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Bringas M, Luck M, Müller P, Scheidt HA, Di Lella S. Effects of the RNA-Polymerase Inhibitors Remdesivir and Favipiravir on the Structure of Lipid Bilayers-An MD Study. MEMBRANES 2022; 12:941. [PMID: 36295700 PMCID: PMC9608901 DOI: 10.3390/membranes12100941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/22/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
The structure and dynamics of membranes are crucial to ensure the proper functioning of cells. There are some compounds used in therapeutics that show nonspecific interactions with membranes in addition to their specific molecular target. Among them, two compounds recently used in therapeutics against COVID-19, remdesivir and favipiravir, were subjected to molecular dynamics simulation assays. In these, we demonstrated that the compounds can spontaneously bind to model lipid membranes in the presence or absence of cholesterol. These findings correlate with the corresponding experimental results recently reported by our group. In conclusion, insertion of the compounds into the membrane is observed, with a mean position close to the phospholipid head groups.
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Affiliation(s)
- Mauro Bringas
- Instituto de Química Biológica—Ciencias Exactas y Naturales (IQUIBICEN)—CONICET and Departamento de Química Biológica FCEN, Universidad de Buenos Aires, Int. Güiraldes 2160, Buenos Aires C1428EGA, Argentina
| | - Meike Luck
- Department of Biology, Humboldt Universität zu Berlin, Invalidenstr. 42, D-10115 Berlin, Germany
| | - Peter Müller
- Department of Biology, Humboldt Universität zu Berlin, Invalidenstr. 42, D-10115 Berlin, Germany
| | - Holger A. Scheidt
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16–18, D-04107 Leipzig, Germany
| | - Santiago Di Lella
- Instituto de Química Biológica—Ciencias Exactas y Naturales (IQUIBICEN)—CONICET and Departamento de Química Biológica FCEN, Universidad de Buenos Aires, Int. Güiraldes 2160, Buenos Aires C1428EGA, Argentina
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2
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Scrima S, Tiberti M, Campo A, Corcelle-Termeau E, Judith D, Foged MM, Clemmensen KKB, Tooze SA, Jäättelä M, Maeda K, Lambrughi M, Papaleo E. Unraveling membrane properties at the organelle-level with LipidDyn. Comput Struct Biotechnol J 2022; 20:3604-3614. [PMID: 35860415 PMCID: PMC9283888 DOI: 10.1016/j.csbj.2022.06.054] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/23/2022] [Accepted: 06/25/2022] [Indexed: 12/22/2022] Open
Abstract
Lipidomics of organelles could be used to design models for molecular simulations. The bottleneck is the analysis and rationalization of the data from simulations. LipidDyn is an automated pipeline to streamline the analyses of lipid bilayers. LipidDyn allows to collect analysis in a non-time-consuming and reproducible manner. We applied LipidDyn to different case studies to illustrate its potential.
Cellular membranes are formed from different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and its alterations are linked to several diseases. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins. Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and resolutions. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data. In this context, we developed LipidDyn, a Python-based pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, order parameters, diffusion motions, lipid density, and lipid enrichment/depletion. The calculations exploit parallelization, and the pipeline includes graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.
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Affiliation(s)
- Simone Scrima
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark.,Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | - Alessia Campo
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | - Elisabeth Corcelle-Termeau
- Cell Death and Metabolism, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | - Delphine Judith
- Institut Cochin, Inserm U1016-CNRS, UMR8104, Université de Paris, Paris, France
| | - Mads Møller Foged
- Cell Death and Metabolism, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | | | - Sharon A Tooze
- Molecular Cell Biology of Autophagy Laboratory, The Francis Crick Institute, London NW1 1AT, United Kingdom
| | - Marja Jäättelä
- Cell Death and Metabolism, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark.,Department of Cellular and Molecular Medicine, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Kenji Maeda
- Cell Death and Metabolism, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | - Matteo Lambrughi
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 2100 Copenhagen, Denmark
| | - Elena Papaleo
- Cancer Structural Biology, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, 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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3
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Róg T, Girych M, Bunker A. Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design. Pharmaceuticals (Basel) 2021; 14:1062. [PMID: 34681286 PMCID: PMC8537670 DOI: 10.3390/ph14101062] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 11/17/2022] Open
Abstract
We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.
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Affiliation(s)
- Tomasz Róg
- Department of Physics, University of Helsinki, 00014 Helsinki, Finland;
| | - Mykhailo Girych
- Department of Physics, University of Helsinki, 00014 Helsinki, Finland;
| | - Alex Bunker
- Drug Research Program, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, 00014 Helsinki, Finland;
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4
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Roterman I, Stapor K, Fabian P, Konieczny L, Banach M. Model of Environmental Membrane Field for Transmembrane Proteins. Int J Mol Sci 2021; 22:ijms22073619. [PMID: 33807215 PMCID: PMC8036355 DOI: 10.3390/ijms22073619] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/20/2021] [Accepted: 03/27/2021] [Indexed: 11/16/2022] Open
Abstract
The water environment determines the activity of biological processes. The role of such an environment interpreted in the form of an external field expressed by the 3D Gaussian distribution in the fuzzy oil drop model directs the folding process towards the generation of a centrally located hydrophobic core with the simultaneous exposure of polar residues on the surface. In addition to proteins soluble in the water environment, there is a significant group of membrane proteins that act as receptors or channels, including ion channels in particular. The change of the polar (water) environment into a highly hydrophobic (membrane) environment is quite radical, resulting in a different hydrophobicity distribution within the membrane protein. Modification of the notation of the force field expressing the presence of the hydrophobic environment has been proposed in this work. A modified fuzzy oil drop model with its adaptation to membrane proteins was used to interpret the structure of membrane proteins–mechanosensitive channel. The modified model was also used to describe the so-called negative cases—i.e., for water-soluble proteins with a clear distribution consistent with the fuzzy oil drop model.
