1
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Scrima S, Lambrughi M, Tiberti M, Fadda E, Papaleo E. ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167260. [PMID: 38782304 DOI: 10.1016/j.bbadis.2024.167260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/30/2024] [Accepted: 05/18/2024] [Indexed: 05/25/2024]
Abstract
Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from a molecular dynamics simulation in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.
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Affiliation(s)
- Simone Scrima
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Lambrughi
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Elisa Fadda
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, co. Kildare, Ireland
| | - Elena Papaleo
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark.
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2
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Tang W, Shen T, Chen Z. In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism. Front Chem 2024; 12:1404573. [PMID: 38957406 PMCID: PMC11217521 DOI: 10.3389/fchem.2024.1404573] [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: 03/21/2024] [Accepted: 05/31/2024] [Indexed: 07/04/2024] Open
Abstract
Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.
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Affiliation(s)
| | | | - Zhoumiao Chen
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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3
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Saravanan V, Ahammed I, Bhattacharya A, Bhattacharya S. Uncovering allostery and regulation in SORCIN through molecular dynamics simulations. J Biomol Struct Dyn 2024; 42:1812-1825. [PMID: 37098805 DOI: 10.1080/07391102.2023.2202772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 04/08/2023] [Indexed: 04/27/2023]
Abstract
Soluble resistance-related calcium-binding protein or Sorcin is an allosteric, calcium-binding Penta-EF hand (PEF) family protein implicated in multi-drug resistant cancers. Sorcin is known to bind chemotherapeutic molecules such as Doxorubicin. This study uses in-silico molecular dynamics simulations to explore the dynamics and allosteric behavior of Sorcin in the context of Ca2+ uptake and Doxorubicin binding. The results show that Ca2+ binding induces large, but reversible conformational changes in the Sorcin structure which manifest as rigid body reorientations that preserve the local secondary structure. A reciprocal allosteric handshake centered around the EF5 hand is found to be key in Sorcin dimer formation and stabilization. Binding of Doxorubicin results in rearrangement of allosteric communities which disrupts long-range allosteric information transfer from the N-terminal domain to the middle lobe. However, this binding does not result in secondary structure destabilization. Sorcin does not appear to have a distinct Ca2+ activated mode of Doxorubicin binding.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Vinnarasi Saravanan
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Ijas Ahammed
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Akash Bhattacharya
- Visiting Assistant Professor of Physics, St. Mary's University, San Antonio, Texas, USA
| | - Swati Bhattacharya
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India
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4
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Xiang J, Pompetti AJ, Faranda AP, Wang Y, Novo SG, Li DWC, Duncan MK. ATF4 May Be Essential for Adaption of the Ocular Lens to Its Avascular Environment. Cells 2023; 12:2636. [PMID: 37998373 PMCID: PMC10670291 DOI: 10.3390/cells12222636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 10/30/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023] Open
Abstract
The late embryonic mouse lens requires the transcription factor ATF4 for its survival although the underlying mechanisms were unknown. Here, RNAseq analysis revealed that E16.5 Atf4 null mouse lenses downregulate the mRNA levels of lens epithelial markers as well as known markers of late lens fiber cell differentiation. However, a comparison of this list of differentially expressed genes (DEGs) with other known transcriptional regulators of lens development indicated that ATF4 expression is not directly controlled by the previously described lens gene regulatory network. Pathway analysis revealed that the Atf4 DEG list was enriched in numerous genes involved in nutrient transport, amino acid biosynthesis, and tRNA charging. These changes in gene expression likely result in the observed reductions in lens free amino acid and glutathione levels, which would result in the observed low levels of extractable lens protein, finally leading to perinatal lens disintegration. These data demonstrate that ATF4, via its function in the integrated stress response, is likely to play a crucial role in mediating the adaption of the lens to the avascularity needed to maintain lens transparency.
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Affiliation(s)
- Jiawen Xiang
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
- The State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510230, China
| | - Anthony J. Pompetti
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Adam P. Faranda
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Yan Wang
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - Samuel G. Novo
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
| | - David Wan-Cheng Li
- The State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510230, China
| | - Melinda K. Duncan
- Department of Biological Sciences, University of Delaware, Newark, DE 19716, USA
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5
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Manna B, Chanda P, Datta S, Ghosh A. Elucidating the Ionic Liquid-Induced Mixed Inhibition of GH1 β-Glucosidase H0HC94. J Phys Chem B 2023; 127:8406-8416. [PMID: 37751511 DOI: 10.1021/acs.jpcb.3c02125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Deciphering the ionic liquid (IL) tolerance of glycoside hydrolases (GHs) to improve their hydrolysis efficiency for fermentable sugar synthesis in the "one-pot" process has long been a hurdle for researchers. In this work, we employed experimental and theoretical approaches to investigate the 1-ethyl-3-methylimidazolium acetate ([C2C1im][MeCO2])-induced inhibition of GH1 β-glucosidase (H0HC94) from Agrobacterium tumefaciens 5A. At 10-15% [C2C1im][MeCO2] concentration, H0HC94 experiences competitive inhibition (R2 = 0.97, alpha = 2.8). As the IL content increased to 20-25%, the inhibition pattern shifted to mixed-type inhibition (R2 = 0.98, alpha = 3.4). These findings were further confirmed through characteristic inhibition plots using Lineweaver-Burk plots. Atomistic molecular dynamics simulations conducted with 0% [C2C1im][MeCO2], 10% [C2C1im][MeCO2], and 25% [C2C1im][MeCO2] revealed the accumulation of [C2C1im]+ at the negatively charged active site of H0HC94 in 10% [C2C1im][MeCO2], supporting the occurrence of competitive inhibition at lower IL concentrations. At higher IL concentrations, the cations and anions bound to the secondary binding sites (SBSs) of H0HC94, leading to a tertiary conformational change, as captured by the principal component analysis based on the free-energy landscape and protein structure networks. The altered conformation of H0HC94 affected the interaction with [C2C1im][MeCO2], which could possibly shift the inhibition from competitive to more mixed-type (competitive + noncompetitive) inhibition, as observed in the experiments. For the first time, we report a combined experimental and theoretical insight behind the mixed inhibition of a GH1 β-glucosidase. Our findings indicated the role of SBS in IL-induced inhibition, which could aid in developing more IL-tolerant β-glucosidases for biorefinery applications.
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Affiliation(s)
- Bharat Manna
- Protein Engineering Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal741246, India
| | - Pinaki Chanda
- Protein Engineering Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal741246, India
| | - Supratim Datta
- Protein Engineering Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal741246, India
- Center for the Advanced Functional Materials, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
- Center for the Climate and Environmental Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Amit Ghosh
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
- P.K. Sinha Centre for Bioenergy and Renewables, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
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6
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Dean E, Dominique A, Palillero A, Tran A, Paradis N, Wu C. Probing the Activation Mechanisms of Agonist DPI-287 to Delta-Opioid Receptor and Novel Agonists Using Ensemble-Based Virtual Screening with Molecular Dynamics Simulations. ACS OMEGA 2023; 8:32404-32423. [PMID: 37720760 PMCID: PMC10500586 DOI: 10.1021/acsomega.3c01918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 08/16/2023] [Indexed: 09/19/2023]
Abstract
Pain drugs targeting mu-opioid receptors face major addiction problems that have caused an epidemic. The delta-opioid receptor (DOR) has shown to not cause addictive effects when bound to an agonist. While the active conformation of the DOR in complex with agonist DPI-287 has been recently solved, there are still no FDA-approved agonists targeting it, providing the opportunity for structure-based virtual screening. In this study, the conformational plasticity of the DOR was probed using molecular dynamics (MD) simulations, identifying two representative conformations from clustering analysis. The two MD conformations as well as the crystal conformation of DOR were used to screen novel compounds from the ZINC database (17 million compounds), in which 69 drugs were picked as potential compounds based on their docking scores. Notably, 37 out of the 69 compounds were obtained from the simulated conformations. The binding stability of the 69 compounds was further investigated using MD simulations. Based on the MM-GBSA binding energy and the predicted drug properties, eight compounds were chosen as the most favorable, six of which were from the simulated conformations. Using a dynamic network model, the communication between the crystal agonist and the top eight molecules with the receptor was analyzed to confirm if these novel compounds share a similar activation mechanism to the crystal ligand. Encouragingly, docking of these eight compounds to the other two opioid receptors (kappa and mu) suggests their good selectivity toward DOR.
