Gas Dynamics By Radhakrishnan Pdf Free 37
Cdztattoo Barreto
Our research interests lie at the interface of chemical physics and molecular biology. Our goal is to provide molecular level characterization of complex biomolecular systems and formulate quantitatively accurate microscopic models for predicting the interactions of various therapeutic agents with innate biochemical signaling mechanisms.We employ several computational algorithms ranging from techniques to treat electronic structure, molecular dynamics, Monte Carlo simulations, stochastic kinetic equations, and complex systems analyses in conjunction with the theoretical formalisms of statistical and quantum mechanics, and high performance computing in massively parallel architectures.
Research in the Radhakrishnan lab focuses on the molecular mechanisms of eukaryotic transcription regulation with emphasis on how transcription factors engage with DNA, recruit specific coactivators and corepressors via intrinsically disordered transactivation or transrepression domains and how multi-protein coactivator/corepressor-bearing chromatin-modifying complexes assemble and engage with chromatin. We are asking these questions in the context of (i) nuclear receptors that use atypical mechanisms to effect transcriptional activation and (ii) a cohort of related, yet functionally distinct, histone deacetylase (HDAC)-associated chromatin-modifying complexes that fundamentally impact on cellular physiology in eukaryotes. We address these questions using molecular biological, biochemical, and biophysical approaches including solution NMR spectroscopy, electron paramagnetic resonance (EPR), macromolecular X-ray crystallography, and cryogenic electron microscopy (cryoEM) as well as computational approaches including informatics and molecular dynamics (MD) simulations. Both projects have immense biological and biomedical significance as inhibitors of HDACs and nuclear receptors are targets for treating a variety of human diseases including cancer.
Current projects in the lab focus on the NR4A family of nuclear receptors comprising Nur77, Nurr1, and NOR1. Each of these receptors plays important roles in metabolism, inflammation, and the proper development of dopaminergic neurons, among others. We are asking how these rather atypical receptors activate transcription via their ligand-binding domain as well as their activation domain at the N-terminus of these proteins. We are also asking whether these receptors function in a ligand-dependent or ligand-independent manner. Separately, we are asking how the evolutionarily-conserved, histone deacetylase (HDAC)-containing Sin3L/Rpd3L complex is assembled, what the precise molecular role(s) of the conserved subunits, which harbor domains of poorly characterized structure and function, are, including whether they regulate HDAC activity and how the complex engages chromatin and DNA-bound factors. Finally, we are developing the next iteration of a popular web application called MONSTER that can mine experimentally-determined structures for stabilizing interactions in macromolecular complexes. New enhancements include a JavaScript-based user interface, a database for storing and mining results, a stability predictor for mutants, and an automated tool for generating evolutionary conservation profiles.
The main objective of this paper is to study the soliton solutions and dynamics analysis of the fractional Radhakrishnan-Kundu-Lakshmanan equation with multiplicative noise in the Stratonovich sense. Firstly, the wave transformation is used to obtain the nonlinear ordinary differential equation, and then the nonlinear ordinary differential equation is transformed into a two-dimensional plane dynamic system with a Hamiltonian system. Secondly, the phase portrait and sensitivity of the plane dynamic system and its perturbed system are studied using Maple software. Thirdly, the soliton solutions of the stochastic fractional Radhakrishnan-Kundu-Lakshmanan equation can be constructed, and the Jacobian function solutions and hyperbolic function solutions are obtained. Finally, some three-dimensional and two-dimensional diagrams of the obtained solutions are also drawn. Moreover, the modulation stability of the equation under consideration is also given.
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We investigate the transient dynamics of quantum coherence for a system of two central spins in a spin-star environment by employing a numerical procedure based on a Laguerre polynomial expansion scheme. The dynamics of the total, local, and global coherence are calculated for different values of the anisotropy parameter, the system-bath interaction strengths, and temperature for different initial bipartite states. Significant dynamical features of quantum coherence are found as follows: (i) an X state can only have global coherence; (ii) a state with only initial local coherence gains global coherence during the course of evolution by the induced correlations between the two-qubit system and the common bath; (iii) an incoherent state gains coherence by interacting with an external bath. We find there are two primary ways to gain coherence for an incoherent state: one is by interacting with the external quantum bath and the other is through interconversion of other quantum properties such as purity into coherence. Finally, we demonstrate that our results for the system in an infinite bath also hold qualitatively when the system is in contact with a finite bath.
