Research ArticleIdentification of a Potential Target of Capsaicin byComputational Target Fishing
Xuan-yi Ye1 Qing-zhi Ling2 and Shao-jun Chen2
1College of Ecology Lishui University Lishui Zhejiang 323000 China2Department of Traditional Chinese Medicine Zhejiang Pharmaceutical College Ningbo 315100 China
Correspondence should be addressed to Shao-jun Chen chenshaojunhotmailcom
Received 15 September 2015 Revised 17 November 2015 Accepted 18 November 2015
Academic Editor Ki-Wan Oh
Copyright copy 2015 Xuan-yi Ye et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Capsaicin the component responsible for the pungency of chili peppers shows beneficial effects in many diseases although theunderlying mechanisms remain unclear In the present study the potential targets of capsaicin were predicted using PharmMapperand confirmed via chemical-protein interactome (CPI) and molecular docking Carbonic anhydrase 2 was identified as the maindisease-related target with the pharmacophore model matching well with the molecular features of capsaicin The relation wasconfirmed by CPI and molecular docking and supported by previous research showing that capsaicin is a potent inhibitor ofcarbonic anhydrase isoenzymes The present study provides a basis for understanding the mechanisms of action of capsaicin orthose of other natural compounds
1 Introduction
Capsaicin (Figure 1) the component responsible for thepungency of chili peppers is an alkaloid from the Capsicumspecies which is used worldwide in foods spices andmedicines [1ndash4] Capsaicin has been used as traditionalmedicine to treat muscular pain and headaches to improvecirculation for its gastrointestinal protective effects and tofight against many types of cancer [4 5] It is commonlyadded to herbal formulations because it acts as a catalystfor other herbs and aids in their absorption [4] As a resultcapsaicin has become an exciting pharmacological agent andits utility in different clinical conditions is being explored [1]However the mechanisms underlying the therapeutic effectsof capsaicin remain unclear [1]
Target fishing or target identification is an importantstep in modern drug development that explores the mech-anism of action of bioactive small molecules by identifyingtheir interacting proteins [6 7] In recent years a largenumber of computational target fishing methods have beendeveloped [8] For example reverse or inverse docking rep-resents a useful tool that involves docking a small-moleculedrugligand into the potential binding cavities of a set ofclinically relevant macromolecular targets [9] Identification
of the top-ranking targets based on their binding affinity withthe drugligand may be relevant for drug repositioning andor rescue [9] In recent work from our group computationaltools were used to identify targets of Danshensu and Tanshi-none IIA [10 11] Computational target fishing technologieshave increased our ability to efficiently and effectively screenfor targets in a high-throughput format which is expected tohave a large impact on drug development [6 8]
In the present study potential targets of capsaicin werepredicted by reverse docking and confirmed via chemical-protein interactome (CPI) and molecular docking Thepresent study describes a computational drug repositioningmethod and explores its potential for elucidating the mecha-nism of action of natural compounds
2 Methods
21 Targets Predicted by PharmMapper PharmMapper is aweb server for potential drug target identification based onthe use of a pharmacophore mapping approach [12] It auto-matically finds the best mapping poses of the query moleculeagainst all the pharmacophore models in PharmTargetDBand lists the top N best-fitted hits with appropriate target
Hindawi Publishing CorporationEvidence-Based Complementary and Alternative MedicineVolume 2015 Article ID 983951 6 pageshttpdxdoiorg1011552015983951
2 Evidence-Based Complementary and Alternative Medicine
HH
HO
OH H
HH
H
H
H
H H
HH
H
H
H
H
H H
HH
HH H
H
H
N O
Figure 1 The chemical structure of capsaicin (PubChem CID 1548943)
annotations as well as the aligned poses of the respectivemolecules [12]
The molecular file of capsaicin was downloaded fromthe PubChem database (CID 1548943) and uploaded to thePharmMapper serverThe search started using themaximumgenerated conformations at 300 by selecting ldquoall targets(7302)rdquo option and default value of 300 for the number ofreserved matched targets as described previously [10 11 13]The default settings were used for other parameters
22 Targets Checked by the CPI TheCPI refers to the interac-tion information of a panel of chemicals across a panel oftarget proteins in terms of binding strength and binding con-formation for each chemical-protein pocket pair [14] BothDRAR-CPI and DDI-CPI are the servers for computationaldrug repositioning via the CPI [15 16]
The molecular file of capsaicin was downloaded and pre-treated following theweb instructions as described previously[11 15] Then it was submitted to the DRAR-CPI and DDI-CPI servers Parameters were set to default values
23 Molecular Docking Molecular docking is a computa-tional procedure that attempts to predict noncovalent bind-ing of macromolecules or a macromolecule (receptor) anda small molecule (ligand) efficiently [17] Autodock Vina inPyRx 08 is a new program for molecular docking and virtualscreening that has been widely used [17ndash19]
The target protein was prepared using the protein prepar-ing tool in TCM DatabaseTaiwan (httpdockcmuedutwligandphp) which can extract ligands from binding sitesprotonate protein structures and show ligand coordinatesand radius information as described previously [10 11]Thenthe ligand capsaicin was pretreated through OpenBabel inPyRx 08 During the docking procedure the grid box wascentered to cover the binding site residues and to allow theligand to move freely [10 11] The box was set to 10 times 10 times10 nm and the center coordinates are shown in Table 2Other parameters were set to default values
24 Visualization The 3D visualizations of the complexstructure were performed using soft PyMol and the diagramsof chemical-protein interactions were prepared using Ligplotsoftware
3 Results
31 Target Prediction by PharmMapper Ranking by fit scorein descending order and the top ten disease-related targetsare shown in Table 1 Carbonic anhydrase 2 (CA2) (PDB ID1BNV 1I9Q and 1I9O) ranked number one three and ninerespectively The pharmacophore model (1BNV) shows threehydrophobic sites one donor and three acceptors (Figure 2)Moreover the pharmacophoremodel showed thatCA2 iswellmatched with capsaicin (Figure 2)These results indicate that
Evidence-Based Complementary and Alternative Medicine 3
Table 1 Top ten potential disease-related targets of capsaicin predicted by PharmMapper
Table 2 Results of capsaicin-CA interactome by DRAR-CPI and DDI-CPI
