The LBFGS Quasi-Newtonian Method for Molecular Modeling Prion AGAAAAGA Amyloid Fibrils
Jiapu Zhang, Yating Hou, Yiju Wang, Changyu Wang, Xiangsun Zhang

TL;DR
This paper presents an improved LBFGS quasi-Newton optimization method tailored for modeling unstable, insoluble prion amyloid fibrils, providing a computational approach to predict their 3D structures where experimental data is lacking.
Contribution
The paper introduces a novel enhanced LBFGS optimization algorithm specifically designed for modeling noncrystalline, insoluble protein structures like prion amyloid fibrils.
Findings
Successfully modeled the 3D structure of Prion AGAAAAGA fibrils.
Provides a computational reference for experimental studies.
May aid in drug design targeting prion diseases.
Abstract
Experimental X-ray crystallography, NMR (Nuclear Magnetic Resonance) spectroscopy, dual polarization interferometry, etc are indeed very powerful tools to determine the 3-Dimensional structure of a protein (including the membrane protein); theoretical mathematical and physical computational approaches can also allow us to obtain a description of the protein 3D structure at a submicroscopic level for some unstable, noncrystalline and insoluble proteins. X-ray crystallography finds the X-ray final structure of a protein, which usually need refinements using theoretical protocols in order to produce a better structure. This means theoretical methods are also important in determinations of protein structures. Optimization is always needed in the computer-aided drug design, structure-based drug design, molecular dynamics, and quantum and molecular mechanics. This paper introduces some…
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