in silico investigation of the association of the trpm8 ion channel with the pungent flavor of chinese herbs

In silico investigation of the association ofthe TRPM8 ion channel with the pungent flavor of Chinese herbs Yu-xin Zhang a,c, Xing Wangb,c, Shi-feng Wanga, Qiao Zhang a, Sha Peng a, Xi L

In silico investigation of the association of

the TRPM8 ion channel with the pungent

flavor of Chinese herbs

Yu-xin Zhang a,c, Xing Wangb,c, Shi-feng Wanga, Qiao Zhang a,

Sha Peng a, Xi Li a, Yan-Ling Zhanga,*, Yan-Jiang Qiao a,**

a

Key Laboratory of TCM-Information Engineer of State Administration of TCM, School of Chinese

Materia Medica, Beijing University of Chinese Medicine, 6 Wangjing Zhonghuan South Road, Beijing

100102, China

b

Beijing Key Lab of Traditional Chinese Medicine (TCM) Collateral Disease Theory Research, School of

Traditional Chinese Medicine, Capital Medical University, 10 Youanmen, Xitoutiao, Beijing 100069,

China

Received 27 February 2016; received in revised form 30 December 2016; accepted 30 December 2016

Available online

-KEYWORDS

Five flavors;

Pungent flavor;

TRPM8;

Pharmacophore;

Pharmacological

action

Abstract Objective: Explicating the property and action of traditional Chinese medicine (TCM) in the perspectives of modern science deepens the insight into the property of TCM, and provides the basis for new drug discovery and clinical therapy In this study, we investi-gated the relationship between transient receptor potential melastatin 8 (TRPM8) and pungent flavor using three-dimensional pharmacophores based on virtual screening methods

Methods: Firstly, an inhouse database was established to identify the related pharmacological action according to the traditional Chinese herbs expressing an action of promoting blood cir-culation Then, several therapeutic targets, 3-hydroxy-3-methylglutaryl-coenzyme A reduc-tase (HMG-CoAR), cholesteryl ester transfer protein (CETP), Niemann-Pick C1-Like 1 (NPC1L1) and platelet-activating factor receptor (PAFR), were selected to screen traditional Chinese herbs, and the common virtual screening hits with various hit scores providing data

to reveal the correlation among TRPM8 and therapeutic targets

Results: According to the screening results, TRPM8 agonists were able to identify the effective components of pungent herbs and TRPM8, which shares the common virtual screening hits with the therapeutic targets, was considered to be related to the action of pungent taste

* Corresponding author Fax: þ86 21 84738620.

** Corresponding author Fax: þ86 21 84738620.

E-mail addresses: collean_zhang@163.com (Y.-L Zhang), yjqiao@263.net (Y.-J Qiao).

Peer review under responsibility of Beijing University of Chinese Medicine.

c These authors are equally contributed to this article.

http://dx.doi.org/10.1016/j.jtcms.2016.12.005

2095-7548/ ª 2017 Beijing University of Chinese Medicine Production and hosting by Elsevier B.V This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Available online atwww.sciencedirect.com

ScienceDirect

journal homepage: http://www.e lsevie r com/l ocate /jtcms

Conclusion: The novel ideas and methods in this study are beneficial to unveil the scientific relationship between a TCM property and its action

ª 2017 Beijing University of Chinese Medicine Production and hosting by Elsevier B.V This is

an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/)

