Computational Evaluation and In Vitro Validation of New Epidermal Growth Factor Receptor Inhibitors

Abstract

Background:
The Epidermal Growth Factor Receptor (EGFR) is a transmembrane protein that acts as a receptor of extracellular protein ligands of the epidermal growth factor (EGF/ErbB) family. It has been shown that EGFR is overexpressed by many tumours and correlates with poor prognosis. Therefore, EGFR can be considered as a very interesting therapeutic target for the treatment of a large variety of cancers such as lung, ovarian, endometrial, gastric, bladder and breast cancers, cervical adenocarcinoma, malignant melanoma and glioblastoma.

Methods:
We have followed a structure-based virtual screening (SBVS) procedure with a library composed of several commercial collections of chemicals (615,462 compounds in total) and the 3D structure of EGFR obtained from the Protein Data Bank (PDB code: 1M17). The docking results from this campaign were then ranked according to the theoretical binding affinity of these molecules to EGFR, and compared with the binding affinity of erlotinib, a well-known EGFR inhibitor. A total of 23 top-rated commercial compounds displaying potential binding affinities similar or even better than erlotinib were selected for experimental evaluation. In vitro assays in different cell lines were performed. A preliminary test was carried out with a simple and standard quick cell proliferation assay kit, and six compounds showed significant activity when compared to positive control. Then, viability and cell proliferation of these compounds were further tested using a protocol based on propidium iodide (PI) and flow cytometry in HCT116, Caco-2 and H358 cell lines.

Results:
The whole six compounds displayed good effects when compared with erlotinib at 30 μM. When reducing the concentration to 10μM, the activity of the 6 compounds depends on the cell line used: the six compounds showed inhibitory activity with HCT116, two compounds showed inhibition with Caco-2, and three compounds showed inhibitory effects with H358. At 2 μM, one compound showed inhibiting effects close to those from erlotinib.

Conclusion:
Therefore, these compounds could be considered as potential primary hits, acting as promising starting points to expand the therapeutic options against a wide range of cancers.

Full text

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Current Topics in Medicinal Chemistry, 2020, 20, 1-12 1
RESEARCH ARTICLE
1568-0266/20 $65.00+.00 © 2020 Bentham Science Publishers
Computational Evaluation and In Vitro Validation of New Epidermal
Growth Factor Receptor Inhibitors
Sergi Gómez-Ganau1,#, Josefa Castillo2,3, Andrés Cervantes2, Jesus Vicente de Julián-Ortiz4 and
Rafael Gozalbes1,5,*
1ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, Avenida Ben-
jamín Franklin 12, 46980 Paterna (Valencia, Spain); 2Departmento de Oncología Médica, Instituto de Investigación
Biomédica INCLIVA, Universidad de Valencia (Spain); 3Departamento de Bioquímica y Biología Molecular, Universi-
dad de Valencia (Spain); 4Departmento de Química Física, Facultad de Farmacia, Universidad de Valencia (Spain);
5MolDrug AI Systems SL, c/Olimpia Arozena Torres 45, 46018 Valencia (Spain)
A R T I C L E H I S T O R Y
Received: February 03, 2020
Revised: February 15, 2020
Accepted: February 20, 2020
DOI:
10.2174/1568026620666200603122726
Abstract: The epidermal growth factor receptor (EGFR) is a transmembrane protein that acts as a recep-
tor of extracellular protein ligands of the epidermal growth factor (EGF/ErbB) family. It has been shown
that EGFR is overexpressed by many tumours and correlates with poor prognosis. Therefore, EGFR can
be considered as a very interesting therapeutic target for the treatment of a large variety of cancers such
as lung, ovarian, endometrial, gastric, bladder and breast cancers, cervical adenocarcinoma, malignant
melanoma and glioblastoma.
We have followed a structure-based virtual screening (SBVS) procedure with a library composed of
several commercial collections of chemicals (615,462 compounds in total) and the 3D structure of
EGFR obtained from the Protein Data Bank (PDB code: 1M17). The docking results from this campaign
were then ranked according to the theoretical binding affinity of these molecules to EGFR, and com-
pared with the binding affinity of erlotinib, a well-known EGFR inhibitor.
A total of 23 top-rated commercial compounds displaying potential binding affinities similar or even
better than erlotinib were selected for experimental evaluation. In vitro assays in different cell lines were
performed. A preliminary test was carried out with a simple and standard quick cell proliferation assay
kit, and six compounds showed significant activity when compared to positive control. Then, viability
and cell proliferation of these compounds were further tested using a protocol based on propidium io-
dide (PI) and flow cytometry in HCT116, Caco-2 and H358 cell lines. The whole six compounds dis-
played good effects when compared with erlotinib at 30 µM. When reducing the concentration to 10
µM, the activity of the 6 compounds depends on the cell line used: the six compounds showed inhibitory
activity with HCT116, two compounds showed inhibition with Caco-2, and three compounds showed
inhibitory effects with H358. At 2 µM, one compound showed inhibiting effects close to those from er-
lotinib. Therefore, these compounds could be considered as potential primary hits, acting as promising
starting points to expand th e therapeutic options against a wide range of cancers.
Keywords: Drug design, EGFR, docking, virtual screening.
1. INTRODUCTION
The EGF/ErbB family of type 1 receptor tyrosine kinases
(RTKs) is expressed in different cell types mediating numer-
ous physiological processes like differentiation, prolifera-
tion, migration or cellular survival [1]. The EGF/ErbB fam-
ily consists of four different proteins (EGFR, HER2, HER3,
and HER4) which share a similar molecular architecture with
*Address correspondence to this author at the ProtoQSAR SL, Centro Euro-
peo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia,
Avenida Benjamín Franklin 12, 46980 Paterna (Valencia, Spain) and Mol-
Drug AI Systems SL, c/Olympia Arozena Torres 45, 46018 Valencia
(Spain); E-mail: rgozalbes@protoqsar.com, rgozalbes@moldrug.com
#Current address: Eurofins Agroscience Services Regulatory Spain S.L.,
46015 Valencia (Spain)
the other 58 known human RTKs, and which can form
homo- and heterodimers with one another [2-4]. Enhanced
signaling from these receptors leads to the development of a
large diversity of pathologic conditions [5,6].
The best-characterized receptor molecule is the epidermal
growth factor receptor (EGFR), which is found in the cell
membrane [7]. EGFR has been identified as key to the proc-
esses of growth and proliferation of normal cells, cell signal-
ing and angiogenesis [8,9]. Therefore, any disorder in EGFR
regulation leads to cellular imbalance, being its overexpres-
sion one of the major causes of many types of cancers, such
as pancreas, breast, colon, bladder, kidney, neck, head,
ovary, and gliomas [10].