DRAR-CPI DDI-CPIPDB ID Name Docking score 119885
1015840-score PDB ID Name Docking score
1JD0 CA 12 minus459539 148099 3CZV2FOY
CA 13CA 1
minus64
minus61
1Z93 CA 3 minus411238 179532 2FOU3FW3
CA 2CA 4
minus59
minus57
(a) (b) (c)
Figure 2 Alignment of capsaicin and pharmacophoremodel of CA2 (a) Capsaicin features (b) Pharmacophoremodel of CA2 (c)Molecularand pharmacophore model Note pharmacophore features are indicated by color as follows hydrophobic cyan positive blue negative reddonor green and acceptor magenta
CA2 may be a potential target of capsaicin Therefore CA2was selected for further investigation
32 Targets Verified by Chemical-Protein Interactome Whena drug is uploaded to the DRAR-CPI server it is ldquohybridizedrdquowith all targets using the DOCK program [15] Table 2shows the results of DRAR-CPI for capsaicin-CA (12 and 3)including the docking score and 1198851015840-score
When amolecule is submitted toDDI-CPI the server willdock it across 611 human proteins generating a CPI profilethat can be used as a feature vector of the preconstructed
predictionmodel [16] As shown inTable 2 fourCA isoformsincluding CA1 2 4 and 13 docked with capsaicin Thedocking score of capsaicin-CA2 was minus59 kcalmol Further-more the binding pattern of capsaicin-CA2 complex can bevisualized in Figure 3
33 Molecular Docking Upon docking using Autodock Vinain PyRx 08 the lowest binding energy of the capsaicin-CA2complex was minus62 kcalmol (Table 3) As shown in Figure 4the ligand capsaicin formed four hydrogen bonds with theactive site residues (Gln92 Thr199 and Thr200) A number
4 Evidence-Based Complementary and Alternative Medicine
Figure 3 Visualization of a capsaicin-CA2 complex captured from the DDI-CPI server Note protein chain rocket drug stick key residuescolorful line
(a)
Capsaicin
Leu198
Val121
His94
His64Asn62
Asn67
OE1CD
NE2CB
C6
C7C9
C18
C16C8C3C4
C5CG2
CBCA
OG1
O C
CG2O1 C10
NC1 C11C2 C14
C15
C13
C12
Pro201CBC
CAN
O OG1
N
C17
O3O2
N
CO
CGCA
315
316
276
Thr199
Gln92
Thr200
306
(b)
Figure 4 Molecular interactions between capsaicin and CA2 (a) 3D structure of the CA2 (1BVN)-capsaicin complex by PyMol Capsaicinyellow hydrogen bond red dash line (b) 2D interaction scheme by Ligplot Capsaicin yellow C N and O atoms are represented in blackblue and red hydrophobic contacts are presented in brick red
Table 3 The center coordinates of the binding site and the lowestbinding energy by molecular docking
PDB ID Name Center (119909 times 119910 times 119911) Bindingaffinity
1BNV Carbonicanhydrase 2 minus403 times 483 times 1443 minus62 kcalmol
of hydrophobic interactions are depicted in Figure 4(b)Many residues includingAsn62 His64 Asn67 His94 Val121
Leu198 and Pro201 formed hydrophobic contacts with cap-saicin
4 Discussion
The identification of drug targets in the human genomeis important for the development of new pharmaceuticalproducts and the allocation of resources in academic andindustrial biomedical research [20] Various innovative com-putational tools have been developed to integrate biologicaldata such as regulatory networks molecular pathways and
Evidence-Based Complementary and Alternative Medicine 5
cell phenotypes which facilitates the interpretation and pre-diction of the biological activities of drugs and their targets[8 21] Reverse or inverse docking is a powerful tool for drugrepositioning and drug rescue [9] Recently PharmMappera reverse docking server was used to identify potential targetsof small molecules derived from Indigofera species [22] andfor the computational prediction of breast cancer targets for6-methyl-138-trichlorodibenzofuran [13] In our previousreports we used the PharmMapper server to identify poten-tial targets of active compounds from Danshen a traditionalChinese medicine [10 11] We therefore used PharmMappera powerful computational tool to identify CA2 as themain disease-related target of capsaicin in the present study(Table 1) The CA2 pharmacophore confirmed the alignmentof molecular features with capsaicin (Figure 2)
The use of CPI together with systems biology-based inte-grative computational strategies is an essential complement ifnot an alternative to current drug evaluationmethods [14] InaDRAR-CPI job potential drug targets with1198851015840-scoreltminus1 areconsidered as the favorable targets and those with1198851015840-scoregt1are considered as the unfavorable targets [15] In a DDI-CPIjob the docking scores for each drug in the training set aregenerated against the 611 library targets [16] In the presentstudy 1198851015840-score in DRAR-CPI and docking score in DDI-CPI indicated that CA2 is a target of capsaicin and shouldbe further investigatedThese results were consistent with thereverse docking results (Table 1)
Understanding the interactions between proteins andbiologically relevant ligands is an important step towardsidentifying the functions of proteins [23] The hydrophobicsurface of the active site cavity of CA2 contains the residuesAla121 and 135 Val207 Phe91 Leu131 138 146 and 109and Pro201 and 202 and the hydrophilic surface consists ofHis64 67 and 200 Asn69 Gln92 Thr199 Tyr7 and Val62[24]Thr199 plays a significant role by forming two hydrogenbonds with the carboxyl group of Glu106 and zinc hydroxide[24] Residues Asn67 and Leu198 protrude towards the Zn2+ion and reduce the volume of the active site cavity consider-ably [24] His64 Asn67 and Gln92 residues are involved inhistidine recognition [24] In short these residues play keyroles in ligand-protein interactions The original ligand sul-fonamide forms hydrogen bonds with residues Gln92 His119Thr199 and Thr200 and forms hydrophobic interactionswith Phe131 [25] Figure 4(b) shows that capsaicin can formhydrogen bonds with Gln92 Thr199 and Thr200 and hashydrophobic interactions with Asn62 His64 Asn67 His94Val121 Leu198 andPro201The structural details indicate thatcapsaicin may interact with CA2 via these key residues [24]A previous study reported that capsaicin has119870
119894of 69615 120583M
against hCA I and of 20837 120583M against hCA II showingunique inhibition profiles against both CA isoforms I and IIand suggesting that capsaicin is a selective inhibitor of bothcytosolic CA isoenzymes [26]
CAs a group of ubiquitously expressed metalloenzymesare involved in numerous physiological and pathological pro-cesses including gluconeogenesis lipogenesis ureagenesistumorigenicity and the growth and virulence of various path-ogens [27] In addition to the established role of CA inhibitors(CAIs) as diuretics and antiglaucoma drugs the potential of
CAIs as novel antiobesity anticancer anti-infective and anti-Alzheimerrsquos drugs was recently shown [27] Taken togetherwith previous results our findings suggest that capsaicin mayplay a role in these diseases through its effect on CA2
