About 60% of our human body is made up of water. The next most abundant component is protein, which makes up 16% of the body.
Proteins are composed of molecules and work actively every day while receiving the power of water molecules around them. We elucidate the structure and function of the protein.
In order to elucidate the structure and function of proteins, it is important to analyze the structural data obtained by simulation.
We evaluate the structural stability of proteins by making full use of many analytical methods, from traditional methods such as principal component analysis to the latest technologies such as VR. As a result, we are contributing to application fields such as drug discovery.
A protein is a high molecular compound in which 20 kinds of amino acids are linked in a "chain" form. The structure and function of proteins differ depending on the number, type and the order of binding of amino acids.
In addition, the structure of a protein that was born is an amino acid sequence. This is called the primary structure.
From here, proteins are convoluted by the interaction of the surrounding environment and settle into a three-dimensional structure called "tertiary structure".
We will elucidate the structural stability and function of this tertiary structure using molecular simulations.
Amino acids are mainly composed of H (hydrogen), O (oxygen), N (nitrogen) and S (sulfur) atoms. Therefore, proteins are also composed of these atoms, and when they are affected by the interaction between these atoms (Van der Waals, etc.) and the interaction with water molecules around these atoms. (Hydration interaction, etc.)
The purpose of molecular simulation is to elucidate the structural stability and function of proteins composed of these atoms by solving the equation of motion for each of these interacting atoms.
So how do you evaluate the structural stability of proteins based on the data obtained from molecular simulations? Here, we will introduce a method called Principal Component Analysis (PCA) as a specific example.
PCA attempts to visualize the structural stability of proteins by compressing the coordinates (number of dimensions: 3 (x, y, z)-by-number of atoms) of all atoms obtained by simulation at each time to a lower dimension.
Specifically, first, the axis is oriented in the direction in which the fluctuation of the protein structure is maximum, and then the axis is perpendicular to that axis and in the direction in which the fluctuation is the second largest.
Next, by projecting each atomic coordinate at each time on these two axes, a "structural map" as shown in the figure can be obtained. If each of these plot points corresponds to a structure. The more often the structure is obtained, the more stable the structure is.
We may also use VR to observe the results of simulations to elucidate the function of proteins.