In this work we introduce a graph theoretical method to compare MEPs, which is independent of molecular alignment. It is based on the edit distance of weighted rooted trees, which encode the geometrical and topological information of Negative Molecular Isopotential Surfaces. A meaningful chemical classification of a set of 46 molecules with different functional groups was achieved. Structure--activity relationships for the corticosteroid binding affinity (CBG) of 31 steroids by means of hierarchical clustering resulted in a clear partitioning in high, intermediate, and low activity groups, whereas the results from quantitative structure--activity relationships, obtained from a partial least-squares analysis, showed comparable or better cross-validated correlation coefficients than the ones reported for previous methods based solely in the MEP.
Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).
In vitro rumen biohydrogenation kinetics of mixed linoleic and alfa-linolenic acids ¤ Cinética de biohidrogenación ruminal in vitro de los ácidos linoleico y alfa-linolénico mezclados Cinética de biohidrogenação ruminal in vitro dos ácidos linoleico e alfa-linolênico misturados
Drugs are devised to enter into the metabolism of an organism in order to produce a desired effect. From the chemical point of view, cellular metabolism is constituted by a complex network of reactions transforming metabolites one in each other. Knowledge on the structure of this network could help to develop novel methods for drug design, and to comprehend the root of known unexpected side effects. Many large-scale studies on the structure of metabolic networks have been developed following models based on different kinds of graphs as the fundamental image of the reaction network. Graphs models, however, comport wrong assumptions regarding the structure of reaction networks that may lead into wrong conclusions if they are not taken into account. In this article we critically review some graph-theoretical approaches to the analysis of centrality, vulnerability and modularity of metabolic networks, analyzing their limitations in estimating these key network properties, consider some proposals explicit or implicitly based on directed hypergraphs regarding their ability to overcome these issues, and review some recent implementation improvements that make the application of these models in increasingly large networks a viable option.
The receptor-ligand interactions involved in the formation of the complex between Class II Major Histocompatibility Complex molecules and antigenic peptides, which are essential for establishing an adaptive immunological response, were analyzed in the Class II Human Leukocyte Antigen (HLA) - Myelin Basic Protein (MBP) peptide complex (HLA-DRβ1*1501-MBP) using a multipolar molecular electrostatic potential approach. The Human Leukocyte Antigen - peptide complex system was divided into four pockets together with their respective peptide fragment and the corresponding occupying amino acid was replaced by each of the remaining 19 amino acids. Partial atomic charges were calculated by a quantum chemistry approach at the Hatree Fock/3-21*G level, to study the behavior of monopole, dipole and quadrupole electrostatic multipolar moments. Two types of electrostatic behavior were distinguished in the pockets' amino acids: “anchoring” located in Pocket 1 and 4, and “recognition” located in Pocket 4 and 7. According to variations in the electrostatic landscape, pockets were ordered as: Pocket 1>Pocket 9≫Pocket 4≈Pocket 7 which is in agreement with the binding ability reported for Class II Major Histocompatibility Complex pockets. In the same way, amino acids occupying the polymorphic positions β13R, β26F, β28D, β9W, β74A, β47F and β57D were shown to be key for this Receptor-Ligand interaction. The results show that the multipolar molecular electrostatic potential approach is appropriate for characterizing receptor-ligand interactions in the MHC–antigenic peptide complex, which could have potential implications for synthetic vaccine design.
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