2 Current Topics in Medici nal Chemistry, 2020, Vol. 20, No. 18 Gómez-Ganau et al.
1.1. EGFR Structure and Activation
EGFR is an 1186 amino acid single-pass transmembrane
glycoprotein synthesized from a polypeptide precursor that is
cleaved at the N-terminal. From N-terminal to C-terminal,
EGFR is structurally and functionally divided into different
parts (Fig. 1): an extracellular ligand-binding domain and
dimerization arm, a hydrophobic transmembrane region, and
an intracellular cytoplasmic tyrosine kinase region which is
the most conserved domain in the family (excluding HER3)
[11-14].
Fig. (1). Schematic structure of EGFR. (A higher resolution / col-
our version of this figure is available in the electronic copy of the
article).
The extracellular region of EGFR consists of 621 amino
acids separated into four distinct protein domains (domains I
to IV). Domains I and III are two-homologous large leucine-
rich domains participating in ligand binding. Domains II and
IV are glycine-rich and responsible for the dimerization of
EGFR following ligand-induced activation.
The transmembrane region is a 23 amino acid long hy-
drophobic single-pass membrane structure [15]. It holds the
receptor to the membrane and it is thought to play a signifi-
cant role in dimerization.
The intracellular region includes the juxtamembrane
segment, the C-terminal tail and the tyrosine kinase domain
with an ATP-binding site situated between a N-lobe (mainly
a β-sheet structure) and a C-lobe (mainly an α-sheet struc-
ture) [16].
The activation of the EGF/ErbB family of RTKs is medi-
ated by the union of different natural ligands (Fig. 2): EGF,
transforming growth factor-α (TFG- α), amphiregulin (AR),
epiregulin (EPR), betacellulin (BTC), heparin-binding EGF-
like growth factor (HB-EGF), epigen (EPG) and neuregulins
(NRGs). EGF, TFG- α, EPG and AREG are agonists activat-
ing specifically EGFR. BTC, HB-EGF, and EPR show speci-
ficity for both EGFR and HER4. NRGs have dual specificity
for both HER3 and Her4 or only HER4, depending on the
subclass [17,18]. HER2 does not contain a ligand-binding
domain, and in consequence, no direct ligand has been iden-
tified for it.
Fig. (2). EGF/ErbB family ligands divided according to the EGF
receptor where they act. (A higher resolution / colour version of this
figure is available in th e electronic copy of the article).
Ligand binding and EGFR dimerization are crucial for
EGFR activation. Nowadays, it is well accepted that EGFR
exists in a monomeric form at the cell surface before ligand
binding [16,19]. The union of the ligand to the extracellular
domain of EGFR induces dimerization of the receptor
monomer, and as a result, the intracellular kinase domains
become closer and trans-autophosphorylate one another in
the dimeric state. It should be noted that in the activation of
EGFR, the ligand does not act directly to the dimerization
interface, so it is considered “receptor mediated” differing
from the others RTKs where the ligand acts as a bridge be-
tween receptors to form the dimer.
Once the cytosolic domain becomes auto phosphorylated,
it serves as a docking site for the downstream signaling pro-
teins (such as viral sarcoma oncogene homolog (SRC), ho-
mology 2 (SH2) or phosphotyrosine binding (PTB)), initiat-
ing and modulating complex signaling cascades [19]. Muta-
tions that lead to EGFR overexpression or overactivity have
been associated with cancer, cell proliferation, reduced apop-
tosis, invasion and metastasis and also stimulating tumour-
induced angiogenesis [20-26].
1.2. EGFR Targeted Therapies
The identification of EGFR as a validated therapeutic
target and its involvement in diverse cellular processes
opened the door to the development of biological agents ca-
pable of disrupting its signaling pathway. Currently, two
distinct approaches are employed for targeting EGFR in
various human diseases: anti-EGFR monoclonal antibodies
(mAbs) that act in the extracellular domain, and small-
molecule EGFR tyrosine kinase inhibitors (TKIs), acting in
the intracellular domain.
The EGFR-TKIs are reversible or irreversible small and
low molecular weight molecules developed to be adenosine
triphosphate analogues (ATP) [17,27]. They compete with
ATP through the union to ATP binding pockets on the intra-
cellular catalytic kinase domain of RTKs, and prevent the
EGFR autophosphorylation and activation of several down-
stream signaling pathways.

