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Artykuły w czasopismach na temat „Biomolecular systems”

Autor: Grafiati

Data publikacji: 6 września 2023

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1

Miró, Jesús M., and Alfonso Rodríguez-Patón. "Biomolecular Computing Devices in Synthetic Biology." International Journal of Nanotechnology and Molecular Computation 2, no. 2 (2010): 47–64. http://dx.doi.org/10.4018/978-1-59904-996-0.ch014.

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Synthetic biology and biomolecular computation are disciplines that fuse when it comes to designing and building information processing devices. In this chapter, we study several devices that are representative of this fusion. These are three gene circuits implementing logic gates, a DNA nanodevice and a biomolecular automaton. The operation of these devices is based on gene expression regulation, the so-called competitive hybridization and the workings of certain biomolecules like restriction enzymes or regulatory proteins. Synthetic biology, biomolecular computation, systems biology and stan

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Katrusiak, Andrzej, Michalina Aniola, Kamil Dziubek, Kinga Ostrowska, and Ewa Patyk. "Biomolecular systems under pressure." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C1188. http://dx.doi.org/10.1107/s2053273314088111.

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Biological systems are often regarded as the ultimate goal of all knowledge in this respect that they can provide the clue for understanding the origin of life and the means for improving the life conditions and healthcare. Hence the interest in high-pressure behavior of organic and biomolecular systems. Such simple organic systems were among the first structural studies at high pressure at all. They included chloroform by Roger Fourme in 1968 [1] and benzene by Piermarini et al. in 1969, still with the use of photographic technique. The efficient studies on bio-macromolecular crystals had to

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3

Niranjan, Vidya, Purushotham Rao, Akshay Uttarkar, and Jitendra Kumar. "Protocol for the development of coarse-grained structures for macromolecular simulation using GROMACS." PLOS ONE 18, no. 8 (2023): e0288264. http://dx.doi.org/10.1371/journal.pone.0288264.

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Coarse-grained simulations have emerged as a valuable tool in the study of large and complex biomolecular systems. These simulations, which use simplified models to represent complex biomolecules, reduce the computational cost of simulations and enable the study of larger systems for longer periods of time than traditional atomistic simulations. GROMACS is a widely used software package for performing coarse-grained simulations of biomolecules, and several force fields have been developed specifically for this purpose. In this protocol paper, we explore the advantages of using coarse-grained s

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4

Emenecker, Ryan J., Alex S. Holehouse, and Lucia C. Strader. "Biological Phase Separation and Biomolecular Condensates in Plants." Annual Review of Plant Biology 72, no. 1 (2021): 17–46. http://dx.doi.org/10.1146/annurev-arplant-081720-015238.

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A surge in research focused on understanding the physical principles governing the formation, properties, and function of membraneless compartments has occurred over the past decade. Compartments such as the nucleolus, stress granules, and nuclear speckles have been designated as biomolecular condensates to describe their shared property of spatially concentrating biomolecules. Although this research has historically been carried out in animal and fungal systems, recent work has begun to explore whether these same principles are relevant in plants. Effectively understanding and studying biomol

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5

Wang, Li, Coucong Gong, Xinzhu Yuan, and Gang Wei. "Controlling the Self-Assembly of Biomolecules into Functional Nanomaterials through Internal Interactions and External Stimulations: A Review." Nanomaterials 9, no. 2 (2019): 285. http://dx.doi.org/10.3390/nano9020285.

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Biomolecular self-assembly provides a facile way to synthesize functional nanomaterials. Due to the unique structure and functions of biomolecules, the created biological nanomaterials via biomolecular self-assembly have a wide range of applications, from materials science to biomedical engineering, tissue engineering, nanotechnology, and analytical science. In this review, we present recent advances in the synthesis of biological nanomaterials by controlling the biomolecular self-assembly from adjusting internal interactions and external stimulations. The self-assembly mechanisms of biomolecu

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6

Smith, Paul E., and B. Montgomery Pettitt. "Modeling Solvent in Biomolecular Systems." Journal of Physical Chemistry 98, no. 39 (1994): 9700–9711. http://dx.doi.org/10.1021/j100090a002.

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7

Rhodes, William. "Coferent dynamics in biomolecular systems." Journal of Molecular Liquids 41 (October 1989): 165–80. http://dx.doi.org/10.1016/0167-7322(89)80076-5.

