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Wu Q, Wang Y, Liu J, Guan X, Chang X, Liu Z, Liu R. Microtubules and Cardiovascular Diseases: Insights into Pathology and Therapeutic Strategies. Int J Biochem Cell Biol 2024; 175:106650. [PMID: 39237031 DOI: 10.1016/j.biocel.2024.106650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 08/25/2024] [Accepted: 08/31/2024] [Indexed: 09/07/2024]
Abstract
Microtubules, complex cytoskeletal structures composed of tubulin proteins in eukaryotic cells, have garnered recent attention in cardiovascular research. Investigations have focused on the post-translational modifications of tubulin, including acetylation and detyrosination. Perturbations in microtubule homeostasis have been implicated in various pathological processes associated with cardiovascular diseases such as heart failure, ischemic heart disease, and arrhythmias. Thus, elucidating the intricate interplay between microtubule dynamics and cardiovascular pathophysiology is imperative for advancing preventive and therapeutic strategies. Several natural compounds have been identified to potentially modulate microtubules, thereby exerting regulatory effects on cardiovascular diseases. This review synthesizes current literature to delineate the roles of microtubules in cardiovascular diseases and assesses the potential of natural compounds in microtubule-targeted therapies.
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Affiliation(s)
- Qiaomin Wu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yanli Wang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Jinfeng Liu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xuanke Guan
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xing Chang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
| | - Zhiming Liu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Ruxiu Liu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
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Li XL, Zhang JQ, Shen XJ, Zhang Y, Guo DA. Overview and limitations of database in global traditional medicines: A narrative review. Acta Pharmacol Sin 2024:10.1038/s41401-024-01353-1. [PMID: 39095509 DOI: 10.1038/s41401-024-01353-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 07/02/2024] [Indexed: 08/04/2024] Open
Abstract
The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.
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Affiliation(s)
- Xiao-Lan Li
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jian-Qing Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
| | - Xuan-Jing Shen
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yu Zhang
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Research Center of TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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Singh S, Ghosh P, Sharma S, Bhargava S, Kumar AR. Tetrahydropalmatine from medicinal plants activates human glucokinase to regulate glucose homeostasis. Biotechnol Appl Biochem 2024; 71:295-313. [PMID: 38037220 DOI: 10.1002/bab.2541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 11/20/2023] [Indexed: 12/02/2023]
Abstract
Many synthetic glucokinase activators (GKAs), modulating glucokinase (GK), an important therapeutic target in diabetes have failed to clear clinical trials. In this study, an in silico structural similarity search with differing scaffolds of reference GKAs have been used to identify derivatives from natural product databases. Ten molecules with good binding score and similar interactions to that in the co-crystallized GK as well good activation against recombinant human GK experimentally were identified. Tetrahydropalmatine, an alkaloid present in formulations and drugs from medicinal plants, has not been explored as an antidiabetic agent and no information regarding its mechanism of action or GK activation exists. Tetrahydropalmatine activates GK with EC50 value of 71.7 ± 17.9 μM while lowering the S0.5 (7.1 mM) and increasing Vmax (9.22 μM/min) as compared to control without activator (S0.5 = 10.37 mM; Vmax = 4.8 μM/min). Kinetic data (α and β values) suggests it to act as mixed, nonessential type activator. Using microscale thermophoresis, Kd values of 3.8 μM suggests a good affinity for GK. In HepG2 cell line, the compound potentiated the uptake of glucose and maintained glucose homeostasis by increasing the expression of GK, glycogen synthase, and insulin receptor genes and lowering the expression of glucokinase regulatory protein (GKRP) and glucagon. Tetrahydropalmatine at low concentrations could elicit a good response by reducing expression of GKRP, increasing expression of GK while also activating it. Thus, it could be used alone or in combination as therapeutic drug as it could effectively modulate GK and alter glucose homeostasis.
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Affiliation(s)
- Sweta Singh
- Department of Zoology, Savitribai Phule Pune University, Pune, India
- Institute of Bioinformatics and Biotechnology, Savitribai Phule Pune University, Pune, India
| | - Payel Ghosh
- Bioinformatics Centre, Savitribai Phule Pune University, Pune, India
| | - Shilpy Sharma
- Department of Biotechnology, Savitribai Phule Pune University, Pune, India
| | - Shobha Bhargava
- Department of Zoology, Savitribai Phule Pune University, Pune, India
| | - Ameeta Ravi Kumar
- Institute of Bioinformatics and Biotechnology, Savitribai Phule Pune University, Pune, India
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Fan M, Jin C, Li D, Deng Y, Yao L, Chen Y, Ma YL, Wang T. Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review. Front Pharmacol 2023; 14:1289901. [PMID: 38035021 PMCID: PMC10682728 DOI: 10.3389/fphar.2023.1289901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 11/03/2023] [Indexed: 12/02/2023] Open
Abstract
The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.
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Affiliation(s)
- Mengyue Fan
- Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Ching Jin
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, United States
| | - Daping Li
- Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yingshan Deng
- College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Lin Yao
- Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yongjun Chen
- Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yu-Ling Ma
- Oxford Chinese Medicine Research Centre, University of Oxford, Oxford, United Kingdom
| | - Taiyi Wang
- Innovation Research Institute of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
- Oxford Chinese Medicine Research Centre, University of Oxford, Oxford, United Kingdom
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Singh K, Maurya H, Singh P, Panda P, Behera AK, Jamal A, Eslavath G, Mohapatra S, Chauhan H, Sharma D. DISPEL: database for ascertaining the best medicinal plants to cure human diseases. Database (Oxford) 2023; 2023:baad073. [PMID: 37847815 PMCID: PMC10581335 DOI: 10.1093/database/baad073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 08/11/2023] [Accepted: 10/05/2023] [Indexed: 10/19/2023]
Abstract
Medicinal plants are anticipated to be one of the most valuable resources for the remedial usage in the treatment of various ailments. The data on key medicinal plants and their therapeutic efficacy against various ailments are quite scattered and not available on a single platform. Moreover, currently there is no means/mechanism of finding the best medicinal plant(s) from numerous plants known to cure any disease. DISPEL (Diseases Plants Eliminate) is a compendium of medicinal plants available across the world that are used to cure infectious as well as non-infectious diseases in humans. The association of a medicinal plant with a disease it cures is hereby referred to as 'medicinal plant-disease cured' linkage. The DISPEL database hosts ∼60 000 'medicinal plant-disease cured' linkages encompassing ∼5500 medicinal plants and ∼1000 diseases. This platform provides interactive and detailed visualization of medicinal plants, diseases and their relations using comprehensible network graph representation. The user has the freedom to search the database by specifying the name of disease(s) as well as the scientific/common name(s) of plant. Each 'medicinal plant-disease cured' relation is scored based on the availability of any medicine/product derived from that medicinal plant, information about active compound(s), knowledge regarding the part of plant that is effective and number of distinct articles/books/websites confirming the effectiveness of the medicinal plant. The user can find the best plant(s) that can be used to cure any desired disease(s). The DISPEL database is the first step towards generating the 'most-effective' combination of plants to cure a disease since it delineates as well as ranks all the therapeutic medicinal plants for that disease. The combination of best medicinal plants can then be used to conduct clinical trials and thus pave the way for their use in clinics for treatment of diseases. Database URL https://compbio.iitr.ac.in/dispel.
