Structure-based virtual screening and molecular docking for the identification of potential novel EGFRkinase inhibitors against ovarian cancer
Identifieur interne : 000419 ( Pmc/Corpus ); précédent : 000418; suivant : 000420Structure-based virtual screening and molecular docking for the identification of potential novel EGFRkinase inhibitors against ovarian cancer
Auteurs : Khalid Hussain Wali Sait ; Qamre Alam ; Nisrin Anfinan ; Othman Al-Ghamdi ; Arshi Malik ; Rana Noor ; Farheen Jahan ; Mohammed TariqueSource :
- Bioinformation [ 0973-2063 ] ; 2019.
Abstract
Epidermal Growth Factor Receptor (EGFR) is, for the most part, deregulated and over-communicated in ovarian disease, which is legitimately connected with STAT3 enactment that prompts the collection of hostile to apoptotic occasions and along these lines, docetaxel medicate obstruction happens. As to, expanding of docetaxel medicate affectability by focusing on EGFR receptor alongside docetaxel drugs is one of the real techniques in ovarian disease treatment. In this specific circumstance, utilizing atomic recreation considers, the present examination depicted the auxiliary and pragmatic properties of IBS Database mixes as a potential inhibitor of EGFR tyrosine kinase, and furthermore ADMET had researched its Pharmacokinetic profile. As indicated by the outcomes, STOCK1N-98911, STOCK1N- 98869, and STOCK1N-98896 have appeared tremendous restricting vitality by associating with critical build ups in the dynamic site. Natural movement range forecast of these mixes indicated potential anticancer properties by demonstrating important collaboration with EGFR tyrosine kinase. Besides, the investigation is likewise valuable for further clinical based examinations and furthermore for the approval of toxicological and pharmacokinetic contemplate
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DOI: 10.6026/97320630015287
PubMed: 31285646
PubMed Central: 6599442
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PMC:6599442Le document en format XML
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<author><name sortKey="Sait, Khalid Hussain Wali" sort="Sait, Khalid Hussain Wali" uniqKey="Sait K" first="Khalid Hussain Wali" last="Sait">Khalid Hussain Wali Sait</name>
<affiliation><nlm:aff id="A1">Department of Obstetrics and Gynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, SaudiArabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Alam, Qamre" sort="Alam, Qamre" uniqKey="Alam Q" first="Qamre" last="Alam">Qamre Alam</name>
<affiliation><nlm:aff id="A2">King Fahd Medical Research Center, King Abdulaziz University, Jeddah. Saudi Arabia</nlm:aff>
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</author>
<author><name sortKey="Anfinan, Nisrin" sort="Anfinan, Nisrin" uniqKey="Anfinan N" first="Nisrin" last="Anfinan">Nisrin Anfinan</name>
<affiliation><nlm:aff id="A3">Department of Obstetrics andGynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Al Ghamdi, Othman" sort="Al Ghamdi, Othman" uniqKey="Al Ghamdi O" first="Othman" last="Al-Ghamdi">Othman Al-Ghamdi</name>
<affiliation><nlm:aff id="A4">Department of Biological Sciences, Faculty of Science, University of Jeddah, Kingdom of Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Malik, Arshi" sort="Malik, Arshi" uniqKey="Malik A" first="Arshi" last="Malik">Arshi Malik</name>
<affiliation><nlm:aff id="A5">Department of Clinical Biochemistry, College ofMedicine, King Khalid University, Abha, Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Noor, Rana" sort="Noor, Rana" uniqKey="Noor R" first="Rana" last="Noor">Rana Noor</name>
<affiliation><nlm:aff id="A6">Department of Biochemistry, Faculty of Dentistry, Jamia Millia Islamia, JamiaNagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Jahan, Farheen" sort="Jahan, Farheen" uniqKey="Jahan F" first="Farheen" last="Jahan">Farheen Jahan</name>
<affiliation><nlm:aff id="A7">Department of Biosciences Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Tarique, Mohammed" sort="Tarique, Mohammed" uniqKey="Tarique M" first="Mohammed" last="Tarique">Mohammed Tarique</name>
<affiliation><nlm:aff id="A8">8Center forInterdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Structure-based virtual screening and molecular docking for the identification of potential novel EGFRkinase inhibitors against ovarian cancer</title>
<author><name sortKey="Sait, Khalid Hussain Wali" sort="Sait, Khalid Hussain Wali" uniqKey="Sait K" first="Khalid Hussain Wali" last="Sait">Khalid Hussain Wali Sait</name>
<affiliation><nlm:aff id="A1">Department of Obstetrics and Gynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, SaudiArabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Alam, Qamre" sort="Alam, Qamre" uniqKey="Alam Q" first="Qamre" last="Alam">Qamre Alam</name>
<affiliation><nlm:aff id="A2">King Fahd Medical Research Center, King Abdulaziz University, Jeddah. Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Anfinan, Nisrin" sort="Anfinan, Nisrin" uniqKey="Anfinan N" first="Nisrin" last="Anfinan">Nisrin Anfinan</name>
<affiliation><nlm:aff id="A3">Department of Obstetrics andGynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Al Ghamdi, Othman" sort="Al Ghamdi, Othman" uniqKey="Al Ghamdi O" first="Othman" last="Al-Ghamdi">Othman Al-Ghamdi</name>
