中草药

基于“生理-机制-病理”反向开发模式的天然药物创新策略

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中草药 | 综述 2026,57(8): 3251-3260

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中草药 |综述 2026 , 57 (8) : 3251 -3260

基于“生理-机制-病理”反向开发模式的天然药物创新策略

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梁红宝¹, 袁晓梅¹, 刘晓庆¹, 蓝林欣¹, 刘悦¹, 杨敏²

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梁红宝: 梁红宝(1985-),男,博士,高级工程师,从事中药/天然产物创新药物及大健康产品研究。Tel:18764932621 E-mail:lianghongbao1985@163.com

Innovative strategy for natural medicines based on “physiology-mechanism-pathology” reverse development model

LIANG Hongbao, YUAN Xiaomei, LIU Xiaoqing, LAN Linxin, LIU Yue, YANG Min

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doi: 10.7501/j.issn.0253-2670.2026.08.034

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摘要

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传统的天然产物药物开发价值评判模式，多以直接构建疾病或病理模型为先导，通过观测药效强弱，继而深入开展成药性评估。这种传统路径呈现出较为显著的随机性与盲目性，不可避免地导致开发难度的大幅提升以及研发成本的急剧增加。相较而言，基于“生理-机制-病理”的反向开发模式，创新性地以正常动物模型为切入点，首先全面细致观察天然产物所引发的生理效应及毒性作用，进而深入挖掘其内在的作用机制，以此反向推断可能蕴含的药理活性，最终针对性地设计并构建相应的疾病或病理模型进行验证。此策略凭借对天然产物与机体相互作用规律的精准解析，以及对药理效应所提供线索的有效整合，实现了精准化模型构建与有效性科学评估，在一定程度上显著提升了研发的成功率与效率。以银杏叶萜类内酯为研究对象完成了该模式的全流程实践，成功发现其降胆红素-抗黄疸的新药理活性，验证了模式的可行性与实用性。通过系统解析该模式的产生背景、理论基础及技术路径，并展望其在天然药物研发中的多元应用场景，为推动天然药物研发的策略创新与实践应用提供理论依据与方向指引。

关键词

天然药物 / 生理-机制-病理 / 反向开发 / 药物研发策略 / 银杏叶萜类内酯

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Evaluation models for the development value of traditional natural product-based drugs often take the direct construction of disease or pathological models as a precursor. By observing the strength of drug efficacy, further evaluation of in-depth drugability is carried out. However, this traditional approach shows significant randomness and blindness, inevitably leading to a substantial increase in development difficulty and a sharp rise in research and development (R&D) costs. In contrast, the reverse development model based on “physiology-mechanism-pathology” innovatively starts with normal animal models. First, it comprehensively and meticulously observes the physiological effects and toxic effects caused by natural products, and then delves into their underlying mechanisms of action. Based on this, it infers the potential pharmacological activities in a reverse manner. Finally, it specifically designs and constructs corresponding disease or pathological models for rigorous verification. This strategy, through the accurate analysis of the interaction rules between natural products and the body and the effective integration of clues provided by pharmacological effects, achieves precise model construction and scientific evaluation of effectiveness, significantly improving the success rate and efficiency of R&D to a certain extent. In this study, the whole process of the model was practiced with ginkgo terpenoid lactones as the research object, and its new pharmacological activity of reducing bilirubin and anti-jaundice was successfully discovered, which verified the feasibility and practicability of the model. This paper systematically reviews and deeply analyzes the background, basic principles, and technical processes of this innovative approach. At the same time, it predicts and prospects its diverse application prospects in the field of natural medicine R&D. The aim is to provide a solid theoretical basis and forward-looking direction for promoting the strategic innovation and practical application of natural medicine R&D.

