Engineering faster transglycosidases and their acceptor specificity
Transglycosidases are enzymes that have the potential to catalyze the synthesis of a wide range of high-value compounds starting from biomass-derived feedstocks. Improving their activity and broadening the substrate range are important goals to enable the widespread application of this family of biocatalysts. In this work, we engineered 20 mutants of the rice transglycosidase Os9BGlu31 and evaluated their catalysis in 462 reactions over 18 different substrates. This allowed us to identify mutants that expanded their substrate range and showed high activity, including W243L and W243N. We also developed double mutants that show very high activity on certain substrates and exceptional specific…
A novel approach to determining physicochemical and absorption properties of 6-fluoroquinolone derivatives: experimental assessment
The ToSS MoDe approach is used to estimate the n-octanol/buffer partition coefficient, the apparent intestinal absorption rate constant and intestinal permeability from a 6-fluoroquinolone data set. Improved in silico methods for predicting a drug's ability to be transported across biological membranes and other biopharmaceutical properties is highly desirable to optimize new drug development. The physicochemical property (Log P) of 26 6-fluoroquinolone derivatives and the absorption properties (Log K(a) and Log P(eff)) of 21 derivatives were well described by the present approach. The models obtained confirm the important role of lipophilicity in the absorption process and its relation wit…
Unified Markov thermodynamics based on stochastic forms to classify drugs considering molecular structure, partition system, and biological species:
Abstract 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 (Gonzalez-Diaz, H. et al., J. Mol. Mod. 2002, 8, 237), 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 s…
Multi-output Model with Box-Jenkins Operators of Quadratic Indices for Prediction of Malaria and Cancer Inhibitors Targeting Ubiquitin- Proteasome Pathway (UPP) Proteins.
The ubiquitin-proteasome pathway (UPP) is the primary degradation system of short-lived regulatory proteins. Cellular processes such as the cell cycle, signal transduction, gene expression, DNA repair and apoptosis are regulated by this UPP and dysfunctions in this system have important implications in the development of cancer, neurodegenerative, cardiac and other human pathologies. UPP seems also to be very important in the function of eukaryote cells of the human parasites like Plasmodium falciparum, the causal agent of the neglected disease Malaria. Hence, the UPP could be considered as an attractive target for the development of compounds with Anti-Malarial or Anti-cancer properties. R…
Multi-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
Abstract Chemometrics, that based prediction on the probability of chemical distribution to different systems, is highly important for physicochemical, environmental, and life sciences. However, the amount of information is huge and difficult to analyze. A multi-system partition Complex Network (MSP-CN) may be very useful in this sense. We define MSP-CNs as large graphs composed by nodes (chemicals) interconnected by arcs if a pair of chemicals have similar partition in a given system. Experimental quantification of partition in many systems is expensive, so we can use a Quantitative Structure–Partition Relationship (QSPR) model. Unfortunately, with classic QSPR we need to use one model for…
USEDAT: USA-Europe Data Analysis Training Worldwide Program, 2019 ed.
USA-Europe Data Analysis Training School (USEDAT) is a Multi-center Trans-Atlantic initiative offering hands-on training focused in both Introduction to Experimental Data Recording (NMR, MS, IR, 2DGE, EEG, etc.) and/or posterior Computational Data Analysis (Machine Learning, Complex Networks, etc.). We made emphasis on applications in for Cheminformatics, Bioinformatics, Medicinal Chemistry, Nanotechnology, Systems Biology, Biomedical Engineering, etc. The school also promotes training and knowledge of ethical and legal regulatory issues (GDPR, REACH, OECD, FDA, etc.) about data use and data protection in chemistry and biomedical research. The school is directed to researchers and students …