Abstract

Diffuse Large B-cell Lymphoma (DLBCL) is a highly heterogeneous cancer of B cells. Apart from cell-of-origin, genetic variations have been observed to contribute towards heterogeneity leading to different pathogenic mechanisms and overall survival outcomes. Various classification schemes have been proposed that may aid in risk stratification and developing new therapeutics for those who fail frontline therapy. This mini review highlights the significance of genetic variations as biomarkers for DLBCL and ease in extending it to clinical setting.

Abstract

Diffuse large B-cell lymphoma (DLBCL) is the aggressive form of haematological malignancies with relapse/refractory in ~ 40% of cases. It mostly develops due to accumulation of various genetic and epigenetic variations that contribute to its aggressiveness. Though large-scale structural alterations have been reported in DLBCL, their functional role in pathogenesis and as potential targets for therapy is not yet well understood. In this study we performed detection and analysis of copy number variations (CNVs) in 11 human DLBCL cell lines (4 activated B-cell–like [ABC] and 7 germinal-centre B-cell–like [GCB]), that serve as model systems for DLBCL cancer cell biology. Significant heterogeneity observed in CNV profiles of these cell lines and poor prognosis associated with ABC subtype indicates the importance of individualized screening for diagnostic and prognostic targets. Functional analysis of key cancer genes exhibiting copy alterations across the cell lines revealed activation/disruption of ten potentially targetable immuno-oncogenic pathways. Genome guided in silico therapy that putatively target these pathways is elucidated. Based on our analysis, five CNV-genes associated with worst survival prognosis are proposed as potential prognostic markers of DLBCL.

Abstract

Modelling the Sommerfeld radiating boundary is a major challenge appearing in the study of many engineering problems involving elastic wave propagation [1]. Particularly, in the finite element analysis of Structure-Soil-Structure-Interaction (SSSI) problems, where the soil modelling has to be truncated at a finite distance. This truncation of the model at finite boundary leads to reflection of radiating elastic waves. The reflected waves from the boundary will affect the solution and may lead to instabilities in the numerical analysis. Therefore, it is necessary to provide an artificial boundary condition that will transmit the outward propagating waves with minimum or negligible reflections. To address the radiating boundary condition problem, researchers have developed various kinds of formulations over few decades, such as: a). Local Absorbing Boundary Conditions (ABC) [2], b). Absorbing Layers techniques which includes Perfectly Matched Layers [3-4], Caughey Absorbing Layer Method (CALM) [5], Absorbing Layers by Increasing Damping (ALID) [6] c). Boundary element method [7], and d). Infinite elements [8-10]. ABC corresponds to the situation where the boundary is supported on infinitesimal dash-pots oriented normal and tangential to the boundary. Though these boundary conditions are very simple, the major drawback is they are inefficient when the wave impinges the boundary in inclined direction. The key property of a PML that distinguishes it from an ordinary absorbing material is that it is designed such that the propagating waves incident upon the PML from a bulk medium do not reflect on the interface. The CALM consists of defining the absorbing layers at the boundaries of the elastic medium under consideration but requires many absorbing layers which requires much computational time. The objective of this study is to present a method for radiating boundary conditions by using modified ABC to take the effect of viscous damping combining with ALID

Abstract

Cobalt oxide particles have emerged as one of the promising metal oxide systems for their unique properties and various applications. This article reports syntheses of nano to micrometer sized morphology-controlled cobalt oxide particles by using the sol-gel synthesis method. The method can produce cobalt oxide particles in gram quantity. We explored the effects of various factors such the metal precursor, capping agent, solvent, calcination temperature, etc. on the size and morphology of the synthesized particles. FTIR and XRD studies confirmed the formation of crystalline Co3O4 particles. Field-emission scanning electron microscopy (FE-SEM) show that particles with sizes ranging from 180 nm to 6 μm and morphologies mainly smoothed surfaced octahedra formed depending on the metal precursor, capping agent, solvent and calcination temperature. The effects of three calcination temperatures have been explored based on the thermal behavior of the particles as studied by the thermogravimetric and differential thermal analysis (TGA/DTA). The powdered particles offer ~50 to ~75 m2 /g Brunner-Emmett-Teller (BET) surface area. The sol-gel technique is rapid, straightforward, and cost-effective and requires low processing temperatures to produce the particles compared to solvothermal methods. The present study shows that a proper choice of reaction conditions in a sol-gel method could be used to produce morphology-controlled cobalt oxide particles of nanometer to micrometer sizes in high yield

