A Computer Method for Validating Traditional Chinese Medicine Herbal Prescriptions

Computational approaches for modeling and structural design of biological systems: A comprehensive review

The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.

A Novel Framework for Understanding the Pattern Identification of Traditional Asian Medicine From the Machine Learning Perspective

Pattern identification (PI), a unique diagnostic system of traditional Asian medicine, is the process of inferring the pathological nature or location of lesions based on observed symptoms. Despite its critical role in theory and practice, the information processing principles underlying PI systems are generally unclear. We present a novel framework for comprehending the PI system from a machine learning perspective. After a brief introduction to the dimensionality of the data, we propose that the PI system can be modeled as a dimensionality reduction process and discuss analytical issues that can be addressed using our framework. Our framework promotes a new approach in understanding the underlying mechanisms of the PI process with strong mathematical tools, thereby enriching the explanatory theories of traditional Asian medicine.

Treasuring the computational approach in medicinal plant research

Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was time consuming and expensive. Computational methods such as Molecular Docking, Molecular Dynamic Simulation and Artificial intelligence are significant Insilico tools in medicinal plant research. Molecular docking approach exploits the mechanism of potential phytochemicals into the target active site to elucidate its interactions and biological therapeutic properties. MD simulation illuminates the dynamic behavior of biomolecules at atomic level with fine quality representation of biomolecules. Dramatical advancement in computer science is illustrating the biological mechanism via these tools in different diseases treatment. The advancement comprises speed, the system configuration, and other software upgradation to insights into the structural explanation and optimization of biomolecules. A probable shift from simulation to artificial intelligence has in fact accelerated the art of scientific study to a sky high. The most upgraded algorithm in artificial intelligence such as Artificial Neural Networks, Deep Neural Networks, Neuro-fuzzy Logic has provided a wide opportunity in easing the time required in classical experimental strategy. The notable progress in computer science technology has paved a pathway for understanding the pharmacological functions and creating a roadmap for drug design and development and other achievement in the field of medicinal plants research. This review focus on the development and overview in computational research moving from static molecular docking method to a range of dynamic simulation and an advanced artificial intelligence such as machine learning.

A comparative study of the efficacy of Chinese herbal medicine Duhuo Jisheng decoction combined with DMARDs vs isolated DMARDs for rheumatoid arthritis: A protocol for systematic review and meta analysis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic autoimmune system disease that mainly affects joints throughout the body, causing joint pain, deformity, and even disability. The use of Chinese herbal medicine (CHM) to treat RA has achieved certain effects, and Duohuo Jisheng decoction (DHJSD) is one of them. But there is no high-level evidence to support this result. The purpose of this work is to evaluate the effectiveness of DHJSD combined with DMARDs compared with isolated DMARDs for RA.

METHODS

We will search articles in 7 electronic databases including Chinese National Knowledge Infrastructure (CNKI), Wanfang Data (WF), Chinese Scientific Journals Database (VIP), Chinese databases SinoMed (CBM), PubMed, Embase, and Cochrane Library databases. All the publications, with no time restrictions, will be searched without any restriction of language and status, the time from the establishment of the database to October 2020. Two reviewers will independently assess the quality of the selected studies, NoteExpress and Excel software will be used to extract data, and the content will be stored in an electronic chart. Different researchers will separately screen the titles and abstracts of records acquired potential eligibility which comes from the electronic databases. Full-text screening and data extraction will be conducted afterward independently. Statistical analysis will be conducted using RevMan 5.4 software.

RESULTS

This study will evaluate the efficacy and safety of DHJSD combined with DMARDs compared with isolated DMARDs in the treatment of Rheumatoid arthritis, to provide high-quality, evidence-based clinical recommendations.

CONCLUSION

This study will provide reliable evidence on whether Duhuo Jisheng decoction combined with DMARDs compared with isolated DMARDs is more effective in treating RA.

TRIAL REGISTRATION NUMBER

INPLASY2020100089.

Deciphering the combination principles of Traditional Chinese Medicine from a systems pharmacology perspective based on Ma-huang Decoction

ETHNOPHARMACOLOGY RELEVANCE

The main therapeutic concept in Traditional Chinese Medicine (TCM) is herb formula, which treats various diseases via potential herb interactions to maximize the efficacy and minimize the adverse effects. However, the combination principle of herb formula still remains a mystery due to the lack of appropriate methods.

