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Thermodynamic and Conformational Analysis of GTRNase and Lysozyme Proteins Under Thermal Variations using Molecular Dynamics Simulations Huda, Muhamad Mahfuzh; Adawiyah, Rabiatul; Pradana, Andi Rizky
Jurnal Pijar Mipa Vol. 19 No. 6 (2024): November 2024
Publisher : Department of Mathematics and Science Education, Faculty of Teacher Training and Education, University of Mataram. Jurnal Pijar MIPA colaborates with Perkumpulan Pendidik IPA Indonesia Wilayah Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpm.v19i6.7999

Abstract

This study examines the thermodynamic and conformational dynamics of GTRNase and lysozyme proteins under varying temperature conditions using molecular dynamics (MD) simulations. The objective is to evaluate their structural stability, folding behavior, and thermodynamic properties to understand their responses to thermal fluctuations. Protein structures were retrieved from the Protein Data Bank (PDB), refined to remove extraneous molecules, and simulated using GROMACS 2022.2 under NVT and NPT ensembles, spanning temperatures from 270 K to 380 K. The results revealed distinct behaviors for the two proteins. GTRNase exhibited a slight escalation in radius of gyration (Rg) from 1.434 nm at 270 K to 1.445 nm at 380 K, suggesting a marginal conformational expansion. In contrast, lysozyme maintained a consistent Rg of 1.38 nm over the same temperature range, indicating structural compactness. Root mean square deviation (RMSD) data demonstrated increased flexibility in both proteins, with GTRNase escalating from 0.115 nm at 270 K to 0.179 nm at 380 K and lysozyme rising from 0.102 nm to 0.142 nm across the temperature range. Solvent-accessible surface area (SASA) for GTRNase fluctuated between 69 nm² and 73 nm², with the lowest value observed at 300 K and the highest at 370 K. These findings highlight that GTRNase is more susceptible to thermal perturbations than lysozyme, showing greater conformational flexibility and expansion. This research underscores the utility of MD simulations in exploring protein behavior and provides valuable insights for applications in protein engineering and drug design.