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Affiliation(s)
- Kavya Singh
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Harshit Maurya
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
- Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Parthasarathi Singh
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Pujarani Panda
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Amit Kumar Behera
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Arshad Jamal
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Ganesh Eslavath
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Somesh Mohapatra
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Harsh Chauhan
- Plant Molecular Biology and Biotechnology Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
| | - Deepak Sharma
- Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
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Lavanya P, Davis G DJ. Chemo-structural diversity of anti-obesity compound database. J Mol Graph Model 2023; 120:108414. [PMID: 36702059 DOI: 10.1016/j.jmgm.2023.108414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 12/28/2022] [Accepted: 01/12/2023] [Indexed: 01/20/2023]
Abstract
Nature plays a major role in the development of new drugs which helps in preventing and treating human diseases. Anti-obesity compound database (AOCD) contains comprehensive information on all published small molecules from natural sources with anti-obesity potential targeting pancreatic lipase (PL), appetite suppressant (AS) and adipogenesis (AD). Presently the database contains 349 compounds isolated from 307 plants, 26 marine and 16 microbial sources. Users can query the AOCD database (https://aocd.swmd.co.in/) in several ways. The database was divided into three datasets (PL, AS and AD) to perform chemoinformatic analysis using Platform for Unified Molecular Analysis (PUMA), which were analyzed based on molecular descriptors, scaffold diversity and structural fingerprint diversity. Chemoinformatics study inferred the PL dataset has the highest diversity of compounds based on the Euclidean distance on molecular properties, scaffold diversity and pairwise similarity on fingerprint diversity. This study would hasten the process of anti-obesity drug discovery.
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Affiliation(s)
- Prabhakar Lavanya
- Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India
| | - Dicky John Davis G
- Department of Bioinformatics, Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India.
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Multifaceted Pharmacological Potentials of Curcumin, Genistein, and Tanshinone IIA through Proteomic Approaches: An In-Depth Review. Cancers (Basel) 2022; 15:cancers15010249. [PMID: 36612248 PMCID: PMC9818426 DOI: 10.3390/cancers15010249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/03/2022] [Accepted: 12/12/2022] [Indexed: 01/03/2023] Open
Abstract
Phytochemicals possess various intriguing pharmacological properties against diverse pathological conditions. Extensive studies are on-going to understand the structural/functional properties of phytochemicals as well as the molecular mechanisms of their therapeutic function against various disease conditions. Phytochemicals such as curcumin (Cur), genistein (Gen), and tanshinone-IIA (Tan IIA) have multifaceted therapeutic potentials and various efforts are in progress to understand the molecular dynamics of their function with different tools and technologies. Cur is an active lipophilic polyphenol with pleiotropic function, and it has been shown to possess various intriguing properties including antioxidant, anti-inflammatory, anti-microbial, anticancer, and anti-genotoxic properties besides others beneficial properties. Similarly, Gen (an isoflavone) exhibits a wide range of vital functions including antioxidant, anti-inflammatory, pro-apoptotic, anti-proliferative, anti-angiogenic activities etc. In addition, Tan IIA, a lipophilic compound, possesses antioxidant, anti-angiogenic, anti-inflammatory, anticancer activities, and so on. Over the last few decades, the field of proteomics has garnered great momentum mainly attributed to the recent advancement in mass spectrometry (MS) techniques. It is envisaged that the proteomics technology has considerably contributed to the biomedical research endeavors lately. Interestingly, they have also been explored as a reliable approach to understand the molecular intricacies related to phytochemical-based therapeutic interventions. The present review provides an overview of the proteomics studies performed to unravel the underlying molecular intricacies of various phytochemicals such as Cur, Gen, and Tan IIA. This in-depth study will help the researchers in better understanding of the pharmacological potential of the phytochemicals at the proteomics level. Certainly, this review will be highly instrumental in catalyzing the translational shift from phytochemical-based biomedical research to clinical practice in the near future.
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Huo X, Gu Y, Zhang Y. The discovery of multi-target compounds with anti-inflammation activity from traditional Chinese medicine by TCM-target effects relationship spectrum. JOURNAL OF ETHNOPHARMACOLOGY 2022; 293:115289. [PMID: 35427724 DOI: 10.1016/j.jep.2022.115289] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 03/26/2022] [Accepted: 04/08/2022] [Indexed: 06/14/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Rhei Radix et Rhizoma, Lonicerae Japonicae Flos and Zingiberis Rhizoma was widely used in the treatment of inflammatory disease. The discovery of new multi-target compounds for new drug from the TCM was a possible direction. AIM OF THE STUDY Multi-target compounds screening based on polypharmacology was an effective method. As an interdisciplinary field, polypharmacology screen multi-target compounds by various methods. So, a flexible screening framework to avoid the disadvantage of single methods is considered to have great significance. MATERIALS AND METHODS The research propose a common framework called Traditional Chinese medicine target-effect relationship spectrum (TCM-TERS). TCM-TERS was constructed based on the pharmacophore and molecular docking models, which provided predicted activity by compounds screening. TCM-TERS merge the results of different models and visualize the targeted activity of each compounds. Then the TCM-TERS were analyzed by the analytic hierarchy process and active components were chosen by the contributing factors. The activity of components was verified on the RAW264.7 by RT-PCR. RESULTS This article constructed TCM-TERS of Rhei Radix et Rhizoma, Lonicerae Japonicae Flos and Zingiberis Rhizoma with the COX-2, mPGES-1, 5-LOX and SPLA2-IIA. Seven compounds were chosen with multiple targeted activity based on the TCM-TERS, which showed remarkable activity in RT-PCR. CONCLUSION The TCM-TERS was an efficient interdisciplinary method for drug discovery of the TCM, which provide a flexible method to the researcher that can screen specific compounds with multiple screening methods.