In the present study potential targets of capsaicin wereidentified using PharmMapper and confirmed via CPI andAutodock Vina Our results identified CA2 as a potentialtarget of capsaicin although further studies are necessary todetermine their precise interaction The present study dem-onstrated that computational drug repositioning is a usefulstrategy to screen for targets of capsaicin or other naturalcompounds and suggested a mechanism of action of cap-saicin
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
This work was supported by Zhejiang Provincial Natural Sci-ence Foundation of China (LY15H280009) Ningbo Munic-ipal Natural Science Foundation (2015A610280) and theAdministration of Traditional Chinese Medicine of ZhejiangProvince (2014ZB110)
References
[1] S K Sharma A S Vij and M Sharma ldquoMechanisms andclinical uses of capsaicinrdquo European Journal of Pharmacologyvol 720 no 1ndash3 pp 55ndash62 2013
[2] M De Lourdes Reyes-Escogido E G Gonzalez-Mondragonand E Vazquez-Tzompantzi ldquoChemical and pharmacologicalaspects of capsaicinrdquo Molecules vol 16 no 2 pp 1253ndash12702011
[3] J Szolcsanyi ldquoForty years in capsaicin research for sensorypharmacology and physiologyrdquoNeuropeptides vol 38 no 6 pp377ndash384 2004
[4] X-F Huang J-Y Xue A-Q Jiang and H-L Zhu ldquoCapsaicinand its analogues structure-activity relationship studyrdquoCurrentMedicinal Chemistry vol 20 no 21 pp 2661ndash2672 2013
[5] I Dıaz-Laviada and N Rodrıguez-Henche ldquoThe potentialantitumor effects of capsaicinrdquo Progress in Drug Research vol68 pp 181ndash208 2014
[6] L Wang and X-Q Xie ldquoComputational target fishing whatshould chemogenomics researchers expect for the future of insilico drug design and discoveryrdquo Future Medicinal Chemistryvol 6 no 3 pp 247ndash249 2014
[7] B Lomenick RWOlsen and JHuang ldquoIdentification of directprotein targets of small moleculesrdquo ACS Chemical Biology vol6 no 1 pp 34ndash46 2011
[8] A Cereto-Massague M J Ojeda C Valls M Mulero GPujadas and S Garcia-Vallve ldquoTools for in silico target fishingrdquoMethods vol 71 pp 98ndash103 2015
[9] P S Kharkar S Warrier and R S Gaud ldquoReverse docking apowerful tool for drug repositioning and drug rescuerdquo FutureMedicinal Chemistry vol 6 no 3 pp 333ndash342 2014
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
2 Evidence-Based Complementary and Alternative Medicine
HH
HO
OH H
HH
H
H
H
H H
HH
H
H
H
H
H H
HH
HH H
H
H
N O
Figure 1 The chemical structure of capsaicin (PubChem CID 1548943)
annotations as well as the aligned poses of the respectivemolecules [12]
The molecular file of capsaicin was downloaded fromthe PubChem database (CID 1548943) and uploaded to thePharmMapper serverThe search started using themaximumgenerated conformations at 300 by selecting ldquoall targets(7302)rdquo option and default value of 300 for the number ofreserved matched targets as described previously [10 11 13]The default settings were used for other parameters
22 Targets Checked by the CPI TheCPI refers to the interac-tion information of a panel of chemicals across a panel oftarget proteins in terms of binding strength and binding con-formation for each chemical-protein pocket pair [14] BothDRAR-CPI and DDI-CPI are the servers for computationaldrug repositioning via the CPI [15 16]
The molecular file of capsaicin was downloaded and pre-treated following theweb instructions as described previously[11 15] Then it was submitted to the DRAR-CPI and DDI-CPI servers Parameters were set to default values
23 Molecular Docking Molecular docking is a computa-tional procedure that attempts to predict noncovalent bind-ing of macromolecules or a macromolecule (receptor) anda small molecule (ligand) efficiently [17] Autodock Vina inPyRx 08 is a new program for molecular docking and virtualscreening that has been widely used [17ndash19]
The target protein was prepared using the protein prepar-ing tool in TCM DatabaseTaiwan (httpdockcmuedutwligandphp) which can extract ligands from binding sitesprotonate protein structures and show ligand coordinatesand radius information as described previously [10 11]Thenthe ligand capsaicin was pretreated through OpenBabel inPyRx 08 During the docking procedure the grid box wascentered to cover the binding site residues and to allow theligand to move freely [10 11] The box was set to 10 times 10 times10 nm and the center coordinates are shown in Table 2Other parameters were set to default values
24 Visualization The 3D visualizations of the complexstructure were performed using soft PyMol and the diagramsof chemical-protein interactions were prepared using Ligplotsoftware
3 Results
31 Target Prediction by PharmMapper Ranking by fit scorein descending order and the top ten disease-related targetsare shown in Table 1 Carbonic anhydrase 2 (CA2) (PDB ID1BNV 1I9Q and 1I9O) ranked number one three and ninerespectively The pharmacophore model (1BNV) shows threehydrophobic sites one donor and three acceptors (Figure 2)Moreover the pharmacophoremodel showed thatCA2 iswellmatched with capsaicin (Figure 2)These results indicate that
Evidence-Based Complementary and Alternative Medicine 3
Table 1 Top ten potential disease-related targets of capsaicin predicted by PharmMapper
Table 2 Results of capsaicin-CA interactome by DRAR-CPI and DDI-CPI
DRAR-CPI DDI-CPIPDB ID Name Docking score 119885
1015840-score PDB ID Name Docking score
1JD0 CA 12 minus459539 148099 3CZV2FOY
CA 13CA 1
minus64
minus61
1Z93 CA 3 minus411238 179532 2FOU3FW3
CA 2CA 4
minus59
minus57
(a) (b) (c)
Figure 2 Alignment of capsaicin and pharmacophoremodel of CA2 (a) Capsaicin features (b) Pharmacophoremodel of CA2 (c)Molecularand pharmacophore model Note pharmacophore features are indicated by color as follows hydrophobic cyan positive blue negative reddonor green and acceptor magenta
CA2 may be a potential target of capsaicin Therefore CA2was selected for further investigation
32 Targets Verified by Chemical-Protein Interactome Whena drug is uploaded to the DRAR-CPI server it is ldquohybridizedrdquowith all targets using the DOCK program [15] Table 2shows the results of DRAR-CPI for capsaicin-CA (12 and 3)including the docking score and 1198851015840-score
When amolecule is submitted toDDI-CPI the server willdock it across 611 human proteins generating a CPI profilethat can be used as a feature vector of the preconstructed
predictionmodel [16] As shown inTable 2 fourCA isoformsincluding CA1 2 4 and 13 docked with capsaicin Thedocking score of capsaicin-CA2 was minus59 kcalmol Further-more the binding pattern of capsaicin-CA2 complex can bevisualized in Figure 3
33 Molecular Docking Upon docking using Autodock Vinain PyRx 08 the lowest binding energy of the capsaicin-CA2complex was minus62 kcalmol (Table 3) As shown in Figure 4the ligand capsaicin formed four hydrogen bonds with theactive site residues (Gln92 Thr199 and Thr200) A number
