Conformations and coherences in structure determination by ultrafast electron diffraction

In this article we consider consequences of spatial coherences and conformations in diffraction of (macro)molecules with different potential energy landscapes. The emphasis is on using this understanding to extract structural and temporal information from diffraction experiments. The theoretical analysis of structural interconversions spans an increased range of complexity, from small hydrocarbons to proteins. For each molecule considered, we construct the potential energy landscape and assess the characteristic conformational states available. For molecules that are quasiharmonic in the vicinity of energy minima, we find that the distinct conformer model is sufficient even at high temperatures. If, however, the energy surface is either locally flat around the minima or the molecule includes many degrees of conformational freedom, a Boltzmann ensemble must be used, in what we define as the pseudoconformer approach, to reproduce the diffraction. For macromolecules with numerous energy minima, the ensemble of hundreds of structures is considered, but we also utilize the concept of the persistence length to provide information on orientational coherence and its use to assess the degree of resonance contribution to diffraction. It is shown that the erosion of the resonant features in diffraction which are characteristic of some quasiperiodic structural motifs can be exploited in experimental studies of conformational interconversions triggered by a laser-induced temperature jump

Spectral rate theory for projected two-state kinetics

Classical rate theories often fail in cases where the observable(s) or order parameter(s) used are poor reaction coordinates or the observed signal is deteriorated by noise, such that no clear separation between reactants and products is possible. Here, we present a general spectral two-state rate theory for ergodic dynamical systems in thermal equilibrium that explicitly takes into account how the system is observed. The theory allows the systematic estimation errors made by standard rate theories to be understood and quantified. We also elucidate the connection of spectral rate theory with the popular Markov state modeling (MSM) approach for molecular simulation studies. An optimal rate estimator is formulated that gives robust and unbiased results even for poor reaction coordinates and can be applied to both computer simulations and single-molecule experiments. No definition of a dividing surface is required. Another result of the theory is a model-free definition of the reaction coordinate quality (RCQ). The RCQ can be bounded from below by the directly computable observation quality (OQ), thus providing a measure allowing the RCQ to be optimized by tuning the experimental setup. Additionally, the respective partial probability distributions can be obtained for the reactant and product states along the observed order parameter, even when these strongly overlap. The effects of both filtering (averaging) and uncorrelated noise are also examined. The approach is demonstrated on numerical examples and experimental single-molecule force probe data of the p5ab RNA hairpin and the apo-myoglobin protein at low pH, here focusing on the case of two-state kinetics

Rigorous treatment of electrostatics for spatially varying dielectrics based on energy minimization

A novel energy minimization formulation of electrostatics that allows computation of the electrostatic energy and forces to any desired accuracy in a system with arbitrary dielectric properties is presented. An integral equation for the scalar charge density is derived from an energy functional of the polarization vector field. This energy functional represents the true energy of the system even in non-equilibrium states. Arbitrary accuracy is achieved by solving the integral equation for the charge density via a series expansion in terms of the equation's kernel, which depends only on the geometry of the dielectrics. The streamlined formalism operates with volume charge distributions only, not resorting to introducing surface charges by hand. Therefore, it can be applied to any spatial variation of the dielectric susceptibility, which is of particular importance in applications to biomolecular systems. The simplicity of application of the formalism to real problems is shown with analytical and numerical examples.Comment: 27 pages, 5 figure

A connection between computer science and fuzzy theory: midpoints and running time of computing

Following the mathematical formalism introduced by M. Schellekens [Elec- tronic Notes in Theoret. Comput. Sci. 1 (1995), 211-232] in order to give a common foundation for Denotational Semantics and Complexity Analysis, we obtain an application of the theory of midpoints for asymmetric distances de ned between fuzzy sets to the complexity analysis of algorithms and pro- grams. In particular we show that the average running time for the algorithm known as Largetwo is exactly a midpoint between the best and the worst case running time of computingPeer Reviewe

cWINNOWER Algorithm for Finding Fuzzy DNA Motifs

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if multiple mutated copies of the motif (i.e., the signals) are present in the DNA sequence in sufficient abundance. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum number of detectable motifs qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc, by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12000 for (l,d) = (15,4)

FISim: A new similarity measure between transcription factor binding sites based on the fuzzy integral

Background Regulatory motifs describe sets of related transcription factor binding sites (TFBSs) and can be represented as position frequency matrices (PFMs). De novo identification of TFBSs is a crucial problem in computational biology which includes the issue of comparing putative motifs with one another and with motifs that are already known. The relative importance of each nucleotide within a given position in the PFMs should be considered in order to compute PFM similarities. Furthermore, biological data are inherently noisy and imprecise. Fuzzy set theory is particularly suitable for modeling imprecise data, whereas fuzzy integrals are highly appropriate for representing the interaction among different information sources.Results We propose FISim, a new similarity measure between PFMs, based on the fuzzy integral of the distance of the nucleotides with respect to the information content of the positions. Unlike existing methods, FISim is designed to consider the higher contribution of better conserved positions to the binding affinity. FISim provides excellent results when dealing with sets of randomly generated motifs, and outperforms the remaining methods when handling real datasets of related motifs. Furthermore, we propose a new cluster methodology based on kernel theory together with FISim to obtain groups of related motifs potentially bound by the same TFs, providing more robust results than existing approaches.Conclusion FISim corrects a design flaw of the most popular methods, whose measures favour similarity of low information content positions. We use our measure to successfully identify motifs that describe binding sites for the same TF and to solve real-life problems. In this study the reliability of fuzzy technology for motif comparison tasks is proven.This work has been carried out as part of projects P08-TIC-4299 of J. A., Sevilla and TIN2006-13177 of DGICT, Madrid

Generalized intuitionistic fuzzy laplace transform and its application in electrical circuit

In this paper we describe the generalized intuitionistic fuzzy laplace transform method for solving first order generalized intutionistic fuzzy differential equation. The procedure is applied in imprecise electrical circuit theory problem. Here the initial condition of those applications is taken as Generalized Intuitionistic triangular fuzzy numbers (GITFNs).Publisher's Versio