Abstracts

Specific molecular recognition has long been equated with a well-defined set of contacts, which devoid of conformational and interaction ambiguities. Recently, a more stochastic view has been started to emerge, where proteins conform to multiple structural and functional states in their free as well as in partner bound forms. The latter phenomenon is termed as fuzziness, when diversity, either static or dynamic impacts the regulated formation or activity of protein assemblies. Fuzzy regions serve either as direct interaction elements, or as largely unstructured linkers and tails within higher-order structures may connect separate binding modules to increase their local concentration, exert transient interactions to influence adjacent binding elements, facilitate allostery, or promote intramolecular autoinhibition via well-characterized mechanisms (see also in FuzDB, http://protdyn-database.org).

 All these choreographies are especially relevant for higher-order assemblies that involve low-complexity domains (LCDs) and intrinsically disordered regions (IDRs), which may alternatively either fold into ensembles of structures or remain largely disordered, even exhibiting a fast exchange of conformations in their bound states. I demonstrate that these fuzzy structures are common biophysical characteristics of different types of higher-order assemblies, including amyloids and prions, various kinds of signalosomes, nuclear and cytoplasmic granules, which all defy classical structure-function principles. I discuss a uniform framework, which explains the material properties of higher-order protein structures and the pathological consequences of disease-mutations.

Raphael Guerois

Structural modeling and design of protein interactions using evolution

Institute of Integrated Cell Biology  (I2BC)  -  CEA, CNRS : UMR9198

Ozlem Keskin

PROTEIN-PROTEIN INTERFACES: AMINO ACID VARIATIONS and HOT SPOT RESIDUES

Koç University, Computational Systems Biology Lab, Turkey

Missense mutations on protein-protein interaction (PPI) sites play critical roles in diseases. Distribution of amino acid variations over interface residues may be related to their classification as disease-causing or harmless (benign). Protein-protein interfaces have a small subset of residues called hot spots that contribute the most of the binding energy. These residues are not randomly distributed at the interfaces but rather form clusters called hot regions. Mutations destabilizing PPIs are more likely to be found in hot regions and hot spot residues rather than energetically less important interface residues. Also, analysis on mean square fluctuations of interface residues shows that hot spot residues with destabilizing mutations generally corresponded to more stable residues which are less tolerant to substitution than rest of the interface residues. After analyzing the classification of human mutations as disease-causing or harmless, we conclude that disease-causing mutations are most likely to be found in hot spot residues.

Emmanuel Levy

Proteins evolve on the edge of supramolecular self-assembly

Weizmann Institute of Science, Cell architecture lab, Israel

The self-association of proteins into symmetric complexes is ubiquitous in all kingdoms of life. Symmetric complexes possess unique geometric and functional properties, but their internal symmetry can pose a risk. In sickle cell disease, the symmetry of hemoglobin exacerbates the effect of a mutation, triggering assembly into harmful fibrils. We examined the universality of this mechanism and its relation to protein structure geometry. We introduced point mutations solely designed to increase surface hydrophobicity among twelve distinct symmetric complexes. Strikingly, all responded by forming supramolecular assemblies, both in vitro and in vivo. Remarkably, in four cases, micrometer-long fibrils formed in response to a single point mutation. Biophysical measurements and electron microscopy revealed that mutants self-assembled in their folded states and so were not amyloid-like. Structural examination of 73 mutants identified supramolecular assembly hot spots predictable by geometry. A subsequent structural analysis of thousands of proteins showed that geometric hot spots are buffered chemically by hydrophilic residues, suggesting a mechanism preventing mis-assembly of these regions. Thus, folded proteins can readily self-assemble into higher-order structures. This potential must be counterbalanced by negative selection, and can be exploited to design nanomaterials in living cells.

Yanay Ofran

"All models are wrong, some are useful": Predicting and designing interactions based on multiple wrong models

Bar-Ian University, Systems Biology and Functional Genomics, Israel

The common approach for predicting and designing protein interfaces relies on an atomic model of the 3-D structure of the protein-protein complex. However, as can be seen in benchmark analyses such as CAPRI, state of the art tools for modelling complexes yield more wrong models than correct ones. We propose a new approach that integrates large statistical models and multiple structural models to predict and design specific residue-residue contacts across interfaces. We show how this approach allows for de-novo prediction of protein function and for de-novo design of new proteins, antibodies and drug leads.

Understanding binding energetics of protein-protein interactions (PPIs) at the molecular and structural level is not only interesting for basic science but also valuable for biotechnological applications. Early studies showed that different binding interface residues have various importance to binding energetics and only a few key residues, referred to as hot-spots, are the main contributors to the binding free energy. In contrast to previous studies, we focus our analysis on binding cold-spots or binding interface positions that are occupied by suboptimal amino acids and hence exhibit a potential for affinity enhancement through various mutations. Using both computational methods developed in our lab and directed evolution we study how cold-spot positions are distributed in interfaces of various types of PPIs. We find that in high-affinity PPIs, such as enzyme/inhibitor complexes, cold-spot positions are rare and are usually located at the periphery of the binding interface. On the contrary, in low-affinity PPIs cold-spots are not only frequent but could be also situated right in the middle of the binding interface. In such systems, point mutations at cold-spot positions could result in drastic affinity enhancement, converting them into high-affinity PPIs. Predicting and analyzing such cold-spot positions is not only important for understanding of protein evolution and but would also greatly facilitate protein inhibitor and drug design.

 Peter Uetz

Ilya Vakser