FOLLOWUS
Ayurveda and
in silico Approach: A Challenging Proficient Confluence for Better Development of Effective Traditional Medicine Spotlighting Network Pharmacology- Chinese Journal of Integrative Medicine Vol. 29, Issue 5, Pages: 470-480(2023)
- Affiliations：
1.Department of Balroga, Shri NPA Govt. Ayurveda College, Raipur (492010), Chhattisgarh, India
2.Ayurinformatics Lab, Department of Kaumarabhritya, All India Institute of Ayurveda, Sarita Vihar, New Delhi (110076), India
3.Cellular and Molecular Neurobiology Unit, Indian Institute of Technology, Jodhpur(342037), Rajasthan, India
4.Department of Biotechnology, National Institute of Technology, Raipur (492010), Chhattisgarh, India
- Author bio：
Dr. Awanish Kumar, E-mail: drawanishkr@gmail.com
- Funds：
DOI：10.1007/s11655-022-3584-x
CLC：Published：2023-05，
Published Online：12 September 2022，
Accepted：02 June 2022
Scan for full text
Rashmi Sahu, Prashant Kumar Gupta, Amit Mishra, et al. Ayurveda and
in silico Approach: A Challenging Proficient Confluence for Better Development of Effective Traditional Medicine Spotlighting Network Pharmacology. [J]. Chinese Journal of Integrative Medicine 29(5):470-480(2023)Rashmi Sahu, Prashant Kumar Gupta, Amit Mishra, et al. Ayurveda and
in silico Approach: A Challenging Proficient Confluence for Better Development of Effective Traditional Medicine Spotlighting Network Pharmacology. [J]. Chinese Journal of Integrative Medicine 29(5):470-480(2023) DOI： 10.1007/s11655-022-3584-x.
摘要
Abstract
Coalescence of traditional medicine Ayurveda and
in silico
technology is a rigor for supplementary development of future-ready effective traditional medicine. Ayurveda is a popular traditional medicine in South Asia
emanating worldwide for the treatment of metabolic disorders and chronic illness. Techniques of
in silico
biology are not much explored for the investigation of a variety of bioactive phytochemicals of Ayurvedic herbs. Drug repurposing
reverse pharmacology
and polypharmacology in Ayurveda are areas
in silico
explorations that are needed to understand the rich repertoire of herbs
minerals
herbo-minerals
and assorted Ayurvedic formulations. This review emphasizes exploring the concept of Ayurveda with
in silico
approaches and the need for Ayurinformatics studies. It also provides an overview of
in silico
studies done on phytoconstituents of some important Ayurvedic plants
the utility of
in silico
studies in Ayurvedic phytoconstituents/formulations
limitations/challenges
and prospects of
in silico
studies in Ayurveda. This article discusses the convergence of
in silico
work
especially in the least explored field of Ayurveda. The focused coalesce of these two domains could present a predictive combinatorial platform to enhance translational research magnitude. In nutshell
it could provide new insight into an Ayurvedic drug discovery involving an
in silico
approach that could not only alleviate the process of traditional medicine research but also enhance its effectiveness in addressing health care.
关键词
Keywords
Ayurvedain silico approachconfluencechallengeeffective therapeutics
references
Park JJ, Beckman-Harned S, Cho G, et al. The current acceptance, accessibility and recognition of Chinese and Ayurvedic medicine in the United States in the public, governmental, and industrial sectors. Chin J Integr Med 2012;18:405-408.
Ekins S, Mestres J, Testa B. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. Br J Pharmacol 2007;152:9-20.
Sliwoski G, Kothiwale S, Meiler J, et al. Computational methods in drug discovery. Pharmacol Rev 2013;66:334-395.
Singla RK, Bhat GV, Gonzalez-Diaz H. Thematic issue:from phytochemistry to medicinal chemistry: isolation, semisynthesis, evaluation and computational studies. Curr Top Med Chem 2014;14:979-980.