Computational Evaluation and In Vitro Validation Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 3
So far, several inhibitors have been developed that have
proven to be clinically effective [28-30]. Erlotinib (Fig. 3) is
an orally available reversible potent inhibitor of the human
EGFR tyrosine-kinase [31]. It has quinazoline nature, and as
other TKIs, it competes with ATP binding pockets within the
RTKs exerting anti-proliferative effects, cell-cycle arrest and
apoptosis. Active at nanomolar concentrations, it is currently
approved for NSCLC when the first line of chemotherapy
has been declined, as well as for locally advanced, unre-
sectable or metastatic pancreatic cancer patients in combina-
tion with gemcitabine.
Fig. (3). Erlotinib.
Gefitinib (Fig. 4) is an orally active low-molecular
weight EGFR inhibitor with selective tyrosine kinase activity
but without serine-threonine kinase activity [32]. Developed
from anilinoquinazoline, currently it is approved for patients
with NSCLC when the first-line therapy (platinum-based or
docetaxel) has failed.
Fig. (4). Gefitinib.
In addition to these approved drugs, other inhibitors of
EGFR tyrosine kinase activity (canertinib, lapatinib, etc.) are
under study to find new active molecules to treat other hu-
man malignancies. Moreover, a safety profile of these tar-
geted strategies needs to be considered because the use of
EGFR inhibitors can lead to cutaneous toxicities (rashes).
1.3. EGFR Resistance
The main problem in therapy against malignancies asso-
ciated with EGFR mutations is the occurrence of drug resis-
tance. Different reasons and mechanisms are possible, such
as the secondary mutation (TM790M), alternative pathways
(c-Met, HGF, etc.), aberrance of the downstream pathways
(K-RAS mutations, loss of PTEN), impairment of the
EGFR–TKIs-mediated apoptosis pathway [33-35]. There-
fore, new EGFR-TKIs are needed in order to overcome the
most common mechanisms of resistance, as well as new
concepts on EGFR signal transduction inhibition by combin-
ing EGFR-TKIs with therapies that target EGFR mecha-
nisms. The critical barrier to progress in the field is that the
proposed inhibitors are ineffective when resistance mecha-
nisms are launched. To be effective, the inhibitors should
simultaneously act on different targets in the same EGFR
signaling route, and also act on the resistance mechanisms
before they manifest.
1.4. Computational Approaches
Computational methods are commonly used in drug dis-
covery projects when designing hits/leads for complex dis-
eases is required [36,37]. With these methods, we are able to
simulate the mechanism of action of drugs, predict the thera-
peutic efficacy in humans, optimize the pharmacokinetic
properties of chemicals, validate new targets and reduce the
secondary effects of drugs. These methods are part of the
research strategies within the pharmaceutical industry due to
the reduction of costs and time, and the easier and faster ap-
plicability of the models to large libraries of chemicals. Fur-
thermore, these techniques facilitate the fulfillment of the
European directives about the reduction/replacement of ani-
mal assays [38].
There are various computational or “in silico” approaches
available, and the use of one or another depends on the dif-
ferent information available at the beginning of each project.
One of the most common molecular modeling methods is
docking [39], that is, the study of the close relationships
(steric, electronic, etc.) established between a ligand and its
target considering their three-dimensional structure. Docking
simulations play an important role when the features of the
interactions between the ligand and the protein receptor need
to be elucidated. In addition, it allows us to predict the pre-
ferred orientation of a stable ligand-protein complex as well
as interpreting the action mechanisms of biologically active
compounds.
One of the main applications of docking is the develop-
ment of structure-based virtual screening (SBVS) ap-
proaches, that is, the systematic docking of a large library of
small molecule compounds in a target structure in a fast way.
Each compound in the library is virtually docked into the
binding site of the receptor protein, and thanks to specifically
tailored mathematical algorithms, the fit between the docked
compounds and the target can be evaluated in order to dis-
tinguish which compounds are better candidates for later
experimental assays.
Considering these circumstances, we have developed a
study to find completely novel chemicals that can act as po-
tential hits inhibiting EGFR. The search for these com-
pounds was carried out by a SBVS approach with the three-
dimensional structure of EGFR, to analyse the different in-
teractions between ligand-receptor within databases of thou-
sands of compounds commercially available. Further studies
on the different interactions between the best candidates and
EGFR were carried out, and compared with the interactions
responsible for the activity of the known inhibitor erlotinib
(Tarceva®). In addition, to achieve the goal of the project, in
vitro assays in EGFR cell lines were carried out to confirm
the predictive ability of the models, and to select the best hits
for further development as potential new drugs.
2. MATERIALS AND METHODS
2.1. Collection of Compounds
A data set composed of 615,462 commercially available
compounds from different suppliers was compiled from the
ZINC database (http://zinc.docking.org). The ZINC database
is a suitable, easy to access collection of purchasable com-
pounds that currently includes over 35 million molecular