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Affiliation(s)
- Irena Roterman
- Department of Bioinformatics and Telemedicine, Jagiellonian University—Medical College, 30-688 Kraków, Poland;
- Correspondence:
| | - Katarzyna Stapor
- Institute of Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland; (K.S.); (P.F.)
| | - Piotr Fabian
- Institute of Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland; (K.S.); (P.F.)
| | - Leszek Konieczny
- Chair of Medical Biochemistry, Jagiellonian University—Medical College, 31-034 Kraków, Poland;
| | - Mateusz Banach
- Department of Bioinformatics and Telemedicine, Jagiellonian University—Medical College, 30-688 Kraków, Poland;
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5
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Souza FR, Souza LMP, Pimentel AS. Recent Open Issues in Coarse Grained Force Fields. J Chem Inf Model 2020; 60:5881-5884. [PMID: 33231448 DOI: 10.1021/acs.jcim.0c01265] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
This viewpoint intends to show recent open issues of using coarse grained models in molecular dynamics simulation. It reviews the current knowledge of the comparison between experimental and simulation data of structural and physical chemical properties that depend on the hydrophilic and hydrophobic behavior of the molecule.
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Affiliation(s)
- Felipe Rodrigues Souza
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ 22453-900 Brazil
| | - Lucas Miguel Pereira Souza
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ 22453-900 Brazil
| | - Andre Silva Pimentel
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ 22453-900 Brazil
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6
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Enkavi G, Javanainen M, Kulig W, Róg T, Vattulainen I. Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance. Chem Rev 2019; 119:5607-5774. [PMID: 30859819 PMCID: PMC6727218 DOI: 10.1021/acs.chemrev.8b00538] [Citation(s) in RCA: 175] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Indexed: 12/23/2022]
Abstract
Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.
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Affiliation(s)
- Giray Enkavi
- Department
of Physics, University of
Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
| | - Matti Javanainen
- Department
of Physics, University of
Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
- Institute
of Organic Chemistry and Biochemistry of the Czech Academy
of Sciences, Flemingovo naḿesti 542/2, 16610 Prague, Czech Republic
- Computational
Physics Laboratory, Tampere University, P.O. Box 692, FI-33014 Tampere, Finland
| | - Waldemar Kulig
- Department
of Physics, University of
Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
| | - Tomasz Róg
- Department
of Physics, University of
Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
- Computational
Physics Laboratory, Tampere University, P.O. Box 692, FI-33014 Tampere, Finland
| | - Ilpo Vattulainen
- Department
of Physics, University of
Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland
- Computational
Physics Laboratory, Tampere University, P.O. Box 692, FI-33014 Tampere, Finland
- MEMPHYS-Center
for Biomembrane Physics
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7
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Weatherill EE, Coker HLE, Cheetham MR, Wallace MI. Urea-mediated anomalous diffusion in supported lipid bilayers. Interface Focus 2018; 8:20180028. [PMID: 30443327 PMCID: PMC6227775 DOI: 10.1098/rsfs.2018.0028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2018] [Indexed: 12/16/2022] Open
Abstract
Diffusion in biological membranes is seldom simply Brownian motion; instead, the rate of diffusion is dependent on the time scale of observation and so is often described as anomalous. In order to help better understand this phenomenon, model systems are needed where the anomalous diffusion of the lipid bilayer can be tuned and quantified. We recently demonstrated one such model by controlling the excluded area fraction in supported lipid bilayers (SLBs) through the incorporation of lipids derivatized with polyethylene glycol. Here, we extend this work, using urea to induce anomalous diffusion in SLBs. By tuning incubation time and urea concentration, we produce bilayers that exhibit anomalous behaviour on the same scale as that observed in biological membranes.
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Affiliation(s)
- E. E. Weatherill
- Department of Chemistry, Britannia House, King's College London, 7 Trinity Street, London SE1 1DB, UK
| | - H. L. E. Coker
- Department of Chemistry, Britannia House, King's College London, 7 Trinity Street, London SE1 1DB, UK
- Chemistry Research Laboratory, Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK
| | - M. R. Cheetham
- Department of Chemistry, Britannia House, King's College London, 7 Trinity Street, London SE1 1DB, UK
- Cavendish Laboratory, Department of Physics, NanoPhotonics Centre, University of Cambridge, Cambridge CB3 0HE, UK
| | - M. I. Wallace
- Department of Chemistry, Britannia House, King's College London, 7 Trinity Street, London SE1 1DB, UK
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8
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Min Y. Phase dynamics and domain interactions in biological membranes. Curr Opin Chem Eng 2017. [DOI: 10.1016/j.coche.2016.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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