 2.3 Hz), 7.85 (AAʹXXʹ, 2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.3 Hz).
Methyl 4-((2-hydroxyethyl)amino)benzoate (6): A mixture of methyl ester 5 (200 mg, 1.32 mmol) and
2-iodoethanol (0.07 mL, 0.9 mmol) was heated at 90 °C in a sealed vial for 6 h. The resulting solid was
dissolved in ethyl acetate and washed with 2 M aqueous NaOH solution and brine, then dried over
Na2SO4. The solvent was removed under reduced pressure, and the concentrated mixture was purified
by flash column chromatography (n-hexane/EtOAc 1:1) to obtain the pure amino alcohol 6 as an
off-white solid (122 mg, 0.625 mmol, 71% yield). 1H-NMR (CDCl3): 3.37 (t, 2H, J = 5.2 Hz), 3.86 (s,
3H), 3.88 (t, 2H, J = 5.2 Hz), 6.63 (AAʹXXʹ, 2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.3 Hz), 7.87 (AAʹXXʹ, 2H,
JAX = 8.9 Hz, JAAʹ/XXʹ = 2.3 Hz).
4-((2-Hydroxyethyl)amino)benzoic acid (VS1): Intermediate 6 (50.0 mg, 0.256 mmol) was dissolved in
a 1:1 mixture of THF/methanol (2.6 mL) and treated with 0.51 mL of 2 N aqueous solution of LiOH.
The reaction was monitored by TLC, and after consumption of the starting material (48 h), the solvents
of the mixture were evaporated; then, the residue was diluted with water, treated with 1 N aqueous
HCl and extracted with EtOAc. The organic phase was dried and evaporated to afford a crude residue
that was purified by flash column chromatography (n-hexane/EtOAc 3:7) to obtain the desired
1
Compound VS1 as a white solid (17.2 mg, 0.0949 mmol, 37% yield). H-NMR (CD3OD): 3.27–3.32
(m, 2H), 3.72 (t, 2H, J = 5.8 Hz), 6.62 (AAʹXXʹ, 2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.2 Hz), 7.78 (AAʹXXʹ,

Molecules 2015, 20
8785
13
2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.3 Hz). C-NMR(CD3OD): 46.21, 61.37, 112.21 (2C), 118.49, 132.76
(2C), 154.48, 170.76.
Methyl 4-(4-methylphenylsulfonamido)benzoate (7): To a solution of aniline 5 (300 mg, 1.98 mmol) in
dry CH2Cl2 (10 mL), pyridine (3.0 mmol, 0.24 mL) and catalytic DMAP (9.3 mg) were added; then,
the resulting mixture was cooled to 0 °C. Subsequently, commercially available p-toluenesulfonyl
chloride (456 mg, 2.39 mmol) dissolved in dry CH2Cl2 (4 mL) was added dropwise, and the reaction
was kept under stirring at RT overnight. The reaction mixture was acidified with 1 N aqueous HCl,
extracted with CH2Cl2, and the organic phase was dried. Evaporation under vacuum of the organic
solvent afforded a crude product, which was purified by flash column chromatography (n-hexane/Et2O
1:1) to yield the sulfonamide derivative 7 as an off-white solid (384 mg, 1.26 mmol, yield 64%). 1H-NMR
(CDCl3): 2.38 (s, 3H), 3.87 (s, 3H), 6.87 (bs, 1H), 7.12 (AAʹXXʹ, 2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.2 Hz),
7.23–7.25 (m, 2H), 7.67–7.75 (m, 2H), 7.91 (AAʹXXʹ, 2H, JAX = 8.8 Hz, JAAʹ/XXʹ = 2.2 Hz).
