REinforcement learning based Adaptive samPling: REAPing Rewards by Exploring Protein Conformational Landscapes

One of the key limitations of Molecular Dynamics simulations is the computational intractability of sampling protein conformational landscapes associated with either large system size or long timescales. To overcome this bottleneck, we present the REinforcement learning based Adaptive samPling (REAP) algorithm that aims to efficiently sample conformational space by learning the relative importance of each reaction coordinate as it samples the landscape. To achieve this, the algorithm uses concepts from the field of reinforcement learning, a subset of machine learning, which rewards sampling along important degrees of freedom and disregards others that do not facilitate exploration or exploitation. We demonstrate the effectiveness of REAP by comparing the sampling to long continuous MD simulations and least-counts adaptive sampling on two model landscapes (L-shaped and circular), and realistic systems such as alanine dipeptide and Src kinase. In all four systems, the REAP algorithm consistently demonstrates its ability to explore conformational space faster than the other two methods when comparing the expected values of the landscape discovered for a given amount of time. The key advantage of REAP is on-the-fly estimation of the importance of collective variables, which makes it particularly useful for systems with limited structural information

A Comparative Study of the Structural Dynamics of Four Terminal Uridylyl Transferases.

African trypanosomiasis occurs in 36 countries in sub-Saharan Africa with 10,000 reported cases annually. No definitive remedy is currently available and if left untreated, the disease becomes fatal. Structural and biochemical studies of trypanosomal terminal uridylyl transferases (TUTases) demonstrated their functional role in extensive uridylate insertion/deletion of RNA. Trypanosoma brucei RNA Editing TUTase 1 (TbRET1) is involved in guide RNA 3' end uridylation and maturation, while TbRET2 is responsible for U-insertion at RNA editing sites. Two additional TUTases called TbMEAT1 and TbTUT4 have also been reported to share similar function. TbRET1 and TbRET2 are essential enzymes for the parasite viability making them potential drug targets. For this study, we clustered molecular dynamics (MD) trajectories of four TUTases based on active site shape measured by Pocket Volume Measurer (POVME) program. Among the four TUTases, TbRET1 exhibited the largest average pocket volume, while TbMEAT1's and TbTUT4's active sites displayed the most flexibility. A side pocket was also identified within the active site in all TUTases with TbRET1 having the most pronounced. Our results indicate that TbRET1's larger side pocket can be exploited to achieve selective inhibitor design as FTMap identifies it as a druggable pocket

Extending the scope of poly(styrene)-block-poly(methyl methacrylate) for directed self assembly

Directed self-assembly (DSA) is a promising technique for extending conventional lithographic techniques by being able to print features with critical dimensions under 10 nm. The most widely studied block copolymer system is polystyreneblock- polymethyl methacrylate (PS-b-PMMA). The system is well understood in terms of its synthesis, properties and performance in DSA. However, PS-b-PMMA also has a number of limitations that impact on its performance and hence scope of application. The primary limitation is the low Flory-Huggins polymer-polymer interaction parameter (Χ), which limits the size of features that can be printed by DSA. Another issue with block copolymers in general is that specific molecular weights need to be synthesized to achieve desired morphologies and feature sizes. We are exploring blending ionic liquid additiveswithPS-b-PMMAto increase the Χ parameter. This allows smaller feature sizes to be accessed by PS-b-PMMA. Depending on the amount of additive it is also possible to tune the domain size and the morphology of the systems. These findings may expand the scope of PS-b-PMMA for DSA

Towards incorporating the notion of feature shape in music and text retrieval

Extracted feature data augment information resources with concrete characterizations of their content, but only approximate to the meaningful high-level descriptions typically expected by digital musicology scholars (domain experts with some technological affinity, but with no expertise in signal processing or feature data). Feature shapes provide abstract aggregations of feature types which share common characteristics when applied in extraction workflows. We explore the feasibility of feature shape-based filtering and querying within a large audio dataset of live music performances, employing operation sequences as specified by the Audio Feature Ontology and Vocabulary. We further implement analogous semantic structures for the HathiTrust Extracted Feature Dataset to demonstrate the general applicability of feature shapes in music and text retrieval

