Inferring and Using Protein Quaternary Structure Information from Crystallographic Data

A unified statistical potential reveals that amino acid stickiness governs nonspecific recruitment of client proteins into condensates

Membraneless organelles are cellular compartments that form by liquid-liquid phase separation of one or more components. Other molecules, such as proteins and nucleic acids, will distribute between the cytoplasm and the liquid compartment in accordance with the thermodynamic drive to lower the free energy of the system. The resulting distribution colocalizes molecular species to carry out a diversity of functions. Two factors could drive this partitioning: the difference in solvation between the dilute versus dense phase and intermolecular interactions between the client and scaffold proteins. Here, we develop a set of knowledge-based potentials that allow for the direct comparison between stickiness, which is dominated by desolvation energy, and pairwise residue contact propensity terms. We use these scales to examine experimental data from two systems: protein cargo dissolving within phase-separated droplets made from FG repeat proteins of the nuclear pore complex and client proteins dissolving within phase-separated FUS droplets. These analyses reveal a close agreement between the stickiness of the client proteins and the experimentally determined values of the partition coefficients (R > 0.9), while pairwise residue contact propensities between client and scaffold show weaker correlations. Hence, the stickiness of client proteins is sufficient to explain their differential partitioning within these two phase-separated systems without taking into account the composition of the condensate. This result implies that selective trafficking of client proteins to distinct membraneless organelles requires recognition elements beyond the client sequence composition. STATEMENT: Empirical potentials for amino acid stickiness and pairwise residue contact propensities are derived. These scales are unique in that they enable direct comparison of desolvation versus contact terms. We find that partitioning of a client protein to a condensate is best explained by amino acid stickiness.

QSalignWeb: A Server to Predict and Analyze Protein Quaternary Structure

The identification of physiologically relevant quaternary structures (QSs) in crystal lattices is challenging. To predict the physiological relevance of a particular QS, QSalign searches for homologous structures in which subunits interact in the same geometry. This approach proved accurate but was limited to structures already present in the Protein Data Bank (PDB). Here, we introduce a webserver (www.QSalign.org) allowing users to submit homo-oligomeric structures of their choice to the QSalign pipeline. Given a user-uploaded structure, the sequence is extracted and used to search homologs based on sequence similarity and PFAM domain architecture. If structural conservation is detected between a homolog and the user-uploaded QS, physiological relevance is inferred. The web server also generates alternative QSs with PISA and processes them the same way as the query submitted to widen the predictions. The result page also shows representative QSs in the protein family of the query, which is informative if no QS conservation was detected or if the protein appears monomeric. These representative QSs can also serve as a starting point for homology modeling.

On Monomeric and Multimeric Structures-Based Protein-Ligand Interactions

Many ligands simultaneously interact with multiple protein chains in quaternary structure (QS). However, a significant number of previous studies on template-based modeling of protein-ligand interactions were based on monomeric structure (MS), which may suffer from incomplete binding information. The defects of using MS rather than QS have not been systematically studied before. In this work, based on molecular docking experiments and binding free energy estimations, we performed a large-scale comparison of the protein-ligand interactions in both forms of structures. We found that 1) about 18.6 percent biologically relevant ligands bind multiple chains in QS simultaneously. 2) For more than 95 percent complexes with multiple chains involved in the interactions, the binding free energy is lower for the QS form than the MS form. 3) For over 70 percent complexes with multi-chain binding pockets, docking with QS yields more accurate ligand conformations than with MS. While for about 1.82 percent complexes, accurate docking conformations were obtained by MS. Based on this work, it is encouraged to make use of QS rather than MS in future studies on protein-ligand interactions.

