Abstract

Improving thermostability of industrial enzymes is an important protein engineering challenge. Point mutations, induced to increase thermostability, affect the structure and dynamics of the target protein in several ways and thus can also affect its activity. There appears to be no general rules for improving thermostabilty of enzymes, without adversely affecting their enzymatic activity. We report MD simulations, of wild type Bacillus subtilis lipase (WT) and its six progressively thermostable mutants (2M, 3M, 4M, 6M, 9M and 12M), performed at different temperatures, to address this issue. Less thermostable mutants (LTMs), 2M - 6M, show WT-like dynamics at all simulation temperatures. However, the two more thermostable mutants (MTMs), show required flexibility at appropriate temperature ranges and maintain conformational stability at high temperature. They show deep and rugged free-energy landscape, confining them within a near-native conformational space by conserving non-covalent interactions, and thus protecting them from possible aggregation. In contrast, the LTMs having marginally higher thermostabilities than WT show greater probabilities of accessing non-native conformations, which, due to aggregation, have reduced possibilities of reverting to their respective native states under refolding conditions. Our analysis indicates the possibility of non-additive effects of point mutations on the conformational stability of LTMs.

Abstract

Hydrogen bonded non-canonical base pairs have been identified as the key player behind the structural complexity and functional diversity of the RNA molecule. Enormous research have been performed to understand the correlation between different base pairing geometries and their contributions in the overall structural stabilities and functionalities. Towards this goal, calculation of intrinsic interaction energy of different base pairing geometries using ab-initio and DFT based Quantum Mechanical methods provide a significant insight in the context of RNA. Analysis of deviation in geometry and intrinsic interaction energy between the crystal and ground state optimized structures reveal the chemical behaviours of a particular base pair and the contextual effects on its stability. Fueled by the advancement of post Hartree-Fock QM theories and more accurate basis sets, the present knowledge base is flooded with a large amount of QM analysis data which lacks the systematic organization and hence fails to serve the scientific community in the best possible way. We, therefore, have attempted to build a relational database, “RNA Base Pair Count Geometry and Stability (RNABP COGEST)”, which relates the occurrence frequencies of different base pairs in RNA with their crystal and ground state optimized geometries (calculated at different levels of QM theory) and corresponding intrinsic interaction energies. To the best of our knowledge, this is the first attempt to organize energetics information for different RNA base pairs along with their occurrences and geometries. Our database provides an interactive interface which enables the user to extract data by constructing diverse geometry, frequency and energy based search queries for the purpose of better understanding of the complex relation between the geometry and stability of RNA base pairs. RNABP COGEST is a relational database developed in MYSQL with PHP and HTML based web interface. Availability of consolidated QM analysis data regarding interaction energies, structural parameters, and occurrences of all putative base pairing geometries at a glance, in RNABP COGEST, along with multiple comparative searching options will definitely be useful to bridge the gap in the understanding of complex RNA structures and their functionalities

Abstract

Protonated nucleobases have significant roles in facilitating catalytic functions of RNA, and in stabilizing different structural motifs. Reported pKa values of nucleobase protonation suggest that the population of neutral nucleobases is 103 – 104 times higher than that of protonated nucleobases under physiological conditions (pH  7.4). Therefore, a molecular level understanding of various putative roles of protonated nucleobases cannot be achieved without addressing the question of how their occurrence propensities and stabilities are related to the free energy costs associated with the process of protonation under physiological conditions. With water as proton donor, we use advanced QM methods to evaluate the site specific protonation propensities of nucleobases in terms of their associated free energy changes (
Gprot). Quantitative follow up on the energetics of base pair formation and database search for evaluating their occurrence frequencies, reveal a lack of correlation between base pair stability and occurrence propensities on the one hand, and ease of protonation on the other. For example, although N7 protonated Adenine (
Gprot = 40.0 kcal/mol) is found to participate in stable base pairing, base pairs involving N7 protonated Guanine (
Gprot = 36.8 kcal/mol), on geometry optimization, converge to a minima where Guanine transfers its extra proton to its partner base. Such observations, along with examples of weak base pairs involving N3 protonation of Cytosine (
Gprot = 37.0 kcal/mol) are rationalized by analysing the protonation induced charge redistributions which are found to significantly influence, both positively and negatively, the hydrogen bonding potentials of different functional sites of individual nucloebases. Protonation induced charge redistribution is also found to strongly influence (i) the aromatic character of the rings of the participating bases and (ii) hydrogen bonding potential of the free edges of the protonated base pair. Comprehensive analysis of a non-redundant RNA crystal structure dataset further reveals that, while availability of stabilization possibilities determine the feasibility of occurrence of protonated bases, their occurrence context and specific functional roles are important factors determining their occurrence propensities.

