Abstract

Protein domains are minimal structural units that can independently fold and carry out discrete biological functions. Evolutionary divergence amongst proteins not only cause considerable sequence changes of protein domains of similar folds and functions, but can also give rise to remarkable length variations. Rapid and heuristic sequence search algorithms are generally sensitive and effective in recognizing protein domains that are distantly related within large sequence databases, but are not well-suited to identify remote homologues of varying lengths. It is also challenging to distinguish reliable hits from a vast number of putative false positives that could have suboptimal sequence similarities. Here, we present a data-mining approach that provides stage-specific filters in sequence searches to reliably accumulate remote homologues which encourages sampling of length variations albeit no compensation on the validity of hitherto identified distant relationships. Realization of remote homologues with vivid length variations could contribute to better understanding of functional variety within protein domain superfamilies.

Abstract

The detailed molecular level understanding of physiochemical interactions responsible for the overall architecture and dynamics of functional RNA molecules embodies a major challenge to the scientific community. RNA 3D structure is currently analyzed in terms of strongly hydrogenbonded secondary structural elements interacting through primarily noncanonical tertiary base pairing interactions. Identification of recurring combinations of such elements as motifs, important in terms of architecture or as anchors for association, enhances our understanding of the RNA tertiary structures. Current approaches in motif mining are constrained by their dependence on identification of strongly hydrogen bonded base pairs. In our work, we have attempted a bottom-up approach towards identifying and characterizing structural features responsible for the complex architecture and dynamics of functional RNA molecules. At the lower end we have studied, noncovalent interactions such as inter-nucleotide hydrogen bonding interactions, water and ion mediated interactions; and at the higher end we have tried to capture the recurrent structural motifs made of several base-pairs and higher order. To study all the important weak and 'other than base base' interactions, within a non-redundant dataset of functional RNA molecules, we have developed a python based automated tool Inter-Nucleotide Contact Annotator in RNA (INCAR). INCAR efficiently manages space and time complexity to capture, categorize and suitably annotate all significant non-covalent interactions, such as hydrogen bonded and ion mediated interactions. Results are with high specificity, without compromising on sensitivity, with respect to currently available benchmarks like BPFIND and FR3D. Key features of our analysis include a) classification of bifurcated geometries, b) Identification of various structural elements such as platforms, bulges, loops, stems etc. c) significance of weak hydrogen bonds d) classification of higher order interactions such as triplets and quartets and e) use of a new automated centroid based approach which doesn't require a prior knowledge on standard base-pair geometries and atoms involving in hydrogen bonding is designed and implemented for detection of glycosidic bond orientation of various standard and non-standard base-pairing geometries (bifurcated, single hydrogen bonded, deformed). We have identified a new structurally important A-A Di-loop and an interesting tertiary interaction in a ribozyme. In addition, INCAR has been applied in several areas such as comparative analysis to investigate the structural conservancy of a class of sequence variants, investigation of motifs in terms of 'other than base-base' contacts and analysis of molecular dynamics simulation trajectories of RNA molecules.

Abstract

vin the wider biochemical context of their occurrence in functional RNA structures, using a combination of gas phase quantum chemical computations and structural (database) analysis methods. [1-10] Reported studies show that the geometries and intrinsic stabilities of noncanonical base pairs are largely determined by a rich variety of hydrogen bonding patterns, including bifurcated H-bonds, C-H mediated weak H-bonds, amino-acceptor interactions, and those involving interactions of the flexible sugar edge. There are however some special challenges in analyzing base pairs involving protonated nucleobases, which play important roles in mediating global macromolecular conformational changes and in facilitation of catalysis in a variety of functional RNA molecules. Firstly there is the challenge of detection and characterization of protonated base pairs in X-ray crystal structures, where proton coordinates are not available. This constitutes the prerequisite for investigating the context: the roles of protonated base pairs in RNA functions. To address this, we have used a modified version of BPFind to identify and characterize 18 distinct protonated base pair combinations from representative dataset of RNA crystal structure. The experimental base pair geometries were optimized at the B3LYP/cc-pVTZ level, and the interaction energies were calculated at the RIMP2/aug-cc-pVDZ level of theory. Based on our studies, we suggest resolution of structural ambiguities and correlate their geometric and energetic features with their structural and functional roles. In addition we also examine the suitability of specific base pairs as key elements in molecular switches and as nucleators for higher order structures such as base triplets and quartets.[11] However, we have only been able to partially address the other challenge i. e. to understand: “How nucleobases, which have pKa values for imino nitrogens around 4 or less, get protonated at physiological pH?” We will also discuss some of our ongoing efforts in this direction.