4 Evidence-Based Complementary and Alternative Medicine
Figure 3 Visualization of a capsaicin-CA2 complex captured from the DDI-CPI server Note protein chain rocket drug stick key residuescolorful line
(a)
Capsaicin
Leu198
Val121
His94
His64Asn62
Asn67
OE1CD
NE2CB
C6
C7C9
C18
C16C8C3C4
C5CG2
CBCA
OG1
O C
CG2O1 C10
NC1 C11C2 C14
C15
C13
C12
Pro201CBC
CAN
O OG1
N
C17
O3O2
N
CO
CGCA
315
316
276
Thr199
Gln92
Thr200
306
(b)
Figure 4 Molecular interactions between capsaicin and CA2 (a) 3D structure of the CA2 (1BVN)-capsaicin complex by PyMol Capsaicinyellow hydrogen bond red dash line (b) 2D interaction scheme by Ligplot Capsaicin yellow C N and O atoms are represented in blackblue and red hydrophobic contacts are presented in brick red
Table 3 The center coordinates of the binding site and the lowestbinding energy by molecular docking
PDB ID Name Center (119909 times 119910 times 119911) Bindingaffinity
1BNV Carbonicanhydrase 2 minus403 times 483 times 1443 minus62 kcalmol
of hydrophobic interactions are depicted in Figure 4(b)Many residues includingAsn62 His64 Asn67 His94 Val121
Leu198 and Pro201 formed hydrophobic contacts with cap-saicin
4 Discussion
The identification of drug targets in the human genomeis important for the development of new pharmaceuticalproducts and the allocation of resources in academic andindustrial biomedical research [20] Various innovative com-putational tools have been developed to integrate biologicaldata such as regulatory networks molecular pathways and
Evidence-Based Complementary and Alternative Medicine 5
cell phenotypes which facilitates the interpretation and pre-diction of the biological activities of drugs and their targets[8 21] Reverse or inverse docking is a powerful tool for drugrepositioning and drug rescue [9] Recently PharmMappera reverse docking server was used to identify potential targetsof small molecules derived from Indigofera species [22] andfor the computational prediction of breast cancer targets for6-methyl-138-trichlorodibenzofuran [13] In our previousreports we used the PharmMapper server to identify poten-tial targets of active compounds from Danshen a traditionalChinese medicine [10 11] We therefore used PharmMappera powerful computational tool to identify CA2 as themain disease-related target of capsaicin in the present study(Table 1) The CA2 pharmacophore confirmed the alignmentof molecular features with capsaicin (Figure 2)
The use of CPI together with systems biology-based inte-grative computational strategies is an essential complement ifnot an alternative to current drug evaluationmethods [14] InaDRAR-CPI job potential drug targets with1198851015840-scoreltminus1 areconsidered as the favorable targets and those with1198851015840-scoregt1are considered as the unfavorable targets [15] In a DDI-CPIjob the docking scores for each drug in the training set aregenerated against the 611 library targets [16] In the presentstudy 1198851015840-score in DRAR-CPI and docking score in DDI-CPI indicated that CA2 is a target of capsaicin and shouldbe further investigatedThese results were consistent with thereverse docking results (Table 1)
Understanding the interactions between proteins andbiologically relevant ligands is an important step towardsidentifying the functions of proteins [23] The hydrophobicsurface of the active site cavity of CA2 contains the residuesAla121 and 135 Val207 Phe91 Leu131 138 146 and 109and Pro201 and 202 and the hydrophilic surface consists ofHis64 67 and 200 Asn69 Gln92 Thr199 Tyr7 and Val62[24]Thr199 plays a significant role by forming two hydrogenbonds with the carboxyl group of Glu106 and zinc hydroxide[24] Residues Asn67 and Leu198 protrude towards the Zn2+ion and reduce the volume of the active site cavity consider-ably [24] His64 Asn67 and Gln92 residues are involved inhistidine recognition [24] In short these residues play keyroles in ligand-protein interactions The original ligand sul-fonamide forms hydrogen bonds with residues Gln92 His119Thr199 and Thr200 and forms hydrophobic interactionswith Phe131 [25] Figure 4(b) shows that capsaicin can formhydrogen bonds with Gln92 Thr199 and Thr200 and hashydrophobic interactions with Asn62 His64 Asn67 His94Val121 Leu198 andPro201The structural details indicate thatcapsaicin may interact with CA2 via these key residues [24]A previous study reported that capsaicin has119870
119894of 69615 120583M
against hCA I and of 20837 120583M against hCA II showingunique inhibition profiles against both CA isoforms I and IIand suggesting that capsaicin is a selective inhibitor of bothcytosolic CA isoenzymes [26]
CAs a group of ubiquitously expressed metalloenzymesare involved in numerous physiological and pathological pro-cesses including gluconeogenesis lipogenesis ureagenesistumorigenicity and the growth and virulence of various path-ogens [27] In addition to the established role of CA inhibitors(CAIs) as diuretics and antiglaucoma drugs the potential of
CAIs as novel antiobesity anticancer anti-infective and anti-Alzheimerrsquos drugs was recently shown [27] Taken togetherwith previous results our findings suggest that capsaicin mayplay a role in these diseases through its effect on CA2
In the present study potential targets of capsaicin wereidentified using PharmMapper and confirmed via CPI andAutodock Vina Our results identified CA2 as a potentialtarget of capsaicin although further studies are necessary todetermine their precise interaction The present study dem-onstrated that computational drug repositioning is a usefulstrategy to screen for targets of capsaicin or other naturalcompounds and suggested a mechanism of action of cap-saicin
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
This work was supported by Zhejiang Provincial Natural Sci-ence Foundation of China (LY15H280009) Ningbo Munic-ipal Natural Science Foundation (2015A610280) and theAdministration of Traditional Chinese Medicine of ZhejiangProvince (2014ZB110)
References
[1] S K Sharma A S Vij and M Sharma ldquoMechanisms andclinical uses of capsaicinrdquo European Journal of Pharmacologyvol 720 no 1ndash3 pp 55ndash62 2013
[2] M De Lourdes Reyes-Escogido E G Gonzalez-Mondragonand E Vazquez-Tzompantzi ldquoChemical and pharmacologicalaspects of capsaicinrdquo Molecules vol 16 no 2 pp 1253ndash12702011
[3] J Szolcsanyi ldquoForty years in capsaicin research for sensorypharmacology and physiologyrdquoNeuropeptides vol 38 no 6 pp377ndash384 2004
[4] X-F Huang J-Y Xue A-Q Jiang and H-L Zhu ldquoCapsaicinand its analogues structure-activity relationship studyrdquoCurrentMedicinal Chemistry vol 20 no 21 pp 2661ndash2672 2013
[5] I Dıaz-Laviada and N Rodrıguez-Henche ldquoThe potentialantitumor effects of capsaicinrdquo Progress in Drug Research vol68 pp 181ndash208 2014