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Affiliation(s)
- Xiaoqian Huo
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
| | - Yu Gu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
| | - Yanling Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
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LTM-TCM: A Comprehensive Database for the Linking of Traditional Chinese Medicine with Modern Medicine at Molecular and Phenotypic Levels. Pharmacol Res 2022; 178:106185. [DOI: 10.1016/j.phrs.2022.106185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/11/2022] [Accepted: 03/12/2022] [Indexed: 02/07/2023]
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Mahmud S, Paul GK, Biswas S, Kazi T, Mahbub S, Mita MA, Afrose S, Islam A, Ahaduzzaman S, Hasan MR, Shimu MSS, Promi MM, Shehab MN, Rahman E, Sujon KM, Alom MW, Modak A, Zaman S, Uddin MS, Emran TB, Islam MS, Saleh MA. phytochemdb: a platform for virtual screening and computer-aided drug designing. Database (Oxford) 2022; 2022:6535291. [PMID: 35234849 PMCID: PMC9255273 DOI: 10.1093/database/baac002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/23/2021] [Accepted: 01/12/2022] [Indexed: 12/02/2022]
Abstract
The phytochemicals of medicinal plants are regarded as a rich source of diverse chemical spaces that have been used as supplements and alternative medicines in the millennium. Even in this era of combinatorial chemical drugs, phytomedicines account for a large share of the statistics of newly approved drugs. In the field of computational aided and rational drug design, there is an urgent need to develop and build a useful phytochemical database management system with a user-friendly interface that allows proper data storage, retrieval and management. We showed ‘phytochemdb’, a manually managed database that compiles 525 plants and their corresponding 8093 phytochemicals, aiming to incorporate the activities of phytochemicals from medicinal plants. The database collects molecular formula, three-dimensional/two-dimensional structure, canonical SMILES, molecular weight, no. of heavy atoms, no. of aromatic heavy atoms, fraction Csp3, no. of rotatable bonds, no. of H-bond acceptors, no. of H-bond donors, molar refractivity, topological polar surface area, gastrointestinal absorption, Blood–Brain Barrier (BBB) permeant, P-gp substrate, CYP1A2 inhibitor, CYP2C19 inhibitor, CYP2C9 inhibitor, CYP2D6 inhibitor, CYP3A4 inhibitor, Log Kp, Ghose, Veber, Egan, Muegge, bioavailability scores, pan-assay interference compounds, Brenk, Leadlikeness, synthetic accessibility, iLOGP and Lipinski rule of five with the number of violations for each compound. It provides open contribution functions for the researchers who screen phytochemicals in the laboratory and have released their data. ‘phytochemdb’ is a comprehensive database that gathers most of the information about medicinal plants in one platform, which is considered to be very beneficial to the work of researchers on medicinal plants. ‘phytochemdb’ is available for free at https://phytochemdb.com/.
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Affiliation(s)
- Shafi Mahmud
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Gobindo Kumar Paul
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Suvro Biswas
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Taheruzzaman Kazi
- Department of Regenerative Dermatology, Graduate School of Medicine, Osaka University , Suita 565-0871, Japan
| | - Shafquat Mahbub
- Department of Computer Science and Engineering, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Mohasana Akter Mita
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Shamima Afrose
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Ariful Islam
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Sheikh Ahaduzzaman
- Department of Computer Science and Engineering, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Md. Robiul Hasan
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | | | - Maria Meha Promi
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Mobasshir Noor Shehab
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Ekhtiar Rahman
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Khaled Mahmud Sujon
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Md. Wasim Alom
- Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Anik Modak
- Department of Computer Science and Engineering, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Shahriar Zaman
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Md. Salah Uddin
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
| | - Talha Bin Emran
- Department of Pharmacy, BGC Trust University Bangladesh , Chittagong 4381, Bangladesh
| | - Md. Sayeedul Islam
- Department of Biological Sciences, Graduate School of Science, Osaka University , Machikaneyama-cho 1-1, Toyonaka, Osaka 560-0043, Japan
| | - Md. Abu Saleh
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi , Rajshahi 6205, Bangladesh
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Alotaibi BS, Ijaz M, Buabeid M, Kharaba ZJ, Yaseen HS, Murtaza G. Therapeutic Effects and Safe Uses of Plant-Derived Polyphenolic Compounds in Cardiovascular Diseases: A Review. Drug Des Devel Ther 2021; 15:4713-4732. [PMID: 34848944 PMCID: PMC8619826 DOI: 10.2147/dddt.s327238] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/12/2021] [Indexed: 12/29/2022] Open
Abstract
Polyphenols have long been recognized as health-promoting entities, including beneficial effects on cardiovascular disease, but their reputation has been boosted recently following a number of encouraging clinical studies in multiple chronic pathologies, that seem to validate efficacy. Health benefits of polyphenols have been linked to their well-established powerful antioxidant activity. This review aims to provide comprehensive and up-to-date knowledge on the current therapeutic status of polyphenols having sufficient heed towards the treatment of cardiovascular diseases. Furthermore, data about the safety profile of highly efficacious polyphenols has also been investigated to further enhance their role in cardiac abnormalities. Evidence is presented to support the action of phenolic derivatives against cardiovascular pathologies by following receptors and signaling pathways which ultimately cause changes in endogenous antioxidant, antiplatelet, vasodilatory, and anti-inflammatory activities. In addition, in vitro antioxidant and pre-clinical and clinical experiments on anti-inflammatory as well as immunomodulatory attributes of polyphenols have revealed their role as cardioprotective agents. However, an obvious shortage of in vivo studies related to dose selection and toxicity of polyphenols makes these compounds a suitable target for clinical investigations. Further studies are needed for the development of safe and potent herbal products against cardiovascular diseases. The novelty of this review is to provide comprehensive knowledge on polyphenols safety and their health claims. It will help researchers to identify those moieties which likely exert protective and therapeutic effects towards cardiovascular diseases.
