Functional and genomic analyses of α-solenoid proteins

{alpha}-solenoids are flexible protein structural domains formed by ensembles of alpha-helical repeats (Armadillo and HEAT repeats among others). While homology can be used to detect many of these repeats, some {alpha}-solenoids have very little sequence homology to proteins of known structure and we expect that many remain undetected. We previously developed a method for detection of {alpha}-helical repeats based on a neural network trained on a dataset of protein structures. Here we improved the detection algorithm and updated the training dataset using recently solved structures of {alpha}-solenoids. Unexpectedly, we identified occurrences of {alpha}-solenoids in solved protein structures that escaped attention, for example within the core of the catalytic subunit of PI3KC. Our results expand the current set of known {alpha}-solenoids. Application of our tool to the protein universe allowed us to detect their significant enrichment in proteins interacting with many proteins, confirming that {alpha}-solenoids are generally involved in protein-protein interactions. We then studied the taxonomic distribution of {alpha}-solenoids to discuss an evolutionary scenario for the emergence of this type of domain, speculating that {alpha}-solenoids have emerged in multiple taxa in independent events by convergent evolution. We observe a higher rate of {alpha}-solenoids in eukaryotic genomes and in some prokaryotic families, such as Cyanobacteria and Planctomycetes, which could be associated to increased cellular complexity. The method is available at http://cbdm.mdc-berlin.de/~ard2/

Advances and Challenges in Computational Target Prediction

Target deconvolution is a vital initial step in preclinical drug development to determine research focus and strategy. In this respect, computational target prediction is used to identify the most probable targets of an orphan ligand or the most similar targets to a protein under investigation. Applications range from the fundamental analysis of the mode-of-action over polypharmacology or adverse effect predictions to drug repositioning. Here, we provide a review on published ligand- and target-based as well as hybrid approaches for computational target prediction, together with current limitations and future directions.Medicinal Chemistr

Examples of detected alpha-solenoid structures.

<p>Each repeat consists of two alpha-helices, depicted here in red and green. (A) HEAT repeats buried in the core of the PI3KC catalytic subunit p110alpha (cyan), in complex with p85alpha (orange) (PDB ID 3HHM <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Mandelker1" target="_blank">[22]</a>). (B) Alpha-solenoid binding RNA in exportin5 (PDB ID 3A6P <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Okada1" target="_blank">[23]</a>). (C) Lipid-binding protein. Isoprenoid lipid directly binding the HEAT repeats is colored in magenta, zinc atom in blue (PDB ID 3DRA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Hast1" target="_blank">[25]</a>). (D) TPR repeats protein, virulence regulator from <i>Bacillus thuringiensis</i> (PDB ID 2QFC <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Declerck1" target="_blank">[26]</a>). (E) Ankyrin repeats protein Q5ZSV0 from <i>Legionella pneumophila</i> (PDB ID 2AJA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Rose1" target="_blank">[57]</a>). (F) Irregular alpha-solenoid, glutamyl-tRNA synthetase from <i>Thermotoga maritima</i> (PDB ID 3AL0 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Takai1" target="_blank">[61]</a>).</p

Detection of alpha-solenoid proteins using a neural network.

<p>(A) A repeat is made of two helices (H1 and H2) separated by a linker sequence (L). Two detection windows of 19 amino acids are considered, one for each helix. During detection, different window shifts are tested by sliding the input windows H1 or H2 one residue apart from the middle-residue (red box), as indicated by the gaps between red and green boxes. (B) Precision-recall curves comparing the performance of ARD2 in identifying alpha-solenoids in our PDB set using different sets of parameters. A protein was identified as containing an alpha-solenoid if it had 3 or more hits above a given score threshold spaced between 30 and 135 amino acids of each other. This restricts the hits to an expected periodic range within 30 to 40 amino acids. The blue discontinuous and continuous curves show performance for ARD and ARD2 training sets, respectively, without using window shifts. Discontinuous and continuous red curves show performance for ARD and ARD2 training sets, respectively, for a window shift of 1. Different points across each curve correspond to score thresholds from 0.80 to 0.90, with a 0.01 step. The best recall for a 100% precision is obtained when using the window shift and a score threshold of 0.87 (precision: 1.00, recall: 0.28). The ARD2 training set produced generally better results than the ARD training set, and resulted in the best value of precision × recall for a threshold score of 0.86 (precision  = 0.93, recall  = 0.32). (C) Comparison of structures recalled from the positive set (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894.s001" target="_blank">Table S1</a>) by the Armadillo profile from InterPro and ARD2. Proteins detected outside of the positive set circle (Green) are consequently false positives (See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894.s002" target="_blank">Table S2</a> for a detailed list of the proteins detected).</p

Alignment of rotatin homologs.

<p>A multiple sequence alignment of human rotatin and homologs in other species was produced and represented using BiasViz <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079894#pone.0079894-Huska1" target="_blank">[62]</a>. Top lane: Jpred3 2D prediction for human rotatin (red: gaps, green: alpha-helix, blue: beta-strand). Bottom part: multiple sequence alignment (red: gaps, black to white: score of ARD2 prediction from 0 to 1). Most of the secondary structure prediction is alpha-helical. Clusters of periodic alpha-solenoid hits can be seen at the positions indicated by the blue bars. Other scattered hits are distributed through the entire alignment.</p

Proteins with alpha-solenoids establish more protein interactions than other proteins.

<p>Each box-plot indicates the distribution of interacting partners for proteins predicted to contain alpha-solenoids, long proteins not predicted to contain alpha-solenoids, and all proteins not predicted as containing alpha-solenoids. (A) Human proteins. (B) <i>Saccharomyces cerevisiae</i> proteins. Boxes represent the values between first and third quartile of the distributions. The horizontal line inside of the boxes indicates the median value. Circles indicate the outliers. All pairwise differences are significant (see text for details).</p

Functions of proteins with alpha-solenoids.

<p>Each protein is displayed with its PDB ID and the type of interaction its repeats are involved in. Though most of structures dock to proteins, we here point out the involvement of alpha-solenoids in protein-protein (P/P), protein-lipid (P/L) and protein-nucleic acid (P/N), either DNA or RNA. The diversity of function is broader than previously known.</p