Affinity of disordered protein complexes is modulated by entropy-energy reinforcement

Context-dependent, fuzzy protein interactions: Towards sequence-based insights

Predicting protein interactions in the cellular environment still remains a challenge in the AlphaFold era. Protein interactions, similarly to their structures, sample a continuum from ordered to disordered states, with specific partners in many bound configurations. A multiplicity of binding modes (MBM) enables transition between these states under different cellular conditions. This review focuses on how the cellular environment affects protein interactions, highlighting the molecular mechanisms, biophysical origin, and sequence-based principles of context-dependent, fuzzy interactions. It summarises experimental and computational approaches to address the challenge of interaction heterogeneity and its contribution to a wide range of biological functions. These insights will help in understanding complex cellular processes, involving conversions between protein assembly states, such as from liquid-like droplet state to the amyloid state.

RNA's Dynamic Conformational Selection and Entropic Allosteric Mechanism in Controlling Cascade Protein Binding Events

In the TAR RNA of immunodeficiency viruses, an allosteric communication exists between a distant loop and a bulge. The bulge interacts with the TAT protein vital for transactivating viral RNA, while the loop interacts with cyclin-T1, contingent on TAT binding. Through extensive atomistic and free energy simulations, we investigate TAR-TAT binding in nonpathogenic bovine immunodeficiency virus (BIV) and pathogenic human immunodeficiency virus (HIV). Thermodynamic analysis reveals enthalpically driven binding in BIV and entropically favored binding in HIV. The broader global basin in HIV is attributed to binding-induced loop fluctuation, corroborated by nuclear magnetic resonance (NMR), indicating classical entropic allostery onset. While this loop fluctuation affects the TAT binding affinity, it generates a binding-competent conformation that aids subsequent effector (cyclin-T1) binding. This study underscores how two structurally similar apo-RNA scaffolds adopt distinct conformational selection mechanisms to drive enthalpic and entropic allostery, influencing protein affinity in the signaling cascade.

Disorder in CENP-ACse4 tail-chaperone interaction facilitates binding with Ame1/Okp1 at the kinetochore

The centromere is epigenetically marked by a histone H3 variant-CENP-A. The budding yeast CENP-A called Cse4, consists of an unusually long N-terminus that is known to be involved in kinetochore assembly. Its disordered chaperone, Scm3 is responsible for the centromeric deposition of Cse4 as well as in the maintenance of a segregation-competent kinetochore. In this study, we show that the Cse4 N-terminus is intrinsically disordered and interacts with Scm3 at multiple sites, and the complex does not gain any substantial structure. Additionally, the complex forms a synergistic association with an essential inner kinetochore component (Ctf19-Mcm21-Okp1-Ame1), and a model has been suggested to this effect. Thus, our study provides mechanistic insights into the Cse4 N-terminus-chaperone interaction and also illustrates how intrinsically disordered proteins mediate assembly of complex multiprotein networks, in general.

The Rapid Evolution of De Novo Proteins in Structure and Complex

Recent studies in the rice genome-wide have established that de novo genes, evolving from noncoding sequences, enhance protein diversity through a stepwise process. However, the pattern and rate of their evolution in protein structure over time remain unclear. Here, we addressed these issues within a surprisingly short evolutionary timescale (<1 million years for 97% of Oryza de novo genes) with comparative approaches to gene duplicates. We found that de novo genes evolve faster than gene duplicates in the intrinsically disordered regions (such as random coils), secondary structure elements (such as α helix and β strand), hydrophobicity, and molecular recognition features. In de novo proteins, specifically, we observed an 8% to 14% decay in random coils and intrinsically disordered region lengths and a 2.3% to 6.5% increase in structured elements, hydrophobicity, and molecular recognition features, per million years on average. These patterns of structural evolution align with changes in amino acid composition over time as well. We also revealed higher positive charges but smaller molecular weights for de novo proteins than duplicates. Tertiary structure predictions showed that most de novo proteins, though not typically well folded on their own, readily form low-energy and compact complexes with other proteins facilitated by extensive residue contacts and conformational flexibility, suggesting a faster-binding scenario in de novo proteins to promote interaction. These analyses illuminate a rapid evolution of protein structure in de novo genes in rice genomes, originating from noncoding sequences, highlighting their quick transformation into active, protein complex-forming components within a remarkably short evolutionary timeframe.

Combinatorially restricted computational design of protein-protein interfaces to produce IgG heterodimers

Redesigning protein-protein interfaces is an important tool for developing therapeutic strategies. Interfaces can be redesigned by in silico screening, which allows for efficient sampling of a large protein space before experimental validation. However, computational costs limit the number of combinations that can be reasonably sampled. Here, we present combinatorial tyrosine (Y)/serine (S) selection (combYSelect), a computational approach combining in silico determination of the change in binding free energy (ΔΔG) of an interface with a highly restricted library composed of just two amino acids, tyrosine and serine. We used combYSelect to design two immunoglobulin G (IgG) heterodimers-combYSelect1 (L368S/D399Y-K409S/T411Y) and combYSelect2 (D399Y/K447S-K409S/T411Y)-that exhibit near-optimal heterodimerization, without affecting IgG stability or function. We solved the crystal structures of these heterodimers and found that dynamic π-stacking interactions and polar contacts drive preferential heterodimeric interactions. Finally, we demonstrated the utility of our combYSelect heterodimers by engineering both a bispecific antibody and a cytokine trap for two unique therapeutic applications.

