Functions of Essential Genes and a Scale-Free Protein Interaction Network Revealed by Structure-Based Function and Interaction Prediction for a Minimal Genome

Abstract

Deep learning-based contact prediction in C-I-TASSER; violin plots for portions of residues predicted by TMHMM2.0 to be within transmembrane helices for JCVI-syn3.0 proteins that are annotated versus unannotated by C-I-TASSER/ COFACTOR with C-score > 0.5 for specific GO terms in the MF, BP, and CC aspects; structural alignment of the predicted structure of MMSYN1_0877 with the nine closest structural homologues identified in the Protein Data Bank; substrate binding domains for ECF systems targeting riboflavin; and a random PPI network for syn3.0, where 2483 of all 95,703 protein pairs are randomly selected as the positive PPI pairs (PDF)

Investigation of nonsynonymous mutations in the spike protein of SARS-CoV-2 and its interaction with the ACE2 receptor by molecular docking and MM/GBSA approach

“…Unfortunately, the entire length of the S-protein structure is not available in the protein data bank. We have used the earlier proved studies [ [33] , [34] , [35] , [36] , [37] , [38] ] to fix this issue. Hence, we have preferred the I-TASSER online server to predict the 3D structure of the S-protein.…”

“…Some of the collected SNP residue positions do not present in the existed PDB structures. To fix this issue, we have used the previous research studies as an example and implemented them in this study to construct the three-dimensional (3-D) conformation of the native S-protein [ [33] , [34] , [35] , [36] , [37] , [38] ]. Hence, we used the I-TASSER server [ 39 ] to model the native S-protein.…”

“…It is a threading-based structure prediction program which used to generate the three-dimensional structure of proteins from their amino acid sequence. Some recent studies opted for the threading approach to model the protein to check the interaction with other biological molecules [ [33] , [34] , [35] , [36] , [37] , [38] ]. I-TASSER produces great quality model predictions of three-dimensional structures from amino acid sequences.…”

Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy

“…Application of the SPRING method (Guerler, 2013) to Escherichia coli competitively identified protein-protein interactions while producing accurate multimeric protein structure models of which 39 by now have been confirmed in high-resolution experiments. Other studies applied our method to the minimal synthetic genome syn3.0 (Zhang, 2021) and the mouse genome (Li, 2016). In the present study we describe how we implemented our pipeline on Galaxy (Afgan, 2018), a web-based computational workbench used by many scientists across the world to analyze large data sets.…”

Toward the solution of the protein structure prediction problem

“…This percentage was 0.7% in 2010 and 2% in 2004; therefore, it is apparent that the gap between the number of known protein sequences and experimentally solved protein structures is continually widening. Thanks to the tremendous effort made by the community over the last few decades ( 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ), an increasing portion of the genes in organisms have had their tertiary structures reliably modeled by computational approaches ( 30 , 31 , 32 , 33 , 34 , 35 , 36 ). In addition, numerous high-quality structural models are being created every day by online structure prediction systems ( 22 , 23 , 27 , 29 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ), which have been used to assist various biomedical studies, including structure-based protein function annotation ( 44 , 45 , 46 , 47 , 48 ), mutation analysis ( 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ), ligand screening ( 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ), and drug discovery ( 65 , 66 , 67 , 68 , 69 , 70 ).…”