Introduction

Traditional Chinese herbs are defined by their

characteris-tics, or properties The property theory (yao xing li lun) is

based on the physiologic, pathologic, and clinical effects an

herb has on the human body and guides syndrome pattern

differentiation and prescription formulation As a whole,

the property theory is composed of several aspects that

describe the characteristics of an herb: four qi

(tempera-ture), five tastes, channel entered, directional tendency,

and toxicity When combined, these characteristics impact

one another, and yet form a unified ideology

Applying scientific methods to explicate the

character-istics of Chinese herbs deepens the understanding of the

property theory and provides a foundation for discovery

and clinical application of new drugs An herbal property of

recent scientific interest is the five tastes The five tastes

are: pungent (xin), sweet (gan), bitter (ku), sour (suan),

and salty (xian) Each taste has a unique effect, or action,

on the body In this study, we explored the pungent taste to

scientifically validate the TCM concept that herbs pungent

in flavor promote blood circulation (xin xing xue) and treat

the TCM syndrome pattern, blood stasis Disorders caused

by blood stasis include pain, numbness of the limbs, masses

or lumps, among other problems associated with blood

pathology Many of these herbs are used to treat biomedical

conditions such as angina, hyperlipidemia, dysmenorrhea

and so on

Transient receptor potential (TRP) channels are

belonging to a family of nonselective cation channels that

are expressed in a diverse and large number of tissues, and

have a wide variety of biologic roles.1,2Some TRP channels

are polymodal cell sensors, as they mediate an assortment

of sensations such as temperature, touch, and taste.3,4For

example, channels that are associated with temperature

are known as thermos TRPs.5 One TRP channel is TRP

melastatin 8 (TRPM8) It is activated when it is under cold

environment and by the specific small compound like

menthol.6,7For this reason, this TRP channel is also known

as the cold and menthol receptor 1 (CMR1) Menthol is a

compound found in mint (Mentha haplocalyx Briq.), a

common herb used in Chinese medicine that is considered

pungent in taste In this study, we investigated natural

agonists of TRPs as well as their Chinese herbal sources and

related properties to elucidate whether or not the TRPM8

ion channel may be the potential target by which an herb

exhibits its pungent property

Our investigation was accomplished through in silico

methods that included multi-database mining and

three-dimensional pharmacophore construction The

three-dimensional pharmacophore construction method and

multi-database mining methods have been used to study

the relationship between pungent flavor and the corre-sponding effects under the guidance of TCM property the-ory First, a database of “Flavor-Action-Pharmacology” have been established and the correlation value between pharmacology and action have been calculated to identify the related pharmacological action according to the tradi-tional Chinese herbs which have been designated as typical cases expressing the action of promoting blood circulation Then, in accordance with the identified action, TRPM8, 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoAR), cholesteryl ester transfer protein (CETP), Niemann-Pick C1-Like 1 (NPC1L1) and platelet-activating factor re-ceptor (PAFR) have been selected as typical targets to screen traditional Chinese herbs and the common virtual screening hits with various hit scores provide data to reveal the correlation among these targets Finally, according to the key sources of phytochemical hits, the preliminary re-sults show that the pharmacological effects related to TRPM8 family ion channel is similar to “pungent property promotes blood circulation” effects and TRPM8 ion target is considered as the potential target through which TCM show pungent property

Materials and methods

Database establishment

To identify the association of pharmacologic action with the pungent taste of herbs, we established a database, which

we named Taste-Action-Pharmacology We chose 16 herbs listed in the Chinese Pharmacopoeia 20108known for pro-moting blood circulation, or in TCM terminology, invigo-rating the blood, and are all pungent in taste (Table 1) Based on the Pharmacology of Chinese Materia Medica8, the pharmacologic actions of the herbs were then tagged with “1” (Table 2) If there was no corresponding action, no tag was designated

Correlation between pungent taste and pharmacologic action

To evaluate the correlation value between pungent taste and pharmacologic action of each of the 16 herbs, five parameters (T, X, C, Y, and M) were introduced and calculated as follows:

MZ

C

YC X

C ZC T

Y X

T represents the total number of traditional Chinese herbs; X represents the number of compounds in herbs that improve blood circulation; Y is the number of herbs

possessing specific pharmacologic actions; C is the number

of herbs sharing the specific pharmacologic action of

improving blood circulation When M is equal to 1, the

correlation between pungent taste and the specific

phar-macologic action is insignificant A higher value of M

in-dicates a more pronounced correlation (Fig 1)

