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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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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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