There have been renewed interests in natural products as drug discovery sources. In particular, natural product combinations have been extensively studied, clinically tested, and widely used in traditional, folk and alternative medicines. But opinions about their therapeutic efficacies vary from placebo to synergistic effects. The important questions are whether synergistic effects can sufficiently elevate therapeutic potencies to drug levels, and by what mechanisms and at what odds such combinations can be assembled. We studied these questions by analyzing literature-reported cell-based potencies of 190 approved anticancer and antimicrobial drugs, 1378 anticancer and antimicrobial natural products, 99 natural product extracts, 124 synergistic natural product combinations, and 122 molecular interaction profiles of the 19 natural product combinations with collective potency enhanced to drug level or by >10-fold. Most of the evaluated natural products and combinations are sub-potent to drugs. Sub-potent natural products can be assembled into combinations of drug level potency at low probabilities by distinguished multi-target modes modulating primary targets, their regulators and effectors, and intracellular bioavailability of the active natural products.
Citation: Qin C, Tan KL, Zhang CL, Tan CY, Chen YZ, Jiang YY (2012) What Does It Take to Synergistically Combine Sub-Potent Natural Products into Drug-Level Potent Combinations? PLoS ONE 7(11): e49969. doi:10.1371/journal.pone.0049969
Editor: Daniel S. Sem, Concordia University Wisconsin, United States of America
Received: September 19, 2012; Accepted: October 17, 2012; Published: November 28, 2012
Copyright: © 2012 Qin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors acknowledge support from The Ministry of Science and Technology of China (2012ZX09506001-010 and 2012CB722605), The National Natural Science Foundation of China (21272134) and Academic Research Fund, Singapore (R-148-000-141-750). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Natural products (NP) have been traditional sources of drug discovery and there are renewed interests in them for new drug discovery , , , . In particular, NP combinations have been extensively studied , , tested in clinical trials , , , and widely used in traditional, folk and alternative medicines , . Their novel multi-targeted mechanisms , ,  or molecular scaffolds  may be valuable sources for developing multi-targeted therapeutics . Opinions vary regarding to the therapeutic efficacies of NP combinations. One attributes the efficacies of NP combinations to placebo effects , ,  based on indications from clinical trials ,  and the findings that bioactive NPs are typically sub-potent to drugs , . Another credits the efficacies of NP combinations to synergistic effects , , , ,  based on the findings that some NP combinations produce significantly better effects than equivalent doses of their components ,  and clinical outcomes are not necessarily influenced by positive beliefs .
The contribution of synergistic effects to therapeutic efficacies has been extensively studied , , . While many studies have consistently suggested that therapeutic potency can be enhanced by synergistic effects, the levels of potency enhancement, particularly with respect to those of drugs, have not been sufficiently studied to quantitatively assess the contribution of synergism to the therapeutic efficacies of NP combinations. In particular, four important questions need to be answered: what are the gaps between the potencies of the typically studied bioactive NPs and those of drugs, whether synergistic combination of sub-potent NPs can sufficiently enhance their collective potencies to reach drug potency level, and at what odds and by what molecular modes such NP combinations can be assembled.
The first question was studied by analyzing the literature-reported cell-based potencies of 190 approved drugs and 1378 NPs of anticancer and antimicrobial classes. Potencies derived from cell-based assays were used instead of target-based and in-vivo assays for several reasons. To a certain extent, cell-based assays can predict in-vivo activities ,  and these assays have been successfully used for discovering therapeutic agents that have entered advanced development stages . Within the same disease classes, cell-based assays are more mutually comparable and better reflecting overall effects than target-based assays. The number of NPs with cell-based potency data is significantly higher than those with in-vivo data. The anticancer and antimicrobial classes were particularly focused because of the availability of statistically significant number of cell-based activity data, the relatively comparable bioassays than some other therapeutic classes, and the relevance to our NP combination studies (67% of our studied synergistic NP combinations are from these two classes).
