Abstract

Archaeal chromatin proteins share molecular and functional similarities with both bacterial and eukaryotic chromatin proteins. These proteins play an important role in functionally organizing the genomic DNA into a compact nucleoid. Cren7 and Sul7 are two crenarchaeal nucleoidassociated proteins, which are structurally homologous, but not conserved at the sequence level. Cocrystal structures have shown that these two proteins induce a sharp bend on binding to DNA. In this study, we have investigated the architectural properties of these proteins using atomic force microscopy, molecular dynamics simulations and magnetic tweezers. We demonstrate that Cren7 and Sul7 both compact DNA molecules to a similar extent. Using a theoretical model, we quantify the number of individual proteins bound to the DNA as a function of protein concentration and show that forces up to 3.5 pN do not affect this binding. Moreover, we investigate the flexibility of the bending angle induced by Cren7 and Sul7 and show that the protein–DNA complexes differ in flexibility from analogous bacterial and eukaryotic DNA-bending proteins.

Abstract

BACKGROUND: Thermostable lipases are widely used in the detergent industry and in organic synthesis. B. subtilis lipase (Lip A) is a monomeric protein, which preferentially hydrolyses C8 fatty acid esters. Though the mechanism of thermostability depends on type of lipase, some common factors include additional non-covalent interactions, increase in packing density of the hydrophobic core, stabilization of alpha-helices and shortening of loops between secondary structural elements. RESULTS: We have studied wild type Lip A (WT) and six of its thermostable mutants containing 2, 3, 4, 6, 9 and 12 point mutations respectively, derived from the wild type protein by directed evolution. Experimental observations showed that the most thermostable variant, with twelve mutations, shows remarkable enhancement in melting temperature and temperature optima of activity compared to WT, in vitro. Our MD simulations show decrease in SASA for core regions and slow unfolding rate at several key secondary structural regions due to presence of persistent salt bridges, hydrogen bonds and native contacts for the most thermostable mutant lipase. The principal component (PC) and Free energy landscape (FEL) analyses at 450K suggest that the most thermostable mutant showed least fluctuation and stayed within a single large minimum. The other less thermostable mutants and WT showed higher fluctuation and exhibited two or more minima along the first two PCs. Analysis of representative structures corresponding to each sub-states showed that the most thermostable mutant sampled conformations close to the native state most of the time during the simulation. The other less thermostable mutants and WT lipase sampled non-native conformations more frequently than native conformations. CONCLUSIONS: Our results demonstrate that, the most thermostable lipase maintains its stability and activity at high temperatures by restricting conformational fluctuation through the stabilization of key salt bridges and main-chain H-bonds, which further helped them to maintain the stability of the core regions apart from stabilizing the overall 3D fold.

Abstract

Schistosomiasis is a disease caused by a trematode parasite, Schistosoma mansoni. The host consists of two different redox systems: Glutaredoxin (Grx) and Thioredoxin (Trx), but the parasite has only one multifunctional enzyme Thioredoxin Glutathione Reductase (TGR), which is responsible for carrying out all the redox activities, necessary for protecting the parasite against oxidative stress inside the host. TGR is a fusion of Thioredoxin Reductase (TR) with Glutaredoxin (Grx) at its N-terminus. The dependence of S. mansoni on a single protein for all its redox functions makes it a potential drug target. We have carried out structural analysis of Glutathione Reductase (GR), Thioredoxin Reductase (TR) and Thioredoxin Glutathione Reductase (TGR) using available crystal structures from PDB to understand the catalytic mechanism in these oxidoreductases. NADPH plays a major role as an electron carrier and transfers the electrons to the oxidized cofactor, FAD, which is non-covalently attached to the enzyme. This initiates further steps of the catalytic process. Here, we investigate how the interplay of conformations of these cofactors and those of the neighbouring residues facilitate the charge transfer process. TR, GR and TGR share similarity in their respective active site regions. Several conserved residues and non covalent interactions, play a major role during the electron transfer process. We hypothesise the function of NADPH during the entire charge transfer process as follows: a Tyr residue moves and facilitates the binding of NADPH to FAD in pi-stacking conformation. Two Arg residues reorient to interact with 2'-phosphate group and adenine ring of NADPH for effective binding. Lys, Glu and His residues near the active site regions form salt bridges and possibly aid the charge transfer mechanism in these redox enzymes.

Abstract

Single stranded RNA molecules are known to fold into complex protein like functional structures, consisting of stems and loops, which are further stabilized through tertiary interactions. While it is remarkable that RNA molecules are able to exhibit such structural complexity and functional specificity, with only an alphabet of four bases, one of the strategies employed for creating variety is through post-transcriptional modifications such as methylation, pseudouridylation, thiolation and isomerization. In fact, modified bases are known to play major role in providing chemical and biological diversity to RNA and contribute to overall fitness of the cell1. Base modifications are also known to help RNA molecules to exhibit alternate conformations2. The objectives of this study are: To understand (1) how these modifications affect the base pairing properties of RNA bases and (2) why nature have adopted mechanism to modified these bases. These objectives are studied through quantum chemical methods. We extracted the coordinates of 32 modified base pairs and 11 base triplets from a total of 208 RNA crystal structures from the PDB database. Of these 208 files, 128 were directly taken from HD-RNAS’s non redundant dataset3 and searched for modified bases using BPFind software4. The remaining 77 PDB files were included in the dataset based on information from HET group information from PDBSum5. We have optimized the initial geometries at B3LYP/6-31G (d,p) level and have evaluated the complete basis set (CBS) extrapolated interaction energies using RIMP2 calculation with aug-cc-pVDZ and aug-cc-pVTZ basis sets. Molecular electrostatic surface potential maps were also generated for modified base pairs. This study provides insights into the characteristics of modified base pairs and triples in complex RNA structure.