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Affiliation(s)
- Emily Dean
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - AnneMarie Dominique
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Americus Palillero
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Annie Tran
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Nicholas Paradis
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
| | - Chun Wu
- Department of Molecular &
Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, New Jersey 08028, United States
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7
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Diaz de Greñu B, Fernández-Aroca DM, Organero JA, Durá G, Jalón FA, Sánchez-Prieto R, Ruiz-Hidalgo MJ, Rodríguez AM, Santos L, Albasanz JL, Manzano BR. Ferrozoles: Ferrocenyl derivatives of letrozole with dual effects as potent aromatase inhibitors and cytostatic agents. J Biol Inorg Chem 2023; 28:531-547. [PMID: 37458856 DOI: 10.1007/s00775-023-02006-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 06/07/2023] [Indexed: 08/11/2023]
Abstract
In the treatment of hormone-dependent cancers, aromatase inhibitors (AI) are receiving increased attention due to some undesirable effects such as the risk of endometrial cancer and thromboembolism of SERMs (selective estrogen receptor modulators). Letrozole is the most active AI with 99% aromatase inhibition. Unfortunately, this compound also exhibits some adverse effects such as hot flashes and fibromyalgias. Therefore, there is an urgent need to explore new types of AIs that retain the same-or even increased-antitumor ability. Inspired by the letrozole structure, a set of new derivatives has been synthesized that include a ferrocenyl moiety and different heterocycles. The derivative that contains a benzimidazole ring, namely compound 6, exhibits a higher aromatase inhibitory activity than letrozole and it also shows potent cytostatic behavior when compared to other well-established aromatase inhibitors, as demonstrated by dose-response, cell cycle, apoptosis and time course experiments. Furthermore, 6 promotes the inhibition of cell growth in both an aromatase-dependent and -independent fashion, as indicated by the study of A549 and MCF7 cell lines. Molecular docking and molecular dynamics calculations on the interaction of 6 or letrozole with the aromatase binding site revealed that the ferrocene moiety increases the van der Waals and hydrophobic interactions, thus resulting in an increase in binding affinity. Furthermore, the iron atom of the ferrocene fragment can form a metal-acceptor interaction with a propionate fragment, and this results in a stronger coupling with the heme group-a possibility that is consistent with the strong aromatase inhibition of 6.
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Affiliation(s)
- Borja Diaz de Greñu
- Departamento de Química Inorgánica, Orgánica y Bioquímica, Facultad de Ciencias y Tecnologías Químicas, IRICA, Universidad de Castilla-La Mancha, Avda. C. J Cela, 10, 13071, Ciudad Real, Spain
| | - Diego M Fernández-Aroca
- Laboratorio de Oncología Molecular, Unidad de Medicina Molecular, Centro Regional de Investigaciones Biomédicas, Universidad de Castilla-La Mancha, Unidad Asociada de Biomedicina UCLM, Unidad Asociada al CSIC, Albacete, Spain
| | - Juan A Organero
- Departamento de Química Física, Facultad de Ciencias Ambientales y Bioquímicas and INAMOL, Universidad de Castilla-La Mancha, 45071, Toledo, Spain
| | - Gema Durá
- Departamento de Química Inorgánica, Orgánica y Bioquímica, Facultad de Ciencias y Tecnologías Químicas, IRICA, Universidad de Castilla-La Mancha, Avda. C. J Cela, 10, 13071, Ciudad Real, Spain
| | - Felix Angel Jalón
- Departamento de Química Inorgánica, Orgánica y Bioquímica, Facultad de Ciencias y Tecnologías Químicas, IRICA, Universidad de Castilla-La Mancha, Avda. C. J Cela, 10, 13071, Ciudad Real, Spain
| | - Ricardo Sánchez-Prieto
- Laboratorio de Oncología Molecular, Unidad de Medicina Molecular, Centro Regional de Investigaciones Biomédicas, Universidad de Castilla-La Mancha, Unidad Asociada de Biomedicina UCLM, Unidad Asociada al CSIC, Albacete, Spain
- Departamento de Biología del Cáncer, Instituto de Investigaciones Biomédicas Alberto Sols (CSIC-UAM), Madrid, Spain
- Unidad Asociada de Biomedicina UCLM, Unidad Asociada al CSIC, Albacete, Spain
| | - M José Ruiz-Hidalgo
- Laboratorio de Oncología Molecular, Unidad de Medicina Molecular, Centro Regional de Investigaciones Biomédicas, Universidad de Castilla-La Mancha, Unidad Asociada de Biomedicina UCLM, Unidad Asociada al CSIC, Albacete, Spain
- Área de Bioquímica y Biología Molecular, Departamento de Química Inorgánica, Orgánica y Bioquímica, Facultad de Medicina, Universidad de Castilla-La Mancha, Albacete, Spain
| | - Ana María Rodríguez
- Departamento de Q. Inorgánica, Orgánica y Bioquímica, IRICA, Escuela Técnica Superior de Ingenieros Industriales, Universidad de Castilla-La Mancha, Avda. C. J. Cela, 3, 13071, Ciudad Real, Spain
| | - Lucia Santos
- Departamento de Q. Física, Facultad de Ciencias y Tecnologías Químicas, Universidad de Castilla-La Mancha, Avda. C. J. Cela, S/N, 13071, Ciudad Real, Spain
| | - José L Albasanz
- Department of Inorganic and Organic Chemistry and Biochemistry, Faculty of Chemical and Technological Sciences, School of Medicine of Ciudad Real, Regional Center of Biomedical Research (CRIB), University of Castilla-La Mancha (UCLM), 13071, Ciudad Real, Spain
| | - Blanca R Manzano
- Departamento de Química Inorgánica, Orgánica y Bioquímica, Facultad de Ciencias y Tecnologías Químicas, IRICA, Universidad de Castilla-La Mancha, Avda. C. J Cela, 10, 13071, Ciudad Real, Spain.
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8
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Sora V, Tiberti M, Beltrame L, Dogan D, Robbani SM, Rubin J, Papaleo E. PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles. J Chem Inf Model 2023; 63:4237-4245. [PMID: 37437128 DOI: 10.1021/acs.jcim.3c00574] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.
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Affiliation(s)
- Valentina Sora
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
- Cancer Systems Biology, Section of Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
| | - Ludovica Beltrame
- Cancer Systems Biology, Section of Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Deniz Dogan
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
| | - Shahriyar Mahdi Robbani
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
| | - Joshua Rubin
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
| | - Elena Papaleo
- Cancer Structural Biology, Danish Cancer Institute, Strandboulevarden 49, 2100 Copenhagen, Denmark
- Cancer Systems Biology, Section of Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
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9
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La Sala G, Pfleger C, Käck H, Wissler L, Nevin P, Böhm K, Janet JP, Schimpl M, Stubbs CJ, De Vivo M, Tyrchan C, Hogner A, Gohlke H, Frolov AI. Combining structural and coevolution information to unveil allosteric sites. Chem Sci 2023; 14:7057-7067. [PMID: 37389247 PMCID: PMC10306073 DOI: 10.1039/d2sc06272k] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/02/2023] [Indexed: 07/01/2023] Open
Abstract
Understanding allosteric regulation in biomolecules is of great interest to pharmaceutical research and computational methods emerged during the last decades to characterize allosteric coupling. However, the prediction of allosteric sites in a protein structure remains a challenging task. Here, we integrate local binding site information, coevolutionary information, and information on dynamic allostery into a structure-based three-parameter model to identify potentially hidden allosteric sites in ensembles of protein structures with orthosteric ligands. When tested on five allosteric proteins (LFA-1, p38-α, GR, MAT2A, and BCKDK), the model successfully ranked all known allosteric pockets in the top three positions. Finally, we identified a novel druggable site in MAT2A confirmed by X-ray crystallography and SPR and a hitherto unknown druggable allosteric site in BCKDK validated by biochemical and X-ray crystallography analyses. Our model can be applied in drug discovery to identify allosteric pockets.
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Affiliation(s)
- Giuseppina La Sala
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Christopher Pfleger
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf 40225 Düsseldorf Germany
| | - Helena Käck
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Lisa Wissler
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Philip Nevin
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Kerstin Böhm
- Discovery Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Jon Paul Janet
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Marianne Schimpl
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Cambridge UK
| | - Christopher J Stubbs
- Mechanistic and Structural Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca Cambridge UK
| | - Marco De Vivo
- Laboratory of Molecular Modeling and Drug Design, Istituto Italiano di Tecnologia Via Morego 30 16163 Genoa Italy
| | - Christian Tyrchan
- Medicinal Chemistry, Research and Early Development, Respiratory & Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Anders Hogner
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
| | - Holger Gohlke
- Mathematisch-Naturwissenschaftliche Fakultät, Institut für Pharmazeutische und Medizinische Chemie, Heinrich-Heine-Universität Düsseldorf 40225 Düsseldorf Germany
- John von Neumann Institute for Computing (NIC), Jülich Supercomputing Centre (JSC), Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Institute of Bio- and Geosciences (IBG-4: Bioinformatics) Forschungszentrum Jülich GmbH 52425 Jülich Germany
| | - Andrey I Frolov
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden
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10
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Maschietto F, Morzan UN, Tofoleanu F, Gheeraert A, Chaudhuri A, Kyro GW, Nekrasov P, Brooks B, Loria JP, Rivalta I, Batista VS. Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase. Nat Commun 2023; 14:2239. [PMID: 37076500 PMCID: PMC10115891 DOI: 10.1038/s41467-023-37956-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.
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Affiliation(s)
- Federica Maschietto
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
| | - Uriel N Morzan
- International Center for Theoretical Physics, Strada Costiera 11, 34151, Trieste, Italy.
| | - Florentina Tofoleanu
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
- Treeline Biosciences, 500 Arsenal Street, Watertown, MA, 02472, USA
| | - Aria Gheeraert
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy
| | - Apala Chaudhuri
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gregory W Kyro
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Peter Nekrasov
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Bernard Brooks
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
| | - J Patrick Loria
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
| | - Ivan Rivalta
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France.
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy.
| | - Victor S Batista
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
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11
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Han Z, Wang X, Wu Z, Li C. Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses. J Phys Chem Lett 2023; 14:3452-3460. [PMID: 37010935 DOI: 10.1021/acs.jpclett.3c00366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We propose an improved transfer entropy approach called the dynamic version of the force constant fitted Gaussian network model based on molecular dynamics ensemble (dfcfGNMMD) to explore the allosteric mechanism of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS), one of the aminoacyl-tRNA synthetases that play a crucial role in translation of the genetic code. The dfcfGNMMD method can provide reliable estimates of the transfer entropy and give new insights into the role of the anticodon binding domain in driving the catalytic domain in aminoacylation activity and into the effects of tRNA binding and residue mutation on the enzyme activity, revealing the causal mechanism of the allosteric communication in hmPheRS. In addition, we incorporate the residue dynamic and co-evolutionary information to further investigate the key residues in hmPheRS allostery. This study sheds light on the mechanisms of hmPheRS allostery and can provide important information for related drug design.
