1
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Thai QM, Nguyen TH, Phung HTT, Pham MQ, Pham NKT, Horng JT, Ngo ST. MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods. RSC Adv 2024; 14:18950-18956. [PMID: 38873542 PMCID: PMC11167619 DOI: 10.1039/d4ra02661f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/07/2024] [Indexed: 06/15/2024] Open
Abstract
Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.
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Affiliation(s)
- Quynh Mai Thai
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
| | - Trung Hai Nguyen
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
| | | | - Minh Quan Pham
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Nguyen Kim Tuyen Pham
- Faculty of Environment, Sai Gon University 273 An Duong Vuong, Ward 3, District 5 Ho Chi Minh City Vietnam
| | - Jim-Tong Horng
- Department of Biochemistry and Molecular Biology, College of Medicine, Chang Gung University Kweishan Taoyuan Taiwan
| | - Son Tung Ngo
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University Ho Chi Minh City Vietnam
- Faculty of Pharmacy, Ton Duc Thang University Ho Chi Minh City Vietnam
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2
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Nguyen TH, Thai QM, Pham MQ, Minh PTH, Phung HTT. Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds. Mol Divers 2024; 28:553-561. [PMID: 36823394 PMCID: PMC9950021 DOI: 10.1007/s11030-023-10601-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/04/2023] [Indexed: 02/25/2023]
Abstract
To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.
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Affiliation(s)
- Trung Hai Nguyen
- Laboratory of Theoretical and Computational Biophysics, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Quynh Mai Thai
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Minh Quan Pham
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Pham Thi Hong Minh
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Huong Thi Thu Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
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3
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Thai QM, Phung HTT, Pham NQA, Horng JT, Tran PT, Tung NT, Ngo ST. Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies. J Biomol Struct Dyn 2024:1-9. [PMID: 38419271 DOI: 10.1080/07391102.2024.2321509] [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: 09/30/2023] [Accepted: 02/15/2024] [Indexed: 03/02/2024]
Abstract
VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Quynh Mai Thai
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Huong T T Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
| | - Ngoc Quynh Anh Pham
- Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, ROC
| | - Jim-Tong Horng
- Graduate Institute of Biomedical Sciences, Chang Gung University, Taoyuan, ROC
| | - Phuong-Thao Tran
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - Nguyen Thanh Tung
- Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Son Tung Ngo
- Laboratory of Biophysics, Institute for Advanced Study in Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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4
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Le TTH, Tran LH, Nguyen MT, Pham MQ, Phung HTT. Calculation of binding affinity of JAK1 inhibitors via accurately computational estimation. J Biomol Struct Dyn 2023; 41:7224-7234. [PMID: 36069111 DOI: 10.1080/07391102.2022.2118830] [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: 01/24/2022] [Accepted: 08/23/2022] [Indexed: 10/14/2022]
Abstract
Janus kinase 1 (JAK1) is a tyrosine kinase that is involved in the initiation of responses to a number of different cytokine receptor families. The JAK1-dependent pathway is a therapeutic target, and several JAK inhibitors have been developed thanks to intensive research. However, since the ATP binding sites of JAK family members are quite alike, JAK1 inhibitors can thus be less selective, resulting in unanticipated adverse effects. Despite this, minor variations in the ATP-binding site have been extensively used to find a variety of small compounds with different inhibitory properties. Stronger binding affinity of JAK1 inhibitors is believed to be able to reduce the negative effects, leading to better treatment results. Therefore, a thorough computational search that can effectively identify ligands with extremely high binding affinity for JAK1 to serve as promising inhibitors is required. Here, a method combining steered-molecular dynamic (SMD) simulations with a modified linear interaction energy (LIE) model has been developed to evaluate the binding affinities of known JAK1 inhibitors. The correlation coefficient between the estimated and experimental values was 0.72 and a root-mean-square error was 0.97 kcal•mol-1, revealing that the SMD/LIE method can precisely and quickly predict the binding free energies of JAK1 inhibitors. Furthermore, three marine fungus-derived compounds, namely hansforesters E, hansforesters G and tetroazolemycins B, were identified to be particularly promising JAK1 inhibitors, accordingly. These findings show that the SMD/LIE method has a lot of promise for in silico screening of possible JAK1 inhibitors from a vast number of compounds that are now accessible.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Thi-Thuy-Huong Le
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Linh Hoang Tran
- Vietnam National University, Ho Chi Minh City, Vietnam
- Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam
| | - Minh Tam Nguyen
- Laboratory of Theoretical and Computational Biophysics, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Minh Quan Pham
