Search

Sequential optimization is one of the promising approaches in identifying the optimal candidate(s) (molecules, reactants, drugs, etc.) with desired properties (reaction yield, selectivity, efficacy, etc.) from a large set of potential candidates, while minimizing the number of experiments required. However, the high dimensionality of the feature space (e.g., molecular descriptors) makes it often difficult to utilize the relevant features during the process of updating the set of candidates to be examined. In this article, we developed a new sequential optimization algorithm for molecular problems based on reinforcement learning, multi-armed linear bandit framework, and online, dynamic feature selections in which relevant molecular descriptors are updated along with the experiments. We also designed a stopping condition aimed to guarantee the reliability of the chosen candidate from the dataset pool. The developed algorithm was examined by comparing with Bayesian optimization (BO), using two synthetic datasets and two real datasets in which one dataset includes hydration free energy of molecules and another one includes a free energy difference between enantiomer products in chemical reaction. We found that the dynamic feature selection in representing the desired properties along the experiments provides a better performance (e.g., time required to find the best candidate and stop the experiment) as the overall trend and that our multi-armed linear bandit approach with a dynamic feature selection scheme outperforms the standard BO with fixed feature variables. The comparison of our algorithm to BO with dynamic feature selection is also addressed. [ABSTRACT FROM AUTHOR]

Organisms must adapt to environmental stresses to ensure their survival and prosperity. Different types of stresses, including thermal, mechanical, and hypoxic stresses, can alter the cellular state that accompanies changes in gene expression but not the cellular identity determined by a chromatin state that remains stable throughout life. Some tissues, such as adipose tissue, demonstrate remarkable plasticity and adaptability in response to environmental cues, enabling reversible cellular identity changes; however, the mechanisms underlying these changes are not well understood. We hypothesized that positive and/or negative "Integrators" sense environmental cues and coordinate the epigenetic and transcriptional pathways required for changes in cellular identity. Adverse environmental factors such as pollution disrupt the coordinated control contributing to disease development. Further research based on this hypothesis will reveal how organisms adapt to fluctuating environmental conditions, such as temperature, extracellular matrix stiffness, oxygen, cytokines, and hormonal cues by changing their cellular identities. [ABSTRACT FROM AUTHOR]

Understanding the dynamic disorder behind a process, i.e., the dynamic effect of fluctuations that occur on a timescale slower or comparable with the timescale of the process, is essential for elucidating the dynamics and kinetics of complicated molecular processes in biomolecules and liquids. Despite numerous theoretical studies of single-molecule kinetics, our microscopic understanding of dynamic disorder remains limited. In the present study, we investigate the microscopic aspects of dynamic disorder in the isomerization dynamics of the Cys14–Cys38 disulfide bond in the protein bovine pancreatic trypsin inhibitor, which has been observed by nuclear magnetic resonance. We use a theoretical model with a stochastic transition rate coefficient, which is calculated from the 1-ms-long time molecular dynamics trajectory obtained by Shaw et al. [Science 330, 341–346 (2010)]. The isomerization dynamics are expressed by the transitions between coarse-grained states consisting of internal states, i.e., conformational sub-states. In this description, the rate for the transition from the coarse-grained states is stochastically modulated due to fluctuations between internal states. We examine the survival probability for the conformational transitions from a coarse-grained state using a theoretical model, which is a good approximation to the directly calculated survival probability. The dynamic disorder changes from a slow modulation limit to a fast modulation limit depending on the aspects of the coarse-grained states. Our analysis of the rate modulations behind the survival probability, in relation to the fluctuations between internal states, reveals the microscopic origin of dynamic disorder. [ABSTRACT FROM AUTHOR]

The ATP-binding cassette transporter ABCA3 mediates uptake of choline-phospholipids into intracellular vesicles and is essential for surfactant metabolism in lung alveolar type II cells. We have shown previously that ABCA3 mutations in fatal surfactant deficiency impair intracellular localization or ATP hydrolysis of ABCA3 protein. However, the mechanisms underlying the less severe phenotype of patients with ABCA3 mutation are unclear. In this study, we characterized ABCA3 mutant proteins identified in pediatric interstitial lung disease (pILD). E292V (intracellular loop 1), E690K (adjacent to Walker B motif in nucleotide binding domain 1), and T1114M (8th putative transmembrane segment) mutant proteins are localized mainly in intracellular vesicle membranes as wild-type protein. Lipid analysis and sucrose gradient fractionation revealed that the transport function of E292V mutant protein is moderately preserved, whereas those of E690K and T1114M mutant proteins are severely impaired. Vanadate-induced nucleotide trapping and photoaffinity labeling of wild-type and mutant proteins using 8-azido-[[sup.32]p]ATP revealed an aberrant catalytic cycle in these mutant proteins. These results demonstrate the importance of a functional catalytic cycle in lipid transport of ABCA3 and suggest a pathophysiological mechanism of pILD due to ABCA3 mutation. ATP-binding cassette A3 mutant; pediatric interstitial lung disease; lamellar body; lipid transporter; phosphatidylcholine

Research has been conducted on the diols. A new method for diol monoacylation has been developed and is described in the article.

Research indicates that the rat kidney-specific CIC-K1 chloride channel of the ascending limb of Henle's loop in the kidney is genetically influenced by a 40 bp purine-rich protein gene sequence. Experiments using gel-retardation analysis and inner medullary cells of simian virus 40 transgenic mice are described. Specific protein binding patterns are illustrated.