How can Qubits break the structure prediction puzzle

Links table

1. introduction

2. Poetic models and space coordination

3. Corporation on cases of Qubit

   3.1 Poetic structure coding in Qubit Sta

   3.2 Choose a junction plane

   3.3 Extension to other structures

4. Conclusions and references

1 introduction

Network or structures are engineering organisms with mathematical shapes used to represent physical systems. It was widely used in various fields, which are intense material physics, to study the degrees of freedom of molecules in chemistry and in the study of polymer dynamics and protein structures, to name a few, but not limited to [1]. In this article, we discuss the method of encrypting the network structures in the calculations of Qubits (as used in quantum computing algorithms). We explain a specific use of network models to predict the protein structure. A variety of network models have been used to predict the protein structure. Although proteins have very irregular structures, poetic models have been used to predict the basic structures. Network models are under the category of granular coarse models. The engineering that has been seen in the coarse models can have either constant representation or poetic representation [2]). The network models offer a large account on other representations. Figure 1 gives some poetic representations.

In this article, we do not suggest any quantitative algorithm to solve the problem of prediction of the protein structure, instead, we suggest a general coding methodology for network structures. The protein sequence consists mainly of turns or ties between neighboring monomaments or amino acids (also referred to as a grain in the beloved rough models). The rotation that the bonds can take is limited to the degrees of freedom of the network used. We explain how the coding methodology encodes the turns based on the specified network model. We take two specific models for a hairs, the cube with flat and cubes centered around the face (FCC), and we show the coding methodology. The article is organized as follows. In Section 2, we discuss network models and coordinates space that turns can take. In Section 3, we discuss how to set coordinates to the cases of math basis. Finally, we summarize the methodology in the conclusions.