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Watson G, Velasco-Berrelleza V, Noy A. Atomistic Molecular Dynamics Simulations of DNA in Complex 3D Arrangements for Comparison with Lower Resolution Structural Experiments. Methods Mol Biol 2022; 2476:95-109. [PMID: 35635699 DOI: 10.1007/978-1-0716-2221-6_8] [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] [Indexed: 06/15/2023]
Abstract
Atomic-level computer simulations are a very useful tool for describing the structure and dynamics of complex biomolecules such as DNA and for providing detail at a resolution where experimental techniques cannot arrive. Molecular dynamics (MD) simulations of mechanically distorted DNA caused by agents like supercoiling and protein binding are computationally challenging due to the large size of the associated systems and timescales. However, nowadays they are achievable thanks to the efficient usage of GPU and to the improvements of continuum solvation models. This together with the concurrent improvements in the resolution of single-molecule experiments, such as atomic force microscopy (AFM), makes possible the convergence between the two. Here we present detailed protocols for doing so: for performing molecular dynamics (MD) simulations of DNA adopting complex three-dimensional arrangements and for comparing the outcome of the calculations with single-molecule experimental data with a lower resolution than atomic.
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Affiliation(s)
- George Watson
- Department of Physics, University of York, Heslington, York, UK
| | | | - Agnes Noy
- Department of Physics, University of York, Heslington, York, UK.
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Exploring the dynamics of flagellar dynein within the axoneme with Fluctuating Finite Element Analysis. Q Rev Biophys 2020; 53:e9. [PMID: 32772965 DOI: 10.1017/s0033583520000062] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function.
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Leng J, Shoura M, McLeish TCB, Real AN, Hardey M, McCafferty J, Ranson NA, Harris SA. Securing the future of research computing in the biosciences. PLoS Comput Biol 2019; 15:e1006958. [PMID: 31095554 PMCID: PMC6521984 DOI: 10.1371/journal.pcbi.1006958] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Improvements in technology often drive scientific discovery. Therefore, research requires sustained investment in the latest equipment and training for the researchers who are going to use it. Prioritising and administering infrastructure investment is challenging because future needs are difficult to predict. In the past, highly computationally demanding research was associated primarily with particle physics and astronomy experiments. However, as biology becomes more quantitative and bioscientists generate more and more data, their computational requirements may ultimately exceed those of physical scientists. Computation has always been central to bioinformatics, but now imaging experiments have rapidly growing data processing and storage requirements. There is also an urgent need for new modelling and simulation tools to provide insight and understanding of these biophysical experiments. Bioscience communities must work together to provide the software and skills training needed in their areas. Research-active institutions need to recognise that computation is now vital in many more areas of discovery and create an environment where it can be embraced. The public must also become aware of both the power and limitations of computing, particularly with respect to their health and personal data.
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Affiliation(s)
- Joanna Leng
- School of Computing, University of Leeds, Leeds, United Kingdom
| | - Massa Shoura
- School of Pathology, Stanford University, Palo Alto, California, United States of America
| | | | - Alan N. Real
- Advanced Research Computing, University of Durham, Durham, United Kingdom
| | - Mariann Hardey
- Advanced Research Computing, University of Durham, Durham, United Kingdom
- School of Business, University of Durham, Durham, United Kingdom
| | | | - Neil A. Ranson
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
- School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
| | - Sarah A. Harris
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
- * E-mail:
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Bacci M, Langini C, Vymětal J, Caflisch A, Vitalis A. Focused conformational sampling in proteins. J Chem Phys 2018; 147:195102. [PMID: 29166086 DOI: 10.1063/1.4996879] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
A detailed understanding of the conformational dynamics of biological molecules is difficult to obtain by experimental techniques due to resolution limitations in both time and space. Computer simulations avoid these in theory but are often too short to sample rare events reliably. Here we show that the progress index-guided sampling (PIGS) protocol can be used to enhance the sampling of rare events in selected parts of biomolecules without perturbing the remainder of the system. The method is very easy to use as it only requires as essential input a set of several features representing the parts of interest sufficiently. In this feature space, new states are discovered by spontaneous fluctuations alone and in unsupervised fashion. Because there are no energetic biases acting on phase space variables or projections thereof, the trajectories PIGS generates can be analyzed directly in the framework of transition networks. We demonstrate the possibility and usefulness of such focused explorations of biomolecules with two loops that are part of the binding sites of bromodomains, a family of epigenetic "reader" modules. This real-life application uncovers states that are structurally and kinetically far away from the initial crystallographic structures and are also metastable. Representative conformations are intended to be used in future high-throughput virtual screening campaigns.
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Affiliation(s)
- Marco Bacci
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Cassiano Langini
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Jiří Vymětal
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Andreas Vitalis
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
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Amaro RE, Mulholland AJ. Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures. Nat Rev Chem 2018; 2:0148. [PMID: 30949587 PMCID: PMC6445369 DOI: 10.1038/s41570-018-0148] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based, physical simulations of biochemical systems, which are now able to access experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are of the cusp of realizing long-promised impact in the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field, and outline how different scales can be combined in practical modelling and simulation strategies.
