Qantitative structure - pharmacokinetic relationship of antimicrobial agents drug plasma protein binding

Similar documents
European Committee forantimicrobial SusceptibilityTesting (EUCAST) of the European Society of Clinical Microbiologyand Infectious Diseases (ESCMID)

Removal of Wastewater Pharmaceutical Chemical Contaminants Using AOPs

EUCAST DISCUSSION DOCUMENT E.Dis 5.1 MARCH Determination of minimum inhibitory concentrations (MICs) of antibacterial agents by broth dilution

Bilag 3 Appendix B: Function tests

Quantitative Structure-Activity Relationship (QSAR) computational-drug-design.html

EUCAST Expert Rules Version 3.1. Intrinsic Resistance and Exceptional Phenotypes Tables

Antibiotic Resistance in Enterobacteriaceae

Comparison of log P/D with bio-mimetic properties

New developments in PK/PD

Implementation of Public Health Surveillance of Carbapenemase- Producing Enterobacteriaceae in Victoria, Australia

by author ESCMID Online Lecture Library Epidemiological cutoff values (ECOFFs) and Low Level resistance Gunnar Kahlmeter

Annals of West University of Timisoara

On drug transport after intravenous administration

Butropium Bromide 1. Butropium Bromide 2. Calcium Folinate Ultraviolet-visible Reference Spectra. A solution in methanol (1 in 100,000)

ESCMID Online Lecture Library

COMPUTER AIDED DRUG DESIGN (CADD) AND DEVELOPMENT METHODS

Differentiating Warm vs. Drug-induced AIHA

Structure-Activity Relationship of Fluoroquinolones Against K.pneumoniae

QSAR/QSPR modeling. Quantitative Structure-Activity Relationships Quantitative Structure-Property-Relationships

LUMO + 1 LUMO. Tómas Arnar Guðmundsson Report 2 Reikniefnafræði G

Flatbands in 2D boroxine-linked covalent organic frameworks

Symmetry and Molecular Orbitals (I)

ACCEPTED. *Corresponding author. Mailing address: Faculdade de Medicina Veterinária, Av. da

EPA Method 1694: Analysis of Pharmaceuticals and Personal Care Products in Water

In silico pharmacology for drug discovery

Organic Electronic Devices

Accepted 2 September, 2009

Pre-processing feature selection for improved C&RT models for oral absorption

EARS-Net (European Antimicrobial Resistance Surveillance Network) Isolates from 2014, Belgium

Organic Chemistry FINAL EXAM A (250 points)

Study on the interaction behavior of catalase with. cephalosporins by chemiluminescence with flow injection

In silico prediction and experimental evaluation of furanoheliangolide sesquiterpene. lactones as potent agents against Trypanosoma brucei rhodesiense

2m dx 2. The particle in a one dimensional box (of size L) energy levels are

Introduction to Chemoinformatics

Article. Introduction

5.Experimental Results Table 5.1 Calibration curve for the estimation of Ciprofloxacin. Sl.No. Conc.(μg/ml) Absorbance(nm)

Involvement of efflux pumps in the resistance to peptidoglycan synthesis

MOLECULAR STRUCTURE. Molecular Structure - B. Molecular Structure - B. Molecular Structure - B. Molecular Structure - B. Molecular Structure - B

Radial Basis Function Neural Networks in Protein Sequence Classification ABSTRACT

Topology based deep learning for biomolecular data

PHYSICOCHEMICAL PROPERTIES OF DRUG ACTION

Comparative evaluation of the VITEK 2 Advanced Expert System (AES) in five UK hospitals

The general concept of pharmacokinetics

Pseudomonas putida 5

CHEM 4170 Problem Set #1

NH 3 H 2 O N 2. Why do they make chemical bonds? Molecular Orbitals

Introduction to Chemoinformatics and Drug Discovery

Eric Hajjar, Amit Kumar, Enrico Spiga, Francesca Collu, Atilio Vargiu, Paolo Ruggerone and Matteo Ceccarelli

Reikniefnafræði - Verkefni 2 Haustmisseri 2013 Kennari - Hannes Jónsson

Multidrug resistant Stenotrophomonas maltophilia: an emerging cause of hospital acquired infections in Assiut University Hospitals, Egypt

Prediction of gas emission quantity using artificial neural networks

LIST OF JOURNAL HOLDINGS OF NIPER LIBRARY (AS ON NOV 2001)

Lecture 3: Electron statistics in a solid

TRAINING REAXYS MEDICINAL CHEMISTRY

MASS TRANSFER AND ADSORPTION OF AMOXICILLIN FROM WASTEWATER USING WHEAT GRAIN

Key Words Q Exactive Focus, Orbitrap, veterinary drugs, small molecule HRAM quantitation, small molecule HRAM screening, UHPLC, vdia

Synthesis and Vibration mode study of Schiff base compounds of 4-Dimethyl-aminoantipyrine

In this lecture we will understand how the molecular orbitals are formed from the interaction of atomic orbitals.