Eduardo H, Bechelane M, Letícia CA, et al. Structure-based virtual screening: from classical to artificial intelligence. Front Chem 2022;8:343.
Bruno A, Costantino G, Sartori L, et al. The in silico drug discovery toolbox: applications in lead discovery and optimization. Curr Med Chem 2019;26:3838-3873.
Dearden JC. In silico prediction of drug toxicity. J Comput Aid Mol Des 2003;17:119-127.
Newman DJ, Cragg GM, Snader KM. Natural products as sources of new drugs over the period 1981—2002. J Nat Prod 2003;66:1022-1037.
Shankar A, Dubey A, Saini D, et al. Role of complementary and alternative medicine in prevention and treatment of COVID-19:an overhyped hope. Chin J Integr Med 2020;26:565-567.
Chauhan A, Semwal DK, Mishra SP, et al. Ayurvedic research and methodology: present status and future strategies. Ayu 2015;36:364-369.
Patwardhan K, Gehlot S, Singh G, et al. Ayurveda education in India: how well are the graduates exposed to basic clinical skills? Evid Based Complement Alternat Med 2011;2011:197391.
Patwardhan K, Gehlot S, Singh G, et al. Graduate level Ayurveda education: relevance of curriculum and teaching methodology. J Ayurveda 2009;3:73-82.
Patwardhan K, Gehlot S, Singh G, et al. Global challenges of graduate level Ayurvedic education: a survey. Int J Ayurveda Res 2010;1:49-54.
Patwardhan B, Chaguturu R, eds. Innovative approaches in drug discovery: ethnopharmacology, systems biology and holistic targeting. Cambridge: Academic Press, Elsevier;2016.
Singh B, Kaur H. In silico documentation of medicinal plants in lacchiwala range, dehradun forest division, Uttarakhand(India). J Phytopharmacol 2018;7:92-102.
Mohanraj K, Karthikeyan BS, Vivek-Ananth RP, et al. IMPPAT: a curated database of Indian Medicinal Plants, Phytochemistry and Therapeutics. Sci Rep 2018;8:4329.
Pandey K, Gupta RK. Need of globalisation in Ayurveda:boom and bust. J Biol Sci Opin 2015;3:91-93.
Takeshige K, Baba M, Tsuboi S, et al. Autophagy in yeast demonstrated with proteinase-deficient mutants and conditions for its induction. J Cell Biol 1992;119:301-311.
Harish Chandra Vd, Kushwaha S. Acharya Charaks' Charak Samhita, Kiyantah Shirashiya Adhyaya17/114. Sutrasthan. Varanasi, India: Chaukhambha Surbharati Publication;2011.
Paulke A, Kremer C, Wunder C, et al. Argyreian Nervosa(Burm. f.): receptor profiling of lysergic acid amide and other potential psychedelic LSD-like compounds by computational and binding assay approaches. J Ethnopharmacol 2013;148:492-497.
Ramasamy S, Chin SP, Sukumaran SD, et al. In silico and in vitro analysis of bacoside A aglycones and its derivatives as the constituents responsible for the cognitive effects of Bacopa monnieri. PLoS One 2015;10:e0126565.
Sharanya CS, Arun KG, Vijaytha V. Designing of enzyme inhibitors based on active site specificity: lessons from methyl gallate and its lipoxygenase inhibitory profile. J Recept Signal Transduct Res 2018;38:256-265.
Mohan S, Syam S, Abdelwahab SI, et al. An anti-inflammatory molecular mechanism of action of α-mangostin, the major xanthone from the pericarp of Garcinia mangostana: an in silico, in vitro and in vivo approach. Food Funct 2018;9:3860-3871.
Arulmozhi P, Vijayakumar S, Praseetha PK, et al. Extraction methods and computational approaches for evaluation of antimicrobial compounds from Capparis zeylanica L. Anal Biochem 2019;572:33-44.
