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.

Crystallographic studies of the extracytoplasmic function sigma factor sigma(J) from Mycobacterium tuberculosis

Mycobacterium tuberculosis has multiple sigma factors which enable the bacterium to reprogram its transcriptional machinery under diverse environmental conditions. sigma(J), an extracytoplasmic function sigma factor, is upregulated in late stationary phase cultures and during human macrophage infection. sigma(J) governs the cellular response to hydrogen peroxide-mediated oxidative stress. sigma(J) differs from other canonical sigma factors owing to the presence of a SnoaL_2 domain at the C-terminus. sigma(J) crystals belonged to the tetragonal space group I422, with unit-cell parameters a = b = 133.85, c = 75.08 angstrom. Diffraction data were collected to 2.16 angstrom resolution on the BM14 beamline at the European Synchrotron Radiation Facility (ESRF).

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Towards an exact factorization of the molecular wave function

An exact single-product factorisation of the molecular wave function for the timedependent Schrodinger equation is investigated by using an ansatz involving a phasefactor. By using the Frenkel variational method, we obtain the Schrodinger equations for the electronic and nuclear wave functions. The concept of a potential energy surface (PES) is retained by introducing a modified Hamiltonian as suggested earlier by Cederbaum. The parameter in the phase factor is chosen such that the equations of motion retain the physically appealing Born- Oppenheimer-like form, and is therefore unique.

The putative role of some conserved water molecules in the structure and function of human transthyretin

Human transthyretin (hTTR) is a multifunctional protein that is involved in several neurodegenerative diseases. Besides the transportation of thyroxin and vitamin A, it is also involved in the proteolysis of apolipoprotein A1 and A beta peptide. Extensive analyses of 32 high-resolution X-ray and neutron diffraction structures of hTTR followed by molecular-dynamics simulation studies using a set of 15 selected structures affirmed the presence of 44 conserved water molecules in its dimeric structure. They are found to play several important roles in the structure and function of the protein. Eight water molecules stabilize the dimeric structure through an extensive hydrogen-bonding network. The absence of some of these water molecules in highly acidic conditions (pH <= 4.0) severely affects the interfacial hydrogen-bond network, which may destabilize the native tetrameric structure, leading to its dissociation. Three pairs of conserved water molecules contribute to maintaining the geometry of the ligand-binding cavities. Some other water molecules control the orientation and dynamics of different structural elements of hTTR. This systematic study of the location, absence, networking and interactions of the conserved water molecules may shed some light on various structural and functional aspects of the protein. The present study may also provide some rational clues about the conserved water-mediated architecture and stability of hTTR.

Protein Structure and Function: Looking through the Network of Side-Chain Interactions

Network theory has become an excellent method of choice through which biological data are smoothly integrated to gain insights into complex biological problems. Understanding protein structure, folding, and function has been an important problem, which is being extensively investigated by the network approach. Since the sequence uniquely determines the structure, this review focuses on the networks of non-covalently connected amino acid side chains in proteins. Questions in structural biology are addressed within the framework of such a formalism. While general applications are mentioned in this review, challenging problems which have demanded the attention of scientific community for a long time, such as allostery and protein folding, are considered in greater detail. Our aim has been to explore these important problems through the eyes of networks. Various methods of constructing protein structure networks (PSN) are consolidated. They include the methods based on geometry, edges weighted by different schemes, and also bipartite network of protein-nucleic acid complexes. A number of network metrics that elegantly capture the general features as well as specific features related to phenomena, such as allostery and protein model validation, are described. Additionally, an integration of network theory with ensembles of equilibrium structures of a single protein or that of a large number of structures from the data bank has been presented to perceive complex phenomena from network perspective. Finally, we discuss briefly the capabilities, limitations, and the scope for further explorations of protein structure networks.