JCICS Major Research Areas

College of Science, Xi an University of Science and Technology, Xi an *Corresponding author

Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs

Validation of EUCAST zone diameter breakpoints against reference broth microdilution

Statistical concepts in QSAR.

Reaxys Medicinal Chemistry Fact Sheet

Electroluminescence from Silicon and Germanium Nanostructures

Electronic Excitation by UV/Vis Spectroscopy :

JOURNAL. November 1999 Volume 88, Number 11. Allometric Issues in Drug Development* MINIREVIEW. Iftekhar Mahmood. Introduction. A publication of the

QSARs for trace organics removal by activated carbon and membrane filtration

Reading guide. EUCAST disk diffusion method for antimicrobial susceptibility testing

Structural and Electronic Properties of Small Silicon Nanoclusters

A very brief history of the study of light

Journal of Chemical and Pharmaceutical Research

Acid-Base Properties

Journal of Chemical and Pharmaceutical Research, 2012, 4(1): Research Article

Basic cell design. Si cell

Using Bayesian Statistics to Predict Water Affinity and Behavior in Protein Binding Sites. J. Andrew Surface

On approximate solutions in pharmacokinetics

Periodic Trends in Properties of Homonuclear

Polyamine Effects on Antibiotic Susceptibility in Bacteria

Reading Group on Deep Learning Session 4 Unsupervised Neural Networks

Supplementary Information. Broad Spectrum Anti-Influenza Agents by Inhibiting Self- Association of Matrix Protein 1

Class 24: Density of States

b-lactam resistance and b-lactamase expression in clinical Stenotrophomonas maltophilia isolates having defined phylogenetic relationships

Australian Journal of Basic and Applied Sciences

I. List and composition of ISP media used in the present study for characterization of Streptomyces

Haemophilus influenzae: Antibiotic Susceptibility

Theoretical Approach on structural aspects of antiepileptic agent indoline-2,3- dione-3-oxime by arguslab 4 software

PHARMA SCIENCE MONITOR

Chapter 2. Methodology

Comparative Analysis of Machine Learning Techniques for the Prediction of the DMPK Parameters Intrinsic Clearance and Plasma Protein Binding

Early Stages of Drug Discovery in the Pharmaceutical Industry

CHEM 2010 Symmetry, Electronic Structure and Bonding Winter Numbering of Chapters and Assigned Problems

First description of a RND-type multidrug efflux pump in Achromobacter xylosoxidans:

Visualization in Chemistry. Giovanni Morelli

Fitting PK Models with SAS NLMIXED Procedure Halimu Haridona, PPD Inc., Beijing

Comparing Multi-Label Classification Methods for Provisional Biopharmaceutics Class Prediction

Factors involved in the enhanced efficacy against Gram-negative bacteria of fourth generation cephalosporins

Identification of Penicillinase-Resistant Penicillins in Human Urine by RPLC Method

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Research Article Serotypes and Antimicrobial Resistance of Human Nontyphoidal Isolates of Salmonella enterica from Crete, Greece

Transcription:

W C J P S 2003,18(1) :1 5 3 3 610065 : 61 - (QSPR) ; 51 leave - one - out 10, QSPR : ; ; ; :R969. 1,R911 :A :1006-0103(2003) 01-0001 - 05 Qantitative structure - pharmacokinetic relationship of antimicrobial agents drug plasma protein binding ZHOU Lu,SU Yi,ZUO Zhi - li,zhao Cai - bin,xia Kun - hua Department of Pharmaceutical Engineering, College of Chemical Engineering, Sichuan University, Chengdu 610065, China Abstract :OBJECTIVE To study and demonstrate the application of neural network to research the quantitative structure - pharmacokinetic relationship (QSPR)of 61 kinds of antimicrobial agents. METHODS Firstly,three - layer back propagation system network was established in2 cluding an input layer, a hidden layer and an output layer. The input layer of the neural network is the quantum chemistry parameter, physical - chemistry parameter and molecular connectivity index of drug. The output of the neural network is the pharmacokinetic property - drug plas2 ma protein binding(dppb) of antimicrobial agents which is derived from the experimental data. Secondly, the prediction ability of the network is tested by the leave - one - out method. RESULTS The test involved the prediction of the pharmacokinetic properties(dppb) of ten com2 pound which have never been seen by the network. The predicted by neural network values shew good agreement with the experimental values. CONCL USION This result indicates that the neural network described in this study is proper and effective for QSPR research. Key words :Pharmacokinetics ;Drug molecular structure ;Drug plasma protein binding ;Neural network ;Antimicrobial agent CLC number :R969. 1,R911 Document code :A Article ID :1006-0103(2003) 01-0001 - 05 [1 ] 40 %, ( quantitative structure pharmacokinetic relationslip, : (01GY051-55) : (1954 - ),,E - mail :zhoulu - 007 @163. com