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Affiliation(s)
- Zhongjie Han
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Xiaoli Wang
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Zhixiang Wu
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Chunhua Li
- Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing 100124, China
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12
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Felline A, Gentile S, Fanelli F. psnGPCRdb: The Structure-network Database of G Protein Coupled Receptors. J Mol Biol 2023:167950. [PMID: 36646374 DOI: 10.1016/j.jmb.2023.167950] [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: 11/30/2022] [Revised: 01/02/2023] [Accepted: 01/03/2023] [Indexed: 01/15/2023]
Abstract
G protein coupled receptors (GPCRs) are critical eukaryotic signal transduction gatekeepers and represent the largest protein superfamily in the human proteome, with more than 800 members. They share seven transmembrane helices organized in an up-down bundle architecture. GPCR-mediated signaling pathways have been linked to numerous human diseases, and GPCRs are the targets of approximately 35% of all drugs currently on the market. Structure network analysis, a graph theory-based approach, represents a cutting-edge tool to deeply understand GPCR function, which strongly relies on communication between the extracellular and intracellular poles of their structure. psnGPCRdb stores the structure networks (i.e., linked nodes, hubs, communities and communication pathways) computed on all updated GPCR structures in the Protein Data Bank, in their isolated states or in complex with extracellular and/or intracellular molecules. The structure communication signatures of a sub-family or family of GPCRs as well as of their small-molecule activators or inhibitors are stored as consensus networks. The database stores also all meaningful structure network-based comparisons (i.e., difference networks) of functionally different states (i.e., inactive or active) of a given receptor sub-type, or of consensus networks representative of a receptor sub-type, type, sub-family or family. Single or consensus GPCR networks hold also information on amino acid conservation. The database allows to graphically analyze 3D structure networks together with interactive data-tables. Ligand-centric networks can be analyzed as well. psnGPCRdb is unique and represents a powerful resource to unravel GPCR function with important implications in cell signaling and drug design. psnGPCRdb is freely available at: http://webpsn.hpc.unimo.it/psngpcr.php.
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Affiliation(s)
- Angelo Felline
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campy 103, 41125 Modena, Italy
| | - Sara Gentile
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campy 103, 41125 Modena, Italy
| | - Francesca Fanelli
- Department of Life Sciences, University of Modena and Reggio Emilia, via Campy 103, 41125 Modena, Italy; Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, via Campi 287, 41125 Modena, Italy.
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13
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Panigrahi R, Kailasam S. Mapping allosteric pathway in NIa-Pro using computational approach. QUANTITATIVE BIOLOGY 2023. [DOI: 10.15302/j-qb-022-0296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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14
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Kumari M, Singh R, Subbarao N. Exploring the interaction mechanism between potential inhibitor and multi-target Mur enzymes of mycobacterium tuberculosis using molecular docking, molecular dynamics simulation, principal component analysis, free energy landscape, dynamic cross-correlation matrices, vector movements, and binding free energy calculation. J Biomol Struct Dyn 2022; 40:13497-13526. [PMID: 34662260 DOI: 10.1080/07391102.2021.1989040] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Multi-targeting enzyme approaches are considered to be the most significant in suppressing pathogen growth and disease control for MDR and XDR-resistant Mycobacterium tuberculosis. The multiple Mur enzymes involved in peptidoglycan biosynthesis play a key role in a cell's growth. Firstly, homology modeling was employed to construct the 3 D structure of the Mur enzymes. The computational approaches, including molecular docking and molecular dynamics simulations and MM-PBSA methods, were performed to explore the detailed interaction mechanism to evaluate the inhibitory activity against targeted proteins. The computational calculations revealed that the best-docked phytochemical compound (gallomyricitrin) inhibits the selected targets: Mur enzymes by forming stable hydrogen bonds. The analysis of RMSD, RMSF, Rg, PCA, DCCM, cross-correlation network, FEL, H-bond, and vector movement reveal that the docked complex of MurA, MurI, MurG, MurC, and MurE is more stable compared to MurB, MurF, MurD, and MurX docked complexes during MD simulations. Moreover, FEL exposed that gallomyricitrin stabilized to the minimum global energy of Mur Enzymes. The PCA, DCCM, and vector movements and binding free energy results provided further evidence for the stability of gallomyricitrin's interactions inside the binding sites by forming hydrogen bonds. The cross-correlation analysis reveals that Mur enzymes exhibit a positive and negative correlated motion between residues in different protein domains. The computational results contribute in several ways to our understanding of inhibition activity and provide a basic insight into the binding activity of gallomyricitrin as a multi-target drug for tuberculosis. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Madhulata Kumari
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Ruhar Singh
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Naidu Subbarao
- School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India
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15
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Ning S, Wang H, Zeng C, Zhao Y. Prediction of allosteric druggable pockets of cyclin-dependent kinases. Brief Bioinform 2022; 23:6643454. [PMID: 35830869 DOI: 10.1093/bib/bbac290] [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: 05/04/2022] [Revised: 06/07/2022] [Accepted: 06/24/2022] [Indexed: 11/13/2022] Open
Abstract
Cyclin-dependent kinase (Cdk) proteins play crucial roles in the cell cycle progression and are thus attractive drug targets for therapy against such aberrant cell cycle processes as cancer. Since most of the available Cdk inhibitors target the highly conserved catalytic ATP pocket and their lack of specificity often lead to side effects, it is imperative to identify and characterize less conserved non-catalytic pockets capable of interfering with the kinase activity allosterically. However, a systematic analysis of these allosteric druggable pockets is still in its infancy. Here, we summarize the existing Cdk pockets and their selectivity. Then, we outline a network-based pocket prediction approach (NetPocket) and illustrate its utility for systematically identifying the allosteric druggable pockets with case studies. Finally, we discuss potential future directions and their challenges.
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Affiliation(s)
- Shangbo Ning
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China
| | - Huiwen Wang
- School of Physics and Engineering, Henan University of Science and Technology, Luoyang 471023, China
| | - Chen Zeng
- Department of Physics, The George Washington University, Washington, DC 20052, USA
| | - Yunjie Zhao
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China
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16
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Wu N, Yaliraki SN, Barahona M. Prediction of Protein Allosteric Signalling Pathways and Functional Residues Through Paths of Optimised Propensity. J Mol Biol 2022; 434:167749. [PMID: 35841931 DOI: 10.1016/j.jmb.2022.167749] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 07/09/2022] [Accepted: 07/11/2022] [Indexed: 11/28/2022]
Abstract
Allostery commonly refers to the mechanism that regulates protein activity through the binding of a molecule at a different, usually distal, site from the orthosteric site. The omnipresence of allosteric regulation in nature and its potential for drug design and screening render the study of allostery invaluable. Nevertheless, challenges remain as few computational methods are available to effectively predict allosteric sites, identify signalling pathways involved in allostery, or to aid with the design of suitable molecules targeting such sites. Recently, bond-to-bond propensity analysis has been shown successful at identifying allosteric sites for a large and diverse group of proteins from knowledge of the orthosteric sites and its ligands alone by using network analysis applied to energy-weighted atomistic protein graphs. To address the identification of signalling pathways, we propose here a method to compute and score paths of optimised propensity that link the orthosteric site with the identified allosteric sites, and identifies crucial residues that contribute to those paths. We showcase the approach with three well-studied allosteric proteins: h-Ras, caspase-1, and 3-phosphoinositide-dependent kinase-1 (PDK1). Key residues in both orthosteric and allosteric sites were identified and showed agreement with experimental results, and pivotal signalling residues along the pathway were also revealed, thus providing alternative targets for drug design. By using the computed path scores, we were also able to differentiate the activity of different allosteric modulators.
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Affiliation(s)
- Nan Wu
- Department of Chemistry Imperial College London, United Kingdom
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17
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Archaeal Lipids Regulating the Trimeric Structure Dynamics of Bacteriorhodopsin for Efficient Proton Release and Uptake. Int J Mol Sci 2022; 23:ijms23136913. [PMID: 35805918 PMCID: PMC9278134 DOI: 10.3390/ijms23136913] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/19/2022] [Accepted: 06/20/2022] [Indexed: 11/30/2022] Open
Abstract
S-TGA-1 and PGP-Me are native archaeal lipids associated with the bacteriorhodopsin (bR) trimer and contribute to protein stabilization and native dynamics for proton transfer. However, little is known about the underlying molecular mechanism of how these lipids regulate bR trimerization and efficient photocycling. Here, we explored the specific binding of S-TGA-1 and PGP-Me with the bR trimer and elucidated how specific interactions modulate the bR trimeric structure and proton release and uptake using long-term atomistic molecular dynamic simulations. Our results showed that S-TGA-1 and PGP-Me are essential for stabilizing the bR trimer and maintaining the coherent conformational dynamics necessary for proton transfer. The specific binding of S-TGA-1 with W80 and K129 regulates proton release on the extracellular surface by forming a “Glu-shared” model. The interaction of PGP-Me with K40 ensures proton uptake by accommodating the conformation of the helices to recruit enough water molecules on the cytoplasmic side. The present study results could fill in the theoretical gaps of studies on the functional role of archaeal lipids and could provide a reference for other membrane proteins containing similar archaeal lipids.