The second question was addressed by evaluating 124 literature-reported synergistic combinations of 158 NPs with cell-based activity data available for all of the constituents both in individual and in the respective combination. These data are necessary for deriving combination index (CI) and dose reduction index (DRI) for rigorous evaluation of synergistic effects . The third question was probed by analyzing 122 molecular interaction profiles (MIPs) in 19 NP combinations with potencies enhanced to drug level or by over 10-fold. These MIPs are linked to the potency-enhancing synergistic molecular modes involving collective modulation of the primary targets, their regulators and effectors, and the pharmacokinetics of the active NP ingredients , .
While these 122 MIPs have been individually reported in the literatures, few of them have been collectively analyzed for probing potency enhancing molecular modes in NP combinations. It is cautioned that, although connections can be made between these MIPs and the synergistic potency-enhancing modes, many of these interconnections are much more complicated than those analyzed here. Their activities are highly dynamic , ,  influenced by genetic variations , environmental factors , host’s behavior , and therapeutic scheduling . Their use should be more appropriately viewed as a start to a more comprehensive analysis of the potency-enhancing modes in NP combinations.
Materials and Methods
Experimentally determined cell-based inhibitory activities of anticancer and antibacterial drugs and NPs were searched from the Pubmed database  by using keyword ‘drug’, ‘natural product’, ‘herb’, ‘medicinal plant’, ‘extract’, ‘ingredient’, ‘GI50’, ‘IC50’, ‘MIC’, “activity”, ‘cell-line’, and ‘in vitro’. Cell-based inhibitory activities of 88 anticancer and 102 antimicrobial drugs were obtained from the literatures and the NCI standard agent database (Table S1 and S2). Their approval status was further checked against the drug data in the Therapeutic target database . Cell-based inhibitory activities of 1378 anticancer and antimicrobial NPs (Table S3 and S4) and 99 antimicrobial NP extracts (Table S5) were obtained from the literatures. These activities are typically given as GI50 or IC50 values against cancer cell-lines or MIC values against microbial cells. For drugs and NPs with multiple potency data, the best potency was selected.
Literature-reported synergistic NP combinations were searched from the Pubmed database  by keywords ‘natural product’, ‘herb’, ‘medicinal plant’, ‘extract’, ‘ingredient’, ‘synergistic’, ‘synergy’, ‘synergism’, ‘synergize’, and ‘potentiate’. Although many NP combinations are synergistic , , , only 124 synergistic combinations of 158 NPs are with sufficient cell-based data for computing CI and DRI values (Table S6). The cell-based activities of the constituent NPs in some of these combinations are given in terms of the percent inhibitory rates at particular concentrations. Their CI and DRI values were computed by using the median effect equation, the multiple drug effect equation, and the combination index theorem .
Results and Discussion
Comparison of the Potencies of Natural Products and Drugs in Cell-based Assays
Drug potency is context dependent, varying with assay, target and technology. Previous analysis has suggested that drugs in cell-based assays typically exhibit potencies of ≤1 µM . Hence, we tentatively define drug potency level for anticancer and antimicrobial classes as GI50/IC50≤1 µM and MIC≤1 µg/mL respectively, which are satisfied by 76% anticancer and 86% antimicrobial drugs. In some cases, drug efficacy is not only determined by cell-based activities. A minority of drugs sub-potent in cell-based assays are nonetheless clinically efficacious by such additional mechanisms as immuo- and hormone modulations , . While drug potency level can be more rigorously defined by considering these mechanisms, few drugs and NPs have been sufficiently studied for enabling such a consideration. It is more practically feasible to tentatively focus on cell-based activities that nonetheless reflect the potencies of most drugs and NPs.
