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Wang R, Duan L, Zhao B, Zheng Y, Chen L. Molecular recognition between volatile molecules and odorant binding proteins 7 by homology modeling, molecular docking and molecular dynamics simulation. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2024; 104:7592-7602. [PMID: 38767431 DOI: 10.1002/jsfa.13595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 05/01/2024] [Accepted: 05/04/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Odorant-binding proteins (OBPs) in insects are key to detection and recognition of external chemical signals associated with survival. OBP7 in Spodoptera frugiperda's larval stage (SfruOBP7) may search for host plants by sensing plant volatiles, which are important sources of pest attractants and repellents. However, the atomic-level basis of binding modes remains elusive. RESULTS SfruOBP7 structure was constructed through homology modeling, and complex models of six plant volatiles ((E)-2-hexenol, α-pinene, (Z)-3-hexenyl acetate, lauric acid, O-cymene and 1-octanol) and SfruOBP7 were obtained through molecular docking. To study the detailed interactions between the six plant volatile molecules and SfruOBP7, we conducted three 300 ns molecular dynamics simulations for each study object. The correlation coefficients between binding free energy obtained by molecular mechanics/generalized Born surface area together with solvated interaction energy methods and experimental values are 0.90 and 0.88, respectively, showing a good correlation. By comparing binding free energy along with interaction patterns between SfruOBP7 and the six volatile molecules, hotspot residues of SfruOBP7 when binding with different volatile molecules were determined. Hydrophobic interactions stemming from van der Waals interactions play a significant role in SfruOBP7 and these plant volatile systems. CONCLUSION The optimized three-dimensional structure of SfruOBP7 and its binding modes with six plant volatiles revealed their interactions, thus providing a means for estimating the binding energies of other plant volatiles. Our study will help to guide the rational design of effective and selective insect attractants. © 2024 Society of Chemical Industry.
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Affiliation(s)
- Ruige Wang
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, China
| | - Lixin Duan
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, China
| | - Bing Zhao
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, China
- Heilongjiang Provincial Key Laboratory of Surface Active Agent and Auxiliary, Qiqihar University, Qiqihar, China
| | - Yongjie Zheng
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, China
| | - Lin Chen
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar, China
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Chuntakaruk H, Boonpalit K, Kinchagawat J, Nakarin F, Khotavivattana T, Aonbangkhen C, Shigeta Y, Hengphasatporn K, Nutanong S, Rungrotmongkol T, Hannongbua S. Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery. J Comput Chem 2024; 45:953-968. [PMID: 38174739 DOI: 10.1002/jcc.27298] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/30/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024]
Abstract
In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy (ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.
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Affiliation(s)
- Hathaichanok Chuntakaruk
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, Thailand
- Department of Biochemistry, Faculty of Science, Center of Excellence in Structural and Computational Biology, Chulalongkorn University, Bangkok, Thailand
| | - Kajjana Boonpalit
- School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand
| | - Jiramet Kinchagawat
- School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand
| | - Fahsai Nakarin
- School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand
| | - Tanatorn Khotavivattana
- Center of Excellence in Natural Products Chemistry (CENP), Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
| | - Chanat Aonbangkhen
- Center of Excellence in Natural Products Chemistry (CENP), Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, Ibaraki, Japan
| | | | - Sarana Nutanong
- School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand
| | - Thanyada Rungrotmongkol
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, Thailand
- Department of Biochemistry, Faculty of Science, Center of Excellence in Structural and Computational Biology, Chulalongkorn University, Bangkok, Thailand
| | - Supot Hannongbua
- Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, Thailand
- Department of Chemistry, Faculty of Science, Center of Excellence in Computational Chemistry (CECC), Chulalongkorn University, Bangkok, Thailand
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Wang M, Liu K. Molecular dynamics simulations to explore the binding mode between the amyloid-β protein precursor (APP) and adaptor protein Mint2. Sci Rep 2024; 14:7975. [PMID: 38575686 PMCID: PMC10995209 DOI: 10.1038/s41598-024-58584-9] [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: 12/04/2023] [Accepted: 04/01/2024] [Indexed: 04/06/2024] Open
Abstract
Alzheimer's disease (AD) presents a significant challenge in neurodegenerative disease management, with limited therapeutic options available for its prevention and treatment. At the heart of AD pathogenesis is the amyloid-β (Aβ) protein precursor (APP), with the interaction between APP and the adaptor protein Mint2 being crucial. Despite previous explorations into the APP-Mint2 interaction, the dynamic regulatory mechanisms by which Mint2 modulates APP binding remain poorly understood. This study undertakes molecular dynamics simulations across four distinct systems-free Mint2, Mint2 bound to APP, a mutant form of Mint2, and the mutant form bound to APP-over an extensive 400 ns timeframe. Our findings reveal that the mutant Mint2 experiences significant secondary structural transformations, notably the formation of an α-helix in residues S55-K65 upon APP binding, within the 400 ns simulation period. Additionally, we observed a reduction in the active pocket size of the mutant Mint2 compared to its wild-type counterpart, enhancing its APP binding affinity. These insights hold promise for guiding the development of novel inhibitors targeting the Mints family, potentially paving the way for new therapeutic strategies in AD prevention and treatment.
