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The mitochondrial citrate-malate exchanger (CIC), a known target of acetylation, is up-regulated in activated immune cells and plays a key role in the production of inflammatory mediators. However, the role of acetylation in CIC activity is elusive. We show that CIC is acetylated in activated primary human macrophages and U937 cells and the level of acetylation is higher in glucose-deprived compared to normal glucose medium. Acetylation enhances CIC transport activity, leading to a higher citrate efflux from mitochondria in exchange with malate. Cytosolic citrate levels do not increase upon activation of cells grown in deprived compared to normal glucose media, indicating that citrate, transported from mitochondria at higher rates from acetylated CIC, is consumed at higher rates. Malate levels in the cytosol are lower in activated cells grown in glucose-deprived compared to normal glucose medium, indicating that this TCA intermediate is rapidly recycled back into the cytosol where it is used by the malic enzyme. Additionally, in activated cells CIC inhibition increases the NADP+/NADPH ratio in glucose-deprived cells; this ratio is unchanged in glucose-rich grown cells due to the activity of the pentose phosphate pathway. Consistently, the NADPH-producing isocitrate dehydrogenase level is higher in activated glucose-deprived as compared to glucose rich cells. These results demonstrate that, in the absence of glucose, activated macrophages increase CIC acetylation to enhance citrate efflux from mitochondria not only to produce inflammatory mediators but also to meet the NADPH demand through the actions of isocitrate dehydrogenase and malic enzyme., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The functional characterization of proteins represents a daily challenge for biochemical, medical and computational sciences. Although finally proved on the bench, the function of a protein can be successfully predicted by computational approaches that drive the further experimental assays. Current methods for comparative modeling allow the construction of accurate 3D models for proteins of unknown structure, provided that a crystal structure of a homologous protein is available. Binding regions can be proposed by using binding site predictors, data inferred from homologous crystal structures, and data provided from a careful interpretation of the multiple sequence alignment of the investigated protein and its homologs. Once the location of a binding site has been proposed, chemical ligands that have a high likelihood of binding can be identified by using ligand docking and structure-based virtual screening of chemical libraries. Most docking algorithms allow building a list sorted by energy of the lowest energy docking configuration for each ligand of the library. In this review the state-of-the-art of computational approaches in 3D protein comparative modeling and in the study of protein-ligand interactions is provided. Furthermore a possible combined/concerted multistep strategy for protein function prediction, based on multiple sequence alignment, comparative modeling, binding region prediction, and structure-based virtual screening of chemical libraries, is described by using suitable examples. As practical examples, Abl-kinase molecular modeling studies, HPV-E6 protein multiple sequence alignment analysis, and some other model docking-based characterization reports are briefly described to highlight the importance of computational approaches in protein function prediction., (Copyright © 2010 Elsevier B.V. All rights reserved.)