Molecular Dynamics in Protein Structure Quality Assessment and Refinement
Creators: name: Monroe, Lyman K
Publisher: name: Purdue University Graduate School
Year: 2022
Subjects: Animal physiology - biophysics
Human biophysics
Bioinformatics and computational biology not elsewhere classified
Structural biology (incl. macromolecular modelling)

description: Proteins are the active biomolecules of the cell. They perform metabolic action, give the cell structure, protect the cell from antigens, give the cell motility, and much more. The function of proteins are intrinsically linked to their structures, so it is therefore necessary to characterize the structure of a protein to fully understand its function and operation. In this research the application of computational methods, primarily molecular dynamics, towards protein structure determination, refinement, and quality assessment were studied. I applied molecular dynamics techniques to four major projects; the determination of relative error of atomic models deposited with electron microscopy maps in the EMDB, solving and refining atomics structure models for the PhageG major capsid proteins, the elucidation of the structure the protein USP7 and the binding pose of a of a candidate therapeutic drug, and the determination of relative stability of candidate protein folds to distinguish near native models from not. Each year an increasing number of protein structures have been solved using electron microscopy (EM). The influx of solved structure has proven to be a boon to the community, but it is necessary to note that the quality EM maps vary substantially. To understand to what extent atomic structure models generated from EM matched their respective maps, two computational structure refinement methods were used to examine how much structures could be refined. The deviation from the starting structure by refinement, as well as the disagreement between refined models produced by the two computational methods, scaled inversely with both the global and local map resolutions. The results suggested that the observed discrepancy between the deposited maps and refined models is due to the lack of resolvable structural data present in EM maps at low to moderate resolutions, and therefore these annotations must be used with caution in further applications. I also successfully implemented molecular dynamics as a method for protein structure quality assessment. Proteins tend towards shapes which minimize their energy. Experimentally, the stability of a protein can be measured through several techniques, one such technique includes the controlled application of tension to proteins in an atomic force microscopy (AFM) framework. This kind of tension-based approach is of interest as it probes the force required to unfold individual domains of a protein rather than a bulk characteristic like molting point or activity. It has been shown that key features observed in an AFM experiment can be well reproduced with molecular dynamics simulation, which has been applied to characterize the mechanisms of unfolding of proteins as well as ligand-protein interactions. Steered molecular dynamics (SMD) was applied to pull and unfold proteins and determine the force required to unfold them. The relative force required to unfold different models with the same sequence was used to estimate relative model accuracy. This follows from the hypothesis that the structural stability of a given model’s conformation would positively correlate with its accuracy, i.e. how close that model is to its native fold. It was found that near-native models could be successfully selected by comparing the forces required to unfold models, indicating that high unfolding forces indeed indicated high model stability, which in turn correlated with model accuracy. I also applied molecular dynamics-based approaches for refinement of protein structures that are determined from cryo-EM density maps. Computational approaches for protein structure refinement are often developed with the design aim of requiring a user input and experimental data. I modeled the atomic structure of the major capsid protein gp27 and the decoration protein gp26 of PhageG to a 6.1Å resolution electron microscopy map. PhageG modeling was done by mapping the sequences to a presumed homolog (Hk97), arranging the subunits into hexamers and trimmers as suggested by mass spectroscopy data, rigid docking to respective map segments, refinement against half maps using MDFF across a range of weights, and then finally refinement to the whole map using the optimized weight. I also modeled the atomic structure of the protein USP7 to an 8.2 Å resolution map. USP7 modeling was done by combining crystalized domains of the whole structure, rigidly docking the model to the EM map by hand, and then refining in a similar manner as PhageG, with the added approach of weight scaling to overcome local minima along the relaxation. The USP7 model was further validated by exhibiting a ligand-protein binding pose, determined by glide, which corresponded to enzymatic activity mutation assays. In summary I applied molecular dynamics, in conjunction with other computational methods, towards protein structure determination, refinement, and quality assessment.