4-(4-Methylphenylsulfonamido)benzoic acid (VS2): Intermediate 7 (100 mg, 0.327 mmol) was
dissolved in a 1:1 mixture of THF/methanol (2.6 mL) and treated with 0.40 mL of 2 N aqueous
solution of LiOH. The reaction was monitored by TLC; 0.4 mL of 2 N LiOH were added after 24 h,
and the mixture was heated at 50 °C. After consumption of the starting material (48 h), the solvents of
the mixture were evaporated; then, the residue was diluted with water, treated with 1 N aqueous HCl
and extracted with EtOAc. The organic phase was dried and evaporated to afford a crude residue that
was purified by flash column chromatography (n-hexane/EtOAc 3:7) to obtain the desired compound
1
VS2 as a pink solid (73.0 mg, 0.251 mmol, 77% yield). H-NMR (CD3OD): 2.36 (s, 3H), 7.17
(AAʹXXʹ, 2H, JAX = 8.9 Hz, JAAʹ/XXʹ = 2.2 Hz), 7.29–7.31 (m, 2H), 7.71 (AAʹXXʹ, 2H, JAX = 8.4 Hz,
JAAʹ/XXʹ = 1.8 Hz), 7.85 (AAʹXXʹ, 2H, JAX = 8.9 Hz, JAAʹ/XXʹ = 2.2 Hz). 13C-NMR (CD3OD): 21.39,
119.78, 128.23 (4C), 130.68 (4C), 131.95, 138.03, 143.53, 145.36.
5-Phenyl-oxazolidin-2-one (9): To a solution of commercially available 2-amino-l-phenylethanol 8
(500 mg, 3.64 mmol) in CH2Cl2 (37.4 mL) was added imidazole (124 mg, 1.82 mmol) followed by
N,N-carbonyldiimidazole (620 mg, 3.82 mmol), and the reaction was stirred at room temperature
overnight. The mixture was diluted with water and extracted with CH2Cl2, then with EtOAc. The
combined organic phase was dried and evaporated to afford a crude residue, which was purified by
flash column chromatography (n-hexane/EtOAc 1:1) to obtain Compound 9 as a white solid (411 mg,
2.53 mmol, 70% yield). 1H-NMR (CDCl3): 3.55 (t, 1H, J = 8.2 Hz), 3.99 (t, 1H, J = 8.6 Hz), 5.40–5.50
(bs, 1H), 5.63 (t, 1H, J = 8.1 Hz), 7.36–7.44 (m, 5H).
Tert-Butyl 2-(2-oxo-5-phenyloxazolidin-3-yl)acetate (10). To a stirred and cooled solution of
5-phenyl-oxazolidin-2-one 9 (350 mg, 2.16 mmol) in dry DMF (3.5 mL) was added sodium hydride
(103 mg of a 60% dispersion in mineral oil, 2.57 mmol). The mixture was stirred at room temperature
for 10 minutes; then, tert-butyl bromoacetate (505 mg, 2.57 mmol) was added, and stirring was
continued for 4 h. The reaction mixture was quenched with ice and H2O, treated with 1 N aqueous HCl
and extracted with EtOAc. The organic phase was dried and concentrated to obtain a crude residue,
which was subjected to flash column chromatography (n-hexane/EtOAc 7:3) to afford alkylated
1
derivative 10 as a white solid (413 mg, 1.49 mmol, 69% yield). H-NMR (CDCl3): 1.47 (s, 9H), 3.62

Molecules 2015, 20
8786
(t, 1H, J = 7.9 Hz), 3.96 (ABq, 2H, ΔδAB = 0.05, JAB = 18.3 Hz), 4.02 (t, 1H, J = 8.5 Hz), 5.53 (t, 1H,
J = 8.2 Hz), 7.35–7.43 (m, 5H).
