Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning

We developed a method to improve protein thermostability, "loop-walking method". Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as a hot-spot loop having an impact on thermostability, and the P233G/L234E/V235M mutant was found from 214 variants in the L7 library. Although a more excellent mutant might be discovered by screening all the 8000 P233X/L234X/V235X mutants, it was difficult to assay all of them. We therefore employed machine learning. Using thermostability data of the 214 mutants, a computational discrimination model was constructed to predict thermostability potentials. Among 7786 combinations ranked in silico, 20 promising candidates were selected and assayed. The P233D/L234P/V235S mutant retained 66% activity after heat treatment at 60 degrees C for 30 min, which was higher than those of the wild-type enzyme (5%) and the P233G/L234E/V235M mutant (35%)

Synthesis of high-silica CHA type zeolite by interzeolite conversion of FAU type zeolite in the presence of seed crystals

The influence of seed crystals on the interzeolite conversion of FAU type zeolite into CHA type zeolite was investigated in the presence of benzyltrimethylammonium hydroxide as a structure-directing agent under various hydrothermal synthesis conditions. Pure and highly crystalline CHA type zeolites with a wide range of Si/Al ratios were obtained in a shorter crystallization time as compared with those obtained without seed crystals. Furthermore, we achieved the first successful synthesis of high-silica CHA type zeolite in the absence of Na(+) cations by increasing the seed content. The protonated CHA type zeolite with a Si/Al ratio of ca. 15 yielded the highest propylene yield of ca. 48 C-% in ethanol conversion into light olefins

Activation of Rho in the injured axons following spinal cord injury

Axons of the adult central nervous system have very limited ability to regenerate after injury. This inability may be, at least partly, attributable to myelin-derived proteins, such as myelin-associated glycoprotein, Nogo and oligodendrocyte myelin glycoprotein. Recent evidence suggests that these proteins inhibit neurite outgrowth by activation of Rho through the neurotrophin receptor p75(NTR)/Nogo receptor complex. Despite rapidly growing knowledge on these signals at the molecular level, it remained to be determined whether Rho is activated after injury to the central nervous system. To assess this question, we establish a new method to visualize endogenous Rho activity in situ. After treatment of cerebellar granular neurons with the Nogo peptide in vitro, Rho is spatially activated and colocalizes with p75(NTR). Following spinal cord injury in vivo, massive activation of Rho is observed in the injured neurites. Spatial regulation of Rho activity may be necessary for axonal regulation by the inhibitory cues

Collection of Data Variation Using a High-Throughput Image-Based Assay Platform Facilitates Data-Driven Understanding of TRPA1 Agonist Diversity

Because transient receptor potential ankyrin 1 (TRPA1) is involved in various physiological functions, TRPA1-targeting drugs have been energetically developed. Although TRPA1 is considered a multimodal receptor, the structural diversity of TRPA1 agonists is not fully elucidated. We hypothesized that collecting a wider variation of TRPA1–compound interaction data would aid the understanding of its complex mechanism and aimed to challenge such data collection using an “image-based TRPA1 assay system combined with an in silico chemical space clustering concept.” Our library was clustered with 27 physicochemical molecular descriptors in silico, and structurally diverse compounds from each cluster were selected for a detailed kinetic assay to investigate variations of agonist structural rules. Through two sets of assays evaluating various compounds in parallel with validating effects of the previously established structural rules, we discovered that different chemical groups contribute to agonist activity, indicating that there are multiple agonist design concepts. A novel core structure for a TRPA1 agonist has been also proposed. Our new approach, “collection of TRPA1 activity data on compounds with physicochemical diversity,” will not only facilitate the understanding of the structural diversity of TRPA1 agonists but also contribute to the development of a new type of TRPA1-targeting drug