1
|
Liu L, Bi M, Wang Y, Liu J, Jiang X, Xu Z, Zhang X. Artificial intelligence-powered microfluidics for nanomedicine and materials synthesis. NANOSCALE 2021; 13:19352-19366. [PMID: 34812823 DOI: 10.1039/d1nr06195j] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Artificial intelligence (AI) is an emerging technology with great potential, and its robust calculation and analysis capabilities are unmatched by traditional calculation tools. With the promotion of deep learning and open-source platforms, the threshold of AI has also become lower. Combining artificial intelligence with traditional fields to create new fields of high research and application value has become a trend. AI has been involved in many disciplines, such as medicine, materials, energy, and economics. The development of AI requires the support of many kinds of data, and microfluidic systems can often mine object data on a large scale to support AI. Due to the excellent synergy between the two technologies, excellent research results have emerged in many fields. In this review, we briefly review AI and microfluidics and introduce some applications of their combination, mainly in nanomedicine and material synthesis. Finally, we discuss the development trend of the combination of the two technologies.
Collapse
Affiliation(s)
- Linbo Liu
- John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA 02138, USA
| | - Mingcheng Bi
- Institute of Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou 310027, P.R. China
| | - Yunhua Wang
- John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA 02138, USA
| | - Junfeng Liu
- Institute of Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou 310027, P.R. China
| | - Xiwen Jiang
- College of Biological Science and Engineering, Fuzhou university, Fuzhou 350108, P.R. China
| | - Zhongbin Xu
- Institute of Process Equipment, College of Energy Engineering, Zhejiang University, Hangzhou 310027, P.R. China
| | - Xingcai Zhang
- John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA 02138, USA
- School of Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| |
Collapse
|
2
|
Porras G, Chassagne F, Lyles JT, Marquez L, Dettweiler M, Salam AM, Samarakoon T, Shabih S, Farrokhi DR, Quave CL. Ethnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery. Chem Rev 2021; 121:3495-3560. [PMID: 33164487 PMCID: PMC8183567 DOI: 10.1021/acs.chemrev.0c00922] [Citation(s) in RCA: 133] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The crisis of antibiotic resistance necessitates creative and innovative approaches, from chemical identification and analysis to the assessment of bioactivity. Plant natural products (NPs) represent a promising source of antibacterial lead compounds that could help fill the drug discovery pipeline in response to the growing antibiotic resistance crisis. The major strength of plant NPs lies in their rich and unique chemodiversity, their worldwide distribution and ease of access, their various antibacterial modes of action, and the proven clinical effectiveness of plant extracts from which they are isolated. While many studies have tried to summarize NPs with antibacterial activities, a comprehensive review with rigorous selection criteria has never been performed. In this work, the literature from 2012 to 2019 was systematically reviewed to highlight plant-derived compounds with antibacterial activity by focusing on their growth inhibitory activity. A total of 459 compounds are included in this Review, of which 50.8% are phenolic derivatives, 26.6% are terpenoids, 5.7% are alkaloids, and 17% are classified as other metabolites. A selection of 183 compounds is further discussed regarding their antibacterial activity, biosynthesis, structure-activity relationship, mechanism of action, and potential as antibiotics. Emerging trends in the field of antibacterial drug discovery from plants are also discussed. This Review brings to the forefront key findings on the antibacterial potential of plant NPs for consideration in future antibiotic discovery and development efforts.
