Systematic identification of phosphorylation-mediated protein interaction switches.

Proteomics techniques can identify thousands of phosphorylation sites in a single experiment, the majority of which are new and lack precise information about function or molecular mechanism. Here we present a fast method to predict potential phosphorylation switches by mapping phosphorylation sites to protein-protein interactions of known structure and analysing the properties of the protein interface. We predict 1024 sites that could potentially enable or disable particular interactions. We tested a selection of these switches and showed that phosphomimetic mutations indeed affect interactions. We estimate that there are likely thousands of phosphorylation mediated switches yet to be uncovered, even among existing phosphorylation datasets. The results suggest that phosphorylation sites on globular, as distinct from disordered, parts of the proteome frequently function as switches, which might be one of the ancient roles for kinase phosphorylation.

Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.

Systematic interrogation of mutation or protein modification data is important to identify sites with functional consequences and to deduce global consequences from large data sets. Mechismo (mechismo.russellab.org) enables simultaneous consideration of thousands of 3D structures and biomolecular interactions to predict rapidly mechanistic consequences for mutations and modifications. As useful functional information often only comes from homologous proteins, we benchmarked the accuracy of predictions as a function of protein/structure sequence similarity, which permits the use of relatively weak sequence similarities with an appropriate confidence measure. For protein-protein, protein-nucleic acid and a subset of protein-chemical interactions, we also developed and benchmarked a measure of whether modifications are likely to enhance or diminish the interactions, which can assist the detection of modifications with specific effects. Analysis of high-throughput sequencing data shows that the approach can identify interesting differences between cancers, and application to proteomics data finds potential mechanistic insights for how post-translational modifications can alter biomolecular interactions.

ProtChemSI: a network of protein-chemical structural interactions.

Progress in structure determination methods means that the set of experimentally determined 3D structures of proteins in complex with small molecules is growing exponentially. ProtChemSI exploits and extends this useful set of structures by both collecting and annotating the existing data as well as providing models of potential complexes inferred by protein or chemical structure similarity. The database currently includes 7704 proteins from 1803 organisms, 11,324 chemical compounds and 202, 289 complexes including 178,974 predicted. It is publicly available at http://pcidb.russelllab.org.

Combinations of protein-chemical complex structures reveal new targets for established drugs.

Biological networks are powerful tools for predicting undocumented relationships between molecules. The underlying principle is that existing interactions between molecules can be used to predict new interactions. Here we use this principle to suggest new protein-chemical interactions via the network derived from three-dimensional structures. For pairs of proteins sharing a common ligand, we use protein and chemical superimpositions combined with fast structural compatibility screens to predict whether additional compounds bound by one protein would bind the other. The method reproduces 84% of complexes in a benchmark, and we make many predictions that would not be possible using conventional modeling techniques. Within 19,578 novel predicted interactions are 7,793 involving 718 drugs, including filaminast, coumarin, alitretonin and erlotinib. The growth rate of confident predictions is twice that of experimental complexes, meaning that a complete structural drug-protein repertoire will be available at least ten years earlier than by X-ray and NMR techniques alone.

Probing lipid- and drug-binding domains with fluorescent dyes.

A series of 2- and 3-OH Nile red dyes was prepared in order to generate water-soluble probes that could be used to probe lipid binding to proteins. Various substitutions in positions 2-/3-, 6-, and 7-shifted wavelengths while maintaining the environmental sensitivity of Nile red. In order to increase the solubility of the dyes in aqueous solutions, we attached butyric acid groups to the 2- or 3-OH position. In addition, phenothiazine dyes, which exhibited particularly long excitation properties, were synthesized and tested for the first time. All dyes showed Stoke's shifts of 70-100 nm and changes in excitation and emission of over 100 nm, depending on the hydrophobicity of the environment. Binding studies with bovine serum albumin and the non-specific lipid transfer protein SCP2 revealed emission changes of more than 30 nm upon binding to the protein and a five-fold increase in emission intensity. Titration of the dye-loaded proteins with various lipids or drugs replaced the dye and thereby reversed the shift in wavelength intensity. This allowed us to estimate the lipid binding affinity of the investigated proteins. For SCP2, isothermal calorimetry (ITC) data verified the titration experiments. NMR titration experiments of SCP2 with Nile red 2-O-butyric acid (1a) revealed that the dye is bound within the lipid binding pocket and competes with lipid ligands for this binding site. These results give valuable insight into lipid and drug transport by proteins outside and inside cells.

Probing phospholipase a(2) with fluorescent phospholipid substrates.

The Foerster resonance energy transfer-based sensor, PENN, measures intracellular phospholipase A(2) (PLA(2)) activity in living cells and small organisms. In an attempt to modify the probe for the detection of particular isoforms, we altered the sn-2 fatty acid in such a way that either one or three of the Z double bonds in arachidonic acid were present in the sensor molecule. Arachidonic-acid-mimicking fatty acids were prepared by copper-mediated coupling reactions. Probes with a single double bond in the 5-position exhibited favorable substrate properties for secretory PLA(2)s. In vitro experiments with the novel unsaturated doubly labeled phosphatidylethanolamine derivatives showed preferred cleavage of the sensor PENN2 (one double bond) by the physiologically important group V sPLA(2), while the O-methyl-derivative PMNN2 was accepted best by the isoform from hog pancreas. For experiments in living cells, we demonstrated that bioactivation via S-acetylthioethyl (SATE) groups is essential for probe performance. Surprisingly, membrane-permeant versions of the new sensors that contained double bonds, PENN2 and PENN3, were only cleaved to a minor extent in HeLa cells while the saturated form, PENN, was well accepted.