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Sereda YV, Ortoleva PJ. Temporally Coarse-Grained All-Atom Molecular Dynamics Achieved via Stochastic Padé Approximants. J Phys Chem B 2020; 124:1392-1410. [PMID: 31958947 DOI: 10.1021/acs.jpcb.9b10735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A Padé approximant scheme for realizing the discrete-time evolution of the state of a many-atom system is introduced. This temporal coarse-graining scheme accounts for the underlying Newtonian physics and avoids the need for construction of spatially coarse-grained variables. Newtonian physics is incorporated through short molecular dynamics simulations at the beginning of each of the large coarse-grained timesteps. The balance between stochastic and coherent dynamics expressed by many-atom systems is captured via incorporation of the Ito formula into a Padé approximant for the time dependence of individual atom positions over large timesteps. Since the time for a many-atom system to express a characteristic ensemble of atomic velocity fluctuations is typically short relative to the characteristic time of large-scale atomic displacements, a computationally efficient and accurate temporal coarse-graining of the atom-resolved Newtonian dynamics is formulated, denoted all-atom Padé-Ito molecular dynamics (APIMD). Evolution of the system over a time step much longer than that required for standard molecular dynamics (MD) is achieved via incorporation of information from the short MD simulations into a Padé approximant extrapolation in time. The extrapolated atomic configuration is subjected to energy minimization and, when needed, thermal equilibration so as to avoid occasional unphysical close encounters deriving from the Padé approximant extrapolation and to represent configurations appropriate for the temperature of interest. APIMD is implemented and tested via comparison with traditional MD simulations of five phenomena: (1) pertussis toxin subunit deformation, (2) structural transition in a T = 1 capsid-like structure of HPV16 L1 protein, (3) coalescence of argon nanodroplets, and structural transitions in dialanine in (4) vacuum, and (5) water. Accuracy of APIMD is demonstrated using semimicroscopic descriptors (rmsd, radius of gyration, residue-residue contact maps, and densities) and the free energy. Significant computational acceleration relative to traditional molecular dynamics is illustrated.
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Affiliation(s)
- Yuriy V Sereda
- Department of Chemistry Indiana University Bloomington , Indiana 47405 , United States
| | - Peter J Ortoleva
- Department of Chemistry Indiana University Bloomington , Indiana 47405 , United States
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Espinosa-Duran JM, Sereda YV, Abi-Mansour A, Ortoleva P. Multiscale Molecular Dynamics Approach to Energy Transfer in Nanomaterials. J Chem Theory Comput 2018; 14:916-928. [PMID: 29191013 DOI: 10.1021/acs.jctc.7b00702] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
After local transient fluctuations are dissipated, in an energy transfer process, a system evolves to a state where the energy density field varies slowly in time relative to the dynamics of atomic collisions and vibrations. Furthermore, the energy density field remains strongly coupled to the atomic scale processes (collisions and vibrations), and it can serve as the basis of a multiscale theory of energy transfer. Here, a method is introduced to capture the long scale energy density variations as they coevolve with the atomistic state in a way that yields insights into the basic physics and implies an efficient algorithm for energy transfer simulations. The approach is developed based on the N-atom Liouville equation and an interatomic force field and avoids the need for conjectured phenomenological equations for energy transfer and other processes. The theory is demonstrated for sodium chloride and silicon dioxide nanoparticles immersed in a water bath via molecular dynamics simulations of the energy transfer between a nanoparticle and its aqueous host fluid. The energy density field is computed for different sets of symmetric grid densities, and the multiscale theory holds when slowly varying energy densities at the nodes are obtained. Results strongly depend on grid density and nanoparticle constituent material. A nonuniform temperature distribution, larger thermal fluctuations in the nanoparticle than in the bath, and enhancement of fluctuations at the surface, which are expressed due to the atomic nature of the systems, are captured by this method rather than by phenomenological continuum energy transfer models.