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18
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Cancer-related Mutations with Local or Long-range Effects on an Allosteric Loop of p53. J Mol Biol 2022; 434:167663. [PMID: 35659507 DOI: 10.1016/j.jmb.2022.167663] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/19/2022] [Accepted: 05/25/2022] [Indexed: 12/31/2022]
Abstract
The tumor protein 53 (p53) is involved in transcription-dependent and independent processes. Several p53 variants related to cancer have been found to impact protein stability. Other variants, on the contrary, might have little impact on structural stability and have local or long-range effects on the p53 interactome. Our group previously identified a loop in the DNA binding domain (DBD) of p53 (residues 207-213) which can recruit different interactors. Experimental structures of p53 in complex with other proteins strengthen the importance of this interface for protein-protein interactions. We here characterized with structure-based approaches somatic and germline variants of p53 which could have a marginal effect in terms of stability and act locally or allosterically on the region 207-213 with consequences on the cytosolic functions of this protein. To this goal, we studied 1132 variants in the p53 DBD with structure-based approaches, accounting also for protein dynamics. We focused on variants predicted with marginal effects on structural stability. We then investigated each of these variants for their impact on DNA binding, dimerization of the p53 DBD, and intramolecular contacts with the 207-213 region. Furthermore, we identified variants that could modulate long-range the conformation of the region 207-213 using a coarse-grain model for allostery and all-atom molecular dynamics simulations. Our predictions have been further validated using enhanced sampling methods for 15 variants. The methodologies used in this study could be more broadly applied to other p53 variants or cases where conformational changes of loop regions are essential in the function of disease-related proteins.
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19
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Xiao F, Zhou Z, Song X, Gan M, Long J, Verkhivker G, Hu G. Dissecting mutational allosteric effects in alkaline phosphatases associated with different Hypophosphatasia phenotypes: An integrative computational investigation. PLoS Comput Biol 2022; 18:e1010009. [PMID: 35320273 PMCID: PMC8979438 DOI: 10.1371/journal.pcbi.1010009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/04/2022] [Accepted: 03/10/2022] [Indexed: 11/18/2022] Open
Abstract
Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the ALPL mutations showed a significant difference between the control, mild and severe HPP phenotypes. Molecular dynamics simulations coupled with protein structure network analysis were employed to analyze the effect of single-residue variation on conformational dynamics of TNSALP dimers, and the developed machine learning model suggested that the topological network parameters could serve as a robust indicator of severe mutations. The results indicated that the severity of disease-associated mutations is often linked with mutation-induced modulation of allosteric communications in the protein. This study suggested that ALPL mutations associated with mild and more severe HPPs can exert markedly distinct effects on the protein stability and long-range network communications. By linking the disease phenotypes with dynamic and allosteric molecular signatures, the proposed integrative computational approach enabled to characterize and quantify the allosteric effects of ALPL mutations and role of allostery in the pathogenesis of HPPs.
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Affiliation(s)
- Fei Xiao
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Ziyun Zhou
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Xingyu Song
- Department of Chemistry, Multiscale Research Institute of Complex Systems and Institute of Biomedical Sciences, Fudan University, Shanghai, China
| | - Mi Gan
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Jie Long
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Gennady Verkhivker
- Department of Computational and Data Sciences, Chapman University, One University Drive, Orange, California, United States of America
- Department of Biomedical and Pharmaceutical Sciences, Chapman University Pharmacy School 9401 Jeronimo Rd, Irvine, California, United States of America
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
- * E-mail:
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20
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Yao XQ, Hamelberg D. From Distinct to Differential Conformational Dynamics to Map Allosteric Communication Pathways in Proteins. J Phys Chem B 2022; 126:2612-2620. [PMID: 35319195 DOI: 10.1021/acs.jpcb.2c00199] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Initiation of biological processes involving protein-ligand binding, transient protein-protein interactions, or amino acid modifications alters the conformational dynamics of proteins. Accompanying these biological processes are ensuing coupled atomic level conformational changes within the proteins. These conformational changes collectively connect multiple amino acid residues at distal allosteric, binding, and/or active sites. Local changes due to, for example, binding of a regulatory ligand at an allosteric site initiate the allosteric regulation. The allosteric signal propagates throughout the protein structure, causing changes at distal sites, activating, deactivating, or modifying the function of the protein. Hence, dynamical responses within protein structures to stimuli contain critical information on protein function. In this Perspective, we examine the description of allosteric regulation from protein dynamical responses and associated alternative and emerging computational approaches to map allosteric communication pathways between distal sites in proteins at the atomic level.
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Affiliation(s)
- Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
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21
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Ni D, Liu Y, Kong R, Yu Z, Lu S, Zhang J. Computational elucidation of allosteric communication in proteins for allosteric drug design. Drug Discov Today 2022; 27:2226-2234. [DOI: 10.1016/j.drudis.2022.03.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 01/22/2022] [Accepted: 03/17/2022] [Indexed: 02/07/2023]
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22
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Costa F, Guardiani C, Giacomello A. Molecular dynamics simulations suggest possible activation and deactivation pathways in the hERG channel. Commun Biol 2022; 5:165. [PMID: 35210539 PMCID: PMC8873449 DOI: 10.1038/s42003-022-03074-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 01/25/2022] [Indexed: 11/17/2022] Open
Abstract
The elusive activation/deactivation mechanism of hERG is investigated, a voltage-gated potassium channel involved in severe inherited and drug-induced cardiac channelopathies, including the Long QT Syndrome. Firstly, the available structural data are integrated by providing a homology model for the closed state of the channel. Secondly, molecular dynamics combined with a network analysis revealed two distinct pathways coupling the voltage sensor domain with the pore domain. Interestingly, some LQTS-related mutations known to impair the activation/deactivation mechanism are distributed along the identified pathways, which thus suggests a microscopic interpretation of their role. Split channels simulations clarify a surprising feature of this channel, which is still able to gate when a cut is introduced between the voltage sensor domain and the neighboring helix S5. In summary, the presented results suggest possible activation/deactivation mechanisms of non-domain-swapped potassium channels that may aid in biomedical applications. Costa et al. present the electro-mechanical coupling between the voltage sensor and pore domain of the hERG channel using a combination of molecular dynamics simulations and theoretical network analyses.
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Affiliation(s)
- Flavio Costa
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184, Rome, Italy
| | - Carlo Guardiani
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184, Rome, Italy
| | - Alberto Giacomello
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184, Rome, Italy.
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23
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Yao XQ, Hamelberg D. Residue–Residue Contact Changes during Functional Processes Define Allosteric Communication Pathways. J Chem Theory Comput 2022; 18:1173-1187. [DOI: 10.1021/acs.jctc.1c00669] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30302-3965, United States
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24
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Wu N, Strömich L, Yaliraki SN. Prediction of allosteric sites and signaling: Insights from benchmarking datasets. PATTERNS (NEW YORK, N.Y.) 2022; 3:100408. [PMID: 35079717 PMCID: PMC8767309 DOI: 10.1016/j.patter.2021.100408] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 09/06/2021] [Accepted: 11/15/2021] [Indexed: 12/12/2022]
Abstract
Allostery is a pervasive mechanism that regulates protein activity through ligand binding at a site different from the orthosteric site. The universality of allosteric regulation complemented by the benefits of highly specific and potentially non-toxic allosteric drugs makes uncovering allosteric sites invaluable. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis has successfully predicted allosteric sites in 19 of 20 cases using an energy-weighted atomistic graph. We here extended the analysis onto 432 structures of 146 proteins from two benchmarking datasets for allosteric proteins: ASBench and CASBench. We further introduced two statistical measures to account for the cumulative effect of high-propensity residues and the crucial residues in a given site. The allosteric site is recovered for 127 of 146 proteins (407 of 432 structures) knowing only the orthosteric sites or ligands. The quantitative analysis using a range of statistical measures enables better characterization of potential allosteric sites and mechanisms involved.
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Affiliation(s)
- Nan Wu
- Department of Chemistry, Imperial College London, London W12 0BZ, UK
| | - Léonie Strömich
- Department of Chemistry, Imperial College London, London W12 0BZ, UK
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25
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Guardiani C, Cecconi F, Chiodo L, Cottone G, Malgaretti P, Maragliano L, Barabash ML, Camisasca G, Ceccarelli M, Corry B, Roth R, Giacomello A, Roux B. Computational methods and theory for ion channel research. ADVANCES IN PHYSICS: X 2022; 7:2080587. [PMID: 35874965 PMCID: PMC9302924 DOI: 10.1080/23746149.2022.2080587] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/15/2022] [Indexed: 06/15/2023] Open
Abstract
Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.
