Exploring Human Diseases and Biological Mechanisms by Protein Structure Prediction and Modeling

Abstract

Protein structure prediction and modeling provide a tool for understanding protein functions by computationally constructing protein structures from amino acid sequences and analyzing them. With help from protein prediction tools and web servers, users can obtain the three-dimensional protein structure models and gain knowledge of functions from the proteins. In this chapter, we will provide several examples of such studies. As an example, structure modeling methods were used to investigate the relation between mutation-caused misfolding of protein and human diseases including epilepsy and leukemia. Protein structure prediction and modeling were also applied in nucleotide-gated channels and their interaction interfaces to investigate their roles in brain and heart cells. In molecular mechanism studies of plants, rice salinity tolerance mechanism was studied via structure modeling on crucial proteins identified by systems biology analysis; trait-associated protein-protein interactions were modeled, which sheds some light on the roles of mutations in soybean oil/protein content. In the age of precision medicine, we believe protein structure prediction and modeling will play more and more important roles in investigating biomedical mechanism of diseases and drug design.

Keywords: Biological mechanism; GWAS; Human disease; Plant breeding; Protein misfolding; Protein structure modeling; Protein structure prediction; Sequence mutation.

Figure 3.1:. An example of using the ProBis web server to perform protein-ligand binding site prediction.

Section A represents the template protein 2P3E and depicts its binding region (represented by red spheres) as identified by ProBis. Section B shows an enlarged view of this binding region surrounded by a simplified view of the tertiary structure of 2P3E. Section C depicts the structure of T0515 with its predicted binding region and the aligned region of 2P3E. Section D provides a closer view of the predicted binding region of T0515 without the aligned region of 2P3E and surrounded by a simplified representation of the tertiary structure of T0515. Section E depicts the same view as section C but also includes the aligned region of 2P3E (represented as a mixture of blue and red spheres). Section F offers a more detailed view of the predicted binding region of T0515 and the aligned region of 2P3E.

Figure 3.2:. ProBis results depicting the tertiary structure of PDB ID 1VPQ (Tm1631) and its predicted binding region (red spheres).

The red spheres represent the predicted binding region and the rest of the image follows the same coloring scheme as Figure 3.1.

Figure 3.3:. Predicted protein structural modeling of the wild-type γ2 and the mutant γ2(R136X), γ2(Q390X) and γ2(W429X) subunits.

Figure 3.4:. Docking models for potential mutant γ2 subunit homodimers by SymmDock.

In each panel, the two γ2 subunits are shown in red and green; (A) wide-type γ2 dimer; (B) γ2 (R136X) mutant dimer; (C) γ2 (Q390X) mutant dimer; (D) γ2 (W429X) mutant dimer.

Figure 3.5:. A schematic representation of the interaction between HCN2/4 and Cav3.

HCN2 was shown in left and HCN4 in right. Cav3 N-terminal domain was shown in blue, and HCN2/HCN4 N-terminal ordered region was shown in red. The side chains of the three hydrophobic residuals (W, Y, F) in caveolin-binding motif were labeled in orange.

Figure 3.6:. Effect of AKT1 mutation on the protein structure.

(A) Superimposed structures of AKT1 protein structure template (PDB ID = 3O96) and homology model of AKT1 protein with point mutation (from JMML patient) (the AKT1 protein sequence in template structure is shifted by 62 residues in the template sequence). (B) & (C) Polar contacts around the wild type ARG251 residue and its immediate neighbors were visualized using Ligplot+[75]; similarly, polar contacts around CYS189 and its immediate neighbors were also visualized using Ligplot+. There is a change in the electron density due to mutation as shown by change in positions of the hydrophobic contacts and loss of hydrogen bonding between ASP248 and PHE407.

Figure 3.7:. Predicted structural model of protein Os01g0725800.

Figure 3.8:. Protein-protein interaction on predicted protein structures containing SNP locations.

SNP293 is located in the protein Glyma08g26580.1 (upper, green) and SNP 792 is located in the protein Glyma19g07330.1 (lower, cyan). The polymorphism sites (red) are located at the interface of the interaction