Quantitative Biology

Bone repair using BMP-2 is a promising therapeutic approach in clinical practices, however, high dosages required to be effective pose issues of cost and safety. The present study explores the potential of low dose BMP-2 treatment via tissue engineering approach, which amalgamates 3-D macro/microporous-nanofibrous bacterial cellulose (mNBC) scaffolds and low dose BMP-2 primed murine mesenchymal stem cells (C3H10T1/2 cells). Initial studies on cell-scaffold interaction using unprimed C3H10T1/2 cells confirmed that scaffolds provided a propitious environment for cell adhesion, growth, and infiltration, owing to its ECM-mimicking nano-micro-macro architecture. Osteogenic studies were conducted by preconditioning the cells with 50 ng/mL BMP-2 for 15 minutes, followed by culturing on mNBC scaffolds for up to three weeks. The results showed an early onset and significantly enhanced bone matrix secretion and maturation in the scaffolds seeded with BMP-2 primed cells compared to the unprimed ones. Moreover, mNBC scaffolds alone were able to facilitate the mineralization of cells to some extent. These findings suggest that, with the aid of 'osteoinduction' from low dose BMP-2 priming of stem cells and 'osteoconduction' from nano-macro/micro topography of mNBC scaffolds, a cost-effective bone tissue engineering strategy can be designed for quick and excellent in vivo osseointegration.

With the recent advances in machine learning for quantum chemistry, it is now possible to predict the chemical properties of compounds and to generate novel molecules. Existing generative models mostly use a string- or graph-based representation, but the precise three-dimensional coordinates of the atoms are usually not encoded. First attempts in this direction have been proposed, where autoregressive or GAN-based models generate atom coordinates. Those either lack a latent space in the autoregressive setting, such that a smooth exploration of the compound space is not possible, or cannot generalize to varying chemical compositions. We propose a new approach to efficiently generate molecular structures that are not restricted to a fixed size or composition. Our model is based on the variational autoencoder which learns a translation-, rotation-, and permutation-invariant low-dimensional representation of molecules. Our experiments yield a mean reconstruction error below 0.05 Angstrom, outperforming the current state-of-the-art methods by a factor of four, and which is even lower than the spatial quantization error of most chemical descriptors. The compositional and structural validity of newly generated molecules has been confirmed by quantum chemical methods in a set of experiments.

Protein function and activity are a consequence of its three-dimensional structure. Single particle analysis of cryogenic electron micrographs has radically changed structural biology allowing atomic reconstruction of almost any type of proteins. While such an approach provides snapshots of three-dimensional structural information that can be correlated with function, the new frontier of protein structural biology is in the fourth dimension, time. Here we propose the use of liquid phase electron microscopy to expand structural biology into dynamic studies. We apply here single particle analysis algorithm to images of proteins in Brownian motion through time; thus, Brownian single particle analysis (BSPA). BSPA enables to reduce the acquisition time from hours, in cryo-EM, to seconds and achieve information on conformational changes, hydration dynamics, and effects of thermal fluctuations. Yielding all these previously neglected aspects, BSPA may lead to the verge of a new field: dynamic structural biology.

Fatty acid sugar esters represent an important class of non-ionic bio-based surfactants. They can be synthesized from vinyl fatty acids and sugars with enzyme as a catalyst. Herein, the influence of the solvent, the lipase and the temperature on a model reaction between vinyl palmitate and glucose via enzymatic catalysis has been investigated and the reaction conditions optimized. Full conversion into 6-O-glucose palmitate was reached in 40 hours in acetonitrile starting from a reactant ratio 1:1, at only 5%-wt loading of lipase from Candida antarctica B (CALB) without the presence of molecular sieves.

The theory of elastic rods can be used to describe certain geometric and topological properties of the DNA molecules. A similar effective field theory approach was previously suggested to describe the conformations and dynamics of proteins. In this letter we report a detailed study of the basic features of a version of the proposed model, which assumes proteins to be very long continuous curves. In the most appealing case, the model is based on a potential with a pair of minima corresponding to helical and strand-like configurations of the curves. It allows to derive several predictions about the geometric features of the molecules, and we show that the predictions are compatible with the phenomenology. While the helices represent the ground state configurations, the abundance of beta strands is controlled by a parameter, which can either completely suppress their presence in a molecule, or make them abundant. The few-parameter model investigated in the letter rather represents a universality class of protein molecules. Generalizations accounting for the discrete nature and inhomogeneity of the molecules presumably allow to model realistic cases.

In view of recent intense experimental and theoretical interests in the biophysics of liquid-liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs), heteropolymer models with chain molecules configured as self-avoiding walks on the simple cubic lattice are constructed to study how phase behaviors depend on the sequence of monomers along the chains. To address pertinent general principles, we focus primarily on two fully charged 50-monomer sequences with significantly different charge patterns. Each monomer in our models occupies a single lattice site and all monomers interact via a screened pairwise Coulomb potential. Phase diagrams are obtained by extensive Monte Carlo sampling performed at multiple temperatures on ensembles of 300 chains in boxes of sizes ranging from 52×52×52 to 246×246×246 to simulate a large number of different systems with the overall polymer volume fraction ϕ in each system varying from 0.001 to 0.1 . Phase separation in the model systems is characterized by the emergence of a large cluster connected by inter-monomer nearest-neighbor lattice contacts and by large fluctuations in local polymer density. The simulated critical temperatures, T cr , of phase separation for the two sequences differ significantly, whereby the sequence with a more "blocky" charge pattern exhibits a substantially higher propensity to phase separate. The trend is consistent with our sequence-specific random-phase-approximation (RPA) polymer theory, but the variation of the simulated T cr with a previously proposed "sequence charge decoration" pattern parameter is milder than that predicted by RPA. Ramifications of our findings for the development of analytical theory and simulation protocols of IDP LLPS are discussed.