4 Current Topics in Medici nal Chemistry, 2020, Vol. 20, No. 18 Gómez-Ganau et al.
structures in ready-to-dock formats. Each molecule has been
assigned biologically relevant protonation states and is regis-
tered with different properties such as molecular weight or
number of rotatable bonds. The information of the vendor is
added, and the structure is available for free download in
different formats (2D, 3D SDF, SMILES, etc.). Therefore,
all compounds are already prepared for docking and SBVS
purposes without needing any minimization or conforma-
tional change in the ligand.
2.2. Crystal Structure of the Receptor
The crystal 3D structure of EGFR co-crystallized with
the kinase inhibitor erlotinib (placed inside the ATP binding
site) with the code 1M17 was selected from the Protein Data
Bank (PDB, www.rcsb.org/pdb/home/home.do) (Fig. 5). For
docking purposes, the residues around erlotinib were se-
lected, and the co-crystallized ligand and water molecules
were deleted.
Fig. (5). Epidermal growth factor receptor kinase (EGFR). PDB-
code: 1M17. Co-crystallized ligand: [6,7-bis(2-methoxy-ethoxy)
quinazoline-4-yl] -(3-ethynylphenyl) amine (erlotinib). (A higher
resolution / colour version of this figure is available in the elec-
tronic copy of the article).
2.3. Docking and Scoring Approach
A standard docking of the above-mentioned ZINC com-
pounds was carried out on the EGFR structure extracted
from the PDB. The site of the union was the ATP binding
site where erlotinib was situated (Fig. 6) on a radius of 10 Å.
Water molecules were deleted because all EGFR-TK struc-
tures contain no conserved position for water molecules.
The primary docking program employed in this study
was iGEMDOCK (http://gemdock.life.nctu.edu.tw), which
was used a) for the determination of the coordinates of target
atoms in the PDB structure from the ligand-binding area
close to erlotinib, b) as the interface to search by SBVS for
potential inhibitors on EGFR ATP binding site, and c) to
analyse the post-virtual screening results. Pymol
(https://pymol.org/) and BIOVIA Discovery Studio Visual-
izer (http://accelrys.com/products/collaborative-science/ bio-
via-discovery-studio/) were employed to visualize the recep-
tor and ligand structures. BIOVIA Discovery Studio Visual-
izer was also used for deleting waters of the receptor 3D
structure (pdbqt file) and to extract the ligand erlotinib for
re-docking.
Fig. (6). Erlotinib situated in the ligand binding area. (A higher
resolution / colour version of this figure is available in the elec-
tronic copy of the article).
Erlotinib was suppressed when docking the ZINC struc-
tures, but it was re-docked on EGFR in order to compare its
binding affinity results with those of ZINC compounds.
iGemDock is based on a previous program from the same
authors, GemDock, which uses an empirical scoring function
and a generic evolutionary method (GA). The Gemdock en-
ergy function consists of electrostatic, steric, and hydrogen-
bonding potentials. Additionally, it may be run as either a
purely flexible or hybrid docking approach. In our study, we
developed a hybrid docking where the ligand was flexible
and the receptor was rigid.
After the SBVS procedure, the chemistry of the top-
ranked molecules was checked in order to select a short list
of compounds as structurally diverse as possible.
2.4. In Vitro Assays
In vitro inhibition assays were developed for the deter-
mination of the activity of a short list of compounds selected
from the SBVS. Three different types of cells were used:
HCT 116 and Caco-2 from human colon and H358 from
human lung.
The Quick Cell Proliferation Assay kit ab65473 from
Abcam® was used for fast and sensitive quantification of
cell proliferation and viability. The kit was selected because
of its simple application, demanding no washing, no harvest-
ing and no solubilization assays. The assay is based on the
cleavage of the tetrazolium salt WST-1 to formazan by cellu-
lar mitochondrial dehydrogenases. An increase in the activity
of the mitochondrial dehydrogenases due to the expansion of
viable cells leads to an increase in the amount of formazan
dye formed. The formazan dye generated from viable cells
can be later determined by a multi-well spectrophotometer
(microtiter plate reader) by measuring the absorbance of the
dye solution at 440 nm.
Compounds were solubilized in DMSO (50 mM or 100
mM depending on its solubility), and were tested in the HCT
cell line at 100 µm, 50 µm and 10 µm during 48 hours.

