NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

被引:250
作者
Chen, Xing [1 ]
Ren, Biao [2 ,3 ]
Chen, Ming [2 ]
Wang, Quanxin [2 ,4 ]
Zhang, Lixin [2 ,5 ]
Yan, Guiying [6 ]
机构
[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou, Peoples R China
[2] Chinese Acad Sci, Key Lab Pathogen Microbiol & Immunol, Inst Microbiol, Beijing, Peoples R China
[3] Sichuan Univ, West China Hosp Stomatol, State Key Lab Oral Dis, Chengdu, Peoples R China
[4] Univ Chinese Acad Sci, Beijing, Peoples R China
[5] Chinese Acad Sci, South China Sea Inst Oceanol, Guangzhou, Guangdong, Peoples R China
[6] Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
AMPHOTERICIN-B; CANDIDA-ALBICANS; EXTENDED-SPECTRUM; TRANSPORTER CDR1P; CALCINEURIN; FLUCONAZOLE; RESISTANCE; TERBINAFINE; THERAPY; STRESS;
D O I
10.1371/journal.pcbi.1004975
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations.
引用
收藏
页数:23
相关论文
共 82 条
[1]   DISCOVERY, BIOCHEMISTRY AND BIOLOGY OF LOVASTATIN [J].
ALBERTS, AW .
AMERICAN JOURNAL OF CARDIOLOGY, 1988, 62 (15) :J10-J15
[2]   Calcineurin is essential for virulence in Candida albicans [J].
Bader, T ;
Bodendorfer, B ;
Schröppel, K ;
Morschhäuser, J .
INFECTION AND IMMUNITY, 2003, 71 (09) :5344-5354
[3]   Role of calcineurin in stress resistance, morphogenesis, and virulence of a Candida albicans wild-type strain [J].
Bader, Teresa ;
Schroeppel, Klaus ;
Bentink, Stefan ;
Agabian, Nina ;
Koehler, Gerwald ;
Morschhaeuser, Joachim .
INFECTION AND IMMUNITY, 2006, 74 (07) :4366-4369
[4]  
Baginski M, 2005, ACTA BIOCHIM POL, V52, P655
[5]  
Belkin M, 2006, J MACH LEARN RES, V7, P2399
[6]  
BERENBAUM MC, 1989, PHARMACOL REV, V41, P93
[7]   Calcineurin is required for Candida albicans to survive calcium stress in serum [J].
Blankenship, JR ;
Heitman, J .
INFECTION AND IMMUNITY, 2005, 73 (09) :5767-5774
[8]   Calcineurin is essential for Candida albicans survival in serum and virulence [J].
Blankenship, JR ;
Wormley, FL ;
Boyce, MK ;
Schell, WA ;
Filler, SG ;
Perfect, JR ;
Heitman, J .
EUKARYOTIC CELL, 2003, 2 (03) :422-430
[9]   The toxicity of poisons applied jointly [J].
Bliss, CI .
ANNALS OF APPLIED BIOLOGY, 1939, 26 (03) :585-615
[10]   Systematic discovery of multicomponent therapeutics [J].
Borisy, AA ;
Elliott, PJ ;
Hurst, NW ;
Lee, MS ;
Lehár, J ;
Price, ER ;
Serbedzija, G ;
Zimmermann, GR ;
Foley, MA ;
Stockwell, BR ;
Keith, CT .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (13) :7977-7982