1
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Tu G, Gong Y, Yao X, Liu Q, Xue W, Zhang R. Pathways and mechanism of MRTX1133 binding to KRAS G12D elucidated by molecular dynamics simulations and Markov state models. Int J Biol Macromol 2024; 274:133374. [PMID: 38925182 DOI: 10.1016/j.ijbiomac.2024.133374] [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: 04/12/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024]
Abstract
KRAS G12D is the most common oncogenic mutation identified in several types of cancer. Therefore, design of inhibitors targeting KRAS G12D represents a promising strategy for anticancer therapy. MRTX1133 is a highly potent inhibitor (approximate experiment Kd ≈ 0.0002 nM) of KRAS G12D and is currently in Phase 1/2 study, however, pathways of the compound binding to KRAS G12D has remained unknown, and the mechanism underlying the complicated dynamic process are challenging to capture experimentally, which hinder the structure-based anti-cancer drug design. Here, using MRTX1133 as a probe, unbiased molecular dynamics (MD) was used to simulate the process of MRTX1133 spontaneously binding to KRAS G12D. In six of 42 independent MD simulation (a total of 99 μs), MRTX1133 was observed to successfully associate with KRAS G12D. The kinetically metastable states refer to the potential pathways of MRTX1133 binding to KRAS G12D were revealed by Markov state models (MSM) analysis. Additionally, 8 key residues that are essential for MRTX1133 recognition and tight binding at the preferred low energy states were identified by MM/GBSA analysis. In sum, this study provides a new perspective on understanding the pathways and mechanism of MRTX1133 binding to KRAS G12D.
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Affiliation(s)
- Gao Tu
- Department of Pharmacy, The Second Affiliated Hospital, Army Medical University, 183 Xinqiao Road, Chongqing 400037, China; Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, 999078, Macau
| | - Yaguo Gong
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, 999078, Macau
| | - Xiaojun Yao
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, 999078, Macau.
| | - Qing Liu
- Suzhou Institute for Advance Research, University of Science and Technology of China, Suzhou, China
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China.
| | - Rong Zhang
- Department of Pharmacy, The Second Affiliated Hospital, Army Medical University, 183 Xinqiao Road, Chongqing 400037, China.
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2
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Inan T, Flinko R, Lewis GK, MacKerell AD, Kurkcuoglu O. Identifying and Assessing Putative Allosteric Sites and Modulators for CXCR4 Predicted through Network Modeling and Site Identification by Ligand Competitive Saturation. J Phys Chem B 2024; 128:5157-5174. [PMID: 38647430 PMCID: PMC11139592 DOI: 10.1021/acs.jpcb.4c00925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Abstract
The chemokine receptor CXCR4 is a critical target for the treatment of several cancer types and HIV-1 infections. While orthosteric and allosteric modulators have been developed targeting its extracellular or transmembrane regions, the intramembrane region of CXCR4 may also include allosteric binding sites suitable for the development of allosteric drugs. To investigate this, we apply the Gaussian Network Model (GNM) to the monomeric and dimeric forms of CXCR4 to identify residues essential for its local and global motions located in the hinge regions of the protein. Residue interaction network (RIN) analysis suggests hub residues that participate in allosteric communication throughout the receptor. Mutual residues from the network models reside in regions with a high capacity to alter receptor dynamics upon ligand binding. We then investigate the druggability of these potential allosteric regions using the site identification by ligand competitive saturation (SILCS) approach, revealing two putative allosteric sites on the monomer and three on the homodimer. Two screening campaigns with Glide and SILCS-Monte Carlo docking using FDA-approved drugs suggest 20 putative hit compounds including antifungal drugs, anticancer agents, HIV protease inhibitors, and antimalarial drugs. In vitro assays considering mAB 12G5 and CXCL12 demonstrate both positive and negative allosteric activities of these compounds, supporting our computational approach. However, in vivo functional assays based on the recruitment of β-arrestin to CXCR4 do not show significant agonism and antagonism at a single compound concentration. The present computational pipeline brings a new perspective to computer-aided drug design by combining conformational dynamics based on network analysis and cosolvent analysis based on the SILCS technology to identify putative allosteric binding sites using CXCR4 as a showcase.