Fauzi FM, John CM, Karunanidhi A, et al. Understanding the mode-of-action of Cassia auriculata via in silico and in vivo studies towards validating it as a long term therapy for type Ⅱ diabetes. J Ethnopharmacol 2017;197:61-72.
Margret AA, Begum TN, Parthasarathy S, et al. A strategy to employ Clitoria ternatea as a prospective brain drug confronting monoamine oxidase (MAO) against neurodegenerative diseases and depression. Nat Prod Bioprospect 2015;5:293-306.
Sheela DL, Nazeem PA, Narayanankutty A, et al. Coconut phytocompounds inhibits polyol pathway enzymes: implication in prevention of microvascular diabetic complications. Prostaglandins Leukot Essent Fatty Acids 2017;127:20-24.
Ikhlas S, Ahmad M. Binding studies of guggulsterone-E to calf thymus DNA by multi-spectroscopic, calorimetric and molecular docking studies. Spectrochim Acta A Mol Biomol Spectrosc 2018;190:402-408.
Kalachaveedu M, Raghavan D, Telapolu S, et al. Phytoestrogenic effect of Inula racemosa Hook f—a cardioprotective root drug in traditionalmedicine. J Ethnopharmacol 2018;210:408-416.
Srivastava A, Karthick T, Joshi BD, et al. Spectroscopic (far or terahertz, mid-infrared and Raman) investigation, thermal analysis and biological activity of piplartine. Spectrochim Acta A Mol Biomol Spectrosc 2017;184:368-381.
Tomy MJ, Sharanya CS, Dileep KV, et al. Derivatives form better lipoxygenase inhibitors than piperine: in vitro and in silico study. Chem Biol Drug Des 2015;85:715-721.
Tanabe G, Xie W, Balakishan G, et al. Hydrophobic substituents increase the potency of salacinol, a potent α-glucosidase inhibitor from Ayurvedic traditional medicine"Salacia". Bioorg Med Chem 2016;24:3705-3715.
Ahmad F, Misra L, Gupta VK, et al. Synergistic effect of(+)-pinitol from Saraca asoca with β-lactam antibiotics and studies on the in silico possible mechanism. J Asian Nat Prod Res 2016;18:172-183.
Adhami HR, Linder T, Kaehlig H, et al. Catecholalkenyls from Semecarpus anacardium: acetylcholinesterase inhibition and binding mode predictions. J Ethnopharmacol 2012;139:142-148.
Sudeep HV, Gouthamchandra K, Venkatesh BJ, et al. Viwithan, a standardized Withania somnifera root extract induces apoptosis in murine melanoma cells. Pharmacogn Mag 2018;13(Suppl 4):S801-S806.
Saggam A, Tillu G, Dixit S, et al. Withania somnifera(L.) Dunal: a potential therapeutic adjuvant in cancer. J Ethnopharmacol 2020;255:112759.
Chandran U, Patwardhan B. Network ethnopharmacological evaluation of the immunomodulatory activity of Withania somnifera. J Ethnopharmacol 2017;197:250-256.
Grover A, Shandilya A, Punetha A, et al. Inhibition of the NEMO/IKKβ association complex formation, a novel mechanism associated with the NF-κB activation suppression by Withania somnifera's key metabolite withaferin A. BMC Genomics 2010;11(Suppl4):S25.
Chandran U, Mehendale N, Tillu G, et al. Network pharmacology of Ayurveda formulation Triphala with special reference to anti-cancer property. Comb Chem High Throughput Screen 2015;18:846-854.
Peterson CT, Denniston K, Chopra D. Therapeutic use of Triphala in Ayurvedic medicine. J Alternat Complement Med 2017;23:607-614.
Baliga MS, Meera S, Shivashankara AR, eds. Chapter 16: The health benefits of Indian traditional Ayurvedic Rasayana (anti-aging) drugs: a review. In: Watson RR, ed. Foods and dietary supplements in the prevention and treatment of disease in older adults. Cambridge: Academic Press;2015:151-161.