Next, pharmacologic actions with highest scores were

searched in the Drug Bank database (www.drugbank.ca) to

define the drug targets associated with specific

pharmacologic activities In the current study, HMG-CoAR, CETP, NPC1L1, and PAFR were identified as targets for further study HMG-CoAR is the rate-limiting enzyme for hepatic cholesterol biosynthesis9 and its antagonists, the statins are commonly prescribed for preventing cardiovas-cular disease CETP inhibitors, attenuate cholesteryl ester hetero-exchange within the circulation.10The drug, ezeti-mibe, blocks the NPC1L1, reduces cholesterol absorption, and results in a blood cholesterol reduction of between 15% and 20%.11 PAFR is a G-protein coupled receptor binding with PAF, which is a potent phospholipid activator involved

in atherosclerosis.12,13 Generation of common feature pharmacophore model

Pharmacophore is a specific three-dimensional model con-taining common characters of compounds that binding the same site of the target protein.14 Pharmacophore genera-tion of TRPM8 was used as a model for determining the association between tastes and targets In this study, the HipHop algorithm15(common feature pharmacophore gen-eration) was used to build the pharmacophore of TRPM8 Pharmacophore model having highest CAI value of TRPM8 was selected to screen compounds the Traditional Chinese Medicine Database (TCMD; Version 2009)16for agonists for

Table 1 Pungent herbs that promote blood circulation

used to establish Taste-Action-Pharmacology database

name Chuanxiong

root

Ligusticum chuanxiong Hort

chuanxiong Corydalis

rhizome

Corydalis yanhusuo W.T.Wang

yan hu suo Dalbergia

heartwood

Dalbergia odorifera T.C.Chen

jiang xiang Lycopos Lycopus lucidus var hirtus

Regel

ze lan Leonurus Leonurus japonicus Houtt yi mu cao

Safflower Carthamus tinctorius L hong hua

Frankincense Boswellia sacra Flueck ru xiang

Red peony root Paeonia lactiflora Pall chi shao

Curcuma

rhizome

Curcuma zedoaria (Christm.) Roscoe

e zhu Sparganium Sparganium stoloniferum

(Buch.-Ham ex Graebn.) Buch.-Ham ex Juz

san leng

Mylabris Mylabris phalerata Pallas ban mao

Turmeric

rhizome

Curcuma longa L jiang huang Anomalous

artemisia

Artemisia anomala S.Moore liu ji nu Tangkuei Angelica sinensis (Oliv.)

Diels

dang gui Musk Moschus berezovskii Flerov she xiang

Table 2 Pharmacologic action of pungent Chinese herbs

Pharmacologic

action

Chuanxiong root

Corydalis rhizome

Turmeric rhizome

Safflower Curcuma

rhizome

Sparganium Red peony

root

Fig 1 Schema of parameters evaluating correlation between pungent taste and pharmacologic action

further exploration of the association between the pungent

taste and TRPM8

Compounds and biologic data

The studies were implemented on a series of TRPM8

ago-nists reported in the literature.17,18Given the distribution

of structural diversity, 11 compounds were selected to

generate the pharmacophore model and the structures of

agonists and their 50% effected concentrations (EC50) are

shown inFig 2 Considering the biological activity with the

chemical structure, CHEMBL258405, CHEMBL2087057,

CHEMBL2087059, CHEMBL2087052, CHEMBL2087055, and

CHEMBL2087056 were selected as training set Other

ago-nists were used as the test set to validate the model

Pharmacophore generation and validation

Pharmacophore generation was accomplished as described

below

Conformation analysis

The 3D qualitative pharmacophore hypotheses were

con-structed by HipHop in Discovery Studio 4.0 (Biovia, San

Diego, CA) Ligand conformations were created by the best

mode (best quality conformer generation) According to the

Feature Mapping’s initial analysis by the mapping feature,

which well-mapped all of the training set ligands, a

hydrogen bond acceptor (A), hydrogen bond donor (D),

hydrophobic (H), and aromatic ring (R) were selected

during pharmacophore generation These pharmacophore features characterize the interaction between the ligand and receptor