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8

Rowe, Rhianon K., and P. Shing Ho. "Relationships between hydrogen bonds and halogen bonds in biological systems." Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials 73, no. 2 (2017): 255–64. http://dx.doi.org/10.1107/s2052520617003109.

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The recent recognition that halogen bonding (XB) plays important roles in the recognition and assembly of biological molecules has led to new approaches in medicinal chemistry and biomolecular engineering. When designing XBs into strategies for rational drug design or into a biomolecule to affect its structure and function, we must consider the relationship between this interaction and the more ubiquitous hydrogen bond (HB). In this review, we explore these relationships by asking whether and how XBs can replace, compete against or behave independently of HBs in various biological systems. The

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9

Wang, Yue, Lei Ren, Hongzhen Peng, Linjie Guo, and Lihua Wang. "DNA-Programmed Biomolecular Spatial Pattern Recognition." Chemosensors 11, no. 7 (2023): 362. http://dx.doi.org/10.3390/chemosensors11070362.

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Molecular recognition based on non-covalent interactions between two or more molecules plays a crucial role in biological systems. Specific biological molecule recognition has been widely applied in biotechnology, clinical diagnosis, and treatment. The efficiency and affinity of molecular recognition are greatly determined by the spatial conformation of biomolecules. The designability of DNA nanotechnology makes possible the precise programming of the spatial conformation of biomolecules including valency and spacing, further achieving spatial pattern recognition regulation between biomolecule

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10

Ren, Pengyu, Jaehun Chun, Dennis G. Thomas, et al. "Biomolecular electrostatics and solvation: a computational perspective." Quarterly Reviews of Biophysics 45, no. 4 (2012): 427–91. http://dx.doi.org/10.1017/s003358351200011x.

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AbstractAn understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzy

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11

Yatskou, M. M., and V. V. Apanasovich. "Data analysis in complex biomolecular systems." Informatics 18, no. 1 (2021): 105–22. http://dx.doi.org/10.37661/1816-0301-2021-18-1-105-122.

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The biomolecular technology progress is directly related to the development of effective methods and algorithms for processing a large amount of information obtained by modern high-throughput experimental equipment. The priority task is the development of promising computational tools for the analysis and interpretation of biophysical information using the methods of big data and computer models. An integrated approach to processing large datasets, which is based on the methods of data analysis and simulation modelling, is proposed. This approach allows to determine the parameters of biophysic

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12

Stayton, PS, MEH El-Sayed, N. Murthy, et al. "'Smart' delivery systems for biomolecular therapeutics." Orthodontics and Craniofacial Research 8, no. 3 (2005): 219–25. http://dx.doi.org/10.1111/j.1601-6343.2005.00336.x.

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13

Keenan, Thomas M., and Albert Folch. "Biomolecular gradients in cell culture systems." Lab Chip 8, no. 1 (2008): 34–57. http://dx.doi.org/10.1039/b711887b.

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14

Stoessel, James P., and Peter Nowak. "Absolute free energies in biomolecular systems." Macromolecules 23, no. 7 (1990): 1961–65. http://dx.doi.org/10.1021/ma00209a014.

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15

McGuigan, Kevin G. "Radiation Damage in Biomolecular Systems (RADAM07)." Journal of Physics: Conference Series 101 (March 1, 2008): 011001. http://dx.doi.org/10.1088/1742-6596/101/1/011001.

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16

Finney, J. L., J. M. Goodfellow, P. L. Howell, and F. Vovelle. "Computer Simulation of Aqueous Biomolecular Systems." Journal of Biomolecular Structure and Dynamics 3, no. 3 (1985): 599–622. http://dx.doi.org/10.1080/07391102.1985.10508447.

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17

Kuliński, Tadeusz. "Molecular Dynamics Simulations of Biomolecular Systems." Computational Methods in Science and Technology 1, no. 1 (1996): 43–54. http://dx.doi.org/10.12921/cmst.1996.01.01.43-54.

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18

Sen, Shaunak. "Tradeoffs in simple biomolecular signaling systems." Systems & Control Letters 61, no. 8 (2012): 834–38. http://dx.doi.org/10.1016/j.sysconle.2012.04.011.