[6] L Wang and X-Q Xie ldquoComputational target fishing whatshould chemogenomics researchers expect for the future of insilico drug design and discoveryrdquo Future Medicinal Chemistryvol 6 no 3 pp 247ndash249 2014
[7] B Lomenick RWOlsen and JHuang ldquoIdentification of directprotein targets of small moleculesrdquo ACS Chemical Biology vol6 no 1 pp 34ndash46 2011
[8] A Cereto-Massague M J Ojeda C Valls M Mulero GPujadas and S Garcia-Vallve ldquoTools for in silico target fishingrdquoMethods vol 71 pp 98ndash103 2015
[9] P S Kharkar S Warrier and R S Gaud ldquoReverse docking apowerful tool for drug repositioning and drug rescuerdquo FutureMedicinal Chemistry vol 6 no 3 pp 333ndash342 2014
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
Evidence-Based Complementary and Alternative Medicine 3
Table 1 Top ten potential disease-related targets of capsaicin predicted by PharmMapper
Table 2 Results of capsaicin-CA interactome by DRAR-CPI and DDI-CPI
DRAR-CPI DDI-CPIPDB ID Name Docking score 119885
1015840-score PDB ID Name Docking score
1JD0 CA 12 minus459539 148099 3CZV2FOY
CA 13CA 1
minus64
minus61
1Z93 CA 3 minus411238 179532 2FOU3FW3
CA 2CA 4
minus59
minus57
(a) (b) (c)
Figure 2 Alignment of capsaicin and pharmacophoremodel of CA2 (a) Capsaicin features (b) Pharmacophoremodel of CA2 (c)Molecularand pharmacophore model Note pharmacophore features are indicated by color as follows hydrophobic cyan positive blue negative reddonor green and acceptor magenta
CA2 may be a potential target of capsaicin Therefore CA2was selected for further investigation
32 Targets Verified by Chemical-Protein Interactome Whena drug is uploaded to the DRAR-CPI server it is ldquohybridizedrdquowith all targets using the DOCK program [15] Table 2shows the results of DRAR-CPI for capsaicin-CA (12 and 3)including the docking score and 1198851015840-score
When amolecule is submitted toDDI-CPI the server willdock it across 611 human proteins generating a CPI profilethat can be used as a feature vector of the preconstructed
predictionmodel [16] As shown inTable 2 fourCA isoformsincluding CA1 2 4 and 13 docked with capsaicin Thedocking score of capsaicin-CA2 was minus59 kcalmol Further-more the binding pattern of capsaicin-CA2 complex can bevisualized in Figure 3
33 Molecular Docking Upon docking using Autodock Vinain PyRx 08 the lowest binding energy of the capsaicin-CA2complex was minus62 kcalmol (Table 3) As shown in Figure 4the ligand capsaicin formed four hydrogen bonds with theactive site residues (Gln92 Thr199 and Thr200) A number
4 Evidence-Based Complementary and Alternative Medicine
Figure 3 Visualization of a capsaicin-CA2 complex captured from the DDI-CPI server Note protein chain rocket drug stick key residuescolorful line
(a)
Capsaicin
Leu198
Val121
His94
His64Asn62
Asn67
OE1CD
NE2CB
C6
C7C9
C18
C16C8C3C4
C5CG2
CBCA
OG1
O C
CG2O1 C10
NC1 C11C2 C14
C15
C13
C12
Pro201CBC
CAN
O OG1
N
C17
O3O2
N
CO
CGCA
315
316
276
Thr199
Gln92
Thr200
306
(b)
Figure 4 Molecular interactions between capsaicin and CA2 (a) 3D structure of the CA2 (1BVN)-capsaicin complex by PyMol Capsaicinyellow hydrogen bond red dash line (b) 2D interaction scheme by Ligplot Capsaicin yellow C N and O atoms are represented in blackblue and red hydrophobic contacts are presented in brick red
Table 3 The center coordinates of the binding site and the lowestbinding energy by molecular docking
PDB ID Name Center (119909 times 119910 times 119911) Bindingaffinity
1BNV Carbonicanhydrase 2 minus403 times 483 times 1443 minus62 kcalmol
of hydrophobic interactions are depicted in Figure 4(b)Many residues includingAsn62 His64 Asn67 His94 Val121
Leu198 and Pro201 formed hydrophobic contacts with cap-saicin
4 Discussion
The identification of drug targets in the human genomeis important for the development of new pharmaceuticalproducts and the allocation of resources in academic andindustrial biomedical research [20] Various innovative com-putational tools have been developed to integrate biologicaldata such as regulatory networks molecular pathways and
Evidence-Based Complementary and Alternative Medicine 5
cell phenotypes which facilitates the interpretation and pre-diction of the biological activities of drugs and their targets[8 21] Reverse or inverse docking is a powerful tool for drugrepositioning and drug rescue [9] Recently PharmMappera reverse docking server was used to identify potential targetsof small molecules derived from Indigofera species [22] andfor the computational prediction of breast cancer targets for6-methyl-138-trichlorodibenzofuran [13] In our previousreports we used the PharmMapper server to identify poten-tial targets of active compounds from Danshen a traditionalChinese medicine [10 11] We therefore used PharmMappera powerful computational tool to identify CA2 as themain disease-related target of capsaicin in the present study(Table 1) The CA2 pharmacophore confirmed the alignmentof molecular features with capsaicin (Figure 2)
The use of CPI together with systems biology-based inte-grative computational strategies is an essential complement ifnot an alternative to current drug evaluationmethods [14] InaDRAR-CPI job potential drug targets with1198851015840-scoreltminus1 areconsidered as the favorable targets and those with1198851015840-scoregt1are considered as the unfavorable targets [15] In a DDI-CPIjob the docking scores for each drug in the training set aregenerated against the 611 library targets [16] In the presentstudy 1198851015840-score in DRAR-CPI and docking score in DDI-CPI indicated that CA2 is a target of capsaicin and shouldbe further investigatedThese results were consistent with thereverse docking results (Table 1)
Understanding the interactions between proteins andbiologically relevant ligands is an important step towardsidentifying the functions of proteins [23] The hydrophobicsurface of the active site cavity of CA2 contains the residuesAla121 and 135 Val207 Phe91 Leu131 138 146 and 109and Pro201 and 202 and the hydrophilic surface consists ofHis64 67 and 200 Asn69 Gln92 Thr199 Tyr7 and Val62[24]Thr199 plays a significant role by forming two hydrogenbonds with the carboxyl group of Glu106 and zinc hydroxide[24] Residues Asn67 and Leu198 protrude towards the Zn2+ion and reduce the volume of the active site cavity consider-ably [24] His64 Asn67 and Gln92 residues are involved inhistidine recognition [24] In short these residues play keyroles in ligand-protein interactions The original ligand sul-fonamide forms hydrogen bonds with residues Gln92 His119Thr199 and Thr200 and forms hydrophobic interactionswith Phe131 [25] Figure 4(b) shows that capsaicin can formhydrogen bonds with Gln92 Thr199 and Thr200 and hashydrophobic interactions with Asn62 His64 Asn67 His94Val121 Leu198 andPro201The structural details indicate thatcapsaicin may interact with CA2 via these key residues [24]A previous study reported that capsaicin has119870
