Ultrafast underdamped solvation: Agreement between computer simulation and various theories of solvation dynamics

A theoretical analysis of the three currently popular microscopic theories of solvation dynamics, namely, the dynamic mean spherical approximation (DMSA), the molecular hydrodynamic theory (MHT), and the memory function theory (MFT) is carried out. It is shown that in the underdamped limit of momentum relaxation, all three theories lead to nearly identical results when the translational motions of both the solute ion and the solvent molecules are neglected. In this limit, the theoretical prediction is in almost perfect agreement with the computer simulation results of solvation dynamics in the model Stockmayer liquid. However, the situation changes significantly in the presence of the translational motion of the solvent molecules. In this case, DMSA breaks down but the other two theories correctly predict the acceleration of solvation in agreement with the simulation results. We find that the translational motion of a light solute ion can play an important role in its own solvation. None of the existing theories describe this aspect. A generalization of the extended hydrodynamic theory is presented which, for the first time, includes the contribution of solute motion towards its own solvation dynamics. The extended theory gives excellent agreement with the simulations where solute motion is allowed. It is further shown that in the absence of translation, the memory function theory of Fried and Mukamel can be recovered from the hydrodynamic equations if the wave vector dependent dissipative kernel in the hydrodynamic description is replaced by its long wavelength value. We suggest a convenient memory kernel which is superior to the limiting forms used in earlier descriptions. We also present an alternate, quite general, statistical mechanical expression for the time dependent solvation energy of an ion. This expression has remarkable similarity with that for the translational dielectric friction on a moving ion.

Fatigue crack propagation model and size effect in concrete using dimensional analysis

It is well known that fatigue in concrete causes excessive deformations and cracking leading to structural failures. Due to quasi-brittle nature of concrete and formation of a fracture process zone, the rate of fatigue crack growth depends on a number of parameters, such as, the tensile strength, fracture toughness, loading ratio and most importantly the structural size. In this work, an analytical model is proposed for estimating the fatigue crack growth in concrete by using the concepts of dimensional analysis and including the above parameters. Knowing the governed and the governing parameters of the physical problem and by using the concepts of self-similarity, a relationship is obtained between different parameters involved. It is shown that the proposed fatigue law is able to capture the size effect in plain concrete and agrees well with different experimental results. Through a sensitivity analysis, it is shown that the structural size plays a dominant role followed by loading ratio and the initial crack length in fatigue crack propagation. (C) 2010 Elsevier Ltd. All rights reserved.

Using Correlated Parameters for Improved Ranking of Protein-Protein Docking Decoys

A successful protein-protein docking study culminates in identification of decoys at top ranks with near-native quaternary structures. However, this task remains enigmatic because no generalized scoring functions exist that effectively infer decoys according to the similarity to near-native quaternary structures. Difficulties arise because of the highly irregular nature of the protein surface and the significant variation of the nonbonding and solvation energies based on the chemical composition of the protein-protein interface. In this work, we describe a novel method combining an interface-size filter, a regression model for geometric compatibility (based on two correlated surface and packing parameters), and normalized interaction energy (calculated from correlated nonbonded and solvation energies), to effectively rank decoys from a set of 10,000 decoys. Tests on 30 unbound binary protein-protein complexes show that in 16 cases we can identify at least one decoy in top three ranks having <= 10 angstrom backbone root mean square deviation from true binding geometry. Comparisons with other state-of-art methods confirm the improved ranking power of our method without the use of any experiment-guided restraints, evolutionary information, statistical propensities, or modified interaction energy equations. Tests on 118 less-difficult bound binary protein-protein complexes with <= 35% sequence redundancy at the interface showed that in 77% cases, at least 1 in 10,000 decoys were identified with <= 5 angstrom backbone root mean square deviation from true geometry at first rank. The work will promote the use of new concepts where correlations among parameters provide more robust scoring models. It will facilitate studies involving molecular interactions, including modeling of large macromolecular assemblies and protein structure prediction. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 32: 787-796, 2011.

Studies on molecular evolution and structural features of double-headed inhibitors of ?-amylase and trypsin in plants

Plant seeds usually have high concentrations of proteinase and amylase inhibitors. These inhibitors exhibit a wide range of specificity, stability and oligomeric structure. In this communication, we report analysis of sequences that show statistically significant similarity to the double-headed alpha-amylase/trypsin inhibitor of ragi (Eleusine coracana). Our aim is to understand their evolutionary and structural features. The 14 sequences of this family that are available in the SWISSPROT database form three evolutionarily distinct branches. The branches relate to enzyme specificities and also probably to the oligomeric state of the proteins and not to the botanical class of the plant from which the enzymes are derived. This suggests that the enzyme specificities of the inhibitors evolved before the divergence of commercially cultivated cereals. The inhibitor sequences have three regions that display periodicity in hydrophobicity. It is likely that this feature reflects extended secondary structure in these segments. One of the most variable regions of the polypeptide corresponds to a loop, which is most probably exposed in the native structure of the inhibitors and is responsible for the inhibitory property.