2 18 QSPR) (QSAR),QSPR [2 7 ] energy [8 ], 15 165. 06 0. 30 115. 57 43. 80 470. 33-214. 00 16 171. 62-0. 36 113. 34 42. 49 414. 48-190. 97 :, 1 - ( - ) / / 60 108. 04-1. 09 87. 74 31. 81 319. 34-160. 19 61 1,, (tetracycline),qspr 461 Hyperchem7. 0 541 1 3 1 Table 1 Physical - chemistry parameter values of antimicrobial agent No. Hydration Logp Refractivity Polarizability Mass Total energy 1 168. 70 6. 66 82. 55 35. 18 349. 40-161. 66 2 164. 49 11. 91 89. 76 39. 94 401. 44-187. 38 3 162. 95 1. 01 94. 96 36. 06 415. 46-196. 74 4 163. 86 12. 43 94. 56 41. 87 435. 88-200. 60 5 163. 37-0. 15 89. 12 35. 82 365. 40-173. 64 6 172. 23 10. 72 78. 34 33. 83 334. 39-153. 53 7 226. 83 13. 32 81. 64 36. 39 378. 40-181. 74 8 172. 88-0. 62 90. 48 34. 47 350. 39-165. 49 9 117. 63 0. 85 103. 94 39. 92 389. 47-177. 94 10 178. 39-0. 27 84. 12 33. 93 341. 43-159. 24 11 351. 25-1. 11 130. 34 50. 22 517. 56-248. 55 12 224. 08 8. 27 84. 80 35. 91 384. 42-178. 44 13 288. 35-1. 12 129. 29 47. 60 539. 58-257. 77 14 291. 74-1. 03 115. 76 44. 62 461. 49-221. 39 17 171. 41-1. 77 96. 77 36. 94 380. 42-182. 95 18 126. 05 1. 09 84. 63 33. 42 325. 43-147. 42 19 234. 96 0. 44 117. 80 45. 72 465. 52-224. 73 20 156. 20 6. 65 116. 53 47. 06 489. 48-250. 51 21 152. 36 7. 75 104. 26 43. 04 442. 43-223. 88 22 155100 7. 76 110. 34 45. 16 478. 89-238. 16 23 157. 55 7. 59 105. 24 43. 23 444. 44-224. 94 24 154. 61 5. 80 107. 58 43. 23 444. 44-224. 66 25 154. 10 7. 76 110. 34 45. 16 478. 89-238. 17 26 229. 31-2. 79 98. 34 37. 56 369. 44-183. 31 27 165. 64-1. 31 93. 12 34. 99 347. 39-160. 80 28 217. 25-2. 18 99. 68 38. 12 424. 38-214. 73 29 172. 81-1. 05 92100 35. 18 349. 40-161. 82 30 155. 79 0. 45 122. 29 44. 52 462. 50-212. 27 31 225. 51-3. 30 105. 83 40. 33 423. 46-196. 15 32 158. 10-2. 33 94. 72 35. 63 363. 93-172. 57 33 165. 09-2. 25 110. 93 42. 47 415. 48-181. 75 34 217. 21-2. 03 107. 55 41. 60 455. 46-218. 32 35 149. 10 0. 26 112. 50 41. 99 454. 50-201. 77 36 166. 26-1. 68 93. 55 35. 09 367. 81-168. 29 37 209. 87-0. 77 134. 75 49. 63 519. 55-242. 59 38 220. 65-2. 26 103. 31 39. 54 427. 45-203. 18 39 279. 84-2. 17 118. 27 46. 18 510. 48-260. 12 40 263. 43 0. 45 135. 12 51. 23 575. 60-264. 17 41 203. 42 0. 01 128. 97 47. 19 520. 47-262. 64 42 331. 42-1. 40 164. 32 60. 90 645. 66-307. 78 43 156. 72-1. 31 92. 34 35. 38 383. 40-201. 77 44 206. 16-0. 79 131. 44 50. 72 554. 57-258. 01 45 215. 66-1. 29 138. 60 52. 84 547. 58-257. 08 46 105. 83-2. 81 76. 21 29. 14 299. 34-141. 97 47 155. 46-0. 53 95. 13 35. 12 435. 40-216. 02 48 8. 89-3. 06 118. 07 48. 20 477. 60-241. 09 49-4. 50-5. 63 106. 13 43. 89 484. 50-262. 95 50-7. 38-4. 69 128. 57 52. 70 581. 58-312. 94 51-3. 46-5. 56 106. 69 43. 97 467. 52-247. 51 52 49. 28-6. 91 129. 84 53. 31 585. 61-316. 50 53 13. 91-2. 19 121. 76 49. 40 475. 63-235. 03 54 150. 60 2. 72 186. 03 74. 88 733. 94-368. 73 55 69. 25 0. 06 102. 72 41. 23 406. 54-194. 89 56 72. 02 1. 21 105. 77 42. 52 424. 98-196. 34 57 155. 56 7. 16 100. 89 41. 40 430. 41-219. 23 58 151. 81 6. 67 110. 62 45. 30 458. 47-229. 39 59 107. 18 1. 39 63. 59 23. 76 232. 24-112. 92 61 109. 95-1. 85 90. 21 32. 88 331. 35-164. 84 11 (ampicillin) ;21 (oxacilin) ;31 (sulbencillin) ; 41 (cloxacillin) ; 51 ( amoxicillin) ; 61 G (penicillin G) ;71 (carbenicillin) 81 V (penicillin V) ; 91 (hetacillin) ;101 (cyclacillin) ;111 (piperacillin) ;121 (ticarcillin) ;131 (mezlocillin) ; 141 (axlocillin) ;151 (diclxacillin) ;161 (nafcillin) ;171 (methicillin) ;181 (mecillinam) ;191 (bacampicillin) ;201 (minocydine) ;211 (methacycline) ;221 (chlortetracycline) ;231 (doxycy2 cline) ;241 ;251 (oxytetracycline) ;261 (cephacothin) ;271 (cephacexin) ;281 (ce2 furoxine) ;291 (cephracline) ;301 (cafamandole) ;311 (cephapivin) ;321 (cefadroxic) ; 331 (cephaloridine) ;341 (cepfotaxine) ;351 (cefazolin) ; 361 (cefaclor) ;371 (ceforanide) ;381 (ce2 faxintin) ;391 (cefuroximeaxetil) ;401 (cefotetan) ; 411 (catamoxef) ;421 (cefoperazone) ;431 (ceftizoxime) ;441 (ceftriaxone) ;451 (ceftazidime) ; (imipenem) ;471 (aztreonam) ;481 (gen2 tamicin) ;491 (kanamycin) ;501 (steptomycin) ;511 (tobramycin) ;521 (amikacin) ;531 (netilmich) ; (erythromycin) ; 551 (lincomycin) ; 561 (clindymycin) ;571 ( demeclocycline) ; 581 ( minocy2 cline) ;591 (nalidixic acid) ;601 (norfloxacin) ;611 (ciprofloxacin)