Estrogen-related receptor gamma (ERRγ), the latest member of the ERR family, does not have any known reported natural ligands. Although the crystal structures of the apo, agonist-bound, and inverse agonist-bound ligand-binding domain (LBD) of ERRγ have been solved previously, their dynamic behavior has not been studied. Hence, to explore the intrinsic dynamics of the apo and ligand-bound forms of ERRγ, we applied long-range molecular dynamics (MD) simulations to the crystal structures of the apo and ligand-bound forms of the LBD of ERRγ. Using the MD trajectories, we performed hydrogen bond and binding free energy analysis, which suggested that the agonist displayed more hydrogen bonds with ERRγ than the inverse agonist 4-OHT. However, the binding energy of 4-OHT was higher than that of the agonist GSK4716, indicating that hydrophobic interactions are crucial for the binding of the inverse agonist. From principal component analysis, we observed that the AF-2 helix conformation at the C-terminal domain was similar to the initial structures during simulations, indicating that the AF-2 helix conformation is crucial with respect to the agonist or inverse agonist for further functional activity of ERRγ. In addition, we performed residue network analysis to understand intramolecular signal transduction within the protein. The betweenness centrality suggested that few of the amino acids are important for residue signal transduction in apo and ligand-bound forms. The results from this study may assist in designing better therapeutic compounds against ERRγ associated diseases.
Copyright: 2023 Sasidharan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The estrogen-related receptor (ERR) subfamily consists of three orphan NRs, ERRα (NR3B1), ERRβ (NR3B2), and ERRγ (NR3B23), which are closely related to the estrogen receptors (ER) [2]. The regions of the DNA-binding domains of both classic ERs and orphan ERRs are conserved and therefore recognize common DNA-binding sites or response elements that are proximal to the target genes [3]. ERRs are capable of controlling classic ER target genes in the breast and bones [4, 5]. Although a certain degree of sequence identity exists between the ERR and ER LBD, there is a significant difference in their ligand binding capacities. ERRα and ERRβ were studied extensively before ERRγ was identified; therefore, not much is known about the role and dynamics of ERRγ [2, 6, 7].
ERRγ was first identified when it was linked to a region critical for Usher syndrome type IIa. Later, the receptor was discovered to interact functionally with the NR co-activator glucocorticoid receptor-interacting protein (GRIP) [3, 8]. This protein receptor is primarily expressed in metabolic tissues such as muscle, liver, brain, heart, and adipose tissues. The complete role and function of the receptor have not yet been elucidated, as ERRγ-null mice were found to be non-viable after birth [9]. However, tissue-specific ERRγ knock-out mice, ERRγ-specific ligands that can modulate the transcriptional activity of the receptor, and studies involving gain/loss of function have allowed researchers to understand the functions of this unique receptor [10, 11]. Indeed, studies have shown that ERRγ plays a vital role in the metabolic functions of the liver, such as the regulation of glucose, alcohol, and lipids, along with iron metabolism and modulation of specific gene expression in endocrine and metabolic processes [12, 13]. In addition, it is now well known that abnormal regulation of ERRγ results in hepatocellular carcinoma, as it regulates the expression of microRNA and DNA methyltransferase [14, 15].
All computational works were performed on a Linux (Ubuntu) workstation. All-atom molecular dynamics (MD) simulations were performed using GROMACS v5.1.4 [33, 34] and the trajectories were analyzed using the in-built modules of the software. The residue network analysis was conducted using the NAPS web server [35, 36]. All graphical images were generated using PyMol [37]. Graphs were plotted using Microsoft Excel, and free-energy landscape (FEL) plots were generated using Mathematica.
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