<affiliation><nlm:aff id="A4">Department of Biological Sciences, Faculty of Science, University of Jeddah, Kingdom of Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Malik, Arshi" sort="Malik, Arshi" uniqKey="Malik A" first="Arshi" last="Malik">Arshi Malik</name>
<affiliation><nlm:aff id="A5">Department of Clinical Biochemistry, College ofMedicine, King Khalid University, Abha, Saudi Arabia</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Noor, Rana" sort="Noor, Rana" uniqKey="Noor R" first="Rana" last="Noor">Rana Noor</name>
<affiliation><nlm:aff id="A6">Department of Biochemistry, Faculty of Dentistry, Jamia Millia Islamia, JamiaNagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Jahan, Farheen" sort="Jahan, Farheen" uniqKey="Jahan F" first="Farheen" last="Jahan">Farheen Jahan</name>
<affiliation><nlm:aff id="A7">Department of Biosciences Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Tarique, Mohammed" sort="Tarique, Mohammed" uniqKey="Tarique M" first="Mohammed" last="Tarique">Mohammed Tarique</name>
<affiliation><nlm:aff id="A8">8Center forInterdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</nlm:aff>
</affiliation>
</author>
</analytic>
<series><title level="j">Bioinformation</title>
<idno type="eISSN">0973-2063</idno>
<imprint><date when="2019">2019</date>
</imprint>
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<front><div type="abstract" xml:lang="en"><p>Epidermal Growth Factor Receptor (EGFR) is, for the most part, deregulated and over-communicated in ovarian disease, which is
legitimately connected with STAT3 enactment that prompts the collection of hostile to apoptotic occasions and along these lines, docetaxel
medicate obstruction happens. As to, expanding of docetaxel medicate affectability by focusing on EGFR receptor alongside docetaxel
drugs is one of the real techniques in ovarian disease treatment. In this specific circumstance, utilizing atomic recreation considers, the
present examination depicted the auxiliary and pragmatic properties of IBS Database mixes as a potential inhibitor of EGFR tyrosine
kinase, and furthermore ADMET had researched its Pharmacokinetic profile. As indicated by the outcomes, STOCK1N-98911, STOCK1N-
98869, and STOCK1N-98896 have appeared tremendous restricting vitality by associating with critical build ups in the dynamic site.
Natural movement range forecast of these mixes indicated potential anticancer properties by demonstrating important collaboration with
EGFR tyrosine kinase. Besides, the investigation is likewise valuable for further clinical based examinations and furthermore for the
approval of toxicological and pharmacokinetic contemplate
</p>
</div>
</front>
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</TEI>
<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Bioinformation</journal-id>
<journal-id journal-id-type="iso-abbrev">Bioinformation</journal-id>
<journal-id journal-id-type="publisher-id">Bioinformation</journal-id>
<journal-title-group><journal-title>Bioinformation</journal-title>
</journal-title-group>
<issn pub-type="epub">0973-2063</issn>
<publisher><publisher-name>Biomedical Informatics</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">31285646</article-id>
<article-id pub-id-type="pmc">6599442</article-id>
<article-id pub-id-type="publisher-id">97320630015287</article-id>
<article-id pub-id-type="doi">10.6026/97320630015287</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Structure-based virtual screening and molecular docking for the identification of potential novel EGFRkinase inhibitors against ovarian cancer</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Sait</surname>
<given-names>Khalid Hussain Wali</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Alam</surname>
<given-names>Qamre</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Anfinan</surname>
<given-names>Nisrin</given-names>
</name>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Al-Ghamdi</surname>
<given-names>Othman</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Malik</surname>
<given-names>Arshi</given-names>
</name>
<xref ref-type="aff" rid="A5">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Noor</surname>
<given-names>Rana</given-names>
</name>
<xref ref-type="aff" rid="A6">6</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Jahan</surname>
<given-names>Farheen</given-names>
</name>
<xref ref-type="aff" rid="A7">7</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Tarique</surname>
<given-names>Mohammed</given-names>
</name>
<xref ref-type="aff" rid="A8">8</xref>
<xref ref-type="corresp" rid="COR1">*</xref>
</contrib>
<aff id="A1"><label>1</label>
Department of Obstetrics and Gynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, SaudiArabia</aff>
<aff id="A2"><label>2</label>
King Fahd Medical Research Center, King Abdulaziz University, Jeddah. Saudi Arabia</aff>
<aff id="A3"><label>3</label>
Department of Obstetrics andGynecology, Gynecology Oncology Unite, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia</aff>
<aff id="A4"><label>4</label>
Department of Biological Sciences, Faculty of Science, University of Jeddah, Kingdom of Saudi Arabia</aff>
<aff id="A5"><label>5</label>
Department of Clinical Biochemistry, College ofMedicine, King Khalid University, Abha, Saudi Arabia</aff>
