Monte Carlo simulation algorithm for B-DNA

Investigating the potential of organic semiconductor materials by DFT and TD-DFT calculations on aNDTs

The effects of substituting electron withdrawing and electron donating functional groups on the electronic and optical properties of angular naphthodithiophene (aNDT) were studied. Substitutions were made to the aNDT molecule at position 2 and 7, respectively. The computed ionization parameters and reorganisation energies distinguished between the p-type and n-type semiconducting natures of the unsubstituted aNDT molecule and those with the -C₂H₅, -OCH₃, -NO₂, and -CN substituents. However, the aNDT molecule with C₂H₅ as a substitution showed p-type behaviour since it had the largest electron reorganisation energy of about 0.37 eV. The ambipolar semiconducting property of methoxy [-OCH₃-] substituted aNDT molecule was revealed from the RMSD value of 0.03 Å for both positive and negative charges with respect to neutral geometry. The absorption spectra differ significantly from those of unsubstituted aNDT, which reveals the impact of functional group substitution that changes the energy level of the molecules. The maximum absorption (λ_max) and oscillator strength (f) at the excited states in vacuum was investigated using time dependent density functional theory (TD-DFT). The aNDT with electron withdrawing group [-NO₂] substitution has a maximum absorption wavelength of 408 nm. Studying the intermolecular interactions between aNDT molecules was also accomplished with the help of Hirshfeld surface analysis. The current work provides insight into the development of novel organic semiconductors.

Searching for Aquamelt Behavior among Silklike Biomimetics during Fibrillation under Flow

In this paper, we elucidate a generic mechanism behind strain-induced phase transition in aqueous solutions of silk-inspired biomimetics by atomistic molecular dynamics simulations. We show the results of modeling of homopeptides polyglycine Gly₃₀ and polyalanine Ala₃₀ and a heteropeptide (Gly-Ala-Gly-Ala-Gly-Ser)₅, i.e., the simplest and yet relevant sequences that could mimic the behavior of natural silk under stress conditions. First, we analyze hydrophobicities of the sequences by calculating the Gibbs free energy of hydration and inspecting the interchain hydrogen bonding and hydration by water. Second, the force-extension profiles are scanned and compared with the results for poly(ethylene oxide), the synthetic polymer for which the aquamelt behavior has been proved recently. Additionally, the conformational transitions of oligopeptides from coiled to extended states are characterized by a generalized order parameter and by the dependence of the solvent-accessible surface area of the chains on applied stretching. Fibrillation itself is surveyed using both the two-dimensional interchain pair correlation function and the SAXS/WAXS patterns for the aggregates formed under stress. These are compared with experimental data found in the literature on fibril structure of silk composite materials doped with oligoalanine peptides. Our results show that tensile stress introduced into aqueous oligopeptide solutions facilitates interchain interactions. The oligopeptides display both a greater resistance to extension as compared to poly(ethylene oxide) and a reduced ability for hydrogen bonding of the stretched chains between oligomers and with water. Fiber formation is proved for all simulated objects, but the most structured one is made of a heteropeptide (Gly-Ala-Gly-Ala-Gly-Ser)₅: For this sequence, we obtain the highest degree of the secondary structure motifs in the fiber. We conclude that this is the most promising candidate among considered sequences to find the aquamelt behavior in further experimental studies.

Flow-Induced Formation of Thin PEO Fibers in Water and Their Stability After the Strain Release

Recently, we have shown that a tensile stress applied to chains of poly(ethylene oxide) (PEO) in water reduces the solubility and leads to phase separation of PEO chains from water with the formation of a two-phase region. In this work, we further elucidate the generic mechanism behind strain-induced phase transitions in aqueous PEO solutions with concentrations of 50-60 wt % by performing all-atom molecular dynamics simulations. In particular, we study the stability of oriented PEO fibers after removing stretching forces. We found that the size of the PEO bundle increased with time, which is associated with the dissolution of PEO chains on the fiber surface due to the reformation of hydrogen bonds between the outer PEO molecules and water. For precise characterization of the fibers, the scattering patterns (small- and wide-angle X-ray spectra) for configurations taken at different relaxation times are calculated. The tendency of the oligomer chains to be peeled off from the surface of the bundle eventually might lead to a complete dissolution of the PEO fiber. We conclude that either entanglement constraints or a quick drying process are necessary to conserve the fiber structure in a quiescent state. The scattering results show that external strain induced a liquid-liquid phase separation first. On long time scales, this can be a precursor for crystallization of the fiber.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

BEES: Bayesian Ensemble Estimation from SAS

Many biomolecular complexes exist in a flexible ensemble of states in solution that is necessary to perform their biological function. Small-angle scattering (SAS) measurements are a popular method for characterizing these flexible molecules because of their relative ease of use and their ability to simultaneously probe the full ensemble of states. However, SAS data is typically low dimensional and difficult to interpret without the assistance of additional structural models. In theory, experimental SAS curves can be reconstituted from a linear combination of theoretical models, although this procedure carries a significant risk of overfitting the inherently low-dimensional SAS data. Previously, we developed a Bayesian-based method for fitting ensembles of model structures to experimental SAS data that rigorously avoids overfitting. However, we have found that these methods can be difficult to incorporate into typical SAS modeling workflows, especially for users that are not experts in computational modeling. To this end, we present the Bayesian Ensemble Estimation from SAS (BEES) program. Two forks of BEES are available, the primary one existing as a module for the SASSIE web server and a developmental version that is a stand-alone Python program. BEES allows users to exhaustively sample ensemble models constructed from a library of theoretical states and to interactively analyze and compare each model's performance. The fitting routine also allows for secondary data sets to be supplied, thereby simultaneously fitting models to both SAS data as well as orthogonal information. The flexible ensemble of K63-linked ubiquitin trimers is presented as an example of BEES' capabilities.

Determining Atomistic SAXS Models of Tri-Ubiquitin Chains from Bayesian Analysis of Accelerated Molecular Dynamics Simulations

Small-angle X-ray scattering (SAXS) has become an increasingly popular technique for characterizing the solution ensemble of flexible biomolecules. However, data resulting from SAXS is typically low-dimensional and is therefore difficult to interpret without additional structural knowledge. In theory, molecular dynamics (MD) trajectories can provide this information, but conventional simulations rarely sample the complete ensemble. Here, we demonstrate that accelerated MD simulations can be used to produce higher quality models in shorter time scales than standard simulations, and we present an iterative Bayesian Monte Carlo method that is able to identify multistate ensembles without overfitting. This methodology is applied to several ubiquitin trimers to demonstrate the effect of linkage type on the solution states of the signaling protein. We observe that the linkage site directly affects the solution flexibility of the trimer and theorize that this difference in plasticity contributes to their disparate roles in vivo.