Computational Evaluation and In Vitro Validation Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 5
For a more precise evaluation to measure cell death, a
protocol based on the use of propidium iodide and flow cy-
tometry was performed. Propidium iodide (PI) is a small
fluorescent molecule that binds DNA but cannot passively
traverse into cells with the plasma membrane intact. Because
of that, it is possible to differentiate between dead cells
(permeable membrane) from live cells (intact membrane).
Lasers and photodetectors in flow cytometers and micro-
scopes using rhodamine (red) filter can detect the light emit-
ted by PI.
The flow cytometry analysis was carried out using an
Accuri C6 (BD Biosciences, US) that is equipped with a 20
mW solid-state blue laser (488 nm), a 17.4 mW red laser
diode (640 nm) two light scattering detectors (FSC and SSC)
and four fluorescence detectors. These channels are a band-
pass filter of 533/30 nm (FL1), a band-pass filter of 585/40
nm (FL2), a high-pass filter of 670 nm (FL3) and another
high-pass filter (675/25 nm (FL4)). Data is digitally col-
lected in a dynamic range of six decades.
To perform the assay, 105 cells/mL of HCT 116, H358
and caco-2 cell lines were suspended in culture media. 200
µL of cell suspension were dispensed in the wells with 5% of
fetal bovine serum (FBS) culture media. The plates were
incubated at 37ºC for 24 hours and treated with different
concentrations of compounds for 72 hours. After 72 hours,
the supernatant was recollected in order not to lose necrotic
and apoptotic cells and the wells were washed with 50 µL of
PBS. 50 µL of trypsin EDTA at 25% was added to each well.
After that, a 37ºC incubation for five minutes was per-
formed, and 100 µL of PI solution was added. The final con-
centration of PI in each well was 2.5 µg/mL. After incuba-
tion at room temperature for 5 minutes, cells were analysed
by flow cytometry and observed by fluorescent microscope.
3. RESULTS AND DISCUSSION
3.1. SBVS
SBVS for the 615,462 compounds was carried out using
iGEMDOCK, and 23 of the tested molecules (Table 1) were
selected for experimental assays depending on various pa-
rameters, such as potential binding affinity, conformation
inside the ATP binding site, and chemical diversity.
Table 2 shows the total binding energy and Van der
Waals, hydrogen bond energies for the selected 23 chemi-
cals. Additionally, the values for the re-docked erlotinib are
showed to facilitate the comparison between the selected
compounds and this well-known inhibitor. The compounds
were ranked by their total energy.
Our selection includes compounds with higher total en-
ergy than erlotinib and others with lower total energy. The
decision about taking into account some compounds with
lower energy is the result of the balance with the other
parameters in our study. A lot of compounds that obtained
higher total energy in the SBVS were in fact structurally
similar, and thus they were discarded in order to select only
one chemotype each time. With this decision, we wished to
increase the chances of obtaining future hits.
All 23 compounds showed high binding energies with
EGFR and established a network of molecular interactions
(electrostatic, H-bond, van der Waals, hydrophobic) with the
active-site residues of EGFR (Fig. 7).
The interaction energies between the amino acids of the
ligand-binding site and the atoms for compound 21 and re-
docked erlotinib are displayed in Table 3. The table shows
Van der Waals interactions and hydrogen bond energies
from both erlotinib and compound 21. As showed in Table 3
and in the 2D diagram of (Fig. 8), the re-docked erlotinib
tends to interact with almost all the amino acids considered
important in the bibliography for the inhibition of EGFR:
Leu 694, Thr 766, Met 769, Gly 772 and Leu 820.
After docking compound 21 was aligned with erlotinib
inside the ATP binding site of EGFR (Fig. 9). Both com-
pounds fit in a similar manner in the pocket.
Additionally, interactions for compound 21 are also
shown in Table 3 and Fig. (10). As can be seen, compound
21 interacts with most of the same amino acids than er-
lotinib. However, the Van der Waals and hydrogen interac-
tion energy are quite higher for the most important amino
acids in the ATP binding site which makes total energy
higher than erlotinib at the SBVS exercise. Additionally, the
2D diagram in (Fig. 10) shows that Val 702 has a double π-
sigma interaction with the two aromatic rings in addition to
π-alkyl interactions. Ala 719, Leu 768, Leu 694, Leu 820 and
Leu 764 have also π-alkyl interactions while Lys 721 has an
alkyl interaction like erlotinib but also a π-cation interaction
which strengthens the union.
3.2. In Vitro Assays
3.2.1. Preliminary Test
As mentioned, 23 compounds were selected from the
SBVS to perform in vitro assays in different cell lines. First
of all, a preliminary test (Fig. 11) was conducted. The com-
pounds were assayed at high concentrations (from 10 µM to
100 µM) in order to perceive a possible activity that gives us
some clues about the structural requirements of the active
molecules. The compounds were diluted in DMSO, and
Trichostatin A (TSA), an organic compound that inhibits the
eukaryotic cell cycle during the beginning of the growth
stage, was used as a positive control at 0,5 µM in order to
compare the activity. Fig. (11) shows the activity of each
compound at 100µM during 48 hours of treatment in the A1
cell line.
Four compounds (1, 10, 12 and 21) showed significant
activity when tested at 100 µM. Otherwise, compounds 11
and 13 showed a very important inhibitory effect that is not
displayed at A450nm, because of precipitation in solution
and their colorless appearance, which interfered with the
measurement.
The four best compounds (1, 10, 12 and 21) were tested
in the HCT cell line at 50 µM and 10 µM during 48 hours of
treatment (Fig. 12). As can be seen, compound 12 was the
one displaying the better activity when tested at 50µM, and
no compounds demonstrated any activity at 10 µM.