<aff id="A6"><label>6</label>
Department of Biochemistry, Faculty of Dentistry, Jamia Millia Islamia, JamiaNagar, New Delhi-110025, India</aff>
<aff id="A7"><label>7</label>
Department of Biosciences Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</aff>
<aff id="A8"><label>8</label>
8Center forInterdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India</aff>
</contrib-group>
<author-notes><corresp id="COR1"><label>*</label>
Mohammed Tarique<email>tariqueaiims@gmail.com</email>
</corresp>
</author-notes>
<pub-date pub-type="collection"><year>2019</year>
</pub-date>
<pub-date pub-type="epub"><day>15</day>
<month>4</month>
<year>2019</year>
</pub-date>
<volume>15</volume>
<issue>4</issue>
<fpage>287</fpage>
<lpage>294</lpage>
<history><date date-type="received"><day>26</day>
<month>3</month>
<year>2019</year>
</date>
<date date-type="accepted"><day>31</day>
<month>3</month>
<year>2019</year>
</date>
</history>
<permissions><copyright-statement>© 2019 Biomedical Informatics</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p>This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.</license-p>
</license>
</permissions>
<abstract><p>Epidermal Growth Factor Receptor (EGFR) is, for the most part, deregulated and over-communicated in ovarian disease, which is
legitimately connected with STAT3 enactment that prompts the collection of hostile to apoptotic occasions and along these lines, docetaxel
medicate obstruction happens. As to, expanding of docetaxel medicate affectability by focusing on EGFR receptor alongside docetaxel
drugs is one of the real techniques in ovarian disease treatment. In this specific circumstance, utilizing atomic recreation considers, the
present examination depicted the auxiliary and pragmatic properties of IBS Database mixes as a potential inhibitor of EGFR tyrosine
kinase, and furthermore ADMET had researched its Pharmacokinetic profile. As indicated by the outcomes, STOCK1N-98911, STOCK1N-
98869, and STOCK1N-98896 have appeared tremendous restricting vitality by associating with critical build ups in the dynamic site.
Natural movement range forecast of these mixes indicated potential anticancer properties by demonstrating important collaboration with
EGFR tyrosine kinase. Besides, the investigation is likewise valuable for further clinical based examinations and furthermore for the
approval of toxicological and pharmacokinetic contemplate
</p>
</abstract>
<kwd-group><kwd>ADMET</kwd>
<kwd>Biological activity spectrum</kwd>
<kwd>EGFR tyrosine kinase</kwd>
<kwd>Pharmacokinetic</kwd>
<kwd>Inhibitor</kwd>
</kwd-group>
</article-meta>
</front>
<body><sec id="s1"><title>Background</title>
<p> Recently, the primary source of death in ladies is ovarian
malignancy adding up to 1, 40,000 passings consistently <xref rid="R01" ref-type="bibr">1</xref>
. Even
though most ladies with epithelial ovarian malignant growth (EOC)
are analyzed at cutting edge organizes, the reduced expectation of
this malady causes more passing <xref rid="R02" ref-type="bibr">2</xref>
. Thus, the clinical reaction rate
at the start is extremely high, where platinum-based mixes are
benchmark first-line operators for ovarian malignant growth
treatment.<xref rid="R03" ref-type="bibr">3</xref>
. Be that as it may, because of the advancement of
obtained chemo resistance in most ovarian malignant growth, the
treatment procedures are presently in a significant test. <xref rid="R04" ref-type="bibr">4</xref>
,<xref rid="R05" ref-type="bibr">5</xref>
. In this
manner, in such condition, there is a pressing need to create novel
and useful helpful systems against malignant ovarian growth <xref rid="R06" ref-type="bibr">6</xref>
,<xref rid="R07" ref-type="bibr">7</xref>
.
Epidermal Growth Factor Receptor (EGFR), which has a place with
the group of Human Epidermal Receptor (HER), is very
communicated in numerous fatalities, basically in ovarian disease
<xref rid="R08" ref-type="bibr">8</xref>
. It's one of the tyrosine kinases and for the most part initiated by
extracellular ligands that trigger receptor auto phosphorylation,
which may prompt the actuation of downstream pathways
engaged with expansion, survival, angiogenesis, and attack <xref rid="R09" ref-type="bibr">9</xref>
, <xref rid="R10" ref-type="bibr">10</xref>
.
Ongoing investigations have demonstrated that the EGFR pathway
is intermittently enacted in most malignant growth cell, and it is
focused on restraint with a little atom kinase inhibitor has been
useful for lung, bosom and ovarian disease with EGFR
transformations <xref rid="R11" ref-type="bibr">11</xref>
, <xref rid="R12" ref-type="bibr">12</xref>
. Along these lines, the present examination
was meant to explore the helpful properties of IBS information base
as EGFR tyrosine kinase inhibitor through different computational
investigation, including atomic docking, ADME/T examination,
and organic range <xref rid="R13" ref-type="bibr">13</xref>
, <xref rid="R14" ref-type="bibr">14</xref>
. </p>
</sec>
<sec id="s2"><title>Methodology</title>
<sec id="s2a"><title>Identification of EGFR gene:</title>
<p>All the sequences of the EGFR were retrieved from the genome
database NCBI (http://www.ncbi.nlm.nih.gov). The FASTA
formats of the retrieved sequences were used for BLAST-P analysis.
