A Computational Approach to Studying Protein Folding Problems Considering the Crucial Role of the Intracellular Environment
| Autor: | Irving Peña, Pedro Pablo González-Pérez, S. J. Alas, Daniel J. Orta, Eduardo C. Flores, José U. Ramírez, Hiram I. Beltrán |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Models Molecular Protein Folding Protein Conformation Evolutionary algorithm Biology Cell Physiological Phenomena 03 medical and health sciences Convergence (routing) Genetics Humans Computer Simulation Amino Acid Sequence Molecular Biology Simulation Sequence 030102 biochemistry & molecular biology Modelling biological systems Computational Biology Proteins Reproducibility of Results Folding (DSP implementation) Computational Mathematics 030104 developmental biology Computational Theory and Mathematics Modeling and Simulation Benchmark (computing) Thermodynamics Protein folding Biological system Hydrophobic and Hydrophilic Interactions Lattice model (physics) Algorithms |
| Zdroj: | Journal of computational biology : a journal of computational molecular cell biology. 24(10) |
| ISSN: | 1557-8666 |
| Popis: | Intracellular protein folding (PF) is performed in a highly inhomogeneous, crowded, and correlated environment. Due to this inherent complexity, the study and understanding of PF phenomena is a fundamental issue in the field of computational systems biology. In particular, it is important to use a modeled medium that accurately reflects PF in natural systems. In the current study, we present a simulation wherein PF is carried out within an inhomogeneous modeled medium. Simulation resources included a two-dimensional hydrophobic-polar (HP) model, evolutionary algorithms, and the dual site-bond model. The dual site-bond model was used to develop an environment where HP beads could be folded. Our modeled medium included correlation lengths and fractal-like behavior, which were selected according to HP sequence lengths to induce folding in a crowded environment. Analysis of three benchmark HP sequences showed that the modeled inhomogeneous space played an important role in deeper energy folding and obtained better performance and convergence compared with homogeneous environments. Our computational approach also demonstrated that our correlated network provided a better space for PF. Thus, our approach represents a major advancement in PF simulations, not only for folding but also for understanding functional chemical structure and physicochemical properties of proteins in crowded molecular systems, which normally occur in nature. |
| Databáze: | OpenAIRE |
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