Figure 1 and 2 show the potency distribution profiles of 88 and 650 anticancer drugs and NPs, and those of 102, 609 and 99 antimicrobial drugs, NPs and NP extracts respectively. The median potencies of anticancer (GI50/IC50 = 28 nM) and antimicrobial (MIC = 0.12 µg/mL) drugs are 214-fold and 104-fold higher than those of anticancer (GI50/IC50 = 6 µM) and antimicrobial (MIC = 12.5 µg/mL) NPs. Overall, 25% of the anticancer and 10% of the antimicrobial NPs reach drug potency level, and additional 33% of the anticancer and 37% of the antibacterial NPs are within 10-fold range of drug potency level (1 µM<GI50/IC50≤10 µM, 1 µg/mL<MIC≤10 µg/mL). The pool of potent NPs is relatively small (10–25%). A significantly expanded pool of active NPs (47–58%) may be explored if NP combinations of >10-fold potency enhancement can be assembled at reasonable probabilities. The potencies of the NP extracts are mostly 100–1,000 folds lower than those of individual NPs, as the active constituents only constitute a small portion of their contents . Partly because of this gap, NP extracts have been typically prescribed in g/kg ,  in contrast to the mg/kg ranges for drugs and NPs.
Synergistic Natural Product Combinations
Based on Chou’s method , the levels of synergism in the NP combinations (Figure 3) were categorized into the levels of very strong synergism (CI<0.1), strong synergism (CI = 0.1–0.3), synergism (CI = 0.3–0.7), moderate synergism (CI = 0.7–0.85), slight synergism (CI = 0.85–0.90), nearly additive (CI = 0.90–1.10), slight antagonism (CI = 1.10–1.20), and moderate antagonism (CI = 1.20–1.45) respectively. Overall, 24% and 34% of the combinations are at the strong/very strong synergism and synergism levels, indicating that highly synergistic combinations can be formed at fair probabilities. Figure 4 shows the potency improvement profile of the NPs in these combinations, in which 4% and 19% of the NPs exhibit >100-fold and 10–100 fold potency improvement respectively. This suggests that >10-fold potency improvement is achievable at moderate probabilities. These combinations are mostly composed of sub-potent NPs. There are only 6 potent NPs, and 1 and 3 combinations fully and partially composed of potent NPs. Synergism elevates the collective potencies of 5 fully sub-potent and 2 partially sub-potent combinations to drug level, and lifts the potency of 4 NPs in another 3 sub-potent combinations to drug level. Overall, the potencies of 22 (14.4%) sub-potent NPs and collective potencies of 7 (5.6%) sub-potent combinations are enhanced to drug level, suggesting that the individual and collective potencies of sub-potent NPs can be raised to drug level at moderate and low probabilities respectively.
VSS, SS, S, MS, sS: very strong, strong, normal, moderate, slight synergism, NA: nearly additive, SA, MA: slight, moderate antagonism.
Potency Enhancing Molecular Modes of Natural Product Combinations
The molecular mechanisms of synergism of drug combinations  and NP combinations  can be studied from their MIPs. We conducted comprehensive literature search for identifying the targets and synergism-related MIPs of three NP combinations with collective potencies improved to drug levels, which identified 11 targets related to the reported therapeutic effects of these combinations and 72 MIPs likely contributing to the potency-enhancing modes (Table S7). The targets and potency-enhancing MIPs of two of the NP combinations are also summarized in Table 1 and 2. Specific potency-enhancing molecular modes were identified. The potencies of the principal NP in these combinations are at or near drug potency level (IC50 = 0.8–1.1 µM, 0.94 µg/mL) probably due in part to the multi-target activities of each principal NPs (2, 4, 5 targets respectively). Network and activity analysis have shown that weak inhibition of multiple targets in related pathways may be more efficient than strong inhibition against a single target , . The potencies of the companion NPs are substantially weaker (IC50 = 1.7–656 µM, 5.07–251 µg/mL). The potencies of all NPs in these combinations are significantly enhanced (mostly by >10-fold) by multi-target actions in modulating multiple regulators, partners and effectors of the primary targets of the active NPs (complementary actions), elevating intra-cellular bioavailability of the active NPs, and antagonizing the processes counteractive to the therapeutic effects of the active NPs (anti-counteractive actions).