The series was downloaded and analyzed in detail. The nucleotide
sequence of EGFR is 3630 bases, and it codes for a protein of 1210
amino acids. Multiple-sequence alignment was done by using
ClustalW (http://www.ebi.ac.uk/Tools/msa/clustalw2/) and
Clustal Omega (http://www.ebi.ac.uk/Tools/msa/clustalo/). </p>
</sec>
<sec id="s2b"><title>Domain Organization:</title>
<p>The retrieved sequences were in-silico studied, and various
domains were manually assigned and confirmed by using Pfam,
Prosite and integrated software, InterProScan. And conserved
motifs were identified manually as well as using Pfam and
InterProScan software. </p>
</sec>
<sec id="s2c"><title>Selection of Ligands and protein molecule:</title>
<p>Schematic outline of the work process examine configuration is
shown in <xref ref-type="fig" rid="F3">Figure 3</xref>
. Ligand atoms were chosen from IBS natural
compound library (InterBioScreen Ltd). Ligands were set up by
utilizing the LigPrep module of the Maestro 10.5 application.
LigPrep performs numerous amendments on the ligands, for
example, the expansion of hydrogen, 2D - 3D transformation,
rectified bond lengths and bond angles, low-vitality structure, and
ring compliance. Separated from that another parameter, for
example, ionization does not change, tautomers not made and hold
specific philanthropies create at most one for every ligand were
utilized as a default parameter in Maestro 10.5. After that all iota
compel, and particle types were appointed by the optimized
potential for fluid reproductions (OPLS_2005) drive field <xref rid="R15" ref-type="bibr">15</xref>
, <xref rid="R16" ref-type="bibr">16</xref>
.
At long last, one adaptation for every ligand was generated, and
ligands are prepared for docking. The structure of the epidermal
growth factor receptor (EGFR) kinase space (PDB id: 1M17) is
recovered from the protein information bank. Maestro 10.5 protein
arrangement wizard applications were performed for the redress of
crude structure, where changes, for example, expansion of
hydrogen atoms, doling out security orders, a formation of zerorequest
bonds to metal, making of disulfide securities, fixing of the
charges and introduction of gatherings were consolidated into the
fibrous structure. </p>
</sec>
<sec id="s2d"><title>Molecular docking:</title>
<p>Molecular docking studies using the selected ligand molecules
were conducted using Maestro 10.5 molecular docking suite <xref rid="R17" ref-type="bibr">17</xref>
, <xref rid="R18" ref-type="bibr">18</xref>
.
Every one of these mixes was docked into target protein as needs
be with positions, introductions, and compliances of the ligand in
the receptor restricting site, and the docking structure having the
most reduced vitality was favored. In the present examination, we
screened around 50,000 standard mixes from the IBS againstEGFR
kinase. IBS characteristic mixes docked with each chosen protein
particles by utilizing HTVS. To give a superior connection be
tween's correct stances and high scores, GLIDE-XP mode was used
accordingly on the adaptations picked from HTVS mode. Based on
Score, we select 20 mixes for GLIDEXP atomic docking. After the
fruition of ligands and proteins planning, a receptor network
record was created. For running the framework age module, we
have scaled van der Waal radii of receptor molecules by 1.00 Å as
the default setting of Maestro 10.5. The dynamic site of the receptor
keeps up an exact scoring capacity with thermodynamically most
ideal vitality and is determined on a framework by different
arrangements of fields. After the method of the receptor network
document, adaptable ligands with rigid receptor-based sub-atomic
docking were performed. The best-fit mixes have been decided for
each objective by ideal vitality esteem and kinds of
communications. </p>
</sec>
<sec id="s2e"><title>Prime MM-GBSA:</title>
<p>Prime MM-GBSA approach was utilized to compute ligand
restricting energies and ligand strain energies for a ligand and a
single receptor. MM-GBSA is a strategy that joins OPLSAA atomic
mechanics energies (EMM), an SGB solvation display for polar
solvation (GSGB), and a non-polar solvation term (GNP) made out
of the non-polar dissolvable available surface region and van der
Waals communications. Here, the Glide present watcher document
of the best conformation picked was given as the source in Prime
MM-GBS A simulation. The all-out free vitality of official: ΔGbind =
G-complex - (G-protein + Gligand), where G = EMM + GSGB
+ GNP </p>
</sec>
<sec id="s2f"><title>Absorption, distribution, metabolism, excretion, and toxicity
(ADME/T) properties studies:</title>
<p> Most of the medication competitors don't prevail in clinical trials
because of poor toxicology appraisals (ADME/T). In this way,
ADME/T properties of best-docked mixes were anticipated
utilizing QikProp use of Maestro 10.5 (auxiliary, physicochemical,
biochemical, pharmacokinetics, and harmfulness properties). It
predicts characteristic features of the atoms (medicate like
properties, for example, octanol/water segment, log BB, by and
substantial CNS action, log IC50 for Herg K+ channel blockage,
Caco-2, MDCK cell porousness and log Khsa for human serum egg
whites official <xref rid="R19" ref-type="bibr">19</xref>
, <xref rid="R20" ref-type="bibr">20</xref>
. </p>
</sec>
<sec id="s2g"><title>Boiled-egg Plot:</title>
<p> A boiled-Egg plot loan consoling help and gives an interesting
measurable plot to help the two aloof expectations made, which is
gastrointestinal retention and cerebrum entrance of little particles,
which is necessary for revelation, and improvement of medications.
