TY - BOOK

T1 - Monte Carlo Methods Development and Applications in Conformational Sampling of Proteins

AU - Tian, Pengfei

PY - 2014

Y1 - 2014

N2 - Proteins are molecular machines that carry out essential functions in theliving cell. Since the structure and dynamics are crucial for a protein’s functionalmechanism, a detailed knowledge of the protein’s conformation andconformational landscape at atomic level provides an ultimate descriptionof its exact function. Establishing a fundamental understanding of proteinsis vital to elucidate the causes of human diseases, so that potential curesand efficient drugs can be designed. An increasingly accurate computationalmodelling of protein molecules is, in many aspects, able to produce quantitativeinsights into their thermodynamic and mechanistic properties thatare difficult to probe in laboratory experiments. However, despite the rapidprogress in the development of molecular simulation, there are still two limitingfactors, (1), the current molecular mechanics force fields alone are notsufficient to provide an accurate structural and dynamical description ofcertain properties of proteins, (2), it is difficult to obtain correct statisticalweights of the samples generated, due to lack of equilibrium sampling. Inthis dissertation I present several new methodologies based on Monte Carlosampling methods to address these two problems. First of all, a novel techniquehas been developed for reliably estimating diffusion coefficients for usein the enhanced sampling of molecular simulations. A broad applicability ofthis method is illustrated by studying various simulation problems such asprotein folding and aggregation. Second, by combining Monte Carlo samplingwith a flexible probabilistic model of NMR chemical shifts, a series ofsimulation strategies are developed to accelerate the equilibrium sampling offree energy landscapes of proteins. Finally, a novel approach is presented topredict the structure of a functional amyloid protein, by using intramolecularevolutionary restrains in Monte Carlo simulations.

AB - Proteins are molecular machines that carry out essential functions in theliving cell. Since the structure and dynamics are crucial for a protein’s functionalmechanism, a detailed knowledge of the protein’s conformation andconformational landscape at atomic level provides an ultimate descriptionof its exact function. Establishing a fundamental understanding of proteinsis vital to elucidate the causes of human diseases, so that potential curesand efficient drugs can be designed. An increasingly accurate computationalmodelling of protein molecules is, in many aspects, able to produce quantitativeinsights into their thermodynamic and mechanistic properties thatare difficult to probe in laboratory experiments. However, despite the rapidprogress in the development of molecular simulation, there are still two limitingfactors, (1), the current molecular mechanics force fields alone are notsufficient to provide an accurate structural and dynamical description ofcertain properties of proteins, (2), it is difficult to obtain correct statisticalweights of the samples generated, due to lack of equilibrium sampling. Inthis dissertation I present several new methodologies based on Monte Carlosampling methods to address these two problems. First of all, a novel techniquehas been developed for reliably estimating diffusion coefficients for usein the enhanced sampling of molecular simulations. A broad applicability ofthis method is illustrated by studying various simulation problems such asprotein folding and aggregation. Second, by combining Monte Carlo samplingwith a flexible probabilistic model of NMR chemical shifts, a series ofsimulation strategies are developed to accelerate the equilibrium sampling offree energy landscapes of proteins. Finally, a novel approach is presented topredict the structure of a functional amyloid protein, by using intramolecularevolutionary restrains in Monte Carlo simulations.

UR - https://soeg.kb.dk/permalink/45KBDK_KGL/fbp0ps/alma99122816240205763

M3 - Ph.D. thesis

BT - Monte Carlo Methods Development and Applications in Conformational Sampling of Proteins

PB - The Niels Bohr Institute, Faculty of Science, University of Copenhagen

ER -