Abstract

Riboswitches are RNA elements, in the leader region of mRNAs, which control gene expression through metabolite binding. They consist of an aptamer domain which can communicate specific ligand binding event with the expression platform. With growing number of riboswitches being discovered, the molecular basis of discriminative ligand binding, and consequent conformational changes which facilitate the communication with the expression platform, is an important area of research. We have shown earlier, that quantum chemical studies of noncovalent interactions in riboswitches, with and without the bound ligand, can help us to supplement biophysical experiments in this regard. In this study, we have chosen, PreQ1 riboswitch, which exhibits the smallest known ligand – binding domain. It has efficient structural organization and high affinity interactions with guanine derived metabolites such as 7-cyano-7-deazaguanine (PreQ0) and 7-aminomethyl-7-deazaguanine (PreQ1). To understand systematically the physicochemical basis of ligand - aptamer interaction, gas phase quantum chemical studies on the models consisting ligand (PreQ1 and PreQ0) and conserved nucleotides of mRNA aptamer that stabilizes the ligand through hydrogen bonding and stacking interactions. The optimal geometries and interaction energies of models, evaluated at B3LYP/6-31G(d,p)//RIMP2/aug-cc-pVDZ level respectively. The models that include stacking interactions are studied using DFT-D with PBE functional. Contribution of pairwise interactions of individual nucleotides with ligand, towards the total binding energy of the ligand – aptamer complex is studied. Cooperative effect arising out of interactions of ligand and surrounding bases are also calculated. The results from above calculations highlight the crucial importance of in depth quantitative understanding of different types of noncovalent interactions in the context of molecular recognition and switching processes.

Abstract

Protonation and deprotonation of RNA bases, although energetically unfavorable, are known to play a key role in stabilization of the global structure of the RNA molecules and in regulating their functionalities. In this study an attempt has been made to look at the gas phase energies of the individual protonated and deprotonated bases, and the accompanying changes in their respective geometries and charge distribution. . Geometry optimization and energy calculations were carried out using QM methods at different levels of theory and approximations (B3LYP/6-31G++(2d,2p) and MP2/aug-ccpvdz). As expected, free energy calculations show that protonation/deprotonation at any possible site of a RNA base as a disfavored process characterized by a positive free energy change. It is however important to note that protonation at any exocyclic site or at ring imino nitrogen sites, and deprotonation from any site lead to planar and stable geometry of the corresponding conjugate acids and bases respectively. Protonation of secondary amino nitrogen atoms in the ring, such as N1of G or N3 of U, on the other hand, give significantly deformed structures where covalent bonds are also broken. Comparison of the geometrical parameters and Mulliken charge distribution in the neutral bases, with those of the corresponding charged species, showed interesting variations depending on the identity of the bases as well as on their respective protonation/deprotonation sites. It has been found that protonation at imino nitrogen atoms are not only energetically less costly, geometrical changes and charge redistribution that take place in the protonated species also help the protonated base to take part in non-covalent interactions like hydrogen bonding. Protonation at N7 position of Guanine is found to be most favorable among all possible protonation sites in any RNA base. Similar free energy calculation for nucleosides also showed the same trend and N7 protonation of Guanosine comes out to be the energetically least costly process. When we examined experimentally detected protonated base pairs involving N7 of guanine, and carried out geometry optimization for the two protonation possibilities, it was remarkable to note that it was the partner base-protonated configuration which turned out to be more stable. In fact, geometry optimization of the configuration, containing N7-protonated Guanine, resulted in the transfer of proton from N7 of Guanine to the nearest electronegative atom of the partner base. This may be because of enhanced hydrogen bonding in the alternate configuration. The next best possible protonation site among the nucleic acid bases is N3 of Cytosine, which also has many other biochemical roles. N7 protonation of Guanine, however, leads to variation of several theoretically calculated IR frequencies, some of which may destabilize the glycosidic bond. As the protonated bases are quite stable, they may play greater role in base pairing interactions in RNA.