Pharmacophore generation and verification HipHop algorithm was used to generate pharmacophore model, which is a superposition of diverse conformations shared among the compounds Parameter of the procedure used the defined default value Compounds not used for pharmacophore model generation were used as an external test set for validating the pharmacophore hypotheses A test database of 11 experimentally known TRPM8 agonists embedded in a database consisting of 314 drug-like com-pounds (taken from the MDL Drug Database Report, Version 2007.2http://www.mdli.com) was constructed to evaluate all of the pharmacophore models Identified ligands were filtered by Lipinski’s Rule of Five19 and were similar in chemical structural characteristics Furthermore, four pa-rameters (A%, Y%, N, and CAI) were used to evaluate the performance of the models (Fig 3).20

Using the above methods, the pharmacophore models of HMG-CoAR, CETP, NPC1L1, and PAFR were generated The training set of each target is listed in the Supplementary data

Virtual screening Based on the enrichment factor (CAI value) of the phar-macophore models, the highest scoring models were used for virtual screening of TRPM8 agonists, and antagonists of

Fig 2 Chemical structures with EC50of TRPM8 agonists

HMG-CoAR, CETP, NPC1L1, and PAFR in Chinese herbs The

model with highest CAI value served as the query to

perform 3D flexible searching in Discovery Studio 4.0 to

search the TCMD, which contains 23,033 natural compounds

from 6735 medicinal plants Moreover, all potential hit

compounds in the database should satisfy the Lipinski’s

Rule of Five requirements

Results

Pharmacologic actions associated with the pungent

taste

Based on the formula for M value, 30 kinds of

pharmaco-logic actions were used to compute their association with

the pungent taste Ten of the best M values are shown in

Table 3

Pharmacophore model generation

Eleven compounds of TRPM8 were used as the training set

for a HipHop trial The top 10 pharmacophore models with

calculation results are detailed inTable 4 Two R features,

an H feature and an A feature were contained in 5

phar-macophore models; an R feature, two H features and an A

feature were contained in 4 pharmacophore models; an R

feature, two H features, and a D feature were contained in

1 pharmacophore model (Table 4) Both the direct hit and

partial hit values of these 10 models were “111111” and

“000000,” which confirmed that all 11 compounds in the training set were considered in the generation of the models The “4” value of max fit validates that all features

in the models matched the compounds in the training set The rank scores represented the degree of matching be-tween the pharmacophore feature and the compounds In general, the higher the rank, the more satisfactory the model match

Pharmacophore model validation Based on the diagram of indicators (Fig 4A) evaluating the pharmacophore models, the parameter value for each pharmacophore model is listed inTable 5 Model 2 had the highest CAI value and was thus selected to screen the TCMD

2009 database The pharmacophore feature of model 2 mapped with ligand CHEMBL258405 (Fig 4B)

Fig 3 Schema of indicators evaluating the pharmacophore models A% represents the ability to identify active compounds from the test database and Y% represents the proportion of active compounds in the hit compounds CAI, a comprehensive evaluation index, is used to identify the best pharmacophore model D is the total number of compounds in the test database and A is the number of active compounds The model with the highest value of CAI is considered to be the best

Table 3 Pharmacologic actions associated with the

pun-gent taste

Table 4 Pharmacophore model calculation results Model Features Rank Direct hit Partial hit Max fit

Fig 4 Pharmacophore model_2: (A) features and (B) the matching map with ligand

In summary, the pharmacophore model of HMG-CoAR,

CETP, NPC1L1, and PAFR was generated and results of each

target are listed in theSupplementary data

Virtual screening of compounds

To identify potential agonists of TRPM8, the

pharmaco-phore model generated by HipHop was used to search

compounds in TCMD 2009 Virtual screening yielded a hit

list of 265 compounds with our desired pharmacologic

ac-tivities Of the 265 compounds, 114 were from Chinese

herbs listed in the Chinese Pharmacopoeia 2010.8 Of the

114 compounds, 71 (62.3%) were associated with the

pun-gent taste (partial list inTable 6), indicating that the target

TRPM8 bears some relation to the pungent taste

Correlation analysis of pungent taste and pharmacologic action

Based on the virtual screening results, hits not only inter-acted with TRPM8, but also with the ligands of HMGCoAR, CETP, NPC1L1, and PAFR, whose pharmacologic actions were among the 10 best M values (Table 3) The results (Table 7) provided the data to interpret the TCM concept that the pungent taste is associated with the pharmacologic action of promoting blood circulation

