A General Model for Prediction of Caco‐2 Cell Permeability

Wiley - Tập 23 Số 5 - Trang 303-310 - 2004
Anneli Nordqvist1,2, Jonas Nilsson3,4, Tuulikki Lindmark2, Alf Eriksson5, Per Garberg2, Mats Kihlén3
1Division of Organic Pharmaceutical Chemistry, Department of Medicinal Chemistry, BMC, Uppsala University, Box 574, SE-751 23 Uppsala, Sweden
2In Vitro Sciences
3Stuctural Chemistry
4Tel.: +46 8 6973870
5Analytical Sciences, Biovitrum AB, SE-112 76 Stockholm, Sweden

Tóm tắt

AbstractPermeability across the epithelium is one of the major barriers to drug absorption and is one property subject to in silico prediction attempts. Prediction models provide a possibility to address absorption issues, early in drug discovery, for a large number of compounds. The aim of this study was to develop a general comprehensive partial least square projection to latent structures (PLS)‐model for prediction of Caco‐2 cell permeability using theoretically calculated descriptors suited for large virtual libraries. In order to deal with current issues of data quantity and quality the well‐established Caco‐2 cell model was used to generate accurate permeability data of apparent passive transport for a large set of structurally diverse compounds. PLS statistics was used to correlate calculated descriptors to log Papp. This new prediction model for Caco‐2 cell permeability has incorporated many different descriptor types to deal with the multivariate nature of permeability. The model is designed to classify discovery compounds as low, medium or high permeable. A good statistical model was derived (R2=0.79, Q2=0.65, n=46) using 70 descriptors including lipophilicity, hydrogen bonding, polar surface area, size and charge descriptors and some nonlinear terms. The model has been tested and proved valid on two different external test sets (n=5 and n=125 respectively). Root mean square error of prediction (RMSEP) was 0.45 for the small external test set. The model predicted 82% of the compounds in the test sets as members to the correct class, 18% were classified wrong. No low permeable compounds were classified as high permeable and only one high permeable compound was classified as low permeable. With this model it has been shown that the in silico prediction models for Caco‐2 cell permeability has taken a step closer to meet the expectations of a high throughput filter tool applied in early phase drug discovery.

Từ khóa


Tài liệu tham khảo

10.1016/S1359-6446(97)01099-4

10.1016/S1359-6446(01)01712-3

10.1016/S0169-409X(00)00129-0

10.1016/S0168-3659(99)00239-4

10.1016/S1093-3263(99)00034-0

10.1021/ci010108d

10.1002/jps.1061

10.1021/ci000065l

10.1002/qsar.19960150604

10.1023/A:1011930411574

10.1007/978-3-0348-8391-7_1

10.1021/jm980313t

10.1021/js950285r

10.1023/A:1011905522110

10.1021/jm020986i

10.1002/jps.10214

10.1021/jm001101a

10.1016/S0378-5173(02)00045-5

10.1023/A:1012196216736

10.1002/(SICI)1521-3838(200002)19:1<39::AID-QSAR39>3.0.CO;2-N

10.1016/S0166-1280(99)00360-7

10.1016/S0928-0987(00)00162-7

10.1021/js9804011

10.1002/jps.2600840622

10.1021/ci980029a

10.1016/0006-291X(91)91647-U

10.1016/S0169-409X(02)00004-2

10.1016/S0169-409X(96)00415-2

Artursson P., Epithelial Cell Culture. A Practical Approach

10.1023/A:1018838121975

10.1021/ac50047a019

10.1021/ci010127n

10.1021/ci00028a014

10.1023/A:1025330209199

10.1023/A:1012188625088

10.1023/A:1025358319677

Garberg P., Toxicol. in Vitro

Kier L. B., Molecular structure description

10.1021/ac00220a013

Thông tin
Thông tin xuất bản

Wiley

Tập 23 Số 5

303-310

Thông tin tác giả