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Huong Thi Thu Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
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5
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Mechanistic Insights of Polyphenolic Compounds from Rosemary Bound to Their Protein Targets Obtained by Molecular Dynamics Simulations and Free-Energy Calculations. Foods 2023; 12:foods12020408. [PMID: 36673500 PMCID: PMC9858269 DOI: 10.3390/foods12020408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/09/2023] [Accepted: 01/12/2023] [Indexed: 01/17/2023] Open
Abstract
Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid, are the main compounds responsible for these actions. In our earlier research, we carried out an inverse molecular docking at the proteome scale to determine possible protein targets of the mentioned compounds. Here, we subjected the previously identified ligand-protein complexes with HIV-1 protease, K-RAS, and factor X to molecular dynamics simulations coupled with free-energy calculations. We observed that carnosic acid and rosmanol act as viable binders of the HIV-1 protease. In addition, carnosol represents a potential binder of the oncogene protein K-RAS. On the other hand, rosmarinic acid was characterized as a weak binder of factor X. We also emphasized the importance of water-mediated hydrogen-bond networks in stabilizing the binding conformation of the studied polyphenols, as well as in mechanistically explaining their promiscuous nature.
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Nguyen TH, Tam NM, Tuan MV, Zhan P, Vu VV, Quang DT, Ngo ST. Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations. Chem Phys 2023; 564:111709. [PMID: 36188488 PMCID: PMC9511900 DOI: 10.1016/j.chemphys.2022.111709] [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: 05/03/2022] [Revised: 08/11/2022] [Accepted: 09/21/2022] [Indexed: 11/28/2022]
Abstract
Inhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R=0.748±0.044. Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine compounds from the top 100 ML inhibitors were suggested to bind well to the protease with the domination of van der Waals interactions. Furthermore, the binding affinity of these compounds is also higher than that of nirmatrelvir, which was recently approved by the US FDA to treat COVID-19. In addition, the ligands altered the catalytic triad Cys145 - His41 - Asp187, possibly disturbing the biological activity of SARS-CoV-2.
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7
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Ngo ST, Nguyen TH, Tung NT, Vu VV, Pham MQ, Mai BK. Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches. Phys Chem Chem Phys 2022; 24:29266-29278. [PMID: 36449268 DOI: 10.1039/d2cp04476e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.
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Affiliation(s)
- Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam. .,Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Trung Hai Nguyen
- Laboratory of Theoretical and Computational Biophysics, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam. .,Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Nguyen Thanh Tung
- Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam. .,Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Van V Vu
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam
| | - Minh Quan Pham
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam.,Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Binh Khanh Mai
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, USA
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8
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Mai NT, Lan NT, Vu TY, Tung NT, Phung HTT. A computationally affordable approach for accurate prediction of the binding affinity of JAK2 inhibitors. J Mol Model 2022; 28:163. [DOI: 10.1007/s00894-022-05149-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 05/06/2022] [Indexed: 11/24/2022]
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9
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In silico screening of potential β-secretase (BACE1) inhibitors from VIETHERB database. J Mol Model 2022; 28:60. [DOI: 10.1007/s00894-022-05051-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/07/2022] [Indexed: 11/25/2022]
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10
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Tam NM, Nguyen TH, Ngan VT, Tung NT, Ngo ST. Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211480. [PMID: 35116157 PMCID: PMC8790385 DOI: 10.1098/rsos.211480] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 12/20/2021] [Indexed: 05/03/2023]
Abstract
The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic-area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro.
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Affiliation(s)
- Nguyen Minh Tam
- Computational Chemistry Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Trung Hai Nguyen
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
| | - Vu Thi Ngan
- Laboratory of Computational Chemistry and Modelling, Department of Chemistry, Quy Nhon University, Quy Nhon, Vietnam
| | - Nguyen Thanh Tung
- Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Son Tung Ngo
- Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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11
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King E, Aitchison E, Li H, Luo R. Recent Developments in Free Energy Calculations for Drug Discovery. Front Mol Biosci 2021; 8:712085. [PMID: 34458321 PMCID: PMC8387144 DOI: 10.3389/fmolb.2021.712085] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/27/2021] [Indexed: 01/11/2023] Open
Abstract
The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.