Discussion

According to the simulation results, menthol, eriodictyol and other “hit” compounds are derived from medicinal herbs with pungent flavor and cold property, such as M haplocalyx Moreover, the number of “Hit” compounds whose Hit Score higher than 3.0 is 94 and 62.8% compounds are from pungent TCM sources It indicated that the phar-macophore model of TRPM8 can gather the same structural characteristics of pungent TCM The model is capable to identify the compounds extracted from pungent TCM

To evaluate the correlation value between “pungent taste” and pharmacological action, M parameter was calculated to determine its correlation A higher value of M indicates a more pronounced correlation between them As shown inTable 2, the pharmacological action of improving circulation, decreasing blood viscosity and expansion of blood vessels is closely related to its effect of “xin xing xue” The methods used in this study give us a profound inspiration for exploring the scientific connotation of five flavor theory, and it can be extended to solve similar problems in property study of Chinese medicines

In this paper, TRPM8 target was studied through phar-macophore model and virtual screening to explore its relationship with pungent property However, in addition to the TRPV1 ion channel, the TRPs family includes a variety

of other ion channels, such as TRPV, TRPA and so on One

Table 5 Parameter values for each pharmacophore

model

a A is the number of active compounds.

b D is the number of compounds in the test database.

c Ht is the number of hits using pharmacophore search.

d Ha is the number of active hits using pharmacophore search.

e A% represents the ability to identify active compounds in

the test database.

f N represents the ability to identify active compounds from

nonactive compounds.

g CAI is the comprehensive appraisal index.

Table 6 Partial virtual screening hits of TRPM8 agonists

10829 2.84 40-Hydroxy-wogonin Scutellaria barbata D.Don (bearded scutellaria) Pungent/Bitter

Abbreviation: TCM ID: ID number of Traditional Chinese Medicine Database.

TCMD ID Compound TRPM8 HMG

-CoAR

CETP NPC1L1 PAFR Pharmacologic

actions

10870 Scopolamine 3.49 2.18 3.23 3.57 4.12 Vasodilator Datura metel L (devil’s trumpet flower) Pungent

17036 Peucenidin 3.20 2.98 Unknown 3.30 1.06 Vasodilator Peucedanum praeruptorum Dunn (peucedanum root) Pungent/

Bitter

7719 Dimethoxy

ashanti

3.11 2.45 0.36 1.38 3.41 Blood viscosity

reducer

19507 Nepitrin E 3.08 1.82 2.98 3.11 3.78 Unknown Schizonepeta tenuifolia Briq (Japanese catnip) Pungent

13474 Manasatin A 2.93 2.32 3.41 3.14 4.12 Anti-inflammatory Saururus chinensis (Lour.) Baill (lizard’s tail) Pungent/

Sweet

19402 Saucerneol 2.93 2.91 3.53 3.02 4.12 Improve circulation Saururus chinensis (Lour.) Baill Pungent/

Sweet

17550 Plaunol C 2.88 3.04 1.96 y 3.16 Anti-inflammatory Croton tiglium L (croton seed) Pungent

4601 Dahuribirin E 2.78 1.12 2.82 2.82 2.59 y Angelica dahurica (Hoffm.) Benth & Hook.f ex Franch &

Sav (angelica root)

Pungent

4602 Dahuribirin F 2.73 1.74 2.53 2.33 3.35 y Angelica dahurica (Hoffm.) Benth & Hook.f ex Franch &

Sav (angelica root)