119894of 69615 120583M
against hCA I and of 20837 120583M against hCA II showingunique inhibition profiles against both CA isoforms I and IIand suggesting that capsaicin is a selective inhibitor of bothcytosolic CA isoenzymes [26]
CAs a group of ubiquitously expressed metalloenzymesare involved in numerous physiological and pathological pro-cesses including gluconeogenesis lipogenesis ureagenesistumorigenicity and the growth and virulence of various path-ogens [27] In addition to the established role of CA inhibitors(CAIs) as diuretics and antiglaucoma drugs the potential of
CAIs as novel antiobesity anticancer anti-infective and anti-Alzheimerrsquos drugs was recently shown [27] Taken togetherwith previous results our findings suggest that capsaicin mayplay a role in these diseases through its effect on CA2
In the present study potential targets of capsaicin wereidentified using PharmMapper and confirmed via CPI andAutodock Vina Our results identified CA2 as a potentialtarget of capsaicin although further studies are necessary todetermine their precise interaction The present study dem-onstrated that computational drug repositioning is a usefulstrategy to screen for targets of capsaicin or other naturalcompounds and suggested a mechanism of action of cap-saicin
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
This work was supported by Zhejiang Provincial Natural Sci-ence Foundation of China (LY15H280009) Ningbo Munic-ipal Natural Science Foundation (2015A610280) and theAdministration of Traditional Chinese Medicine of ZhejiangProvince (2014ZB110)
References
[1] S K Sharma A S Vij and M Sharma ldquoMechanisms andclinical uses of capsaicinrdquo European Journal of Pharmacologyvol 720 no 1ndash3 pp 55ndash62 2013
[2] M De Lourdes Reyes-Escogido E G Gonzalez-Mondragonand E Vazquez-Tzompantzi ldquoChemical and pharmacologicalaspects of capsaicinrdquo Molecules vol 16 no 2 pp 1253ndash12702011
[3] J Szolcsanyi ldquoForty years in capsaicin research for sensorypharmacology and physiologyrdquoNeuropeptides vol 38 no 6 pp377ndash384 2004
[4] X-F Huang J-Y Xue A-Q Jiang and H-L Zhu ldquoCapsaicinand its analogues structure-activity relationship studyrdquoCurrentMedicinal Chemistry vol 20 no 21 pp 2661ndash2672 2013
[5] I Dıaz-Laviada and N Rodrıguez-Henche ldquoThe potentialantitumor effects of capsaicinrdquo Progress in Drug Research vol68 pp 181ndash208 2014
[6] L Wang and X-Q Xie ldquoComputational target fishing whatshould chemogenomics researchers expect for the future of insilico drug design and discoveryrdquo Future Medicinal Chemistryvol 6 no 3 pp 247ndash249 2014
[7] B Lomenick RWOlsen and JHuang ldquoIdentification of directprotein targets of small moleculesrdquo ACS Chemical Biology vol6 no 1 pp 34ndash46 2011
[8] A Cereto-Massague M J Ojeda C Valls M Mulero GPujadas and S Garcia-Vallve ldquoTools for in silico target fishingrdquoMethods vol 71 pp 98ndash103 2015
[9] P S Kharkar S Warrier and R S Gaud ldquoReverse docking apowerful tool for drug repositioning and drug rescuerdquo FutureMedicinal Chemistry vol 6 no 3 pp 333ndash342 2014
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
4 Evidence-Based Complementary and Alternative Medicine
Figure 3 Visualization of a capsaicin-CA2 complex captured from the DDI-CPI server Note protein chain rocket drug stick key residuescolorful line
(a)
Capsaicin
Leu198
Val121
His94
His64Asn62
Asn67
OE1CD
NE2CB
C6
C7C9
C18
C16C8C3C4
C5CG2
CBCA
OG1
O C
CG2O1 C10
NC1 C11C2 C14
C15
C13
C12
Pro201CBC
CAN
O OG1
N
C17
O3O2
N
CO
CGCA
315
316
276
Thr199
Gln92
Thr200
306
(b)
Figure 4 Molecular interactions between capsaicin and CA2 (a) 3D structure of the CA2 (1BVN)-capsaicin complex by PyMol Capsaicinyellow hydrogen bond red dash line (b) 2D interaction scheme by Ligplot Capsaicin yellow C N and O atoms are represented in blackblue and red hydrophobic contacts are presented in brick red
Table 3 The center coordinates of the binding site and the lowestbinding energy by molecular docking
PDB ID Name Center (119909 times 119910 times 119911) Bindingaffinity
1BNV Carbonicanhydrase 2 minus403 times 483 times 1443 minus62 kcalmol
of hydrophobic interactions are depicted in Figure 4(b)Many residues includingAsn62 His64 Asn67 His94 Val121
Leu198 and Pro201 formed hydrophobic contacts with cap-saicin
4 Discussion
The identification of drug targets in the human genomeis important for the development of new pharmaceuticalproducts and the allocation of resources in academic andindustrial biomedical research [20] Various innovative com-putational tools have been developed to integrate biologicaldata such as regulatory networks molecular pathways and
Evidence-Based Complementary and Alternative Medicine 5
cell phenotypes which facilitates the interpretation and pre-diction of the biological activities of drugs and their targets[8 21] Reverse or inverse docking is a powerful tool for drugrepositioning and drug rescue [9] Recently PharmMappera reverse docking server was used to identify potential targetsof small molecules derived from Indigofera species [22] andfor the computational prediction of breast cancer targets for6-methyl-138-trichlorodibenzofuran [13] In our previousreports we used the PharmMapper server to identify poten-tial targets of active compounds from Danshen a traditionalChinese medicine [10 11] We therefore used PharmMappera powerful computational tool to identify CA2 as themain disease-related target of capsaicin in the present study(Table 1) The CA2 pharmacophore confirmed the alignmentof molecular features with capsaicin (Figure 2)
The use of CPI together with systems biology-based inte-grative computational strategies is an essential complement ifnot an alternative to current drug evaluationmethods [14] InaDRAR-CPI job potential drug targets with1198851015840-scoreltminus1 areconsidered as the favorable targets and those with1198851015840-scoregt1are considered as the unfavorable targets [15] In a DDI-CPIjob the docking scores for each drug in the training set aregenerated against the 611 library targets [16] In the presentstudy 1198851015840-score in DRAR-CPI and docking score in DDI-CPI indicated that CA2 is a target of capsaicin and shouldbe further investigatedThese results were consistent with thereverse docking results (Table 1)