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Affiliation(s)
- Edward King
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
| | - Erick Aitchison
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
| | - Han Li
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA, United States
| | - Ray Luo
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA, United States
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA, United States
- Department of Materials Science and Engineering, University of California, Irvine, CA, United States
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
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12
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Cao DT, Huong Doan TM, Pham VC, Minh Le TH, Chae JW, Yun HY, Na MK, Kim YH, Pham MQ, Nguyen VH. Molecular design of anticancer drugs from marine fungi derivatives. RSC Adv 2021; 11:20173-20179. [PMID: 35479875 PMCID: PMC9033662 DOI: 10.1039/d1ra01855h] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/24/2021] [Indexed: 12/21/2022] Open
Abstract
Heat shock protein 90 (Hsp90) is one of the most potential targets in cancer therapy. We have demonstrated using a combination of molecular docking and fast pulling of ligand (FPL) simulations that marine fungi derivatives can be possible inhibitors, preventing the biological activity of Hsp90. The computational approaches were validated and compared with previous experiments. Based on the benchmark of available inhibitors of Hsp90, the GOLD docking package using the ChemPLP scoring function was found to be superior over both Autodock Vina and Autodock4 in the preliminary estimation of the ligand-binding affinity and binding pose with the Pearson correlation, R = -0.62. Moreover, FPL calculations were also indicated as a suitable approach to refine docking simulations with a correlation coefficient with the experimental data of R = -0.81. Therefore, the binding affinity of marine fungi derivatives to Hsp90 was evaluated. Docking and FPL calculations suggest that five compounds including 23, 40, 46, 48, and 52 are highly potent inhibitors for Hsp90. The obtained results enhance cancer therapy research.
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Affiliation(s)
- Duc Tuan Cao
- Hai Phong University of Medicine and Pharmacy Haiphong Vietnam
| | - Thi Mai Huong Doan
- Institute of Marine Biochemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Van Cuong Pham
- Institute of Marine Biochemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Thi Hong Minh Le
- Institute of Marine Biochemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Jung-Woo Chae
- College of Pharmacy, Chungnam National University Daejeon Republic of Korea
| | - Hwi-Yeol Yun
- College of Pharmacy, Chungnam National University Daejeon Republic of Korea
| | - Min-Kyun Na
- College of Pharmacy, Chungnam National University Daejeon Republic of Korea
| | - Young-Ho Kim
- College of Pharmacy, Chungnam National University Daejeon Republic of Korea
| | - Minh Quan Pham
- Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam
- Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology Hanoi Vietnam
| | - Van Hung Nguyen
- Hai Phong University of Medicine and Pharmacy Haiphong Vietnam
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13
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Ngo ST, Tam NM, Pham MQ, Nguyen TH. Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro. J Chem Inf Model 2021; 61:2302-2312. [PMID: 33829781 PMCID: PMC8043216 DOI: 10.1021/acs.jcim.1c00159] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Indexed: 12/13/2022]
Abstract
The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE ≈ FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26, His41, Ser46, Asn142, Gly143, Cys145, His164, Glu166, and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches.
