Retention of local conformational compactness in unfolding of barnase; Contribution of end-to-end interactions within quasi-modules

Protein folding pathways and state transitions described by classical equations of motion of an elastic network model

Protein topology defined by the matrix of residue contacts has proved to be a fruitful basis for the study of protein dynamics. The widely implemented coarse-grained elastic network model of backbone fluctuations has been used to describe crystallographic temperature factors, allosteric couplings, and some aspects of the folding pathway. In the present study, we develop a model of protein dynamics based on the classical equations of motion of a damped network model (DNM) that describes the folding path from a completely unfolded state to the native conformation through a single-well potential derived purely from the native conformation. The kinetic energy gained through the collapse of the protein chain is dissipated through a friction term in the equations of motion that models the water bath. This approach is completely general and sufficiently fast that it can be applied to large proteins. Folding pathways for various proteins of different classes are described and shown to correlate with experimental observations and molecular dynamics and Monte Carlo simulations. Allosteric transitions between alternative protein structures are also modeled within the DNM through an asymmetric double-well potential.

AS-ALPS: a database for analyzing the effects of alternative splicing on protein structure, interaction and network in human and mouse

We have constructed a database, AS-ALPS (alternative splicing-induced alteration of protein structure), which provides information that would be useful for analyzing the effects of alternative splicing (AS) on protein structure, interactions with other bio-molecules and protein interaction networks in human and mouse. Several AS events have been revealed to contribute to the diversification of protein structure, which results in diversification of interaction partners or affinities, which in turn contributes to regulation of bio-molecular networks. Most AS variants, however, are only known at the sequence level. It is important to determine the effects of AS on protein structure and interaction, and to provide candidates for experimental targets that are relevant to network regulation by AS. For this purpose, the three-dimensional (3D) structures of proteins are valuable sources of information; however, these have not been fully exploited in any other AS-related databases. AS-ALPS is the only AS-related database that describes the spatial relationships between protein regions altered by AS ('AS regions') and both the proteins' hydrophobic cores and sites of inter-molecular interactions. This information makes it possible to infer whether protein structural stability and/or protein interaction are affected by each AS event. AS-ALPS can be freely accessed at http://as-alps.nagahama-i-bio.ac.jp and http://genomenetwork.nig.ac.jp/as-alps/.

Protein unfolding behavior studied by elastic network model

Experimental and theoretical studies have showed that the native-state topology conceals a wealth of information about protein folding/unfolding. In this study, a method based on the Gaussian network model (GNM) is developed to study some properties of protein unfolding and explore the role of topology in protein unfolding process. The GNM has been successful in predicting atomic fluctuations around an energy minimum. However, in the GNM, the normal mode description is linear and cannot be accurate in studying protein folding/unfolding, which has many local minima in the energy landscape. To describe the nonlinearity of the conformational changes during protein unfolding, a method based on the iterative use of normal mode calculation is proposed. The protein unfolding process is mimicked through breaking the native contacts between the residues one by one according to the fluctuations of the distance between them. With this approach, the unfolding processes of two proteins, CI2 and barnase, are simulated. It is found that the sequence of protein unfolding events revealed by this method is consistent with that obtained from thermal unfolding by molecular dynamics and Monte Carlo simulations. The results indicate that this method is effective in studying protein unfolding. In this method, only the native contacts are considered, which implies that the native topology may play an important role in the protein unfolding process. The simulation results also show that the unfolding pathway is robust against the introduction of some noise, or stochastic characters. Furthermore, several conformations selected from the unfolding process are studied to show that the denatured state does not behave as a random coil, but seems to have highly cooperative motions, which may help and promote the polypeptide chain to fold into the native state correctly and speedily.