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Affiliation(s)
- C. Guardiani
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Rome, Italy
| | - F. Cecconi
- CNR - Istituto dei Sistemi Complessi, Rome, Italy and Istituto Nazionale di Fisica Nucleare, INFN, Roma1 section. 00185, Roma, Italy
| | - L. Chiodo
- Department of Engineering, Campus Bio-Medico University, Rome, Italy
| | - G. Cottone
- Department of Physics and Chemistry-Emilio Segrè, University of Palermo, Palermo, Italy
| | - P. Malgaretti
- Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (IEK-11), Forschungszentrum Jülich, Erlangen, Germany
| | - L. Maragliano
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Ancona, Italy, and Center for Synaptic Neuroscience and Technology, Istituto Italiano di Tecnologia, Genova, Italy
| | - M. L. Barabash
- Department of Materials Science and Nanoengineering, Rice University, Houston, TX 77005, USA
| | - G. Camisasca
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Rome, Italy
- Dipartimento di Fisica, Università Roma Tre, Rome, Italy
| | - M. Ceccarelli
- Department of Physics and CNR-IOM, University of Cagliari, Monserrato 09042-IT, Italy
| | - B. Corry
- Research School of Biology, The Australian National University, Canberra, ACT 2600, Australia
| | - R. Roth
- Institut Für Theoretische Physik, Eberhard Karls Universität Tübingen, Tübingen, Germany
| | - A. Giacomello
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Rome, Italy
| | - B. Roux
- Department of Biochemistry & Molecular Biology, University of Chicago, Chicago IL, USA
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26
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Felline A, Seeber M, Fanelli F. PSNtools for standalone and web-based structure network analyses of conformational ensembles. Comput Struct Biotechnol J 2022; 20:640-649. [PMID: 35140884 PMCID: PMC8801349 DOI: 10.1016/j.csbj.2021.12.044] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 12/22/2021] [Accepted: 12/30/2021] [Indexed: 12/03/2022] Open
Abstract
Structure graphs, in which interacting amino acids/nucleotides correspond to linked nodes, represent cutting-edge tools to investigate macromolecular function. The graph-based approach defined as Protein Structure Network (PSN) was initially implemented in the Wordom software and subsequently in the webPSN server. PSNs are computed either on a molecular dynamics (MD) trajectory (PSN-MD) or on a single structure. In the latter case, information on atomic fluctuations is inferred from the Elastic Network Model-Normal Mode Analysis (ENM-NMA) (PSN-ENM). While Wordom performs both PSN-ENM and PSN-MD analyses but without output post-processing, the webPSN server performs only single-structure PSN-EMN but assisting the user in input setup and output analysis. Here we release for the first time the standalone software PSNtools, which allows calculation and post-processing of PSN analyses carried out either on single structures or on conformational ensembles. Relevant unique and novel features of PSNtools are either comparisons of two networks or computations of consensus networks on sets of homologous/analogous macromolecular structures or conformational ensembles. Network comparisons and consensus serve to infer differences in functionally different states of the same system or network-based signatures in groups of bio-macromolecules sharing either the same functionality or the same fold. In addition to the new software, here we release also an updated version of the webPSN server, which allows performing an interactive graphical analysis of PSN-MD, following the upload of the PSNtools output. PSNtools, the auxiliary binary version of Wordom software, and the WebPSN server are freely available at http://webpsn.hpc.unimo.it/wpsn3.php.
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27
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Costa F, Guardiani C, Giacomello A. Exploring K v 1.2 Channel Inactivation Through MD Simulations and Network Analysis. Front Mol Biosci 2021; 8:784276. [PMID: 34988118 PMCID: PMC8721119 DOI: 10.3389/fmolb.2021.784276] [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: 09/27/2021] [Accepted: 11/12/2021] [Indexed: 12/12/2022] Open
Abstract
The KCNA2 gene encodes the K v 1.2 channel, a mammalian Shaker-like voltage-gated K+ channel, whose defections are linked to neuronal deficiency and childhood epilepsy. Despite the important role in the kinetic behavior of the channel, the inactivation remained hereby elusive. Here, we studied the K v 1.2 inactivation via a combined simulation/network theoretical approach that revealed two distinct pathways coupling the Voltage Sensor Domain and the Pore Domain to the Selectivity Filter. Additionally, we mutated some residues implicated in these paths and we explained microscopically their function in the inactivation mechanism by computing a contact map. Interestingly, some pathological residues shown to impair the inactivation lay on the paths. In summary, the presented results suggest two pathways as the possible molecular basis of the inactivation mechanism in the K v 1.2 channel. These pathways are consistent with earlier mutational studies and known mutations involved in neuronal channelopathies.
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Affiliation(s)
| | | | - Alberto Giacomello
- Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Rome, Italy
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28
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Helderop E, Bienenstock EJ, Grubesic TH, Miller J, Tong D, Brosi B, Jha S. Network-based geoforensics: Connecting pollen and plants to place. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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29
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Levintov L, Vashisth H. Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides. Biophys J 2021; 120:5060-5073. [PMID: 34710377 PMCID: PMC8633718 DOI: 10.1016/j.bpj.2021.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 08/17/2021] [Accepted: 10/06/2021] [Indexed: 12/14/2022] Open
Abstract
Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.
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Affiliation(s)
- Lev Levintov
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire.
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30
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Hidden electrostatic energy contributions define dynamic allosteric communications within p53 during molecular recognition. Biophys J 2021; 120:4512-4524. [PMID: 34478701 DOI: 10.1016/j.bpj.2021.08.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/03/2021] [Accepted: 08/26/2021] [Indexed: 12/15/2022] Open
Abstract
Molecular recognition is fundamental to transcription regulation. As a transcription factor, the tumor suppressor p53 has to recognize either specific DNA sequences or repressor protein partners. However, the molecular mechanism underlying the p53 conformational switch from the DNA-bound to repressor-bound states is not fully characterized. The highly charged nature of these interacting molecules prompted us to explore the nonbonded energy contributions behind molecular recognition of either a DNA or the repressor protein iASPP by p53 DNA binding domain (p53DBD), using molecular dynamics simulation followed by rigorous analyses of energy terms. Our results illuminate the allosteric pathway by which iASPP binding to p53 diminishes binding affinity between p53 and DNA. Even though the p53DBD uses a common framework of residues for recognizing both DNA and iASPP, a comparison of the electrostatics in the two p53DBD complexes revealed significant differences in residue-wise contributions to the electrostatic energy. We found that an electrostatic allosteric communication path exists in the presence of both substrates. It consists of evolutionarily conserved residues, from residue K120 of the binding loop L1 to a distal residue R213 of p53DBD. K120 is near the DNA in the p53DBD-DNA complex, whereas iASPP binding moves it away from its DNA binding position in the p53DBD-iASPP complex. The "energy hubs" (the residues show a higher degree of connectivity with other residues in the electrostatic networks) determined from the electrostatic network analysis established that this conformational change in K120 completely rewires the electrostatic network from K120 to R213, thereby impeding DNA binding. Furthermore, we found shifting populations of hydrogen bonds and salt bridges reduce pairwise electrostatic energies within p53DBD in its DNA-bound state.
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31
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Atilgan AR, Atilgan C. Computational strategies for protein conformational ensemble detection. Curr Opin Struct Biol 2021; 72:79-87. [PMID: 34563946 DOI: 10.1016/j.sbi.2021.08.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 01/18/2023]
Abstract
Protein function is constrained by the three-dimensional structure but is delineated by its dynamics. This framework must satisfy specificity of function along with adaptability to changing environments and evolvability under external constraints. The accessibility of the available regions of the energy landscape for a set of conditions and shifts in the populations upon their modulation have effects propagating across scales, from biomolecular interactions, to organisms, to populations. Developing the ability to detect and juggle protein conformations supplemented by a physics-based understanding has implications for not only in vivo problems but also for resistance impeding drug discovery and bionano-sensor design.
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Affiliation(s)
- Ali Rana Atilgan
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey
| | - Canan Atilgan
- Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey.
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32
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Li X, Qi Z, Ni D, Lu S, Chen L, Chen X. Markov State Models and Molecular Dynamics Simulations Provide Understanding of the Nucleotide-Dependent Dimerization-Based Activation of LRRK2 ROC Domain. Molecules 2021; 26:5647. [PMID: 34577121 PMCID: PMC8467336 DOI: 10.3390/molecules26185647] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 09/11/2021] [Accepted: 09/14/2021] [Indexed: 01/26/2023] Open
Abstract
Mutations in leucine-rich repeat kinase 2 (LRRK2) are recognized as the most frequent cause of Parkinson's disease (PD). As a multidomain ROCO protein, LRRK2 is characterized by the presence of both a Ras-of-complex (ROC) GTPase domain and a kinase domain connected through the C-terminal of an ROC domain (COR). The bienzymatic ROC-COR-kinase catalytic triad indicated the potential role of GTPase domain in regulating kinase activity. However, as a functional GTPase, the detailed intrinsic regulation of the ROC activation cycle remains poorly understood. Here, combining extensive molecular dynamics simulations and Markov state models, we disclosed the dynamic structural rearrangement of ROC's homodimer during nucleotide turnover. Our study revealed the coupling between dimerization extent and nucleotide-binding state, indicating a nucleotide-dependent dimerization-based activation scheme adopted by ROC GTPase. Furthermore, inspired by the well-known R1441C/G/H PD-relevant mutations within the ROC domain, we illuminated the potential allosteric molecular mechanism for its pathogenetic effects through enabling faster interconversion between inactive and active states, thus trapping ROC in a prolonged activated state, while the implicated allostery could provide further guidance for identification of regulatory allosteric pockets on the ROC complex. Our investigations illuminated the thermodynamics and kinetics of ROC homodimer during nucleotide-dependent activation for the first time and provided guidance for further exploiting ROC as therapeutic targets for controlling LRRK2 functionality in PD treatment.