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Affiliation(s)
- John M Espinosa-Duran
- Center for Theoretical and Computational Nanoscience, Department of Chemistry, Indiana University , Bloomington, Indiana 47405, United States
| | - Yuriy V Sereda
- Center for Theoretical and Computational Nanoscience, Department of Chemistry, Indiana University , Bloomington, Indiana 47405, United States
| | - Andrew Abi-Mansour
- Center for Theoretical and Computational Nanoscience, Department of Chemistry, Indiana University , Bloomington, Indiana 47405, United States
| | - Peter Ortoleva
- Center for Theoretical and Computational Nanoscience, Department of Chemistry, Indiana University , Bloomington, Indiana 47405, United States
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Castillo HD, Espinosa-Duran JM, Dobscha JR, Ashley DC, Debnath S, Hirsch BE, Schrecke SR, Baik MH, Ortoleva PJ, Raghavachari K, Flood AH, Tait SL. Amphiphile self-assembly dynamics at the solution-solid interface reveal asymmetry in head/tail desorption. Chem Commun (Camb) 2018; 54:10076-10079. [DOI: 10.1039/c8cc04465a] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Asymmetric dynamics in fundamental adsorption and desorption steps drive self-assembly at solution/solid interface.
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Affiliation(s)
| | | | | | | | | | | | | | - Mu-Hyun Baik
- Department of Chemistry
- Indiana University
- Bloomington
- USA
| | | | | | - Amar H. Flood
- Department of Chemistry
- Indiana University
- Bloomington
- USA
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Jiang J, Abi Mansour A, Ortoleva PJ. Multiscale time-dependent density functional theory: Demonstration for plasmons. J Chem Phys 2017; 147:054102. [DOI: 10.1063/1.4994896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Jiajian Jiang
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University, Bloomington, Indiana 47405, USA
| | - Andrew Abi Mansour
- Center for Materials Science and Engineering, Merck & Co., Inc., West Point, Pennsylvania 19486, USA
| | - Peter J. Ortoleva
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University, Bloomington, Indiana 47405, USA
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Abi Mansour A, Ortoleva PJ. Reverse Coarse-Graining for Equation-Free Modeling: Application to Multiscale Molecular Dynamics. J Chem Theory Comput 2016; 12:5541-5548. [PMID: 27631340 DOI: 10.1021/acs.jctc.6b00348] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Constructing atom-resolved states from low-resolution data is of practical importance in many areas of science and engineering. This problem is addressed in this article in the context of multiscale factorization methods for molecular dynamics. These methods capture the crosstalk between atomic and coarse-grained scales arising in macromolecular systems. This crosstalk is accounted for by Trotter factorization, which is used to separate the all-atom from the coarse-grained phases of the computation. In this approach, short molecular dynamics runs are used to advance in time the coarse-grained variables, which in turn guide the all-atom state. To achieve this coevolution, an all-atom microstate consistent with the updated coarse-grained variables must be recovered. This recovery is cast here as a nonlinear optimization problem that is solved with a quasi-Newton method. The approach yields a Boltzmann-relevant microstate whose coarse-grained representation and some of its fine-scale features are preserved. Embedding this algorithm in multiscale factorization is shown to be accurate and scalable for simulating proteins and their assemblies.
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Affiliation(s)
- Andrew Abi Mansour
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University , Bloomington, Indiana 47405, United States
| | - Peter J Ortoleva
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University , Bloomington, Indiana 47405, United States
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Clancy CE, An G, Cannon WR, Liu Y, May EE, Ortoleva P, Popel AS, Sluka JP, Su J, Vicini P, Zhou X, Eckmann DM. Multiscale Modeling in the Clinic: Drug Design and Development. Ann Biomed Eng 2016; 44:2591-610. [PMID: 26885640 PMCID: PMC4983472 DOI: 10.1007/s10439-016-1563-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Accepted: 02/02/2016] [Indexed: 01/30/2023]
Abstract
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.