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Affiliation(s)
- Badriyah Shadid Alotaibi
- Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Munazza Ijaz
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan
| | - Manal Buabeid
- Medical and Bio-Allied Health Sciences Research Centre, Ajman University, Ajman, United Arab Emirates
- Department of Clinical Sciences, Ajman University, Ajman, 346, United Arab Emirates
| | - Zelal Jaber Kharaba
- Department of Clinical Sciences, College of Pharmacy, Al-Ain University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Hafiza Sidra Yaseen
- Department of Pharmacy, COMSATS University Islamabad, Lahore Campus, Lahore, 54000, Pakistan
| | - Ghulam Murtaza
- Department of Pharmacy, COMSATS University Islamabad, Lahore Campus, Lahore, 54000, Pakistan
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12
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Khan DA, Hamdani SDA, Iftikhar S, Malik SZ, Zaidi NUSS, Gul A, Babar MM, Ozturk M, Turkyilmaz Unal B, Gonenc T. Pharmacoinformatics approaches in the discovery of drug-like antimicrobials of plant origin. J Biomol Struct Dyn 2021; 40:7612-7628. [PMID: 33663347 DOI: 10.1080/07391102.2021.1894982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Medicinal plants have served as an important source for addressing the ailments of humans and animals alike. The emergence of advanced technologies in the field of drug discovery and development has helped in isolating various bioactive phytochemicals and developing them as drugs. Owing to their significant pharmacological benefits and minimum adverse effects, they not only serve as good candidates for therapeutics themselves but also help in the identification and development of related drug like molecules against various metabolic and infectious diseases. The ever-increasing diversity, severity and incidence of infectious diseases has resulted in an exaggerated mortality and morbidity levels. Geno-proteomic mutations in microbes, irrational prescribing of antibiotics, antimicrobial resistance and human population explosion, all call for continuous efforts to discover and develop alternated therapeutic options against the microbes. This review article describes the pharmacoinformatics tools and methods which are currently used in the discovery of bioactive phytochemicals, thus making the process more efficient and effective. The pharmacological aspects of the drug discovery and development process have also been reviewed with reference to the in silico activities. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Duaa Ahmad Khan
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Syed Damin Abbas Hamdani
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan.,Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan
| | - Sahar Iftikhar
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Sohaib Zafar Malik
- Riphah Institute of Pharmaceutical Sciences, Riphah International University, Islamabad, Pakistan
| | - Najam-Us-Sahar Sadaf Zaidi
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences & Technology, Islamabad, Pakistan
| | - Alvina Gul
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences & Technology, Islamabad, Pakistan
| | - Mustafeez Mujtaba Babar
- Shifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, Pakistan
| | - Munir Ozturk
- Botany Department and Centre for Environmental Studies, Ege University, Izmir, Turkey
| | - Bengu Turkyilmaz Unal
- Biotechnology Department, Arts & Sciences Faculty, Nigde Omer Halisdemir University, Nigde, Turkey
| | - Tuba Gonenc
- Department of Pharmacognosy, Faculty of Pharmacy, Izmir Katip Çelebi University, Izmir, Turkey
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13
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Zhang R, Li X, Zhang X, Qin H, Xiao W. Machine learning approaches for elucidating the biological effects of natural products. Nat Prod Rep 2021; 38:346-361. [PMID: 32869826 DOI: 10.1039/d0np00043d] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural products (NPs) has developed in order to manage the challenge of the discovery of bioactive NPs. In the present review, we will introduce the basic principles and protocols for using the ML approach to investigate the bioactivity of NPs, citing a series of practical examples regarding the study of anti-microbial, anti-cancer, and anti-inflammatory NPs, etc. ML algorithms manage a variety of classification and regression problems associated with bioactive NPs, from those that are linear to non-linear and from pure compounds to plant extracts. Inspired by cases reported in the literature and our own experience, a number of key points have been emphasized for reducing modeling errors, including dataset preparation and applicability domain analysis.
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Affiliation(s)
- Ruihan Zhang
- Key Laboratory of Medicinal Chemistry for Natural Resource, Ministry of Education, Yunnan Research & Development Center for Natural Products, School of Chemical Science and Technology, Yunnan University, 2 Rd Cuihubei, P. R. China.
| | - Xiaoli Li
- Key Laboratory of Medicinal Chemistry for Natural Resource, Ministry of Education, Yunnan Research & Development Center for Natural Products, School of Chemical Science and Technology, Yunnan University, 2 Rd Cuihubei, P. R. China.
| | - Xingjie Zhang
- Key Laboratory of Medicinal Chemistry for Natural Resource, Ministry of Education, Yunnan Research & Development Center for Natural Products, School of Chemical Science and Technology, Yunnan University, 2 Rd Cuihubei, P. R. China.
| | - Huayan Qin
- Key Laboratory of Medicinal Chemistry for Natural Resource, Ministry of Education, Yunnan Research & Development Center for Natural Products, School of Chemical Science and Technology, Yunnan University, 2 Rd Cuihubei, P. R. China.
| | - Weilie Xiao
- Key Laboratory of Medicinal Chemistry for Natural Resource, Ministry of Education, Yunnan Research & Development Center for Natural Products, School of Chemical Science and Technology, Yunnan University, 2 Rd Cuihubei, P. R. China.
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14
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Shen M, Chen M, Liang T, Wang S, Xue Y, Bertz R, Xie XQ, Feng Z. Pain Chemogenomics Knowledgebase (Pain-CKB) for Systems Pharmacology Target Mapping and Physiologically Based Pharmacokinetic Modeling Investigation of Opioid Drug-Drug Interactions. ACS Chem Neurosci 2020; 11:3245-3258. [PMID: 32966035 DOI: 10.1021/acschemneuro.0c00372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
More than 50 million adults in America suffer from chronic pain. Opioids are commonly prescribed for their effectiveness in relieving many types of pain. However, excessive prescribing of opioids can lead to abuse, addiction, and death. Non-steroidal anti-inflammatory drugs (NSAIDs), another major class of analgesic, also have many problematic side effects including headache, dizziness, vomiting, diarrhea, nausea, constipation, reduced appetite, and drowsiness. There is an urgent need for the understanding of molecular mechanisms that underlie drug abuse and addiction to aid in the design of new preventive or therapeutic agents for pain management. To facilitate pain related small-molecule signaling pathway studies and the prediction of potential therapeutic target(s) for the treatment of pain, we have constructed a comprehensive platform of a pain domain-specific chemogenomics knowledgebase (Pain-CKB) with integrated data mining computing tools. Our new computing platform describes the chemical molecules, genes, proteins, and signaling pathways involved in pain regulation. Pain-CKB is implemented with a friendly user interface for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, and Spider Plot. Combining these with other novel tools, we performed three case studies to systematically demonstrate how further studies can be conducted based on the data generated from Pain-CKB and its algorithms and tools. First, systems pharmacology target mapping was carried out for four FDA approved analgesics in order to identify the known target and predict off-target interactions. Subsequently, the target mapping outcomes were applied to build physiologically based pharmacokinetic (PBPK) models for acetaminophen and fentanyl to explore the drug-drug interaction (DDI) between this pair of drugs. Finally, pharmaco-analytics was conducted to explore the detailed interaction pattern of acetaminophen reactive metabolite and its hepatotoxicity target, thioredoxin reductase.
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Affiliation(s)
- Mingzhe Shen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Maozi Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Tianjian Liang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Siyi Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Ying Xue
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Richard Bertz
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, and Departments of Computational Biology and Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Zhiwei Feng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
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15
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Shen L, Shen K, Bai J, Wang J, Singla RK, Shen B. Data-driven microbiota biomarker discovery for personalized drug therapy of cardiovascular disease. Pharmacol Res 2020; 161:105225. [PMID: 33007417 DOI: 10.1016/j.phrs.2020.105225] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 02/07/2023]
Abstract
Cardiovascular disease (CVD) is the most wide-spread disorder all over the world. The personalized and precision diagnosis, treatment and prevention of CVD is still a challenge. With the developing of metagenome sequencing technologies and the paradigm shifting to data-driven discovery in life science, the computer aided microbiota biomarker discovery for CVD is becoming reality. We here summarize the data resources, knowledgebases and computational models available for CVD microbiota biomarker discovery, and review the present status of the findings about the microbiota patterns associated with the therapeutic effects on CVD. The future challenges and opportunities of the translational informatics on the personalized drug usages in CVD diagnosis, prognosis and treatment are also discussed.