Regulation of multiple regulators of the primary targets of principal NPs is important for elevating the collective potencies to drug level. In two combinations, 6 and 13 regulators of the primary targets of the principal NPs are modulated. In the third combination, each constituent NP targets one or two of the four redundant processes to collectively achieve therapeutic effects. These multi-target potency-enhancing modes are consistent with the reports that weak inhibition of multiple targets in related pathways may be more efficient than strong inhibition of a single target , . In these combinations, complementary actions are achieved by modulating the expression, upstream regulators, crosstalk/redundant signaling, and substrates/effectors of the targets of individual NPs. Intra-cellular bioavailability of NPs are enhanced by inhibiting/downregulating efflux pumps and upregulating/activating cell-entry transporters. Anti-counteractive actions involve regulation of the pathways activated by the NPs that subsequently reduce the therapeutic effects of the NPs. Drug efficacies are reportedly reduced by network robustness , redundancy , crosstalk , and compensatory and neutralizing actions . Our revealed potency-enhancing molecular modes provide useful clues for reducing these literature-reported negative effects by multi-targeted strategies.
Additional potency-enhancing mechanisms were studied by analyzing 8 and 26 MIPs in 2 and 9 combinations with the potency of the principal NP enhanced by >100-fold and 10–100 fold, and 16 MIPs of 5 combinations with the potency of a non-principal NP improved by >10-fold respectively (Table S8, S9, 10). The potency of individual NPs in 13 combinations is enhanced by a single mechanism: enhancement of the intra-cellular bioavailability of an active NP, which is an extensively-explored effective potency-enhancing strategy for those NPs with hindered intra-cellular bioavailability. In addition to actions on efflux and cell-entry transporters, intra-cellular bioavailability of NPs can be enhanced by regulating their metabolism, disrupting membrane structures, and the use of pro-drug NPs of better cell-entry abilities, The potency of individual NPs in the remaining 3 combination is enhanced by complementary and anti-counteractive modes similar to those of the three NP combinations with potencies improved to drug levels.
Although the potencies of some of the individual NPs in these combinations are significantly improved, none is elevated to drug level possibly due to low potencies of their principal NPs (44.6–800 µg/mL with one exception) and modulation of few regulators of the primary targets of the principal NPs. The success rate of assembling sub-potent NPs into drug-level potent combinations may be significantly improved by careful selection of principal NPs of sufficient potency (e.g. potency <10 µM) and the use of cooperative NPs that enhance the bioavailability and modulate the regulators, partners and effectors of the targets of the principal NPs.
Influence of Individual Genetic Variations
Combinations of sub-potent NPs heavily rely on their synergistic actions for improved potencies, which typically involve collective modulation of a certain set of the primary targets and the corresponding secondary targets. Because of their heavy reliance on the modulation of the specific sets of secondary targets for achieving sufficiently improved potency, the level of potency improvement of synergistic NP combinations is expected to be sensitively influenced by the genetic variations that alter the expression and activity level of this set of targets . Table 3 shows the expression profiles of the primary targets and some of the potency-enhancing secondary targets of the selected NP combinations in specific patient groups. The primary targets are expressed in 42%–95% the patients and the secondary targets are expressed in 15%–100% of the patients in different patient groups. Significantly lower percentages of patients in each patient group are expected to have the right set of the targets co-expressed to make them responsive to a particular sub-potent NP combination. Multi-herb combinations have been frequently prescribed in personalized manner ,  possibly out of the need for exploiting certain potency-enhancing modes active in specific patients.
Our analysis indicates the possibility of synergistically assembling sub-potent NPs into drug-level potent combinations, which can be achieved at low probabilities by the exploration of specific potency-enhancing modes that combine multi-target actions of the principal NPs of sufficient potency (typically within 10-fold range of drug potency levels) against specific disease processes with the enhancement of their bioavailability and/or the modulation of the regulators, effectors and counteractive elements of their targets. The low probabilities for assembling sub-potent NPs into drug-level potent combinations may arise from the difficulties in finding the right combination of NPs with sufficient potency and the appropriate and complementary potency-enhancing MIPs. Moreover, synergistic actions typically involve interactions with multiple sites, targets and pathways which are sensitively influenced by genetic , environmental , behavioral , and scheduling  profiles. NP combinations and related therapeutics may be better designed, applied and studied in personalized and environment-dependent manners , . The efforts in the exploration of NP combinations can be facilitated by expanded knowledge in the activities of NPs , MIPs of NPs , disease regulations, and potency-enhancing molecular modes that synergistically target key positive  and negative  regulatory nodes of therapeutic efficacies, and collectively modulate anti-targets and counter-targets , compensatory and neutralizing actions , , and transporter and enzyme mediated pharmacokinetic activities .
