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Combined structure and ligand-based design of dual BACE-1/GSK-3β inhibitors for Alzheimer’s disease. CHEMICAL PAPERS 2022. [DOI: 10.1007/s11696-022-02421-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Yuan Y, Pei J, Lai L. LigBuilder V3: A Multi-Target de novo Drug Design Approach. Front Chem 2020; 8:142. [PMID: 32181242 PMCID: PMC7059350 DOI: 10.3389/fchem.2020.00142] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 02/14/2020] [Indexed: 12/18/2022] Open
Abstract
With the rapid development of systems-based pharmacology and poly-pharmacology, method development for rational design of multi-target drugs has becoming urgent. In this paper, we present the first de novo multi-target drug design program LigBuilder V3, which can be used to design ligands to target multiple receptors, multiple binding sites of one receptor, or various conformations of one receptor. LigBuilder V3 is generally applicable in de novo multi-target drug design and optimization, especially for the design of concise ligands for protein targets with large difference in binding sites. To demonstrate the utility of LigBuilder V3, we have used it to design dual-functional inhibitors targeting HIV protease and HIV reverse transcriptase with three different strategy, including multi-target de novo design, multi-target growing, and multi-target linking. The designed compounds were computational validated by MM/GBSA binding free energy estimation as highly potential multi-target inhibitors for both HIV protease and HIV reverse transcriptase. The LigBuilder V3 program can be downloaded at “http://www.pkumdl.cn/ligbuilder3/”.
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Affiliation(s)
- Yaxia Yuan
- Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Jianfeng Pei
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Luhua Lai
- Beijing National Laboratory for Molecular Sciences, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
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Schaduangrat N, Prachayasittikul V, Choomwattana S, Wongchitrat P, Phopin K, Suwanjang W, Malik AA, Vincent B, Nantasenamat C. Multidisciplinary approaches for targeting the secretase protein family as a therapeutic route for Alzheimer's disease. Med Res Rev 2019; 39:1730-1778. [PMID: 30628099 DOI: 10.1002/med.21563] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 11/21/2018] [Accepted: 12/24/2018] [Indexed: 12/27/2022]
Abstract
The continual increase of the aging population worldwide renders Alzheimer's disease (AD) a global prime concern. Several attempts have been focused on understanding the intricate complexity of the disease's development along with the on- andgoing search for novel therapeutic strategies. Incapability of existing AD drugs to effectively modulate the pathogenesis or to delay the progression of the disease leads to a shift in the paradigm of AD drug discovery. Efforts aimed at identifying AD drugs have mostly focused on the development of disease-modifying agents in which effects are believed to be long lasting. Of particular note, the secretase enzymes, a group of proteases responsible for the metabolism of the β-amyloid precursor protein (βAPP) and β-amyloid (Aβ) peptides production, have been underlined for their promising therapeutic potential. This review article attempts to comprehensively cover aspects related to the identification and use of drugs targeting the secretase enzymes. Particularly, the roles of secretases in the pathogenesis of AD and their therapeutic modulation are provided herein. Moreover, an overview of the drug development process and the contribution of computational (in silico) approaches for facilitating successful drug discovery are also highlighted along with examples of relevant computational works. Promising chemical scaffolds, inhibitors, and modulators against each class of secretases are also summarized herein. Additionally, multitarget secretase modulators are also taken into consideration in light of the current growing interest in the polypharmacology of complex diseases. Finally, challenging issues and future outlook relevant to the discovery of drugs targeting secretases are also discussed.
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Affiliation(s)
- Nalini Schaduangrat
- Faculty of Medical Technology, Center of Data Mining and Biomedical Informatics, Mahidol University, Bangkok, Thailand
| | - Veda Prachayasittikul
- Faculty of Medical Technology, Center of Data Mining and Biomedical Informatics, Mahidol University, Bangkok, Thailand
| | - Saowapak Choomwattana
- Faculty of Medical Technology, Center of Data Mining and Biomedical Informatics, Mahidol University, Bangkok, Thailand
| | - Prapimpun Wongchitrat
- Faculty of Medical Technology, Center for Research and Innovation, Mahidol University, Bangkok, Thailand
| | - Kamonrat Phopin
- Faculty of Medical Technology, Center for Research and Innovation, Mahidol University, Bangkok, Thailand
| | - Wilasinee Suwanjang
- Faculty of Medical Technology, Center for Research and Innovation, Mahidol University, Bangkok, Thailand
| | - Aijaz Ahmad Malik
- Faculty of Medical Technology, Center of Data Mining and Biomedical Informatics, Mahidol University, Bangkok, Thailand
| | - Bruno Vincent
- Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, Thailand.,Centre National de la Recherche Scientifique, Paris, France
| | - Chanin Nantasenamat
- Faculty of Medical Technology, Center of Data Mining and Biomedical Informatics, Mahidol University, Bangkok, Thailand
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