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Affiliation(s)
- Tugce Inan
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
| | - Robin Flinko
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - George K. Lewis
- Institute
of Human Virology, University of Maryland
School of Medicine, Baltimore, Maryland 21201, United States
| | - Alexander D. MacKerell
- University
of Maryland Computer-Aided Drug Design Center, Department of Pharmaceutical
Sciences, School of Pharmacy, University
of Maryland, Baltimore, Maryland 21201, United States
| | - Ozge Kurkcuoglu
- Department
of Chemical Engineering, Istanbul Technical
University, Istanbul 34469, Turkey
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3
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Pawnikar S, Magenheimer BS, Munoz EN, Haldane A, Maser RL, Miao Y. Activation of Polycystin-1 Signaling by Binding of Stalk-derived Peptide Agonists. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.06.574465. [PMID: 38260358 PMCID: PMC10802338 DOI: 10.1101/2024.01.06.574465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Polycystin-1 (PC1) is the membrane protein product of the PKD1 gene whose mutation is responsible for 85% of the cases of autosomal dominant polycystic kidney disease (ADPKD). ADPKD is primarily characterized by the formation of renal cysts and potential kidney failure. PC1 is an atypical G protein-coupled receptor (GPCR) consisting of 11 transmembrane helices and an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Recently, signaling activation of the PC1 CTF was shown to be regulated by a stalk tethered agonist (TA), a distinct mechanism observed in the adhesion GPCR family. A novel allosteric activation pathway was elucidated for the PC1 CTF through a combination of Gaussian accelerated molecular dynamics (GaMD), mutagenesis and cellular signaling experiments. Here, we show that synthetic, soluble peptides with 7 to 21 residues derived from the stalk TA, in particular, peptides including the first 9 residues (p9), 17 residues (p17) and 21 residues (p21) exhibited the ability to re-activate signaling by a stalkless PC1 CTF mutant in cellular assays. To reveal molecular mechanisms of stalk peptide-mediated signaling activation, we have applied a novel Peptide GaMD (Pep-GaMD) algorithm to elucidate binding conformations of selected stalk peptide agonists p9, p17 and p21 to the stalkless PC1 CTF. The simulations revealed multiple specific binding regions of the stalk peptide agonists to the PC1 protein including an "intermediate" bound yet inactive state. Our Pep-GaMD simulation findings were consistent with the cellular assay experimental data. Binding of peptide agonists to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of the PC1 CTF signaling activation mechanism. Using sequence covariation analysis of PC1 homologs, we further showed that the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. Therefore, structural dynamic insights into the mechanisms of PC1 activation by stalk-derived peptide agonists have enabled an in-depth understanding of PC1 signaling. They will form a foundation for development of PC1 as a therapeutic target for the treatment of ADPKD.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Brenda S. Magenheimer
- Departments of Biochemistry and Molecular Biology, Temple University, Philadelphia, PA 19122
- Clinical Laboratory Sciences, Temple University, Philadelphia, PA 19122
| | | | - Allan Haldane
- Dept of Physics, and Center for Biophysics and Computational Biology, Temple University, Philadelphia, PA 19122
| | - Robin L. Maser
- Departments of Biochemistry and Molecular Biology, Temple University, Philadelphia, PA 19122
- Clinical Laboratory Sciences, Temple University, Philadelphia, PA 19122
- The Jared Grantham Kidney Institute, University of Kansas Medical Center, Kansas City, KS 66160
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North Carolina – Chapel Hill, Chapel Hill, NC 27599
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4
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Hassanzadeh L, Erfani M, Jokar S, Shariatpanahi M. Design of a New 99mTc-radiolabeled Cyclo-peptide as Promising Molecular Imaging Agent of CXCR 4 Receptor: Molecular Docking, Synthesis, Radiolabeling, and Biological Evaluation. Curr Radiopharm 2024; 17:77-90. [PMID: 37921191 DOI: 10.2174/0118744710249305231017073022] [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: 02/16/2023] [Revised: 07/09/2023] [Accepted: 08/28/2023] [Indexed: 11/04/2023]
