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

Competition and Oligopoly: A Case of UK Grocery Retailing

In this paper we develop a model of Bertrand price competition with uncertainty as to the number of bidders. The auction models predict retail price dispersion as an observable feature of price discrimination. The implications of the auction models are tested using a logit model on primary data. Some simulations of the logit model further enrich and capture critical states of chain-store rivalry. The findings show that consumer characteristics define type of store choice and that an auction model of price competition with uncertainty is an appropriate way to model retail grocery competition.

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

Spatial distribution of trace metals in urban soils and road dusts : an example from Manchester, UK

Urban soil quality is of concern under current UK contaminated land legislation in terms of potential impacts on human health, due to the legacy of industrial, mining and waste disposal activities and the fact that soils can act as a sink for potentially harmful substances (PHS) in the urban environment. As part of the the Geochemical Baseline Survey of the Environment (G-BASE) project of the British Geological Survey (BGS), 27 UK cities have been surveyed to establish baselines and assess the quality of urban soils. The G-BASE soil geochemical dataset for Manchester forms the basis of this project. Another medium that is a likely sink for PHS in urban environments is road dust sediment (RDS). RDS forms as an accumulation of particles on pavements and road surfaces, and has been shown to be both spatially and temporally highly variable in composition, as it is more susceptible to remobilisation and transport. RDS has been documented as carrying a high loading of contaminant species, including significant amounts of trace metals. Geochemical data from both soils and RDS, despite having different properties, are essential for environmental assessment in urban areas. Although studies of PHS in RDS and soils have been published, little is known about the spatial, geochemical and mineralogical linkages between these two media. The aim of this research is to define and establish these linkages, and produce novel mineralogical data on the PHS–particulate relationships within soils and RDS

The Economics of Mortgage Terminations: Implications for Mortgage Lenders and Mortgage Terms

The paper begins with the development of models explaining the mortgage refinancing and assumption decisions of households Having identified the economic variables influencing these decisions, we then simulate the models for different values to determine under what conditions households will refinance or assume. Finally, we draw some implications of these results for: (1) the impact of a decline in mortgage rates on the asset portfolio yields of mortgage lending institutions and (2) the effect of the observed rise in interest rate volatility, including the optimal terminations response of mortgage borrowers, on the terms of the mortgage contract and the returns to mortgage lenders on recently issued mortgage loans.