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Mai TT, Phan MH, Thai TT, Lam TP, Lai NVT, Nguyen TT, Nguyen TVP, Vo CVT, Thai KM, Tran TD. Discovery of novel flavonoid derivatives as potential dual inhibitors against α-glucosidase and α-amylase: virtual screening, synthesis, and biological evaluation. Mol Divers 2024; 28:1629-1650. [PMID: 37369956 DOI: 10.1007/s11030-023-10680-0] [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: 01/28/2023] [Accepted: 06/17/2023] [Indexed: 06/29/2023]
Abstract
Diabetes mellitus is one of the top ten causes of death worldwide, accounting for 6.7 million deaths in 2021, and is one of the most rapidly growing global health emergencies of this century. Although several classes of therapeutic drugs have been invented and applied in clinical practice, diabetes continues to pose a serious and growing threat to public health and places a tremendous burden on those affected and their families. The strategy of reducing carbohydrate digestibility by inhibiting the activities of α-glucosidase and α-amylase is regarded as a promising preventative treatment for type 2 diabetes. In this study, we investigated the dual inhibitory effect against two polysaccharide hydrolytic enzymes of flavonoid derivatives from an in-house chemical database. By combining molecular docking and structure-activity relationship analysis, twelve compounds with docking energies less than or equal to - 8.0 kcal mol-1 and containing required structural features for dual inhibition of the two enzymes were identified and subjected to chemical synthesis and in vitro evaluation. The obtained results showed that five compounds exhibited dual inhibitory effects on the target enzymes with better IC50 values than the approved positive control acarbose. Molecular dynamics simulations were performed to elucidate the binding of these flavonoids to the enzymes. The predicted pharmacokinetic and toxicological properties suggest that these compounds are viable for further development as type 2 diabetes drugs.
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Affiliation(s)
- Tan Thanh Mai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Minh-Hoang Phan
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Thao Thi Thai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Thua-Phong Lam
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Nghia Vo-Trong Lai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Thanh-Thao Nguyen
- Faculty of Medicine and Pharmacy, Tay Nguyen University, Buon Ma Thuot, Dak Lak, 630000, Vietnam
| | - Thuy-Viet-Phuong Nguyen
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Cam-Van Thi Vo
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Khac-Minh Thai
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam
| | - Thanh-Dao Tran
- Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, 700000, Vietnam.
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Rusic D, Kumric M, Seselja Perisin A, Leskur D, Bukic J, Modun D, Vilovic M, Vrdoljak J, Martinovic D, Grahovac M, Bozic J. Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence. Microorganisms 2024; 12:842. [PMID: 38792673 PMCID: PMC11123121 DOI: 10.3390/microorganisms12050842] [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: 03/16/2024] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 05/26/2024] Open
Abstract
Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery. Unfortunately, there is an evident gap between the number of machine learning applications in science and the effective implementation of these systems. This narrative review highlights some of the outstanding opportunities that machine learning offers when applied in research related to antimicrobial resistance. In the future, machine learning tools may prove to be superbugs' kryptonite. This review aims to provide an overview of available publications to aid researchers that are looking to expand their work with new approaches and to acquaint them with the current application of machine learning techniques in this field.
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Affiliation(s)
- Doris Rusic
- Department of Pharmacy, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (D.R.); (A.S.P.); (D.L.); (J.B.); (D.M.)
| | - Marko Kumric
- Department of Pathophysiology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (M.K.); (M.V.); (J.V.); (D.M.)
- Laboratory for Cardiometabolic Research, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia
| | - Ana Seselja Perisin
- Department of Pharmacy, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (D.R.); (A.S.P.); (D.L.); (J.B.); (D.M.)
| | - Dario Leskur
- Department of Pharmacy, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (D.R.); (A.S.P.); (D.L.); (J.B.); (D.M.)
| | - Josipa Bukic
- Department of Pharmacy, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (D.R.); (A.S.P.); (D.L.); (J.B.); (D.M.)
| | - Darko Modun
- Department of Pharmacy, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (D.R.); (A.S.P.); (D.L.); (J.B.); (D.M.)
| | - Marino Vilovic
- Department of Pathophysiology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (M.K.); (M.V.); (J.V.); (D.M.)
- Laboratory for Cardiometabolic Research, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia
| | - Josip Vrdoljak
- Department of Pathophysiology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (M.K.); (M.V.); (J.V.); (D.M.)
- Laboratory for Cardiometabolic Research, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia
| | - Dinko Martinovic
- Department of Pathophysiology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (M.K.); (M.V.); (J.V.); (D.M.)
- Department of Maxillofacial Surgery, University Hospital of Split, Spinciceva 1, 21000 Split, Croatia
| | - Marko Grahovac
- Department of Pharmacology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia;
| | - Josko Bozic
- Department of Pathophysiology, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia; (M.K.); (M.V.); (J.V.); (D.M.)
- Laboratory for Cardiometabolic Research, University of Split School of Medicine, Soltanska 2A, 21000 Split, Croatia
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Marotta L, Rossi S, Ibba R, Brogi S, Calderone V, Butini S, Campiani G, Gemma S. The green chemistry of chalcones: Valuable sources of privileged core structures for drug discovery. Front Chem 2022; 10:988376. [PMID: 36172001 PMCID: PMC9511966 DOI: 10.3389/fchem.2022.988376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 08/12/2022] [Indexed: 11/26/2022] Open
Abstract
The sustainable use of resources is essential in all production areas, including pharmaceuticals. However, the aspect of sustainability needs to be taken into consideration not only in the production phase, but during the whole medicinal chemistry drug discovery trajectory. The continuous progress in the fields of green chemistry and the use of artificial intelligence are contributing to the speed and effectiveness of a more sustainable drug discovery pipeline. In this light, here we review the most recent sustainable and green synthetic approaches used for the preparation and derivatization of chalcones, an important class of privileged structures and building blocks used for the preparation of new biologically active compounds with a broad spectrum of potential therapeutic applications. The literature here reported has been retrieved from the SciFinder database using the term “chalcone” as a keyword and filtering the results applying the concept: “green chemistry”, and from the Reaxys database using the keywords “chalcone” and “green”. For both databases the time-frame was 2017–2022. References were manually selected based on relevance.
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Affiliation(s)
- Ludovica Marotta
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Sara Rossi
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Roberta Ibba
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Simone Brogi
- Department of Pharmacy, University of Pisa, Pisa, Italy
- *Correspondence: Simone Brogi, ; Giuseppe Campiani,
| | | | - Stefania Butini
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Giuseppe Campiani
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
- *Correspondence: Simone Brogi, ; Giuseppe Campiani,
| | - Sandra Gemma
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
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