Abstract
INTRODUCTION C-X-C Chemokine receptor type 4 (CXCR4) is often overexpressed or overactivated in different types and stages of cancer disease. Therefore, it is considered a promising target for imaging and early detection of primary tumors and metastasis. In the present research, a new cyclo-peptide radiolabelled with 99mTc, 99mTc-Cyclo [D-Phe-D-Tyr-Lys (HYNIC)- D-Arg-2-Nal-Gly-Lys(iPr)], was designed based on the parental LY251029 peptide, as a potential in vivo imaging agent of CXCR4-expressing tumors. METHODS The radioligand was successfully prepared using the method of Fmoc solid-phase peptide synthesis and was evaluated in biological assessment. Molecular docking findings revealed high affinity (binding energy of -9.7 kcal/mol) and effective interaction of Cyclo [D-Phe- D-Tyr-Lys (HYNIC)-D-Arg-2-Nal-Gly-Lys(iPr)] in the binding pocket of CXCR4 receptor (PDB code: 3OE0) as well. RESULT The synthesized peptide and its purity were assessed by both reversed-phase high-performance liquid chromatography (RP-HPLC) and mass spectroscopy. High stability (95%, n = 3) in human serum and favorable affinity (Kd = 28.70 ± 13.56 nM and Bmax = 1.896 ± 0.123 fmol/mg protein) in the B16-F10 cell line resulted. Biodistribution evaluation findings and planar image interpretation of mice both showed high affinity and selectivity of the radiotracer to the CXCR4 receptors. CONCLUSION Therefore, the findings indicate this designed radioligand could be used as a potential SPECT imaging agent in highly proliferated CXCR4 receptor tumors.
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Affiliation(s)
- Leila Hassanzadeh
- Department of Nuclear Medicine, School of Medicine, Rajaie Cardiovascular, Medical & Research Center, Iran University of Medical Sciences, Tehran, Iran
- Department of Medical Imaging Technology, Molecular Imaging, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mostafa Erfani
- Radiation Application Research School, Nuclear Science and Technology Research Institute, (NSTRI), P.O. Box: 14395-836, Tehran, Iran
| | - Safura Jokar
- Department of Nuclear Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Marjan Shariatpanahi
- Department of Pharmacology and Toxicology, School of Pharmacy, Iran University of Medical Sciences, Tehran, Iran
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5
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Adediwura VA, Miao Y. Mechanistic Insights into Peptide Binding and Deactivation of an Adhesion G Protein-Coupled Receptor. Molecules 2023; 29:164. [PMID: 38202747 PMCID: PMC10780249 DOI: 10.3390/molecules29010164] [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: 11/27/2023] [Revised: 12/20/2023] [Accepted: 12/23/2023] [Indexed: 01/12/2024] Open
Abstract
Adhesion G protein-coupled receptors (ADGRGs) play critical roles in the reproductive, neurological, cardiovascular, and endocrine systems. In particular, ADGRG2 plays a significant role in Ewing sarcoma cell proliferation, parathyroid cell function, and male fertility. In 2022, a cryo-EM structure was reported for the active ADGRG2 bound by an optimized peptide agonist IP15 and the Gs protein. The IP15 peptide agonist was also modified to antagonists 4PH-E and 4PH-D with mutations of the 4PH residue to Glu and Asp, respectively. However, experimental structures of inactive antagonist-bound ADGRs remain to be resolved, and the activation mechanism of ADGRs such as ADGRG2 is poorly understood. Here, we applied Gaussian accelerated molecular dynamics (GaMD) simulations to probe conformational dynamics of the agonist- and antagonist-bound ADGRG2. By performing GaMD simulations, we were able to identify important low-energy conformations of ADGRG2 in the active, intermediate, and inactive states, as well as explore the binding conformations of each peptide. Moreover, our simulations revealed critical peptide-receptor residue interactions during the deactivation of ADGRG2. In conclusion, through GaMD simulations, we uncovered mechanistic insights into peptide (agonist and antagonist) binding and deactivation of the ADGRG2. These findings will potentially facilitate rational design of new peptide modulators of ADGRG2 and other ADGRs.
