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Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set. [ABSTRACT FROM AUTHOR]

Nicotinamide Adenine Dinucleotide (NAD) levels are essential for cellular homeostasis and survival. Main sources of intracellular NAD are the salvage pathways from nicotinamide, where Nicotinamide phosphoribosyltransferases (NAMPTs) and Nicotinamidases (PNCs) have a key role. NAMPTs and PNCs are important in aging, infection and disease conditions such as diabetes and cancer. These enzymes have been considered redundant since either one or the other exists in each individual genome. The co-occurrence of NAMPT and PNC was only recently detected in invertebrates though no structural or functional characterization exists for them. Here, using expression and evolutionary analysis combined with homology modeling and protein-ligand docking, we show that both genes are expressed simultaneously in key species of major invertebrate branches and emphasize sequence and structural conservation patterns in metazoan NAMPT and PNC homologues. The results anticipate that NAMPTs and PNCs are simultaneously active, raising the possibility that NAD salvage pathways are not redundant as both are maintained to fulfill the requirement for NAD production in some species. [ABSTRACT FROM AUTHOR]

Protein–protein binding is one of the critical events in biology, and knowledge of proteic complexes three-dimensional structures is of fundamental importance for the biochemical study of pharmacologic compounds. In the past two decades there was an emergence of a large variety of algorithms designed to predict the structures of protein–protein complexes—a procedure named docking. Computational methods, if accurate and reliable, could play an important role, both to infer functional properties and to guide new experiments. Despite the outstanding progress of the methodologies developed in this area, a few problems still prevent protein–protein docking to be a widespread practice in the structural study of proteins. In this review we focus our attention on the principles that govern docking, namely the algorithms used for searching and scoring, which are usually referred as the docking problem. We also focus our attention on the use of a flexible description of the proteins under study and the use of biological information as the localization of the hot spots, the important residues for protein–protein binding. The most common docking softwares are described too. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [ABSTRACT FROM AUTHOR]