Zhao Y, Wang M, Tsering J, et al. An integrated study on the antitumor effect and mechanism of Triphala against gynecological cancers based on network pharmacological prediction and in vitro experimental validation. Integr Cancer Ther 2018;17:894-901.
Tsering J, Hu X. Triphala suppresses growth and migration of human gastric carcinoma cells in vitro and in a zebra fish xenograft model. Biomed Res Int 2018;2018:7046927.
Babu D, Prema G, Sai KB, et al. In vitro and in vivo protective action of ethanolic extract of Triphala on LDL against glycation-oxidation. Afr J Pharm Pharmacol 2014;8:758-764.
Kuchewar V. Efficacy and safety study of Triphala in patients of dyslipidemia: a pilot project. Int J Res Ayurveda Pharm 2017;8:177-180.
Wang WJ, Liu TL, Yang LD, et al. Study on the multi-targets mechanism of Triphala on cardio-cerebralvascular diseases based on network pharmacology. Biomed Pharmacother 2019;116:108994.
Kalaiselvan S, Rasool MK. The anti-inflammatory effect of Triphala in arthritic-induced rats. Pharm Biol 2015;53:51-60.
Sato VH, Sungthong B, Nuamnaichati N, et al. In vivo and in vitro evidence for the anti hyperuricemic, anti-inflammatory and antioxidant effects of a traditional Ayurvedic medicine, Triphala. Nat Prod Commun 2017;12:1635-1638.
Singh R. Asparagus racemosus: a review on its phytochemical and therapeutic potential. Nat Prod Res 2016;30:1896-1908.
Sharma R, Jaitak V. Asparagus racemosus (Shatavari) targeting estrogen receptor α: —an in-vitro and in-silico mechanistic study. Nat Prod Res 2020;34:1571-1574.
Govindarajan R, Vijayakumar M, Pushpangadan P. Antioxidant approach to disease management and the role of "Rasayana"herbs of Ayurveda. J Ethnopharmacol 2005;99:165-178.
Mallick MN, Khan W, Parveen R, et al. Exploring the cytotoxic potential of triterpenoids-enriched fraction of Bacopa monnieri by implementing in vitro, in vivo, and in silico approaches. Pharmacogn Mag 2017;13(Suppl 3):S595-S606.
Poovathinal SA, Anitha A, Puliyappatta P, et al. In silico target identification of nootropic bioactive compounds from Ayurvedic herbs. Int J Ayurveda Pharm Res 2017;5:55-61.
Manap ASA, Vijayabalan S, Madhvan P, et al. Bacopa monnieri, a neuroprotective lead in Alzheimer disease: a review on its properties, mechanisms of action, and preclinical and clinical studies. Drug Target Insights 2019;13:1177392819866412.
Kumar N, Abichandani LG, Thawani V, et al. Efficacy of standardized extract of Bacopa monnieri (Bacognize®) on cognitive functions of medical students: a six-week, randomized placebo-controlled trial. Evid Based Complement Alternat Med 2016;2016:4103423.
Prasad S, Aggarwal BB. Turmeric, the golden spice: from traditional medicine to modern medicine. In: Benzie IFF, Wachtel-Galor S, eds. Herbal medicine: biomolecular and clinical aspects. 2nd ed. Boca Raton: CRC Press/Taylor and Francis;2011.
Chowdhury A, Chy MNU, Paul A. In silico molecular docking analysis of isolated compounds of Curcuma longa L against 3 receptors of type 2 diabetes. Conference: Poster Presentation; 2019. Organized by Global Network of Bangladeshi Biotechnologists.
Olatunde A, Luka CD, Tijjani H, et al. Anti-diabetic activity of aqueousextract of Curcuma longa (Linn) rhizome in normal and alloxan-induced diabetic rats. Researcher 2014;6:58-65.
Lekshmi PC, Arimboor R, Nisha VM, et al. In vitro antidiabetic and inhibitory potential of turmeric (Curcuma longa L) rhizome against cellular and LDL oxidation and angiotensin converting enzyme. J Food Sci Technol 2014;51:3910-3917.