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Affiliation(s)
| | - Yinglong Miao
- Department of Pharmacology and Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA;
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6
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Pawnikar S, Akhter S, Miao Y. Structural dynamics of chemokine receptors. VITAMINS AND HORMONES 2023; 123:645-662. [PMID: 37718001 DOI: 10.1016/bs.vh.2023.05.005] [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] [Indexed: 09/19/2023]
Abstract
Membrane proteins such as G protein-coupled receptors (GPCRs) are involved in awide range of physiological and pathological cellular processes. Binding of extracellular signals to GPCRs, including hormones, neurotransmitters, peptides and proteins, can activate intracellular signaling cascades via G protein interaction. Chemokine receptors are key GPCRs implicated in cancers, immune responses, cell migration and inflammation. Specifically, the CCR5 and CXCR4 chemokine receptors serve as important therapeutic targets against Human Immunodeficiency virus (HIV) entry into human cells. Maraviroc and Vicriviroc, two clinically used HIV entry inhibitors, are antagonists of the CCR5 receptor. These drugs block HIV entry, but ultimately resistance develops, due to emergence of viruses that can utilize the CXCR4 co-receptor. Unfortunately, development of chemokine receptor antagonists as selective drugs of HIV infection has been greatly hindered as their target orthosteric site is conserved among different receptor subtypes. Accordingly, it is important to understand the structural dynamics of these receptors to develop more effective therapeutics. In this chapter, we describe the latest advances in studies of these two key chemokine receptors with respect to their structures, dynamics and function.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Sana Akhter
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States.
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7
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Yang Y, Li J, Lei W, Wang H, Ni Y, Liu Y, Yan H, Tian Y, Wang Z, Yang Z, Yang S, Yang Y, Wang Q. CXCL12-CXCR4/CXCR7 Axis in Cancer: from Mechanisms to Clinical Applications. Int J Biol Sci 2023; 19:3341-3359. [PMID: 37497001 PMCID: PMC10367567 DOI: 10.7150/ijbs.82317] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 05/16/2023] [Indexed: 07/28/2023] Open
Abstract
Cancer is a multi-step disease caused by the accumulation of genetic mutations and/or epigenetic changes, and is the biggest challenge around the world. Cytokines, including chemokines, exhibit expression changes and disorders in all human cancers. These cytokine abnormalities can disrupt homeostasis and immune function, and make outstanding contributions to various stages of cancer development such as invasion, metastasis, and angiogenesis. Chemokines are a superfamily of small molecule chemoattractive cytokines that mediate a variety of cellular functions. Importantly, the interactions of chemokine members CXCL12 and its receptors CXCR4 and CXCR7 have a broad impact on tumor cell proliferation, survival, angiogenesis, metastasis, and tumor microenvironment, and thus participate in the onset and development of many cancers including leukemia, breast cancer, lung cancer, prostate cancer and multiple myeloma. Therefore, this review aims to summarize the latest research progress and future challenges regarding the role of CXCL12-CXCR4/CXCR7 signaling axis in cancer, and highlights the potential of CXCL12-CXCR4/CXCR7 as a biomarker or therapeutic target for cancer, providing essential strategies for the development of novel targeted cancer therapies.
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Affiliation(s)
- Yaru Yang
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Jiayan Li
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Wangrui Lei
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Haiying Wang
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Yunfeng Ni
- Department of Thoracic Surgery, Tangdu Hospital, The Airforce Medical University, Xi'an, China
| | - Yanqing Liu
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Huanle Yan
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Yifan Tian
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Zheng Wang
- Department of Cardiothoracic Surgery, Central Theater Command General Hospital of Chinese People's Liberation Army, Wuhan, China
| | - Zhi Yang
- Department of Thoracic Surgery, Tangdu Hospital, The Airforce Medical University, Xi'an, China
| | - Shulin Yang
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Yang Yang
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
| | - Qiang Wang
- Department of Orthopedics, Shenmu Hospital, Faculty of Life Sciences and Medicine, Northwest University, Shenmu, China
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education. Faculty of Life Sciences and Medicine, Northwest University, Xi'an, China
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8
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Zhao Y, Zhang J, Zhang H, Gu S, Deng Y, Tu Y, Hou T, Kang Y. Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems. J Phys Chem Lett 2023; 14:1103-1112. [PMID: 36700836 DOI: 10.1021/acs.jpclett.2c03688] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling long-standing challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value ∼30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 Å. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in ∼60% less simulation time.