Key words

natural medicines / physiology-mechanism-pathology / reverse development / drug development strategy / ginkgo terpene lactones

引用本文

梁红宝, 袁晓梅, 刘晓庆, 蓝林欣, 刘悦, 杨敏. 基于“生理-机制-病理”反向开发模式的天然药物创新策略. 中草药, 2026 , 57 (8) : 3251 -3260 . DOI: 10.7501/j.issn.0253-2670.2026.08.034

LIANG Hongbao, YUAN Xiaomei, LIU Xiaoqing, LAN Linxin, LIU Yue, YANG Min. Innovative strategy for natural medicines based on “physiology-mechanism-pathology” reverse development model[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (8) : 3251 -3260 . DOI: 10.7501/j.issn.0253-2670.2026.08.034

基金

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山东省中医药科技重点项目 (Z20242118); 烟台市自然科学基金重点项目 (ZR2025Z052); 烟台市科技创新发展计划（政策引导类）项目 (2025YD018)

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Atanasov A G, Zotchev S B, Dirsch V M, et al. Natural products in drug discovery:Advances and opportunities[J]. Nat Rev Drug Discov, 2021, 20(3):200-216.
Wang Y X, Wang F, Liu W X, et al. New drug discovery and development from natural products:Advances and strategies[J]. Pharmacol Ther, 2024, 264:108752.
Cragg G M, Pezzuto J M. Natural products as a vital source for the discovery of cancer chemotherapeutic and chemopreventive agents[J]. Med Princ Pract, 2016, 25(Suppl 2):41-59.
Saldívar-González F I, Aldas-Bulos V D, Medina-Franco J L, et al. Natural product drug discovery in the artificial intelligence era[J]. Chem Sci, 2021, 13(6):1526-1546.
Pham P, Nguyen V T D, Cho K H, et al. DrugPipe:Generative artificial intelligence-assisted virtual screening pipeline for generalizable and efficient drug repurposing[J]. Biol Methods Protoc, 2025, 10(1):bpaf038.
Ancuceanu R, Lascu B E, Drăgănescu D, et al. In silico ADME methods used in the evaluation of natural products[J]. Pharmaceutics, 2025, 17(8):1002.
Sadgrove N J, Jones G L. From Petri dish to patient:Bioavailability estimation and mechanism of action for antimicrobial and immunomodulatory natural products[J]. Front Microbiol, 2019, 10:2470.
Skrajnowska D, Bobrowska-Korczak B. The effects of diet, dietary supplements, drugs and exercise on physical, diagnostic values of urine characteristics[J]. Nutrients, 2024, 16(18):3141.
Fan Z J, Liu J M, Li X X, et al. Glycyrrhizin-induced pseudohyperaldosteronism:A case report[J]. Chin J Integr Med, 2022, 28(7):644-649.
Andersson K E. PDE5 inhibitors-pharmacology and clinical applications 20 years after Sildenafil discovery[J]. Br J Pharmacol, 2018, 175(13):2554-2565.
Newman D J, Cragg G M. Natural products as sources of new drugs over the nearly four decades from 01/1981 to 09/2019[J]. J Nat Prod, 2020, 83(3):770-803.
Butler M S. Natural products to drugs:Natural product-derived compounds in clinical trials[J]. Nat Prod Rep, 2008, 25(3):475.
Demain A L, Sanchez S. Microbial drug discovery:80 years of progress[J]. J Antibiot, 2009, 62(1):5-16.
Sams-Dodd F. Drug discovery:Selecting the optimal approach[J]. Drug Discov Today, 2006, 11(9/10):465-472.
Swinney D C, Anthony J. How were new medicines discovered?[J]. Nat Rev Drug Discov, 2011, 10(7):507-519.
Lei C F, Chen Z G, Ma C Y, et al. Optimization of potential targets for antidepressant Chinese medicines:AI and multi-omics methods[J]. Chin Med, 2026, 21(1):67.
Drews J. Drug discovery:A historical perspective[J]. Science, 2000, 287(5460):1960-1964.
Moffat J G, Rudolph J, Bailey D. Phenotypic screening in cancer drug discovery:Past, present and future[J]. Nat Rev Drug Discov, 2014, 13(8):588-602.
Zimmermann G R, Lehár J, Keith C T. Multi-target therapeutics:When the whole is greater than the sum of the parts[J]. Drug Discov Today, 2007, 12(1/2):34-42.