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Affiliation(s)
- Li Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Ke Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Jinwei Bai
- Library of West-China Hospital, Sichuan University, Chengdu 610041, China
| | - Jiao Wang
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Rajeev K Singla
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Bairong Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
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16
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An enumeration of natural products from microbial, marine and terrestrial sources. PHYSICAL SCIENCES REVIEWS 2020. [DOI: 10.1515/psr-2018-0121] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Abstract
The discovery of a new drug is a multidisciplinary and very costly task. One of the major steps is the identification of a lead compound, i.e. a compound with a certain degree of potency and that can be chemically modified to improve its activity, metabolic properties, and pharmacokinetics profiles. Terrestrial sources (plants and fungi), microbes and marine organisms are abundant resources for the discovery of new structurally diverse and biologically active compounds. In this chapter, an attempt has been made to quantify the numbers of known published chemical structures (available in chemical databases) from natural sources. Emphasis has been laid on the number of unique compounds, the most abundant compound classes and the distribution of compounds in terrestrial and marine habitats. It was observed, from the recent investigations, that ~500,000 known natural products (NPs) exist in the literature. About 70 % of all NPs come from plants, terpenoids being the most represented compound class (except in bacteria, where amino acids, peptides, and polyketides are the most abundant compound classes). About 2,000 NPs have been co-crystallized in PDB structures.
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17
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Zhou Z, Chen B, Chen S, Lin M, Chen Y, Jin S, Chen W, Zhang Y. Applications of Network Pharmacology in Traditional Chinese Medicine Research. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2020; 2020:1646905. [PMID: 32148533 PMCID: PMC7042531 DOI: 10.1155/2020/1646905] [Citation(s) in RCA: 169] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/08/2020] [Accepted: 01/20/2020] [Indexed: 01/01/2023]
Abstract
Human diseases, especially infectious ones, have been evolving constantly. However, their treatment strategies are not developing quickly. Some diseases are caused by a variety of factors with very complex pathologies, and the use of a single drug cannot solve these problems. Traditional Chinese Medicine (TCM) medication is a unique treatment method in China. TCM formulae contain multiple herbs with multitarget, multichannel, and multilink characteristics. In recent years, with the flourishing development of network pharmacology, a new method for searching therapeutic drugs has emerged. The multitarget action in network pharmacology is consistent with the complex mechanisms of disease and drug action. Using network pharmacology to understand TCM is an emerging trend.
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Affiliation(s)
- Zhuchen Zhou
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Bing Chen
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Simiao Chen
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Minqiu Lin
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Ying Chen
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Shan Jin
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Weiyan Chen
- School of Basic Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
| | - Yuyan Zhang
- School of Life Science, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
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18
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Nguyen-Vo TH, Nguyen L, Do N, Nguyen TN, Trinh K, Cao H, Le L. Plant Metabolite Databases: From Herbal Medicines to Modern Drug Discovery. J Chem Inf Model 2020; 60:1101-1110. [PMID: 31873010 DOI: 10.1021/acs.jcim.9b00826] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Traditional herbal medicine has been an inseparable part of the traditional medical science in many countries throughout history. Nowadays, the popularity of using herbal medicines in daily life, as well as clinical practices, has gradually expanded to numerous Western countries with positive impacts and acceptance. The continuous growth of the herbal consumption market has promoted standardization and modernization of herbal-derived products with present pharmacological criteria. To store and extensively share this knowledge with the community and serve scientific research, various herbal metabolite databases have been developed with diverse focuses under the support of modern advances. The advent of these databases has contributed to accelerating research on pharmaceuticals of natural origins. In the scope of this study, we critically review 30 herbal metabolite databases, discuss different related perspectives, and provide a comparative analysis of 18 accessible noncommercial ones. We hope to provide you with fundamental information and multidimensional perspectives from herbal medicines to modern drug discovery.
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Affiliation(s)
- Thanh-Hoang Nguyen-Vo
- School of Mathematics and Statistics, Victoria University of Wellington, Wellington 6140, New Zealand
| | - Loc Nguyen
- Computational Biology Center, International University-VNU HCMC, Ho Chi Minh City 700000, Vietnam
| | - Nguyet Do
- Computational Biology Center, International University-VNU HCMC, Ho Chi Minh City 700000, Vietnam
| | - Thien-Ngan Nguyen
- Computational Biology Center, International University-VNU HCMC, Ho Chi Minh City 700000, Vietnam
| | - Khang Trinh
- Computational Biology Center, International University-VNU HCMC, Ho Chi Minh City 700000, Vietnam
| | - Hung Cao
- The Henry Samueli School of Engineering, University of California at Irvine, Irvine, California 92697, United States
| | - Ly Le
- Computational Biology Center, International University-VNU HCMC, Ho Chi Minh City 700000, Vietnam.,Vingroup Big Data Institute, Ha Noi 100000, Vietnam
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19
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Zhang W, Huai Y, Miao Z, Qian A, Wang Y. Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery. Front Pharmacol 2019; 10:743. [PMID: 31379563 PMCID: PMC6657703 DOI: 10.3389/fphar.2019.00743] [Citation(s) in RCA: 100] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 06/07/2019] [Indexed: 01/01/2023] Open
Abstract
As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, traditional Chinese medicine (TCM) has attracted global attention in the life science field. TCM provides extensive natural resources for medicinal compounds, and these resources are generally regarded as effective and safe for use in drug discovery. However, owing to the complexity of compounds and their related multiple targets of TCM, it remains difficult to dissect the mechanisms of action of herbal medicines at a holistic level. To solve the issue, in the review, we proposed a novel approach of systems pharmacology to identify the bioactive compounds, predict their related targets, and illustrate the molecular mechanisms of action of TCM. With a predominant focus on the mechanisms of actions of TCM, we also highlighted the application of the systems pharmacology approach for the prediction of drug combination and dynamic analysis, the synergistic effects of TCMs, formula dissection, and theory analysis. In summary, the systems pharmacology method contributes to understand the complex interactions among biological systems, drugs, and complex diseases from a network perspective. Consequently, systems pharmacology provides a novel approach to promote drug discovery in a precise manner and a systems level, thus facilitating the modernization of TCM.