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Affiliation(s)
- Yihao Zhao
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Jintu Zhang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Haotian Zhang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Shukai Gu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Yafeng Deng
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Yaoquan Tu
- Division of Theoretical Chemistry and Biology, Department of Chemistry, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Yu Kang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
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9
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Wang YT, Liao JM, Lin WW, Li CC, Huang BC, Cheng TL, Chen TC. Structural insights into Nirmatrelvir (PF-07321332)-3C-like SARS-CoV-2 protease complexation: a ligand Gaussian accelerated molecular dynamics study. Phys Chem Chem Phys 2022; 24:22898-22904. [PMID: 36124909 DOI: 10.1039/d2cp02882d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Coronavirus 3C-like protease (3CLpro) is found in SARS-CoV-2 virus, which causes COVID-19. 3CLpro controls virus replication and is a major target for target-based antiviral discovery. As reported by Pfizer, Nirmatrelvir (PF-07321332) is a competitive protein inhibitor and a clinical candidate for orally delivered medication. However, the binding mechanisms between Nirmatrelvir and 3CLpro complex structures remain unknown. This study incorporated ligand Gaussian accelerated molecular dynamics, the one-dimensional and two-dimensional potential of mean force, normal molecular dynamics, and Kramers' rate theory to determine the binding and dissociation rate constants (koff and kon) associated with the binding of the 3CLpro protein to the Nirmatrelvir inhibitor. The proposed approach addresses the challenges in designing small-molecule antiviral drugs.
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Affiliation(s)
- Yeng-Tseng Wang
- School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Taiwan. .,Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan
| | - Jun-Min Liao
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Wen-Wei Lin
- School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Taiwan. .,Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chia-Ching Li
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Bo-Cheng Huang
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Institute of Biomedical Sciences, National Sun Yat-Sen University, Kaohsiung, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Tian-Lu Cheng
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan.,Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Tun-Chieh Chen
- Department of Internal Medicine, College of Medicine, Kaohsiung Medical University, Taiwan
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10
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Pawnikar S, Miao Y. Mechanism of Peptide Agonist Binding in CXCR4 Chemokine Receptor. Front Mol Biosci 2022; 9:821055. [PMID: 35359589 PMCID: PMC8963245 DOI: 10.3389/fmolb.2022.821055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/14/2022] [Indexed: 01/07/2023] Open
Abstract
Chemokine receptors are key G-protein-coupled receptors (GPCRs) that control cell migration in immune system responses, development of cardiovascular and central nervous systems, and numerous diseases. In particular, the CXCR4 chemokine receptor promotes metastasis, tumor growth and angiogenesis in cancers. CXCR4 is also used as one of the two co-receptors for T-tropic HIV-1 entry into host cells. Therefore, CXCR4 serves as an important therapeutic target for treating cancers and HIV infection. Apart from the CXCL12 endogenous peptide agonist, previous studies suggested that the first 17 amino acids of CXCL12 are sufficient to activate CXCR4. Two 17-residue peptides with positions 1-4 mutated to RSVM and ASLW functioned as super and partial agonists of CXCR4, respectively. However, the mechanism of peptide agonist binding in CXCR4 remains unclear. Here, we have investigated this mechanism through all-atom simulations using a novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) method. The Pep-GaMD simulations have allowed us to explore representative binding conformations of each peptide and identify critical low-energy states of CXCR4 activated by the super versus partial peptide agonists. Our simulations have provided important mechanistic insights into peptide agonist binding in CXCR4, which are expected to facilitate rational design of new peptide modulators of CXCR4 and other chemokine receptors.
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11
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Do HN, Wang J, Bhattarai A, Miao Y. GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling. J Chem Theory Comput 2022; 18:1423-1436. [PMID: 35200019 PMCID: PMC9773012 DOI: 10.1021/acs.jctc.1c01055] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A1 receptor (A1AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A1AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.