Shang X F, Dai L X, Cao X Y, et al. Natural products in antiparasitic drug discovery:Advances, opportunities and challenges[J]. Nat Prod Rep, 2025, 42(9):1419-1458.
Yuan Y J, Shi C Y, Zhao H M. Machine learning-enabled genome mining and bioactivity prediction of natural products[J]. ACS Synth Biol, 2023, 12(9):2650-2662.
Hark R, Zürlein S, Nguyen V T, et al. AI-assisted phenotyping in a zebrafish hypophosphatasia model enables early and precise detection of skeletal alterations[J]. Sci Rep, 2025, 15(1):32578.
Lyu J K, Kapolka N, Gumpper R, et al. AlphaFold2 structures guide prospective ligand discovery[J]. Science, 2024, 384(6702):eadn6354.
Díaz-Holguín A, Saarinen M, Vo D D, et al. AlphaFold accelerated discovery of psychotropic agonists targeting the trace amine-associated receptor 1[J]. Sci Adv, 2024, 10(32):eadn1524.
Siafis S, Wu H, Wang D F, et al. Antipsychotic dose, dopamine D2 receptor occupancy and extrapyramidal side-effects:A systematic review and dose-response meta-analysis[J]. Mol Psychiatry, 2023, 28(8):3267-3277.
Hopkins A L. Network pharmacology:The next paradigm in drug discovery[J]. Nat Chem Biol, 2008, 4(11):682-690.
Czechowicz P, Więch-Walów A, Sławski J, et al. Old drugs, new challenges:Reassigning drugs for cancer therapies[J]. Cell Mol Biol Lett, 2025, 30(1):27.
Yang H J, Chen X, Li K, et al. Repurposing old drugs as new inhibitors of the ubiquitin-proteasome pathway for cancer treatment[J]. Semin Cancer Biol, 2021, 68:105-122.
Quitkin F. Monoamine oxidase inhibitors:A review of antidepressant effectiveness[J]. Arch Gen Psychiatry, 1979, 36(7):749.
Olsen E A, Dunlap F E, Funicella T, et al. A randomized clinical trial of 5% topical minoxidil versus 2% topical minoxidil and placebo in the treatment of androgenetic alopecia in men[J]. J Am Acad Dermatol, 2002, 47(3):377-385.
Tong X L, Dong L, Chen L, et al. Treatment of diabetes using traditional Chinese medicine:Past, present and future[J]. Am J Chin Med, 2012, 40(5):877-886.
Dagenais S, Russo L, Madsen A, et al. Use of real-world evidence to drive drug development strategy and inform clinical trial design[J]. Clin Pharmacol Ther, 2022, 111(1):77-89.
Wedam S, Fashoyin-Aje L, Bloomquist E, et al. FDA approval summary:Palbociclib for male patients with metastatic breast cancer[J]. Clin Cancer Res, 2020, 26(6):1208-1212.
成小兰, 王倩, 袁飞飞, 等. 以临床价值为导向的中药复方转化医学研究思路与方法[J]. 南京中医药大学学报, 2021, 37(5):648-653.
赵晓晓, 谢雁鸣. 中医药真实世界研究现状及未来[J]. 中国药物评价, 2022, 39(6):441-450.
Takenaka T. Classical vs reverse pharmacology in drug discovery[J]. BJU Int, 2001, 88(Suppl 2):7-10.
Patwardhan B, Vaidya A D. Natural products drug discovery:Accelerating the clinical candidate development using reverse pharmacology approaches[J]. Indian J Exp Biol, 2010, 48(3):220-227.
Willcox M L, Graz B, Falquet J, et al. A "reverse pharmacology" approach for developing an anti-malarial phytomedicine[J]. Malar J, 2011, 10(1):S8.
Chen M, Wen S S, Wang R, et al. Advanced development of supercritical fluid chromatography in herbal medicine analysis[J]. Molecules, 2022, 27(13):4159.
Liang X J, Zhang Y P, Chen W, et al. High-speed counter-current chromatography coupled online to high performance liquid chromatography-diode array detector-mass spectrometry for purification, analysis and identification of target compounds from natural products[J]. J Chromatogr A, 2015, 1385:69-76.
Su Z, Fang J, Wang S S, et al. Integrating multi-omics and network pharmacology:A novel approach to elucidate Chinese medicine mechanisms in Crohn's disease treatment[J]. Crit Rev Microbiol, 2026, doi:10.1080/1040841X.2026.2623245.