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Affiliation(s)
- Xinyi Li
- School of Medical Laboratory, Weifang Medical University, Weifang 261053, China;
- Medicinal Chemistry and Bioinformatics Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China;
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China;
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Huashan Hospital, Fudan University, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200433, China
| | - Duan Ni
- Medicinal Chemistry and Bioinformatics Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China;
| | - Shaoyong Lu
- Medicinal Chemistry and Bioinformatics Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China;
| | - Liang Chen
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China;
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Huashan Hospital, Fudan University, Shanghai 200040, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai 200433, China
| | - Xiangyu Chen
- School of Medical Laboratory, Weifang Medical University, Weifang 261053, China;
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33
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Goswami S, Manna B, Chattopadhyay K, Ghosh A, Datta S. Role of Conformational Change and Glucose Binding Sites in the Enhanced Glucose Tolerance of Agrobacterium tumefaciens 5A GH1 β-Glucosidase Mutants. J Phys Chem B 2021; 125:9402-9416. [PMID: 34384214 DOI: 10.1021/acs.jpcb.1c02150] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
β-Glucosidases are often inhibited by their reaction product glucose and a barrier to the efficient lignocellulosic biomass hydrolysis to glucose. We had previously reported the mutants, C174V, and H229S, with a nearly 2-fold increased glucose tolerance over the wild type (WT), H0HC94, encoded in Agrobacterium tumefaciens 5A (apparent Ki,Glc = 686 mM). We report our steady-state and time-resolved intrinsic fluorescence spectroscopy, circular dichroism, and isothermal titration calorimetry (ITC) studies to further understand increased glucose tolerance. Changes in the mutants' emission intensity and the differential change in quenching rate in the absence and presence of glucose reflect changes in protein conformation by glucose. Time-resolved lifetime and anisotropy measurements further indicated the microenvironment differences across solvent-exposed tryptophan residues and a higher hydrodynamic radius due to glucose binding, respectively. ITC measurements confirmed the increase of glucose binding sites in the mutants. The experiment results were supported by molecular dynamics simulations, which revealed significant variations in the glucose-protein hydrogen-bonding profiles. Protein structure network analysis of the simulated structures further indicates the mutants' conformation change than the WT. Computational studies also indicated additional glucose binding sites in mutants. Our results indicate the role of glucose binding in modulating the enzyme response to glucose.
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Affiliation(s)
- Shubhasish Goswami
- Protein Engineering Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India
| | - Bharat Manna
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Krishnananda Chattopadhyay
- Structural Biology & Bio-Informatics Division, CSIR-Indian Institute of Chemical Biology, 4, Raja S. C. Mallick Road, Kolkata 700032, India
| | - Amit Ghosh
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India.,P. K. Sinha Centre for Bioenergy and Renewables, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Supratim Datta
- Protein Engineering Laboratory, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India.,Center for the Advanced Functional Materials, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India.,Center for the Climate and Environmental Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India
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34
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Sladek V, Yamamoto Y, Harada R, Shoji M, Shigeta Y, Sladek V. pyProGA-A PyMOL plugin for protein residue network analysis. PLoS One 2021; 16:e0255167. [PMID: 34329304 PMCID: PMC8323899 DOI: 10.1371/journal.pone.0255167] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 07/11/2021] [Indexed: 11/18/2022] Open
Abstract
The field of protein residue network (PRN) research has brought several useful methods and techniques for structural analysis of proteins and protein complexes. Many of these are ripe and ready to be used by the proteomics community outside of the PRN specialists. In this paper we present software which collects an ensemble of (network) methods tailored towards the analysis of protein-protein interactions (PPI) and/or interactions of proteins with ligands of other type, e.g. nucleic acids, oligosaccharides etc. In parallel, we propose the use of the network differential analysis as a method to identify residues mediating key interactions between proteins. We use a model system, to show that in combination with other, already published methods, also included in pyProGA, it can be used to make such predictions. Such extended repertoire of methods allows to cross-check predictions with other methods as well, as we show here. In addition, the possibility to construct PRN models from various kinds of input is so far a unique asset of our code. One can use structural data as defined in PDB files and/or from data on residue pair interaction energies, either from force-field parameters or fragment molecular orbital (FMO) calculations. pyProGA is a free open-source software available from https://gitlab.com/Vlado_S/pyproga.
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Affiliation(s)
- Vladimir Sladek
- Institute of Chemistry, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Yuta Yamamoto
- Department of Chemistry, Rikkyo University, Nishi-Ikebukuro, Tokyo, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Mitsuo Shoji
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Vladimir Sladek
- Institute of Construction and Architecture, Slovak Academy of Sciences, Bratislava, Slovakia
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35
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Understanding the conformational change and inhibition of hyperthermophilic GH10 xylanase in ionic liquid. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.115875] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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36
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Sobieraj M, Setny P. Entropy-based distance cutoff for protein internal contact networks. Proteins 2021; 89:1333-1339. [PMID: 34053102 DOI: 10.1002/prot.26154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 11/05/2022]
Abstract
Protein structure networks (PSNs) have long been used to provide a coarse yet meaningful representation of protein structure, dynamics, and internal communication pathways. An important question is what criteria should be applied to construct the network so that to include relevant interresidue contacts while avoiding unnecessary connections. To address this issue, we systematically considered varying residue distance cutoff length and the probability threshold for contact formation to construct PSNs based on atomistic molecular dynamics in order to assess the amount of mutual information within the resulting representations. We found that the minimum in mutual information is universally achieved at the cutoff length of 5 Å, irrespective of the applied contact formation probability threshold in all considered, distinct proteins. Assuming that the optimal PSNs should be characterized by the least amount of redundancy, which corresponds to the minimum in mutual information, this finding suggests an objective criterion for cutoff distance and supports the existing preference towards its customary selection around 5 Å length, typically based to date on heuristic criteria.
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Affiliation(s)
- Marcin Sobieraj
- Center of New Technologies, University of Warsaw, Warsaw, Poland.,Department of Physics, University of Warsaw, Warsaw, Poland
| | - Piotr Setny
- Center of New Technologies, University of Warsaw, Warsaw, Poland
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37
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Bourgeat L, Pacini L, Serghei A, Lesieur C. Experimental diagnostic of sequence-variant dynamic perturbations revealed by broadband dielectric spectroscopy. Structure 2021; 29:1419-1429.e3. [PMID: 34051139 DOI: 10.1016/j.str.2021.05.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 03/23/2021] [Accepted: 05/07/2021] [Indexed: 02/08/2023]
Abstract
Genetic diversity leads to protein robustness, adaptability, and failure. Some sequence variants are structurally robust but functionally disturbed because mutations bring the protein onto unfolding/refolding routes resulting in misfolding diseases (e.g., Parkinson). We assume dynamic perturbations introduced by mutations foster the alternative unfolding routes and test this possibility by comparing the unfolding dynamics of the heat-labile enterotoxin B pentamers and the cholera toxin B pentamers, two pentamers structurally and functionally related and robust to 17 sequence variations. The B-subunit thermal unfolding dynamics are monitored by broadband dielectric spectroscopy in nanoconfined and weakly hydrated conditions. Distinct dielectric signals reveal the different B-subunits unfolding dynamics. Combined with network analyses, the experiments pinpoint the role of three mutations A1T, E7D, and E102A, in diverting LTB5 to alternative unfolding routes that protect LTB5 from dissociation. Altogether, the methodology diagnoses dynamics faults that may underlie functional disorder, drug resistance, or higher virulence of sequence variants.
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Affiliation(s)
- Laëtitia Bourgeat
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Univ Lyon, CNRS, IMP, 69622, Villeurbanne, France
| | - Lorenza Pacini
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Institut Rhônalpin des systèmes complexes, IXXI-ENS-Lyon, 69007, Lyon, France
| | | | - Claire Lesieur
- Univ Lyon, CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, Ampère, UMR5005, 69622 Villeurbanne, France; Institut Rhônalpin des systèmes complexes, IXXI-ENS-Lyon, 69007, Lyon, France.