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Affiliation(s)
- Son Tung Ngo
- Laboratory of Theoretical and Computational
Biophysics, Ton Duc Thang University, Ho Chi Minh City 700000,
Vietnam
- Faculty of Applied Sciences, Ton Duc
Thang University, Ho Chi Minh City 700000,
Vietnam
| | - Nguyen Minh Tam
- Faculty of Applied Sciences, Ton Duc
Thang University, Ho Chi Minh City 700000,
Vietnam
- Computional Chemistry Research Group, Ton
Duc Thang University, Ho Chi Minh City 700000,
Vietnam
| | - Minh Quan Pham
- Graduate University of Science and Technology,
Vietnam Academy of Science and Technology, Hanoi 100000,
Vietnam
- Institute of Natural Products Chemistry,
Vietnam Academy of Science and Technology, Hanoi 100000,
Vietnam
| | - Trung Hai Nguyen
- Laboratory of Theoretical and Computational
Biophysics, Ton Duc Thang University, Ho Chi Minh City 700000,
Vietnam
- Faculty of Applied Sciences, Ton Duc
Thang University, Ho Chi Minh City 700000,
Vietnam
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14
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Ngo ST. Estimating the ligand-binding affinity via λ-dependent umbrella sampling simulations. J Comput Chem 2020; 42:117-123. [PMID: 33078419 DOI: 10.1002/jcc.26439] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/21/2020] [Accepted: 09/24/2020] [Indexed: 12/16/2022]
Abstract
The umbrella sampling (US) approach has been demonstrated to be a very efficient method for estimating the ligand-binding affinity. However, most of the calculated values overestimate experimental ones that are probably caused by the inaccurate representation of the interaction between the ligand and the surrounding molecules. The issue can be resolved via the implementation aspects of λ-alteration simulation into the US approach, which we call the λ-dependent umbrella sampling (λUS) scheme. In particular, the electrostatic and van der Waals interactions were simultaneously changed by using the coupling parameter λ during λUS simulations. The mean value of obtained results, ∆ G US λ = 0.20 = - 11.59 ± 1.51 kcal mol-1 , is in good fitting to the mean value of respective experiments, ∆GEXP = - 11.26 ± 0.89 kcal mol-1 . Moreover, the correlation between the proposed approach and experiment is quite good with a value of R US λ = 0.20 = 0.82 ± 0.10 . The λUS scheme significantly enhances the calculated accuracy since the RMSE of the proposed scheme is smaller than traditional US simulations, RMSE US λ = 0.20 = 2.99 ± 0.82 kcal mol-1 versus RMSE US λ = 0.00 = 5.48 ± 0.81 kcal mol-1 . Furthermore, the precision is increased since the computed error via λUS approach, δ US λ = 0.20 = 1.51 kcal mol-1 , was smaller than those of the US simulation, δ US λ = 0.00 = 1.78 kcal mol-1 . Overall, the proposed approach perhaps provides an efficient way to accurately and precisely estimate the ligand-binding free energy.
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Affiliation(s)
- Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Applied Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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15
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Mai NT, Lan NT, Vu TY, Duong PTM, Tung NT, Phung HTT. Estimation of the ligand-binding free energy of checkpoint kinase 1 via non-equilibrium MD simulations. J Mol Graph Model 2020; 100:107648. [PMID: 32653524 DOI: 10.1016/j.jmgm.2020.107648] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 04/29/2020] [Accepted: 05/18/2020] [Indexed: 02/07/2023]
Abstract
Checkpoint kinase 1 (CHK1) is a serine/threonine-protein kinase that is involved in cell cycle regulation in eukaryotes. Inhibition of CHK1 is thus considered as a promising approach in cancer therapy. In this study, the fast pulling of ligand (FPL) process was applied to predict the relative binding affinities of CHK1 inhibitors using non-equilibrium molecular dynamics (MD) simulations. The work of external harmonic forces to pull the ligand out of the binding cavity strongly correlated with the experimental binding affinity of CHK1 inhibitors with the correlation coefficient of R = -0.88 and an overall root mean square error (RMSE) of 0.99 kcal/mol. The data indicate that the FPL method is highly accurate in predicting the relative binding free energies of CHK1 inhibitors with an affordable CPU time. A new set of molecules were designed based on the molecular modeling of interactions between the known inhibitor and CHK1 as inhibitory candidates. Molecular docking and FPL results exhibited that the binding affinities of developed ligands were similar to the known inhibitor in interaction with the catalytic site of CHK1, producing very potential CHK1 inhibitors of that the inhibitory activities should be further evaluated in vitro.
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Affiliation(s)
- Nguyen Thi Mai
- Laboratory of Theoretical and Computational Biophysics, Ho Chi Minh City, Viet Nam; Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Viet Nam
| | - Ngo Thi Lan
- Institute of Materials Science & Graduate University of Science and Technology, Academy of Science and Technology, Hanoi, Viet Nam
| | - Thien Y Vu
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Viet Nam
| | - Phuong Thi Mai Duong
- Department of Chemistry, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Nguyen Thanh Tung
- Institute of Materials Science & Graduate University of Science and Technology, Academy of Science and Technology, Hanoi, Viet Nam.
| | - Huong Thi Thu Phung
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Viet Nam.
