Risk-sensitive control of continuous time Markov chains

We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterize the value function via Hamilton Jacobi Bellman equation and obtain an optimal Markov control. We do the same for infinite horizon discounted cost case. In the infinite horizon average cost case we establish the existence of an optimal stationary control under certain Lyapunov condition. We also develop a policy iteration algorithm for finding an optimal control.

De novo inference of protein function from coarse-grained dynamics

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 mu s coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. (C) 2014 Wiley Periodicals, Inc.

Beadex Function in the Motor Neurons Is Essential for Female Reproduction in Drosophila melanogaster

Drosophila melanogaster has served as an excellent model system for understanding the neuronal circuits and molecular mechanisms regulating complex behaviors. The Drosophila female reproductive circuits, in particular, are well studied and can be used as a tool to understand the role of novel genes in neuronal function in general and female reproduction in particular. In the present study, the role of Beadex, a transcription co-activator, in Drosophila female reproduction was assessed by generation of mutant and knock down studies. Null allele of Beadex was generated by transposase induced excision of P-element present within an intron of Beadex gene. The mutant showed highly compromised reproductive abilities as evaluated by reduced fecundity and fertility, abnormal oviposition and more importantly, the failure of sperm release from storage organs. However, no defect was found in the overall ovariole development. Tissue specific, targeted knock down of Beadex indicated that its function in neurons is important for efficient female reproduction, since its neuronal knock down led to compromised female reproductive abilities, similar to Beadex null females. Further, different neuronal class specific knock down studies revealed that Beadex function is required in motor neurons for normal fecundity and fertility of females. Thus, the present study attributes a novel and essential role for Beadex in female reproduction through neurons.

Identifying functionally important cis-peptide containing segments in proteins and their utility in molecular function annotation

Cis-peptide embedded segments are rare in proteins but often highlight their important role in molecular function when they do occur. The high evolutionary conservation of these segments illustrates this observation almost universally, although no attempt has been made to systematically use this information for the purpose of function annotation. In the present study, we demonstrate how geometric clustering and level-specific Gene Ontology molecular-function terms (also known as annotations) can be used in a statistically significant manner to identify cis-embedded segments in a protein linked to its molecular function. The present study identifies novel cis-peptide fragments, which are subsequently used for fragment-based function annotation. Annotation recall benchmarks interpreted using the receiver-operator characteristic plot returned an area-under-curve >0.9, corroborating the utility of the annotation method. In addition, we identified cis-peptide fragments occurring in conjunction with functionally important trans-peptide fragments, providing additional insights into molecular function. We further illustrate the applicability of our method in function annotation where homology-based annotation transfer is not possible. The findings of the present study add to the repertoire of function annotation approaches and also facilitate engineering, design and allied studies around the cis-peptide neighborhood of proteins.

Two-point correlation function of an exclusion process with hole-dependent rates

We consider an exclusion process on a ring in which a particle hops to an empty neighboring site with a rate that depends on the number of vacancies n in front of it. In the steady state, using the well-known mapping of this model to the zero-range process, we write down an exact formula for the partition function and the particle-particle correlation function in the canonical ensemble. In the thermodynamic limit, we find a simple analytical expression for the generating function of the correlation function. This result is applied to the hop rate u(n) = 1 + (b/n) for which a phase transition between high-density laminar phase and low-density jammed phase occurs for b > 2. For these rates, we find that at the critical density, the correlation function decays algebraically with a continuously varying exponent b - 2. We also calculate the two-point correlation function above the critical density and find that the correlation length diverges with a critical exponent nu = 1/(b - 2) for b < 3 and 1 for b > 3. These results are compared with those obtained using an exact series expansion for finite systems.

Enriching the annotation of Mycobacterium tuberculosis H37Rv proteome using remote homology detection approaches: Insights into structure and function

The availability of the genome sequence of Mycobacterium tuberculosis H37Rv has encouraged determination of large numbers of protein structures and detailed definition of the biological information encoded therein; yet, the functions of many proteins in M. tuberculosis remain unknown. The emergence of multidrug resistant strains makes it a priority to exploit recent advances in homology recognition and structure prediction to re-analyse its gene products. Here we report the structural and functional characterization of gene products encoded in the M. tuberculosis genome, with the help of sensitive profile-based remote homology search and fold recognition algorithms resulting in an enhanced annotation of the proteome where 95% of the M. tuberculosis proteins were identified wholly or partly with information on structure or function. New information includes association of 244 proteins with 205 domain families and a separate set of new association of folds to 64 proteins. Extending structural information across uncharacterized protein families represented in the M. tuberculosis proteome, by determining superfamily relationships between families of known and unknown structures, has contributed to an enhancement in the knowledge of structural content. In retrospect, such superfamily relationships have facilitated recognition of probable structure and/or function for several uncharacterized protein families, eventually aiding recognition of probable functions for homologous proteins corresponding to such families. Gene products unique to mycobacteria for which no functions could be identified are 183. Of these 18 were determined to be M. tuberculosis specific. Such pathogen-specific proteins are speculated to harbour virulence factors required for pathogenesis. A re-annotated proteome of M. tuberculosis, with greater completeness of annotated proteins and domain assigned regions, provides a valuable basis for experimental endeavours designed to obtain a better understanding of pathogenesis and to accelerate the process of drug target discovery. (C) 2014 Elsevier Ltd. All rights reserved.