Both the parameters are spoken to on a cartesian plane in the state
of obscurations and incorporate other vital parameters, for
example, MW, TPSA, MLOGP, GI, and BBB to recondition the
boiled Egg plot. As needs are, in the cartesian plane, if our mixes
rest in the yolk locale spoken to by the yellow oval, the likelihood
of BBB-Blood Brain Barrier is though if the blends relax under
white zones, the guess of gastrointestinal retention is enhanced.
Adjacent to these locales, if the mixes rest in dark areas barring the
"egg" or are out of the scope of the chart, the combinations are nonabsorptive
even non-mind infiltration, and consequently, it mulled
over as a commented box. The areas are not selective of one
another. </p>
</sec>
<sec id="s2h"><title>Biological activity spectrum (BAS):</title>
<p>BAS of a best-docked compound speaks to the complex of
pharmacological impacts and the characteristic properties of the
compound relied upon its essential feature. The pharmacological
impacts, displayed by a mixture and its correspondence with
organic substances were anticipated by PASS online by transferring
the SMILES string of regular mixes <xref rid="R21" ref-type="bibr">21</xref>
. </p>
</sec>
</sec>
<sec id="s3"><title>Results and Discussion</title>
<p> In this study we have reported the in silico analysis of all the EGFR
gene of ovarian cancer. </p>
<sec id="s3a"><title>Identification and sequence analysis EGFR gene:</title>
<p>An alignment of the complete amino acid sequence of EGFR and its
isoform using BLAST (http://blast.ncbi.nlm.nih.gov/Blast) was
completed. The protein sequence of EGFR (1210 amino acid) was
aligned with the other EGFR genes sequence of, and conserved
motifs are boxed in red color (<xref ref-type="fig" rid="F1">Figure 1</xref>
). The results indicate that
EGFR contains all the specific topics including signal peptide
domain, nucleotide binding sites and the protein kinase domain.
Similarly, the results show that EGFR is highly conserved and it
possesses all the characteristic motifs (<xref ref-type="fig" rid="F2">Figure 2</xref>
). </p>
</sec>
<sec id="s3b"><title>Molecular docking and binding energy analysis:</title>
<p>This examination is concentrated to investigate the firm focused on
inhibitor against EGFR kinase utilizing atomic docking approach.
Atomic docking of EGFR kinase against original mixes has been
done. To begin with, we performed HTVS of IBS against the EGFR
kinase appeared beneficial <xref rid="T1" ref-type="table">Table 1</xref>
. Further, 20 best combinations
from every protein atoms that have negligible Gscore sub-atomic
docking were performed using the XP method of GLIDE. In the
present examination, our outcome featured that aggravates a
prevalent dock score for proteins EGFR kinase appeared in <xref rid="T1" ref-type="table">Table 1</xref>
.
Protein-ligand connections highlighted that the lipophilic,
hydrogen holding, pp stacking, and cation-p communications
speak to a decision commitment at the dynamic site. Sub-atomic
docking activity recognizes the premier docking free vitality esteem
(Gscore) against these receptor particles. Sub-atomic docking
aftereffect of EGFR kinase against IBS original mixes divulged that
mixes STOCK1N-98911, STOCK1N-98869, and STOCK1N-98896
yielded the best Gscore-12.22, - 8.207and - 7.061kcal/mol,
individually. The atomic docking study has done seek to outline the
protein - ligands communications and to condense the different
securities, for example, hydrogen and electrostatic protection. </p>
<p>STOCK1N-98911 was observed to be most potent and pleasantly
limited into the dynamic site of EGFR kinase with best Gscore
contrasted with Docetaxel (<xref rid="T3" ref-type="table">Table 3</xref>
). Compound STOCK1N-98911
showed three hydrogen bonds with Met: 769 and Asp: 831 of EGFR
kinase 2.9 Aring;, 2.1 Aring;, and 2.2 Å separately (<xref ref-type="fig" rid="F4">Figure 4B</xref>
). The compound
STOCK1N-98911 additionally associates with the EGFR kinase
restricting site by connecting with different deposits (Ala: 696 and
Phe: 699) when contrasted with Docetaxel appeared in <xref ref-type="fig" rid="F4">Figure 4A</xref>
.