Abstract

Unlike structures of double stranded DNA, stabilized by canonical base pairings, single stranded RNA molecules are known to fold into complex functional 3D structures. Several of these structures provide sites for binding with cognate molecules that induce conformational changes related to their respective functionalities. Their structures and functional dynamics are scripted by a multitude of noncovalent interactions, involving base edges, 2’-OH of ribose, backbone phosphates and metal cations. In the context of the importance of the ribosome as a potential drug target [1], we have studied the geometries and interaction energies associated with hydrogen bonded base pairs and pseudo pairs observed in crystal structures of drug molecules complexed with their target RNAs. Previous studies, as reviewed recently [2], provide insights into the structural aspects of these RNA-ligand interactions. However, the molecular level understanding of their role in RNA functions require the analysis of their stabilities and interaction energies. We have shown earlier how appropriate quantum chemical calculations can be used to assess gas phase interaction energies and intrinsic stabilities of nucleic acid base pairs [3 – 9]. Here we report results of our calculations, at B3LYP/6-31G(d,p) and RIMP2/aug-cc-pVDZ level, for geometry optimization and interaction energy calculation respectively, for base pairs and pseudobase pairs observed in experimental structures of distinct classes of drug molecules such as aminoglycosides, oxazolidinones, tetracyclines, lincosamides etc., bound to RNA. Our studies show that on full geometry optimization, these base pairs tend to achieve greater stability compared to that in their respective experimental geometries. The increase in interaction energies is not due to any increase in the number of hydrogen bonds but due to increase in their strengths because of increased planarity and by approaching in-range donor-acceptor distances of hydrogen bonds. Their gas phase interaction energies range from -11.32 to -29.70 kcal/mol and compare well with those of standard Watson Crick base pairs. Except for the Puromycin - Guanine pair involving sugar-sugar interaction, the Hartree Fock component dominates the interaction energies, in all fully optimised geometries, with values ranging from 53.09% to 87.13%. The EDFT-D energies ranging from -9.68 to -66.94 kcal/mol, suggest that the interaction between the RNA-Drug pairs is further stabilised due to dispersion. We also report detailed studies on the discriminative ability of the theophylline aptamer with respect to its cognate ligand. Unlike in the context of purine riboswitches observed earlier [6], cooperativity is found to be negligible in multiple base-ligand interactions studied in case of Theophylline interacting with its aptamer. However, the binding affinities of theophylline, caffeine and theobromine with the theophylline aptamer correlates well with the experimental data [10] with high binding affinity for theophylline and least for caffeine

Abstract

Riboswitches, typically an integral part of several mRNAs, consist of two domains – a ‘cognate metabolite’ sensing aptamer domain and an expression platform – regulating gene expression at the transcription or in the translation level. Because of their small size and high discriminative ability, p urine riboswitches have been studied extensively both experimentally as well as computationally. Crystal structures of ligand bound aptamer domain of purine riboswitches (Fig. 1) reveal a compact three-way junction architecture consisting of two stem-loops (P2-L2 and P3-L3), held together in parallel orientation by tertiary base pairing interactions between the loops (L2 and L3), converging to a base stem (P1) which communicates with the expression platform. Nucleotides belonging to the three junction loops (J1-2, J2-3 and J3-1) constitute the binding pocket which is lined above and below with double layers of stacked base triples. Though crystal structures of corresponding ligand-free aptamer domains are not available, biophysical and computational studies, including our earlier MD simulations of the add adenine riboswitch1, have provided insights into the functional dynamics connecting the two mechanistic events: discriminative ligand binding and communication with the expression Fig. 1 Ligand bound add platform. Adenine riboswitch In order to gain better insights into the ligand binding induced conformational changes, at the molecular level, and an understanding of the general principles underlying the switching event, we have carried out all-atom explicit solvent molecular dynamics simulations of add adenine riboswitch and xpt-pbuX guanine riboswitch, in ligand-free (APO) state and ligand-bound (HOLO) state, using ff99parmbsc0. Detailed analysis, including principal component analysis and conformational clustering, of the trajectories, reveal interesting insights into changes in conformational dynamics accompanying ligand binding. While confirming the existence of a preformed and ‘binding ready’ APO form and ligand binding induced stabilization of the expression platform linking P1 helices in both aptamers, our studies indicate possible role of stronger L2-L3 interactions in giving rise to fine differences in the functional dynamics of the guanine riboswitch, vis-a-vis the adenine riboswitch.

