Towards a Stochastic Paradigm: From Fuzzy Ensembles to Cellular Functions

Protein structure-function continuum model: Emerging nexuses between specificity, evolution, and structure

The rationale for replacing the old binary of structure-function with the trinity of structure, disorder, and function has gained considerable ground in recent years. A continuum model based on the expanded form of the existing paradigm can now subsume importance of both conformational flexibility and intrinsic disorder in protein function. The disorder is actually critical for understanding the protein-protein interactions in many regulatory processes, formation of membrane-less organelles, and our revised notions of specificity as amply illustrated by moonlighting proteins. While its importance in formation of amyloids and function of prions is often discussed, the roles of intrinsic disorder in infectious diseases and protein function under extreme conditions are also becoming clear. This review is an attempt to discuss how our current understanding of protein function, specificity, and evolution fit better with the continuum model. This integration of structure and disorder under a single model may bring greater clarity in our continuing quest for understanding proteins and molecular mechanisms of their functionality.

Protein interactions: anything new?

How do proteins interact in the cellular environment? Which interactions stabilize liquid-liquid phase separated condensates? Are the concepts, which have been developed for specific protein complexes also applicable to higher-order assemblies? Recent discoveries prompt for a universal framework for protein interactions, which can be applied across the scales of protein communities. Here, we discuss how our views on protein interactions have evolved from rigid structures to conformational ensembles of proteins and discuss the open problems, in particular related to biomolecular condensates. Protein interactions have evolved to follow changes in the cellular environment, which manifests in multiple modes of interactions between the same partners. Such cellular context-dependence requires multiplicity of binding modes (MBM) by sampling multiple minima of the interaction energy landscape. We demonstrate that the energy landscape framework of protein folding can be applied to explain this phenomenon, opening a perspective toward a physics-based, universal model for cellular protein behaviors.

Liquid-liquid phase separation as an organizing principle of intracellular space: overview of the evolution of the cell compartmentalization concept

At the turn of the twenty-first century, fundamental changes took place in the understanding of the structure and function of proteins and then in the appreciation of the intracellular space organization. A rather mechanistic model of the organization of living matter, where the function of proteins is determined by their rigid globular structure, and the intracellular processes occur in rigidly determined compartments, was replaced by an idea that highly dynamic and multifunctional "soft matter" lies at the heart of all living things. According this "new view", the most important role in the spatio-temporal organization of the intracellular space is played by liquid-liquid phase transitions of biopolymers. These self-organizing cellular compartments are open dynamic systems existing at the edge of chaos. They are characterized by the exceptional structural and compositional dynamics, and their multicomponent nature and polyfunctionality provide means for the finely tuned regulation of various intracellular processes. Changes in the external conditions can cause a disruption of the biogenesis of these cellular bodies leading to the irreversible aggregation of their constituent proteins, followed by the transition to a gel-like state and the emergence of amyloid fibrils. This work represents a historical overview of changes in our understanding of the intracellular space compartmentalization. It also reflects methodological breakthroughs that led to a change in paradigms in this area of science and discusses modern ideas about the organization of the intracellular space. It is emphasized here that the membrane-less organelles have to combine a certain resistance to the changes in their environment and, at the same time, show high sensitivity to the external signals, which ensures the normal functioning of the cell.

Protein conformational dynamics and phenotypic switching

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure but exist as conformational ensembles. Because of their structural plasticity, they can interact with multiple partners. The protein interactions between IDPs and their partners form scale-free protein interaction networks (PINs) that facilitate information flow in the cell. Because of their plasticity, IDPs typically occupy hub positions in cellular PINs. Furthermore, their conformational dynamics and propensity for post-translational modifications contribute to "conformational" noise which is distinct from the well-recognized transcriptional noise. Therefore, upregulation of IDPs in response to a specific input, such as stress, contributes to increased noise and, hence, an increase in stochastic, "promiscuous" interactions. These interactions lead to activation of latent pathways or can induce "rewiring" of the PIN to yield an optimal output underscoring the critical role of IDPs in regulating information flow. We have used PAGE4, a highly intrinsically disordered stress-response protein as a paradigm. Employing a variety of experimental and computational techniques, we have elucidated the role of PAGE4 in phenotypic switching of prostate cancer cells at a systems level. These cumulative studies over the past decade provide a conceptual framework to better understand how IDP conformational dynamics and conformational noise might facilitate cellular decision-making.

FuzDB: a new phase in understanding fuzzy interactions

Fuzzy interactions are specific, variable contacts between proteins and other biomolecules (proteins, DNA, RNA, small molecules) formed in accord to the cellular context. Fuzzy interactions have recently been demonstrated to regulate biomolecular condensates generated by liquid-liquid phase separation. The FuzDB v4.0 database (https://fuzdb.org) assembles experimentally identified examples of fuzzy interactions, where disordered regions mediate functionally important, context-dependent contacts between the partners in stoichiometric and higher-order assemblies. The new version of FuzDB establishes cross-links with databases on structure (PDB, BMRB, PED), function (ELM, UniProt) and biomolecular condensates (PhaSepDB, PhaSePro, LLPSDB). FuzDB v4.0 is a source to decipher molecular basis of complex cellular interaction behaviors, including those in protein droplets.