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38
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Dodd T, Yao XQ, Hamelberg D, Ivanov I. Subsets of adjacent nodes (SOAN): a fast method for computing suboptimal paths in protein dynamic networks. Mol Phys 2021. [DOI: 10.1080/00268976.2021.1893847] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Thomas Dodd
- Department of Chemistry, Georgia State University, Atlanta, GA, USA
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA
| | - Xin-Qiu Yao
- Department of Chemistry, Georgia State University, Atlanta, GA, USA
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA
| | - Donald Hamelberg
- Department of Chemistry, Georgia State University, Atlanta, GA, USA
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA
| | - Ivaylo Ivanov
- Department of Chemistry, Georgia State University, Atlanta, GA, USA
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA
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39
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Ezaj MMA, Junaid M, Akter Y, Nahrin A, Siddika A, Afrose SS, Nayeem SMA, Haque MS, Moni MA, Hosen SMZ. Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy. J Biomol Struct Dyn 2021; 40:6477-6502. [PMID: 33586620 DOI: 10.1080/07391102.2021.1886171] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the most cryptic pandemic outbreak of the 21st century, has gripped more than 1.8 million people to death and infected almost eighty six million. As it is a new variant of SARS, there is no approved drug or vaccine available against this virus. This study aims to predict some promising cytotoxic T lymphocyte epitopes in the SARS-CoV-2 proteome utilizing immunoinformatic approaches. Firstly, we identified 21 epitopes from 7 different proteins of SARS-CoV-2 inducing immune response and checked for allergenicity and conservancy. Based on these factors, we selected the top three epitopes, namely KAYNVTQAF, ATSRTLSYY, and LTALRLCAY showing functional interactions with the maximum number of MHC alleles and no allergenicity. Secondly, the 3D model of selected epitopes and HLA-A*29:02 were built and Molecular Docking simulation was performed. Most interestingly, the best two epitopes predicted by docking are part of two different structural proteins of SARS-CoV-2, namely Membrane Glycoprotein (ATSRTLSYY) and Nucleocapsid Phosphoprotein (KAYNVTQAF), which are generally target of choice for vaccine designing. Upon Molecular Docking, interactions between selected epitopes and HLA-A*29:02 were further validated by 50 ns Molecular Dynamics (MD) simulation. Analysis of RMSD, Rg, SASA, number of hydrogen bonds, RMSF, MM-PBSA, PCA, and DCCM from MD suggested that ATSRTLSYY is the most stable and promising epitope than KAYNVTQAF epitope. Moreover, we also identified B-cell epitopes for each of the antigenic proteins of SARS CoV-2. Findings of our work will be a good resource for wet lab experiments and will lessen the timeline for vaccine construction.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Md Muzahid Ahmed Ezaj
- Department of Genetic Engineering and Biotechnology, University of Chittagong, Chattogram, Bangladesh.,Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh
| | - Md Junaid
- Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh.,Molecular Modeling Drug-design and Discovery Laboratory, Pharmacology Research Division, BCSIR Laboratories Chattogram, Bangladesh Council of Scientific and Industrial Research, Chattogram, Bangladesh
| | - Yeasmin Akter
- Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh.,Department of Biotechnology & Genetic Engineering, Noakhali Science & Technology University, Noakhali, Bangladesh
| | - Afsana Nahrin
- Department of Pharmacy, University of Science and Technology Chittagong, Chattogram, Bangladesh
| | - Aysha Siddika
- Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh.,Department of Chemistry, University of Chittagong, Chattogram, Bangladesh
| | - Syeda Samira Afrose
- Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh.,Department of Chemistry, University of Chittagong, Chattogram, Bangladesh
| | - S M Abdul Nayeem
- Reverse Vaccinology Research Division, Advanced Bioinformatics, Computational Biology and Data Science Laboratory, Chattogram, Bangladesh.,Department of Chemistry, University of Chittagong, Chattogram, Bangladesh
| | - Md Sajedul Haque
- Department of Chemistry, University of Chittagong, Chattogram, Bangladesh
| | - Mohammad Ali Moni
- WHO Collaborating Centre on eHealth, UNSW Digital Health, School of Public Health and Community Medicine, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia
| | - S M Zahid Hosen
- Molecular Modeling Drug-design and Discovery Laboratory, Pharmacology Research Division, BCSIR Laboratories Chattogram, Bangladesh Council of Scientific and Industrial Research, Chattogram, Bangladesh.,Pancreatic Research Group, South Western Sydney Clinical School, and Ingham Institute for Applied Medical Research, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
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40
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Bhattacharjee S, Bhattacharyya R, Sengupta J. Dynamics and electrostatics define an allosteric druggable site within the receptor-binding domain of SARS-CoV-2 spike protein. FEBS Lett 2021; 595:442-451. [PMID: 33449359 PMCID: PMC8014131 DOI: 10.1002/1873-3468.14038] [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: 10/19/2020] [Revised: 12/11/2020] [Accepted: 01/07/2021] [Indexed: 02/07/2023]
Abstract
The pathogenesis of the SARS‐CoV‐2 virus initiates through recognition of the angiotensin‐converting enzyme 2 (ACE2) receptor of the host cells by the receptor‐binding domain (RBD) located at the spikes of the virus. Here, using molecular dynamics simulations, we have demonstrated the allosteric crosstalk within the RBD in the apo‐ and the ACE2 receptor‐bound states, revealing the contribution of the dynamics‐based correlated motions and the electrostatic energy perturbations to this crosstalk. While allostery, based on correlated motions, dominates inherent distal communication in the apo‐RBD, the electrostatic energy perturbations determine favorable pairwise crosstalk within the RBD residues upon binding to ACE2. Interestingly, the allosteric path is composed of residues which are evolutionarily conserved within closely related coronaviruses, pointing toward the biological relevance of the communication and its potential as a target for drug development.
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Affiliation(s)
- Sayan Bhattacharjee
- Division of Structural Biology and Bioinformatics, CSIR-Indian Institute of Chemical Biology, Kolkata, India
| | - Rajanya Bhattacharyya
- Division of Structural Biology and Bioinformatics, CSIR-Indian Institute of Chemical Biology, Kolkata, India
| | - Jayati Sengupta
- Division of Structural Biology and Bioinformatics, CSIR-Indian Institute of Chemical Biology, Kolkata, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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41
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Halder A, Anto A, Subramanyan V, Bhattacharyya M, Vishveshwara S, Vishveshwara S. Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case. Front Mol Biosci 2020; 7:596945. [PMID: 33392257 PMCID: PMC7775578 DOI: 10.3389/fmolb.2020.596945] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/04/2020] [Indexed: 02/04/2023] Open
Abstract
Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.
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Affiliation(s)
- Anushka Halder
- Department of Pharmacology, Yale University, New Haven, CT, United States
| | - Arinnia Anto
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Varsha Subramanyan
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | | | - Smitha Vishveshwara
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
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42
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Villani G. A Time-Dependent Quantum Approach to Allostery and a Comparison With Light-Harvesting in Photosynthetic Phenomenon. Front Mol Biosci 2020; 7:156. [PMID: 33005625 PMCID: PMC7483663 DOI: 10.3389/fmolb.2020.00156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/19/2020] [Indexed: 11/26/2022] Open
Abstract
The allosteric effect is one of the most important processes in regulating the function of proteins, and the elucidation of this phenomenon plays a significant role in understanding emergent behaviors in biological regulation. In this process, a perturbation, generated by a ligand in a part of the macromolecule (the allosteric site), moves along this system and reaches a specific (active) site, dozens of Ångströms away, with a great efficiency. The dynamics of this perturbation in the macromolecule can model precisely the allosteric process. In this article, we will be studying the general characteristics of allostery, using a time-dependent quantum approach to obtain rules that apply to this kind of process. Considering the perturbation as a wave that moves within the molecular system, we will characterize the allosteric process with three of the properties of this wave in the active site: (1) ta, the characteristic time for reaching that site, (2) Aa, the amplitude of the wave in this site, and (3) Ba, its corresponding spectral broadening. These three parameters, together with the process mechanism and the perturbation efficiency in the process, can describe the phenomenon. One of the main purposes of this paper is to link the parameters ta, Aa, and Ba and the perturbation efficiency to the characteristics of the system. There is another fundamental process for life that has some characteristics similar to allostery: the light-harvesting (LH) process in photosynthesis. Here, as in allostery, two distant macromolecular sites are involved—two sites dozens of Ångströms away. In both processes, it is particularly important that the perturbation is distributed efficiently without dissipating in the infinite degrees of freedom within the macromolecule. The importance of considering quantum effects in the LH process is well documented in literature, and the quantum coherences are experimentally proven by time-dependent spectroscopic techniques. Given the existing similarities between these two processes in macromolecules, in this work, we suggest using Quantum Mechanics (QM) to study allostery.
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Affiliation(s)
- Giovanni Villani
- Istituto di Chimica dei Composti OrganoMetallici (UOS Pisa) - CNR, Area della Ricerca di Pisa, Pisa, Italy
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43
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Felline A, Seeber M, Fanelli F. webPSN v2.0: a webserver to infer fingerprints of structural communication in biomacromolecules. Nucleic Acids Res 2020; 48:W94-W103. [PMID: 32427333 PMCID: PMC7319592 DOI: 10.1093/nar/gkaa397] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 04/21/2020] [Accepted: 05/17/2020] [Indexed: 12/25/2022] Open
Abstract
A mixed Protein Structure Network (PSN) and Elastic Network Model-Normal Mode Analysis (ENM-NMA)-based strategy (i.e. PSN-ENM) was developed to investigate structural communication in bio-macromolecules. Protein Structure Graphs (PSGs) are computed on a single structure, whereas information on system dynamics is supplied by ENM-NMA. The approach was implemented in a webserver (webPSN), which was significantly updated herein. The webserver now handles both proteins and nucleic acids and relies on an internal upgradable database of network parameters for ions and small molecules in all PDB structures. Apart from the radical restyle of the server and some changes in the calculation setup, other major novelties concern the possibility to: a) compute the differences in nodes, links, and communication pathways between two structures (i.e. network difference) and b) infer links, hubs, communities, and metapaths from consensus networks computed on a number of structures. These new features are useful to identify commonalties and differences between two different functional states of the same system or structural-communication signatures in homologous or analogous systems. The output analysis relies on 3D-representations, interactive tables and graphs, also available for download. Speed and accuracy make this server suitable to comparatively investigate structural communication in large sets of bio-macromolecular systems. URL: http://webpsn.hpc.unimore.it.