Cell-based inhibitory activity data of 88 anticancer drugs.
Cell-based microbial inhibitory activity data of 102 antimicrobial drugs.
Cell-based inhibitory activity values of 650 anticancer natural products.
Cell-based microbial inhibitory activity values of 609 antimicrobial natural products.
Cell-based microbial inhibitory activity values of 99 antimicrobial natural product extracts.
List of 124 synergistic natural product combinations with available cell-based potency data.
Targets and potency-enhancing synergistic molecular modes in 3 fully or partially sub-potent natural product combinations with group potencies improved to drug levels.
Targets and potency-enhancing molecular interaction modes in 2 fully sub-potent natural product combinations with potencies of the principal component increased by >100 fold.
Targets and potency-enhancing molecular interaction modes in 9 fully sub-potent natural product combinations with potencies of the principal component increased by 10–100 fold.
Targets and potency-enhancing molecular interaction modes in 5 fully sub-potent natural product combinations with potencies of a non-principal component increased by 10–100 fold.
Conceived and designed the experiments: CQ YYJ YZC. Performed the experiments: CQ KLT CLZ CYT YYJ YZC. Analyzed the data: CQ KLT CLZ CYT YYJ YZC. Contributed reagents/materials/analysis tools: CQ KLT CLZ. Wrote the paper: CQ YZC.
- 1. Molinski TF, Dalisay DS, Lievens SL, Saludes JP (2009) Drug development from marine natural products. Nat Rev Drug Discov 8: 69–85. doi: 10.1038/nrd2487
- 2. Li JW, Vederas JC (2009) Drug discovery and natural products: end of an era or an endless frontier? Science 325: 161–165. doi: 10.1126/science.1168243
- 3. Newman DJ, Cragg GM (2007) Natural products as sources of new drugs over the last 25 years. J Nat Prod 70: 461–477. doi: 10.1021/np068054v
- 4. Zhu F, Qin C, Tao L, Liu X, Shi Z, et al. (2011) Clustered patterns of species origins of nature-derived drugs and clues for future bioprospecting. Proc Natl Acad Sci U S A 108: 12943–12948. doi: 10.1073/pnas.1107336108
- 5. Junio HA, Sy-Cordero AA, Ettefagh KA, Burns JT, Micko KT, et al. (2011) Synergy-directed fractionation of botanical medicines: a case study with goldenseal (Hydrastis canadensis). J Nat Prod 74: 1621–1629. doi: 10.1021/np200336g
- 6. Gertsch J (2011) Botanical drugs, synergy, and network pharmacology: forth and back to intelligent mixtures. Planta Med 77: 1086–1098. doi: 10.1055/s-0030-1270904
- 7. Shabbir M, Love J, Montgomery B (2008) Phase I trial of PC-Spes2 in advanced hormone refractory prostate cancer. Oncol Rep 19: 831–835. doi: 10.3892/or.19.3.831
- 8. Ma XH, Zheng CJ, Han LY, Xie B, Jia J, et al. (2009) Synergistic therapeutic actions of herbal ingredients and their mechanisms from molecular interaction and network perspectives. Drug Discov Today 14: 579–588. doi: 10.1016/j.drudis.2009.03.012
- 9. Cochrane ZR, Gregory P, Wilson A (2011) Quality of natural product clinical trials: a comparison of those published in alternative medicine versus conventional medicine journals. J Diet Suppl 8: 135–143.