2-(2-Oxo-5-phenyloxazolidin-3-yl)acetic acid (VS3): To a solution of intermediate 10 (140 mg,
0.507 mmol) in CH2Cl2 (3.6 mL) was added dropwise trifluoroacetic acid (0.20 mL), and the reaction
was stirred for 26 h, then quenched with ice. After evaporation of the solvent, the residue was carefully
neutralized with an aqueous saturated solution of NaHCO3, followed by the addition of 1 M aqueous
solution of NaOH. The water phase was washed with Et2O, then treated with 1 N aqueous HCl and
finally extracted with EtOAc. The organic phase was dried, filtered and evaporated to furnish an
off-white solid. Formation of a crystalline white precipitate after the addition of hexane resulted in the
pure acid VS3 (151 mg, 0.686 mmol, 99% yield). 1H-NMR (CDCl3): 3.67 (t, 1H, J = 8.0 Hz), 4.06 (t,
1H, J = 8.5 Hz), 4.17 (ABq, 2H, ΔδAB = 0.03, JAB = 18.4 Hz), 4.43 (bs, 1H), 5.59 (t, 1H, J = 8.1 Hz),
7.39–7.43 (m, 5H). 13C-NMR (CDCl3): 45.25, 52.72, 76.10, 126.19 (2C), 129.22 (2C), 129.50, 137.67,
159.31, 172.94.
LDH assays: The LDH inhibition properties of the selected compounds were evaluated against
purified human lactate dehydrogenase isoform 5 (Lee Biosolution, Inc., St. Louis, MO, USA). The
“forward” direction (pyruvate→lactate) of the lactate dehydrogenase reaction was conducted, and the
kinetic parameters were measured by fluorescence (emission wavelength at 460 nm, excitation
wavelength at 340 nm) to monitor the amount of consumed NADH. Assays were carried out in wells
containing 200 μL of a reagent solution dissolved in 100 mM phosphate buffer (pH = 7.4). For the IC50
calculations of the compounds, seven different concentrations (in duplicate for each concentration) of
the isolated compounds were used to produce the concentration-response curve. All of the compounds
were tested in the presence of 200 μM pyruvate and 40 μM NADH. Any background fluorescence
likelihood of the tested samples, or NADH fluorescence quenching, was subtracted. In addition to the
sample test wells, maximum and minimum controls were also included in each plate. After 15 min of
incubation, the final measurements were carried out by using a Victor X3 Microplates Reader
(PerkinElmer®). IC50 values were produced using GraphPad Prism software.
Virtual Fragment Scanning: The 3,5 dinitrobenzene portion of Compound VS8 was virtually
replaced with similar fragments by using BROOD software [26]. For the analysis, the default values
were used, and the query mask was created, so that the 3,5-dinitrobenzene could be replaced only by
fragments possessing an aromatic ring connected with at least three H-bond acceptors in
correspondence to the oxygen atoms that showed interactions with R169 and T248. All of the
fragments that, when attached to Compound VS8, clashed with the protein were eliminated. The
filtered compounds were then docked by using the consensus docking procedure described above. All
of the compounds possessing a consensus level of 4 and showing H-bonds with R169 and T248 were
subjected to MD simulation, and all of the ligands that showed an average RMSD greater than 2 Å
with respect to the reference disposition were discarded.
4. Conclusions
In this preliminary work, we tested the development of a mixed ensemble/consensus docking
platform for identifying new hLDH5 inhibitors. The platform was used for filtering the University of

Molecules 2015, 20
8787
Illinois Marvel library of about 10,000 molecules, and the results were further filtered by applying MD
simulations. To experimentally verify the reliability of this procedure, ten compounds from the library,
which were predicted to be active by the above-mentioned VS study, were tested for their inhibitory
potency against hLDH5, and two compounds showed IC50 values in the high micromolar range. The
activity of the newly discovered compounds is quite low and, in another system, would not be
considered in the hit range; however, as shown in Table 2, they show an activity that is only about
3–25-fold lower than those of reference LDH inhibitors, and they are characterized by simple
molecular structures that can be further functionalized in order to improve their inhibition activity.
