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Luo D, Tong Z, Wen L, Bai M, Jin X, Liu Z, Li Y, Xue W. DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders. Comput Biol Med 2024; 175:108536. [PMID: 38701592 DOI: 10.1016/j.compbiomed.2024.108536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 04/15/2024] [Accepted: 04/28/2024] [Indexed: 05/05/2024]
Abstract
In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.
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Affiliation(s)
- Ding Luo
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Zhuohao Tong
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Lu Wen
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Mingze Bai
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Xiaojie Jin
- College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Zerong Liu
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical Co., Ltd, Sichuan, 646100, China; Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400030, China
| | - Yinghong Li
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.
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Tu G, Fu T, Zheng G, Xu B, Gou R, Luo D, Wang P, Xue W. Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives. J Chem Inf Model 2024; 64:1433-1455. [PMID: 38294194 DOI: 10.1021/acs.jcim.3c01736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.
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Affiliation(s)
- Gao Tu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Tingting Fu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | | | - Binbin Xu
- Chengdu Sintanovo Biotechnology Co., Ltd., Chengdu 610200, China
| | - Rongpei Gou
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Panpan Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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Bao Y, Jia F, Li M, Xu R, Xie Y, Zhang F, Guo J. Characterizing the Molecular Mechanism of the Lethal C423D Mutation in FgMyoI: A Molecular Perspective. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:1539-1549. [PMID: 38226494 DOI: 10.1021/acs.jafc.3c08648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
The lethal mutation C423D in Fusarium graminearum myosin I (FgMyoI) occurs close to the binding pocket of the allosteric inhibitor phenamacril and causes severe inhibition on mycelial growth of F. graminearum strain PH-1. Here, based on extensive Gaussian accelerated molecular dynamics simulations and wet experiments, we elucidate the underlying molecular mechanism of the abnormal functioning of the FgMyoIC423D mutant at the atomistic level. Our results suggest that the damaging mutation C423D exhibits a synergistic allosteric inhibition mechanism similar to but more robust than that of phenamacril, including effects on the active site and actin binding. Unlike phenamacril-induced closure of Switch2, the mutation results in unfolding of the N-terminal relay helix with a partially opened Switch2 and blocks the structural rearrangement of the relay/SH1 helices, impairing the proper initiation of the recovery stroke. Due to the significant influence of C423D mutation on the function of FgMyoI, designing covalent inhibitors targeting this site holds tremendous potential.
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Affiliation(s)
- Yiqiong Bao
- College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Fangying Jia
- College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
| | - Mengrong Li
- College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Ran Xu
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China
| | - Yanjie Xie
- College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Feng Zhang
- College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
| | - Jingjing Guo
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China
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Bao Y, Xu Y, Jia F, Li M, Xu R, Zhang F, Guo J. Allosteric inhibition of myosin by phenamacril: a synergistic mechanism revealed by computational and experimental approaches. PEST MANAGEMENT SCIENCE 2023; 79:4977-4989. [PMID: 37540764 DOI: 10.1002/ps.7699] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 07/29/2023] [Accepted: 08/04/2023] [Indexed: 08/06/2023]
Abstract
BACKGROUND Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species-specific and non-competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear. RESULTS This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin-binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin. CONCLUSION Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Yiqiong Bao
- College of Life Sciences, Nanjing Agricultural University, Nanjing, China
| | - Yan Xu
- College of Life Sciences, Nanjing Agricultural University, Nanjing, China
| | - Fangying Jia
- College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - Mengrong Li
- College of Life Sciences, Nanjing Agricultural University, Nanjing, China
| | - Ran Xu
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
| | - Feng Zhang
- College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - Jingjing Guo
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
- Engineering Research Centre of Applied Technology on Machine Translation and Artificial Intelligence, Macao Polytechnic University, Macao, China
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Mijit A, Wang X, Li Y, Xu H, Chen Y, Xue W. Mapping synthetic binding proteins epitopes on diverse protein targets by protein structure prediction and protein-protein docking. Comput Biol Med 2023; 163:107183. [PMID: 37352638 DOI: 10.1016/j.compbiomed.2023.107183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 06/25/2023]
Abstract
Synthetic binding proteins (SBPs) are a class of artificial proteins engineered from privileged protein scaffolds, which can form highly specific molecular recognition interfaces with a variety of targets. Due to the characteristics of small size, high stability, and good tissue permeability, SBPs have important applications in biomedical research, disease diagnosis and treatment. However, knowledge of SBPs epitopes on the structures of target proteins is still limited, which hinder the development of novel SBPs. In this study, based on the currently available information of SBPs and their targets, 96 pairs of interacting proteins referring to 96 representative SBPs and 80 different targets, were systemically investigated using the state-of-the-art computational modeling techniques including AlphaFold2 protein structure prediction and Rosetta protein-protein docking. As a result, 71 out of the 96 pairs were successfully docked, of which 18, 33, and 20 pairs were defined as models with high, medium, and acceptable quality, respectively. In addition, the interface information was analyzed to decipher the interaction types driven SBPs and targets recognition. Overall, this work not only provides important structural information for understanding the mechanism of action of other SBPs with same protein scaffold, but also for aiding the rational protein engineering and to design of novel SBPs with biomedical applications.
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Affiliation(s)
- Arzu Mijit
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Xiaona Wang
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Yanlin Li
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Hangwei Xu
- School of Medicine, Hangzhou City University, Hangzhou, 310000, China
| | - Yingjun Chen
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.
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Deng S, Zhang H, Gou R, Luo D, Liu Z, Zhu F, Xue W. Structure-Based Discovery of a Novel Allosteric Inhibitor against Human Dopamine Transporter. J Chem Inf Model 2023. [PMID: 37410882 DOI: 10.1021/acs.jcim.3c00477] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
Human dopamine transporter (hDAT) regulates the reuptake of extracellular dopamine (DA) and is an essential therapeutic target for central nervous system (CNS) diseases. The allosteric modulation of hDAT has been identified for decades. However, the molecular mechanism underlying the transportation is still elusive, which hinders the rational design of allosteric modulators against hDAT. Here, a systematic structure-based method was performed to explore allosteric sites on hDAT in inward-open (IO) conformation and to screen compounds with allosteric affinity. First, the model of the hDAT structure was constructed based on the recently reported Cryo-EM structure of the human serotonin transporter (hSERT) and Gaussian-accelerated molecular dynamics (GaMD) simulation was further utilized for the identification of intermediate energetic stable states of the transporter. Then, with the potential druggable allosteric site on hDAT in IO conformation, virtual screening of seven enamine chemical libraries (∼440,000 compounds) was processed, resulting in 10 compounds being purchased for in vitro assay and with Z1078601926 discovered to allosterically inhibit hDAT (IC50 = 0.527 [0.284; 0.988] μM) when nomifensine was introduced as an orthosteric ligand. Finally, the synergistic effect underlying the allosteric inhibition of hDAT by Z1078601926 and nomifensine was explored using additional GaMD simulation and postbinding free energy analysis. The hit compound discovered in this work not only provides a good starting point for lead optimization but also demonstrates the usability of the method for the structure-based discovery of novel allosteric modulators of other therapeutic targets.
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Affiliation(s)
- Shengzhe Deng
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Haiwei Zhang
- Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Department of Pathology, Chongqing University Cancer Hospital, Chongqing 400030, China
| | - Rongpei Gou
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Zerong Liu
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical Co., Ltd., Luzhou 646000, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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