- 10. Eisenberg DM, Davis RB, Ettner SL, Appel S, Wilkey S, et al. (1998) Trends in alternative medicine use in the United States, 1990–1997: results of a follow-up national survey. JAMA 280: 1569–1575. doi: 10.1001/jama.280.18.1569
- 11. Cordell GA, Colvard MD (2012) Natural products and traditional medicine: turning on a paradigm. J Nat Prod 75: 514–525. doi: 10.1021/np200803m
- 12. Jia J, Zhu F, Ma X, Cao Z, Li Y, et al. (2009) Mechanisms of drug combinations: interaction and network perspectives. Nat Rev Drug Discov 8: 111–128. doi: 10.1038/nrd2683
- 13. Zimmermann GR, Lehar J, Keith CT (2007) Multi-target therapeutics: when the whole is greater than the sum of the parts. Drug Discov Today 12: 34–42. doi: 10.1016/j.drudis.2006.11.008
- 14. Kong DX, Jiang YY, Zhang HY (2010) Marine natural products as sources of novel scaffolds: achievement and concern. Drug Discov Today 15: 884–886. doi: 10.1016/j.drudis.2010.09.002
- 15. Kaiser J (2011) Combining targeted drugs to stop resistant tumors. Science 331: 1542–1545. doi: 10.1126/science.331.6024.1542
- 16. Lewith GT, Hyland ME, Shaw S (2002) Do attitudes toward and beliefs about complementary medicine affect treatment outcomes? American Journal of Public Health 92: 1604–1606. doi: 10.2105/ajph.92.10.1604
- 17. Barker Bausell R (2009) Are positive alternative medical therapy trials credible?: Evidence from four high-impact medical journals. Eval Health Prof 32: 349–369. doi: 10.1177/0163278709346810
- 18. Staud R (2011) Effectiveness of CAM therapy: understanding the evidence. Rheum Dis Clin North Am 37: 9–17. doi: 10.1016/j.rdc.2010.11.009
- 19. Williamson EM (2001) Synergy and other interactions in phytomedicines. Phytomedicine 8: 401–409. doi: 10.1078/0944-7113-00060
- 20. Dinan L, Bourne PC, Meng Y, Sarker SD, Tolentino RB, et al. (2001) Assessment of natural products in the Drosophila melanogaster B(II) cell bioassay for ecdysteroid agonist and antagonist activities. Cell Mol Life Sci 58: 321–342. doi: 10.1007/pl00000859
- 21. Stermitz FR, Lorenz P, Tawara JN, Zenewicz LA, Lewis K (2000) Synergy in a medicinal plant: antimicrobial action of berberine potentiated by 5′-methoxyhydnocarpin, a multidrug pump inhibitor. Proceedings of the National Academy of Sciences of the United States of America 97: 1433–1437. doi: 10.1073/pnas.030540597
- 22. Wagner H (2011) Synergy research: approaching a new generation of phytopharmaceuticals. Fitoterapia 82: 34–37. doi: 10.1016/j.fitote.2010.11.016
- 23. Fantin B, Leggett J, Ebert S, Craig WA (1991) Correlation between in vitro and in vivo activity of antimicrobial agents against gram-negative bacilli in a murine infection model. Antimicrob Agents Chemother 35: 1413–1422. doi: 10.1128/aac.35.7.1413
- 24. Johnson JI, Decker S, Zaharevitz D, Rubinstein LV, Venditti JM, et al. (2001) Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br J Cancer 84: 1424–1431.
- 25. Shoemaker RH (2006) The NCI60 human tumour cell line anticancer drug screen. Nat Rev Cancer 6: 813–823. doi: 10.1038/nrc1951
- 26. Chou TC (2006) Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacol Rev 58: 621–681. doi: 10.1124/pr.58.3.10
- 27. Kumar N, Afeyan R, Kim HD, Lauffenburger DA (2008) Multi-Pathway Model Enables Prediction of Kinase Inhibitor Cross-Talk Effects on Migration of Her2-Overexpressing Mammary Epithelial Cells. Mol Pharmacol.