Transverse single spin asymmetry in e plus p up arrow -> e plus J/psi plus X and Q(2) evolution of Sivers function-II

We present estimates of single spin asymmetry in the electroproduction of J/psi taking into account the transverse momentum-dependent (TMD) evolution of the gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS and eRHIC energies using the color evaporation model of J/psi. We have calculated the asymmetry using recent parameters extracted by Echevarria et al. using the Collins-Soper-Sterman approach to TMD evolution. These recent TMD evolution fits are based on the evolution kernel in which the perturbative part is resummed up to next-to-leading logarithmic accuracy. We have also estimated the asymmetry by using parameters which had been obtained by a fit by Anselmino et al., using both an exact numerical and an approximate analytical solution of the TMD evolution equations. We find that the variation among the different estimates obtained using TMD evolution is much smaller than between these on one hand and the estimates obtained using DGLAP evolution on the other. Even though the use of TMD evolution causes an overall reduction in asymmetries compared to the ones obtained without it, they remain sizable. Overall, upon use of TMD evolution, predictions for asymmetries stabilize.

Logarithmic corrections to twisted indices from the quantum entropy function

We compute logarithmic corrections to the twisted index B-6(g) in four-dimensional N = 4 and N = 8 string theories using the framework of the Quantum Entropy Function. We find that these vanish, matching perfectly with the large-charge expansion of the corresponding microscopic expressions.

Quick, Decentralized, Energy-Efficient One-Shot Max Function Computation Using Timer-Based Selection

In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.

B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy). A comparative study of the proposed technique with the state-of-art maximum likelihood (ML) and maximum-a-posteriori (MAP) with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED. (C) 2015 Author(s).

Gamma oscillations in the midbrain spatial attention network: linking circuits to function

Gamma-band (25-140 Hz) oscillations are ubiquitous in mammalian forebrain structures involved in sensory processing, attention, learning and memory. The optic tectum (01) is the central structure in a midbrain network that participates critically in controlling spatial attention. In this review, we summarize recent advances in characterizing a neural circuit in this midbrain network that generates large amplitude, space-specific, gamma oscillations in the avian OT, both in vivo and in vitro. We describe key physiological and pharmacological mechanisms that produce and regulate the structure of these oscillations. The extensive similarities between midbrain gamma oscillations in birds and those in the neocortex and hippocampus of mammals, offer important insights into the functional significance of a midbrain gamma oscillatory code.

Mode coupling theory analysis of electrolyte solutions: Time dependent diffusion, intermediate scattering function, and ion solvation dynamics

A self-consistent mode coupling theory (MCT) with microscopic inputs of equilibrium pair correlation functions is developed to analyze electrolyte dynamics. We apply the theory to calculate concentration dependence of (i) time dependent ion diffusion, (ii) intermediate scattering function of the constituent ions, and (iii) ion solvation dynamics in electrolyte solution. Brownian dynamics with implicit water molecules and molecular dynamics method with explicit water are used to check the theoretical predictions. The time dependence of ionic self-diffusion coefficient and the corresponding intermediate scattering function evaluated from our MCT approach show quantitative agreement with early experimental and present Brownian dynamic simulation results. With increasing concentration, the dispersion of electrolyte friction is found to occur at increasingly higher frequency, due to the faster relaxation of the ion atmosphere. The wave number dependence of intermediate scattering function, F(k, t), exhibits markedly different relaxation dynamics at different length scales. At small wave numbers, we find the emergence of a step-like relaxation, indicating the presence of both fast and slow time scales in the system. Such behavior allows an intriguing analogy with temperature dependent relaxation dynamics of supercooled liquids. We find that solvation dynamics of a tagged ion exhibits a power law decay at long times-the decay can also be fitted to a stretched exponential form. The emergence of the power law in solvation dynamics has been tested by carrying out long Brownian dynamics simulations with varying ionic concentrations. The solvation time correlation and ion-ion intermediate scattering function indeed exhibit highly interesting, non-trivial dynamical behavior at intermediate to longer times that require further experimental and theoretical studies. (c) 2015 AIP Publishing LLC.