Glucose biosensors play an important role in the diagnosis and continued monitoring of the disease, diabetes mellitus. This report proposes the development of a novel enzymatic electrochemical glucose biosensor based on TiO 2 nanotubes modified by AgO and Prussian blue (PB) nanoparticles (NPs), which has an additional advantage of possessing antimicrobial properties for implantable biosensor applications. In this study, we developed two high performance glucose biosensors based on the immobilization of glucose oxidase (GOx) onto Prussian blue (PB) modified TiO 2 nanotube arrays functionalized by Au and AgO NPs. AgO-deposited TiO 2 nanotubes were synthesized through an electrochemical anodization process followed by Ag electroplating process in the same electrolyte. Deposition of PB particles was performed from an acidic ferricyanide solution. The surface morphology and elemental composition of the two fabricated biosensors were investigated by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) which indicate the successful deposition of Au and AgO nanoparticles as well as PB nanocrystals. Cyclic voltammetry and chronoamperometry were used to investigate the performance of the modified electrochemical biosensors. The results show that the developed electrochemical biosensors display excellent properties in terms of electron transmission, low detection limit as well as high stability for the determination of glucose. Under the optimized conditions, the amperometric response shows a linear dependence on the glucose concentration to a detection limit down to 4.91 μ M with sensitivity of 185.1 mA M ?? cm$^{-2]$ in Au modified biosensor and detection limit of 58.7 μ M with 29.1 mA M ?? cm$^{-2]$ sensitivity in AgO modified biosensor.

Melanoma is one of the most dangerous skin malignancies due to its high metastatic tendency and high mortality. Activation of key signaling pathways enforcing melanoma progression depends on phosphorylation of tyrosine kinases, and oxidative stress. We here investigated the effect of the new bis-coumarin derivative (3,5-DCPBC) on human melanoma cell survival, growth, proliferation, migration, and intracellular redox state, and deciphered associated signal pathways. This novel derivative was found to be toxic for melanoma cells, and non-toxic for their benign counterparts, melanocytes and fibroblasts. 3,5-DCPBC inhibited cell survival, migration and proliferation of different metastatic, and non-metastatic melanoma cell lines through the profound suppression of phosphorylation of the Epidermal Growth Factor receptor, and related downstream pathways. Suppression of phosphorylation of key downstream transcription factors and different tyrosine kinases comprise JAK/STAT, SRC kinases, ERK and MAP kinases (p38alpha), all involved in melanoma progression. Simultaneous and specific targeting of multiple tyrosine kinases and corresponding key genes in melanoma cells makes 3,5-DCPBC a highly interesting anti-melanoma, and anti-metastatic drug candidate which may in the long term hold promise in the therapy of advanced melanoma.

Recent events leading to the worldwide pandemic of COVID-19 have demonstrated the effective use of genomic sequencing technologies to establish the genetic sequence of this virus. In contrast, the COVID-19 pandemic has demonstrated the absence of computational approaches to understand the molecular basis of this infection rapidly. Here we present an integrated approach to the study of the nsp1 protein in SARS-CoV-1, which plays an essential role in maintaining the expression of viral proteins and further disabling the host protein expression, also known as the host shutoff mechanism. We present three independent methods of evaluating two potential binding sites speculated to participate in host shutoff by nsp1. We have combined results from computed models of nsp1, with deep mining of all existing protein structures (using PDBMine), and binding site recognition (using msTALI) to examine the two sites consisting of residues 55-59 and 73-80. Based on our preliminary results, we conclude that the residues 73-80 appear as the regions that facilitate the critical initial steps in the function of nsp1. Given the 90% sequence identity between nsp1 from SARS-CoV-1 and SARS-CoV-2, we conjecture the same critical initiation step in the function of COVID-19 nsp1.

Biomolecular condensates such as membraneless organelles, underpinned by liquid-liquid phase separation (LLPS), are important for physiological function, with electrostatics -- among other interaction types -- being a prominent force in their assembly. Charge interactions of intrinsically disordered proteins (IDPs) and other biomolecules are sensitive to the aqueous dielectric environment. Because the relative permittivity of protein is significantly lower than that of water, the interior of an IDP condensate is a relatively low-dielectric regime, which, aside from its possible functional effects on client molecules, should facilitate stronger electrostatic interactions among the scaffold IDPs. To gain insight into this LLPS-induced dielectric heterogeneity, addressing in particular whether a low-dielectric condensed phase entails more favorable LLPS than that posited by assuming IDP electrostatic interactions are uniformly modulated by the higher dielectric constant of the pure solvent, we consider a simplified multiple-chain model of polyampholytes immersed in explicit solvents that are either polarizable or possess a permanent dipole. Notably, simulated phase behaviors of these systems exhibit only minor to moderate differences from those obtained using implicit-solvent models with a uniform relative permittivity equals to that of pure solvent. Buttressed by theoretical treatments developed here using random phase approximation and polymer field-theoretic simulations, these observations indicate a partial compensation of effects between favorable solvent-mediated interactions among the polyampholytes in the condensed phase and favorable polyampholyte-solvent interactions in the dilute phase, often netting only a minor enhancement of overall LLPS propensity from the very dielectric heterogeneity that arises from the LLPS itself. Further ramifications of this principle are discussed.