Chloroquine compound cooperates with the EGFR kinase-binding
site by collaborating with deposits (Lys: 692 and Glu: 780) appeared
in <xref rid="T1" ref-type="table">Table 1</xref>
. Sub-atomic docking thinks about proposed that the
various van der Waals, covalent, carbon-hydrogen, Pi alkyl and
electrostatic collaborations are the critical power for holding of
mixes STOCK1N-98911, STOCK1N-98869 and STOCK1N-98896
together with the EGFR kinase. Once more, to watch the general
clearness of docking examines, we presented Prime MM-GBSA way
to deal with ascertaining ligand-restricting energies. In our
investigation, the coupling vitality of STOCK1N-98911, STOCK1N-
98869, and STOCK1N-98896 indicates a stable holding connection
and the precision of ligand-protein official (<xref rid="T1" ref-type="table">Table 1</xref>
). In this
manner, at long last finished up mixes STOCK1N-98911,
STOCK1N-98869 and STOCK1N-98896have demonstrated better
restricting vitality for EGFR kinase, and it might be considered as
an apparent inhibitor of the EGFR kinase. </p>
</sec>
<sec id="s3c"><title>ADME and Toxicity analysis:</title>
<p>Pharmacokinetic and pharmaco dynamics properties of the lead
mixes were assessed by the Qikprop utility of Maestro 10.5. Mixes
STOCK1N-98911, STOCK1N-98869 and STOCK1N-98896 yielded
the best Score. A most intriguing part of these mixes is their
commendable QPlogPo/w, QPlogHERGK+ channels, QPlogBB,
QPlogKP and QPlogKhsa values that fulfill the Lipinski's Rule of
Five (<xref rid="T2" ref-type="table">Table 2</xref>
). The chosen properties are known to impact
digestion, cell saturation, and bioavailability. All the anticipated
features of the lead mixes were in the range for 95% of known oral
medications and furthermore fulfilled the Lipinski's standard of
five to be considered as a medication like potential. </p>
</sec>
<sec id="s3d"><title>Boiled-egg Plot:</title>
<p>The compounds STOCK1N-98911, STOCK1N-98869, and
STOCK1N-98896 were plotted in the bioled - egg plot. <xref rid="T3" ref-type="table">Table 3</xref>
abridges the consequences of the scheme. Perceptions demonstrate
that every one of the three medications shows high GI assimilation
and an adverse outcome for Blood-Brain pervasion. This perception
legitimizes the position of all the three mixes in the white district of
the boiled-Egg plot. The virtual screened tranquilize with
STOCK1N-98911; STOCK1N-98869 and STOCK1N-98896
demonstrate the most astounding an incentive for TPSA and lies
nearly in the focal point of the white district. None of the mixes fall
in the dark locale of the plot, which affirms that every one of these
mixes shows high GI ingestion and is largely BBB not penetrable (<xref ref-type="fig" rid="F5">Figure 5</xref>
). </p>
</sec>
<sec id="s3e"><title>Biological activity predictions:</title>
<p>Using PASS online server, selected bioactive constituents were
obtained to evaluate the possible biological activity. The biological
activity spectrum (BAS) of a compound is known to have
pharmacological effects, specific toxicities, and mechanisms of
action occurring due to compounds. Because these probabilities can
be calculated independently, the Pa and Pi values vary from 0 to 1,
and Pa + Pi < 1. Pa belongs to the class of active whereas Pi is for
inactive compounds <xref rid="R22" ref-type="bibr">22</xref>
. PASS prediction results showed that the
highest Pa value than Pi value come off for anticancer activity and
hence indicated the anticancer of selected compounds (<xref rid="T4" ref-type="table">Table 4</xref>
).
