No abstract

One of the most important challenges in biology is to understand and simulate the folding behavior of some simple two-state proteins. In this work, a large pool for descriptors of proteins was developed including amino acid descriptors, topological descriptors and charged partial surface area descriptors. A heuristic method was employed to select significant features. As a result, three descriptors, total contact distance, unfolding entropy change and total charge weighted partial negative surface area were chosen. Total contact distance was proved to be the most relevant factor controlling the folding behavior. Based on these descriptors, a support vector machine method was applied to build a predictive model. Comparing the statistical results of other works and methods, support vector machine method exhibited the best whole performance. Our results demonstrate that the native-state topology is the major determinant for the folding rates of two-state proteins and that the support vector machine method is a powerful tool to build a predictive model. In turn, the method and the knowledge can be used to develop in-silico predictive models to simulate the folding process of proteins.

No abstract

According to previous studies, oxidative stress is a leading cause of dopaminergic neuron death and may contribute to the pathogenesis of Parkinson's disease (PD). In the current study, we used chromatography of gel filtration to identify a novel peptide ( Lignosus rhinocerotis peptide [LRP]) from the sclerotium of Lignosus rhinocerotis (Cooke) Ryvarden. Its neuroprotective effect was evaluated using an in vitro PD model constructed by 6‐hydroxydopamine (6‐OHDA)‐stimulated to apoptosis in PC12 cells. The molecular weight of LRP is determined as 1532 Da and the secondary structure is irregular. The simple amino acid sequence of LRP is Thr‐Leu‐Ala‐Pro‐Thr‐Phe‐Leu‐Ser‐Ser‐Leu‐Gly‐Pro‐Cys‐Leu‐Leu. Notably, LRP has the ability to significantly boost the viability of PC12 cells after exposure to 6‐OHDA, as well as enhance the cellular activity of antioxidative enzymes like superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH‐Px). LRP also lowers the level of malondialdehyde (MDA), decreases the activation performance of Caspase‐3, and reduces 6‐OHDA‐induced apoptosis via inhibition of nuclear factor‐kappa B (NF‐κB) activation. These data indicate that LRP may have the potential to act as a neuroprotective agent.