METHODS

A systems pharmacology method integrating the pharmacokinetic analysis, drug targeting, and drug-target-disease network is developed to dissect this rule embedded in the herbal formula. All these are exemplified by a representative TCM formula, Ma-huang decoction, made up of four botanic herbs.

RESULTS

Based on the deep investigation of the function and compatibility of each herb, in a molecular/systems level, we demonstrate the different pharmacological roles that each herb might play in the prescription. By the way of enhancing the bioavailability and/or making the pharmacological synergy among different herbs, the four herbs effectively combine together to be suitable for treating diseases.

CONCLUSIONS

The present work lays foundations for a more comprehensive understanding of the combination rule of TCM, which might also be beneficial to drug development and applications.

Immunomodulatory activity of a Chinese herbal drug Yi Shen Juan Bi in adjuvant arthritis

OBJECTIVE

To investigate the immunomodulating mechanisms of a Chinese herbal medicine Yi Shen Juan Bi (YJB) in treatment of adjuvant arthritis (AA) in rats.

MATERIALS AND METHODS

Levels of serum tumor necrosis factor alpha (TNF-alpha) and interleukin-1beta (IL-1beta) were measured by the Enzyme-Linked Immunosorbent Assay (ELISA). Expression of TNF-alpha mRNA and IL-1beta mRNA in synovial cells was measured with the semi-quantitative technique of reverse transcription-polymerase chain reaction (RT-PCR), while caspase-3 was examined by western blot analysis.

RESULTS

The administration of YJB significantly decreased the production of serum TNF-alpha and IL-1beta. It also decreased significantly the TNF-alpha mRNA, IL-1beta mRNA, and caspase-3 expression in synoviocytes.

CONCLUSIONS

YJB produces the immunomodulatory effects by downregulating the over-activated cytokines, while it activates caspase-3, which is the key executioner of apoptosis in the immune system. This may be the one of the underlying mechanisms that explains how YJB treats the rheumatoid arthritis.

Sini tang prevents depression-like behavior in rats exposed to chronic unpredictable stress

Sini Tang, a Chinese traditional prescription containing three herbs, has been widely used for Yang-deficiency. Recent clinical studies have shown that Sini Tang could treat and improve depression symptoms, but the mechanisms underlying the antidepressant effect of Sini Tang remains unknown. In rats with chronic unpredictable stress (CUS), we examined the effects of Sini Tang on sucrose preference and open field exploratory behavior. The levels of corticosterone level in plasma and corticotropin-releasing hormone (CRH) mRNA expression in hypothalamus were also measured by enzyme-linked immunosorbent assays (ELISA) and real-time reverse transcription PCR (RT-PCR), respectively. Rats subjected to CUS exhibited decreases in sucrose preference and ambulation in the open field test. These were all attenuated by Sini Tang in a dose-dependent manner. Biochemically, Sini Tang also reversed CUS-induced increases in corticosterone in plasma and CRH mRNA in the hypothalamus. The behavioral effects of the Sini Tang were correlated to the biochemical actions. These results suggest that Sini Tang produces an antidepressant-like effect, which appears to involve CRH in the brain.

Are herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties

Multi-herb prescriptions of traditional Chinese medicine (TCM) often include special herb-pairs for mutual enhancement, assistance, and restraint. These TCM herb-pairs have been assembled and interpreted based on traditionally defined herbal properties (TCM-HPs) without knowledge of mechanism of their assumed synergy. While these mechanisms are yet to be determined, properties of TCM herb-pairs can be investigated to determine if they exhibit features consistent with their claimed unique synergistic combinations. We analyzed distribution patterns of TCM-HPs of TCM herb-pairs to detect signs indicative of possible synergy and used artificial intelligence (AI) methods to examine whether combination of their TCM-HPs are distinguishable from those of non-TCM herb-pairs assembled by random combinations and by modification of known TCM herb-pairs. Patterns of the majority of 394 known TCM herb-pairs were found to exhibit signs of herb-pair correlation. Three AI systems, trained and tested by using 394 TCM herb-pairs and 2470 non-TCM herb-pairs, correctly classified 72.1-87.9% of TCM herb-pairs and 91.6-97.6% of the non-TCM herb-pairs. The best AI system predicted 96.3% of the 27 known non-TCM herb-pairs and 99.7% of the other 1,065,100 possible herb-pairs as non-TCM herb-pairs. Our studies suggest that TCM-HPs of known TCM herb-pairs contain features distinguishable from those of non-TCM herb-pairs consistent with their claimed synergistic or modulating combinations.

