DOMMINO: a database of macromolecular interactions

Abstract

With the growing number of experimentally resolved structures of macromolecular complexes, it becomes clear that the interactions that involve protein structures are mediated not only by the protein domains, but also by various non-structured regions, such as interdomain linkers, or terminal sequences. Here, we present DOMMINO (http://dommino.org), a comprehensive database of macromolecular interactions that includes the interactions between protein domains, interdomain linkers, N- and C-terminal regions and protein peptides. The database complements SCOP domain annotations with domain predictions by SUPERFAMILY and is automatically updated every week. The database interface is designed to provide the user with a three-stage pipeline to study macromolecular interactions: (i) a flexible search that can include a PDB ID, type of interaction, SCOP family of interacting proteins, organism name, interaction keyword and a minimal threshold on the number of contact pairs; (ii) visualization of subunit interaction network, where the user can investigate the types of interactions within a macromolecular assembly; and (iii) visualization of an interface structure between any pair of the interacting subunits, where the user can highlight several different types of residues within the interfaces as well as study the structure of the corresponding binary complex of subunits.

Systematic Mutagenesis of Serine Hydroxymethyltransferase Reveals an Essential Role in Nematode Resistance

“…The resulting superfamilies for GmSHMT08 and GmSNAP18 are PLP-dependent transferases (SCOP identifier 53383) and TPR-like proteins (SCOP identifier 48452), respectively. Next, we searched DOMMINO, our comprehensive database of macromolecular interactions (Kuang et al, 2012(Kuang et al, , 2016, for a protein complex that involves the interaction between two proteins, one from the PLP-dependent transferases superfamily and another from the TPR-like superfamily. As a result, we found one complex, involving the interaction between human Ala-glyoxylate aminotransferase and the TPR domain of human PEX5P (PDB identifier 3R9A).…”

DISPOT: A simple knowledge-based protein domain interaction statistical potential

“…Second, for each pair of SCOP families we count a number of non-redundant protein-protein interactions between the members of these families that have been experimentally determined. Our source of data is DOMMINO (Kuang, et al, 2016;Kuang, et al, 2011) a comprehensive database of structurally resolved macromolecular interactions. It contains information about interactions between the protein domains, interdomain linkers, terminal sequences, and protein peptides.…”

Advances in Human Biology: Combining Genetics and Molecular Biophysics to Pave the Way for Personalized Diagnostics and Medicine

“…At the same time, since practically every macromolecule is involved in various interactions including interactions with other macromolecules [93,94], it is equally important to reveal the interacting partners and the structure of the corresponding protein complexes. Several databases summarize and provide details about such interactions [95][96][97][98], including the changes to the binding affinity caused by mutations [99]. While a significant amount of thermodynamics data exists, very few structures of macromolecular complexes are available (as compared with monomeric macromolecules) and therefore the structures have to be predicted in most cases [100][101][102][103].…”

“…Despite the fact that the existing methods are not particularly accurate to predict the exact changes of the binding free energy due to mutation, as can be seen from benchmarking tests against various databases of experimental data points [95,97,99], the predictions still can be used to evaluate the trend of the changes without being too concerned about the magnitude of the changes [33,65,66,131]. In addition, the structures of the corresponding complexes, either experimentally available or modeled in silico, can be used for structural analysis to predict the effect of mutations [152,153].…”