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Affiliation(s)
- Wenjuan Zhang
- Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- Research Center for Special Medicine and Health Systems Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
| | - Ying Huai
- Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- Research Center for Special Medicine and Health Systems Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
| | - Zhiping Miao
- Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- Research Center for Special Medicine and Health Systems Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
| | - Airong Qian
- Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- Research Center for Special Medicine and Health Systems Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
- NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences, Northwestern Polytechnical University, Xi’an, China
| | - Yonghua Wang
- Lab of Systems Pharmacology, College of Life Sciences, Northwest University, Xi’an, China
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20
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Chadar D, Lande DN, Gejji SP, Nikalje MD, Chakravarty D, Salunke-Gawali S. Trimerization of Vitamin K3: Molecular structure and density functional theoretic investigations. J Mol Struct 2019. [DOI: 10.1016/j.molstruc.2019.03.082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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21
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22
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Li B, Ma C, Zhao X, Hu Z, Du T, Xu X, Wang Z, Lin J. YaTCM: Yet another Traditional Chinese Medicine Database for Drug Discovery. Comput Struct Biotechnol J 2018; 16:600-610. [PMID: 30546860 PMCID: PMC6280608 DOI: 10.1016/j.csbj.2018.11.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 11/04/2018] [Accepted: 11/06/2018] [Indexed: 12/13/2022] Open
Abstract
Traditional Chinese Medicine (TCM) has a long history of widespread clinical applications, especially in East Asia, and is becoming frequently used in Western countries. However, owing to extreme complicacy in both chemical ingredients and mechanism of action, a deep understanding of TCM is still difficult. To accelerate the modernization and popularization of TCM, a single comprehensive database is required, containing a wealth of TCM-related information and equipped with complete analytical tools. Here we present YaTCM (Yet another Traditional Chinese Medicine database), a free web-based toolkit, which provides comprehensive TCM information and is furnished with analysis tools. YaTCM allows a user to (1) identify the potential ingredients that are crucial to TCM herbs through similarity search and substructure search, (2) investigate the mechanism of action for TCM or prescription through pathway analysis and network pharmacology analysis, (3) predict potential targets for TCM molecules by multi-voting chemical similarity ensemble approach, and (4) explore functionally similar herb pairs. All these functions can lead to one systematic network for visualization of TCM recipes, herbs, ingredients, definite or putative protein targets, pathways, and diseases. This web service would help in uncovering the mechanism of action of TCM, revealing the essence of TCM theory and then promoting the drug discovery process. YaTCM is freely available at http://cadd.pharmacy.nankai.edu.cn/yatcm/home.
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Affiliation(s)
- Baiqing Li
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China
| | - Chunfeng Ma
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China.,Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine, Tianjin 300457, China
| | - Xiaoyong Zhao
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China
| | - Zhigang Hu
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China
| | - Tengfei Du
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China
| | - Xuanming Xu
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China
| | - Zhonghua Wang
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West 7th Avenue, Tianjin Airport Economic Area, Tianjin 300308, China
| | - Jianping Lin
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, China.,Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, 32 West 7th Avenue, Tianjin Airport Economic Area, Tianjin 300308, China.,Platform of Pharmaceutical Intelligence, Tianjin International Joint Academy of Biomedicine, Tianjin 300457, China
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23
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Mohanraj K, Karthikeyan BS, Vivek-Ananth RP, Chand RPB, Aparna SR, Mangalapandi P, Samal A. IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics. Sci Rep 2018. [PMID: 29531263 PMCID: PMC5847565 DOI: 10.1038/s41598-018-22631-z] [Citation(s) in RCA: 226] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Phytochemicals of medicinal plants encompass a diverse chemical space for drug discovery. India is rich with a flora of indigenous medicinal plants that have been used for centuries in traditional Indian medicine to treat human maladies. A comprehensive online database on the phytochemistry of Indian medicinal plants will enable computational approaches towards natural product based drug discovery. In this direction, we present, IMPPAT, a manually curated database of 1742 Indian Medicinal Plants, 9596 Phytochemicals, And 1124 Therapeutic uses spanning 27074 plant-phytochemical associations and 11514 plant-therapeutic associations. Notably, the curation effort led to a non-redundant in silico library of 9596 phytochemicals with standard chemical identifiers and structure information. Using cheminformatic approaches, we have computed the physicochemical, ADMET (absorption, distribution, metabolism, excretion, toxicity) and drug-likeliness properties of the IMPPAT phytochemicals. We show that the stereochemical complexity and shape complexity of IMPPAT phytochemicals differ from libraries of commercial compounds or diversity-oriented synthesis compounds while being similar to other libraries of natural products. Within IMPPAT, we have filtered a subset of 960 potential druggable phytochemicals, of which majority have no significant similarity to existing FDA approved drugs, and thus, rendering them as good candidates for prospective drugs. IMPPAT database is openly accessible at: https://cb.imsc.res.in/imppat.
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Affiliation(s)
- Karthikeyan Mohanraj
- The Institute of Mathematical Sciences (IMSc), Homi Bhabha National Institute (HBNI), Chennai, 600113, India
| | | | - R P Vivek-Ananth
- The Institute of Mathematical Sciences (IMSc), Homi Bhabha National Institute (HBNI), Chennai, 600113, India
| | - R P Bharath Chand
- The Institute of Mathematical Sciences (IMSc), Homi Bhabha National Institute (HBNI), Chennai, 600113, India
| | - S R Aparna
- Stella Maris College, Chennai, 600086, India
| | - Pattulingam Mangalapandi
- The Institute of Mathematical Sciences (IMSc), Homi Bhabha National Institute (HBNI), Chennai, 600113, India
| | - Areejit Samal
- The Institute of Mathematical Sciences (IMSc), Homi Bhabha National Institute (HBNI), Chennai, 600113, India.
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24
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Liu Z, Du J, Yan X, Zhong J, Cui L, Lin J, Zeng L, Ding P, Chen P, Zhou X, Zhou H, Gu Q, Xu J. TCMAnalyzer: A Chemo- and Bioinformatics Web Service for Analyzing Traditional Chinese Medicine. J Chem Inf Model 2018; 58:550-555. [PMID: 29420025 DOI: 10.1021/acs.jcim.7b00549] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Traditional Chinese medicine (TCM) has been widely used and proven effective in long term clinical practice. However, the molecular mechanism of action for many TCMs remains unclear due to the complexity of many ingredients and their interactions with biological receptors. This is one of the major roadblocks in TCM modernization. In order to solve this problem, we have developed TCMAnalyzer, which is a free web-based toolkit allowing a user to (1) identify the potential compounds that are responsible for the bioactivities for a TCM herb through scaffold-activity relation searches using structural search techniques, (2) investigate the molecular mechanism of action for a TCM herb at the systemic level, and (3) explore the potentially targeted bioactive herbs. The toolkit can result in TCM networks that demonstrate the relations among natural product molecules (small molecular ligands), putative protein targets, pathways, and diseases. These networks are graphically depicted to reveal the mechanism of actions for a TCM herb or to identify new molecular scaffolds for new chemotherapies. TCMAnalyzer is freely available at http://www.rcdd.org.cn/tcmanalyzer .