Usefulness of traditionally defined herbal properties for distinguishing prescriptions of traditional Chinese medicine from non-prescription recipes

Traditional Chinese medicine (TCM) has been widely practiced and is considered as an attractive to conventional medicine. Multi-herb recipes have been routinely used in TCM. These have been formulated by using TCM-defined herbal properties (TCM-HPs), the scientific basis of which is unclear. The usefulness of TCM-HPs was evaluated by analyzing the distribution pattern of TCM-HPs of the constituent herbs in 1161 classical TCM prescriptions, which shows patterns of multi-herb correlation. Two artificial intelligence (AI) methods were used to examine whether TCM-HPs are capable of distinguishing TCM prescriptions from non-TCM recipes. Two AI systems were trained and tested by using 1161 TCM prescriptions, 11,202 non-TCM recipes, and two separate evaluation methods. These systems correctly classified 83.1-97.3% of the TCM prescriptions, 90.8-92.3% of the non-TCM recipes. These results suggest that TCM-HPs are capable of separating TCM prescriptions from non-TCM recipes, which are useful for formulating TCM prescriptions and consistent with the expected correlation between TCM-HPs and the physicochemical properties of herbal ingredients responsible for producing the collective pharmacological and other effects of specific TCM prescriptions.

Database of traditional Chinese medicine and its application to studies of mechanism and to prescription validation

BACKGROUND AND PURPOSE

Traditional Chinese Medicine (TCM) is widely practised and is viewed as an attractive alternative to conventional medicine. Quantitative information about TCM prescriptions, constituent herbs and herbal ingredients is necessary for studying and exploring TCM.

EXPERIMENTAL APPROACH

We manually collected information on TCM in books and other printed sources in Medline. The Traditional Chinese Medicine Information Database TCM-ID, at http://tcm.cz3.nus.edu.sg/group/tcm-id/tcmid.asp, was introduced for providing comprehensive information about all aspects of TCM including prescriptions, constituent herbs, herbal ingredients, molecular structure and functional properties of active ingredients, therapeutic and side effects, clinical indication and application and related matters.

RESULTS

TCM-ID currently contains information for 1,588 prescriptions, 1,313 herbs, 5,669 herbal ingredients, and the 3D structure of 3,725 herbal ingredients. The value of the data in TCM-ID was illustrated by using some of the data for an in-silico study of molecular mechanism of the therapeutic effects of herbal ingredients and for developing a computer program to validate TCM multi-herb preparations.

CONCLUSIONS AND IMPLICATIONS

The development of systems biology has led to a new design principle for therapeutic intervention strategy, the concept of 'magic shrapnel' (rather than the 'magic bullet'), involving many drugs against multiple targets, administered in a single treatment. TCM offers an extensive source of examples of this concept in which several active ingredients in one prescription are aimed at numerous targets and work together to provide therapeutic benefit. The database and its mining applications described here represent early efforts toward exploring TCM for new theories in drug discovery.

Effect of 3-Phenyl-2-Propene-1-ol on PGE2 release from rat cerebral microvascular endothelial cells stimulated by IL-1beta

Fever, an elevation in body temperature, is thought to be terminally mediated by prostaglandin E(2) (PGE(2)). Both Guizhi Tang (GZT) and its active fraction A (Fr.A) showed an antipyretic effect in rats. 3-Phenyl-2-propene-1-ol was one of the active compounds isolated from Fr.A. In the present study, we examined the influence of interleukin-1beta (IL-1beta) on prostaglandin E(2) (PGE(2)) release, and the effect of 3-phenyl-2-propene-1-ol on IL-1beta-induced PGE(2) release from rat cerebral endothelial cells (rCMEC). Cultured rCMEC were used in the study. In vitro, cells express typical phenotypic markers of brain endothelium. Using a monoclonal antibody against von Willebrand factor, immunocytochemical analysis revealed positive immunoreactivity in the cytoplasm of cultured cells. rCMEC were incubated in M199 medium containing IL-1beta in the presence or absence of 3-phenyl-2-propene-1-ol. After incubation, the conditioned media were collected and the amount of PGE(2) was measured by enzyme-linked immunosorbent assay (ELISA). IL-1beta increased the production of PGE(2) in a dose- and time-dependent manner. 3-Phenyl-2-propene-1-ol significantly decreased IL-1beta-induced PGE(2) release in a dose-dependent manner. Our results indicate that 3-phenyl-2-propene-1-ol inhibits the PGE(2) release from rCMEC stimulated by IL-1beta, and may have an antipyretic effect.