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The ability of protein molecules to fold into their highly structured functional states is one of the most remarkable evolutionary achievements of biology. In recent years, our understanding of the way in which this complex self-assembly process takes place has increased dramatically. Much of the reason for this advance has been the development of energy surfaces (landscapes), which allow the folding reaction to be described and visualized in a meaningful manner. Analysis of these surfaces, derived from the constructive interplay between theory and experiment, has led to the development of a unified mechanism for folding and a recognition of the underlying factors that control the rates and products of the folding process.

To study protein folding in vitro, the solution conditions are generally changed from ones that stabilize the unfolded state to ones that stabilize the native state (e.g. by rapid dilution of denaturant). The reaction thus starts with a denatured polypeptide chain, which, in its limiting form, can be described as a random coil with no persistent long-range interactions8, 9. It consists of a statistical distribution of rapidly interconverting states with different local and global properties .

Simulations of protein folding

It typically takes a millisecond or more for even a small protein to fold. However, with present-day computers, it is not possible to simulate the behavior of a protein for more than approximately one μs of physical time if the motions of all the atoms and the associated solvent molecules are considered explicitly13. It has been necessary therefore to develop simplified theoretical models to perform the large number of simulations required to obtain a meaningful description of the kinetics and

Experimental methods of studying folding

Experiments can be used to test the concepts arising from the simulations, but the methods of doing so are not straightforward because the population of polypeptide chains is extremely heterogeneous during the critical parts of the folding process. As a result, the conventional description of a 'structure' is often inadequate, and even the concept of an 'average structure' might be of limited value. Another complication is that, although folding is slow compared with many simple reactions, it

 

The ability of protein molecules to fold into their highly structured functional states is one of the most remarkable evolutionary achievements of biology. In recent years, our understanding of the way in which this complex self-assembly process takes place has increased dramatically. Much of the reason for this advance has been the development of energy surfaces (landscapes), which allow the folding reaction to be described and visualized in a meaningful manner. Analysis of these surfaces, derived from the constructive interplay between theory and experiment, has led to the development of a unified mechanism for folding and a recognition of the underlying factors that control the rates and products of the folding process.

To study protein folding in vitro, the solution conditions are generally changed from ones that stabilize the unfolded state to ones that stabilize the native state (e.g. by rapid dilution of denaturant). The reaction thus starts with a denatured polypeptide chain, which, in its limiting form, can be described as a random coil with no persistent long-range interactions8, 9. It consists of a statistical distribution of rapidly interconverting states with different local and global properties .

Simulations of protein folding

It typically takes a millisecond or more for even a small protein to fold. However, with present-day computers, it is not possible to simulate the behavior of a protein for more than approximately one μs of physical time if the motions of all the atoms and the associated solvent molecules are considered explicitly13. It has been necessary therefore to develop simplified theoretical models to perform the large number of simulations required to obtain a meaningful description of the kinetics and

Experimental methods of studying folding

Experiments can be used to test the concepts arising from the simulations, but the methods of doing so are not straightforward because the population of polypeptide chains is extremely heterogeneous during the critical parts of the folding process. As a result, the conventional description of a 'structure' is often inadequate, and even the concept of an 'average structure' might be of limited value. Another complication is that, although folding is slow compared with many simple reactions, it

 

The ability of protein molecules to fold into their highly structured functional states is one of the most remarkable evolutionary achievements of biology. In recent years, our understanding of the way in which this complex self-assembly process takes place has increased dramatically. Much of the reason for this advance has been the development of energy surfaces (landscapes), which allow the folding reaction to be described and visualized in a meaningful manner. Analysis of these surfaces, derived from the constructive interplay between theory and experiment, has led to the development of a unified mechanism for folding and a recognition of the underlying factors that control the rates and products of the folding process.

To study protein folding in vitro, the solution conditions are generally changed from ones that stabilize the unfolded state to ones that stabilize the native state (e.g. by rapid dilution of denaturant). The reaction thus starts with a denatured polypeptide chain, which, in its limiting form, can be described as a random coil with no persistent long-range interactions8, 9. It consists of a statistical distribution of rapidly interconverting states with different local and global properties .

Simulations of protein folding

It typically takes a millisecond or more for even a small protein to fold. However, with present-day computers, it is not possible to simulate the behavior of a protein for more than approximately one μs of physical time if the motions of all the atoms and the associated solvent molecules are considered explicitly13. It has been necessary therefore to develop simplified theoretical models to perform the large number of simulations required to obtain a meaningful description of the kinetics and

Experimental methods of studying folding

Experiments can be used to test the concepts arising from the simulations, but the methods of doing so are not straightforward because the population of polypeptide chains is extremely heterogeneous during the critical parts of the folding process. As a result, the conventional description of a 'structure' is often inadequate, and even the concept of an 'average structure' might be of limited value. Another complication is that, although folding is slow compared with many simple reactions, it

 

The ability of protein molecules to fold into their highly structured functional states is one of the most remarkable evolutionary achievements of biology. In recent years, our understanding of the way in which this complex self-assembly process takes place has increased dramatically. Much of the reason for this advance has been the development of energy surfaces (landscapes), which allow the folding reaction to be described and visualized in a meaningful manner. Analysis of these surfaces, derived from the constructive interplay between theory and experiment, has led to the development of a unified mechanism for folding and a recognition of the underlying factors that control the rates and products of the folding process.

To study protein folding in vitro, the solution conditions are generally changed from ones that stabilize the unfolded state to ones that stabilize the native state (e.g. by rapid dilution of denaturant). The reaction thus starts with a denatured polypeptide chain, which, in its limiting form, can be described as a random coil with no persistent long-range interactions8, 9. It consists of a statistical distribution of rapidly interconverting states with different local and global properties .

Simulations of protein folding

It typically takes a millisecond or more for even a small protein to fold. However, with present-day computers, it is not possible to simulate the behavior of a protein for more than approximately one μs of physical time if the motions of all the atoms and the associated solvent molecules are considered explicitly13. It has been necessary therefore to develop simplified theoretical models to perform the large number of simulations required to obtain a meaningful description of the kinetics and

Experimental methods of studying folding

Experiments can be used to test the concepts arising from the simulations, but the methods of doing so are not straightforward because the population of polypeptide chains is extremely heterogeneous during the critical parts of the folding process. As a result, the conventional description of a 'structure' is often inadequate, and even the concept of an 'average structure' might be of limited value. Another complication is that, although folding is slow compared with many simple reactions, it