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Affiliation(s)
- Min Wang
- International Research Centre for Nano Handling and Manufacturing of China, Changchun University of Science and Technology, Changchun, 130022, China.
- Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing, Changchun University of Science and Technology, Changchun, 130022, China.
| | - Kaifeng Liu
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, China
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Wang K, Cui H, Liu K, He Q, Fu X, Li W, Han W. Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis. Comput Biol Med 2024; 172:108252. [PMID: 38493604 DOI: 10.1016/j.compbiomed.2024.108252] [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: 01/14/2024] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/19/2024]
Abstract
Gout, a painful condition marked by elevated uric acid levels often linked to the diet's high purine and alcohol content, finds a potential treatment target in xanthine oxidase (XO), a crucial enzyme for uric acid production. This study explores the therapeutic properties of alkaloids extracted from sunflower (Helianthus annuus L.) receptacles against gout. By leveraging computational chemistry and introducing a novel R-based clustering algorithm, "TriDimensional Hierarchical Fingerprint Clustering with Tanimoto Representative Selection (3DHFC-TRS)," we assessed 231 alkaloid molecules from sunflower receptacles. Our clustering analysis pinpointed six alkaloids with significant gout-targeting potential, particularly emphasizing the fifth cluster's XO inhibition capabilities. Through molecular docking and the BatchDTA prediction model, we identified three top compounds-2-naphthylalanine, medroxalol, and fenspiride-with the highest XO affinity. Further molecular dynamics simulations assessed their enzyme active site interactions and binding free energies, employing MM-PBSA calculations. This investigation not only highlights the discovery of promising compounds within sunflower receptacle alkaloids via LC-MS but also introduces medroxalol as a novel gout treatment candidate, showcasing the synergy of computational techniques and LC-MS in drug discovery.
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Affiliation(s)
- Kaiyu Wang
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Huizi Cui
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Kaifeng Liu
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Qizheng He
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Xueqi Fu
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China
| | - Wannan Li
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China.
| | - Weiwei Han
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, Qianjin road 2699, China.
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5
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He Y, Liu K, Cao F, Song R, Liu J, Zhang Y, Li W, Han W. Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase. Sci Rep 2024; 14:174. [PMID: 38168773 PMCID: PMC10761953 DOI: 10.1038/s41598-023-50686-0] [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: 10/24/2023] [Accepted: 12/22/2023] [Indexed: 01/05/2024] Open
Abstract
Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitors of XO. We used molecular docking to obtain three systems and then conducted 200 ns molecular dynamics simulations for the Apo, LWM, and ALPM systems. The results reveal a stronger binding affinity of the LWM peptide to XO, potentially due to increased hydrogen bond formation. Notable changes were observed in the XO tunnel upon inhibitor binding, particularly with LWM, which showed a thinner, longer, and more twisted configuration compared to ALPM. The study highlights the importance of residue F914 in the allosteric pathway. Methodologically, we utilized the perturbed response scan (PRS) based on Python, enhancing tools for MD analysis. These findings deepen our understanding of food-derived anti-XO inhibitors and could inform the development of food-based therapeutics for reducing uric acid levels with minimal side effects.
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Affiliation(s)
- Yi He
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China
| | - Kaifeng Liu
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China
| | - Fuyan Cao
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China
| | - Renxiu Song
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China
| | - Jianxuan Liu
- Jilin Academy of Chinese Medicine Sciences, Chuangju Road 155, Changchun, 130012, China
| | - Yinghua Zhang
- Jilin Academy of Chinese Medicine Sciences, Chuangju Road 155, Changchun, 130012, China.
| | - Wannan Li
- Edmond H. Fischer Signal Transduction Laboratory, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China.
| | - Weiwei Han
- Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Qianjin Road 2699, Changchun, 130012, China.
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Chen J, Wang W, Sun H, He W. Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters. Mini Rev Med Chem 2024; 24:1323-1333. [PMID: 38265367 DOI: 10.2174/0113895575252165231122095555] [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: 03/06/2023] [Revised: 09/05/2023] [Accepted: 10/16/2023] [Indexed: 01/25/2024]
Abstract
Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs. The methods involved in molecular dynamics simulations are applied to not only probe conformational changes of targets but also reveal calculations of residence time that is significant for drug efficiency. For this review, special attention are paid to accelerated molecular dynamics (aMD) and Gaussian aMD (GaMD) simulations that have been adopted to predict the association or disassociation rate constant. We also expect that this review can provide useful information for future drug design.