Sharma V, Agrawal RC. Glycyrrhiza glabra—a plant for the future. Mintage J Pharm Med Sci 2013;2:15-20.
Hejazi II, Khanam R, Mehdi SH, et al. New insights into the antioxidant and apoptotic potential of Glycyrrhiza glabra L.during hydrogen peroxide mediated oxidative stress: an in vitro and in silico evaluation. Biomed Pharmacother 2017;94:265-279.
Pattanayak P, Behera P, Das D, et al. Ocimum sanctum Linn. a reservoir plant for therapeutic applications: an overview. Pharmacogn Rev 2010;4:95-105.
Shree P, Mishra P, Selvaraj C, et al. Targeting COVID-19 (SARS-CoV-2) main protease through active phytochemicals of Ayurvedic medicinal plants—Withania somnifera (Ashwagandha), Tinospora cordifolia (Giloy) and Ocimum sanctum (Tulsi)—a molecular docking study. J Biomol Struct Dyn 2022;40:190-203.
Ghoke SS, Sood R, Kumar N, et al. Evaluation of antiviral activity of Ocimum sanctum and Acacia arabica leaves extracts against H9N2 virus using embryonated chicken egg model. BMC Complement Altern Med 2018;18:174.
Devpura G, Tomar BS, Nathiya D, et al. Randomized placebo-controlled pilot clinical trial on the efficacy of Ayurvedic treatment regime on COVID-19 positive patients. Phytomedicine 2021;84:153494.
Dhama K, Sachan S, Khandia R, et al. Medicinal and beneficial health applications of Tinospora cordifolia(Guduchi): a miraculous herb countering various diseases/disorders and its immunomodulatory effects. Recent Pat Endocr Metab Immune Drug Discov 2017;10:96-111.
Herowati R, Widodo GP. Molecular docking studies of chemical constituents of Tinospora cordifolia on glycogen phosphorylase. Proced Chem 2014;13:63-68.
Patel MB, Mishra S. Hypoglycemic activity of alkaloidal fraction of Tinospora cordifolia. Phytomedicine 2011;18:1045-1052.
Kumar V, Mahdi F, Singh R, et al. A clinical trial to assess the antidiabetic, antidyslipidemic and antioxidant activities of Tinospora cordifolia in management of type-2 diabetes mellitus. Int J Pharm Sci Res 2016;7:757-764.
Diwanay S, Chitre D, Patwardhan B. Immunoprotection by botanical drugs in cancer chemotherapy. J Ethnopharmacol 2004;90:49-55.
More P, Pai K. Immunomodulatory effects of Tinospora cordifolia (Guduchi) on macrophage activation. Biol Med 2011;3:134-140.
Chowdhury P. In silico investigation of phytoconstituents from Indian medicinal herb 'Tinospora cordifolia (giloy) 'against SARS-CoV-2 (COVID-19) by molecular dynamics approach. J Biomol Struct Dyn 2021;39:6792-6809.
Balkrishna A, Khandrika L, Varshney A. Giloy Ghanvati(Tinospora cordifolia (Willd.) Hook. f. and Thomson)reversed SARS-CoV-2 viral spike-protein induced disease phenotype in the xenotransplant model of humanized Zebra fish. Front Pharmacol 2021;12:635510.
Shukla U, Ujjaliya N, Gupta P, et al. Efficacy and safety of Guduchighana Vati in asymptomatic and mild-to-moderate cases of coronavirus disease-19: a randomized controlled pilot study. Ayu 2020;41:188-196.
Dar NJ, Hamid A, Ahmad M. Pharmacologic overview of Withania somnifera, the Indian Gginseng. Cell Mol Life Sci 2015;72:4445-4460.
Chandran U, Patwardhan B. Network ethnopharmacological evaluation of the immunomodulatory activity of Withania somnifera. J Ethnopharmacol 2017;197:250-256.