Fuzzy protein theory for disordered proteins

Why proteins are fuzzy? Constant adaptation to the cellular environment requires a wide range of changes in protein structure and interactions. Conformational ensembles of disordered proteins in particular exhibit large shifts to activate or inhibit alternative pathways. Fuzziness is critical for liquid–liquid phase separation and conversion of biomolecular condensates into fibrils. Interpretation of these phenomena presents a challenge for the classical structure-function paradigm. Here I discuss a multi-valued formalism, based on fuzzy logic, which can be applied to describe complex cellular behavior of proteins.

Recent Developments in the Field of Intrinsically Disordered Proteins: Intrinsic Disorder-Based Emergence in Cellular Biology in Light of the Physiological and Pathological Liquid-Liquid Phase Transitions

This review deals with two important concepts-protein intrinsic disorder and proteinaceous membrane-less organelles (PMLOs). The past 20 years have seen an upsurge of scientific interest in these phenomena. However, neither are new discoveries made in this century, but instead are timely reincarnations of old ideas that were mostly ignored by the scientific community for a long time. Merging these concepts in the form of the intrinsic disorder-based biological liquid-liquid phase separation provides a basis for understanding the molecular mechanisms of PMLO biogenesis.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Asymmetric dynamic coupling promotes alternative evolutionary pathways in an enzyme dimer

The importance of dynamic factors in enzyme evolution is gaining recognition. Here we study how the evolution of a new enzymatic activity exploits conformational tinkering and demonstrate that conversion of a dimeric phosphotriesterase to an arylesterase in Pseudomonas diminuta is accompanied by structural divergence between the two subunits. Deviations in loop conformations increase with promiscuity, leading to functionally distinct states, while they decrease during specialisation for the new function. We show that opposite loop movements in the two subunits are due to a dynamic coupling with the dimer interface, the importance of which is also corroborated by the co-evolution of the loop and interface residues. These results illuminate how protein dynamics promotes conformational heterogeneity in a dimeric enzyme, leading to alternative evolutionary pathways for the emergence of a new function.

Moonlighting Proteins in the Fuzzy Logic of Cellular Metabolism

The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how they interact, and their regulation. Each cell contains thousands of proteins with changing levels of expression, levels of activity, and patterns of interactions. Adding more layers of complexity is the number of proteins that have multiple functions. Moonlighting proteins include a wide variety of proteins where two or more functions are performed by one polypeptide chain. In this article, we discuss examples of proteins with variable functions that contribute to the fuzziness of cellular metabolism.

Structural Fuzziness of the RNA-Organizing Protein SERF Determines a Toxic Gain-of-interaction

The mechanisms by which protein complexes convert from functional to pathogenic are the subject of intensive research. Here, we report how functionally unfavorable protein interactions can be induced by structural fuzziness, i.e., by persisting conformational disorder in protein complexes. We show that extreme disorder in the bound state transforms the intrinsically disordered protein SERF1a from an RNA-organizing factor into a pathogenic enhancer of alpha-synuclein (aSyn) amyloid toxicity. We demonstrate that SERF1a promotes the incorporation of RNA into nucleoli and liquid-like artificial RNA-organelles by retaining an unusually high degree of conformational disorder in the RNA-bound state. However, this type of structural fuzziness also determines an undifferentiated interaction with aSyn. RNA and aSyn both bind to one identical, positively charged site of SERF1a by an analogous electrostatic binding mode, with similar binding affinities, and without any observable disorder-to-order transition. The absence of primary or secondary structure discriminants results in SERF1a being unable to select between nucleic acid and amyloidogenic protein, leading the pro-amyloid aSyn:SERF1a interaction to prevail in the cytosol under conditions of cellular stress. We suggest that fuzzy disorder in SERF1a complexes accounts for an adverse gain-of-interaction which favors toxic binding to aSyn at the expense of nontoxic RNA binding, thereby leading to a functionally distorted and pathogenic process. Thus, structural fuzziness constitutes a direct link between extreme conformational flexibility, amyloid aggregation, and the malfunctioning of RNA-associated cellular processes, three signatures of neurodegenerative proteinopathies.

Intrinsically disordered proteins and phenotypic switching: Implications in cancer

It is now well established that intrinsically disordered proteins (IDPs) that constitute a large part of the proteome across the three kingdoms, play critical roles in several biological processes including phenotypic switching. However, dysregulated expression of IDPs that engage in promiscuous interactions can lead to pathological states. In this chapter, using cancer as a paradigm, we discuss how IDP conformational dynamics and the resultant conformational noise can modulate phenotypic switching. Thus, contrary to the prevailing wisdom that phenotypic switching is highly deterministic (has a genetic underpinning) in cancer, emerging evidence suggests that non-genetic mechanisms, at least in part due to the conformational noise, may also be a confounding factor in phenotypic switching.

Computational Structural Biology: Successes, Future Directions, and Challenges

Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous 'big data' integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells' actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions.