NestedAE: interpretable nested autoencoders for multi-scale materials characterization.

We introduce an interpretable machine learning architecture, NestedAE, for multiscale materials using nested supervised autoencoders. We benchmarked the performance of NestedAE on two databases: (1) a synthetic dataset created from nested analytical functions whose dimensionality is therefore known a priori, and (2) a multiscale MHP dataset that is a combination of an open source dataset containing atomic and ionic properties, and a second dataset containing device characterization using current density-voltage (J-V) analysis. The NestedAE architecture was found to have higher noise robustness and lower reconstruction losses when compared to a vanilla autoencoder (AE). Its application on the MHP dataset revealed links between crystal scale properties and device performance in agreement with earlier experimental observations.

Correlation between chemical denaturation and the unfolding energetics of Acanthamoeba actophorin.

The actin filament network is in part remodeled by the action of a family of filament severing proteins that are responsible for modulating the ratio between monomeric and filamentous actin. Recent work on the protein actophorin from the amoeba Acanthamoeba castellani identified a series of site-directed mutations that increase the thermal stability of the protein by 22°C. Here, we expand this observation by showing that the mutant protein is also significantly stable to both equilibrium and kinetic chemical denaturation, and employ computer simulations to account for the increase in thermal or chemical stability through an accounting of atomic-level interactions. Specifically, the potential of mean force (PMF) can be obtained from steered molecular dynamics (SMD) simulations in which a protein is unfolded. However, SMD can be inefficient for large proteins as they require large solvent boxes, and computationally expensive as they require increasingly many SMD trajectories to converge the PMF. Adaptive steered molecular dynamics (ASMD) overcomes the second of these limitations by steering the particle in stages, which allows for convergence of the PMF using fewer trajectories compared with SMD. Use of the telescoping water scheme within ASMD partially overcomes the first of these limitations by reducing the number of waters at each stage to only those needed to solvate the structure within a given stage. In the PMFs obtained from ASMD, the work of unfolding Acto-2 was found to be higher than the Acto-WT by approximately 120 kCal/mol and reflects the increased stability seen in the chemical denaturation experiments. The evolution of the average number of hydrogen bonds and number of salt bridges during the pulling process provides a mechanistic view of the structural changes of the actophorin protein as it is unfolded, and how it is affected by the mutation in concert with the energetics reported through the PMF.

Implementation of Telescoping Boxes in Adaptive Steered Molecular Dynamics.

Long-time dynamical processes, such as those involving protein unfolding and ligand interactions, can be accelerated and realized through steered molecular dynamics (SMD). The challenge has been the extraction of information from such simulations that generalize for complex nonequilibrium processes. The use of Jarzynski's equality opened the possibility of determining the free energy along the steered coordinate, but sampling over the nonequilibrium trajectories is slow to converge. Adaptive steered molecular dynamics (ASMD) and other related techniques have been introduced to overcome this challenge through the use of stages. Here, we take advantage of these stages to address the numerical cost that arises from the required use of very large solvent boxes. We introduce telescoping box schemes within adaptive steered molecular dynamics (ASMD) in which we adjust the solvent box between stages and thereby vary (and optimize) the required number of solvent molecules. We have benchmarked the method on a relatively long α-helical peptide, Ala30, with respect to the potential of mean force and hydrogen bonds. We show that the use of telescoping boxes introduces little numerical error while significantly reducing the computational cost.

A stoichiometric and pseudo kinetic model of loop mediated isothermal amplification.

Loop mediated isothermal amplification (LAMP) is one of the most popular isothermal DNA amplification techniques for research and commercial applications, enabling amplification of both DNA and RNA (with the assistance of reverse transcriptase). The LAMP mechanism is powered by strategic primer design and a strand displacement polymerase, generating products that fold over, creating loops. LAMP leads to generation of products of increasing length over time. These products containing multiple loops are conventionally called cauliflower structures. Existing literature on LAMP provides extremely limited understanding of progression of cascades of reactions involved in the reaction and it is believed that cauliflower structures of increasing length constitute a majority of the product formed in LAMP. This study presents a first of its kind stoichiometric and pseudo kinetic model to comprehend LAMP reactions in deeper depth by (i) classifying LAMP reaction products into uniquely identifiable categories, (ii) generating a condensed reaction network to depict millions of interconnected reactions occurring during LAMP, and (iii) elucidating the pathways for amplicon generation. Despite the inherent limitations of conventional stoichiometric modelling for polymerization type reactions (the network rapidly becomes too large and intractable), our model provides new theoretical understanding of the LAMP reaction pathway. The model shows that while longer length products are formed, it is the smaller length recycle amplicons that contribute more towards the exponential increase in the amount of double stranded DNA. Prediction of concentration of different types of LAMP amplicons will also contribute substantially towards informing design of probe-based assays.