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16
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Minh Hung H, Nguyen MT, Tran PT, Truong VK, Chapman J, Quynh Anh LH, Derreumaux P, Vu VV, Ngo ST. Impact of the Astaxanthin, Betanin, and EGCG Compounds on Small Oligomers of Amyloid Aβ 40 Peptide. J Chem Inf Model 2020; 60:1399-1408. [PMID: 32105466 DOI: 10.1021/acs.jcim.9b01074] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
There is experimental evidence that the astaxanthin, betanin, and epigallocatechin-3-gallate (EGCG) compounds slow down the aggregation kinetics and the toxicity of the amyloid-β (Aβ) peptide. How these inhibitors affect the self-assembly at the atomic level remains elusive. To address this issue, we have performed for each ligand atomistic replica exchange molecular dynamic (REMD) simulations in an explicit solvent of the Aβ11-40 trimer from the U-shape conformation and MD simulations starting from Aβ1-40 dimer and tetramer structures characterized by different intra- and interpeptide conformations. We find that the three ligands have similar binding free energies on small Aβ40 oligomers but very distinct transient binding sites that will affect the aggregation of larger assemblies and fibril elongation of the Aβ40 peptide.
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Affiliation(s)
- Huynh Minh Hung
- Department of Chemistry, KU Leuven, Celestijnenlaan 200F, B-3001 Leuven, Belgium
| | - Minh Tho Nguyen
- Computational Chemistry Research Group, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
| | - Phuong-Thao Tran
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, Hanoi 100000, Vietnam
| | - Vi Khanh Truong
- School of Science, RMIT University, GPO Box 2476, Melbourne 3001, Australia
| | - James Chapman
- School of Science, RMIT University, GPO Box 2476, Melbourne 3001, Australia
| | - Le Huu Quynh Anh
- Department of Climate Change and Renewable Energy, Ho Chi Minh City University of Natural Resources and Environment, Ho Chi Minh City 700000, Vietnam
| | - Philippe Derreumaux
- Laboratory of Theoretical Chemistry, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam.,Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam.,Laboratoire de Biochimie Théorique, UPR9080, CNRS, Université de Paris, 13 rue Pierre et Marie Curie, F-75005 Paris, France.,Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, 75005 Paris, France
| | - Van V Vu
- NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam
| | - Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam.,Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
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17
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Ngo ST, Hong ND, Quynh Anh LH, Hiep DM, Tung NT. Effective estimation of the inhibitor affinity of HIV-1 protease via a modified LIE approach. RSC Adv 2020; 10:7732-7739. [PMID: 35492181 PMCID: PMC9049864 DOI: 10.1039/c9ra09583g] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 02/06/2020] [Indexed: 01/07/2023] Open
Abstract
The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses. Computer-aided drug design (CADD) would enhance the discovery of new therapies, through which the estimation of ligand-binding affinity is critical to predict the most efficient inhibitor. A time-consuming binding free energy method would reduce the usefulness of CADD. The modified linear interaction energy (LIE) approach emerges as an appropriate protocol that performs this task. In particular, the polar interaction free energy, which is obtained via numerically resolving the linear Poisson–Boltzmann equation, plays as an important role in driving the binding mechanism of the HIV-1 PR + inhibitor complex. The electrostatic interaction energy contributes to the attraction between two molecules, but the vdW interaction acts as a repulsive factor between the ligand and the HIV-1 PR. Moreover, the ligands were found to adopt a very strong hydrophobic interaction with the HIV-1 PR. Furthermore, the results obtained corroborate the high accuracy and precision of computational studies with a large correlation coefficient value R = 0.83 and a small RMSE δRMSE = 1.25 kcal mol−1. This method is less time-consuming than the other end-point methods, such as the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and free energy perturbation (FEP) approaches. Overall, the modified LIE approach would provide ligand-binding affinity with HIV-1 PR accurately, precisely, and rapidly, resulting in a more efficient design of new inhibitors. The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses.![]()
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Affiliation(s)
- Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics
- Ton Duc Thang University
- Ho Chi Minh City
- Vietnam
- Faculty of Applied Sciences
| | - Nam Dao Hong
- University of Medicine and Pharmacy at Ho Chi Minh City
- Ho Chi Minh City
- Vietnam
| | - Le Huu Quynh Anh
- Department of Climate Change and Renewable Energy
- Ho Chi Minh City University of Natural Resources and Environment
- Ho Chi Minh City
- Vietnam
| | | | - Nguyen Thanh Tung
- Institute of Materials Science & Graduate University of Science and Technology
- Vietnam Academy of Science and Technology
- Hanoi
- Vietnam
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