A dPIP5K dependent pool of phosphatidylinositol 4,5 bisphosphate (PIP2) is required for G-protein coupled signal transduction in Drosophila photoreceptors.

Multiple PIP2 dependent molecular processes including receptor activated phospholipase C activity occur at the neuronal plasma membranes, yet levels of this lipid at the plasma membrane are remarkably stable. Although the existence of unique pools of PIP2 supporting these events has been proposed, the mechanism by which they are generated is unclear. In Drosophila photoreceptors, the hydrolysis of PIP2 by G-protein coupled phospholipase C activity is essential for sensory transduction of photons. We identify dPIP5K as an enzyme essential for PIP2 re-synthesis in photoreceptors. Loss of dPIP5K causes profound defects in the electrical response to light and light-induced PIP2 dynamics at the photoreceptor membrane. Overexpression of dPIP5K was able to accelerate the rate of PIP2 synthesis following light induced PIP2 depletion. Other PIP2 dependent processes such as endocytosis and cytoskeletal function were unaffected in photoreceptors lacking dPIP5K function. These results provide evidence for the existence of a unique dPIP5K dependent pool of PIP2 required for normal Drosophila phototransduction. Our results define the existence of multiple pools of PIP2 in photoreceptors generated by distinct lipid kinases and supporting specific molecular processes at neuronal membranes.

Protein model discrimination using mutational sensitivity derived from deep sequencing.

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout.

Structural correlates of the temperature sensitive phenotype derived from saturation mutagenesis studies of CcdB.

Temperature sensitive (ts) mutants are widely used to reversibly modulate protein function in vivo and to understand functions of essential genes. Despite this, little is known about the protein structural features and mechanisms responsible for generating a ts phenotype. Also, such mutants are often difficult to isolate, limiting their use. In this study, a library consisting of 75% of all possible single-site mutants of the 101-residue, homodimeric Escherichia coli toxin CcdB was constructed. Mutants were characterized in terms of their activity at two different temperatures and at six different expression levels. Of the total of 1430 single-site mutants that were screened, 231 (16%) mutants showed a ts phenotype. The bulk of these consisted of 120 ts mutants found at all 22 buried sites and 34 ts mutants at all seven active site residues involved in binding DNA gyrase. Of the remaining ts mutants, 16 were found at residues in van der Waals contact with active site residues, 36 were at partially buried residues, and 30 resulted from introduction of Pro. Thus virtually all ts mutants could be rationalized in terms of the structure of the native protein and without knowledge of folding pathways. Data were analyzed to obtain insights into molecular features responsible for the ts phenotype and to outline structure- and sequence-based criteria for designing ts mutants of any globular protein. The criteria were validated by successful prediction of ts mutants of three other unrelated proteins, TBP, T4 lysozyme, and Gal4.

Stereochemical criteria for prediction of the effects of proline mutations on protein stability.

When incorporated into a polypeptide chain, proline (Pro) differs from all other naturally occurring amino acid residues in two important respects. The phi dihedral angle of Pro is constrained to values close to -65 degrees and Pro lacks an amide hydrogen. Consequently, mutations which result in introduction of Pro can significantly affect protein stability. In the present work, we describe a procedure to accurately predict the effect of Pro introduction on protein thermodynamic stability. Seventy-seven of the 97 non-Pro amino acid residues in the model protein, CcdB, were individually mutated to Pro, and the in vivo activity of each mutant was characterized. A decision tree to classify the mutation as perturbing or nonperturbing was created by correlating stereochemical properties of mutants to activity data. The stereochemical properties including main chain dihedral angle phi and main chain amide H-bonds (hydrogen bonds) were determined from 3D models of the mutant proteins built using MODELLER. We assessed the performance of the decision tree on a large dataset of 163 single-site Pro mutations of T4 lysozyme, 74 nsSNPs, and 52 other Pro substitutions from the literature. The overall accuracy of this algorithm was found to be 81% in the case of CcdB, 77% in the case of lysozyme, 76% in the case of nsSNPs, and 71% in the case of other Pro substitution data. The accuracy of Pro scanning mutagenesis for secondary structure assignment was also assessed and found to be at best 69%. Our prediction procedure will be useful in annotating uncharacterized nsSNPs of disease-associated proteins and for protein engineering and design.

Mutagenesis-based definitions and probes of residue burial in proteins.

Every residue of the 101-aa Escherichia coli toxin CcdB was substituted with Ala, Asp, Glu, Lys, and Arg by using site-directed mutagenesis. The activity of each mutant in vivo was characterized as a function of Controller of Cell Division or Death B protein (CcdB) transcriptional level. The mutation data suggest that an accessibility value of 5% is an appropriate cutoff for definition of buried residues. At all buried positions, introduction of Asp results in an inactive phenotype at all CcdB transcriptional levels. The average amount of destabilization upon substitution at buried positions decreases in the order Asp>Glu>Lys>Arg>Ala. Asp substitutions at buried sites in two other proteins, maltose-binding protein and thioredoxin, also were shown to be severely destabilizing. Ala and Asp scanning mutagenesis, in combination with dose-dependent expression phenotypes, was shown to yield important information on protein structure and activity. These results also suggest that such scanning mutagenesis data can be used to rank order sequence alignments and their corresponding homology models, as well as to distinguish between correct and incorrect structural alignments. With continuous reductions in oligonucleotide costs and increasingly efficient site-directed mutagenesis procedures, comprehensive scanning mutagenesis experiments for small proteins/domains are quite feasible.

Accurate detection of protein:ligand binding sites using molecular dynamics simulations.

Accurate prediction of location of cavities and surface grooves in proteins is important, as these are potential sites for ligand binding. Several currently available programs for cavity detection are unable to detect cavities near the surface or surface grooves. In the present study, an optimized molecular dynamics based procedure is described for detection and quantification of interior cavities as well as surface pockets. This is based on the observation that the mobility of water in such pockets is significantly lower than that of bulk water. The algorithm efficiently detects surface grooves that are sites of protein-ligand and protein-protein interaction. The algorithm was also used to substantially improve the performance of an automated docking procedure for docking monomers of nonobligate protein-protein complexes. In addition, it was applied to predict key residues involved in the binding of the E. coli toxin CcdB with its inhibitor. Predictions were subsequently validated by mutagenesis experiments.