Davis L, Kuttan G. Immunomodulatory activity of Withania somnifera. J Ethnopharmacol 2000;71:193-200.
Chengappa KNR, Brar JS, Gannon JM, et al. Adjunctive use of a standardized extract of Withania somnifera(Ashwagandha) to treat symptom exacerbation in schizophrenia: a randomized, double-blind, placebo-controlled study. J Clin Psychiatry 2018;79:17m11826.
Madhusudan M, Zameer F, Naidu A, et al. Evaluating the inhibitory potential of Withania somnifera on platelet aggregation and inflammation enzymes: an in vitro and in silico study. Pharm Biol 2016;54:1936-1941.
Zaka M, Sehgal SA, Shafique S, et al. Comparative in silico analyses of Cannabis sativa, Prunella vulgaris and Withania somnifera compounds elucidating the medicinal properties against rheumatoid arthritis. J Mol Graph Model 2017;74:296-304.
Dhanjal JK, Kumar V, Garg S, et al. Molecular mechanism of anti-SARS-CoV2 activity of Ashwagandha-derived with anolides. Int J Biol Macromol 2021;184:297-312.
Gundeti MS, Bhurke LW, Mundada PS, et al. AYUSH 64, a polyherbal Ayurvedic formulation in influenza-like illness-results of a pilot study. J Ayurveda Integr Med 2022;13:100325.
Mahija KC, Nazeer KAA. Repurposing AYUSH-64 for COVID-19: a computational study based on network pharmacology and molecular docking. Comb Chem High Throughput Screen 2022; Online ahead of print. doi: 10.2174/1386207325666220210125923http://doi.org/10.2174/1386207325666220210125923.
Singh H, Srivastava S, Yadav B, et al. AYUSH-64 as an adjunct to standard care in mild to moderate COVID-19: an open-label randomized controlled trial in Chandigarh, India. Complement Ther Med 2022;66:102814.
Sánchez-Rodríguez A, Pérez-Castillo Y, Schürer SC, et al. From flamingo dance to (desirable) drug discovery: a nature-inspired approach. Drug Discov Today 2017;22:1489-1502.
Singh N, Bhalla M, de Jager P, et al. An overview on Ashwagandha: a Rasayana (rejuvenator) of Ayurveda. Afr J Tradit Complement Altern Med 2011;8:208-213.
Borse S, Joshi M, Saggam A, et al. Ayurveda botanicals in COVID-19 management: an in silico multi-target approach. PLoS One 2021;16:e0248479.
Maurya SP, Das BK, Singh R, et al. Effect of Withania somnifer on CD38 expression on CD8+ T lymphocytes among patients of HIV infection. Clin Immunol 2019;203:122-124.
Patwardhan B. Ayurveda GCP guidelines: need for freedom from RCT ascendancy in favor of whole system approach. J Ayurveda Integr Med 2011;2:1-4.
Joshi A, Rajagopala S, Patel KS. A critical review on Balachaturbhadra Churna: an effective Ayurveda formulation for the pediatric age. Intl J Interrelig Intercult Studies 2019;2:1-4.
Ioannides C. Drug-phytochemical interactions. Inflammopharmacology 2003;11:7-42.
Rath LS. Ayurinformatics—the application of bioinformatics in the Ayurvedic system of medicine. Bhubaneswar: The 9th International Conference on Information Technology; 2006.
Mohan CG, Gandhi T, Garg D, et al. Computer-assisted methods in chemical toxicity prediction. Mini Rev Med Chem 2007;7:499-507.
March-Vila E, Pinzi L, Sturm N, et al. On the integration of in silico drug design methods for drug repurposing. Fron Pharmacol 2017;8:298.
Stojkovic A, Parojcic J, Djuric Z, et al. A case study of in silico modelling of Ciprofloxacin Hydrochloride/metallic compound interactions. AAPS Pharm Sci Tech 2014;15:270-278.
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