MOTIVATION: More than half of the human proteome contains the proline-rich motif, PxxP. This motif has a high propensity for adopting a left-handed polyproline II (PPII) helix and can potentially bind SH3 domains. SH3 domains are generally grouped into two classes, based on whether the PPII binds in a positive (N-to-C terminal) or negative (C-to-N terminal) orientation. Since the discovery of this structural motif, over six decades ago, a systematic understanding of its binding remains poor and the consensus amino acid sequence that binds SH3 domains is still ill defined. RESULTS: Here, we show that the PPII interaction with SH3 domains is governed by the helix backbone and its prolines, and their rotation angle around the PPII helical axis. Based on a geometric analysis of 131 experimentally solved SH3 domains in complex with PPIIs, we observed a rotary translation along the helical screw axis, and separated them by 120° into three categories we name α (0-120°), β (120-240°) and γ (240-360°). Furthermore, we found that PPII helices are distinguished by a shifting PxxP motif preceded by positively charged residues which act as a structural reading frame and dictates the organization of SH3 domains; however, there is no one single consensus motif for all classified PPIIs. Our results demonstrate a remarkable apparatus of a lock with a rotating and translating key with no known equivalent machinery in molecular biology. We anticipate our model to be a starting point for deciphering the PPII code, which can unlock an exponential growth in our understanding of the relationship between protein structure and function. AVAILABILITY AND IMPLEMENTATION: We have implemented the proposed methods in the R software environment and in an R package freely available at https://github.com/Grantlab/bio3d. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Polyproline II (PPII) is a common conformation, comparable to α-helix and β-sheet. PPII, recently termed with a more generic name-κ-helix, adopts a left-handed structure with 3-fold rotational symmetry. Lately, a new type of binding mechanism-the helical lock and key model was introduced in SH3-domain complexes, where the interaction is characterized by a sliding helical pattern. However, whether this binding mechanism is unique only to SH3 domains is unreported. RESULTS: Here, we show that the helical binding pattern is a universal feature of the κ-helix conformation, present within all the major target families-SH3, WW, profilin, MHC-II, EVH1 and GYF domains. Based on a geometric analysis of 255 experimentally solved structures, we found that they are characterized by a distinctive rotational angle along the helical axis. Furthermore, we found that the range of helical pitch varies between different protein domains or peptide orientations and that the interaction is also represented by a rotational displacement mimicking helical motion. The discovery of rotational interactions as a mechanism, reveals a new dimension in the realm of protein-protein interactions, which introduces a new layer of information encoded by the helical conformation. Due to the extensive involvement of the conformation in functional interactions, we anticipate our model to expand the current molecular understanding of the relationship between protein structure and function. AVAILABILITY AND IMPLEMENTATION: We have implemented the proposed methods in an R package freely available at https://github.com/Grantlab/bio3d. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Accurate prediction of active sites is an important tool in bioinformatics. Here we present an improved structure based technique to expose active sites that is based on large changes of solvent accessibility accompanying normal mode dynamics. The technique which detects EXPOsure of active SITes through normal modEs is named EXPOSITE. The technique is trained using a small 133 enzyme dataset and tested using a large 845 enzyme dataset, both with known active site residues. EXPOSITE is also tested in a benchmark protein ligand dataset (PLD) comprising 48 proteins with and without bound ligands. EXPOSITE is shown to successfully locate the active site in most instances, and is found to be more accurate than other structure-based techniques. Interestingly, in several instances, the active site does not correspond to the largest pocket. EXPOSITE is advantageous due to its high precision and paves the way for structure based prediction of active site in enzymes.

UNLABELLED: Finding related conformations in the Protein Data Bank is essential in many areas of bioscience. To assist this task, we designed a dihedral angle database for searching protein segment homologs. The search engine relies on encoding of the protein coordinates into text characters representing amino acid sequence, φ and ψ dihedral angles. The search engine is advantageous owing to its high speed and interactive nature and is expected to assist scientists in discovering conformation homologs and evolutionary kinship. The search engine is fast, with query times lasting a few seconds, and freely available at http://tarshish.md.biu.ac.il/∼samsona. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.