Could chroman-4-one derivative be a better inhibitor of PTR1? – Reason for the identified disparity in its inhibitory potency in Trypanosoma brucei and Leishmania major

Most notable Kinetoplastids are of the genus Trypanosoma and Leishmania, affecting several millions of humans in Africa and Latin America. Current therapeutic options are limited by several drawbacks, hence the need to develop more efficacious inhibitors. An investigation to decipher the mechanism behind greater inhibitory potency of a chroman-4-one derivative (compound 1) in Trypanosoma brucei pteridine reductase 1 (TbPTR1) and Leishmania major pteridine reductase 1 (LmPTR1) was performed. Estimation of ΔG_bind revealed that compound 1 had a greater binding affinity in TbPTR1 with a ΔG_bind value of −49.0507 Kcal/mol than −29.2292 Kcal/mol in LmPTR1. The ΔGbind in TbPTR1 were predominantly contributed by “strong” electrostatic energy compared to the “weak” van der Waals in LmPTR1. In addition to this, the NADPH cofactor contributed significantly to the total energy of TbPTR1. A characteristic weak aromatic π interaction common in PTR1 was more prominent in TbPTR1 than LmPTR1. The consistent occurrence of high-affinity conventional hydrogen bond interactions as well as a steady interaction of crucial active site residues like Arg14/Arg17, Ser95/Ser111, Phe97/Phe113 in TbPTR1/LmPTR1 with chroman-4-one moiety equally revealed the important role the moiety played in the activity of compound 1. Overall, the structural and conformational analysis of the active site residues in TbPTR1 revealed them to be more rigid than LmPTR1. This could be the mechanism of interaction TbPTR1 employs in exerting a greater potency than LmPTR1. These findings will further give insight that will be assistive in modifying compound 1 for better potency and the design of novel inhibitors of PTR1.     

An M/G/1 Retrial Queueing System with Two-Phase Service and Preemptive Resume

An M/G/1 retrial queueing system with additional phase of service and possible preemptive resume service discipline is considered. For an arbitrarily distributed retrial time distribution, the necessary and sufficient condition for the system stability is obtained, assuming that only the customer at the head of the orbit has priority access to the server. The steady-state distributions of the server state and the number of customers in the orbit are obtained along with other performance measures. The effects of various parameters on the system performance are analysed numerically. A general decomposition law for this retrial queueing system is established.     

A stochastic algorithm using one sample point per iteration and diminishing stepsizes

A stochastic algorithm for finding stationary points of real-valued functions defined on a Euclidean space is analyzed. It is based on the Robbins-Monro stochastic approximation procedure. Gradient evaluations are done by means of Monte Carlo simulations. At each iteratex _i , one sample point is drawn from an underlying probability space, based on which the gradient is approximated. The descent direction is against the approximation of the gradient, and the stepsize is 1/i. It is shown that, under broad conditions, w.p.1 if the sequence of iteratesx ₁,x ₂,...generated by the algorithm is bounded, then all of its accumulation points are stationary.     

On the optimal allocation of two active redundancies in a two-component series system

Components C₁ and C₂ form a series system. Suppose we can allocate the spare R₁ in parallel with C₁ and the spare R₂ in parallel with C₂, or otherwise, allocate R₁ with C₂ and R₂ with C₁. In this paper, we compare these two options using hazard rate ordering.     

Stochastic techniques for global optimization: A survey of recent advances

In this paper stochastic algorithms for global optimization are reviewed. After a brief introduction on random-search techniques, a more detailed analysis is carried out on the application of simulated annealing to continuous global optimization. The aim of such an analysis is mainly that of presenting recent papers on the subject, which have received only scarce attention in the most recent published surveys. Finally a very brief presentation of clustering techniques is given.     

A priori tests of a stochastic mode reduction strategy

Several a priori tests of a systematic stochastic mode reduction procedure recently devised by the authors [Proc. Natl. Acad. Sci. 96 (1999) 14687; Commun. Pure Appl. Math. 54 (2001) 891] are developed here. In this procedure, reduced stochastic equations for a smaller collections of resolved variables are derived systematically for complex nonlinear systems with many degrees of freedom and a large collection of unresolved variables. While the above approach is mathematically rigorous in the limit when the ratio of correlation times between the resolved and the unresolved variables is arbitrary small, it is shown here on a systematic hierarchy of models that this ratio can be surprisingly big. Typically, the systematic reduced stochastic modeling yields quantitatively realistic dynamics for ratios as large as 1/2. The examples studied here vary from instructive stochastic triad models to prototype complex systems with many degrees of freedom utilizing the truncated Burgers–Hopf equations as a nonlinear heat bath. Systematic quantitative tests for the stochastic modeling procedure are developed here which involve the stationary distribution and the two-time correlations for the second and fourth moments including the resolved variables and the energy in the resolved variables. In an important illustrative example presented here, the nonlinear original system involves 102 degrees of freedom and the reduced stochastic model predicted by the theory for two resolved variables involves both nonlinear interaction and multiplicative noises. Even for large value of the correlation time ratio of the order of 1/2, the reduced stochastic model with two degrees of freedom captures the essentially nonlinear and non-Gaussian statistics of the original nonlinear systems with 102 modes extremely well. Furthermore, it is shown here that the standard regression fitting of the second-order correlations alone fails to reproduce the nonlinear stochastic dynamics in this example.     

Stochastic signal analysis: Numerical representation and applications to system theory

Alternative procedures for representing a stochastic signal as a denumerable series with uncorrelated terms are developed. The study includes considerations about parametric rescaling and its repercussions on the orthogonal expansion, as well as numerical techniques for approaching such an expansion. In addition, applications to the Gaussian characterization of stochastic signals, filtering and stochastic modelling are treated.