Combinatorial synthesis and biological evaluation of isoxazole-based libraries as antithrombotic agents

The 3-substitutedphenyl-5-isoxazolecarboxaldehydes have been identified as activated aldehydes for the generation of isoxazole-based combinatorial libraries on solid phase through automation. Three highly functionalized isoxazole-based libraries comprising of 32, 96 and 45 compounds each have been synthesized in parallel format using Baylis Hillman reaction, Michael addition, reductive amination and alkylation reactions. With an objective of lead generation all the three libraries were evaluated for their antithrombin activity in vivo.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

GRASP with Hybrid Path Relinking for Bi-Objective Winner Determination in Combinatorial Transportation Auctions

The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.

Combinatorial chromophore assembly inside a DNA four-way junction

In 1964 first proposed by Robin Holliday as a mechanistic model to solve the mystery of how genetic information is exchanged in yeast, the DNA four-way junction or Holliday junction (HJ) was proofed to be the key in- termediate in homologous recombination and became an important tool in the field of DNA origami, computation and nanomachines. Herein we use the assembly of four modified nucleic acid strands into the planar square conformation of this higher order DNA structure to demonstrate in a proof of principle manner the cumulative effect of pyrene moieties interacting inside the junction.[1][2]

An application of combinatorial optimization in the printing industry

Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The print- ing technology used yields a number of specific constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technologi- cal and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.