Abstract

Base pairs involving protonated nucleobases play important roles in mediating global macromolecular conformational changes and in facilitation of catalysis in a variety of functional RNA molecules. Here we present our attempts at understanding the role of such base pairs by detecting possible protonated base pairs in the available RNA crystal structures using BPFind software, in their specific structural contexts, and by the characterization of their geometries, interaction energies, and stabilities using advanced quantum chemical computations. We report occurrences of 18 distinct protonated base pair combinations from a representative data set of RNA crystal structures and propose a theoretical model for one putative base pair combination. Optimization of base pair geometries was carried out at the B3LYP/cc-pVTZ level, and the BSSE corrected interaction energies were calculated at theMP2/aug-ccpVDZ level of theory. The geometries for each of the base pairs were characterized in terms of Hbonding patterns observed, rmsd values observed on optimization, and base pair geometrical parameters. In addition, the intermolecular interaction in these complexes was also analyzed using Morokuma energy decomposition. The gas phase interaction energies of the base pairs range from-24 to-49 kcal/mol and reveal the dominance of Hartree-Fock component of interaction energy constituting 73% to 98%of the total interaction energy values.Onthe basis of our combined bioinformatics and quantum chemical analysis of different protonated base pairs, we suggest resolution of structural ambiguities and correlate their geometric and energetic features with their structural and functional roles. In addition, we also examine the suitability of specific base pairs as key elements in molecular switches and as nucleators for higher order structures such as base triplets and quartets.

Abstract

This paper proposes the Fourier-Bessel cepstral coefficients (FBCC) as features for robust text-independent speaker identification. Fourier-Bessel (FB) expansion is used instead of Fourier transform for representing the signal in frequency domain. FB expansion can be viewed as two-dimensional Fourier transform. Change in the kernel of the transform from exponential to decaying exponentials helps in viewing the speech signal as a linear sum of decaying exponentials. For signals arising out of acoustic tubes, where the signal is subjected to many damping effects, delays in the different components of the signal is inevitable. Representing such signals using FB coefficients helps in able identification of different components present in the signal. The random non-stationary nature of speech signal is more efficiently represented by damped sinusoidal nature of basis function that is more natural for the voiced speech signal since Bessel functions have damped sinusoidal as basis function, so it is more natural choice for the representation of natural signals. Vocal tract is modeled as a set of linear acoustic tubes being cylindrical in shape can be efficiently modeled using FB expansion because Bessel functions are solutions to cylindrical wave equations. The proposed approach to speaker identification is based on FBCC features, and method employ Gaussian mixture for modeling the speaker characteristics. However, we have build the speaker models from the Fourier-Bessel features derived from the speech samples, as an alternative to Mel-frequency cepstral coefficients (MFCC) and linear prediction cepstral coefficients (LPCC) for building the speaker models. An evaluation of the Gaussian mixture model is conducted on TIMIT database which consists of 630 speakers and 10 speech utterances per speaker and white noise signals of TIMIT database having various SNRs of 50, 40, 30 and 20 dB. Using the statistical model like Gaussian mixture model (GMM) and features extracted from the speech signals build a unique identity for each person who enrolled for speaker identification [1]. Estimation and Maximization algorithm is used for finding the maximum likelihood solution for a model with features, to test the later speeches against the database of all speakers who enrolled in the database. Experimental results shows that the FBCC can be used as the alternate feature for the LPCC and MFCC since it can improve the performance of the speaker identification task

Abstract

In this paper we describe the development of Mandi Information System, a Telugu spoken dialogue system for obtaining price information of agricultural commodities like vegetables, fruits, pulses, spices, etc.. The target users of MIS are primarily the farmers in rural and semiurban areas. Speech recognition is error prone and it is necessary for the dialogue system to make minimum number of errors while acquiring information from a user and also to detect errors (if not correctable) and adopt appropriate strategies. In this paper we suggest an approach to improve the performance and usability of the system by using multiple decoders and contextual information