Discriminating the native structure from decoys using scoring functions based on the residue packing in globular proteins

<p>Abstract</p> <p>Background</p> <p>Setting the rules for the identification of a stable conformation of a protein is of utmost importance for the efficient generation of structures in computer simulation. For structure prediction, a considerable number of possible models are generated from which the best model has to be selected.</p> <p>Results</p> <p>Two scoring functions, R_sand R_p, based on the consideration of packing of residues, which indicate if the conformation of an amino acid sequence is native-like, are presented. These are defined using the solvent accessible surface area (ASA) and the partner number (PN) (other residues that are within 4.5 Å) of a particular residue. The two functions evaluate the deviation from the average packing properties (ASA or PN) of all residues in a polypeptide chain corresponding to a model of its three-dimensional structure. While simple in concept and computationally less intensive, both the functions are at least as efficient as any other energy functions in discriminating the native structure from decoys in a large number of standard decoy sets, as well as on models submitted for the targets of CASP7. R_sappears to be slightly more effective than R_p, as determined by the number of times the native structure possesses the minimum value for the function and its separation from the average value for the decoys.</p> <p>Conclusion</p> <p>Two parameters, R_sand R_p, are discussed that can very efficiently recognize the native fold for a sequence from an ensemble of decoy structures. Unlike many other algorithms that rely on the use of composite scoring function, these are based on a single parameter, viz., the accessible surface area (or the number of residues in contact), but still able to capture the essential attribute of the native fold.</p

Accessibility and partner number of protein residues, their relationship and a webserver, ContPlot for their display

<p>Abstract</p> <p>Background</p> <p>Depending on chemical features residues have preferred locations – interior or exterior – in protein structures, which also determine how many other residues are found around them. The close packing of residues is the hallmark of protein interior and protein-protein interaction sites.</p> <p>Results</p> <p>The average values of accessible surface area (ASA) and partner number (PN, the number of other residues within a distance of 4.5 Å from any atom of a given residue) of different residues have been determined and a webserver, ContPlot has been designed to display these values (relative to the average values) along the protein sequence. This would be useful to visually identify residues that are densely packed, or those involved in protein-protein interactions. The skewness observed in the distribution of PNs is indicative of the hydrophobic or hydrophilic nature of the residue. The variation of ASA with PN can be analytically expressed in terms of a cubic equation. These equations (one for each residue) can be used to estimate the ASA of a polypeptide chain using the PNs of the individual residues in the structure.</p> <p>Conclusion</p> <p>The atom-based PNs (obtained by counting surrounding atoms) are highly correlated to the residue-based PN, indicating that the latter can adequately capture the atomic details of packing. The average values of ASA and PN associated with each residue should be useful in protein structure prediction or fold-recognition algorithm. ContPlot would provide a handy tool to assess the importance of a residue in the protein structure or interaction site.</p

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Interresidue contacts in proteins and protein-protein interfaces and their use in characterizing the homodimeric interface

The environment of amino acid residues in protein tertiary structures and three types of interfaces formed by protein-protein association in complexes, homodimers, and crystal lattices of monomeric proteins has been analyzed in terms of the propensity values of the 20 amino acid residues to be in contact with a given residue. On the basis of the similarity of the environment, twenty residues can be divided into nine classes, which may correspond to a set of reduced amino acid alphabet. There is no appreciable change in the environment in going from the tertiary structure to the interface, those participating in the crystal contacts showing the maximum deviation. Contacts between identical residues are very prominent in homodimers and crystal dimers and arise due to 2-fold related association of residues lining the axis of rotation. These two types of interfaces, representing specific and nonspecific associations, are characterized by the types of residues that partake in "self-contacts' most notably Leu in the former and Glu in the latter. The relative preference of residues to be involved in "self-contacts' can be used to develop a scoring function to identify homodimeric proteins from crystal structures. Thirty-four percent of such residues are fully conserved among homologous proteins in the homodimer dataset, as opposed to only 20% in crystal dimers. Results point to Leu being the stickiest of all amino acid residues, hence its widespread use in motifs, such as leucine zippers

Molecular modeling of protein–protein interaction to decipher the structural mechanism of nonhost resistance in rice