The beta hairpin structure within ribosomal protein S5 mediates interplay between domains II and IV and regulates HCV IRES function

Translation initiation in Hepatitis C Virus (HCV) is mediated by Internal Ribosome Entry Site (IRES), which is independent of cap-structure and uses a limited number of canonical initiation factors. During translation initiation IRES-40S complex formation depends on high affinity interaction of IRES with ribosomal proteins. Earlier, it has been shown that ribosomal protein S5 (RPS5) interacts with HCV IRES. Here, we have extensively characterized the HCV IRES-RPS5 interaction and demonstrated its role in IRES function. Computational modelling and RNA-protein interaction studies demonstrated that the beta hairpin structure within RPS5 is critically required for the binding with domains II and IV. Mutations disrupting IRES-RPS5 interaction drastically reduced the 80S complex formation and the corresponding IRES activity. Computational analysis and UV cross-linking experiments using various IRES-mutants revealed interplay between domains II and IV mediated by RPS5. In addition, present study demonstrated that RPS5 interaction is unique to HCV IRES and is not involved in 40S-3 ` UTR interaction. Further, partial silencing of RPS5 resulted in preferential inhibition of HCV RNA translation. However, global translation was marginally affected by partial silencing of RPS5. Taken together, results provide novel molecular insights into IRES-RPS5 interaction and unravel its functional significance in mediating internal initiation of translation.

The nuclease activities of both the Smr domain and an additional LDLK motif are required for an efficient anti-recombination function of Helicobacter pyloriMutS2

Helicobacter pylori, a human pathogen, is a naturally and constitutively competent bacteria, displaying a high rate of intergenomic recombination. While recombination events are essential for evolution and adaptation of H.pylori to dynamic gastric niches and new hosts, such events should be regulated tightly to maintain genomic integrity. Here, we analyze the role of the nuclease activity of MutS2, a protein that limits recombination during transformation in H.pylori. In previously studied MutS2 proteins, the C-terminal Smr domain was mapped as the region responsible for its nuclease activity. We report here that deletion of Smr domain does not completely abolish the nuclease activity of HpMutS2. Using bioinformatics analysis and mutagenesis, we identified an additional and novel nuclease motif (LDLK) at the N-terminus of HpMutS2 unique to Helicobacter and related epsilon-proteobacterial species. A single point mutation (D30A) in the LDLK motif and the deletion of Smr domain resulted in approximate to 5-10-fold loss of DNA cleavage ability of HpMutS2. Interestingly, the mutant forms of HpMutS2 wherein the LDLK motif was mutated or the Smr domain was deleted were unable to complement the hyper-recombination phenotype of a mutS2(-) strain, suggesting that both nuclease sites are indispensable for an efficient anti-recombinase activity of HpMutS2.

De-DUFing the DUFs: Deciphering distant evolutionary relationships of Domains of Unknown Function using sensitive homology detection methods

Background: In the post-genomic era where sequences are being determined at a rapid rate, we are highly reliant on computational methods for their tentative biochemical characterization. The Pfam database currently contains 3,786 families corresponding to ``Domains of Unknown Function'' (DUF) or ``Uncharacterized Protein Family'' (UPF), of which 3,087 families have no reported three-dimensional structure, constituting almost one-fourth of the known protein families in search for both structure and function. Results: We applied a `computational structural genomics' approach using five state-of-the-art remote similarity detection methods to detect the relationship between uncharacterized DUFs and domain families of known structures. The association with a structural domain family could serve as a start point in elucidating the function of a DUF. Amongst these five methods, searches in SCOP-NrichD database have been applied for the first time. Predictions were classified into high, medium and low-confidence based on the consensus of results from various approaches and also annotated with enzyme and Gene ontology terms. 614 uncharacterized DUFs could be associated with a known structural domain, of which high confidence predictions, involving at least four methods, were made for 54 families. These structure-function relationships for the 614 DUF families can be accessed on-line at http://proline.biochem.iisc.ernet.in/RHD_DUFS/. For potential enzymes in this set, we assessed their compatibility with the associated fold and performed detailed structural and functional annotation by examining alignments and extent of conservation of functional residues. Detailed discussion is provided for interesting assignments for DUF3050, DUF1636, DUF1572, DUF2092 and DUF659. Conclusions: This study provides insights into the structure and potential function for nearly 20 % of the DUFs. Use of different computational approaches enables us to reliably recognize distant relationships, especially when they converge to a common assignment because the methods are often complementary. We observe that while pointers to the structural domain can offer the right clues to the function of a protein, recognition of its precise functional role is still `non-trivial' with many DUF domains conserving only some of the critical residues. It is not clear whether these are functional vestiges or instances involving alternate substrates and interacting partners. Reviewers: This article was reviewed by Drs Eugene Koonin, Frank Eisenhaber and Srikrishna Subramanian.