Phased Acoustic Array Measurements of a 5.75 Percent Hybrid Wing Body Aircraft

Detailed acoustic measurements of the noise from the leading-edge Krueger flap of a 5.75 percent Hybrid Wing Body (HWB) aircraft model were recently acquired with a traversing phased microphone array in the AEDC NFAC (Arnold Engineering Development Complex, National Full Scale Aerodynamics Complex) 40- by 80-Foot Wind Tunnel at NASA Ames Research Center. The spatial resolution of the array was sufficient to distinguish between individual support brackets over the full-scale frequency range of 100 to 2875 Hertz. For conditions representative of landing and take-off configuration, the noise from the brackets dominated other sources near the leading edge. Inclusion of flight-like brackets for select conditions highlights the importance of including the correct number of leading-edge high-lift device brackets with sufficient scale and fidelity. These measurements will support the development of new predictive models

Statistical Workflow for Feature Selection in Human Metabolomics Data.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations

Inhibition of the Gab2/PI3K/mTOR signaling ameliorates myeloid malignancy caused by Ptpn11 (Shp2) gain-of-function mutations

Activating mutations, such as E76K and D61Y, in PTPN11 (SHP2), a protein tyrosine phosphatase implicated in multiple cell signaling processes, are associated with 35% of patients with juvenile myelomonocytic leukemia (JMML), an aggressive childhood myeloproliferative neoplasm (MPN). Here we show that the interaction between leukemia-associated mutant Shp2 and Gab2, a scaffolding protein important for cytokine-induced PI3K/Akt signaling, was enhanced, and that the mTOR pathway was elevated in Ptpn11E76K/+ leukemic cells. Importantly, MPN induced by the Ptpn11E76K/+ mutation was markedly attenuated in Ptpn11E76K/+/Gab2-/- double mutant mice-overproduction of myeloid cells was alleviated, splenomegaly was diminished and myeloid cell infiltration in nonhematopoietic organs was decreased in these double mutants. Excessive myeloid differentiation of stem cells was also normalized by depletion of Gab2. Acute leukemia progression of MPN was reduced in the double mutant mice and, as such, their survival was much prolonged. Furthermore, treatment of Ptpn11E76K/+ mice with Rapamycin, a specific and potent mTOR inhibitor, mitigated MPN phenotypes. Collectively, this study reveals an important role of the Gab2/PI3K/mTOR pathway in mediating the pathogenic signaling of the PTPN11 gain-of-function mutations and a therapeutic potential of Rapamycin for PTPN11 mutation-associated JMML

An Investigation of the Ionic Conductivity and Species Crossover of Lithiated Nafion 117 in Nonaqueous Electrolytes

Nonaqueous redox flow batteries are a fast-growing area of research and development motivated by the need to develop low-cost energy storage systems. The identification of a highly conductive, yet selective membrane, is of paramount importance to enabling such a technology. Herein, we report the swelling behavior, ionic conductivity, and species crossover of lithiated Nafion 117 membranes immersed in three nonaqueous electrolytes (PC, PC : EC, and DMSO). Our results show that solvent volume fraction within the membrane has the greatest effect on both conductivity and crossover. An approximate linear relationship between diffusive crossover of neutral redox species (ferrocene) and the ionic conductivity of membrane was observed. As a secondary effect, the charge on redox species modifies crossover rates in accordance with Donnan exclusion. The selectivity of membrane is derived mathematically and compared to experimental results reported here. The relatively low selectivity for lithiated Nafion 117 in nonaqueous conditions suggests that new membranes are required for competitive nonaqueous redox flow batteries to be realized. Potential design rules are suggested for the future membrane engineering work.United States. Dept. of Energy. Office of Basic Energy Sciences. Joint Center for Energy Storage Researc