Hongtao Guo

Traditional Chinese Medicine-Based Network Pharmacology Could Lead to New Multicompound Drug Discovery

Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM) has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Exploring the biological basis of deficiency pattern in rheumatoid arthritis through text mining

In the theory of traditional Chinese medicine, deficiency pattern is a distinguished one among patterns in rheumatoid arthritis. As for the explanation of deficiency pattern in rheumatoid arthritis, traditional Chinese medicine explains the deficiency in organs of both liver and kidney. As for the modern medicine, no specific factor available to explain it. In this paper, we propose an approach through data mining to explore the biological basis of deficiency pattern in rheumatoid arthritis. In this approach, the first step is to find the formula in traditional Chinese medicine in the treatment of rheumatoid arthritis. Then, list out the top three diseases which can be regulated by this formula. After that, we can find the networks of biological basis existing among all these three diseases by data mining. By analyzing these networks, directly or not, the deficiency pattern in rheumatoid arthritis might be caused by the chronic inflammation.

Predicting and verifying outcome of Tripterygium wilfordii Hook F. based therapy in rheumatoid arthritis: from open to double-blinded randomized trial

Tripterygium wilfordii Hook F. (TwHF) based therapy has been proved as effective in treating rheumatoid arthritis (RA), yet the predictors to its response remains unclear. A two-stage trial was designed to identify and verify the baseline symptomatic predictors of this therapy. 167 patients with active RA were enrolled with a 24-week TwHF based therapy treatment and the symptomatic predictors were identified in an open trial; then in a randomized clinical trial (RCT) for verification, 218 RA patients were enrolled and classified into predictor positive (P+) and predictor negative (P−) group, and were randomly assigned to accept the TwHF based therapy and Methotrexate and Sulfasalazine combination therapy (M&S) for 24 weeks, respectively. Five predictors were identified (diuresis, excessive sweating, night sweats for positive; and yellow tongue-coating, thermalgia in the joints for negative). In the RCT, The ACR 20 responses were 82.61% in TwHF/P+ group, significantly higher than that in TwHF/P− group (P = 0.0001) and in M&S/P+ group (P < 0.05), but not higher than in M&S/P− group. Similar results were yielded in ACR 50 yet not in ACR 70 response. No significant differences were detected in safety profiles among groups. The identified predictors enable the TwHF based therapy more efficiently in treating RA subpopulations.

Corrigendum: Safety Profiles of Tripterygium wilfordii Hook F: A Systematic Review and Meta-Analysis

[This corrects the article on p. 402 in vol. 7, PMID: 27877128.].

Text mining of rheumatoid arthritis and diabetes mellitus to understand the mechanisms of Chinese medicine in different diseases with same treatment

ObjectiveTo identify the commonalities between rheumatoid arthritis (RA) and diabetes mellitus (DM) to understand the mechanisms of Chinese medicine (CM) in different diseases with the same treatment.MethodsA text mining approach was adopted to analyze the commonalities between RA and DM according to CM and biological elements. The major commonalities were subsequently verified in RA and DM rat models, in which herbal formula for the treatment of both RA and DM identified via text mining was used as the intervention.ResultsSimilarities were identified between RA and DM regarding the CM approach used for diagnosis and treatment, as well as the networks of biological activities affected by each disease, including the involvement of adhesion molecules, oxidative stress, cytokines, T-lymphocytes, apoptosis, and inflammation. The Ramulus Cinnamomi-Radix Paeoniae Alba-Rhizoma Anemarrhenae is an herbal combination used to treat RA and DM. This formula demonstrated similar effects on oxidative stress and inflammation in rats with collagen-induced arthritis, which supports the text mining results regarding the commonalities between RA and DM.ConclusionCommonalities between the biological activities involved in RA and DM were identified through text mining, and both RA and DM might be responsive to the same intervention at a specific stage.