Collapse
Affiliation(s)
- Gina Porras
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
| | - François Chassagne
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
| | - James T. Lyles
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
| | - Lewis Marquez
- Molecular and Systems Pharmacology Program, Laney Graduate School, Emory University, 615 Michael St., Whitehead 115, Atlanta, Georgia 30322
| | - Micah Dettweiler
- Department of Dermatology, Emory University, 615 Michael St., Whitehead 105L, Atlanta, Georgia 30322
| | - Akram M. Salam
- Molecular and Systems Pharmacology Program, Laney Graduate School, Emory University, 615 Michael St., Whitehead 115, Atlanta, Georgia 30322
| | - Tharanga Samarakoon
- Emory University Herbarium, Emory University, 1462 Clifton Rd NE, Room 102, Atlanta, Georgia 30322
| | - Sarah Shabih
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
| | - Darya Raschid Farrokhi
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
| | - Cassandra L. Quave
- Center for the Study of Human Health, Emory University, 1557 Dickey Dr., Atlanta, Georgia 30322
- Emory University Herbarium, Emory University, 1462 Clifton Rd NE, Room 102, Atlanta, Georgia 30322
- Department of Dermatology, Emory University, 615 Michael St., Whitehead 105L, Atlanta, Georgia 30322
- Molecular and Systems Pharmacology Program, Laney Graduate School, Emory University, 615 Michael St., Whitehead 115, Atlanta, Georgia 30322
| |
Collapse
|
3
|
Li X, Zhao H, Chen X. Screening of Marine Bioactive Antimicrobial Compounds for Plant Pathogens. Mar Drugs 2021; 19:69. [PMID: 33525648 PMCID: PMC7912171 DOI: 10.3390/md19020069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 01/21/2021] [Accepted: 01/25/2021] [Indexed: 01/09/2023] Open
Abstract
Plant diseases have been threatening food production. Controlling plant pathogens has become an important strategy to ensure food security. Although chemical control is an effective disease control strategy, its application is limited by many problems, such as environmental impact and pathogen resistance. In order to overcome these problems, it is necessary to develop more chemical reagents with new functional mechanisms. Due to their special living environment, marine organisms have produced a variety of bioactive compounds with novel structures, which have the potential to develop new fungicides. In the past two decades, screening marine bioactive compounds to inhibit plant pathogens has been a hot topic. In this review, we summarize the screening methods of marine active substances from plant pathogens, the identification of marine active substances from different sources, and the structure and antibacterial mechanism of marine active natural products. Finally, the application prospect of marine bioactive substances in plant disease control was prospected.
Collapse
Affiliation(s)
- Xiaohui Li
- College of Food and Pharmaceutical Sciences, Ningbo University, Ningbo 315832, China; (X.L.); (H.Z.)
| | - Hejing Zhao
- College of Food and Pharmaceutical Sciences, Ningbo University, Ningbo 315832, China; (X.L.); (H.Z.)
| | - Xiaolin Chen
- State Key Laboratory of Agricultural Microbiology and Provincial Hubei Key Laboratory of Plant Pathology, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| |
Collapse
|
4
|
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.
Collapse
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.
| |
Collapse
|
5
|
Alberto AVP, da Silva Ferreira NC, Soares RF, Alves LA. Molecular Modeling Applied to the Discovery of New Lead Compounds for P2 Receptors Based on Natural Sources. Front Pharmacol 2020; 11:01221. [PMID: 33117147 PMCID: PMC7553047 DOI: 10.3389/fphar.2020.01221] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 07/27/2020] [Indexed: 12/24/2022] Open
Abstract
P2 receptors are a family of transmembrane receptors activated by nucleotides and nucleosides. Two classes have been described in mammals, P2X and P2Y, which are implicated in various diseases. Currently, only P2Y12 has medicines approved for clinical use as antiplatelet agents and natural products have emerged as a source of new drugs with action on P2 receptors due to the diversity of chemical structures. In drug discovery, in silico virtual screening (VS) techniques have become popular because they have numerous advantages, which include the evaluation of thousands of molecules against a target, usually proteins, faster and cheaper than classical high throughput screening (HTS). The number of studies using VS techniques has been growing in recent years and has led to the discovery of new molecules of natural origin with action on different P2X and P2Y receptors. Using different algorithms it is possible to obtain information on absorption, distribution, metabolism, toxicity, as well as predictions on biological activity and the lead-likeness of the selected hits. Selected biomolecules may then be tested by molecular dynamics and, if necessary, rationally designed or modified to improve their interaction for the target. The algorithms of these in silico tools are being improved to permit the precision development of new drugs and, in the future, this process will take the front of drug development against some central nervous system (CNS) disorders. Therefore, this review discusses the methodologies of in silico tools concerning P2 receptors, as well as future perspectives and discoveries, such as the employment of artificial intelligence in drug discovery.
Collapse
Affiliation(s)
- Anael Viana Pinto Alberto
- Laboratory of Cellular Communication, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | | | - Rafael Ferreira Soares
- Laboratory of Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Luiz Anastacio Alves
- Laboratory of Cellular Communication, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| |
Collapse
|
6
|
Ponomaryov DV, Grigorʼeva LR, Nemtarev AV, Tsepaeva OV, Mironov VF, Gnezdilov OI, Antipin IS. 3,28-Diacetoxylup-20(29)-ene-30-oic Acid and Its ω-Bromoalkyl
Esters. RUSSIAN JOURNAL OF ORGANIC CHEMISTRY 2020. [DOI: 10.1134/s1070428020040107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|