1 3 2 Table 2 Quantum chemistry parameter values of antimicrobial agent No. Binding Iso - atomic Electronic c - c energy energy energy interaction HOF HOMO LUMO 1-4294. 44-97154. 52-759741. 60 658292. 64 73. 36-0. 0519 0. 2087 2-4788. 02-112802. 51-908418. 05 790827. 51 152. 01-0. 4337 0. 0041 3-4685. 07-118777. 06-949856. 00 826393. 86-185. 18-0. 0903 0. 0450 4-4762. 66-121122. 96-975522. 59 849636. 96 154. 26-0. 5728 0. 1696 5-4524. 01-104444. 09-808617. 89 699649. 78-96. 64 0. 1945 0. 0357 6-4125. 30-92223. 98-693472. 89 597123. 60 77. 40-0. 0438 0. 1199 7-4458. 29-109589. 28-839243. 68 725196. 10 34. 42-0. 0009 0. 1414 8-4340. 18-99513. 56-761092. 45 657238. 70-77. 91-0. 0468 0. 2129 9-5101. 62-106564. 14-898321. 82 786656. 05-12. 73-9. 2339 0. 0657 10-4509. 46-95419. 59-749682. 73 649753. 67-104. 13-8. 9708 0. 1540 11-6011. 84-149964. 11-1345864. 32 1189888. 37 373. 69-0. 0551 0. 0379 12-4064. 37-107912. 93-818214. 25 706236. 94 48. 76-0. 0118 0. 1234 13-6179. 08-155577. 34-1425172. 67 1263416. 25-113. 57-0. 0443 0. 0401 14-5665. 53-133264. 90-1199636. 23 1060705. 80-60. 63-0. 1060 0. 1048 15-4849. 02-129443. 42-1038246. 83 903954. 39 44. 79-0. 0214 0. 0633 16-5345. 38-114495. 46-1005815. 23 885974. 37-20. 26-0. 0663 0. 0902 17-4690. 78-110114. 89-860255. 65 745449. 97-93. 86-0. 4559 0. 0732 18-4383. 28-88130. 01-668792. 88 576279. 59-37. 50-8. 7718 0. 2904 19-5971. 94-135056. 37-1197983. 24 1056954. 92-154. 18-0. 1295 0. 0536 20-6415. 33-150786. 28-1445539. 30 1288337. 67-203. 08-0. 0143 0. 3019 21-5763. 16-134728. 81-1206417. 46 1065925. 48-154. 86-0. 1242 0. 2449 22-5879. 10-143574. 88-1300007. 40 1150553. 41-189. 72-0. 0832 1. 0551 23-5901. 27-135254. 42-1232468. 73 1091313. 03-188. 77-0. 1581 0. 0031 24-5727. 82-135254. 42-1205365. 31 1064383. 06-15. 32-0. 1569 0. 0742 25-5882. 61-143574. 88-1294861. 33 1145403. 83-193. 22-0. 0564 1. 1398 26-4335. 27-110699. 07-868686. 77 753652. 42-51. 25-0. 1683 0. 2053 27-4278. 81-96628. 91-701945. 37 601037. 65-15. 20-0. 5644 0. 2132 28-4557. 05-130192. 16-1040000. 65 905251. 44 5. 69-0. 0885 0. 2324 29-4396. 16-97154. 51-787445. 54 685894. 86-28. 35-0. 4852 0. 2567 30-5028. 21-128178. 29-1082981. 98 949775. 47 94. 24-0. 1956 0. 0237 31-4677. 12-118415. 74-883471. 77 760378. 90-57. 10-0. 0783 0. 