A Combined Computational and Experimental Approach to Studying Tropomyosin Kinase Receptor B Binders for Potential Treatment of Neurodegenerative Diseases.

Tropomyosin kinase receptor B (TrkB) has been explored as a therapeutic target for neurological and psychiatric disorders. However, the development of TrkB agonists was hindered by our poor understanding of the TrkB agonist binding location and affinity (both affect the regulation of disorder types). This motivated us to develop a combined computational and experimental approach to study TrkB binders. First, we developed a docking method to simulate the binding affinity of TrkB and binders identified by our magnetic drug screening platform from Gotu kola extracts. The Fred Docking scores from the docking computation showed strong agreement with the experimental results. Subsequently, using this screening platform, we identified a list of compounds from the NIH clinical collection library and applied the same docking studies. From the Fred Docking scores, we selected two compounds for TrkB activation tests. Interestingly, the ability of the compounds to increase dendritic arborization in hippocampal neurons matched well with the computational results. Finally, we performed a detailed binding analysis of the top candidates and compared them with the best-characterized TrkB agonist, 7,8-dyhydroxyflavon. The screening platform directly identifies TrkB binders, and the computational approach allows for the quick selection of top candidates with potential biological activities based on the docking scores.

The impact of surface area, volume, curvature, and Lennard-Jones potential to solvation modeling.

This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc.

Accurate, robust, and reliable calculations of Poisson-Boltzmann binding energies.

Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimation of electrostatic solvation free energy, ΔGel, and binding free energy, ΔΔGel, is important to computational biophysics and biochemistry. In this work, we investigate the grid dependence of our PB solver (MIBPB) with solvent excluded surfaces for estimating both electrostatic solvation free energies and electrostatic binding free energies. It is found that the relative absolute error of ΔGel obtained at the grid spacing of 1.0 Å compared to ΔGel at 0.2 Å averaged over 153 molecules is less than 0.2%. Our results indicate that the use of grid spacing 0.6 Å ensures accuracy and reliability in ΔΔGel calculation. In fact, the grid spacing of 1.1 Å appears to deliver adequate accuracy for high throughput screening. © 2017 Wiley Periodicals, Inc.

Rigidity Strengthening: A Mechanism for Protein-Ligand Binding.

Protein-ligand binding is essential to almost all life processes. The understanding of protein-ligand interactions is fundamentally important to rational drug and protein design. Based on large scale data sets, we show that protein rigidity strengthening or flexibility reduction is a mechanism in protein-ligand binding. Our approach based solely on rigidity is able to unveil a surprisingly apparently long-range contribution of apparently four residue layers to protein-ligand binding, which has ramifications for drug and protein design. Additionally, the present work reveals that among various pairwise interactions, the short-range ones within the distance of the van der Waals diameter are most important. It is found that the present approach outperforms all other state-of-the-art scoring functions for protein-ligand binding affinity predictions of two benchmark test sets.

Graphene woven fabric-polydimethylsiloxane piezoresistive films for smart multi-stimuli responses.

The outstanding properties of graphene, including its electromechanical property, could be engineered for wearable electronic sensor platforms. The tubular graphene weaved into a mesh or graphene woven fabrics (GWF) has been reported as one of the most sensitive materials for deformation detection, as well as a promising temperature sensor. Herein, we present the performance of our developed flexible, stretchable, and multiple sensitive sensors fabricated from GWF embedded in polydimethylsiloxane (PDMS) film substrate. The GWF/PDMS sensor shows a pressure sensitivity of 0.0142 kPa-1 in a wide linearity range of 0-20 kPa, an outstanding Gauge factor (GF) of 582 at a strain of 6.2 %, and a very high positive sensitivity of 0.0238 °C-1 in the temperature range of 25-80 °C. A practical application as a high sensitivity air pressure sensor able to measure low pressures (in the range of Pa to kPa) was also demonstrated. This sensor platform having desirable performance characteristics is an excellent candidate for wearable devices in the healthcare sector.

Wastewater treatment using a modified A2O process based on fiber polypropylene media.

The removal rates of organics and nutrients in municipal wastewater were examined using a laboratory-scale Anaerobic/Anoxic/Oxic (A2O) process modified with fiber polypropylene media at different operational conditions. The system demonstrated excellent performance with the removal rates of chemical oxygen demand (COD), total nitrogen (TN) and total phosphorous (TP) ranging from 91% to 98%, from 48% to 63%, and from 56% to 71%, respectively. Our system was superior to those previously reported based on more complex biofilm reactors, particularly from an economic point of view. For our system, a considerable reduction of COD (55%-68%) occurred even in the anaerobic reactor. The removal rates of COD and nutrients exhibited a slight decreasing trend with a higher organic loading rate (OLR) (0.5 to 2.2 kg COD m(-3) day(-1)) or with a shorter hydraulic retention time (HRT). The results may be attributed to the competition between nitrifying and heterotrophic bacteria and/or the insufficient time for biological uptake. It is expected that applying fiber polypropylene media to a conventional A2O process may significantly enhance the treatment efficacy of organics and nutrients as a cost-effective strategy.

Fibroblast growth and H-7 protein kinase inhibitor response monitored in microimpedance sensor arrays.

Functional genomic studies and drug candidate testing both require high throughput, parallel experimentation strategies to screen for variable cellular behaviors. In this article we describe the use of an impedance sensing electrode array that is capable of sensing cell "presence" as well as the extent of cell (focal) attachment to the substrate. The signals provided by mouse fibroblasts on a sensing structure containing four different sized electrodes are reported. In the absence of cells, each electrode's impedance was found to depend as expected on electrode size and frequency. The impedance increased by several-fold when fibroblasts attached and spread out over time. More notably, the sensors also detected the cellular response to the protein kinase C inhibitor, H-7. H-7 inhibits actomyosin contractility; thereafter, the loss of focal adhesion complexes occurs. The sensors, in turn, detected an impedance decrease after H-7 addition and an increase in impedance after H-7 removal.