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19

Barkai, Naama, and Ben-Zion Shilo. "Variability and Robustness in Biomolecular Systems." Molecular Cell 28, no. 5 (2007): 755–60. http://dx.doi.org/10.1016/j.molcel.2007.11.013.

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20

Zavadlav, Julija, Staš Bevc, and Matej Praprotnik. "Adaptive resolution simulations of biomolecular systems." European Biophysics Journal 46, no. 8 (2017): 821–35. http://dx.doi.org/10.1007/s00249-017-1248-0.

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21

Senn, Hans Martin, and Walter Thiel. "QM/MM Methods for Biomolecular Systems." Angewandte Chemie International Edition 48, no. 7 (2009): 1198–229. http://dx.doi.org/10.1002/anie.200802019.

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22

Fox, Jerome M., Mengxia Zhao, Michael J. Fink, Kyungtae Kang, and George M. Whitesides. "The Molecular Origin of Enthalpy/Entropy Compensation in Biomolecular Recognition." Annual Review of Biophysics 47, no. 1 (2018): 223–50. http://dx.doi.org/10.1146/annurev-biophys-070816-033743.

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Biomolecular recognition can be stubborn; changes in the structures of associating molecules, or the environments in which they associate, often yield compensating changes in enthalpies and entropies of binding and no net change in affinities. This phenomenon—termed enthalpy/entropy (H/S) compensation—hinders efforts in biomolecular design, and its incidence—often a surprise to experimentalists—makes interactions between biomolecules difficult to predict. Although characterizing H/S compensation requires experimental care, it is unquestionably a real phenomenon that has, from an engineering pe

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23

Fujisaki, Hiroshi, Kei Moritsugu, and Yasuhiro Matsunaga. "Exploring Configuration Space and Path Space of Biomolecules Using Enhanced Sampling Techniques—Searching for Mechanism and Kinetics of Biomolecular Functions." International Journal of Molecular Sciences 19, no. 10 (2018): 3177. http://dx.doi.org/10.3390/ijms19103177.

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To understand functions of biomolecules such as proteins, not only structures but their conformational change and kinetics need to be characterized, but its atomistic details are hard to obtain both experimentally and computationally. Here, we review our recent computational studies using novel enhanced sampling techniques for conformational sampling of biomolecules and calculations of their kinetics. For efficiently characterizing the free energy landscape of a biomolecule, we introduce the multiscale enhanced sampling method, which uses a combined system of atomistic and coarse-grained model

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24

Harris, Sarah A., and Vivien M. Kendon. "Quantum-assisted biomolecular modelling." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1924 (2010): 3581–92. http://dx.doi.org/10.1098/rsta.2010.0087.

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Our understanding of the physics of biological molecules, such as proteins and DNA, is limited because the approximations we usually apply to model inert materials are not, in general, applicable to soft, chemically inhomogeneous systems. The configurational complexity of biomolecules means the entropic contribution to the free energy is a significant factor in their behaviour, requiring detailed dynamical calculations to fully evaluate. Computer simulations capable of taking all interatomic interactions into account are therefore vital. However, even with the best current supercomputing facil

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25

Zhang, Jing, Li-Dong Gong, and Zhong-Zhi Yang. "Recent Development and Applications of the ABEEM/MM Polarizable Force Field." Journal of Computational Biophysics and Chemistry 21, no. 04 (2022): 485–98. http://dx.doi.org/10.1142/s2737416521420084.

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In this paper, we review both development and applications of the atom-bond electronegativity equalization method fused into molecular mechanics, i.e., ABEEM/MM polarizable force field (FF). We will focus on the applications of the ABEEM/MM in pure water systems, chemical and biomolecular ion-containing systems, small molecules and biomolecules, etc. The results show that the performance of ABEEM/MM is generally better than that of the commonly used nonpolarizable force fields.

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26

Winter, Roland. "Interrogating the Structural Dynamics and Energetics of Biomolecular Systems with Pressure Modulation." Annual Review of Biophysics 48, no. 1 (2019): 441–63. http://dx.doi.org/10.1146/annurev-biophys-052118-115601.