0146 32-4373. 77-103918. 49-759839. 24 651546. 98-50. 60-0. 5456 0. 2461 33-4646. 50-109408. 85-895875. 59 781820. 23 196. 17-0. 3635 0. 0310 34-4750. 19-132254. 65-1011568. 40 874563. 56-15. 50-0. 0050 0. 1386 35-4168. 56-122449. 94-938045. 04 811426. 53 294. 75-0. 1009 0. 0606 36-3970. 58-101637. 62-736408. 38 630800. 18-5. 17-0. 0323 0. 1925 37-5740. 14-146496. 29-1334903. 31 1182666. 88 52. 95-0. 4108 0. 1136 38-4585. 96-122919. 18-975436. 99 847931. 83-77. 27-1. 0600 0. 0480 39-5741. 71-157492. 70-1367964. 61 1204730. 19-63. 68-0. 0408 0. 3336 40-5266. 26-160508. 89-1413870. 37 1248095. 22 57. 67-0. 0031 0. 1247 41-5804. 37-159012. 97-1463954. 19 1299136. 85-64. 09-0. 0341 0. 1070 42-7222. 48-185918. 42-1956194. 82 1763053. 91 82. 79-0. 0273 0. 0521 43-4168. 56-122449. 94-938045. 04 811426. 53 294. 75-0. 1009 0. 0606 44-5396. 08-156514. 45-1332748. 79 1170838. 26 137. 88-0. 1944 0. 0371 45-6110. 46-155216. 02-1407509. 20 1246182. 70 75. 17-0. 0948 0. 2414 46-3605. 56-85484. 36-562463. 09 473373. 17-25. 51-0. 4204 1. 0084 47-4374. 94-131185. 81-1027516. 08 891955. 32-93. 36-0. 0682 0. 1238 48-7119. 95-144175. 15-1499378. 60 1348083. 48-308. 96-9. 4716 1. 6968 49-6539. 31-158467. 72-1510983. 79 1345976. 75-480. 47-9. 6254 1. 9506 50-7470. 70-188907. 31-1993176. 05 1796798. 03-344. 32-1. 4393 1. 5283 51-6500. 89-148819. 09-1418710. 54 1263390. 55-396. 07-9. 5735 1. 9020 52-7916. 87-190698. 78-1964595. 78 1765980. 12-577. 63-9. 5741 1. 7351 53-7292. 58-140197. 32-1468120. 65 1320630. 75-266. 05-9. 1480 2. 0838 54-11264. 70-220127. 20-3026471. 67 2795079. 73-563. 69-9. 1196 1. 3228 55-5720. 58-116580. 27-1053040. 71 930739. 85-223. 34-8. 9294 0. 0561 56-5600. 48-117611. 14-1043794. 30 920582. 67-185. 91-8. 8588 0. 1288 57-5632. 95-131942. 68-1162197. 54 1024621. 91-195. 54-0. 0781 0. 2075 58-6121. 42-137825. 91-1270602. 17 1126654. 84-138. 27-0. 0463 0. 0745 59-3068. 53-67791. 50-426874. 30 356014. 26 12. 04-0. 5191 0. 4442 60-4223. 99-96302. 71-702204. 39 601677. 69-15. 34-0. 5269 0. 1501 61-4357. 56-99088. 85-740825. 76 637379. 34 21. 96-0. 5028 0. 2755 No. 1 61 are the same as table 1 ;C - C interaction = core - core interation,hof = heat of formation,homd = hightest occupied molecular orbit,lumo = lowest unoccupied molecular orbit