However, all compounds have shown a significant Pa value as
compared to Pi value. These compounds might be inhibiting cancer
infection via blocking EGFR kinase action as evidenced by docking
studies. </p>
</sec>
</sec>
<sec id="s4"><title>Conclusion</title>
<p>From the perspectives of docetaxel resistant ovarian cancer, the
current study is an attempt to explore out the therapeutic
potentiality of STOCK1N-98911, STOCK1N-98869 and STOCK1N-
98896 compound. The compound STOCK1N-98911, STOCK1N-
98869, and STOCK1N-98896 shows a high degree of binding to the
EGFR kinase. The pharmacophore mapping of the molecule shows
the efficiency with which it binds to the receptor structure. The
ADMET profile of this ligand is highly favorable, which predicts
the ligand would give positive results when in vitro and in vivo
studies are conducted. Furthermore, the review is also useful for
further clinical based studies and also for the validation of
toxicological and pharmacokinetic study. </p>
</sec>
<sec id="s5"><title>Conflict of Interest</title>
<p>Authors declare no conflict of interest.</p>
</sec>
</body>
<back><ack><p>The authors acknowledge with much obliged for Almanac Life
Science India Pvt. Ltd. for data analysis and valuable inputs.</p>
</ack>
<fn-group><fn id="FN" fn-type="other"><p><bold>Edited by P Kangueane</bold>
</p>
</fn>
</fn-group>
<fn-group><fn id="FN1" fn-type="other"><p><bold>Citation: </bold>
Wali Sait <italic>et al.</italic>
Bioinformation 15(4): 287-294 (2019)</p>
</fn>
</fn-group>
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<floats-group><table-wrap id="T1" position="float"><label>Table 1</label>
<caption><title>Lowest binding energy for the Ligands-EGFR kinase interaction, along with scores for various interaction types, as detected by GLIDE</title>
</caption>
<table frame="hsides" rules="groups"><thead><tr><td rowspan="1" colspan="1">Compounds ID</td>
<td rowspan="1" colspan="1">Binding Energy </td>
<td rowspan="1" colspan="1">GScore</td>
<td rowspan="1" colspan="1">Lipophilic E vdw</td>
<td rowspan="1" colspan="1">H-bond</td>
<td rowspan="1" colspan="1">Electro</td>
<td rowspan="1" colspan="1">Protein ligands interaction</td>
</tr>
</thead>
<tbody><tr><td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1">MM-GBSA (kcal/mol)</td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98911</td>
<td rowspan="1" colspan="1">-62.7277</td>
<td rowspan="1" colspan="1">-12.22</td>
<td rowspan="1" colspan="1">-3.436</td>
<td rowspan="1" colspan="1">-1.025</td>
<td rowspan="1" colspan="1">-2.65</td>
<td rowspan="1" colspan="1">Ala:696, Phe:699, Met:769 and Asp:831</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98869</td>
<td rowspan="1" colspan="1">-51.2494</td>
<td rowspan="1" colspan="1">-8.207</td>
<td rowspan="1" colspan="1">-4.631</td>
<td rowspan="1" colspan="1">-1.032</td>
<td rowspan="1" colspan="1">-0.428</td>
<td rowspan="1" colspan="1">Lys:721and Asp:831</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98896</td>
<td rowspan="1" colspan="1">-49.2545</td>
<td rowspan="1" colspan="1">-7.061</td>
<td rowspan="1" colspan="1">-3.708</td>
<td rowspan="1" colspan="1">-1.805</td>
<td rowspan="1" colspan="1">-0.669</td>
<td rowspan="1" colspan="1">Met:769 and Gln:767</td>
</tr>
<tr><td rowspan="1" colspan="1">Known Inhibitor</td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
</tr>
<tr><td rowspan="1" colspan="1">Docetaxel</td>
<td rowspan="1" colspan="1">-47.1282</td>
<td rowspan="1" colspan="1">-5.14</td>
<td rowspan="1" colspan="1">-4.532</td>
<td rowspan="1" colspan="1">-1.072</td>
<td rowspan="1" colspan="1">-0.931</td>
<td rowspan="1" colspan="1">Lys:692 and Glu:780</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T2" position="float"><label>Table 2</label>
<caption><title>Evaluation of drug-like properties of the lead molecules by Qikprop Maestro 10.5 molecular docking suite</title>
</caption>
<table frame="hsides" rules="groups"><thead><tr><td rowspan="1" colspan="1">Molecule</td>
<td rowspan="1" colspan="1">QPlog Po/w</td>
<td rowspan="1" colspan="1">Q P log</td>
<td rowspan="1" colspan="1">QPP Caco</td>
<td rowspan="1" colspan="1">Q P log</td>
<td rowspan="1" colspan="1">QPP</td>
<td rowspan="1" colspan="1">Q Plog</td>
</tr>
</thead>
<tbody><tr><td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1">(-2.0 to 6.5)</td>
<td rowspan="1" colspan="1">HERG</td>
<td rowspan="1" colspan="1">(nm/s)</td>
<td rowspan="1" colspan="1">BB</td>
<td rowspan="1" colspan="1">MDCK</td>
<td rowspan="1" colspan="1">Kp</td>
</tr>
<tr><td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1">(acceptable range:</td>
<td rowspan="1" colspan="1"><25 - poor</td>
<td rowspan="1" colspan="1">(-3 to 1.2)</td>
<td rowspan="1" colspan="1">(nm/s)</td>
<td rowspan="1" colspan="1">(-8.0 to -0.1)</td>
</tr>
<tr><td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1">above -5.0)</td>