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Affiliation(s)
- Colleen E Clancy
- Department of Pharmacology, University of California, Davis, CA, USA.
| | - Gary An
- Department of Surgery, University of Chicago, Chicago, IL, USA
| | - William R Cannon
- Computational Biology Group, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yaling Liu
- Department of Mechanical Engineering and Mechanics, Bioengineering Program, Lehigh University, Bethlehem, PA, USA
| | - Elebeoba E May
- Department of Biomedical Engineering, University of Houston, Houston, TX, USA
| | - Peter Ortoleva
- Department of Chemistry, Indiana University, Bloomington, IN, USA
| | - Aleksander S Popel
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - James P Sluka
- Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - Jing Su
- Department of Radiology, Wake Forest University, Winston-Salem, NC, USA
| | - Paolo Vicini
- Clinical Pharmacology and DMPK, MedImmune, Cambridge, UK
| | - Xiaobo Zhou
- Department of Radiology, Wake Forest University, Winston-Salem, NC, USA
| | - David M Eckmann
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA.
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Abi Mansour A, Ortoleva PJ. Implicit Time Integration for Multiscale Molecular Dynamics Using Transcendental Padé Approximants. J Chem Theory Comput 2016; 12:1965-71. [PMID: 26845510 DOI: 10.1021/acs.jctc.5b01232] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Molecular dynamics systems evolve through the interplay of collective and localized disturbances. As a practical consequence, there is a restriction on the time step imposed by the broad spectrum of time scales involved. To resolve this restriction, multiscale factorization was introduced for molecular dynamics as a method that exploits the separation of time scales by coevolving the coarse-grained and atom-resolved states via Trotter factorization. Developing a stable time-marching scheme for this coevolution, however, is challenging because the coarse-grained dynamical equations depend on the microstate; therefore, these equations cannot be expressed in closed form. The objective of this paper is to develop an implicit time integration scheme for multiscale simulation of large systems over long periods of time and with high accuracy. The scheme uses Padé approximants to account for both the stochastic and deterministic features of the coarse-grained dynamics. The method is demonstrated for a protein either undergoing a conformational change or migrating under the influence of an external force. The method shows promise in accelerating multiscale molecular dynamics without a loss of atomic precision or the need to conjecture the form of coarse-grained governing equations.
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Affiliation(s)
- Andrew Abi Mansour
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University , Bloomington, Indiana 47405, United States
| | - Peter J Ortoleva
- Department of Chemistry and Center for Theoretical and Computational Nanoscience, Indiana University , Bloomington, Indiana 47405, United States
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Mansour AA, Sereda YV, Yang J, Ortoleva PJ. Prospective on multiscale simulation of virus-like particles: Application to computer-aided vaccine design. Vaccine 2015; 33:5890-6. [DOI: 10.1016/j.vaccine.2015.05.099] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Revised: 05/25/2015] [Accepted: 05/28/2015] [Indexed: 10/23/2022]
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Yang J, Singharoy A, Sereda Y, Ortoleva P. Quasiequivalence of multiscale coevolution and ensemble MD simulations: A demonstration with lactoferrin. Chem Phys Lett 2014. [DOI: 10.1016/j.cplett.2014.10.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Sereda YV, Espinosa-Duran JM, Ortoleva PJ. Energy transfer between a nanosystem and its host fluid: a multiscale factorization approach. J Chem Phys 2014; 140:074102. [PMID: 24559333 DOI: 10.1063/1.4864200] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Energy transfer between a macromolecule or supramolecular assembly and a host medium is considered from the perspective of Newton's equations and Lie-Trotter factorization. The development starts by demonstrating that the energy of the molecule evolves slowly relative to the time scale of atomic collisions-vibrations. The energy is envisioned to be a coarse-grained variable that coevolves with the rapidly fluctuating atomistic degrees of freedom. Lie-Trotter factorization is shown to be a natural framework for expressing this coevolution. A mathematical formalism and workflow for efficient multiscale simulation of energy transfer is presented. Lactoferrin and human papilloma virus capsid-like structure are used for validation.
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Affiliation(s)
- Yuriy V Sereda
- Center for Cell and Virus Theory, Department of Chemistry, Indiana University, 800 E. Kirkwood Ave, Bloomington, Indiana 47405, USA
| | - John M Espinosa-Duran
- Center for Cell and Virus Theory, Department of Chemistry, Indiana University, 800 E. Kirkwood Ave, Bloomington, Indiana 47405, USA
| | - Peter J Ortoleva
- Center for Cell and Virus Theory, Department of Chemistry, Indiana University, 800 E. Kirkwood Ave, Bloomington, Indiana 47405, USA
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