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Structure-based protein comparison enables mapping of protein relationships

Claim that using structure-based protein comparison facilitates mapping and exploration of protein relationships.

Confidence
90%
active

Evidence Quote

“Protein structural comparisons generate maps revealing protein relationships.”

Relationship

Protein structural comparison enables protein relationships

Arguments

Protein structural comparisonsubject
TM-score (structural similarity)object

Connections (8)

Structure-based protein comparison increases insight over sequence-only analysesInferenceChain
Structural similarity often diverges from sequence similarityAssociation
Leiden clustering algorithmFactor
t-SNE dimensionality reductionFactor
UMAP dimensionality reductionFactor
Structural similarity provides deeper protein space insight than sequence aloneInferenceChain
Protein structure is substantially more conserved than sequenceInferenceChain
Structural methods and algorithms enable protein relationship mappingInferenceChain

Evidence

“Evidence line summarizing advances in clustering and visualization of large datasets using well-connected community detection (Leiden), optimized t-SNE, and UMAP dimensionality reduction.”

From Louvain to Leiden; AOP-tSNE; UMAP

“Reference to the CATH protein structure classification database (2010)”

(2010). The CATH database doi:10.1186/1479-7364-4-3-207 ↗

“Reference describing the SCOPe database by Fox et al. (2013)”

Fox NK et al. (2013). SCOPe: Structural Classification of Proteins—extended, integrating SCOP and ASTRAL data and classification of new structures doi:10.1093/nar/gkt1240 ↗

“Reference for SCOPe database updates (Chandonia et al., 2021)”

Chandonia J-M et al. (2021). SCOPe: improvements to the structural classification of proteins – extended database to facilitate variant interpretation and machine learning doi:10.1093/nar/gkab1054 ↗

“Reference to Hou J et al. (2005) on global mapping of protein structure space”

Hou J et al. (2005). Global mapping of the protein structure space and application in structure-based inference of protein function doi:10.1073/pnas.0409772102 ↗

“Reference to Hou J et al. (2003) describing a global view of protein fold space”

Hou J et al. (2003). A global representation of the protein fold space doi:10.1073/pnas.2628030100 ↗

“Reference to Choi IG and Kim SH (2006) on evolution of protein structural classes”

Choi I-G & Kim S-H (2006). Evolution of protein structural classes and protein sequence families doi:10.1073/pnas.0606239103 ↗

“Reference to Levitt M. (2009) describing the nature of the protein universe”

Levitt M. (2009). Nature of the protein universe doi:10.1073/pnas.0905029106 ↗

“Reference to Osadchy M, Kolodny R. (2011) on protein structure/function mapping”

Osadchy M & Kolodny R (2011). Maps of protein structure space reveal a fundamental relationship between protein structure and function doi:10.1073/pnas.1102727108 ↗

“Reference for the methodology on clustering protein structures at large scale”

Barrio-Hernandez I et al. (2023). Clustering predicted structures at the scale of the known protein universe doi:10.1038/s41586-023-06510-w ↗

“Reference to the UniProt protein database consortium 2021”

UniProt: the universal protein knowledgebase in 2021 doi:10.1093/nar/gkaa1100 ↗

“Reference to ColabFold open-source protein structure prediction platform”

Mirdita M et al. (2022). ColabFold: making protein folding accessible to all doi:10.1038/s41592-022-01488-1 ↗