<td rowspan="1" colspan="1">>500 - great</td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
<td rowspan="1" colspan="1"></td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98911</td>
<td rowspan="1" colspan="1">3.09</td>
<td rowspan="1" colspan="1">-8.158</td>
<td rowspan="1" colspan="1">50.367</td>
<td rowspan="1" colspan="1">-0.543</td>
<td rowspan="1" colspan="1">23.953</td>
<td rowspan="1" colspan="1">-5.767</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98869</td>
<td rowspan="1" colspan="1">3.198</td>
<td rowspan="1" colspan="1">-8.015</td>
<td rowspan="1" colspan="1">50.441</td>
<td rowspan="1" colspan="1">-0.628</td>
<td rowspan="1" colspan="1">23.987</td>
<td rowspan="1" colspan="1">-5.864</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98896</td>
<td rowspan="1" colspan="1">0.887</td>
<td rowspan="1" colspan="1">-4.804</td>
<td rowspan="1" colspan="1">100.053</td>
<td rowspan="1" colspan="1">-1.541</td>
<td rowspan="1" colspan="1">41.088</td>
<td rowspan="1" colspan="1">-4.179</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T3" position="float"><label>Table 3</label>
<caption><title>Boiled egg parameters</title>
</caption>
<table frame="hsides" rules="groups"><thead><tr><td rowspan="1" colspan="1">Molecule</td>
<td rowspan="1" colspan="1">MW</td>
<td rowspan="1" colspan="1">TPSA</td>
<td rowspan="1" colspan="1">XLOGP3</td>
<td rowspan="1" colspan="1">MLOGP</td>
<td rowspan="1" colspan="1">GI absorption</td>
<td rowspan="1" colspan="1">BBB permeant</td>
</tr>
</thead>
<tbody><tr><td rowspan="1" colspan="1">STOCK1N-98911</td>
<td rowspan="1" colspan="1">492.56</td>
<td rowspan="1" colspan="1">101.24</td>
<td rowspan="1" colspan="1">3.37</td>
<td rowspan="1" colspan="1">0.58</td>
<td rowspan="1" colspan="1">High</td>
<td rowspan="1" colspan="1">No</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98869</td>
<td rowspan="1" colspan="1">522.59</td>
<td rowspan="1" colspan="1">110.47</td>
<td rowspan="1" colspan="1">3.34</td>
<td rowspan="1" colspan="1">0.3</td>
<td rowspan="1" colspan="1">High</td>
<td rowspan="1" colspan="1">No</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98896</td>
<td rowspan="1" colspan="1">378.34</td>
<td rowspan="1" colspan="1">131.08</td>
<td rowspan="1" colspan="1">0.58</td>
<td rowspan="1" colspan="1">0.93</td>
<td rowspan="1" colspan="1">High</td>
<td rowspan="1" colspan="1">No</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T4" position="float"><label>Table 4</label>
<caption><title>Biological activity spectrum of compounds (Pa � Active; Pi � Inactive)</title>
</caption>
<table frame="hsides" rules="groups"><thead><tr><td rowspan="1" colspan="1">Molecule</td>
<td rowspan="1" colspan="1">Pa</td>
<td rowspan="1" colspan="1">Pi</td>
<td rowspan="1" colspan="1">Activity</td>
</tr>
</thead>
<tbody><tr><td rowspan="1" colspan="1">STOCK1N-98911</td>
<td rowspan="1" colspan="1">0.919</td>
<td rowspan="1" colspan="1">0.049</td>
<td rowspan="1" colspan="1">Anticancer</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98869</td>
<td rowspan="1" colspan="1">0.812</td>
<td rowspan="1" colspan="1">0.042</td>
<td rowspan="1" colspan="1">Anticancer</td>
</tr>
<tr><td rowspan="1" colspan="1">STOCK1N-98896</td>
<td rowspan="1" colspan="1">0.921</td>
<td rowspan="1" colspan="1">0.018</td>
<td rowspan="1" colspan="1">Anticancer</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="F1" position="float"><label>Figure 1</label>
<caption><p>Multiple sequence alignment of EGFR. Comparison of amino acid sequences for EGFR is shown. The alignment was done using
BLAST program (http://blast.ncbi.nlm.nih.gov/Blast). The conserved motifs are boxed and the name of each motif is written in words.</p>
</caption>
<graphic xlink:href="97320630015287F1"></graphic>
</fig>
<fig id="F2" position="float"><label>Figure 2</label>
<caption><p>Schematic diagrams showing the domain organization in (A-D) Domain analysis was done using Scan Prosite at
(http://expasy.org).</p>
</caption>
<graphic xlink:href="97320630015287F2"></graphic>
</fig>
<fig id="F3" position="float"><label>Figure 3</label>
<caption><p>Workflow of screening of targeted compounds against EGFR kinase</p>
</caption>
<graphic xlink:href="97320630015287F3"></graphic>
</fig>
<fig id="F4" position="float"><label>Figure 4</label>
<caption><p>Molecular docking of compounds with EGFR kinase: (A)
2D schematic diagram showing interactions of compound
STOCK1N-98911. (B) Cartoon view of EGFR kinase with compound
STOCK1N-98911.</p>
</caption>
<graphic xlink:href="97320630015287F4"></graphic>
</fig>
<fig id="F5" position="float"><label>Figure 5</label>
<caption><p>Boiled-egg Plot.</p>
</caption>
<graphic xlink:href="97320630015287F5"></graphic>
</fig>
</floats-group>
</pmc>
</record>
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