Automated Procedure for Contact-Map-Based Protein Structure Reconstruction

Abstract

Knowledge of the three-dimensional structures of ion channels allows for modeling their conductivity characteristics using biophysical models and can lead to discovering their cellular functionality. Recent studies show that quality of structure predictions can be significantly improved using protein contact site information. Therefore, a number of procedures for protein structure prediction based on their contact-map have been proposed. Their comparison is difficult due to different methodologies used for validation. In this work, a Contact Map-to-Structure pipeline (C2S_pipeline) for contact-based protein structure reconstruction is designed and validated. The C2S_pipeline can be used to reconstruct monomeric and multimeric proteins. The median RMSD of structures obtained during validation on a representative set of protein structures, equaled 5.27 Å, and the best structure was reconstructed with RMSD of 1.59 Å. The validation is followed by a detailed case study on the KcsA ion channel. Models of KcsA are reconstructed based on different portions of contact site information. Structural feature analysis of acquired KcsA models is supported by a thorough analysis of electrostatic potential distributions inside the channels. The study shows that electrostatic parameters are correlated with structural quality of models. Therefore, they can be used to discriminate between high and low quality structures. We show that 30 % of contact information is needed to obtain accurate structures of KcsA, if contacts are selected randomly. This number increases to 70 % in case of erroneous maps in which the remaining contacts or non-contacts are changed to the opposite. Furthermore, the study reveals that local reconstruction accuracy is correlated with the number of contacts in which amino acid are involved. This results in higher reconstruction accuracy in the structure core than peripheral regions.

Fast assessment of structural models of ion channels based on their predicted current-voltage characteristics

“…The protocol was adapted for modeling multimeric symmetric proteins (see Ref. ). Eventually each complete model was aligned to the original structure using Pymol .…”

“…Modeling a channel structure from the contact map Spatial coordinates of a channel were reconstructed from the contact map in a three step procedure C2S_pipeline, which applied several state-of-the-art bioinformatic tools. 40 Coordinates of C a atoms were estimated based on constraints imposed by the contact map using FT-COMAR. 42,43 The protein backbone was reconstructed by SABBAC 44 (KcsA channel) or REMO 45 (other channels), and side-chains were added using SCWRL.…”

Detection of native and mirror protein structures based on Ramachandran plot analysis by interpretable machine learning models

“…In order to emulate the necessary procedures in structure modeling from contact maps, the authors derived these maps [17] from a set of 1, 305 representative domains of SCOPe superfamilies. Those maps were in turn the base for reconstructing full-atom proteins of different configurations [24,25,29,54], approximately 50 native and mirror models for each domain. Consequently the whole data set comprises 130, 500 models, from which the dihedral angles were calculated [10].…”

Tree-based Secondary Structure Interactions Predictor Method for Protein Contact Maps

“…In addition, threshold values for the residues belonging to the sub-sequence that is formed between i and j. At the end, these rules can be used in the developing drugs process as properties or requirements to be met [41], or as restrictions on the reconstruction of unknown or damaged proteins [42].…”