Unified Markov thermodynamics based on stochastic forms to classify drugs considering molecular structure, partition system, and biological species:

To date, molecular descriptors do not commonly account for important information beyond chemical structure. The present work, attempts to extend, in this sense, the stochastic molecular descriptors, incorporating information about the specific biphasic partition system, the biological species, and chemical structure inside the molecular descriptors. Consequently, MARCH-INSIDE molecular descriptors may be identified with time-dependent thermodynamic parameters (entropy and mean free energy) of partition process. A classification function was developed to classify data of 423 drugs and up to 14 different partition systems at the same time. The model has shown a high overall accuracy of 92.1% (293 out of 318 cases) in training series and 90% (36 out of 40 cases) in predicting ones. Finally, we illustrate the use of the model by predicting a high probability (%) for G1 (a novel antibacterial drug) to undergo partition on different biotic systems (rat organs): liver (97.7), spleen (97.5), lung (97.4), and adipose tissue (97.6). These theoretical results coincide with herein reported steady state plasma concentrations (c) and partition coefficients (P) in liver (c=42.25+/-7.86/P=4.75), spleen (11.47+/-4.43/P=1.29), lung (17.04+/-3.58/P=1.91), and adipose tissue (28.19+/-11.82/P=3.17). All values were relative to (14)C-labeled-radioactive-G1 in plasma (c=8.9+/-3.05) after 3h of oral administration. In closing, the present stochastic forms derive average thermodynamic parameters fitting on a more clearly physicochemical framework with respect to classic vector-matrix-vector forms, which include, as particular cases, quadratic forms such as Wiener index, Randic invariants, Zagreb descriptors, Harary index, Balaban index, and Marrero-Ponce quadratic molecular indices.

Amylase partitioning and extractive bioconversion of starch using thermoseparating aqueous two-phase systems

The effectiveness of thermoseparating polymer-based aqueous two-phase systems (ATPS) in the enzymatic hydrolysis of starch was investigated. In this work, the phase diagrams of PEO-PPO-2500/ammonium sulfate and PEO-PPO-2500/magnesium sulfate systems were determined at 25 degrees C. The partition behavior of pure alpha-amylase and amyloglucosidase in four ATPS, namely, PEO-PPO/(NH(4))(2)SO(4), PEO-PPO/MgSO(4), polyethylene glycol (PEG)/(NH(4))(2)SO(4), and PEG/MgSO(4), was evaluated. The effects of phase-forming component concentrations on the enzyme activity and partitioning were assessed. Partitioning of a recombinant, thermostable alpha-amylase (MJA1) from the hyperthermophile, Methanococcus jannaschii was also investigated. All of the studied enzymes partitioned unevenly in these polymer/salt systems. The PEO-PPO-2500/MgSO(4) system was extremely attractive for starch hydrolysis. Polymer-based starch hydrolysis experiments containing PEO-PPO-2500/MgSO(4) indicated that the use of ATPS had a significant effect on soluble starch hydrolysis. Batch starch hydrolysis experiments with PEO-PPO/salt two-phase systems resulted in higher production of maltose or glucose and exhibited remarkably faster hydrolysis. A 22% gain in maltose yield was obtained as a result of the increased productivity. This work is the first reported application of thermoseparating polymer ATPS in the processing of starches. These results reveal the potential for thermoseparating polymer-enhanced extractive bioconversion of starch as a practical technology.