Predicting Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence
Akira R. Kinjo, Ken Nishikawa
Abstract
Residue-wise contact order (RWCO) is a new kind of one-dimensional protein structures which represents the extent of long-range contacts. We have recently shown that a set of three types of one-dimensional structures (secondary structure, contact number, and RWCO) contains sufficient information for reconstructing the three-dimensional structure of proteins. Currently, there exist prediction methods for secondary structure and contact number from amino acid sequence, but none exists for RWCO. Also, the properties of amino acids that affect RWCO is not clearly understood. Here, we present a linear regression-based method to predict RWCO from amino acid sequence, and analyze the regression parameters to identify the properties that correlates with the RWCO. The present method achieves the significant correlation of 0.59 between the native and predicted RWCOs on average. An unusual feature of the RWCO prediction is the remarkably large optimal half window size of 26 residues. The regression parameters for the central and near-central residues of the local sequence segment highly correlate with those of the contact number prediction, and hence with hydrophobicity.
Create a lesson
Related papers
SaltyMeta: a curated benchmark and protein language model-informed web tool for salty peptide prediction
Wanchao Chen, Wen Li, Yanan He et al.
Exploring Optimal Parameters for Ligand-Based Virtual Screening in Early Drug Discovery
Temitope Sobodu, Victor Chibuzor Johnson, Ryan Kern et al.
Synthesizing State-of-the-Art Structure Predictions from Soup of Co-folding Models
Hyosoon Jang, Taewon Kim, Sungsoo Ahn
Sequence-Informed Geometric Evaluation of RNA 3D Structures
Andrea Zerio, Yighua Yao, Alessandro Micheli et al.
Multi-ligand simultaneous docking of Carica papaya leaf phytochemicals, Carpaine and Rutin, reveals multi-mechanism inhibition of cancer proteins BCL-2 and WWP1
Merla Sudha, Asmita Saha, Belaguppa Manjunath Ashwin Desai et al.
Predicting directional flexibility in proteins
Vsevolod Viliuga, Leif Seute, Matteo Tadiello et al.