Taken together, these findings suggest that the optimized techniques herein reported may be suitable
for the identification of new hLDH5 inhibitors and encourage us to apply this method to other larger
databases of compounds and to further refine the VS platform. Furthermore, even if the reported active
compounds possess inhibition activities that are lower than those of reference inhibitors, it should be
considered that they are small molecules suitable as starting structures for further chemical
modifications in order to improve their enzyme inhibition potencies. Therefore, these compounds can
be considered as potential hits for the development of new hLDH5 inhibitors belonging to novel
chemical classes.
Supplementary Materials
Supplementary materials can be accessed at: http://www.mdpi.com/1420-3049/20/05/8772/s1.
Acknowledgments
We are grateful to the NIH (R01GM098453) and the University of Pisa (Progetti di Ricerca di
Ateneo, PRA) for funding. Many thanks are due to Maurizio Botta for the use of the GLIDE program
in his computational laboratory (University of Siena, Italy) and to Paul J. Hergenrother (University of
Illinois) for helpful discussions and for providing us with the compounds of the Marvel library.
Author Contributions
Del Frate and Martinelli carried out the computational studies; Granchi, Capecchi, Macchia and
Minutolo synthesized the compounds, Granchi and Minutolo carried out the biological experiments
and Tuccinardi supervised the whole study.
Conflicts of Interest
The authors declare no conflict of interest.
References
1. Granchi, C.; Bertini, S.; Macchia, M.; Minutolo, F. Inhibitors of lactate dehydrogenase isoforms
and their therapeutic potentials. Curr. Med. Chem. 2010, 17, 672–697.
2. Granchi, C.; Minutolo, F. Anticancer agents that counteract tumor glycolysis. ChemMedChem
2012, 7, 1318–1350.

Molecules 2015, 20
8788
3. Granchi, C.; Fancelli, D.; Minutolo, F. An update on therapeutic opportunities offered by cancer
glycolytic metabolism. Bioorg. Med. Chem. Lett. 2014, 24, 4915–4925.
4. Granchi, C.; Paterni, I.; Rani, R.; Minutolo, F. Small-molecule inhibitors of human LDH5.
Future Med. Chem. 2013, 5, 1967–1991.
5. Granchi, C.; Roy, S.; Giacomelli, C.; Macchia, M.; Tuccinardi, T.; Martinelli, A.; Lanza, M.; Betti, L.;
Giannaccini, G.; Lucacchini, A.; et al. Discovery of N-hydroxyindole-based inhibitors of human
lactate dehydrogenase isoform A (LDH-A) as starvation agents against cancer cells. J. Med.
Chem. 2011, 54, 1599–1612.
6. Granchi, C.; Roy, S.; De Simone, A.; Salvetti, I.; Tuccinardi, T.; Martinelli, A.; Macchia, M.;
Lanza, M.; Betti, L.; Giannaccini, G.; et al. N-Hydroxyindole-based inhibitors of lactate
dehydrogenase against cancer cell proliferation. Eur. J. Med. Chem. 2011, 46, 5398–5407.
7. Granchi, C.; Roy, S.; Mottinelli, M.; Nardini, E.; Campinoti, F.; Tuccinardi, T.; Lanza, M.; Betti, L.;
Giannaccini, G.; Lucacchini, A.; et al. Synthesis of sulfonamide-containing N-hydroxyindole-2-
carboxylates as inhibitors of human lactate dehydrogenase-isoform 5. Bioorgainc Med. Chem. Lett.
2011, 21, 7331–7336.
8. Zhang, M.; Peh, J.; Hergenrother, P.J.; Cunningham, B.T. Detection of protein-small molecule
binding using a self-referencing external cavity laser biosensor. J. Am. Chem. Soc. 2014, 136,
5840–5843.
9. Calvaresi, E.C.; Granchi, C.; Tuccinardi, T.; Di Bussolo, V.; Huigens, R.W., 3rd; Lee, H.Y.;
Palchaudhuri, R.; Macchia, M.; Martinelli, A.; Minutolo, F.; et al. Dual targeting of the warburg
effect with a glucose-conjugated lactate dehydrogenase inhibitor. ChemBioChem 2013, 14,
2263–2267.