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Affiliation(s)
- Hung N. Do
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Jinan Wang
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Apurba Bhattarai
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047
| | - Yinglong Miao
- The Center for Computational Biology and Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66047,Corresponding author:
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12
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Pawnikar S, Bhattarai A, Wang J, Miao Y. Binding Analysis Using Accelerated Molecular Dynamics Simulations and Future Perspectives. Adv Appl Bioinform Chem 2022; 15:1-19. [PMID: 35023931 PMCID: PMC8747661 DOI: 10.2147/aabc.s247950] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 02/20/2021] [Indexed: 12/12/2022] Open
Abstract
Biomolecular recognition such as binding of small molecules, nucleic acids, peptides and proteins to their target receptors plays key roles in cellular function and has been targeted for therapeutic drug design. Molecular dynamics (MD) is a computational approach to analyze these binding processes at an atomistic level, which provides valuable understandings of the mechanisms of biomolecular recognition. However, the rather slow biomolecular binding events often present challenges for conventional MD (cMD), due to limited simulation timescales (typically over hundreds of nanoseconds to tens of microseconds). In this regard, enhanced sampling methods, particularly accelerated MD (aMD), have proven useful to bridge the gap and enable all-atom simulations of biomolecular binding events. Here, we will review the recent method developments of Gaussian aMD (GaMD), ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD), which have greatly expanded our capabilities to simulate biomolecular binding processes. Spontaneous binding of various biomolecules to their receptors has been successfully simulated by GaMD. Microsecond LiGaMD and Pep-GaMD simulations have captured repetitive binding and dissociation of small-molecule ligands and highly flexible peptides, and thus enabled ligand/peptide binding thermodynamics and kinetics calculations. We will also present relevant application studies in simulations of important drug targets and future perspectives for rational computer-aided drug design.
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Affiliation(s)
- Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Apurba Bhattarai
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
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13
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Wang J, Lan L, Wu X, Xu L, Miao Y. Mechanism of RNA recognition by a Musashi RNA-binding protein. Curr Res Struct Biol 2021; 4:10-20. [PMID: 34988468 PMCID: PMC8695263 DOI: 10.1016/j.crstbi.2021.12.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 10/31/2021] [Accepted: 12/07/2021] [Indexed: 12/21/2022] Open
Abstract
The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology, University of Kansas, Lawrence, KS, 66047, USA
- Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Lan Lan
- Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Xiaoqing Wu
- Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
| | - Liang Xu
- Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
- Department of Radiation Oncology, The University of Kansas Cancer Center, Kansas City, KS, 66160, USA
| | - Yinglong Miao
- Center for Computational Biology, University of Kansas, Lawrence, KS, 66047, USA
- Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA
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Wang J, Arantes PR, Bhattarai A, Hsu RV, Pawnikar S, Huang YMM, Palermo G, Miao Y. Gaussian accelerated molecular dynamics (GaMD): principles and applications. WILEY INTERDISCIPLINARY REVIEWS. COMPUTATIONAL MOLECULAR SCIENCE 2021; 11:e1521. [PMID: 34899998 PMCID: PMC8658739 DOI: 10.1002/wcms.1521] [Citation(s) in RCA: 95] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 01/28/2021] [Indexed: 12/20/2022]
Abstract
Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, 2030 Becker Dr., Lawrence, KS, 66047, United States
| | - Pablo R Arantes
- Department of Bioengineering, University of California Riverside, 900 University Avenue, Riverside, CA 92512, United States
| | - Apurba Bhattarai
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, 2030 Becker Dr, Lawrence, KS, 66047, United States
| | - Rohaine V Hsu
- Department of Bioengineering, University of California Riverside, 900 University Avenue, Riverside, CA 92512, United States
| | - Shristi Pawnikar
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, 2030 Becker Dr., Lawrence, KS, 66047, United States
| | - Yu-Ming M Huang
- Department of Physics & Astronomy, Wayne State University, 666 W Hancock St, Detroit, MI 48207, USA
