Protein functions can be predicted based on their three-dimensional structures. However, many multidomain proteins have unstable structures, making it difficult to determine the whole structure in biological experiments. Additionally, multidomain proteins are often decomposed and identified based on their domains, with the structure of each domain often found in public databases. Recent studies have advanced structure prediction methods of multidomain proteins through computational analysis. In existing methods, proteins that serve as templates are used for three-dimensional structure prediction. However, when no protein template is available, the accuracy of the prediction is decreased. This study was conducted to predict the structures of multidomain proteins without the need for whole structure templates.
We improved structure prediction methods by performing rigid-body docking from the structure of each domain and reranking a structure closer to the correct structure to have a higher value. In the proposed method, the score for the domain-domain interaction obtained without a structural template of the multidomain protein and score for the three-dimensional structure obtained during docking calculation were newly incorporated into the score function. We successfully predicted the structures of 50 of 55 multidomain proteins examined in the test dataset.
Interaction residue pair information of the protein-protein complex interface contributes to domain reorganizations even when a structural template for a multidomain protein cannot be obtained. This approach may be useful for predicting the structures of multidomain proteins with important biochemical functions.
In the present study, thermodynamic properties of coarse-grained protein models have been studied by an extended ensemble method. Two types of protein model were analyzed; one is categorized into a fast folder and the other into a slow folder. Both models exhibit the following thermodynamic transitions: the collapse transition between random coil states and spatially compact, but non-native states and the folding transition between the collapsed states and the folded native states. Caloric curve for the fast folder shows strong statistical ensemble dependence, while almost no ensemble dependence is found for the slow folder. Microcanonical caloric curve for the fast folder exhibits S-shaped temperature dependence on the internal energy around the collapse transition which is reminiscent of the van der Waals loop observed for the first order transition; at the transition temperature, the collapsed and random coil states coexist dynamically. The corresponding microcanonical heat capacity is found to have negative region around the transition. This kind of exotic behaviors could be utilized to distinguish fast folding proteins.
Low-complexity (LC) sequences, regions that are predominantly made up of limited amino acids, are often observed in eukaryotic nuclear proteins. The role of these LC sequences has remained unclear for decades. Recent studies have shown that LC sequences are important in the formation of membrane-less organelles via liquid–liquid phase separation (LLPS). The RNA binding protein, fused in sarcoma (FUS), is the most widely studied of the proteins that undergo LLPS. It forms droplets, fibers, or hydrogels using its LC sequences. The N-terminal LC sequence of FUS is made up of Ser, Tyr, Gly, and Gln, which form a labile cross-β polymer core while the C-terminal Arg-Gly-Gly repeats accelerate LLPS. Normally, FUS localizes to the nucleus via the nuclear import receptor karyopherin β2 (Kapβ2) with the help of its C-terminal proline-tyrosine nuclear localization signal (PY-NLS). Recent findings revealed that Kapβ2 blocks FUS mediated LLPS, suggesting that Kapβ2 is not only a transport protein but also a chaperone which regulates LLPS during the formation of membrane-less organelles. In this review, we discuss the effects of the nuclear import receptors on LLPS.
A mathematical model of amyloid fiber formation is described that is able to simply specify different rates of fiber breakage at internal versus end regions. This Note presents the derivation of the relevant equations and provides results showing the dramatic effects of position biased fiber breakage on the kinetics of amyloid growth.