10. Di Bussolo, V.; Calvaresi, E.C.; Granchi, C.; Del Bino, L.; Frau, I.; Dasso Lang, M.C.; Tuccinardi, T.;
Macchia, M.; Martinelli, A.; Hergenrother, P.J.; et al. Synthesis and biological evaluation of
non-glucose glycoconjugated N-hydroyxindole class LDH inhibitors as anticancer agents. RSC Adv.
2015, 5, 19944–19954.
11. Calvaresi, E.C.; Hergenrother, P.J. Glucose conjugation for the specific targeting and treatment of
cancer. Chem. Sci. 2013, 4, 2319–2333.
12. Tuccinardi, T. Docking-based virtual screening: Recent developments. Comb. Chem. High
Throughput Screen. 2009, 12, 303–314.
13. Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.;
Bourne, P.E. The protein data bank. Nucleic Acids Res. 2000, 28, 235–242.
14. Read, J.A.; Winter, V.J.; Eszes, C.M.; Sessions, R.B.; Brady, R.L. Structural basis for altered
activity of M- and H-isozyme forms of human lactate dehydrogenase. Proteins 2001, 43, 175–185.
15. Ward, R.A.; Brassington, C.; Breeze, A.L.; Caputo, A.; Critchlow, S.; Davies, G.; Goodwin, L.;
Hassall, G.; Greenwood, R.; Holdgate, G.A.; et al. Design and synthesis of novel lactate
dehydrogenase a inhibitors by fragment-based lead generation. J. Med. Chem. 2012, 55, 3285–3306.
16. Fauber, B.P.; Dragovich, P.S.; Chen, J.; Corson, L.B.; Ding, C.Z.; Eigenbrot, C.; Giannetti, A.M.;
Hunsaker, T.; Labadie, S.; Liu, Y.; et al. Identification of 2-amino-5-aryl-pyrazines as inhibitors
of human lactate dehydrogenase. Bioorg. Med. Chem. Lett. 2013, 23, 5533–5539.

Molecules 2015, 20
8789
17. Tuccinardi, T.; Poli, G.; Romboli, V.; Giordano, A.; Martinelli, A. Extensive consensus docking
evaluation for ligand pose prediction and virtual screening studies. J. Chem. Inf. Model. 2014, 54,
2980–2986.
18. Dragovich, P.S.; Fauber, B.P.; Corson, L.B.; Ding, C.Z.; Eigenbrot, C.; Ge, H.; Giannetti, A.M.;
Hunsaker, T.; Labadie, S.; Liu, Y.; et al. Identification of substituted 2-thio-6-oxo-1,6-
dihydropyrimidines as inhibitors of human lactate dehydrogenase. Bioorg. Med. Chem. Lett. 2013,
23, 3186–3194.
19. Dragovich, P.S.; Fauber, B.P.; Boggs, J.; Chen, J.; Corson, L.B.; Ding, C.Z.; Eigenbrot, C.; Ge, H.;
Giannetti, A.M.; Hunsaker, T.; et al. Identification of substituted 3-hydroxy-2-mercaptocyclohex-
2-enones as potent inhibitors of human lactate dehydrogenase. Bioorg. Med. Chem. Lett. 2014, 24,
3764–3771.
20. Fauber, B.P.; Dragovich, P.S.; Chen, J.; Corson, L.B.; Ding, C.Z.; Eigenbrot, C.; Labadie, S.;
Malek, S.; Peterson, D.; Purkey, H.E.; et al. Identification of 3,6-disubstituted dihydropyrones as
inhibitors of human lactate dehydrogenase. Bioorg. Med. Chem. Lett. 2014, 24, 5683–5687.