Miranda de Souza Duarte-Filho L A, Ortega de Oliveira P C, Yanaguibashi Leal C E, et al. Ligand fishing as a tool to screen natural products with anticancer potential[J]. J Sep Sci, 2023, 46(12):e2200964.
Liao L X, Song X M, Wang L C, et al. Highly selective inhibition of IMPDH2 provides the basis of antineuroinflammation therapy[J]. Proc Natl Acad Sci USA, 2017, 114(29):E5986-E5994.
Yang Z, Zhang X W, Zhuo F F, et al. Allosteric activation of transglutaminase 2 via inducing an "open" conformation for osteoblast differentiation[J]. Adv Sci, 2023, 10(18):2206533.
Barabási A L, Gulbahce N, Loscalzo J. Network medicine:A network-based approach to human disease[J]. Nat Rev Genet, 2011, 12(1):56-68.
Parini P. The use of different types of networks, alone and in combination, for drug target identification[J]. Br J Pharmacol, 2026, 183(8):1653-1662.
Hua Y, Dai X W, Xu Y, et al. Drug repositioning:Progress and challenges in drug discovery for various diseases[J]. Eur J Med Chem, 2022, 234:114239.
Hong C E, Lyu S Y. Formulation strategies for immunomodulatory natural products in 3D tumor spheroids and organoids:Current challenges and emerging solutions[J]. Pharmaceutics, 2025, 17(10):1258.
Zhang L, Huang X P, Xiong H Z, et al. The Nrf2/HO-1 signaling pathway in arthritis:From molecular mechanisms to therapeutic potential[J]. Front Cell Dev Biol, 2026, 14:1728679.
Asghar A, Ali Chohan T, Qayyum A, et al. Unveiling the biochemical potential of Acacia jacquemontii as a therapeutic agent in Parkinson's disease:A multi-model in vitro, in vivo, and in silico study[J]. PLoS One, 2026, 21(2):e0334312.
Ma H, Han X, Lan Z, et al. Toxicological risks in herbal medicines:Component analysis, mechanisms, and detoxification technologies[J]. J Ethnopharmacol, 2026, 357:120915.
朱伟明. 海洋天然产物的高效发现与成药性研究[J]. 中草药, 2019, 50(23):5645-5652.
Li S C, Lv M, Xu H. Overview of piperine:Bioactivities, total synthesis, structural modification, and structure-activity relationships[J]. Mini Rev Med Chem, 2023, 23(8):917-940.
Sun F Q, Quan Y S, Shen Q K, et al. Recent advances in structural modifications of natural products for anti-leishmaniasis therapy (2010-2024)[J]. RSC Med Chem, 2025, 16(11):5268-5291.
Liang H B, Yuan X M, Sun C H, et al. Preparation of a new component group of Ginkgo biloba leaves and investigation of the antihypertensive effects in spontaneously hypertensive rats[J]. Biomed Pharmacother, 2022, 149:112805.
Liang H B, Sun C H, Feng Z, et al. Study on integrated pharmacokinetics of the component-based Chinese medicine of Ginkgo biloba leaves based on nanocrystalline solid dispersion technology[J]. Int J Nanomedicine, 2022, 17:4039-4057.
Liang H B, Yao J C, Miao Y, et al. Pharmacological activities and effective substances of the component-based Chinese medicine of Ginkgo biloba leaves based on serum pharmacochemistry, metabonomics and network pharmacology[J]. Front Pharmacol, 2023, 14:1151447.
梁红宝. 一种银杏叶新型组分中药纳米晶固体分散体的制备及成药性研究[D]. 济南:山东中医药大学, 2024.
张贵民, 梁红宝, 曾振, 等. 一种银杏内酯组合物及其在制备预防和/或治疗溶血性黄疸药物中的用途:中国, CN120053426A[P]. 2025-05-30.
Li J N, Guo C, Yang X F, et al. Effects of natural products on macrophage immunometabolism:A new frontier in the treatment of metabolic diseases[J]. Pharmacol Res, 2025, 213:107634.

2026年第57卷第8期

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doi: 10.7501/j.issn.0253-2670.2026.08.034

接收时间：2026-02-21
首发时间：2026-09-09

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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