4 18 3 4 Table 3 Molecular connectivity index values of antimicrobial agent Table 4 Train result analysis of neural network No1 X 0 X 1 X 2 X 3 X 4 X 5 1 14. 1143 8. 4515 8. 2370 5. 9795 4. 9016 6. 7309 2 16. 3151 9. 6512 9. 1419 6. 6642 5. 4928 7. 3979 3 15. 4127 9. 2449 9. 0290 6. 4466 5. 3717 7. 2126 4 17. 2927 10. 044 9. 5881 7. 0118 5. 6831 7. 5820 5 14. 4068 8. 5025 8. 3285 5. 9762 4. 8532 6. 6762 6 13. 6667 8. 2480 8. 0699 5. 7645 4. 8525 6. 6882 7 14. 8924 8. 8346 8. 5306 6. 1803 5. 1350 6. 9486 8 14. 0750 8. 3872 8. 0093 5. 6702 4. 7275 6. 5335 9 16. 4842 9. 8236 10. 0625 7. 1934 6. 2334 8. 6339 10 14. 1858 8. 8759 9. 0303 6. 7251 5. 5415 7. 7707 11 20. 7247 12. 2890 10. 9151 8. 0630 6. 3378 8. 4215 12 14. 9205 9. 2258 8. 9345 6. 6116 5. 6007 7. 8188 13 20. 5378 12. 1960 11. 3187 8. 0280 6. 3794 8. 4940 14 18. 2149 10. 9320 10. 0254 7. 3031 5. 8959 7. 9419 15 18. 4249 10. 6160 10. 1852 7. 4451 6. 1695 8. 0144 16 17. 1523 10. 3370 9. 4709 7. 1747 6. 1357 8. 3570 17 15. 6214 8. 8489 8. 3510 6. 1820 5. 1352 6. 9460 18 13. 7627 8. 6833 8. 3934 6. 0817 5. 0562 6. 9885 19 19. 1235 11. 1300 9. 7663 6. 8175 5. 4689 7. 4211 20 18. 8636 10. 7150 9. 7439 7. 6222 6. 3146 8. 2217 21 16. 9164 9. 6002 8. 3395 6. 5649 5. 1605 6. 5978 22 18. 7115 10. 4890 9. 7349 8. 2600 7. 1558 9. 2369 23 17. 6041 10. 0150 8. 7920 6. 9958 5. 5823 7. 1616 24 17. 6565 9. 9702 8. 9618 7. 0222 5. 5087 7. 1015 25 17. 9740 10. 0750 9. 0546 7. 0340 5. 5889 7. 1064 26 15. 3871 9. 6539 7. 8779 6. 1385 4. 8842 6. 9529 27 13. 7441 8. 4462 6. 8193 5. 5192 4. 2001 5. 8090 28 15. 7990 9. 1735 6. 9265 5. 4119 4. 2695 5. 9020 29 14. 0036 8. 7358 7. 0989 5. 7963 4. 4291 6. 1439 30 17. 8316 11. 1930 8. 8801 7. 2953 5. 7161 8. 0402 31 16. 4116 10. 2640 8. 1098 6. 3785 4. 8786 6. 9607 32 14. 1139 8. 5805 7. 0002 5. 6127 4. 2214 5. 8515 33 16. 4573 10. 5440 8. 3518 6. 6226 5. 2127 7. 2947 34 17. 4053 10. 3300 8. 0791 6. 1542 4. 8350 6. 8104 35 17. 2435 10. 8450 9. 4256 7. 3153 6. 3483 9. 0475 36 13. 8764 8. 5123 6. 8992 5. 6076 4. 2632 5. 9084 37 19. 8366 12. 3140 10. 2049 8. 5501 7. 2739 10. 0020 38 16. 7180 10. 1440 8. 2131 6. 5658 5. 2474 7. 3165 39 19. 6932 11. 2390 8. 1590 6. 3949 5. 0201 6. 8623 40 21. 6130 13. 5290 12. 0760 10. 5020 9. 2886 13. 4790 41 20. 4406 12. 2760 9. 7648 8. 0970 6. 3616 8. 7132 42 24. 9947 15. 2770 11. 7708 9. 6120 7. 2925 9. 9093 43 14. 3817 8. 8206 6. 9223 5. 2084 4. 1051 5. 6843 44 21. 0076 12. 8270 10. 1733 8. 0925 6. 4210 9. 1009 45 21. 2393 12. 7000 10. 4863 7. 4720 5. 4532 7. 6150 46 11. 9013 7. 3581 5. 5647 4. 3476 3. 5859 4. 9817 47 15. 5723 9. 1670 8. 3579 4. 5853 2. 8215 3. 4193 48 19. 9633 11. 6360 10. 0263 7. 0258 5. 1081 6. 1945 49 17. 7243 10. 5830 8. 5252 6. 2406 4. 2207 5. 1894 50 21. 9867 12. 7130 10. 2120 7. 6704 5. 3361 6. 6396 51 17. 7972 10. 7920 9. 1157 6. 8221 4. 5209 5. 5833 52 21. 