Computational Studies of Protein-ligand Systems Using Enhanced Sampling Methods
Abstract: This thesis focuses on studies of protein-ligand systems using enhanced sampling methods. In chapter I, I give a brief introduction to the time-scale problem and some enhanced sampling methods. In chapter II, the basics of MD simulation are reviewed. In chapter III, the theoretical backgrounds of umbrella sampling, bias-exchange metadynamics and infrequent metadynamics are presented. In chapter IV, the 5 papers included in this thesis are summarized. In paper 1, we studied the relationship between the antibacterial activities of antimicrobial peptides and their aggregation propensities. We found that an increasing aggregation propensity increases the free energy cost of peptide embedding into the bacterial membrane and decreases antibacterial activity. In paper 2, we employed the umbrella sampling approach to obtain the free energy landscape of Pittsburgh compound-B penetrating into the core binding sites of amyloid βfibrils. Our study suggested that, for the design of probes binding to fibril like proteins, other than the binding affinity, the dynamics of probes in the fibrils should also be considered. In paper 3, we studied the coupled folding and binding process of the intrinsically disordered protein p53 to MDM2 with bias-exchange metadynamics and infrequent metadynamics. We reconstructed the free energy landscape and built a kinetic network for this process. In paper 4, we studied the binding modes of ASEM with a chimera structure of α7 nicotinic acetylcholine receptor with well-tempered metadynamics. We found that an important residue, Trp53, can significantly affect the stabilities of the binding modes. In paper 5, we proposed an efficient method to estimate the transition times of rare events in biomolecular systems. In chapter V, I present a conclusion of this thesis and propose an outlook related to the selection of collective variables for enhanced sampling methods.
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