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High hydrostatic pressure affects the structure, dynamics, and stability of biomolecular systems and is a key parameter in the context of the exploration of the origin and the physical limits of life. This review lays out the conceptual framework for exploring the conformational fluctuations, dynamical properties, and activity of biomolecular systems using pressure perturbation. Complementary pressure-jump relaxation studies are useful tools to study the kinetics and mechanisms of biomolecular phase transitions and structural transformations, such as membrane fusion or protein and nucleic acid

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27

Willner, Itamar, and Bilha Willner. "Molecular and biomolecular optoelectronics." Pure and Applied Chemistry 73, no. 3 (2001): 535–42. http://dx.doi.org/10.1351/pac200173030535.

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Reversible electronic transduction of photonic processes occurring on electrodes is the conceptual method to develop molecular and biomolecular optoelectronic systems. Cyclic photochemical activation of molecular or biomolecular monolayer redox-functions provides a general methodology for the amperometric transduction of photonic information that is recorded by the chemical assembly. Alternatively, photoisomerizable monolayers associated with electrodes act as "command interfaces" for controlling the interfacial electron transfer between molecular redox-species or redox-proteins. The systems u

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28

NAGY, NAYA, and SELIM G. AKL. "ASPECTS OF BIOMOLECULAR COMPUTING." Parallel Processing Letters 17, no. 02 (2007): 185–211. http://dx.doi.org/10.1142/s012962640700296x.

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This paper is intended as a survey of the state of the art of some branches of Biomolecular Computing. Biomolecular Computing aims to use biological hardware (biomare), rather than chips, to build a computer. We discuss the following three main research directions: DNA computing, membrane systems, and gene assembly in ciliates. DNA computing combines practical results together with theoretical algorithm design. Various search problems have been implemented using DNA strands. Membrane systems are a family of computational models inspired by the membrane structure of living cells. The process of

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29

Tolokonnikov, Georgy. "Modelling Biomolecular Structures in Categorical Systems Theory." EPJ Web of Conferences 248 (2021): 01015. http://dx.doi.org/10.1051/epjconf/202124801015.

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In the systemic movement there exist numerous approaches to systems, the most profound of which is the theory of functional systems by Anokhin, which remained largely intuitive science until his pioneering works. The basic principles of functional systems are formalized with the help of the convolutional polycategories in the form of categorical systems theory, which embraced the main systemic approaches, including the traditional mathematical theory of systems. Convolutional polycategories can be built using categorical splices that directly model the external and internal parts of systems. F

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30

D’Ascenzo, Luigi, та Pascal Auffinger. "106 Ion-π interactions in biomolecular systems". Journal of Biomolecular Structure and Dynamics 33, sup1 (2015): 67. http://dx.doi.org/10.1080/07391102.2015.1032668.

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31

Brunner, Robert K., James C. Phillips, and Laxmikant V. Kalé. "Scalable Molecular Dynamics for Large Biomolecular Systems." Scientific Programming 8, no. 3 (2000): 195–207. http://dx.doi.org/10.1155/2000/750827.

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We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in inc

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32

Qiao, Yu, and Ben-Zhuo Lu. "Improvements in continuum modeling for biomolecular systems." Chinese Physics B 25, no. 1 (2016): 018705. http://dx.doi.org/10.1088/1674-1056/25/1/018705.

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33

Oishi, K., and E. Klavins. "Biomolecular implementation of linear I/O systems." IET Systems Biology 5, no. 4 (2011): 252–60. http://dx.doi.org/10.1049/iet-syb.2010.0056.

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34

Dey, Abhishek, and Shaunak Sen. "Describing function-based approximations of biomolecular systems." IET Systems Biology 12, no. 3 (2018): 93–100. http://dx.doi.org/10.1049/iet-syb.2017.0026.

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35

Noid, W. G. "Perspective: Coarse-grained models for biomolecular systems." Journal of Chemical Physics 139, no. 9 (2013): 090901. http://dx.doi.org/10.1063/1.4818908.

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36

Leitner, David M., Hari Datt Pandey, and Korey M. Reid. "Energy Transport across Interfaces in Biomolecular Systems." Journal of Physical Chemistry B 123, no. 45 (2019): 9507–24. http://dx.doi.org/10.1021/acs.jpcb.9b07086.

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Klein, ML, M. Marchi, and JC Smith. "Potential functions for simulation of biomolecular systems." Journal de Chimie Physique 94 (1997): 1305–12. http://dx.doi.org/10.1051/jcp/1997941305.

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Birch, David J. S. "Multiphoton excited fluorescence spectroscopy of biomolecular systems." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 57, no. 11 (2001): 2313–36. http://dx.doi.org/10.1016/s1386-1425(01)00487-5.