21. Labadie, S.; Dragovich, P.S.; Chen, J.; Fauber, B.P.; Boggs, J.; Corson, L.B.; Ding, C.Z.;
Eigenbrot, C.; Ge, H.; Ho, Q.; et al. Optimization of 5-(2,6-dichlorophenyl)-3-hydroxy-2-
mercaptocyclohex-2-enones as potent inhibitors of human lactate dehydrogenase. Bioorg. Med.
Chem. Lett. 2015, 25, 75–82.
22. Rohrer, S.G.; Baumann, K. Maximum unbiased validation (MUV) data sets for virtual screening
based on pubchem bioactivity data. J. Chem. Inf. Model. 2009, 49, 169–184.
23. Poli, G.; Giuntini, N.; Martinelli, A.; Tuccinardi, T. Application of a flap-consensus docking mixed
strategy for the identification of new fatty acid amide hydrolase inhibitors. J. Chem. Inf. Model.
2015, 55, 667–675.
24. Manerba, M.; Vettraino, M.; Fiume, L.; Di Stefano, G.; Sartini, A.; Giacomini, E.; Buonfiglio, R.;
Roberti, M.; Recanatini, M. Galloflavin (cas 568–80–9): A novel inhibitor of lactate dehydrogenase.
ChemMedChem 2012, 7, 311–317.
25. Granchi, C.; Calvaresi, E.C.; Tuccinardi, T.; Paterni, I.; Macchia, M.; Martinelli, A.;
Hergenrother, P.J.; Minutolo, F. Assessing the differential action on cancer cells of LDH-A
inhibitors based on the N-hydroxyindole-2-carboxylate (NHI) and malonic (Mal) scaffolds.
Org. Biomol. Chem. 2013, 11, 6588–6596.
26. Brood, version 2.0.0; OpenEye Scientific Software: Santa Fe, NM, USA. Available online:
http://www.eyesopen.com (accessed on 4 April 2015).
27. Ligprep, version 2.5; Schrödinger Inc: Portland, OR, USA, 2011.
28. Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J.
Autodock4 and autodocktools4: Automated docking with selective receptor flexibility.
J. Comput. Chem. 2009, 30, 2785–2791.
29. Morris, G.M.; Goodsell, D.S.; Halliday, R.S.; Huey, R.; Hart, W.E.; Belew, R.K.; Olson, A.J.
Automated docking using a lamarckian genetic algorithm and an empirical binding free energy
function. J. Comput. Chem. 1998, 19, 1639–1662.
30. Dock, version 6.5; Molecular Design Institute, University of California: San Francisco, CA,
USA, 1998.
31. Glide, version 5.0; Schrödinger Inc: Portland, OR, USA, 2009.

Molecules 2015, 20
8790
32. Verdonk, M.L.; Mortenson, P.N.; Hall, R.J.; Hartshorn, M.J.; Murray, C.W. Protein-ligand
docking against non-native protein conformers. J. Chem. Inf. Model. 2008, 48, 2214–2225.
33. Poli, G.; Tuccinardi, T.; Rizzolio, F.; Caligiuri, I.; Botta, L.; Granchi, C.; Ortore, G.; Minutolo, F.;
Schenone, S.; Martinelli, A. Identification of new fyn kinase inhibitors using a flap-based
approach. J. Chem. Inf. Model. 2013, 53, 2538–2547.
34. Case, D.A.; Darden, T.A.; Cheatham, T.E.; Simmerling, C.L.; Wang, J.; Duke, R.E.; Luo, R.;
Walker, R.C.; Zhang, W.; Merz, K.M.; et al. Amber, version 11; University of California:
San Francisco, CA, USA, 2010.
35. York, D.M.; Darden, T.A.; Pedersen, L.G. The effect of long-range electrostatic interactions in
simulations of macromolecular crystals—A comparison of the ewald and truncated list methods.
J. Chem. Phys. 1993, 99, 8345–8348.
Sample Availability: Not available.
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/).