Abstract
Cellular processes often depend on interactions between proteins and the formation of macromolecular complexes. The impairment of such interactions can lead to deregulation of pathways resulting in disease states, and it is hence crucial to gain insights into the nature of macromolecular assemblies. Detailed structural knowledge about complexes and protein-protein interactions is growing, but experimentally determined three-dimensional multimeric assemblies are outnumbered by complexes supported by non-structural experimental evidence. Here, we aim to fill this gap by modeling multimeric structures by homology, only using amino acid sequences to infer the stoichiometry and the overall structure of the assembly. We ask which properties of proteins within a family can assist in the prediction of correct quaternary structure. Specifically, we introduce a description of protein-protein interface conservation as a function of evolutionary distance to reduce the noise in deep multiple sequence alignments. We also define a distance measure to structurally compare homologous multimeric protein complexes. This allows us to hierarchically cluster protein structures and quantify the diversity of alternative biological assemblies known today. We find that a combination of conservation scores, structural clustering, and classical interface descriptors, can improve the selection of homologous protein templates leading to reliable models of protein complexes.
Highlights
Macromolecular complexes are of central interest in structural biology[1,2,3]
These analyses rely on an estimation of conservation that is typically derived from a multiple sequence alignment (MSA) of homologous proteins
Residues participating in interfaces are subject to different evolutionary constraints than residues at the protein surface interacting with the solvent, which creates a confounding factor when proteins organized in different quaternary structures are included in the same alignment
Summary
Macromolecular complexes are of central interest in structural biology[1,2,3]. Direct physical protein-protein interactions (PPIs), as well as indirect ones, are essential for performing and regulating cellular activities such as signal transduction, cell-cycle, morphological differentiation, cell motility, transcription and translation. Shedding light on the atomic details of such interactions is challenging since the expression of protein complexes is often tightly regulated and obtaining sufficient concentrations of intact complexes for structure determination is often not trivial Aiming to fill this gap, several computational techniques to model protein interactions have been developed, which differ in type and amount of structural information required as starting point. We introduce a refined analysis of interface conservation which captures how interface conservation varies as a function of evolutionary distance within a protein family We employ this analysis (which we refer to as Protein-Protein Interaction (PPI) fingerprints) for two critical tasks: first, the discrimination of crystal artifacts from biological contacts, which is a crucial step in determining the correct quaternary state of crystal structures to be used as templates in homology modeling; and second, the evaluation of interface quality in models to assess the confidence in the predicted quaternary structure
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