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Role of structural bioinformatics and traditional Chinese medicine databases in pharmacogenomics “Fundamentally different from Western medicines, the understanding of human bodies in traditional Chinese medicines is based on the holistic comprehension of the universe described in Daoism, and their therapy is based primarily on the diagnosis and differentiation of syndromes using the yin-yang and five elements theories...” With the completion of the Human Genome Project and advancements in genetics and protein sciences, the postgenomic era has been inevitable. Pharmacogenomics emerged with this tide of fashion, which is defined by Vogel and his colleagues as the study of how an individual genetic inheritance affects the body’s response to drugs [1–4] . Pharmacogenomics investigates the genetic basis of individual variations in response to clinical drugs. This subject has a consuming impact on each step of the therapy process, from diagnosis to drug prescription and from drug design to clinical trials. It is believed that the application of pharmacogenomics based on the patient’s genetic profiles would enhance the prediction of a patient’s response to particular drugs and empower physicians to make right decisions for the treatment.
An effective approach to pharmacogenomics requires the integration of interdisciplinary sciences, including structural genomics, functional genomics, proteomics, disease pathogenesis, pharmacology and toxicology. Among these subjects, structural bioinformatics play a significant role for understanding the key issues in pharmacogenomics at the atomic level [5,6] that contain the associations between structures and functions, as well as the interactions among genes, drugs and the environment. Structural bioinformatics mainly investigates the roles that biological molecules play in the context of complicated pathways and interactions, giving an improved understanding of disease and drug mechanisms
at the atomic level. As the development of the biological sciences progresses, a vast number of sequence data are obtained each year. However, the 3D information cannot be detected as fast as this sequence information when only using traditional experimental approaches. Fortunately, structural bioinformatics can overcome this barrier [7,8] . Compared with the traditional experimental approaches, this computational method is quick enough to obtain proteins’ structural information. In ideal conditions, structural bioinformatics is able to accurately predict the structural information of proteins from only their sequence data. As widely recognized by more and more biological scientists, structural bioinformatics has been rapidly developing over the past 10 years. Nowadays, the prediction of protein secondary structures is almost well-rounded and widely used in the biological studies. Nevertheless, the prediction of the 3D structures of proteins is not satisfying. Generally speaking, there are three major approaches to predict the 3D structures of proteins, namely homology modeling, folding recognition, and ab initio method. Although all these methods can accurately obtain structural information of proteins in some special conditions, connatural limitations exist in all of these approaches. Homology modeling and folding recognition are dependent on the known protein structures. The former needs to obtain a homology template with a known structure having high resolution to build the 3D structure of target protein. The latter has to establish a fold database according to the existing crystal structures or NMR structures. It can be concluded that if a protein does not have a homology template in the known structural database and has novel 3D folding, its real 3D structure may not be predicted accurately by the aforementioned approaches. In such a situation, you can think of the ab initio method. However, huge
10.2217/PGS.09.81 © 2009 Future Medicine Ltd
Pharmacogenomics (2009) 10(8), 1213–1215
“Structural bioinformatics mainly
investigates the roles that biological molecules play in the context of complicated pathways and interactions, giving an improved understanding of disease and drug mechanisms at the atomic level.”
Jing-Fang Wang Shanghai Jiaotong University, Shanghai, China
Dong-Qing Wei† Author for correspondence: Department of Bioinformatics & Biostatistics, College of Life Sciences & Biotechnology, Shanghai Jiaotong University, Shanghai, China 200240 Tel.: +86 213 420 4573; Fax: +86 213 420 4573;
[email protected] †
ISSN 1462-2416
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computational works and poor precision limit the application of this approach. Nevertheless, it can confidently be concluded that these computational approaches will be greatly improved and applied to other areas as the rapid development of computer sciences continues, especially the combinational use of the homology modeling and folding recognition approaches [9] . On the other hand, the introduction of the concept of systems biology, enabling the study of living systems based on the profiling of a multitude of biochemical components, opens up a unique opportunity for pharmacogenomics. In the study of their bioactivity, the necessary reductionistic approach on single active components has been successful in the discovery of new medicines, but at the same time the synergetic effects of components were lost. Systems biology, and especially metabolomics, is the ultimate phenotyping. It opens up the possibility of studying the effect of complex mixtures (multiple components), such as those used in traditional Chinese medicine (TCM), in complex biological systems (multiple targets) [10,11] .
“An increasing number of new drugs, which have remarkable efficacies against common maladies, have been derived from Chinese herbs. Therefore, the construction of traditional Chinese medicine databases is impending...” With a history of at least 3000 years, such medicines have developed a novel and unique system to diagnose and cure diseases. It is well known that TCMs are one of the most comprehensive, well-documented traditional and folk medicines in human history. The Asians, especially the Chinese, have used TCMs to treat different kinds of diseases and maintain health since ancientry. Fundamentally different from Western medicines, the understanding of human bodies in TCMs is based on the holistic comprehension of the universe described in Daoism, and their therapy is based primarily on the diagnosis and differentiation of syndromes using the yin–yang and five elements theories, which apllythe phenomena and laws of nature to the physiological activities and pathological changes of human bodies and their interrelationships. In the TCM system, zang-fu organs are considered as the foundation of human bodies, where tissue and organs are integrated by a network of channels and blood vessels. Qi, also called
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Chi, acts as carriers of information and circles in Jingluo system. Pathologically, it is thought in the TCM approach that diseases of bodies may be reflected on the body surface by the aforementioned Jingluo network. So, this kind of treatment starts with analyzing the Jingluo system, subsequently focusing on the correction of pathological changes of bodies. The therapy in the TCM approach is not based only on the symptoms, but also differentiation of syndromes. The evaluation of syndromes involved in the cause, mechanism, location, as well as the confrontation between the pathogenic factors and body resistances. Owing to the limitations of modern Western drugs and demands for alternative and comprehensive medicines, today TCMs have gained more and more interest worldwide. In the search for new drugs and natural remedies, herbs used in TCMs have already been one of the most promising candidates. An increasing number of new drugs, which have remarkable efficacies against common maladies, have been derived from Chinese herbs. Therefore, the construction of TCM databases is impending, where the effective components extracted from TCM are organized in terms of chemical informatics protocols. Recently, two groups have respectively built TCM databases, which includes not only the TCMs, but also the relevant gene and disease information [12,13] . It allows one to use bioinformatics tools to build a systematic correlation between multiple targets with molecules from TCM. At this moment, the information obtained in the aforementioned two TCM databases make it possible to perform virtual screening for detecting novel drug candidates from TCMs. Also, this strategy has been achieved by Wei and his coworkers [14] . They found a novel drug candidate against Alzheimer’s disease from TCMs that has been verified experimentally. Therefore, it is believed that TCMs could provide more and more contributions to drug discovery as well as pharmacogenomics. Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest or financial conflict with the subject matter or materials discussed in this manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties. No writing assistance was utilized in the production of this manuscript.
future science group
Structural bioinformatics & tradition Chinese medicine databases in pharmacogenomics
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