8312 13. 2720 10. 5921 7. 8033 5. 3366 6. 7737 53 19. 4629 11. 4290 9. 0813 6. 4161 4. 5730 5. 5329 54 32. 5147 18. 4190 16. 4506 11. 8220 8. 4283 9. 6798 55 17. 2988 10. 9010 8. 7298 6. 5072 4. 8090 6. 3125 56 17. 9839 11. 2970 9. 3537 6. 7532 4. 9960 6. 5836 57 17. 0513 9. 6965 8. 4482 6. 6253 5. 2482 6. 7159 58 18. 7863 10. 5040 9. 3148 7. 0630 5. 6532 7. 2604 59 9. 5972 5. 2835 3. 7868 2. 6316 1. 7532 2. 1729 60 12. 8036 7. 5825 5. 5208 4. 1775 2. 9614 3. 7496 61 13. 0881 8. 1338 6. 3733 5. 0153 3. 7684 5. 0089 No. 1 61 are the same as table 1 No. EV NLV RD AV RD 1 0. 23 0. 2307-0. 0007 0. 2468-0. 0168 2 0. 94 0. 9341 0. 0059 0. 9032 0. 0368 3 0. 82 0. 8199 1E - 04 0. 8350-0. 0150 4 0. 95 0. 9613-0. 0113 0. 9949-0. 0449 5 0. 23 0. 2308-0. 0008 0. 2204 0. 0096 6 0. 65 0. 6499 1E - 04 0. 6242 0. 0258 7 0. 50 0. 5004-0. 0004 0. 4901 0. 0099 8 0. 80 0. 7989 0. 0011 0. 7394 0. 0606 9 0. 23 0. 2300 010000 0. 2629-0. 0329 10 0. 22 0. 2201-1E - 04 0. 2185 0. 0015 11 0. 16 0. 1598 0. 0002 0. 1596 0. 0004 12 0. 45 0. 4492 0. 0008 0. 4932-0. 0432 13 0. 25 0. 2499 1E - 04 0. 2276 0. 0224 14 0. 30 0. 3001-1E - 04 0. 3215-0. 0215 15 0. 98 0. 9729 0. 0071 0. 9702 0. 0098 16 0. 90 0. 9018-0. 0018 0. 8932 0. 0068 17 0. 37 0. 3702-0. 0002 0. 4270-0. 0570 18 0. 10 0. 0999 0. 0001 0. 1117-0. 0117 19 0. 23 0. 2301-1E - 04 0. 2548-0. 0248 20 0. 90 0. 9015-0. 0015 0. 8925 0. 0075 21 0. 90 0. 8946 0. 0054 0. 9016-0. 0016 22 0. 45 0. 4496 0. 0004 0. 4652-0. 0152 23 0. 80 0. 8016-0. 0016 0. 8028-0. 0028 24 0. 65 0. 6506-0. 0006 0. 6738-0. 0238 25 0. 35 0. 3503-0. 0003 0. 3715-0. 0215 26 0. 65 0. 6504-0. 0004 0. 6313 0. 0187 27 0. 15 0. 1493 0. 0007 0. 1463 0. 0037 28 0. 50 0. 4999 1E - 04 0. 4135 0. 0865 29 0. 10 0. 0995 0. 0005 0. 1305-0. 0305 30 0. 70 0. 7000 010000 0. 7373-0. 0373 31 0. 20 0. 1998 0. 0002 0. 2029-0. 0029 32 0. 50 0. 5003-0. 0003 0. 4878 0. 0122 33 0. 20 0. 1996 0. 0004 0. 1453 0. 0547 34 0. 40 0. 4008-0. 0008 0. 4336-0. 0336 35 0. 86 0. 8602-0. 0002 0. 9378-0. 0778 36 0. 25 0. 2505-0. 0005 0. 2376 0. 0124 37 0. 80 0. 7999 1E - 04 0. 8486-0. 0486 38 0. 73 0. 7291 0. 0009 0. 6870 0. 0430 39 0. 50 0. 5000 010000 0. 3921 0. 1079 40 0. 90 0. 9002-0. 0002 0. 9238-0. 0238 41 0. 40 0. 3998 0. 0002 0. 3605 0. 0395 42 0. 90 0. 9002-0. 0002 0. 8928 0. 0072 43 0. 30 0. 2999 1E - 04 0. 2244 0. 0756 44 0. 95 0. 9510-0. 0010 0. 9536-0. 0036 45 0. 10 0. 1003-0. 0003 0. 0882 0. 0118 46 0. 20 0. 1999 0. 0001 0. 3091-0. 1091 47 0. 40 0. 3999 0. 0001 0. 3933 0. 0067 48 0. 05 0. 0504-0. 0004 0. 0519-0. 0019 49 0. 10 0. 1004-0. 0004 0. 1096-0. 0096 50 0. 35 0. 3500 010000 0. 3369 0. 0131 51 0. 05 0. 0489 0. 0011 0. 0460 0. 0040 R 2 0. 9999 0. 98340 s 0. 0023 0. 0382 No. 1 51 are the same as table 1 ; EV = experimental values,nlv = network learning values,rd = residual difference,av = anticipation values 2 Matlab,, 19,

