The new insights into protein structures by computational methods

Abstract

Protein structures have been reported to the Protein Data Bank (PDB) to share the information with scientists and researchers. They provide structural information and help other scientists and researchers to understand the mechanisms of these proteins. However, crystal structures and electron microscopy (EM) structures only show a single conformation of a protein which makes it difficult to understand the protein’s flexibility and internal motions. Computational and simulation methods offer alternative ways to study protein structures and understand mechanisms, and have recently been more frequently used for chemical, biochemical, and biological research. This work is going to show new insights into protein structures by integrating different computational methods, solving the issues with proteins and protein complexes, and present protein modelling, ligand docking, and simulations. Proctolin is a neuropeptide, RYLPT. The proctolin receptor is a G-protein coupled receptor. They are encoded in arthropods, but not in the honey bee. Varroa destructor is an ectoparasite of honey bees. Here, we tried to use proctolin to design a novel potential drug to treat these mites and save honey bees. In this work, the homology model of proctolin receptor has been built and used to study proctolin docking by Induced fit docking and QM (quantum mechanics) - polarized ligand docking. For further study, we performed molecular dynamics simulations to unravel the binding mechanism of proctolin. We found and explain that the first and second residues of proctolin form two cation-pi interactions with Tyr99 and Arg111 from proctolin receptor. This shows the first two residues act as an anchor docked into the binding pocket. Later, we also studied the chromophore behavior of red fluorescent protein. Fluorescent proteins have been improved from natural fluorescent proteins and heavily used in life science as protein labels, markers of gene expression, and living-cell imaging. The characteristics of fluorescent protein chromophores can give us information about the structure-function relationship with the protein matrix. This can guide us to engineer tuned color variants and broaden the spectral range of useful proteins. We present the behavior of the chromophore with the protein matrix and have a deeper understanding of fluorescent proteins. We performed molecular dynamics simulations on four trans-form fluorescent proteins. All fluorescent proteins with the trans-form chromophores tend to be non-planar, and the residues 67, 92, 143, and 197 are more important sites. These residues interact with the chromophore. Since the most inspiring thing that happened last year was the achievement of AlphaFold2, we also did an assessment and application of the structures predicted by AlphaFold2 on popular drug targets. It provides and emphasizes a valuable way to apply the AI developed method in drug discovery.