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Affiliation(s)
- Angelo Felline
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Michele Seeber
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Francesca Fanelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy.,Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena 41125, Italy
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44
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Fu C, Zhao L, Tan X, Li J, Wang X. Design and activity detection of BH3-mimetic peptide based on Bcl-X L binding potency. J Biomol Struct Dyn 2020; 38:4607-4616. [PMID: 31612794 DOI: 10.1080/07391102.2019.1680433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Chenggong Fu
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Longhe Zhao
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Xiangmin Tan
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Jiazhong Li
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Xin Wang
- School of Pharmacy, Lanzhou University, Lanzhou, China
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45
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Harder-Viddal C, Roshko RM, Stetefeld J. Energy flow and intersubunit signalling in GSAM: A non-equilibrium molecular dynamics study. Comput Struct Biotechnol J 2020; 18:1651-1663. [PMID: 32670505 PMCID: PMC7338781 DOI: 10.1016/j.csbj.2020.06.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 06/14/2020] [Accepted: 06/16/2020] [Indexed: 12/11/2022] Open
Abstract
Non-equilibrium molecular dynamics simulations of vibrational energy flow induced by the imposition of a thermal gradient have been performed on the μ2-dimeric enzyme glutamate-1-semialdehyde aminomutase (GSAM), the key enzyme in the biosynthesis of chlorophyll, in order to identify energy transport pathways and to elucidate their role as potential allosteric communication networks for coordinating functional dynamics, specifically the negative cooperativity observed in the motion of the two active site gating loops. Fully atomistic MD simulations of thermal diffusion were executed with a GROMACS simulation package on a fully solvated GSAM enzyme by heating various active site target ligands (initially, catalytic intermediates and cofactors) to 300K while holding the remainder of the protein and the solvent bath at 10K and monitoring the temperature T(t) of all the enzyme residues as a function of time over a 1ns observation window. Energy is observed to be deposited in a relatively small number of discrete chains of residues most of which contribute to specific structural or biochemical functionality. Thermal linkages between all thermally active chains were established by isolating a specific pair of chains and performing a thermal diffusion simulation on the pair, one held at 300K and the other at 10K, with the rest of the protein frozen in its initial atomic configuration and thus thermally unresponsive. Proceeding in this way, it was possible to map out multiple pathways of vibrational energy flow leading from one of the active sites through a network of contiguous residues, many of which were evolutionarily conserved and linked by hydrogen bonds, into the other active site and ultimately to the other gating loop.
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Affiliation(s)
- C Harder-Viddal
- Department of Chemistry and Physics, Canadian Mennonite University, 500 Shaftesbury Blvd, Winnipeg, Manitoba, Canada
| | - R M Roshko
- Department of Physics and Astronomy, University of Manitoba, 30A Sifton Rd, Winnipeg, Manitoba, Canada
| | - J Stetefeld
- Department of Chemistry, University of Manitoba, 144 Dysart Rd, Winnipeg, Manitoba, Canada.,Center for Oil and Gas Research and Development (COGRAD), Canada.,Department of Biochemistry and Medical Genetics, University of Manitoba, Canada.,Department of Human Anatomy and Cell Science, University of Manitoba, Canada
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46
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Verkhivker GM, Agajanian S, Hu G, Tao P. Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning. Front Mol Biosci 2020; 7:136. [PMID: 32733918 PMCID: PMC7363947 DOI: 10.3389/fmolb.2020.00136] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
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Affiliation(s)
- Gennady M. Verkhivker
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Steve Agajanian
- Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, United States
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Peng Tao
- Department of Chemistry, Center for Drug Discovery, Design, and Delivery (CD4), Center for Scientific Computation, Southern Methodist University, Dallas, TX, United States
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47
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Chakrabarty B, Naganathan V, Garg K, Agarwal Y, Parekh N. NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes. Nucleic Acids Res 2020; 47:W462-W470. [PMID: 31106363 PMCID: PMC6602509 DOI: 10.1093/nar/gkz399] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 04/30/2019] [Accepted: 05/07/2019] [Indexed: 02/04/2023] Open
Abstract
Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein–protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein–nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein–protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/
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Affiliation(s)
- Broto Chakrabarty
- Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology - Hyderabad 500032, India
| | - Varun Naganathan
- Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology - Hyderabad 500032, India
| | - Kanak Garg
- Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology - Hyderabad 500032, India
| | - Yash Agarwal
- Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology - Hyderabad 500032, India
| | - Nita Parekh
- Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology - Hyderabad 500032, India
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48
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Small Conformational Changes Underlie Evolution of Resistance to NNRTI in HIV Reverse Transcriptase. Biophys J 2020; 118:2489-2501. [PMID: 32348721 DOI: 10.1016/j.bpj.2020.04.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 02/12/2020] [Accepted: 04/06/2020] [Indexed: 11/23/2022] Open
Abstract
Despite achieving considerable success in reducing the number of fatalities due to acquired immunodeficiency syndrome, emergence of resistance against the reverse transcriptase (RT) inhibitor drugs remains one of the biggest challenges of the human immunodeficiency virus antiretroviral therapy (ART). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) form a large class of drugs and a crucial component of ART. In NNRTIs, even a single resistance mutation is known to make the drugs completely ineffective. Additionally, several inhibitor-bound RTs with single resistance mutations do not exhibit any significant variations in their three-dimensional structures compared with the inhibitor-bound RT but completely nullify their inhibitory functions. This makes understanding the structural mechanism of these resistance mutations crucial for drug development. Here, we study several single resistance mutations in the allosteric inhibitor (nevirapine)-bound RT to analyze the mechanism of small structural changes leading to these large functional effects. In this study, we have shown that in absence of significant conformational variations in the inhibitor-bound wild-type RT and RT with single resistance mutations, the protein contact network analysis of their static structures, along with molecular dynamics simulations, can be a useful approach to understand the functional effect of small local conformational variations. The simple network analysis exposes the localized contact changes that lead to global rearrangement in the communication pattern within RT. Furthermore, these conformational changes have implications on the overall dynamics of RT. Using various measures, we show that a single resistance mutation can change the network structure and dynamics of RT to behave more like unbound RT, even in the presence of the inhibitor. This combined coarse-grained contact network and molecular dynamics approach promises to be a useful tool to analyze structure-function studies of proteins that show large functional changes with negligible variations in their overall conformation.
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49
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To Probe Full and Partial Activation of Human Peroxisome Proliferator-Activated Receptors by Pan-Agonist Chiglitazar Using Molecular Dynamics Simulations. PPAR Res 2020; 2020:5314187. [PMID: 32308671 PMCID: PMC7152983 DOI: 10.1155/2020/5314187] [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: 01/13/2020] [Revised: 02/25/2020] [Accepted: 03/03/2020] [Indexed: 02/06/2023] Open
Abstract
Chiglitazar is a promising new-generation insulin sensitizer with low reverse effects for the treatment of type II diabetes mellitus (T2DM) and has shown activity as a nonselective pan-agonist to the human peroxisome proliferator-activated receptors (PPARs) (i.e., full activation of PPARγ and a partial activation of PPARα and PPARβ/δ). Yet, it has no high-resolution complex structure with PPARs and its detailed interactions and activation mechanism remain unclear. In this study, we docked chiglitazar into three experimentally resolved crystal structures of hPPAR subtypes, PPARα, PPARβ/δ, and PPARγ, followed by 3 μs molecular dynamics simulations for each system. Our MM-GBSA binding energy calculation revealed that chiglitazar most favorably bound to hPPARγ (-144.6 kcal/mol), followed by hPPARα (-138.0 kcal/mol) and hPPARβ (-135.9 kcal/mol), and the order is consistent with the experimental data. Through the decomposition of the MM-GBSA binding energy by residue and the use of two-dimensional interaction diagrams, key residues involved in the binding of chiglitazar were identified and characterized for each complex system. Additionally, our detailed dynamics analyses support that the conformation and dynamics of helix 12 play a critical role in determining the activities of the different types of ligands (e.g., full agonist vs. partial agonist). Rather than being bent fully in the direction of the agonist versus antagonist conformation, a partial agonist can adopt a more linear conformation and have a lower degree of flexibility. Our finding may aid in further development of this new generation of medication.
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50
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Liang Z, Zhu Y, Long J, Ye F, Hu G. Both intra and inter-domain interactions define the intrinsic dynamics and allosteric mechanism in DNMT1s. Comput Struct Biotechnol J 2020; 18:749-764. [PMID: 32280430 PMCID: PMC7132064 DOI: 10.1016/j.csbj.2020.03.016] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 03/17/2020] [Accepted: 03/17/2020] [Indexed: 01/03/2023] Open
Abstract
Dynamics and allosteric potentials of the RFTS domain are proposed. Hinge sites located at the RFTS-CD interface are key regulators for inter-domain interactions. Network analysis reveals local allosteric networks and inter-domain communication pathways in DNMT1. A potential allosteric site at the TRD interface for DNMT1 is identified.
DNA methyltransferase 1 (DNMT1), a large multidomain enzyme, is believed to be involved in the passive transmission of genomic methylation patterns via methylation maintenance. Yet, the molecular mechanism of interaction networks underlying DNMT1 structures, dynamics, and its biological significance has yet to be fully characterized. In this work, we used an integrated computational strategy that combined coarse-grained and atomistic simulations with coevolution information and network modeling of the residue interactions for the systematic investigation of allosteric dynamics in DNMT1. The elastic network modeling has proposed that the high plasticity of RFTS has strengthened the correlated behaviors of DNMT1 structures through the hinge sites located at the RFTS-CD interface, which mediate the collective motions between domains. The perturbation response scanning (PRS) analysis combined with the enrichment analysis of disease mutations have further highlighted the allosteric potential of the RFTS domain. Furthermore, the long-range paths connect the intra-domain interactions through the TRD interface and catalytic interface, emphasizing some key inter-domain interactions as the bridges in the global allosteric regulation of DNMT1. The observed interplay between conserved intra-domain networks and dynamical plasticity encoded by inter-domain interactions provides insights into the intrinsic dynamics and functional evolution, as well as the design of allosteric modulators of DNMT1 based on the TRD interface.
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Affiliation(s)
- Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Yu Zhu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Jie Long
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Fei Ye
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
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