PDB-wide identification of physiological hetero-oligomeric assemblies based on conserved quaternary structure geometry

An accurate understanding of biomolecular mechanisms and diseases requires information on protein quaternary structure (QS). A critical challenge in inferring QS information from crystallography data is distinguishing biological interfaces from fortuitous crystal-packing contacts. Here, we employ QS conservation across homologs to infer the biological relevance of hetero-oligomers. We compare the structures and compositions of hetero-oligomers, which allow us to annotate 7,810 complexes as physiologically relevant, 1,060 as likely errors, and 1,432 with comparative information on subunit stoichiometry and composition. Excluding immunoglobulins, these annotations encompass over 51% of hetero-oligomers in the PDB. We curate a dataset of 577 hetero-oligomeric complexes to benchmark these annotations, which reveals an accuracy >94%. When homology information is not available, we compare QS across repositories (PDB, PISA, and EPPIC) to derive confidence estimates. This work provides high-quality annotations along with a large benchmark dataset of hetero-assemblies.

Geometric description of self-interaction potential in symmetric protein complexes

Proteins can self-associate with copies of themselves to form symmetric complexes called homomers. Homomers are widespread in all kingdoms of life and allow for unique geometric and functional properties, as reflected in viral capsids or allostery. Once a protein forms a homomer, however, its internal symmetry can compound the effect of point mutations and trigger uncontrolled self-assembly into high-order structures. We identified mutation hot spots for supramolecular assembly, which are predictable by geometry. Here, we present a dataset of descriptors that characterize these hot spot positions both geometrically and chemically, as well as computer scripts allowing the calculation and visualization of these properties for homomers of choice. Since the biological relevance of homomers is not readily available from their X-ray crystallographic structure, we also provide reliability estimates obtained by methods we recently developed. These data have implications in the study of disease-causing mutations, protein evolution and can be exploited in the design of biomaterials.

Design Type(s)	protein interaction analysis objective • protein structure prediction objective • modeling and simulation objective
Measurement Type(s)	protein complex
Technology Type(s)	computational modeling technique
Factor Type(s)	Filtering • source
Sample Characteristic(s)	laboratory environment

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Investigation of quaternary structure of aggregating 3-ketosteroid dehydrogenase from Sterolibacterium denitrificans: In the pursuit of consensus of various biophysical techniques

In this work we analyzed the quaternary structure of FAD-dependent 3-ketosteroid dehydrogenase (AcmB) from Sterolibacterium denitrificans, the protein that in solution forms massive aggregates (>600 kDa). Using size-excursion chromatography (SEC), dynamic light scattering (DLS), native-PAGE and atomic force microscopy (AFM) we studied the nature of enzyme aggregation. Partial protein de-aggregation was facilitated by the presence of non-ionic detergent such as Tween 20 or by a high degree of protein dilution but not by addition of a reducing agent or an increase of ionic strength. De-aggregating influence of Tween 20 had no impact on either enzyme's specific activity or FAD reconstitution to recombinant AcmB. The joint experimental (DLS, isoelectric focusing) and theoretical investigations demonstrated gradual shift of enzyme's isoelectric point upon aggregation from 8.6 for a monomeric form to even 5.0. The AFM imaging on mica or highly oriented pyrolytic graphite (HOPG) surface enabled observation of individual protein monomers deposited from a highly diluted solution (0.2 μg/ml). Such approach revealed that native AcmB can indeed be monomeric. AFM imaging supported by theoretical random sequential adsorption (RSA) kinetics allowed estimation of distribution enzyme forms in the bulk solution: 5%, monomer, 11.4% dimer and 12% trimer. Finally, based on results of AFM as well as analysis of the surface of AcmB homology models we have observed that aggregation is most probably initiated by hydrophobic forces and then assisted by electrostatic attraction between negatively charged aggregates and positively charged monomers.

Infinite Assembly of Folded Proteins in Evolution, Disease, and Engineering

Mutations and changes in a protein's environment are well known for their potential to induce misfolding and aggregation, including amyloid formation. Alternatively, such perturbations can trigger new interactions that lead to the polymerization of folded proteins. In contrast to aggregation, this process does not require misfolding and, to highlight this difference, we refer to it as agglomeration. This term encompasses the amorphous assembly of folded proteins as well as the polymerization in one, two, or three dimensions. We stress the remarkable potential of symmetric homo‐oligomers to agglomerate even by single surface point mutations, and we review the double‐edged nature of this potential: how aberrant assemblies resulting from agglomeration can lead to disease, but also how agglomeration can serve in cellular adaptation and be exploited for the rational design of novel biomaterials.