Journal Article

CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds

Druzhilovskiy, Dmitry S., Gloriozova, Tatyana A., Lagunin, Alexey A., Pogodin, Pavel V., Sastry, Narahari G., Rudik, Anastasia V., Filimonov, Dmitry A., Poroikov, Vladimir V., Dubovskaja, Varvara I.

2018

Overview

In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Algorithms / Anticancer properties / Antineoplastic Agents - chemistry / Antineoplastic Agents - pharmacology / Antineoplastic Agents - toxicity / Antitumor agents / Biocompatibility / Bioinformatics / Biological activity / Biology and Life Sciences / Biotechnology / Breast cancer / Breast Neoplasms - drug therapy / Cell Line / Cell Line, Tumor / Chemical compounds / Chemistry / Computer Simulation / Cytotoxicity / Drug Repositioning / Drug Screening Assays, Antitumor - methods / Drug Screening Assays, Antitumor - statistics & numerical data / Drugs / Experimental data / Female / Genomics / Humans / Internet / Lung cancer / Medical research / Medicine and Health Sciences / Methods / Molecular structure / Pharmaceutical industry / Predictions / Screening / Structure-Activity Relationship / Toxicity / Training / Tumor cell lines / Tumors / Web services