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Affiliation(s)
- Zhihong Liu
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Jiewen Du
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Xin Yan
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Jiali Zhong
- School of Chinese Materia Medica , Guangzhou University of Chinese Medicine , Guangzhou 510006 , China
| | - Lu Cui
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Jinyuan Lin
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Lizhu Zeng
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Peng Ding
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Pin Chen
- National Supercomputer Center in Guangzhou , Sun Yat-sen University , Guangzhou 510006 , China
| | - Xinxin Zhou
- School of Chinese Materia Medica , Guangzhou University of Chinese Medicine , Guangzhou 510006 , China
| | - Huihao Zhou
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Qiong Gu
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
| | - Jun Xu
- Research Center for Drug Discovery, School of Pharmaceutical Sciences , Sun Yat-sen University , 132 East Circle at University City , Guangzhou 510006 , China
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How Can Synergism of Traditional Medicines Benefit from Network Pharmacology? Molecules 2017; 22:molecules22071135. [PMID: 28686181 PMCID: PMC6152294 DOI: 10.3390/molecules22071135] [Citation(s) in RCA: 272] [Impact Index Per Article: 38.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 07/04/2017] [Accepted: 07/05/2017] [Indexed: 12/14/2022] Open
Abstract
Many prescriptions of traditional medicines (TMs), whose efficacy has been tested in clinical practice, have great therapeutic value and represent an excellent resource for drug discovery. Research into single compounds of TMs, such as artemisinin from Artemisia annua L., has achieved great success; however, it has become evident that a TM prescription (which frequently contains various herbs or other components) has a synergistic effect in effecting a cure or reducing toxicity. Network pharmacology targets biological networks and analyzes the links among drugs, targets, and diseases in those networks. Comprehensive, systematic research into network pharmacology is consistent with the perspective of holisticity, which is a main characteristic of many TMs. By means of network pharmacology, research has demonstrated that many a TM show a synergistic effect by acting at different levels on multiple targets and pathways. This approach effectively bridges the gap between modern medicine and TM, and it greatly facilitates studies into the synergistic actions of TMs. There are different kinds of synergistic effects with TMs, such as synergy among herbs, effective parts, and pure compounds; however, for various reasons, new drug discovery should at present focus on synergy among pure compounds.
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26
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Li W, Yuan G, Pan Y, Wang C, Chen H. Network Pharmacology Studies on the Bioactive Compounds and Action Mechanisms of Natural Products for the Treatment of Diabetes Mellitus: A Review. Front Pharmacol 2017; 8:74. [PMID: 28280467 PMCID: PMC5322182 DOI: 10.3389/fphar.2017.00074] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 02/06/2017] [Indexed: 12/19/2022] Open
Abstract
Diabetes mellitus (DM) is a kind of chronic and metabolic disease, which can cause a number of diseases and severe complications. Network pharmacology approach is introduced to study DM, which can combine the drugs, target proteins and disease and form drug-target-disease networks. Network pharmacology has been widely used in the studies of the bioactive compounds and action mechanisms of natural products for the treatment of DM due to the multi-components, multi-targets, and lower side effects. This review provides a balanced and comprehensive summary on network pharmacology from current studies, highlighting different bioactive constituents, related databases and applications in the investigations on the treatment of DM especially type 2. The mechanisms related to type 2 DM, including α-amylase and α-glucosidase inhibitory, targeting β cell dysfunction, AMPK signal pathway and PI3K/Akt signal pathway are summarized and critiqued. It suggests that the network pharmacology approach cannot only provide a new research paradigm for natural products, but also improve the current antidiabetic drug discovery strategies. Furthermore, we put forward the perspectives on the reasonable applications of network pharmacology for the therapy of DM and related drug discovery.
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Affiliation(s)
| | | | | | | | - Haixia Chen
- Tianjin Key Laboratory for Modern Drug Delivery & High-Efficiency, School of Pharmaceutical Science and Technology, Tianjin UniversityTianjin, China
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28
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Aalikhani Pour M, Sardari S, Eslamifar A, Rezvani M, Azhar A, Nazari M. Evaluating the anticoagulant effect of medicinal plants in vitro by cheminformatics methods. J Herb Med 2016. [DOI: 10.1016/j.hermed.2016.05.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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29
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Poornima P, Kumar JD, Zhao Q, Blunder M, Efferth T. Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature. Pharmacol Res 2016; 111:290-302. [PMID: 27329331 DOI: 10.1016/j.phrs.2016.06.018] [Citation(s) in RCA: 127] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2015] [Revised: 06/16/2016] [Accepted: 06/17/2016] [Indexed: 12/14/2022]
Abstract
Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer.
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Affiliation(s)
- Paramasivan Poornima
- School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2DG, United Kingdom
| | - Jothi Dinesh Kumar
- Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3BX, United Kingdom
| | - Qiaoli Zhao
- Department of Pharmaceutical Biology, Johannes Gutenberg University, Mainz, Germany
| | - Martina Blunder
- Department of Neuroscience, Biomedical Center, Uppsala University, Uppsala, Sweden and Brain Institute, Federal University of Rio Grande do Norte, UFRN, Natal, Brazil
| | - Thomas Efferth
- Department of Pharmaceutical Biology, Johannes Gutenberg University, Mainz, Germany.
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Pharmacodynamics and potential synergistic effects of Mai-Luo-Ning injection on cardiovascular protection, based on molecular docking. Chin J Nat Med 2015; 13:815-822. [PMID: 26614456 DOI: 10.1016/s1875-5364(15)30085-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Indexed: 11/20/2022]
Abstract
As a computer-assisted approach, molecular docking has been universally applied in drug research and development and plays an important role in the investigation and evaluation of herbal medicines. Herein, the method was used to estimate the pharmacodynamics of Mai-Luo-Ning injection, a traditional Chinese compound herbal prescription. Through investigating the interactions between several important proteins in cardiovascular system and characteristic components of the formula, its effect on cardiovascular protection was evaluated. Results showed the differences in the interactions between each component and the selected target proteins and revealed the possible mechanisms for synergistic effects of various characteristic components on cardiovascular protection. The study provided scientific evidence supporting the mechanistic study of the interactions among multi-components and targets, offering a general approach to investigating the pharmacodynamics of complicated materials in compound herbal prescriptions.