- 28. Xiong H, Choe Y (2008) Dynamical pathway analysis. BMC Syst Biol 2: 9. doi: 10.1186/1752-0509-2-9
- 29. Sivachenko A, Kalinin A, Yuryev A (2006) Pathway analysis for design of promiscuous drugs and selective drug mixtures. Curr Drug Discov Technol 3: 269–277. doi: 10.2174/157016306780368117
- 30. Kim HS, Fay JC (2007) Genetic variation in the cysteine biosynthesis pathway causes sensitivity to pharmacological compounds. Proc Natl Acad Sci U S A 104: 19387–19391. doi: 10.1073/pnas.0708194104
- 31. Carvalho-Netto EF, Markham C, Blanchard DC, Nunes-de-Souza RL, Blanchard RJ (2006) Physical environment modulates the behavioral responses induced by chemical stimulation of dorsal periaqueductal gray in mice. Pharmacol Biochem Behav 85: 140–147. doi: 10.1016/j.pbb.2006.07.022
- 32. Yang H, Yang T, Baur JA, Perez E, Matsui T, et al. (2007) Nutrient-sensitive mitochondrial NAD+ levels dictate cell survival. Cell 130: 1095–1107. doi: 10.1016/j.cell.2007.07.035
- 33. Tabernero J, Rojo F, Calvo E, Burris H, Judson I, et al.. (2008) Dose- and Schedule-Dependent Inhibition of the Mammalian Target of Rapamycin Pathway With Everolimus: A Phase I Tumor Pharmacodynamic Study in Patients With Advanced Solid Tumors. J Clin Oncol.
- 34. Sayers EW, Barrett T, Benson DA, Bolton E, Bryant SH, et al. (2012) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 40: D13–25. doi: 10.1093/nar/gkr1184
- 35. Zhu F, Shi Z, Qin C, Tao L, Liu X, et al. (2012) Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res 40: D1128–1136. doi: 10.1093/nar/gkr797
- 36. Oprea TI, Bologa CG, Boyer S, Curpan RF, Glen RC, et al. (2009) A crowdsourcing evaluation of the NIH chemical probes. Nat Chem Biol 5: 441–447. doi: 10.1038/nchembio0709-441
- 37. MacIndoe JH, Woods GR, Etre LA, Covey DF (1982) Comparative studies of aromatase inhibitors in cultured human breast cancer cells. Cancer Res 42: 3378s–3381s.
- 38. Quach H, Ritchie D, Stewart AK, Neeson P, Harrison S, et al. (2010) Mechanism of action of immunomodulatory drugs (IMiDS) in multiple myeloma. Leukemia 24: 22–32. doi: 10.1038/leu.2009.236
- 39. Hayashi K, Shimura K, Makino T, Mizukami H (2010) Comparison of the contents of kampo decoctions containing ephedra herb when prepared simply or by re-boiling according to the traditional theory. J Nat Med 64: 70–74. doi: 10.1007/s11418-009-0375-z
- 40. Zhou XM, Lu CN, Qi WB, Ma YJ, Tang YZ, et al. (2011) In vivo anti-avian influenza virus activity of Qingkailing and Shuanghuanglian Orals. Chin. Tradit. Herb Drugs 42: 1351–1356.
- 41. Li LJ, Wang JY, Wang Y, Wang LJ, Wang HY, et al. (2005) Anti-Virus Activities of the Extract and Effective Components Isolated from Senecio Cannabifolius Less. Chin J Basic Med Tradit Chin Med 11: 585–587.
