2023
DOI: 10.1002/pro.4836
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SSDraw: Software for generating comparative protein secondary structure diagrams

Ethan A. Chen,
Lauren L. Porter

Abstract: The program SSDraw generates publication‐quality protein secondary structure diagrams from three‐dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B‐factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other prope… Show more

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Cited by 10 publications
(4 citation statements)
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“…Heat maps of protein domain abundance effects of all mutation types with significant changes in abundance (Bonferroni multiple testing correction of z-stats in a two-tailed test) marked with “*”. We show the 2-dimensional structural representation of the domains (SSDraw 63 ) under each heatmap. For PSD95-PDZ3 and GRB2-SH3 only, we mutated the first 52 residues, leaving, respectively, 32 and 4aa in the C-terminal as wild type.…”
Section: Resultsmentioning
confidence: 99%
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“…Heat maps of protein domain abundance effects of all mutation types with significant changes in abundance (Bonferroni multiple testing correction of z-stats in a two-tailed test) marked with “*”. We show the 2-dimensional structural representation of the domains (SSDraw 63 ) under each heatmap. For PSD95-PDZ3 and GRB2-SH3 only, we mutated the first 52 residues, leaving, respectively, 32 and 4aa in the C-terminal as wild type.…”
Section: Resultsmentioning
confidence: 99%
“…Changes in abundance significant from the weighted mean of the synonymous variants are marked with “*” (Bonferroni multiple testing correction of z-stats in a two-tailed test); y-axis: identity, type or length of mutation; x-axis: mutated position- and the aa sequence of the domain. We show the 2-dimensional structural representation of the domains (SSDraw 63 ) under each heatmap. For PSD95-PDZ3 and GRB2-SH3, we mutated the first 52 residues, leaving, respectively, 32 and 4aa in the C-terminal as wild type.…”
Section: Resultsmentioning
confidence: 99%
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“…Software packages to probe the structural details of protein-ligand interactions do not allow the study of many complexes at once and are limited to only certain types of ligands (Adasme et al, 2021;Laskowski et al, 2018;Laskowski & Swindells, 2011;Schöning-Stierand et al, 2020;Young et al, 2022). And while protein structural search methods such as TM-align (Zhang & Skolnick, 2005), Dali (Holm, 2020), andFold-Seek (van Kempen et al, 2024) have enabled the identification of proteins with local structurally homologous regions, and programs like SSDraw (Chen & Porter, 2023) and ConSurf (Ashkenazy et al, 2016) can align sequences to show how amino acids (AAs) and secondary structures are conserved in a set of homologous proteins, these methods are not designed to highlight or organize conserved binding interactions across diverse proteins: for example, small molecule ligands that bind multiple proteins via different binding pocket geometries or antigens that bind a library of engineered antibodies at non-overlapping epitopes. In such cases, translating trends at the 2D sequence level to the 3D space in related proteins toward identifying molecular patterns that drive or tune biochemical interactions presents a challenge for which no generalizable software is available, even when high-confidence interactions can be predicted at a large scale (Bryant et al, 2022;Evans et al, 2022;Hwang et al, 2017;Petrey et al, 2023;Trudeau et al, 2023;Zhang et al, 2012).…”
Section: Introductionmentioning
confidence: 99%