Abstract

In recent times, our healthcare system is being challenged by many drug-resistant microorganisms and ageing-associated diseases for which we do not have any drugs or drugs with poor therapeutic profile. With pharmaceutical technological advancements, increasing computational power and growth of related biomedical fields, there have been dramatic increase in the number of drugs approved in general, but still way behind in drug discovery for certain class of diseases. Now, we have access to bigger genomics database, better biophysical methods, and knowledge about chemical space with which we should be able to easily explore and predict synthetically feasible compounds for the lead optimization process. In this chapter, we discuss the limitations and highlights of currently available computational methods used for protein–ligand binding affinities estimation and this includes force-field, ab initio electronic structure theory and machine learning approaches. Since the electronic structure-based approach cannot be applied to systems of larger length scale, the free energy methods based on this employ certain approximations, and these have been discussed in detail in this chapter. Recently, the methods based on electronic structure theory and machine learning approaches also are successfully being used to compute protein–ligand binding affinities and other pharmacokinetic and pharmacodynamic properties and so have greater potential to take forward computer-aided drug discovery to newer heights

Abstract

Hydroxymethylbilane synthase (HMBS), the third enzyme in the heme biosynthesis pathway, catalyzes the formation of 1-hydroxymethylbilane (HMB) by a stepwise polymerization of four molecules of porphobilinogen (PBG) using the dipyrromethane (DPM) cofactor. The mechanism by which HMBS polymerizes four units of PBG has not been elucidated to date. In vitro and in silico studies on HMBS have suggested certain residues with catalytic importance, but their specific role in the catalysis is unclear. To understand the catalytic mechanism of HMBS, quantum mechanical (QM) calculations were performed on model systems obtained from the active site of the human HMBS enzyme. The addition of one molecule of PBG to the DPM cofactor is carried out in four steps: (1) protonation of the substrate, PBG; (2) deamination of PBG; (3) electrophilic addition of the deaminated substrate to the terminal pyrrole ring of the enzyme-bound DPM cofactor and (4) deprotonation of the carbon atom at the a-position of the second ring of DPM. Based on the energy profiles from the QM calculations on cluster models, R26 is proposed to be the best suitable proton donor to the PBG moiety, which aids in the deamination of the substrate. During the electrophilic addition step, the intermediate formed is stabilized by the carboxylate side chain of the D99 residue. In the final deprotonation step, an extra proton from the second ring of DPM is transferred to R26 via the carboxylate side chain of D99, thus completing one cycle of the catalytic mechanism. The residues in the cluster model seem to play an important role in obtaining accurate energy barriers. All the stationary points along the reaction pathway have been characterized using QM calculations. The rate limiting step for the complete mechanism is found to be the deamination of the PBG moiety. The results of this study provide a detailed understanding of the catalytic mechanism and would help design future studies aimed at modulating the activity of HMBS

Abstract

Motivated by the persistent anomalies in the semileptonic B-meson decays, we investigate the competency of LHC data to constrain the RDðÞ -favored parameter space in a charge −1=3 scalar leptoquark (S1) model. We consider some scenarios with one large free coupling to accommodate the RDðÞ anomalies. As a result, some of them dominantly yield nonresonant ττ and τν events at the LHC through the t-channel S1 exchange. So far, no experiment has searched for leptoquarks using these signatures and the relevant resonant leptoquark searches are yet to put any strong exclusion limit on the parameter space. We recast the latest ττ and τν resonance search data to obtain new exclusion limits. The nonresonant processes strongly interfere (destructively in our case) with the Standard Model background and play the determining role in setting the exclusion limits. To obtain precise limits, we include non-negligible effects coming from the subdominant (resonant) pair and inclusive single leptoquark productions systematically in our analysis. To deal with large destructive interference, we make use of the transverse mass distributions from the experiments in our statistical analysis. In addition, we also recast the relevant direct search results to obtain the most stringent collider bounds on these scenarios to date. These are independent bounds and are competitive to other known bounds. Finally, we indicate how one can adopt these bounds to a wide class of models with S1 that are proposed to accommodate the RDðÞ anomalies.

