Titration calorimetric studies to elucidate the specificity of the interactions of polymyxin B with lipopolysaccharides and lipid A

Lipopolysaccharide (LPS), the major cell wall constituent of Gram-negative bacteria, evokes a multitude of biological effects in mammals including pyrogenicity and toxic shock syndrome. Polymyxin B (PmB), a polycationic cyclic peptide, is known to neutralize most of its activities. The nature of the interaction of PmB with LPS and lipid A was investigated by isothermal titration calorimetry. PmB binds to LPS as well as lipid A stoichiometrically and non-co-operatively with micromolar affinity. These interactions are driven primarily by a favourable change in entropy (delta S) and are endothermic in nature. These positive changes in enthalpies decrease with increasing temperature, yielding a heat capacity change, delta Cp, of -2385 J.mol-1.degree-1 for PmB-LPS interactions while the binding of PmB to lipid A displays a delta Cp of -2259 J.mol-1.degree-1. The negative heat capacity changes provide strong evidence for the role of hydrophobic interactions as the driving force for the association of PmB with LPS and lipid A. A correlation of the energetics of these interactions with analyses of the molecular models of PmB suggests that a cluster of solvent-exposed non-polar amino acid side-chains that line one surface of the molecule, together with a ring of positively charged residues on its other surface, are responsible for its strong and stoichiometric binding to LPS.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

Co(II) and Cr(III) complexes of formate-formamide mixed ligands: synthesis, structures, single crystal-to-single crystal transformation and magnetic behaviour

Solvothermal treatment of an equimolar mixture of Co(NO3)(2)center dot 6H(2)O, HCONH2 and NaN3 in MeOH at 100 degrees C yielded a three-dimensional NaCl type network Co(HCOO)(2)(HCONH2)(2) center dot HCONH2 (1a) containing formamides in the pores of the structure. Solvated pink 1a undergoes single crystal-to-single crystal (SCSC) transformation at 215 degrees C to form the desolvated dark brown product Co(HCOO)(2)-( HCONH2)(2) (1b) with the retention of the original framework. Reversible single crystal-to-single crystal transformation of 1b (brown) to 1a (pink) in the presence of excess formamide was also established at room temperature. The coordination environment around Co(II) in both 1a and 1b is octahedral with a CoN2O4 coordination composition. A similar reaction replacing Co(II) by Cr(III) produced a heterometallic 3D extended network Na[Cr(HCOO)(4)(HCONH2)(2)]center dot 2H(2)O (2a) at 100 degrees C. An increase in reaction temperature to 150 degrees C produced a simple mononuclear complex Cr(HCOO)(3)(HCONH2)(3) center dot 3H(2)O (2b). Variable temperature magnetic studies revealed the presence of a canting phenomena in both 1a and 1b, and hysteresis loop in the field dependent magnetisation plot at 2 K whereas complex 2a is simply paramagnetic in nature.

Multivalent ligand presentation as a central concept to study intricate carbohydrate-protein interactions

Studying the weak binding affinities between carbohydrates and proteins has been a central theme in sustained efforts to uncover intricate details of this class of biomolecular interaction. The amphiphilic nature of most carbohydrates, the competing nature of the surrounding water molecules to a given protein receptor site and the receptor binding site characteristics led to the realization that carbohydrates are required to exert favorable interactions, primarily through clustering of the ligands. The clustering of sugar ligands has been augmented using many different innovative molecular scaffolds. The synthesis of clustered ligands also facilitates fine-tuning of the spatial and topological proximities between the ligands, so as to allow the identification of optimal molecular features for significant binding affinity enhancements. The kinetic and thermodynamic parameters have been delineated in many instances, thereby allowing an ability to correlate the multivalent presentation and the observed ligand-receptor interaction profiles. This critical review presents various multivalent ligands, synthetic and semisynthetic, and mechanisms by which the weak binding affinities are overcome, and the ligand-receptor complexation leads to significantly enhanced binding affinities (157 references).

A lower bound to the survival probability and an approximate first passage time distribution for Markovian and non-Markovian dynamics in phase space

We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

Lifting the singular nature of a model for peeling of an adhesive tape

We investigate the dynamics of peeling of an adhesive tape subjected to a constant pull speed. Due to the constraint between the pull force, peel angle and the peel force, the equations of motion derived earlier fall into the category of differential-algebraic equations (DAE) requiring an appropriate algorithm for its numerical solution. By including the kinetic energy arising from the stretched part of the tape in the Lagrangian, we derive equations of motion that support stick-slip jumps as a natural consequence of the inherent dynamics itself, thus circumventing the need to use any special algorithm. In the low mass limit, these equations reproduce solutions obtained using a differential-algebraic algorithm introduced for the earlier singular equations. We find that mass has a strong influence on the dynamics of the model rendering periodic solutions to chaotic and vice versa. Apart from the rich dynamics, the model reproduces several qualitative features of the different waveforms of the peel force function as also the decreasing nature of force drop magnitudes.