The cDNA sequence of cytochrome b5 associated with cytokinin-induced haustoria formation in Cuscuta reflexa

A cDNA clone isolated by differentially screening a cytokinin-induced haustorial cDNA library of Cuscuta reflexa was sequenced and identified as the gene coding for cytochrome b(5), based on the similarity of the deduced amino-acid sequence with that of the cauliflower (60% identity) and tobacco (78% identity) proteins. The 5'-UTR is unusually long (720 bp) and contains 14 potential start codons (ATG) and 10 short ORFs.

Normal state tunneling conductance of perovskite oxides: Implications for high-Tc superconductors

We have investigated tunneling conductances in disordered, normally conducting perovskite oxides close to the metal�insulator transition. We show that the normal state tunneling conductance of perovskite oxides can be cast in a general form G(V) = G0[1 + curly logical orV/V*curly logical orn] with 1?n?0.5 and where V* is an intrinsic energy scale. The exponent n graduall y increases from 0.5 to 1 as the metal-insulator (M-I) transition is approached. In the high-Tc Bi(2212) cuprates, the normally observed, linear G(V)(n=1) can be made sub-linear (n<1) by substitution of Ca with Y. From the similarity of the linear conductances, we suggest proximity to the M-I transition as a likely cause for this G(V)logical or, bar below V dependence. In systems showing linear conductances (nreverse similar, equals1), we find that ?G/?Vreverse similar, equalsG?0 with ?reverse similar, equals 1 and the intrinsic energy scale V*reverse similar, equals25�75 meV in the different oxides investigated.

Identification of the active-site peptide of 2,3-dihydroxybenzoic acid decarboxylase from Aspergillus oryzae

The non-oxidative decarboxylation of aromatic acids is a poorly understood reaction. The transformation of 2,3-dihydroxybenzoic acid to catechol in the fungal metabolism of indole is a prototype of such a reaction. 2,3-Dihydroxybenzoic acid decarboxylase (EC 4.1.1.46) which catalyzes this reaction was purified to homogeneity from anthranilate induced cultures of Aspergillus oryzae using affinity chromatography. The enzyme did not require cofactors like NAD(+), PLP, TPP or metal ions for its activity. There was no spectral evidence for the presence of enzyme bound cofactors. The preparation, which was adjudged homogeneous by the criteria of SDS-PAGE, sedimentation analysis and N-terminal analysis, was characterized for its physicochemical and kinetic parameters. The enzyme was inactivated by group-specific modifiers like diethyl pyrocarbonate (DEPC) and N-ethylmaleimide (NEM). The kinetics of inactivation by DEPC suggested the presence of a single class of essential histidine residues, the second order rate constant of inactivation for which was 12.5 M(-1) min(-1). A single class of cysteine residues was modified by NEM with a second order rate constant of 33 M(-1) min(-1). Substrate analogues protected the enzyme against inactivation by both DEPC and NEM, suggesting the Location of the essential histidine and cysteine to be at the active site of the enzyme. The incorporation of radiolabelled NEM in a differential labelling experiment was 0.73 mol per mol subunit confirming the presence of a single essential cysteine per active-site. Differentially labelled enzyme was enzymatically cleaved and the peptide bearing the label was purified and sequenced. The active-site peptide LLGLAETCK and the N-terminal sequence MLGKIALEEAFALPRFEEKT did not bear any similarity to sequences reported in the Swiss-Prot Protein Sequence Databank, a reflection probably of the unique primary structure of this novel enzyme. The sequences reported in this study will appear in the Swiss-Prot Protein Sequence Databank under the accession number P80402.

Knowledge-based clustering

In the knowledge-based clustering approaches reported in the literature, explicit know ledge, typically in the form of a set of concepts, is used in computing similarity or conceptual cohesiveness between objects and in grouping them. We propose a knowledge-based clustering approach in which the domain knowledge is also used in the pattern representation phase of clustering. We argue that such a knowledge-based pattern representation scheme reduces the complexity of similarity computation and grouping phases. We present a knowledge-based clustering algorithm for grouping hooks in a library.

Dependence of giant magnetoresistance on oxygen stoichiometry and magnetization in polycrystalline La0.67Ba0.33MnOz

We have studied resistivity, magnetization, and magnetoresistance in polycrystalline La0.67Ba0.33MnOz by reducing the oxygen stoichiometry from z=2.99 to 2.80. As the oxygen content decreases, the resistivity of La0.67Ba0.33 MnOz increases and the magnetic transition temperature shifts to lower temperature. A large magnetoresistance effect was observed over a wide temperature range for all samples except the insulating z=2.80 sample. The similarity between our results on oxygen-deficient polycrystalline La0.67 Ba0.33MnOz and films previously reported to have a very large intrinsic magnetoresistance is discussed. At low temperature the magnetoresistance was observed to be strongly dependent on the magnetization. A possible mechanism for this effect is discussed.

Self-similar solutions of laser produced blast waves

The aerodynamics of the blast wave produced by laser ablation is studied using the piston analogy. The unsteady one-dimensional gasdynamic equations governing the flow an solved under assumption of self-similarity. The solutions are utilized to obtain analytical expressions for the velocity, density, pressure and temperature distributions. The results predict. all the experimentally observed features of the laser produced blast waves.