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31
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Warr WA. Many InChIs and quite some feat. J Comput Aided Mol Des 2015; 29:681-94. [PMID: 26081259 DOI: 10.1007/s10822-015-9854-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 06/10/2015] [Indexed: 12/14/2022]
Affiliation(s)
- Wendy A Warr
- Wendy Warr & Associates, Holmes Chapel, Crewe, Cheshire, CW4 7HZ, UK,
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32
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Xie T, Song S, Li S, Ouyang L, Xia L, Huang J. Review of natural product databases. Cell Prolif 2015; 48:398-404. [PMID: 26009974 DOI: 10.1111/cpr.12190] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 03/14/2015] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES Many natural products have pharmacological or biological activities that can be of therapeutic benefit in treating diseases, and are also an important source of inspiration for development of potential novel drugs. The past few decades have witnessed extensive study of natural products for their promising prospects in application of medicinal chemistry, molecular biology and pharmaceutical sciences. MATERIALS AND METHODS Natural product databases have provided systematic collection of information concerning natural products and their derivatives, including structure, source and mechanisms of action, which significantly support modern drug discovery. RESULTS Currently, a considerable number of natural product databases, such as TCM Database@Taiwan, TCMID, CEMTDD, SuperToxic and SuperNatural, have been developed, providing data such as integrated medicinal herbs, ingredients, 2D/3D structures of the compounds, related target proteins, relevant diseases, and metabolic toxicity and more. CONCLUSIONS We focus on an analytical overview of current natural product databases, and further discuss the good, bad or imperfection of current ones, in the hope of better integrating existing relevant outcomes, thus providing new routes for future drug discovery.
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Affiliation(s)
- Tao Xie
- State Key Laboratory of Biotherapy/Collaborative Innovation Center of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Sicheng Song
- State Key Laboratory of Biotherapy/Collaborative Innovation Center of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Sijia Li
- State Key Laboratory of Stomatology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - Liang Ouyang
- State Key Laboratory of Biotherapy/Collaborative Innovation Center of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lin Xia
- Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Jian Huang
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, China
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Ru J, Li P, Wang J, Zhou W, Li B, Huang C, Li P, Guo Z, Tao W, Yang Y, Xu X, Li Y, Wang Y, Yang L. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014; 6:13. [PMID: 24735618 PMCID: PMC4001360 DOI: 10.1186/1758-2946-6-13] [Citation(s) in RCA: 2608] [Impact Index Per Article: 260.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2014] [Accepted: 04/11/2014] [Indexed: 02/06/2023] Open
Abstract
Background Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. Description The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski’s rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. Conclusions The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.
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Affiliation(s)
- Jinlong Ru
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peng Li
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jinan Wang
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wei Zhou
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Bohui Li
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chao Huang
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Pidong Li
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zihu Guo
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weiyang Tao
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yinfeng Yang
- School of Chemical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Xue Xu
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yan Li
- School of Chemical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Yonghua Wang
- Center for Bioinformatics, College of Life Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ling Yang
- Laboratory of Pharmaceutical Resource Discovery, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
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Liu H, Wang L, Lv M, Pei R, Li P, Pei Z, Wang Y, Su W, Xie XQ. AlzPlatform: an Alzheimer's disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research. J Chem Inf Model 2014; 54:1050-60. [PMID: 24597646 PMCID: PMC4010297 DOI: 10.1021/ci500004h] [Citation(s) in RCA: 160] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
![]()
Alzheimer’s
disease (AD) is one of the most complicated progressive neurodegeneration
diseases that involve many genes, proteins, and their complex interactions.
No effective medicines or treatments are available yet to stop or
reverse the progression of the disease due to its polygenic nature.
To facilitate discovery of new AD drugs and better understand the
AD neurosignaling pathways involved, we have constructed an Alzheimer’s
disease domain-specific chemogenomics knowledgebase, AlzPlatform (www.cbligand.org/AD/) with cloud computing and sourcing
functions. AlzPlatform is implemented with powerful computational
algorithms, including our established TargetHunter, HTDocking, and
BBB Predictor for target identification and polypharmacology analysis
for AD research. The platform has assembled various AD-related chemogenomics
data records, including 928 genes and 320 proteins related to AD,
194 AD drugs approved or in clinical trials, and 405 188 chemicals
associated with 1 023 137 records of reported bioactivities
from 38 284 corresponding bioassays and 10 050 references.
Furthermore, we have demonstrated the application of the AlzPlatform
in three case studies for identification of multitargets and polypharmacology
analysis of FDA-approved drugs and also for screening and prediction
of new AD active small chemical molecules and potential novel AD drug
targets by our established TargetHunter and/or HTDocking programs.
The predictions were confirmed by reported bioactivity data and our
in vitro experimental validation. Overall, AlzPlatform will enrich
our knowledge for AD target identification, drug discovery, and polypharmacology
analyses and, also, facilitate the chemogenomics data sharing and
information exchange/communications in aid of new anti-AD drug discovery
and development.
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Affiliation(s)
- Haibin Liu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; Drug Discovery Institute; University of Pittsburgh , Pittsburgh, Pennsylvania 15260, United States
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Shu WM, Ma JR, Yang Y, Wu AX. An Efficient Synthesis of Novel Fused Cycloheptatrienes through Mn(II)-Mediated Formal Intermolecular [2 + 2 + 2 + 1] Cycloaddition. Org Lett 2014; 16:1286-9. [DOI: 10.1021/ol500202q] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Wen-Ming Shu
- Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University Hubei, Wuhan 430079, P. R. China
| | - Jun-Rui Ma
- Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University Hubei, Wuhan 430079, P. R. China
| | - Yan Yang
- Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University Hubei, Wuhan 430079, P. R. China
| | - An-Xin Wu
- Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University Hubei, Wuhan 430079, P. R. China
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Lagunin AA, Goel RK, Gawande DY, Pahwa P, Gloriozova TA, Dmitriev AV, Ivanov SM, Rudik AV, Konova VI, Pogodin PV, Druzhilovsky DS, Poroikov VV. Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review. Nat Prod Rep 2014; 31:1585-611. [DOI: 10.1039/c4np00068d] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
An overview of databases andin silicotools for discovery of the hidden therapeutic potential of medicinal plants.
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Affiliation(s)
- Alexey A. Lagunin
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
- Russian National Research Medical University
- Medico-Biologic Faculty
- Moscow, Russia
| | - Rajesh K. Goel
- Department of Pharmaceutical Sciences and Drug Research
- Punjabi University
- Patiala-147002, India
| | - Dinesh Y. Gawande
- Department of Pharmaceutical Sciences and Drug Research
- Punjabi University
- Patiala-147002, India
| | - Priynka Pahwa
- Department of Pharmaceutical Sciences and Drug Research
- Punjabi University
- Patiala-147002, India
| | | | | | - Sergey M. Ivanov
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
| | - Anastassia V. Rudik
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
| | - Varvara I. Konova
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
| | - Pavel V. Pogodin
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
- Russian National Research Medical University
- Medico-Biologic Faculty
- Moscow, Russia
| | | | - Vladimir V. Poroikov
- Orekhovich Institute of Biomedical Chemistry of Rus. Acad. Med. Sci
- Moscow, Russia
- Russian National Research Medical University
- Medico-Biologic Faculty
- Moscow, Russia
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