| | - Giulia Palermo
- Department of Bioengineering and Department of Chemistry, University of California Riverside, 900 University Avenue, Riverside, CA 92512, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, 2030 Becker Dr., Lawrence, Kansas 66047, United States
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Tang Z, Akhter S, Ramprasad A, Wang X, Reibarkh M, Wang J, Aryal S, Thota SS, Zhao J, Douglas JT, Gao P, Holmstrom ED, Miao Y, Wang J. Recognition of single-stranded nucleic acids by small-molecule splicing modulators. Nucleic Acids Res 2021; 49:7870-7883. [PMID: 34283224 PMCID: PMC8373063 DOI: 10.1093/nar/gkab602] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/24/2021] [Accepted: 07/01/2021] [Indexed: 12/16/2022] Open
Abstract
Risdiplam is the first approved small-molecule splicing modulator for the treatment of spinal muscular atrophy (SMA). Previous studies demonstrated that risdiplam analogues have two separate binding sites in exon 7 of the SMN2 pre-mRNA: (i) the 5'-splice site and (ii) an upstream purine (GA)-rich binding site. Importantly, the sequence of this GA-rich binding site significantly enhanced the potency of risdiplam analogues. In this report, we unambiguously determined that a known risdiplam analogue, SMN-C2, binds to single-stranded GA-rich RNA in a sequence-specific manner. The minimum required binding sequence for SMN-C2 was identified as GAAGGAAGG. We performed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which captured spontaneous binding of a risdiplam analogue to the target nucleic acids. We uncovered, for the first time, a ligand-binding pocket formed by two sequential GAAG loop-like structures. The simulation findings were highly consistent with experimental data obtained from saturation transfer difference (STD) NMR and structure-affinity-relationship studies of the risdiplam analogues. Together, these studies illuminate us to understand the molecular basis of single-stranded purine-rich RNA recognition by small-molecule splicing modulators with an unprecedented binding mode.
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Affiliation(s)
- Zhichao Tang
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
| | - Sana Akhter
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA
| | - Ankita Ramprasad
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
| | - Xiao Wang
- Analytical Research & Development, Merck and Co., Inc., Kenilworth, NJ 07033, USA
| | - Mikhail Reibarkh
- Analytical Research & Development, Merck and Co., Inc., Kenilworth, NJ 07033, USA
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA
| | - Sadikshya Aryal
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
| | - Srinivas S Thota
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
| | - Junxing Zhao
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
| | - Justin T Douglas
- Nuclear Magnetic Resonance Lab, University of Kansas, Lawrence, KS 66045, USA
| | - Philip Gao
- Protein Production Group, University of Kansas, Lawrence, KS 66047, USA
| | - Erik D Holmstrom
- Department of Molecular Biosciences and Department of Chemistry, University of Kansas, Lawrence, KS 66045, USA
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA
| | - Jingxin Wang
- Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66047, USA
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Do HN, Akhter S, Miao Y. Pathways and Mechanism of Caffeine Binding to Human Adenosine A 2A Receptor. Front Mol Biosci 2021; 8:673170. [PMID: 33987207 PMCID: PMC8111288 DOI: 10.3389/fmolb.2021.673170] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 03/24/2021] [Indexed: 11/13/2022] Open
Abstract
Caffeine (CFF) is a common antagonist to the four subtypes of adenosine G-protein-coupled receptors (GPCRs), which are critical drug targets for treating heart failure, cancer, and neurological diseases. However, the pathways and mechanism of CFF binding to the target receptors remain unclear. In this study, we have performed all-atom-enhanced sampling simulations using a robust Gaussian-accelerated molecular dynamics (GaMD) method to elucidate the binding mechanism of CFF to human adenosine A2A receptor (A2AAR). Multiple 500–1,000 ns GaMD simulations captured both binding and dissociation of CFF in the A2AAR. The GaMD-predicted binding poses of CFF were highly consistent with the x-ray crystal conformations with a characteristic hydrogen bond formed between CFF and residue N6.55 in the receptor. In addition, a low-energy intermediate binding conformation was revealed for CFF at the receptor extracellular mouth between ECL2 and TM1. While the ligand-binding pathways of the A2AAR were found similar to those of other class A GPCRs identified from previous studies, the ECL2 with high sequence divergence serves as an attractive target site for designing allosteric modulators as selective drugs of the A2AAR.