6 Current Topics in Medici nal Chemistry, 2020, Vol. 20, No. 18 Gómez-Ganau et al.
Table 1. 23 compounds selected from the SBVS.
Id.
ZINC Id.
Molecular Weight
Formula
1
ZINC04808604
358.49
C23H26N4
2
ZINC00817992
385.48
C26H24FNO
3
ZINC01021939
261.37
C19H19N
4
ZINC00104782
251.29
C15H13N3O
5
ZINC00185189
298.77
C17H15ClN2O
6
ZINC19501724
377.49
C22H27N5O
7
ZINC04109493
347.34
C17H13N7O2
8
ZINC04358923
359.38
C18H21N3O5
9
ZINC01104436
382.51
C20H18N2O2S2
10
ZINC03869685
302.24
C15H10O7
11
ZINC00809294
392.5
C27H24N2O
12
ZINC04492596
333.39
C23H15N3
13
ZINC06445915
439.53
C23H25N3O4S
14
ZINC00924422
388.51
C22H16N2OS2
15
ZINC00909652
406.89
C22HClN2O2S
16
ZINC04855214
407.54
C22H25N5OS
17
ZINC04311646
349.39
C20H19N3O3
18
ZINC00055296
321.36
C19H19N3O2
19
ZINC00780608
401.42
C23H19N3O4
20
ZINC00613495
323.21
C13H8Cl2N4S
21
ZINC06678986
403.5
C23H21N3O2S
22
ZINC09263141
457.48
C12H2OFN5O4S
23
ZINC13566858
372.83
C17H13ClN4O2S
Table 2. Results of the Virtual Screening for th e 23 selected compounds and the well-known inhibitor erlotinib.
Id.
Total Energy
VDW energy
Hbond energy
22
-113.49
-96.44
-17.06
11
-109.84
-104.54
-5.31
16
-107.83
-98.16
-9.68
7
-107.26
-89.63
-17.63
8
-106.10
-83.37
-22.73
19
-105.90
-95.24
-10.67
6
-104.38
-85.27
-19.10
21
-103.4
-99.32
-4.08
17
-107.57
-90.58
-11.00
(Table 2) contd….