Dissecting pi-helices: sequence, structure and function

A new procedure for the identification of regular secondary structures using a C-alpha trace has identified 659 pi-helices in 3582 protein chains, solved at high resolution. Taking advantage of this significantly expanded database of pi-helices, we have analysed the functional and structural roles of helices and determined the position-wise amino acid propensity within and around them. These helices range from 5 to 18 residues in length with the average twist and rise being 85.2 +/- 7.2 and 1.28 +/- 0.31 angstrom, respectively. A total of 546 (similar to 83%) out of 659 pi-helices occur in conjunction with alpha-helices, with 101 pi-helices being interspersed between two alpha-helices. The majority of interspersed pi-helices were found to be conserved across a large number of structures within a protein family and produce a significant bend in the overall helical segment as well as local distortions in the neighbouring a-helices. The presence of a pi-helical fragment leads to appropriate orientation of the constituent residues, so as to facilitate favourable interactions and also help in proper folding of the protein chain. In addition to intra helical 6 -> 1 N H center dot center dot center dot O hydrogen bonds, pi-helices are also stabilized by several other non-bonded interactions. pi-Helices show distinct positional residue preferences, which are different from those of a-helices.

Status of the MSSM Higgs sector using global analysis and direct search bounds, and future prospects at the High Luminosity LHC

In this paper, we search for the regions of the phenomenological minimal supersymmetric standard model (pMSSM) parameter space where one can expect to have moderate Higgs mixing angle (alpha) with relatively light (up to 600 GeV) additional Higgses after satisfying the current LHC data. We perform a global fit analysis using most updated data (till December 2014) from the LHC and Tevatron experiments. The constraints coming from the precision measurements of the rare b-decays B-s -> mu(+)mu(-) and b -> s gamma are also considered. We find that low M-A(less than or similar to 350) and high tan beta(greater than or similar to 25) regions are disfavored by the combined effect of the global analysis and flavor data. However, regions with Higgs mixing angle alpha similar to 0.1-0.8 are still allowed by the current data. We then study the existing direct search bounds on the heavy scalar/pseudoscalar (H/A) and charged Higgs boson (H-+/-) masses and branchings at the LHC. It has been found that regions with low to moderate values of tan beta with light additional Higgses (mass <= 600 GeV) are unconstrained by the data, while the regions with tan beta > 20 are excluded considering the direct search bounds by the LHC-8 data. The possibility to probe the region with tan beta <= 20 at the high luminosity run of LHC are also discussed, giving special attention to the H -> hh, H/A -> t (t) over bar and H/A -> tau(+)tau(-) decay modes.

Mutations in the nucleotide binding and hydrolysis domains of Helicobacter pylori MutS2 lead to altered biochemical activities and inactivation of its in vivo function

Background: Helicobacter pylori MutS2 (HpMutS2), an inhibitor of recombination during transformation is a non-specific nuclease with two catalytic sites, both of which are essential for its anti-recombinase activity. Although HpMutS2 belongs to a highly conserved family of ABC transporter ATPases, the role of its ATP binding and hydrolysis activities remains elusive. Results: To explore the putative role of ATP binding and hydrolysis activities of HpMutS2 we specifically generated point mutations in the nucleotide-binding Walker-A (HpMutS2-G338R) and hydrolysis Walker-B (HpMutS2-E413A) domains of the protein. Compared to wild-type protein, HpMutS2-G338R exhibited similar to 2.5-fold lower affinity for both ATP and ADP while ATP hydrolysis was reduced by similar to 3-fold. Nucleotide binding efficiencies of HpMutS2-E413A were not significantly altered; however the ATP hydrolysis was reduced by similar to 10-fold. Although mutations in the Walker-A and Walker-B motifs of HpMutS2 only partially reduced its ability to bind and hydrolyze ATP, we demonstrate that these mutants not only exhibited alterations in the conformation, DNA binding and nuclease activities of the protein but failed to complement the hyper-recombinant phenotype displayed by mutS2-disrupted strain of H. pylori. In addition, we show that the nucleotide cofactor modulates the conformation, DNA binding and nuclease activities of HpMutS2. Conclusions: These data describe a strong crosstalk between the ATPase, DNA binding, and nuclease activities of HpMutS2. Furthermore these data show that both, ATP binding and hydrolysis activities of HpMutS2 are essential for the in vivo anti-recombinase function of the protein.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.