A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments

Abstract

The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected. Next, the remaining fragments are clustered to obtain the central fragments for each cluster. Finally, the central fragments are used as a template to make assignments. Following a large-scale comparison of 11 secondary structure assignment methods, SACF, KAKSI and PROSS are found to have similar agreement with DSSP, while PCASSO agrees with DSSP best. SACF and PCASSO show preference to reducing residues in N and C cap regions, whereas KAKSI, P-SEA and SEGNO tend to add residues to the terminals when DSSP assignment is taken as standard. Moreover, our algorithm is able to assign subtle helices (310-helix, π-helix and left-handed helix) and make uniform assignments, as well as to detect rare SSEs in β-sheets or long helices as outlier fragments from other programs. The structural uniformity should be useful for protein structure classification and prediction, while outlier fragments underlie the structure–function relationship.

Recent advances on polyproline II

“…More than 20 secondary structure assignment methods (SSAM) had been published in 30 years (Aksianov and Alexeevski 2012;Cao et al 2016;Carter et al 2003;Cubellis et al 2005b;Dupuis et al 2004;Fodje and Al-Karadaghi 2002;Frishman and Argos 1995;Hosseini et al 2008;Hutchinson and Thornton 1996;Kabsch and Sander 1983;King and Johnson 1999;Kneller and Hinsen 2015;Labesse et al 1997;Law et al 2014;Majumdar et 6 al. 2005;Martin et al 2005;Oluwatobi Salawu 2016;Parisien and Major 2005;Park et al 2011;Richards and Kundrot 1988;Sklenar et al 1989;Zacharias and Knapp 2014).…”

Automated Protein Secondary Structure Assignment from Cα Positions Using Neural Networks

“…A number of methods, therefore, have been devised to assign a secondary structure solely from C coordinates, e.g., DEFINE_S [ 4 ], P-CURVE [ 5 ], PROSIGN [ 6 ], SACF [ 7 ], P-SEA [ 8 ], PALSSE [ 9 ], STICK [ 10 ], VoTAP [ 11 ], SABA [ 12 ] and SST [ 13 ]. These algorithms can be grouped into three categories: Methods that assign SSE directly from local geometric parameters derived from C positions, e.g., local distances along the chain (DEFINE_S, SABA, STICK), possibly combined with information about close spatial neighbors (P-SEA), dihedral angles (PALSSE), and contact map (VoTAP); fitting a curve to C points was also utilized [ 6 , 7 ]. Methods that cut the query structure into short C structural fragments and compare them to structural fragments extracted from known protein structures, e.g., by means of trained Bayesian (SST) or a Nearest-Neighbor Classifier (SACF).…”

“…Methods that assign SSE directly from local geometric parameters derived from C positions, e.g., local distances along the chain (DEFINE_S, SABA, STICK), possibly combined with information about close spatial neighbors (P-SEA), dihedral angles (PALSSE), and contact map (VoTAP); fitting a curve to C points was also utilized [ 6 , 7 ].…”

Assigning secondary structure in proteins using AI

“…SKSP [24] performs structural alignment of protein pairs prior to structure assignment, and the similarities with these aligned residues are used for structural assignments. SACF [25] introduces fragment-based approaches for conquering structure assignment problems. Here, assignments are done by aligning Cα fragments against some template fragments.…”