Understanding the interactions between proteins andbiologically relevant ligands is an important step towardsidentifying the functions of proteins [23] The hydrophobicsurface of the active site cavity of CA2 contains the residuesAla121 and 135 Val207 Phe91 Leu131 138 146 and 109and Pro201 and 202 and the hydrophilic surface consists ofHis64 67 and 200 Asn69 Gln92 Thr199 Tyr7 and Val62[24]Thr199 plays a significant role by forming two hydrogenbonds with the carboxyl group of Glu106 and zinc hydroxide[24] Residues Asn67 and Leu198 protrude towards the Zn2+ion and reduce the volume of the active site cavity consider-ably [24] His64 Asn67 and Gln92 residues are involved inhistidine recognition [24] In short these residues play keyroles in ligand-protein interactions The original ligand sul-fonamide forms hydrogen bonds with residues Gln92 His119Thr199 and Thr200 and forms hydrophobic interactionswith Phe131 [25] Figure 4(b) shows that capsaicin can formhydrogen bonds with Gln92 Thr199 and Thr200 and hashydrophobic interactions with Asn62 His64 Asn67 His94Val121 Leu198 andPro201The structural details indicate thatcapsaicin may interact with CA2 via these key residues [24]A previous study reported that capsaicin has119870
119894of 69615 120583M
against hCA I and of 20837 120583M against hCA II showingunique inhibition profiles against both CA isoforms I and IIand suggesting that capsaicin is a selective inhibitor of bothcytosolic CA isoenzymes [26]
CAs a group of ubiquitously expressed metalloenzymesare involved in numerous physiological and pathological pro-cesses including gluconeogenesis lipogenesis ureagenesistumorigenicity and the growth and virulence of various path-ogens [27] In addition to the established role of CA inhibitors(CAIs) as diuretics and antiglaucoma drugs the potential of
CAIs as novel antiobesity anticancer anti-infective and anti-Alzheimerrsquos drugs was recently shown [27] Taken togetherwith previous results our findings suggest that capsaicin mayplay a role in these diseases through its effect on CA2
In the present study potential targets of capsaicin wereidentified using PharmMapper and confirmed via CPI andAutodock Vina Our results identified CA2 as a potentialtarget of capsaicin although further studies are necessary todetermine their precise interaction The present study dem-onstrated that computational drug repositioning is a usefulstrategy to screen for targets of capsaicin or other naturalcompounds and suggested a mechanism of action of cap-saicin
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
This work was supported by Zhejiang Provincial Natural Sci-ence Foundation of China (LY15H280009) Ningbo Munic-ipal Natural Science Foundation (2015A610280) and theAdministration of Traditional Chinese Medicine of ZhejiangProvince (2014ZB110)
References
[1] S K Sharma A S Vij and M Sharma ldquoMechanisms andclinical uses of capsaicinrdquo European Journal of Pharmacologyvol 720 no 1ndash3 pp 55ndash62 2013
[2] M De Lourdes Reyes-Escogido E G Gonzalez-Mondragonand E Vazquez-Tzompantzi ldquoChemical and pharmacologicalaspects of capsaicinrdquo Molecules vol 16 no 2 pp 1253ndash12702011
[3] J Szolcsanyi ldquoForty years in capsaicin research for sensorypharmacology and physiologyrdquoNeuropeptides vol 38 no 6 pp377ndash384 2004
[4] X-F Huang J-Y Xue A-Q Jiang and H-L Zhu ldquoCapsaicinand its analogues structure-activity relationship studyrdquoCurrentMedicinal Chemistry vol 20 no 21 pp 2661ndash2672 2013
[5] I Dıaz-Laviada and N Rodrıguez-Henche ldquoThe potentialantitumor effects of capsaicinrdquo Progress in Drug Research vol68 pp 181ndash208 2014
[6] L Wang and X-Q Xie ldquoComputational target fishing whatshould chemogenomics researchers expect for the future of insilico drug design and discoveryrdquo Future Medicinal Chemistryvol 6 no 3 pp 247ndash249 2014
[7] B Lomenick RWOlsen and JHuang ldquoIdentification of directprotein targets of small moleculesrdquo ACS Chemical Biology vol6 no 1 pp 34ndash46 2011
[8] A Cereto-Massague M J Ojeda C Valls M Mulero GPujadas and S Garcia-Vallve ldquoTools for in silico target fishingrdquoMethods vol 71 pp 98ndash103 2015
[9] P S Kharkar S Warrier and R S Gaud ldquoReverse docking apowerful tool for drug repositioning and drug rescuerdquo FutureMedicinal Chemistry vol 6 no 3 pp 333ndash342 2014
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
Evidence-Based Complementary and Alternative Medicine 5
cell phenotypes which facilitates the interpretation and pre-diction of the biological activities of drugs and their targets[8 21] Reverse or inverse docking is a powerful tool for drugrepositioning and drug rescue [9] Recently PharmMappera reverse docking server was used to identify potential targetsof small molecules derived from Indigofera species [22] andfor the computational prediction of breast cancer targets for6-methyl-138-trichlorodibenzofuran [13] In our previousreports we used the PharmMapper server to identify poten-tial targets of active compounds from Danshen a traditionalChinese medicine [10 11] We therefore used PharmMappera powerful computational tool to identify CA2 as themain disease-related target of capsaicin in the present study(Table 1) The CA2 pharmacophore confirmed the alignmentof molecular features with capsaicin (Figure 2)
The use of CPI together with systems biology-based inte-grative computational strategies is an essential complement ifnot an alternative to current drug evaluationmethods [14] InaDRAR-CPI job potential drug targets with1198851015840-scoreltminus1 areconsidered as the favorable targets and those with1198851015840-scoregt1are considered as the unfavorable targets [15] In a DDI-CPIjob the docking scores for each drug in the training set aregenerated against the 611 library targets [16] In the presentstudy 1198851015840-score in DRAR-CPI and docking score in DDI-CPI indicated that CA2 is a target of capsaicin and shouldbe further investigatedThese results were consistent with thereverse docking results (Table 1)
Understanding the interactions between proteins andbiologically relevant ligands is an important step towardsidentifying the functions of proteins [23] The hydrophobicsurface of the active site cavity of CA2 contains the residuesAla121 and 135 Val207 Phe91 Leu131 138 146 and 109and Pro201 and 202 and the hydrophilic surface consists ofHis64 67 and 200 Asn69 Gln92 Thr199 Tyr7 and Val62[24]Thr199 plays a significant role by forming two hydrogenbonds with the carboxyl group of Glu106 and zinc hydroxide[24] Residues Asn67 and Leu198 protrude towards the Zn2+ion and reduce the volume of the active site cavity consider-ably [24] His64 Asn67 and Gln92 residues are involved inhistidine recognition [24] In short these residues play keyroles in ligand-protein interactions The original ligand sul-fonamide forms hydrogen bonds with residues Gln92 His119Thr199 and Thr200 and forms hydrophobic interactionswith Phe131 [25] Figure 4(b) shows that capsaicin can formhydrogen bonds with Gln92 Thr199 and Thr200 and hashydrophobic interactions with Asn62 His64 Asn67 His94Val121 Leu198 andPro201The structural details indicate thatcapsaicin may interact with CA2 via these key residues [24]A previous study reported that capsaicin has119870
119894of 69615 120583M