Abstract

The LHC search strategies for leptoquarks that couple dominantly to a top quark are different than for the ones that couple mostly to the light quarks. We consider charge 1=3 (ϕ1) and 5=3 (ϕ5) scalar leptoquarks that can decay to a top quark and a charged lepton (tl) giving rise to a resonance system of a boosted top and a high-pT lepton. We introduce simple phenomenological models suitable for bottom-up studies and explicitly map them to all possible scalar leptoquark models within the Buchmüller-Rückl-Wyler classifications that can have the desired decays. We study pair and single productions of these leptoquarks. Contrary to the common perception, we find that the single production of top-philic leptoquarks ϕ ¼ fϕ1; ϕ5g in association with a lepton and jets could be significant for order one ϕtl coupling in certain scenarios. We propose a strategy of selecting events with at least one hadronic-top and two high-pT same flavor opposite sign leptons. This captures events from both pair and single productions. Our strategy can significantly enhance the LHC discovery potential especially in the high-mass region where single productions become more prominent. Our estimation shows that a scalar leptoquark as heavy as ∼1.7 TeV can be discovered at the 14 TeV LHC with 3 ab−1 of integrated luminosity in the tll þ X channel for 100% branching ratio in the ϕ → tl decay mode. However, in some scenarios, the discovery reach can increase beyond 2 TeV even though the branching ratio comes down to about 50%

Abstract

Metal ions are crucial for folding and function of noncoding RNAs. The fact that RNAs have very specific metal ion binding motifs further implies that contribution of metal ions (like Mg2+) in RNA’s folding is not limited to simple compensation of electrostatic repulsions. Rather, their binding to RNA is driven by very specific contextual requirements. Elucidation of such factors is necessary for a comprehensive understanding of the sequence–structure–function paradigm in RNA. In this work, we have studied the consequences of Mg2+ binding on the geometry and stability of different noncanonical base pairs that shape up the complex structural landscape of RNA. Our results show that majority of the Mg2+ bound nucleobases are also part of a base pair. Interestingly, such base pairs belong only to a specific set of base pairing geometries. Out of them, we are able to identify 14 unique cases for which the native base pairing geometries are unstable under gas phase geometry optimization carried out in the absence of Mg2+ binding. Our density functional theory based calculations, performed using dispersion corrected M05-2X functional, suggest that, depending on its mode of binding, Mg2+ can stabilize and even fine tune a number of such base pairing geometries. These findings not only provide insights into how metal ions modulate the structure and dynamics of RNA molecules, they also provide a basis for improving the RNA structure prediction algorithms.

Abstract

Characterization of native, intermediate, and denatured states is crucial for understanding the factors influencing the stability of proteins. We have carried out molecular dynamics simulations to study the unfolding of three peripheral subunit binding domains (PSBDs): E. coli BBL, Bacillus stearothermophilus E3BD, and human hbSBD, at three different temperatures: 300, 330, and 400 K, and in the presence of two solvents: water and 5 M guanidinium hydrochloride (GndCl) solution. These proteins share similar folds, with two parallel helices, maintained via a hydrophobic core comprising residues from their interconnecting loop. BBL is more sensitive to thermal and chemical denaturation in comparison to hbSBD, and E3BD is the most stable of all of the three proteins. The effect of temperature on the stability of these proteins is more pronounced in “water-only” simulations compared to that in the presence of guanidium hydrochloride in high concentrations. Our results show cooperative unfolding transitions of these proteins, which are triggered by an initial melting of the C-terminal helix H2. The consequent loss of interhelical interactions or native contacts, as observed, leads to the subsequent melting of the N-terminal helix H1.