CASP3, TP53, and MYC Targeted by Triptolide towards Ovary Induce Female Reproductive Toxicity

Triptolide is an important active compound derived from Chinese herbal medicine Tripterygium wilfordii Hook f. Despite its positive therapeutic effects, the female reproductive toxicity is still blocking its clinical application with its toxicity mechanism is still obscure. In order to tackle the mechanism of female reproductive toxicity, one intuitive approach is to explore the biological molecule network involving targeted proteins and associated ovary expressed proteins. In this study, triptolides target proteins and their biological functions were analyzed first. Then, focused on the enriched process of negative regulation of cell cycle, targeted proteins, together with proteins expressed in ovary which are contributed in negative regulation of cell cycle were extracted so as to form the female reproductive toxicity molecule network. Finally, three targeted proteins of CASP3, TP53, and MYC were highlighted as the leading causation of female reproductive toxicity. Further analysis indicated that these 3 target proteins can further regulate 21 ovary expressed proteins which also participate in associated processes. This study provides specified molecule level mechanism the female reproductive toxicity of triptolide which can be used to prevent toxicity while keeping its therapeutic effects.

Application of acupuncture on coronary heart disease treatment: A text mining study

It is a long histroy that use of acupuncture treatment coronary heart disease (CHD) which belongs to Xiong Bi in Traditional Chinese Medicine (TCM). In this paper, application of acupuncture on CHD treatment was analyzed by text mining. The study was focused on the fields of meridian, acupoints, acupuncture method and constructed the associated network of them. By analyzing the network, we found that Pericardium Meridian of Hand-Jueyin was the frequently used meridian combined with other meridians and Neiguan was the frequently used acupoint combined with other acupoints for acupuncture treatment on CHD. Electroacupuncture was the common used method and often applied in the meridian of Hand-Jueyin and Hand-Shaoyin. The combinations of meridians, acupoints and methods were demonstrated in network. Results could be helpful for both clinical practice and medical research.

Study of acupuncture therapy on hypertension based on text ming

Hypertension becomes a major public health problem due to its serious morbidity and mortality and serious cardiovascular, cerebrovascular and kidney complications. The complementary therapies of Traditional Chinese Medicine (TCM) play important roles in hypertension treatment. Acupuncture, as an important component in TCM, is frequently used in treatment hypertension. In this paper, we mined the data set of literature downloaded from SinoMed on hypertension focused on its treatment with acupuncture technology in TCM common use. The text mining results showed that Shuigou, Zhongshu, Burong, Zusanli, and Taichong were the top 5 acupoints, while Governor Meridian, Bladder Meridian of Foot-Taiyang and Stomach Meridian of Foot-Yangming were the top 3 meridian used for hypertension treatment. The combinations of acupoints were demonstrated in network, which were widely used in the clinical practices of acupuncture. The results provided good references for both clinical practice and medical research.

Rules of acupoint selection in acupoint application therapy on coronary heart disease: A text mining study

Acupoint application therapy is one of the Traditional Chinese medicine (TCM) external therapies, which has been used for coronary heart disease (CHD) treatment for a long time. The prescription of acupoint application therapy includes both Chinese herbal medicines (CHMs) and acupoints. This study aims to reveal the basic rules of acupoint selection in acupoint application therapy on CHD treatment by text mining study. Results showed that on CHD treatment, the most frequently used acupoint was Danzhong (RN17), followed by Xinshu (BL15), Neiguan (PC6), Zusanli (ST36) and Zhiyang (DU9). Acupoints closing to the heart or with specific functions were more frequently used. Moreover, Xinshu, Danzhong and Neiguan were of the top 3 relationships with other acupoints, while Zusanli and Sanyinjiao (SP6) were in the lower grade. The combination of Xinshu-Danzhong-Neiguan could be regard as the basic acupoint prescription of acupoint application therapy on CHD.

Exploring associated rules of Danggui in traditional Chinese medicine through text mining

Single Chinese herbal medicine is the basic element in traditional Chinese medicines clinical treatment against disease. Then, it is an interesting and meaningful task to acquire knowledge of a single Chinese herbal medicine within the framework of traditional Chinese medicine (TCM). In this paper, based on the knowledge of TCM, we explored the association rules of Danggui (Angelica sinensis in Latin). These associated rules include Danggui-TCM syndrome/pattern, Danggui-disease, Danggui-symptom, Danggui-TCM herbal formula, and Danggui-Chinese herbal medicines. Through text mining, these rules can be demonstrated in different networks. These associated networks represent a variety of knowledge points and most of them can be validated in textbooks of traditional Chinese medicines. Thus, these results might be useful for both clinical practice and medical research, and the approach provides a novel way in exploring associated rules of single Chinese herbal medicine within the framework of traditional Chinese medicine.