- 42. Csermely P, Agoston V, Pongor S (2005) The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol Sci 26: 178–182. doi: 10.1016/j.tips.2005.02.007
- 43. Xie L, Evangelidis T, Bourne PE (2011) Drug discovery using chemical systems biology: weak inhibition of multiple kinases may contribute to the anti-cancer effect of nelfinavir. PLoS Comput Biol 7: e1002037. doi: 10.1371/journal.pcbi.1002037
- 44. Papp B, Pal C, Hurst LD (2004) Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429: 661–664. doi: 10.1038/nature02636
- 45. Pilpel Y, Sudarsanam P, Church GM (2001) Identifying regulatory networks by combinatorial analysis of promoter elements. Nat Genet 29: 153–159. doi: 10.1038/ng724
- 46. Muller R (2004) Crosstalk of oncogenic and prostanoid signaling pathways. J Cancer Res Clin Oncol 130: 429–444. doi: 10.1007/s00432-004-0570-y
- 47. Sergina NV, Rausch M, Wang D, Blair J, Hann B, et al. (2007) Escape from HER-family tyrosine kinase inhibitor therapy by the kinase-inactive HER3. Nature 445: 437–441. doi: 10.1038/nature05474
- 48. Tong X, Li A, Zhang Z, Duan J, Chen X, et al. (2004) TCM treatment of infectious atypical pneumonia–a report of 16 cases. J Tradit Chin Med 24: 266–269.
- 49. Zhang GG, Lee W, Bausell B, Lao L, Handwerger B, et al. (2005) Variability in the traditional Chinese medicine (TCM) diagnoses and herbal prescriptions provided by three TCM practitioners for 40 patients with rheumatoid arthritis. J Altern Complement Med 11: 415–421. doi: 10.1089/acm.2005.11.415
- 50. Larder BA, Kemp SD, Harrigan PR (1995) Potential mechanism for sustained antiretroviral efficacy of AZT-3TC combination therapy. Science 269: 696–699. doi: 10.1126/science.7542804
- 51. Dancey JE, Chen HX (2006) Strategies for optimizing combinations of molecularly targeted anticancer agents. Nat Rev Drug Discov 5: 649–659. doi: 10.1038/nrd2089
- 52. Silver LL (2007) Multi-targeting by monotherapeutic antibacterials. Nat Rev Drug Discov 6: 41–55. doi: 10.1038/nrd2202
- 53. Chiu PH, Hsieh HY, Wang SC (2012) Prescriptions of traditional Chinese medicine are specific to cancer types and adjustable to temperature changes. PLoS One 7: e31648. doi: 10.1371/journal.pone.0031648
- 54. Efferth T (2010) Personalized cancer medicine: from molecular diagnostics to targeted therapy with natural products. Planta Med 76: 1143–1154. doi: 10.1055/s-0030-1249937
- 55. Harvey AL, Cree IA (2010) High-throughput screening of natural products for cancer therapy. Planta Med 76: 1080–1086. doi: 10.1055/s-0030-1250162
- 56. Georgakis GV, Li Y, Rassidakis GZ, Medeiros LJ, Younes A (2006) The HSP90 inhibitor 17-AAG synergizes with doxorubicin and U0126 in anaplastic large cell lymphoma irrespective of ALK expression. Exp Hematol 34: 1670–1679. doi: 10.1016/j.exphem.2006.07.002
- 57. Smalley KS, Haass NK, Brafford PA, Lioni M, Flaherty KT, et al. (2006) Multiple signaling pathways must be targeted to overcome drug resistance in cell lines derived from melanoma metastases. Mol Cancer Ther 5: 1136–1144. doi: 10.1158/1535-7163.mct-06-0084
- 58. Overall CM, Kleifeld O (2006) Tumour microenvironment - opinion: validating matrix metalloproteinases as drug targets and anti-targets for cancer therapy. Nat Rev Cancer 6: 227–239. doi: 10.1038/nrc1821
- 59. Kassouf W, Dinney CP, Brown G, McConkey DJ, Diehl AJ, et al. (2005) Uncoupling between epidermal growth factor receptor and downstream signals defines resistance to the antiproliferative effect of Gefitinib in bladder cancer cells. Cancer Res 65: 10524–10535. doi: 10.1158/0008-5472.can-05-1536
- 60. Thanou M, Verhoef JC, Junginger HE (2001) Oral drug absorption enhancement by chitosan and its derivatives. Adv Drug Deliv Rev 52: 117–126. doi: 10.1016/s0169-409x(01)00231-9