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Reinholdt, Peter, Frederik Kamper Jørgensen, Jacob Kongsted, and Jógvan Magnus Haugaard Olsen. "Polarizable Density Embedding for Large Biomolecular Systems." Journal of Chemical Theory and Computation 16, no. 10 (2020): 5999–6006. http://dx.doi.org/10.1021/acs.jctc.0c00763.

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Khurgin, Yu I., V. A. Kudryashova, and V. A. Zavizion. "Interaction of EHF radiation with biomolecular systems." Radiophysics and Quantum Electronics 37, no. 1 (1994): 23–31. http://dx.doi.org/10.1007/bf01039298.

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41

Benenson, Yaakov. "Biomolecular computing systems: principles, progress and potential." Nature Reviews Genetics 13, no. 7 (2012): 455–68. http://dx.doi.org/10.1038/nrg3197.

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Bowling, Alan, and Mahdi Haghshenas-Jaryani. "A multiscale modeling approach for biomolecular systems." Multibody System Dynamics 33, no. 4 (2014): 333–65. http://dx.doi.org/10.1007/s11044-014-9431-x.

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43

Habeck, Michael. "Bayesian Structural Modeling of Large Biomolecular Systems." Biophysical Journal 116, no. 3 (2019): 330a. http://dx.doi.org/10.1016/j.bpj.2018.11.1793.

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Kučera, Ondřej, and Michal Cifra. "Radiofrequency and microwave interactions between biomolecular systems." Journal of Biological Physics 42, no. 1 (2015): 1–8. http://dx.doi.org/10.1007/s10867-015-9392-1.

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Gilbert, D. "Biomolecular Interaction Network Database." Briefings in Bioinformatics 6, no. 2 (2005): 194–98. http://dx.doi.org/10.1093/bib/6.2.194.

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Mogaki, Rina, P. K. Hashim, Kou Okuro, and Takuzo Aida. "Guanidinium-based “molecular glues” for modulation of biomolecular functions." Chem. Soc. Rev. 46, no. 21 (2017): 6480–91. http://dx.doi.org/10.1039/c7cs00647k.

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Hong, Seyoung, Dong Wook Choi, Hong Nam Kim, Chun Gwon Park, Wonhwa Lee, and Hee Ho Park. "Protein-Based Nanoparticles as Drug Delivery Systems." Pharmaceutics 12, no. 7 (2020): 604. http://dx.doi.org/10.3390/pharmaceutics12070604.

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Nanoparticles have been extensively used as carriers for the delivery of chemicals and biomolecular drugs, such as anticancer drugs and therapeutic proteins. Natural biomolecules, such as proteins, are an attractive alternative to synthetic polymers commonly used in nanoparticle formulation because of their safety. In general, protein nanoparticles offer many advantages, such as biocompatibility and biodegradability. Moreover, the preparation of protein nanoparticles and the corresponding encapsulation process involved mild conditions without the use of toxic chemicals or organic solvents. Pro

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48

Zhu, Qiang, and Ray Luo. "Recent Advances in Biomolecular Recognition." International Journal of Molecular Sciences 24, no. 9 (2023): 8310. http://dx.doi.org/10.3390/ijms24098310.

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Leinen, Margaret, Francisco Chavez, Raïssa Meyer, et al. "The Ocean Biomolecular Observing Network (OBON)." Marine Technology Society Journal 56, no. 3 (2022): 106–7. http://dx.doi.org/10.4031/mtsj.56.3.20.

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Abstract Ocean life—from viruses to whales—is built from “biomolecules.” Biomolecules such as DNA infuse each drop of ocean water, grain of sediment, and breath of ocean air. The Ocean Biomolecular Observing Network (OBON) is developing a global collaboration that will allow science and society to understand ocean life like never before. The program will transform how we sense, harvest, protect, and manage ocean life using molecular techniques, as it faces multiple stresses including pollution, habitat loss, and climate change. It will also help communities detect biological hazards such as ha

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50

Matsuura, Kazunori. "Biomolecular Self-assembling Systems for Multivalent Ligand Display." Trends in Glycoscience and Glycotechnology 25, no. 146 (2013): 227–39. http://dx.doi.org/10.4052/tigg.25.227.

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