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Affiliation(s)
- Hung N Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Sana Akhter
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
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Wall H. Welcome to volume 13 of Future Medicinal Chemistry. Future Med Chem 2021; 13:1-3. [PMID: 33319591 DOI: 10.4155/fmc-2020-0338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Harriet Wall
- Future Science Group, Unitec House, 2 Albert Place, London, N3 1QB, UK
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Conrad M, Söldner CA, Miao Y, Sticht H. Agonist Binding and G Protein Coupling in Histamine H 2 Receptor: A Molecular Dynamics Study. Int J Mol Sci 2020; 21:ijms21186693. [PMID: 32932742 PMCID: PMC7554837 DOI: 10.3390/ijms21186693] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 09/04/2020] [Accepted: 09/08/2020] [Indexed: 02/06/2023] Open
Abstract
The histamine H2 receptor (H2R) plays an important role in the regulation of gastric acid secretion. Therefore, it is a main drug target for the treatment of gastroesophageal reflux or peptic ulcer disease. However, there is as of yet no 3D-structural information available hampering a mechanistic understanding of H2R. Therefore, we created a model of the histamine-H2R-Gs complex based on the structure of the ternary complex of the β2-adrenoceptor and investigated the conformational stability of this active GPCR conformation. Since the physiologically relevant motions with respect to ligand binding and conformational changes of GPCRs can only partly be assessed on the timescale of conventional MD (cMD) simulations, we also applied metadynamics and Gaussian accelerated molecular dynamics (GaMD) simulations. A multiple walker metadynamics simulation in combination with cMD was applied for the determination of the histamine binding mode. The preferential binding pose detected is in good agreement with previous data from site directed mutagenesis and provides a basis for rational ligand design. Inspection of the H2R-Gs interface reveals a network of polar interactions that may contribute to H2R coupling selectivity. The cMD and GaMD simulations demonstrate that the active conformation is retained on a μs-timescale in the ternary histamine-H2R-Gs complex and in a truncated complex that contains only Gs helix α5 instead of the entire G protein. In contrast, histamine alone is unable to stabilize the active conformation, which is in line with previous studies of other GPCRs.
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Affiliation(s)
- Marcus Conrad
- Bioinformatik, Institut für Biochemie, Emil-Fischer-Centrum, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany; (M.C.); (C.A.S.)
| | - Christian A. Söldner
- Bioinformatik, Institut für Biochemie, Emil-Fischer-Centrum, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany; (M.C.); (C.A.S.)
| | - Yinglong Miao
- Department of Computational Biology and Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA;
| | - Heinrich Sticht
- Bioinformatik, Institut für Biochemie, Emil-Fischer-Centrum, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany; (M.C.); (C.A.S.)
- Correspondence:
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Miao Y, Bhattarai A, Wang J. Ligand Gaussian Accelerated Molecular Dynamics (LiGaMD): Characterization of Ligand Binding Thermodynamics and Kinetics. J Chem Theory Comput 2020; 16:5526-5547. [PMID: 32692556 DOI: 10.1021/acs.jctc.0c00395] [Citation(s) in RCA: 93] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Calculations of ligand binding free energies and kinetic rates are important for drug design. However, such tasks have proven challenging in computational chemistry and biophysics. To address this challenge, we have developed a new computational method, ligand Gaussian accelerated molecular dynamics (LiGaMD), which selectively boosts the ligand nonbonded interaction potential energy based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique. Another boost potential could be applied to the remaining potential energy of the entire system in a dual-boost algorithm (LiGaMD_Dual) to facilitate ligand binding. LiGaMD has been demonstrated on host-guest and protein-ligand binding model systems. Repetitive guest binding and unbinding in the β-cyclodextrin host were observed in hundreds-of-nanosecond LiGaMD_Dual simulations. The calculated guest binding free energies agreed excellently with experimental data with <1.0 kcal/mol errors. Compared with converged microsecond-time scale conventional molecular dynamics simulations, the sampling errors of LiGaMD_Dual simulations were also <1.0 kcal/mol. Accelerations of ligand kinetic rate constants in LiGaMD simulations were properly estimated using Kramers' rate theory. Furthermore, LiGaMD allowed us to capture repetitive dissociation and binding of the benzamidine inhibitor in trypsin within 1 μs simulations. The calculated ligand binding free energy and kinetic rate constants compared well with the experimental data. In summary, LiGaMD provides a powerful enhanced sampling approach for characterizing ligand binding thermodynamics and kinetics simultaneously, which is expected to facilitate computer-aided drug design.
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Affiliation(s)
- Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Apurba Bhattarai
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States
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