Abstract

With major aerospace companies showing interest in certifying UAV systems for civilian airspace, their use in commercial remote sensing applications like traffic monitoring, map refinement, agricultural data collection, etc., are on the rise. But ambitious requirements like real-time geo-referencing of data, support for multiple sensor angle-of-views, smaller UAV size and cheaper investment cost have lead to challenges in platform stability, sensor noise reduction and increased onboard processing. Especially in small UAVs the geo-referencing of data collected is only as good as the quality of their localization sensors. This drives a need for developing methods that pickup spatial features from the captured video/image and aid in geo-referencing. This paper presents one such method to identify road segments and intersections based on traffic flow and compares well with the accuracy of manual observation. Two test video datasets, one each from moving and stationary platforms were used. The results obtained show a promising average percentage difference of 7.01% and 2.48% for the road segment extraction process using moving and stationary platform respectively. For the intersection identification process, the moving platform shows an accuracy of 75% where as the stationary platform data reaches an accuracy of 100%.

Abstract

Land use and land cover (LULC) changes induced by human or natural processes drive biogeochemistryof the Earth influencing the climate at global as well as regional scales. Drastic changes in the land cover with the decline in vegetation and water bodies due to anthropogenic activities enhances the heat emission from land surface and atmospheric temperatures Increased land surface temperature (LST) is mainly due to increase in concentrated human activities, paved land cover or barren lands. Due to complexity of landscapes the sampling was difficult to derive LST and environmental response relationships. Temporal data acquired through space borne remote sensors has bridged the gap of temporal data for the entire earth surface. The current study explores the relation between surface biophysical parameters to sub-pixel thermal variations. The thermal infrared bands of remote sensing data help to retrieve LST, which are supplemented byground based measurements. Analysis of LST with LULC indicates a negative correlation between vegetation indices and LST. The general trend in the ambient temperature of Uttara Kannada over the 31 year period was established. Itclarifies that there was a fundamental drift of temperature rise in recent years, especially during the last decade.

Abstract

Mangroves are high productive estuarine ecosystem, protect barrage and defend the impact of big storms. Numerous studies attempted to map the locations of mangroves and analyse changes using different sensors including optical sensors: LANDSAT, IRS, SPOT, and other from past four decades. The present work attempts to identify the mangroves at species level using high resolution remote sensing data with field based measurements. The lack of spatial quantitative mangroves maps for the west coast has led to overlooking of the importance of mangroves and also the implementation of restoration programmes. Mangroves planting in the small estuaries of the Uttara Kannada district of Karnataka State during the recent years have yielded desired results of better ecology and higher biological production. The RS data using 2010 IRS p6 L4 MX having resolution of 5 M is useful in mapping the distribution of adult mangroves. However for mapping juveniles and shrubby forms require higher spectral resolution data. Using open source GIS software (QGIS) and remote sensing software (GRASS) and IRS imageries mangrove areas and potential areas available for planting in three river estuaries in the Honnavar Forest Division of Uttara Kannada were mapped. Mangrove species are recommended for planting in suitable areas based on salinity regimes. The effective forest management in the region shows mangroves have expanded in several regions due to the conservation measures and supervision. The net gain in mangroves could be attributed to new plantations by the State Forest Department and effective protection; agriculture to mangroves; mudflat to mangroves. The overall accuracy of satellite imagery processing was 90.89% and the Kappa index was 0.89. The work demonstrates the potential of high resolution multi-temporal satellite remote sensing data with ground based measurements for effective mapping mangrove forests in coastal regions.

Abstract

his paper addresses the problem of reconstruction of specular surfaces using a combination of Dynamic Program­ming and Markov Random Fields formulation. Unlike traditional methods that require the exact position of environment points to be known, our method requires only the relative position of the environment points to be known for computing approximate normals and infer shape from them. We present an approach which estimates the depth from dynamic programming routine and MRF stereo matching and use MRF optimization to fuse the results to get the robust estimate of shape. We used smooth color gradient image as our environment texture so that shape can be recovered using just a single shot. We evaluate our method using synthetic experiments on 3D models like Stanford bunny and show the real experiment results on golden statue and silver coated statue.

Abstract

Sparse representations have emerged as a powerful approach for encoding images in a large class of machine recognition problems including face recognition. These methods rely on the use of an over-complete basis set for representing an image. This often assumes the availability of a large number of labeled training images, especially for high dimensional data. In many practical problems, the number of labeled training samples are very limited leading to significant degradations in classification performance. To address the problem of lack of training samples, we propose a semi-supervised algorithm that labels the unlabeled samples through a multi-stage label propagation combined with sparse representation. In this representation, each image is decomposed as a linear combination of its nearest basis images, which has the advantage of both locality and sparsity.Extensive experiments on publicly available face databases show that the results are significantly better compared to state-of-the-art face recognition methods in semi-supervised setting and are on par with fully supervised techniques

Abstract

Sparse representation based image restoration tech-niques have shown to be successful in solving various inverse problems such as denoising, in painting, and super-resolution,etc. on natural images and videos. In this paper, we explore the use of sparse representation based methods specifically to restore the degraded document images. While natural images form a very small subset of all possible images admitting the possibility of sparse representation, document images are significantly more restricted and are expected to be ideally suited for such a representation. However, the binary nature of textual document images makes dictionary learning and coding techniques unsuitable to be applied directly. We leverage the fact that different characters possess similar strokes, curves, and edges, and learn a dictionary that gives sparse decomposition for patches. Experimental results show significant improvement in image quality and OCR performance on documents collected from a variety of sources such as magazines and books. This method is therefore, ideally suited for restoring highly degraded images in repositories such as digital libraries.