against hCA I and of 20837 120583M against hCA II showingunique inhibition profiles against both CA isoforms I and IIand suggesting that capsaicin is a selective inhibitor of bothcytosolic CA isoenzymes [26]
CAs a group of ubiquitously expressed metalloenzymesare involved in numerous physiological and pathological pro-cesses including gluconeogenesis lipogenesis ureagenesistumorigenicity and the growth and virulence of various path-ogens [27] In addition to the established role of CA inhibitors(CAIs) as diuretics and antiglaucoma drugs the potential of
CAIs as novel antiobesity anticancer anti-infective and anti-Alzheimerrsquos drugs was recently shown [27] Taken togetherwith previous results our findings suggest that capsaicin mayplay a role in these diseases through its effect on CA2
In the present study potential targets of capsaicin wereidentified using PharmMapper and confirmed via CPI andAutodock Vina Our results identified CA2 as a potentialtarget of capsaicin although further studies are necessary todetermine their precise interaction The present study dem-onstrated that computational drug repositioning is a usefulstrategy to screen for targets of capsaicin or other naturalcompounds and suggested a mechanism of action of cap-saicin
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
This work was supported by Zhejiang Provincial Natural Sci-ence Foundation of China (LY15H280009) Ningbo Munic-ipal Natural Science Foundation (2015A610280) and theAdministration of Traditional Chinese Medicine of ZhejiangProvince (2014ZB110)
References
[1] S K Sharma A S Vij and M Sharma ldquoMechanisms andclinical uses of capsaicinrdquo European Journal of Pharmacologyvol 720 no 1ndash3 pp 55ndash62 2013
[2] M De Lourdes Reyes-Escogido E G Gonzalez-Mondragonand E Vazquez-Tzompantzi ldquoChemical and pharmacologicalaspects of capsaicinrdquo Molecules vol 16 no 2 pp 1253ndash12702011
[3] J Szolcsanyi ldquoForty years in capsaicin research for sensorypharmacology and physiologyrdquoNeuropeptides vol 38 no 6 pp377ndash384 2004
[4] X-F Huang J-Y Xue A-Q Jiang and H-L Zhu ldquoCapsaicinand its analogues structure-activity relationship studyrdquoCurrentMedicinal Chemistry vol 20 no 21 pp 2661ndash2672 2013
[5] I Dıaz-Laviada and N Rodrıguez-Henche ldquoThe potentialantitumor effects of capsaicinrdquo Progress in Drug Research vol68 pp 181ndash208 2014
[6] L Wang and X-Q Xie ldquoComputational target fishing whatshould chemogenomics researchers expect for the future of insilico drug design and discoveryrdquo Future Medicinal Chemistryvol 6 no 3 pp 247ndash249 2014
[7] B Lomenick RWOlsen and JHuang ldquoIdentification of directprotein targets of small moleculesrdquo ACS Chemical Biology vol6 no 1 pp 34ndash46 2011
[8] A Cereto-Massague M J Ojeda C Valls M Mulero GPujadas and S Garcia-Vallve ldquoTools for in silico target fishingrdquoMethods vol 71 pp 98ndash103 2015
[9] P S Kharkar S Warrier and R S Gaud ldquoReverse docking apowerful tool for drug repositioning and drug rescuerdquo FutureMedicinal Chemistry vol 6 no 3 pp 333ndash342 2014
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
6 Evidence-Based Complementary and Alternative Medicine
[10] S-J Chen and J-L Ren ldquoIdentification of a potential anticancertarget of Danshensu by inverse dockingrdquo Asian Pacific Journalof Cancer Prevention vol 15 no 1 pp 111ndash116 2014
[11] S-J Chen ldquoA potential target of Tanshinone IIA for acutepromyelocytic leukemia revealed by inverse docking and drugrepurposingrdquoAsian Pacific Journal of Cancer Prevention vol 15no 10 pp 4301ndash4305 2014
[12] X Liu S Ouyang B Yu et al ldquoPharmMapper server a webserver for potential drug target identification using pharma-cophore mapping approachrdquoNucleic Acids Research vol 38 no2 pp W609ndashW614 2010
[13] K N Chitrala and S Yeguvapalli ldquoComputational predictionand analysis of breast cancer targets for 6-methyl-1 3 8-trichlorodibenzofuranrdquo PLoS ONE vol 9 no 11 Article IDe109185 2014
[14] L Yang K J Wang L S Wang et al ldquoChemical-proteininteractome and its application in off-target identificationrdquoInterdisciplinary Sciences Computational Life Sciences vol 3 no1 pp 22ndash30 2011
[15] H Luo J Chen L Shi et al ldquoDRAR-CPI a server for identifyingdrug repositioning potential and adverse drug reactions via thechemical-protein interactomerdquo Nucleic Acids Research vol 39supplement 2 pp W492ndashW498 2011
[16] H Luo P Zhang H Huang et al ldquoDDI-CPI a server thatpredicts drug-drug interactions through implementing thechemical-protein interactomerdquo Nucleic Acids Research vol 42no 1 pp W46ndashW52 2014
[17] O Trott and A J Olson ldquoAutoDock Vina improving the speedand accuracy of docking with a new scoring function efficientoptimization and multithreadingrdquo Journal of ComputationalChemistry vol 31 no 2 pp 455ndash461 2010
[18] A Sridhar S Saremy and B Bhattacharjee ldquoElucidation ofmolecular targets of bioactive principles of black cumin relevantto its anti-tumour functionalitymdashan Insilico target fishingapproachrdquo Bioinformation vol 10 no 11 pp 684ndash688 2014
[19] S Kumar L Jena K Mohod S Daf and A K VarmaldquoVirtual screening for potential inhibitors of high-risk humanpapillomavirus 16 E6 proteinrdquo Interdisciplinary Sciences Com-putational Life Sciences vol 7 no 2 pp 136ndash142 2015
[20] M Rask-Andersen M S Almen and H B Schioth ldquoTrendsin the exploitation of novel drug targetsrdquo Nature Reviews DrugDiscovery vol 10 no 8 pp 579ndash590 2011
[21] J N Y Chan C Nislow and A Emili ldquoRecent advances andmethod development for drug target identificationrdquo Trends inPharmacological Sciences vol 31 no 2 pp 82ndash88 2010
[22] S K Paramashivam K Elayaperumal B B Natarajan MRamamoorthy S Balasubramanian and K Dhiraviam ldquoInsilico pharmacokinetic and molecular docking studies of smallmolecules derived from Indigofera aspalathoides Vahl targetingreceptor tyrosine kinasesrdquo Bioinformation vol 11 no 2 pp 73ndash84 2015
[23] J Yang A Roy and Y Zhang ldquoBioLiP a semi-manually curateddatabase for biologically relevant ligand-protein interactionsrdquoNucleic Acids Research vol 41 no 1 pp D1096ndashD1103 2013
[24] M Imtaiyaz Hassan B Shajee A Waheed F Ahmad andW SSly ldquoStructure function and applications of carbonic anhydraseisozymesrdquo Bioorganic and Medicinal Chemistry vol 21 no 6pp 1570ndash1582 2013
[25] P A Boriack-Sjodin S Zeitlin H-H Chen et al ldquoStructuralanalysis of inhibitor binding to human carbonic anhydrase IIrdquoProtein Science vol 7 no 12 pp 2483ndash2489 1998
[26] B Arabaci I Gulcin and S Alwasel ldquoCapsaicin a potentinhibitor of carbonic anhydrase isoenzymesrdquoMolecules vol 19no 7 pp 10103ndash10114 2014
[27] C T Supuran ldquoCarbonic anhydrases novel therapeutic appli-cations for inhibitors and activatorsrdquo Nature Reviews DrugDiscovery vol 7 no 2 pp 168ndash181 2008