Pungent

19587 Scutellarin 2.68 y 2.51 y 1.77 Platelet inhibitor Scutellaria barbata D.Don (bearded scutellaria) Pungent/

Bitter

1186 Anethole 2.65 0.02 3.36 y 0.71 Anti-inflammatory Illicium verum Hook.f (star anise) Pungent

4384 Curculigosaponin G 2.62 3.08 2.39 y y Anti-inflammatory Curculigo orchioides Gaertn (curculigo) Pungent

14554 Methyl linoleate 2.59 2.54 3.27 3.28 3.79 y Ligusticum chuanxiong Hort (chuanxiong root) Pungent

O2demand

Curculigo orchioides Gaertn (curculigo) Pungent

4386 Curculigoside B 2.43 2.89 1.64 0.94 y Reduce myocardial

O2demand

Curculigo orchioides Gaertn (curculigo) Pungent

11438 Isogingerenone B 2.33 1.70 0.78 0.25 0.49 y Zingiber officinale Roscoe (dried ginger rhizome) Pungent

4600 Dahuribirin D 2.29 3.05 3.01 2.24 2.66 y Angelica dahurica Hoffm.) Benth & Hook.f ex Franch &

Sav (angelica root)

Pungent

18636 Resibufagin 2.27 2.79 2.76 2.20 2.78 y Bufo bufo gargarizans Cantor (toad venom) Pungent

16534 Mudanpioside A 2.20 y 2.75 1.88 2.58 Reduce myocardial

O2demand

Paeonia lactiflora Pall (red peony root) Pungent/

Bitter

7278 Eriodictyol 2.10 2.53 2.43 2.70 1.98 Antimicrobial Mentha haplocalyx Briq (mint) Pungent

12184 Kavain 2.03 3.61 1.20 1.26 2.59 Antibiosis

Antimicrobial

Abbreviations: CETP: cholesteryl ester transfer protein; HMG-CoAR: 3-hydroxy-3-methylglutaryl-coenzyme A reductase; NPC1L: 1Niemann-Pick C1-Like 1; PAFR: platelet-activating factor

receptor; TCMD: Traditional Chinese Medicine Database; TRPM8: transient receptor potential melastatin 8.

limitation to our study is that our pharmacophore model

and virtual screening only used TRPM8 to explore its

asso-ciation with the pungent taste of Chinese herbs Therefore,

only studying TRPM8 does not present a complete

under-standing of the association between the transient receptor

potential channels and the pungent flavor of Chinese herbs

Therefore, further study in this area is needed

Conclusions

In this paper, a pharmacophore model based on virtual

screening, data mining, combined with database

con-struction was used to study the relationship between

TRPM8 ion channel and pungent property The

pharmaco-logical action related to pungent flavor was identified

based on the database of “Flavor-Action-Pharmacology”

The correlation value between pharmacology and action

was calculated to confirm pharmacological action

corre-lated with pungent flavor Next, the pharmacology effect

with highest scores has been searched in Drug Bank

Data-base to define the targets associated with a specific

pharmacological function And in the current study,

HMG-CoAR, CETP, NPC1L1 and PAFR were defined as the typical

targets for further study Then, the pharmacophore

hy-pothesis was developed and used to screen the in-house

database for natural TRPM8 and therapeutic target

ago-nists The results showed that the TRPM8 agonist

phar-macophore model was able to specify/distinguish pungent

herbs and identify the effective components from pungent

herbs It also showed that the pharmacological effects

related to the TRPM8 family ion channel are similar to

“pungent property promotes blood circulation” effects

Thus, the TRPM8 ion target is considered as the potential

target through which TCM shows pungent property This

paper provides a method for exploring the scientific

rele-vance connotation of the five flavors theory of TCM With

further study of TRPs ion channel family, the relationship

and scientific interdependence connotation between TRPs

family and the pungent property of TCM will be revealed

and discovered ceaselessly

Conflicts of interest

The authors declare they have no conflicts of interest

regarding the publication of this paper

Author contributions

YJ Qiao and YL Zhang conceived and designed the

experi-ments YX Zhang and X Wang were involved in processing

data and preparing the manuscript SF Wang participated in

the discussion of views in the paper All authors have read

and approved the final manuscript

Acknowledgment

This study was financially supported by a grant from

Na-tional Science Foundation of China (Project No 81430094

and No 81603311) and Beijing Municipal Natural Science

Foundation (No 7164239)

Appendix A Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jtcms.2016.12.005

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