Computational Evaluation and In Vitro Validation Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 7
Id.
Total Energy
VDW energy
Hbond energy
12
-99.62
-90.27
-9.34
14
-97.36
-87.35
-10.01
-13
-97.04
-86.92
-10.12
Erlotinib
-96.09
-86.13
-9.95
15
-96.0571
-91.3141
-4.743
10
-95.65
-76.63
-19.01
18
-91.65
-81.92
-9.73
1
-91.23
-87.95
-3.27
5
-89.17
-85.68
-3.48
23
-88.23
-76.61
-11.61
9
-87.24
-83.38
-3.86
20
-83.95
-73.23
-10.71
4
-82.48
-72.35
-10.13
2
-82.09
-74.70
-7.83
3
-76.15
-76.15
0
Table 3. Interaction energies b etween the amino a cids of the ligand-binding site and erlotinib and compound 21.
Interaction/Aminoacid
Erlotinib
Compound
H-S-THR-766
-3.47
-1.25
H-M-GLN-767
-2.98
0
H-M-MET-769
0
-2.82
H-M-PRO-772
-3.5
0
V-M-LEU-694
0
-0.98
V-S-LEU-694
-8.48
-13.15
V-S-VAL-702
-6.87
-5.51
V-S-LYS-704
0
-3.90
V-M-ALA-719
0
-4.28
V-S-LYS-721
-8.09
-3.4063
V-S-GLU-738
0
-0.088
V-S-THR-766
0
-2.44
V-S-LEU-768
0
-2.41
V-M-MET-769
-4.31
-9.64
V-S-MET
0
-3.06
V-M-PRO-770
0
-9.51
V-M-PHE-771
0
-2.05
V-M-GLY-772
0
-8.27
(Table 3) contd….

8 Current Topics in Medici nal Chemistry, 2020, Vol. 20, No. 18 Gómez-Ganau et al.
Interaction/Aminoacid
Erlotinib
Compound
V-M-CYS-773
0
-2.01
V-S-CYS-773
0
-2.01
V-S-ASP-776
0
-0.11
V-S-LEU-820
-6.78
-7.07
V-S-THR-830
0
-0.25
V-S-ASP
0
-0.15
Fig. (7). Conformation of compound 21 in the EGFR ATP binding
site. Interactions with the amino acids of EGFR are shown. (A
higher resolution / colour version of this figure is available in the
electronic copy of the article).
Fig. (8). 2D diagram of Erlotinib in the EGFR ligand binding site.
(A higher resolution / colour version of this figure is available in
the electronic copy of the article).
3.2.2. Viability and Cell Proliferation Assay
3.2.2.1. HCT
After the preliminary test, a new protocol to test the in-
hibitor effect through flow cytometry and propidium iodide
staining was carried out. This protocol allowed us to quantify
cell death in a more accurate manner. The viability and the
cellular proliferation in different cell lines at 30 µM, 10 µM
and 2 µM were analysed. Compounds 1, 10, 12 and 21 were
assayed, as well as compounds 11 and 13, and the well-
known inhibitor erlotinib was used as a positive control.
Fig. (9). Alignment of erlotinib (orange) and compound 21 (yellow)
after docking in EGFR. (A higher resolution / colour version of this
figure is available in the electronic copy of the article).
Fig. (10). 2D diagram of compound 21 in the EGFR ligand binding
site. (A higher resolution / colour version of this figure is available
in the electronic copy of the article).
First, the 6 molecules selected were tested in the HCT
cell line for 72 hours. When the viability was detected by
flow cytometry, important effects were observed at 30 µM
but no inhibitory effect was displayed at lower concentra-
tions including erlotinib. However, when we observed our