Abstract

Efficiency of 6-ethynylpyridone (E), a potential Thymine (T) analogue, which forms high-fidelity base pairs with Adenine (A) and gives rise to stabler DNA duplexes, with stability comparable to those containing canonical Cytosine(C):Guanine(G) base pairs, has been reported recently. Estimates of the interaction energies, involving geometry optimization at the DFT level (including middle range dispersion interactions) followed by single point energy calculation at MP2 level, in excellent correlation with the experimentally observed trends, show that E binds more strongly and more discriminatively with A, than T does. Detailed analysis reveals that the increase in base-base interaction arises out of conjugation of acetylenic  electrons with the ring  system of E, which results in not only an extra stabilizing C–H· · ·  interaction in the EA pair, it also leads to a strengthening of the conventional hydrogen bonds. However, the computed base-base interaction energy for the EA pair was found to be much less than that of the canonical CG pair implying that the difference in the TA versus EA base pairing interaction alone cannot explain the large experimentally observed increase in the thermostability of DNA duplexes, where a TA pair is replaced with an EA pair. Our computations show that the conjugation of acetylenic  electrons with the ring  system also possibly plays a role in increasing the stacking potential of the EA pair, which in turn, can explain its marked influence in the enhancement of duplex stability.

Abstract

RNA structural bioinformatics has developed, into a vibrant interdisciplinary area, in response to the emergence of noncoding RNA molecules as key regulatory players in nearly all important biological processes. Here we introduce the different conceptual tools and available resources, related to this new area. We also review its application in studying the role of RNA-protein interactions.

Abstract

The viral protein U (Vpu) encoded by HIV-1 has been shown to assist in the detachment of virion particles from infected cells. Vpu forms cation-specific ion channels in host cells, and has been proposed as a potential drug target. An understanding of the mechanism of ion transport through Vpu is desirable, but remains limited because of the unavailability of an experimental structure of the channel. Using a structure of the pentameric form of Vpu – modeled and validated based on available experimental data – umbrella sampling molecular dynamics simulations (cumulative simulation time of more than 0.4 µs) were employed to elucidate the energetics and the molecular mechanism of ion transport in Vpu. Free energy profiles corresponding to the permeation of Na+ and K+ were found to be similar to each other indicating lack of ion selection, consistent with previous experimental studies. The Ser23 residue is shown to enhance ion transport via two mechanisms: creating a weak binding site, and increasing the effective hydrophilic length of the channel, both of which have previously been hypothesized in experiments. A two-dimensional free energy landscape has been computed to model multiple ion permeation, based on which a mechanism for ion conduction is proposed. It is shown that only one ion can pass through the channel at a time. This, along with a stretch of hydrophobic residues in the transmembrane domain of Vpu, explains the slow kinetics of ion conduction. The results are consistent with previous conductance studies that showed Vpu to be a weakly conducting ion channel.

Abstract

In this paper we introduce a new histogram equalization based contrast enhancement method called High Speed Quantile Based Histogram Equalization (HSQHE) suitable for high contrast digital images. The proposed method is an effective tool to deal with the “mean-shift” problem, which is a usual problem with the histogram equalization based contrast enhancement methods. The main idea of HSQHE is to divide input image histogram into two or more sub-histograms, where segmentation is based on quantile values. Since the histogram segmentation is based on the quantile values, the entire spectrum of gray level will always play an important role in enhancement process. Also the proposed method does not require the recursive segmentation of the histogram as in many other methods, and hence proposed method requires less time for segmentation. The experimental results show that the performance of proposed HSQHE method is better as compared to other existing methods available in literature. Also this method preserves image brightness more accurately than the prevailing state of art and takes less time as compared to the other methods.

Abstract

This paper presents a novel visual servoing controller for a satellite mounted dual-arm space robot. The controller is designed to complete the task of servoing the robot's endeffectors to the desired pose, while regulating orientation of the base-satellite. Task redundancy approach is utilized to coordinate the servoing process and attitude of the base satellite. The visual task is defined as a primary task, while regulating attitude of the base satellite to zero is defined as a secondary task. The secondary task is formulated as an optimization problem in such a way that it does not affect the primary task, and simultaneously minimizes its cost function. A set of numerical experiments are carried out on a dual-arm space robot showing efficacy of the proposed control methodology.

Abstract

In this paper, we present a posture control scheme for step climbing by an in-house developed three-segmented tracked robot, miniUGV. The posture control scheme results in minimum torque at the actuated joints of the segments. Non-linear optimization is carried out offline for progressively decreasing distance of the robot from the step with torque minimization as objective function and force balance, motor torque limits, slippage avoidance and interference avoidance constraints. The resulting angles of the joints are fitted to a third degree polynomial as a function of the robot distance from the step and the step height. It is shown that a single set of polynomial functions is sufficient for climbing steps of all permissible heights and angles of attack of the front segment. The methodology has been verified through simulation followed by implementation on the real robot. As a consequence of this optimization we find that the average current reduced by more than thirty percent, reducing power consumption and confirming the efficacy of the optimization framework

Abstract

In the field of active perception, object search is a widely studied problem. To search for an object in large rooms, it would be expensive to explore and check each object's similarity with the object of interest. The expense could uncontrollably bloat as the number of objects to be searched increases. If the objects are of the order of a 2-5cm, they appear very small, making it difficult for the present algorithms to recognize them. A general human strategy in such cases is to sparsely identify, from far away (4-6m), if the object of interest is present in the scene. Subsequently, each of the possible objects is analysed from closer proximity to recognize, for further manipulation. In this work, we present a similar framework. We reduce search-space, by identifying existential probability of a small object from a distance followed by a closer 3-D analysis of its point cloud to accurately recognize it. This is achieved by 2-D modelling of the objects using Gaussian Mixture Models followed by recognizing objects using efficient RGB-Depth based algorithm.