A Visualization Method of Chromatographic Data for Discovering Fingerprint Features of Natural Herbal Medicines

Transcription

1 ACTA CHIMICA SIICA Vol o Ξ ( ) 34 A Visualization Method of Chromatographic Data for Discovering Fingerprint Features of atural Herbal Medicines CHEG Yi2Yu 3 YU Jie WU Yong2Jiang ( Department of Chemical Engineering & Bioengineering Zhejiang University Hangzhou ) Abstract A novel visualization method of chromatographic data is proposed and applied to discover the chemical fingerprint features of herbal medicines As an example Chuan2Xiong was selected for research in this paper Using Kernel Principal Component Analysis and spatial projection transformation the chromatographic analysis data were processed and the hidden fingerprint features of the herbal medicine can be effectively discovered and extracted Then the transformed data were visualized with two2dimensional grayscale images which can visually reflect the discrepancy of chemical pattern between different quality classifications of the herbal medicine This method was used to identify 34 Chuan2Xiong samples from different areas and quality grades and the results showed that different patterns can be satisfactorily classified with visual sense It was proved that the method is a powerful tool for discovering and representing the hidden fingerprint features in complicated chemical substance system Keywords visualization in scientific computing chemical pattern recognition chromatographic analysis chemoinformatics fingerprint Ξ E - mail zju edu cn Received August ; revised October ; accepted ovember (973 o G ) (o )

2 o ; X [3 ] Y ( Visualization in scientific computing ViSC) ViSC 1 2 [1 ] PCA) [2 ] [4 ] ( Kernel principal component analysis KPCA) [5 6 ] ; PCA KPCA < X k k = 1 2 H <( X k ) k = 1 2 H < <( X k ) k = ( Principal component analysis <( i ) <( i ) T (1) 1 1 V = gcv (2) 0 1 [ <( X k ) V ] = <( X k ) gcv k = 1 2 (3) V V = i <( X i ) (4) X = [ 1 2 l ] T [7 ] <( X k ) = 0 gc = 1

3 330 Vol i =1 i <( X k ) <( X i ) 1 <( i X k ) j = 1 K [ 0 = 1] <( X j ) [ <( X j ) <( X i ) ] k = 1 2 (5) K = { K ij } = { [ <( X i ) <( X j ) ]} (6) [ Y ij ] (5) = K (7) Y ij = X ij - X j min (12) H (2) K gk ij = ( K - l K - Kl + l Kl ) ij (8) Y min l 1/ [ Z ij ] gk K Z ij = Y ij / Y max (13) X i X j [0 1 ] K K ij = K( X i X j ) i j = 1 2 (9) 1 4 K( X i X j ) = exp X i - X j (10) ( ) ( ) k ( k < ) 2 = k i M i (11) i ( 2 ) 3 KPCA (12) (13) 1 K 2 K (8) gk 3 (7) K gc V 4 i ( 2 k ( PCA ) 3 ( ) (1) [ X ij ] X j min [ Y ij ] 1 [0 1 ] 4 ( )

4 o Agilent 1100 Series Pentium 300 Agilent ; SHIMADZU VP2ODS 150 mm 4 6 mm ( 25 ) ; 0 5 ml/ min ; 20 L ; = 254 nm ; min 0 % ; % min 6 % ;45 min 60 % ;60 min 90 % ;70 min 100 % Matlab 5 3 Image Processing Toolbox Matlab ( ) ( ) 2 4 Matlab 1 1 (a) ; (b) ; (c) ; (d) ; (e) Figure 1 Visualization representation of raw analytical data of Chuan- Xiong from different areas (a) sample from Yunnan ; (b) sample from Sichuan ; (c) sample from Hubei ; (d) sample from Jiangxi ; (e) sample from Gansu KPCA 2

5 332 Vol (a) ; (b) ; (c) ; (d) ; (e) Figure 2 Virtual fingerprint of Chuan - Xiong from different areas (a) sample from Yunnan ; (b) sample from Sichuan ; (c) sample from Hubei ; (d) sample from Jiangxi ; (e) sample from Gansu ( ) ( ) 3

6 o (a) ; (b) ; (c) Figure 3 Virtual fingerprint of Chuan2Xiong from different grades (a) sample grade 1 ; (b) sample grade 5 ; (c) sample grade poor References 1 Rossignac J R ; ovak M IEEE Trans CG & A (2) 83 2 Wang Z2M; Xiao S2Y Chin J Chin Materia Medica (4) 244 (in Chinese) ( (4) 244 ) 3 Shi J 2Y; Cai W2L In Algorithms and System of Visualization in Scientific Computing Science Press Beijing 1996 (in Chinese) ( 1996 ) 4 Karhunen J ; Joutsensalo J eural etworks (4) Scholkopf B ; Smola A ; Muller K R eural Computation (5) Scholkopf B ; Burge J C ; Smola A Advances in Kernel Methods Support Vector Learning MIT Press Cambridge MA Vapnik V Statistical Learning Theory John Wiley & Sons Inc ew York 1998 (A SHE H )

7 Graphical Abstract Vol 60 o 2 Study on Recognition Mechanism of Molecu2 larly Imprinted Microsphere Synthesized from Aqueous Solution LAI Jia2Ping ; CAO Xian2Feng ; HE Xi2Wen ; LI Yuan2Yuan Acta Chimica Sinica (2) 322 The molecularly imprinted polymer microspheres against 42aminopyridine (42AP) and trimethoprim ( TMP) were synthesized Chromatographic analyses showed that the interaction between acidic monomer/ polymer and template with amino group mainly depended on the ionic (electrostatic) interaction but not the simply added interaction A Visualization Method of Chromatographic Data for Discovering Fingerprint Features of atural Herbal Medicines CHEG Yi2Yu ; YU Jie ; WU Yong2Jiang Acta Chimica Sinica (2) 328 A novel visualization method of chromatographic data for discovering the fingerprint features of natural herbal medicines is proposed The method can be used to effectively extract the hidden fingerprint features from analytical data set and visually represent the chemical pattern discrepancy between different classes of herbal medicine Studies on the Secondary Metabolite of the Soft Coral Lobophytum sp HE Xi2Xin ; SU Jing2Yu ; ZEG Long2Mei ; YAG Xiao2Ping ; LIAG Yong2Ju Acta Chimica Sinica (2) 334 Five steroidal glycosides (1) (5) were isolated from the soft coral Lobophyton sp collected from Sanya Bay Hainan Island 1 is a new compound These steroidal glycosides exhibited cytotoxic activity toward human tumor cell lines SKMG24Hep2G2 and CE2 The Reaction of 2Trialkylgermanium2()2 substituted Propionic Acid with 12Ethoxystan2 natrane aoet (CH 2 CH 2 OH) 3 SnCl 4 Sn(OEt) 4 EtOSn(OCH2 CH 2 ) 3 Ar 3 GeCHR 1 CHR 2 COOH Ar3 GeCHR 1 CHR 2 COOSn(OCH 2 CH 2 ) 3 SOG Xue2Qing ; LUO ing ; SU Li2Juan ; XIE Qing2Lan Acta Chimica Sinica (2) 338 The reaction of 2trialkylgermanium2( ) 2substituted propionic acid with 12 ethoxystannatrane was studied and fifteen organometallic compounds containing germanium and tin were synthesized were characterized The structures of prepared compounds