<div><p>Nonhost resistance (NHR) is the most common and durable form of plant resistance to disease-causing organisms. A successful example of NHR is the cloning of a maize <i>R</i> gene <i>Rxo1</i> in rice and validating its function in conferring bacterial streak resistance in transgenic rice lines. In order to understand the structural mechanism of NHR in rice, we built the model of the protein–protein interaction between the encoded <i>Rxo1</i> (RXO1) and AvrRXO1 (avirulence protein of rice pathogen, <i>Xanthomonas oryzae</i> pv. <i>oryzicola</i>). Interestingly, although a RXO1 homolog in rice (RHR) is present, it does not interact with AvrRXO1 in nature. We have confirmed that the specificity of RXO1–AvrRXO1 interaction originates from the structured leucine rich repeat (LRR) domain of RXO1, facilitating the recognition process, while the absence of such ordered LRR region makes RHR unfavorable to recognize AvrRXO1. We postulate that the RXO1–AvrRXO1 complex formation is a three step process where electrostatic interactions, shape complementarity and short-range interactions play an important role. The presence of the structural and physicochemical properties essential for the protein–protein recognition process empowers RXO1 to mediate NHR, which the host protein RHR lacks and consequently loses its specificity to bind with AvrRXO1. To the best of our knowledge, this is the first report on the understanding of NHR in rice from the structural perspective of protein–protein interaction.</p></div

Dissecting subunit interfaces in homodimeric proteins

The subunit interfaces of 122 homodimers of known three-dimensional structure are analyzed and dissected into sets of surface patches by clustering atoms at the interface; 70 interfaces are single-patch, the others have up to six patches, often contributed by different structural domains. The average interface buries 1,940 &#197;2 of the surface of each monomer, contains one or two patches burying 600-1,600 &#197;2, is 65% nonpolar and includes 18 hydrogen bonds. However, the range of size and of hydrophobicity is wide among the 122 interfaces. Each interface has a core made of residues with atoms buried in the dimer, surrounded by a rim of residues with atoms that remain accessible to solvent. The core, which constitutes 77% of the interface on average, has an amino acid composition that resembles the protein interior except for the presence of arginine residues, whereas the rim is more like the protein surface. These properties of the interfaces in homodimers, which are permanent assemblies, are compared to those of protein-protein complexes where the components associate after they have independently folded. On average, subunit interfaces in homodimers are twice larger than in complexes, and much less polar due to the large fraction belonging to the core, although the amino acid compositions of the cores are similar in the two types of interfaces

Genome-wide identification of miRNAs and lncRNAs in Cajanus cajan

Abstract Background Non-coding RNAs (ncRNAs) are important players in the post transcriptional regulation of gene expression (PTGR). On one hand, microRNAs (miRNAs) are an abundant class of small ncRNAs (~22nt long) that negatively regulate gene expression at the levels of messenger RNAs stability and translation inhibition, on the other hand, long ncRNAs (lncRNAs) are a large and diverse class of transcribed non-protein coding RNA molecules (> 200nt) that play both up-regulatory as well as down-regulatory roles at the transcriptional level. Cajanus cajan, a leguminosae pulse crop grown in tropical and subtropical areas of the world, is a source of high value protein to vegetarians or very poor populations globally. Hence, genome-wide identification of miRNAs and lncRNAs in C. cajan is extremely important to understand their role in PTGR with a possible implication to generate improve variety of crops. Results We have identified 616 mature miRNAs in C. cajan belonging to 118 families, of which 578 are novel and not reported in MirBase21. A total of 1373 target sequences were identified for 180 miRNAs. Of these, 298 targets were characterized at the protein level. Besides, we have also predicted 3919 lncRNAs. Additionally, we have identified 87 of the predicted lncRNAs to be targeted by 66 miRNAs. Conclusions miRNA and lncRNAs in plants are known to control a variety of traits including yield, quality and stress tolerance. Owing to its agricultural importance and medicinal value, the identified miRNA, lncRNA and their targets in C. cajan may be useful for genome editing to improve better quality crop. A thorough understanding of ncRNA-based cellular regulatory networks will aid in the improvement of C. cajan agricultural traits