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Affiliation(s)
- Jianzhong Chen
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Wei Wang
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Haibo Sun
- School of Science, Shandong Jiaotong University, Jinan-250357, China
| | - Weikai He
- School of Science, Shandong Jiaotong University, Jinan-250357, China
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7
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Wang Y, Yang F, Yan D, Zeng Y, Wei B, Chen J, He W. Identification Mechanism of BACE1 on Inhibitors Probed by Using Multiple Separate Molecular Dynamics Simulations and Comparative Calculations of Binding Free Energies. Molecules 2023; 28:4773. [PMID: 37375328 DOI: 10.3390/molecules28124773] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward the treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively determine the identification mechanism of BACE1 for three inhibitors, 60W, 954 and 60X. The analyses of MD trajectories indicated that the presence of three inhibitors influences the structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward the treatment of AD.
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Affiliation(s)
- Yiwen Wang
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
- School of Aeronautics, Shandong Jiaotong University, Jinan 250357, China
| | - Fen Yang
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
| | - Dongliang Yan
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Yalin Zeng
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao 266112, China
| | - Jianzhong Chen
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
- School of Science, Shandong Jiaotong University, Jinan 250357, China
| | - Weikai He
- School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China
- School of Aeronautics, Shandong Jiaotong University, Jinan 250357, China
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Chen L, Huang X, Li Y, Zhao B, Liang M, Wang R. Structural and energetic basis of interaction between human estrogen-related receptor γ and environmental endocrine disruptors from multiple molecular dynamics simulations and free energy predictions. JOURNAL OF HAZARDOUS MATERIALS 2023; 443:130174. [PMID: 36265380 DOI: 10.1016/j.jhazmat.2022.130174] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 10/04/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
Environmental endocrine disruptors (EEDs), a class of molecules that are widespread in our environment, may adversely affect the endocrine system. Exploring the interactions between these compounds and their potential targets is important for assessing their role in the organism. Focused on the human estrogen-related receptor γ (hERRγ) with BPA, BPB, HPTE, BPE, BP(2,2)(Et), and BP(2,2)(MeO) complexes, respectively, we groped for the mechanisms of conformational changes and interactions of hERRγ when binding to these six EEDs by combining multiple molecular dynamics (MD) simulations with energy prediction (MM-PBSA and solvated interaction energy (SIE)). Dynamics analysis results revealed these six EEDs have different effects on the internal dynamics of hERRγ, resulting in significant changes in the interaction of key residues around Leu268, Val313, Leu345, and Phe435 with EEDs, and thus affected its binding energy with these EEDs. The energy calculations further demonstrated that van der Waals interactions are critical for these EEDs binding to hERRγ. These results present detailed molecular insight into the interaction features between EEDs and hERRγ and help guide the search for safer alternatives to BPA.
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Affiliation(s)
- Lin Chen
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China.
| | - Xu Huang
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China
| | - Yufei Li
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China
| | - Bing Zhao
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China; Heilongjiang Provincial Key Laboratory of Surface Active Agent and Auxiliary, Qiqihar 161006, PR China
| | - Min Liang
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China
| | - Ruige Wang
- College of Chemistry and Chemical Engineering, Qiqihar University, Qiqihar 161006, PR China
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Yu YX, Wang W, Sun HB, Zhang LL, Wang LF, Yin YY. Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2022; 33:805-831. [PMID: 36322686 DOI: 10.1080/1062936x.2022.2140708] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Mutations V32I, I50V and I84V in the HIV-1 protease (PR) induce drug resistance towards drug amprenavir (APV). Multiple short molecular dynamics (MSMD) simulations and molecular mechanics generalized Born surface area (MM-GBSA) method were utilized to investigate drug-resistant mechanism of V32I, I50V and I84V towards APV. Dynamic information arising from MSMD simulations suggest that V32I, I50V and I84V highly affect structural flexibility, motion modes and conformational behaviours of two flaps in the PR. Binding free energies calculated by MM-GBSA method suggest that the decrease in binding enthalpy and the increase in binding entropy induced by mutations V32I, I50V and I84V are responsible for drug resistance of the mutated PRs on APV. The energetic contributions of separate residues on binding of APV to the PR show that V32I, I50V and I84V highly disturb the interactions of two flaps with APV and mostly drive the decrease in binding ability of APV to the PR. Thus, the conformational changes of two flaps in the PR caused by V32I, I50V and I84V play key roles in drug resistance of three mutated PR towards APV. This study can provide useful dynamics information for the design of potent inhibitors relieving drug resistance.
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Affiliation(s)
- Y X Yu
- School of Science, Shandong Jiaotong University, Jinan, China
| | - W Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - H B Sun
- School of Science, Shandong Jiaotong University, Jinan, China
| | - L L Zhang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - L F Wang
- School of Science, Shandong Jiaotong University, Jinan, China
| | - Y Y Yin
- School of Science, Shandong Jiaotong University, Jinan, China
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