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Affiliation(s)
- Rommie E Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0304
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
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Solernou A, Hanson BS, Richardson RA, Welch R, Read DJ, Harlen OG, Harris SA. Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules. PLoS Comput Biol 2018; 14:e1005897. [PMID: 29570700 PMCID: PMC5891030 DOI: 10.1371/journal.pcbi.1005897] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 04/09/2018] [Accepted: 11/27/2017] [Indexed: 12/31/2022] Open
Abstract
Fluctuating Finite Element Analysis (FFEA) is a software package designed to perform continuum mechanics simulations of proteins and other globular macromolecules. It combines conventional finite element methods with stochastic thermal noise, and is appropriate for simulations of large proteins and protein complexes at the mesoscale (length-scales in the range of 5 nm to 1 μm), where there is currently a paucity of modelling tools. It requires 3D volumetric information as input, which can be low resolution structural information such as cryo-electron tomography (cryo-ET) maps or much higher resolution atomistic co-ordinates from which volumetric information can be extracted. In this article we introduce our open source software package for performing FFEA simulations which we have released under a GPLv3 license. The software package includes a C ++ implementation of FFEA, together with tools to assist the user to set up the system from Electron Microscopy Data Bank (EMDB) or Protein Data Bank (PDB) data files. We also provide a PyMOL plugin to perform basic visualisation and additional Python tools for the analysis of FFEA simulation trajectories. This manuscript provides a basic background to the FFEA method, describing the implementation of the core mechanical model and how intermolecular interactions and the solvent environment are included within this framework. We provide prospective FFEA users with a practical overview of how to set up an FFEA simulation with reference to our publicly available online tutorials and manuals that accompany this first release of the package.
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Affiliation(s)
- Albert Solernou
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
| | - Benjamin S. Hanson
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
| | | | - Robert Welch
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
| | - Daniel J. Read
- School of Mathematics, University of Leeds, Leeds, United Kingdom
| | - Oliver G. Harlen
- School of Mathematics, University of Leeds, Leeds, United Kingdom
| | - Sarah A. Harris
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
- * E-mail:
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7
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Sutthibutpong T, Noy A, Harris S. Atomistic Molecular Dynamics Simulations of DNA Minicircle Topoisomers: A Practical Guide to Setup, Performance, and Analysis. Methods Mol Biol 2017; 1431:195-219. [PMID: 27283311 DOI: 10.1007/978-1-4939-3631-1_15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
While DNA supercoiling is ubiquitous in vivo, the structure of supercoiled DNA is more challenging to study experimentally than simple linear sequences because the DNA must have a closed topology in order to sustain superhelical stress. DNA minicircles, which are closed circular double-stranded DNA sequences typically containing between 60 and 500 base pairs, have proven to be useful biochemical tools for the study of supercoiled DNA mechanics. We present detailed protocols for constructing models of DNA minicircles in silico, for performing atomistic molecular dynamics (MD) simulations of supercoiled minicircle DNA, and for analyzing the results of the calculations. These simulations are computationally challenging due to the large system sizes. However, improvements in parallel computing software and hardware promise access to improve conformational sampling and simulation timescales. Given the concurrent improvements in the resolution of experimental techniques such as atomic force microscopy (AFM) and cryo-electron microscopy, the study of DNA minicircles will provide a more complete understanding of both the structure and the mechanics of supercoiled DNA.
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Affiliation(s)
- Thana Sutthibutpong
- Theoretical and Computational Science Center (TaCS), Science Laboratory Building, Faculty of Science, King Mongkut University of Technology Thonburi, 126 Pracha Uthit Road, Bang Mod, Thung Khru, Bangkok, 10140, Thailand.
| | - Agnes Noy
- School of Physics and Astronomy, University of Leeds, Leeds, LS2 9JT, UK
| | - Sarah Harris
- School of Physics and Astronomy, University of Leeds, Leeds, LS2 9JT, UK
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, LS2 9JT, UK
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Lee SC, Khalid S, Pollock NL, Knowles TJ, Edler K, Rothnie AJ, R T Thomas O, Dafforn TR. Encapsulated membrane proteins: A simplified system for molecular simulation. BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES 2016; 1858:2549-2557. [PMID: 26946242 DOI: 10.1016/j.bbamem.2016.02.039] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Revised: 02/23/2016] [Accepted: 02/25/2016] [Indexed: 12/19/2022]
Abstract
Over the past 50years there has been considerable progress in our understanding of biomolecular interactions at an atomic level. This in turn has allowed molecular simulation methods employing full atomistic modelling at ever larger scales to develop. However, some challenging areas still remain where there is either a lack of atomic resolution structures or where the simulation system is inherently complex. An area where both challenges are present is that of membranes containing membrane proteins. In this review we analyse a new practical approach to membrane protein study that offers a potential new route to high resolution structures and the possibility to simplify simulations. These new approaches collectively recognise that preservation of the interaction between the membrane protein and the lipid bilayer is often essential to maintain structure and function. The new methods preserve these interactions by producing nano-scale disc shaped particles that include bilayer and the chosen protein. Currently two approaches lead in this area: the MSP system that relies on peptides to stabilise the discs, and SMALPs where an amphipathic styrene maleic acid copolymer is used. Both methods greatly enable protein production and hence have the potential to accelerate atomic resolution structure determination as well as providing a simplified format for simulations of membrane protein dynamics. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.
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Affiliation(s)
- Sarah C Lee
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Syma Khalid
- School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, UK
| | - Naomi L Pollock
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Tim J Knowles
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Karen Edler
- Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY, UK
| | - Alice J Rothnie
- School of Life & Health Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK
| | - Owen R T Thomas
- School of Chemical Engineering, College of Engineering and Physical Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Timothy R Dafforn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
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