Computational Evaluation and In Vitro Validation Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 9
results at the microscopy, almost all compounds showed
good proliferation inhibitory activity when tested at 10 µM
(1 and 13 like erlotinib) while no compound, including er-
lotinib, showed inhibition at 2 µM (Fig. 13).
3.2.2.1. Caco-2 and H358
Since the HCT cell line presents mutations at the EGFR
signaling route and considering the low effect of erlotinib at
lower concentrations, it was concluded that other cells could
be more suitable for the assays. In consequence, Caco-2 and
H358 cell lines were also tested at 30 µM, 10 µM and 2 µM
for 72 hours.
The results for Caco-2 (Fig. 14, B) showed an inhibitory
activity similar to erlotinib for compound 21 when tested at
10 µM, and compound 12 showed also some inhibitory ef-
fect. However, at 2 µM, erlotinib was the unique active com-
pound. Furthermore, compound 12 showed a better effect of
cellular viability than erlotinib when tested at 10 µM in the
H358 cell line (Fig. 14, C). Nevertheless, no compound was
active at 2 µM.
On the other hand, compounds 12 and 21 showed activity
at 10 µM in the Caco-2 cell line when observed at the mi-
croscopy and when cell proliferation was measured (Fig. 15
B). Only compound 21 showed a certain activity at 2 µM but
Fig. (11). Preliminary assay of the 23 compounds selected at 100 µM in DMSO. (A higher resolution / colour version of this figure is avail-
able in the electronic copy of the article).
Fig. (12). Inhibition assay in the HCT116 cell line for the 4 compounds selected. A) Inhibition at 50 µM during 48 hours; B) Inhibition at 10
µM. (A higher resolution / colour version of this figure is available in the electronic copy of the article).
Fig. (13). Inhibition at 2 µM in HCT 116 cell line. A) Viability assay B) Cellular proliferation assay. (A higher resolution / colour version of
this figure is available in the electronic copy of the article).

10 Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 Gómez-Ganau et al.
lower than that of erlotinib. Compounds 1, 10, 12 and 21
were active at 10 µM in the H358 cell line (Fig. 15, C), but
only erlotinib showed activity at the microscopy when tested
at 2 µM.
CONCLUSION
The occurrence of resistance mechanisms associated with
EGFR mutations is one of the main problems in therapy
against malignancies associated with EGFR. New EGFR
ligands and approaches in the research within EGFR signal
transduction inhibition are necessary to avoid these prob-
lems.
In this study, a total of 615,462 chemical compounds
from the ZINC database were evaluated through SBVS and
experimentally validated through in vitro assays in HCT116,
Caco-2 and H358 cell lines to search for novel EGFR inhibi-
tors. The selected top compounds were compared with the
well-known EGFR inhibitor erlotinib (Tarceva®). The re-
Fig. (14). Viability assay for the 6 compounds selected at 10Μm. a) HCT 116 cell line B) Caco-2 cell line C) H358 cell line. (A higher reso-
lution / colour version of this figure is available in the electronic copy of the article).
Fig. (15). Cell proliferation assay at 10 µM. A) HCT 116 cell line B) Caco-2 cell line C) H358 cell line. (A higher resolution / colour version
of this figure is available in the electronic copy of the article).

Computational Evaluation and In Vitro Validation Current Topics in Medicinal Chemistry, 2020, Vol. 20, No. 18 11
sults obtained both with the in silico methods and the in vitro
cytotoxicity activity allowed us to identify novel molecules
with inhibitory activity.
Taking into account that these new inhibitors showed a
high structural dissimilarity with respect to the current ones,
they can be used as future hits. Further SAR and docking
studies to optimize these structures and interactions have to
be performed, in order to find new regulators of EGFR. The
structural differences between the selected compounds and
the ones that currently exist could be useful in order to avoid
the current resistance mechanisms.
These results can serve us to develop new strategies; on
the one hand, combination therapy of different drugs (as
used in other therapeutical areas like the cocktail drugs in
anti-HIV therapy [40]). Disruption of the cellular proliferation
can be made by a very potent selective inhibitor of one of the
EGFR signaling transduction pathway receptors, or, alterna-
tively, by the synergistic action of less potent selective inhi-
bition of some of them, since this inhibitory effect is cumula-
tive. Instead, two inhibitors acting on the same receptor do
not get this effect due to competition between them.
On the other hand, the use of polypharmacology (that is,
the inhibition of several targets by one drug), is an approach
that is being explored and promises to be part of future che-
motherapies. The rational design of drugs that act through
polypharmacological mechanisms may produce compounds
that exhibit a greater therapeutic potency together with lower
resistance issues.
In light of the results obtained, a focus on new studies
and new strategies can help us to expand the therapeutic op-
tions against a wide range of cancers.
ETHICS APPROVAL AND CONSENT TO PARTICI-
PATE
Not applicable.
HUMAN AND ANIMAL RIGHTS
No Animals/Humans were used for studies that are base
of this research.
CONSENT FOR PUBLICATION
Not applicable.
AVAILABILITY OF DATA AND MATERIALS
Not applicable.
FUNDING
SGG acknowledges the “Agencia Estatal de Investiga-
ción” of Spain for its financial support “Doctorado Indus-
trial” (Grant Reference DI-17-09598 / AEI / Digital Object
Identifier 10.13039/501100011033).
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or
otherwise.
ACKNOWLEDGEMENTS
Declared none.
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