ω-Helices in Proteins

PSIQUE: Protein Secondary Structure Identification on the Basis of Quaternions and Electronic Structure Calculations

The secondary structure is important in protein structure analysis, classification, and modeling. We have developed a novel method for secondary structure assignment, termed PSIQUE, based on the potential energy surface (PES) of polyalanine obtained using an infinitely long chain model and density functional theory calculations. First, uniform protein segments are determined in terms of a difference of quaternions between neighboring amino acids along the protein backbone. Then, the identification of the secondary structure motifs is carried out based on the minima found in the PES. PSIQUE shows good agreement with other secondary structure assignment methods. However, it provides better discrimination of subtle secondary structures (e.g., helix types) and termini and produces more uniform segments while also accounting for local distortions. Overall, PSIQUE provides a precise and reliable assignment of secondary structures, so it should be helpful for the detailed characterization of the protein structure.

SCOT: Rethinking the classification of secondary structure elements

MOTIVATION

Secondary structure classification is one of the most important issues in structure-based analyses due to its impact on secondary structure prediction, structural alignment and protein visualization. There are still open challenges concerning helix and sheet assignments which are currently not addressed by a single multi-purpose software.

RESULTS

We introduce SCOT (Secondary structure Classification On Turns) as a novel secondary structure element assignment software which supports the assignment of turns, right-handed α-, 310- and π-helices, left-handed α- and 310-helices, 2.27- and polyproline II helices, β-sheets and kinks. We demonstrate that the introduction of helix Purity values enables a clear differentiation between helix classes. SCOT's unique strengths are highlighted by comparing it to six state-of-the-art methods (DSSP, STRIDE, ASSP, SEGNO, DISICL and SHAFT). The assignment approaches were compared concerning geometric consistency, protein structure quality and flexibility dependency and their impact on secondary structure element-based structural alignments. We show that only SCOT's combination of hydrogen bonds, geometric criteria and dihedral angles enables robust assignments independent of the structure quality and flexibility. We demonstrate that this combination and the elaborate kink detection lead to SCOT's clear superiority for protein alignments. As the resulting helices and strands are provided in a PDB conform output format, they can immediately be used for structure alignment algorithms. Taken together, the application of our new method and the straight-forward visualization using the accompanying PyMOL scripts enable the comprehensive analysis of regular backbone geometries in proteins.

AVAILABILITY AND IMPLEMENTATION

https://this-group.rocks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Polyproline II Helix as a Recognition Motif of Plant Peptide Hormones and Flagellin Peptide flg22

Background:

Plant peptide hormones play a crucial role in plant growth and development. A group of these peptide hormones are signaling peptides with 5 - 23 amino acids. Flagellin peptide (flg22) also elicits an immune response in plants. The functions are expressed through recognition of the peptide hormones and flg22. This recognition relies on membrane localized receptor kinases with extracellular leucine rich repeats (LRR-RKs). The structures of plant peptide hormones - AtPep1, IDA, IDL1, RGFs 1- 3, TDIF/CLE41 - and of flg22 complexed with LRR domains of corresponding LRRRKs and co-receptors SERKs have been determined. However, their structures are well not analyzed and characterized in detail. The structures of PIP, CEP, CIF, and HypSys are still unknown.

Objective:

Our motivation is to clarify structural features of these plant, small peptides and Flg22 in their bound states.

Methods:

In this article, we performed secondary structure assignments and HELFIT analyses (calculating helix axis, pitch, radius, residues per turn, and handedness) based on the atomic coordinates from the crystal structures of AtPep1, IDA, IDL1, RGFs 1- 3, TDIF/CLE41 - and of flg22. We also performed sequence analysis of the families of PIP, CEP, CIF, and HypSys in order to predict their secondary structures.

Results:

Following AtPep1 with 23 residues adopts two left handed polyproline helices (PPIIs) with six and four residues. IDA, IDL1, RGFs 1 - 2, and TDIF/CLE41 with 12 or 13 residues adopt a four residue PPII; RGF3 adopts two PPIIs with four residues. Flg22 with 22 residues also adopts a six residue PPII. The other peptide hormones – PIP, CEP, CIF, and HypSys – that are rich in proline or hydroxyproline presumably prefer PPII.

Conclusion:

The present analysis indicates that PPII helix in the plant small peptide hormones and in flg22 is crucial for recognition of the LRR domains in receptors.

Super Secondary Structure Consisting of a Polyproline II Helix and a β-Turn in Leucine Rich Repeats in Bacterial Type III Secretion System Effectors

Leucine rich repeats (LRRs) are present in over 100,000 proteins from viruses to eukaryotes. The LRRs are 20–30 residues long and occur in tandem. LRRs form parallel stacks of short β-strands and then assume a super helical arrangement called a solenoid structure. Individual LRRs are separated into highly conserved segment (HCS) with the consensus of LxxLxLxxNxL and variable segment (VS). Eight classes have been recognized. Bacterial LRRs are short and characterized by two prolines in the VS; the consensus is xxLPxLPxx with Nine residues (N-subtype) and xxLPxxLPxx with Ten residues (T-subtype). Bacterial LRRs are contained in type III secretion system effectors such as YopM, IpaH3/9.8, SspH1/2, and SlrP from bacteria. Some LRRs in decorin, fribromodulin, TLR8/9, and FLRT2/3 from vertebrate also contain the motifs. In order to understand structural features of bacterial LRRs, we performed both secondary structures assignments using four programs—DSSP-PPII, PROSS, SEGNO, and XTLSSTR—and HELFIT analyses (calculating helix axis, pitch, radius, residues per turn, and handedness), based on the atomic coordinates of their crystal structures. The N-subtype VS adopts a left handed polyproline II helix (PPII) with four, five or six residues and a type I β-turn at the C-terminal side. Thus, the N-subtype is characterized by a super secondary structure consisting of a PPII and a β-turn. In contrast, the T-subtype VS prefers two separate PPIIs with two or three and two residues. The HELFIT analysis indicates that the type I β-turn is a right handed helix. The HELFIT analysis determines three unit vectors of the helix axes of PPII (P), β-turn (B), and LRR domain (A). Three structural parameters using these three helix axes are suggested to characterize the super secondary structure and the LRR domain.