1 5 [9] 0 1 4 51 30 50 : lr = 0. 1, lr (i) = 51 1. 08, lr (d) Leave - one - out = 0. 9 10 m = 0. 9, R s 0. 9980 0. 0218 12 ; 40,, 30 30, QSPR, QSPR 1 2 (1 ) leave - one - out 50 51 4 3 10 5 6. 28 %, R = 0. 9980 s = 0. 0218 QSPR 5 Table 5 Prediction ability analysis of neural network No. EV AV RD RE/ % 52 0. 06 0. 0702-0. 0102 17 53 0. 07 0. 0626 0. 0074 10. 6 54 0. 5 0. 4531 0. 0469 9. 38 55 0. 7 0. 7295-0. 0295 4. 21 56 0. 9 0. 891 0. 009 1 57 0. 9 0. 885 0. 035 1. 67 58 0. 9 0. 872 0. 028 3. 11 59 0. 9 0. 8896 0. 2104 1. 15 60 0. 1 0. 111-0. 011 9. 9 61 0. 3 0. 2856 0. 0144 4. 8 R 0. 9980 s 0. 0218 No. 52 61 are the same as table 1 ; EV,AV and RD are the same as table 4, RE = relative error 1 Obach RS,Baxter J G, Liston TE, et al. The prediction of human pharma2 cokinetic parameters from Pheclinical and in vitro metabolism data [J ]. J Pharmacol Exp Ther,1997,283 :46 2. [J ].,2000, 32 (3) : 193 3. [ M]. :,2000. 15 4. [M]. :,19991194 5 Blakey GE. Quantitative based model to characterize changes in pharma2 cokinetics across a homologous series of barbiturates in the rat[j ]. Journal of Pharmakokinetic Biopharmaceutical,1997,25 :277 6 Ivan Nestorov. Quantitative structure - pharmacokinetics relationships :A mechanistically based model to evaluate the relationship between tissue distribution parametersand compound lipophilicity[j ]. Journal of Pharma2 cokinetic and Biopharmaceutical,1998,26(5) :521 7 Jogarao V, Gobburu S,William H, et al. Quantitative structure - pharma2 ceutical relationship (QSPR) of beta blocker derived using neural network [J ].Journal of Pharmacutical Science,1995,84 (7) :862 8. [ M]. :, 1994. 10 9 Kuemmerle, HP.. [M]. :,19971238 :2002-09

2024 © sciencedocbox.com Privacy Policy | Terms of Service | Feedback