Active learning of the thermodynamics-dynamics trade-off in protein condensates

Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.

Energy landscape quantifications of histone H3.3 recognition by chaperone DAXX reveal an uncoupled binding specificity and affinity

Histone variant H3.3 differs from the canonical histone H3.1 by only five amino acids, yet its chaperone death domain-associated protein (DAXX) can specifically recognize H3.3 over H3.1, despite having a large DAXX-interacting surface on the H3.3-H4 heterodimer common to that on the H3.1-H4 complex. This observation gives rise to the question of, from the binding energy point view, how high binding specificity may be achieved with small differences of the overall binding energy for protein-protein interactions in general. Here we investigate the mechanism of coupling of binding specificity and affinity in protein-protein interactions using the DAXX-H3.3-H4 complex as a model. Using a multi-scale method, we found that the hydrophobic interactions between DAXX and the H3.3-specific region contributed to their initial binding process. And the structural flexibility of the interacting partners contributed to the binding affinity after their encounter. By quantifying the free energy landscape, we revealed that the interaction between the specific residues of H3.3 and DAXX decreased the encounter barrier height while the folding of H3.3-H4 and DAXX increased the depth of the free energy basin of the final binding state. The encounter barrier height, which is not coupled to the thermodynamic stability of the final binding state, had a marked effect on the initial binding rate of flexible histones and chaperones. Based on the energy landscape theory, we found that the intrinsic binding energy funnel of this uncoupled recognition process was affected by the structural flexibility and the flexibility modulated the degree of coupling between binding specificity and affinity. Our work offers a biophysical explanation of the specific recognition between the histones and their chaperones, and also extends the use of energy landscape theory for understanding molecular recognitions in general.

The influence of tag sequence on recombinant humanized collagen (rhCol) and the evaluation of rhCol on Schwann cell behaviors

Recombinant humanized collagen (rhCol) was an extracellular matrix (ECM)-inspired biomimetic biomaterial prepared by biosynthesis technology, which was considered non-allergenic and could possibly activate tissue regeneration. The influence of tag sequence on both structures and performances of rhCol type III (rhCol III) was investigated, and the effect of rhCol III on cell behaviors was evaluated and discussed using Schwann cells (SCs) as in vitro model that was critical in the repair process after peripheral nerve injury. The results demonstrated that the introduction of tag sequence would influence both advanced structures and properties of rhCol III, while rhCol III regulated SCs adhesion, spreading, migration and proliferation. Also, both nerve growth factor and brain-derived neurotrophic factor increased when exposed to rhCol III. As the downstream proteins of integrin-mediated cell adhesions, phosphorylation of focal adhesion kinase and expression of vinculin was up-regulated along with the promotion of SCs adhesion and migration. The current findings contributed to a better knowledge of the interactions between rhCol III and SCs, and further offered a theoretical and experimental foundation for the development of rhCol III-based medical devices and clinical management of peripheral nerve injury.

Driving forces of the complex formation between highly charged disordered proteins

Highly disordered complexes between oppositely charged intrinsically disordered proteins present a new paradigm of biomolecular interactions. Here, we investigate the driving forces of such interactions for the example of the highly positively charged linker histone H1 and its highly negatively charged chaperone, prothymosin α (ProTα). Temperature-dependent single-molecule Förster resonance energy transfer (FRET) experiments and isothermal titration calorimetry reveal ProTα-H1 binding to be enthalpically unfavorable, and salt-dependent affinity measurements suggest counterion release entropy to be an important thermodynamic driving force. Using single-molecule FRET, we also identify ternary complexes between ProTα and H1 in addition to the heterodimer at equilibrium and show how they contribute to the thermodynamics observed in ensemble experiments. Finally, we explain the observed thermodynamics quantitatively with a mean-field polyelectrolyte theory that treats counterion release explicitly. ProTα-H1 complex formation resembles the interactions between synthetic polyelectrolytes, and the underlying principles are likely to be of broad relevance for interactions between charged biomolecules in general.

Cross-Talk of Cation-π Interactions with Electrostatic and Aromatic Interactions: A Salt-Dependent Trade-off in Biomolecular Condensates

Biomolecular condensates are essential for cellular functionality, yet the complex interplay among the diverse molecular interactions that mediate their formation remains poorly understood. Here, using coarse-grained molecular dynamics simulations, we address the contribution of cation-π interactions to the stability of condensates formed via liquid-liquid phase separation. We found greater stabilization of up to 80% via cation-π interactions in condensates formed from peptides with higher aromatic residue content or less charge clustering. The contribution of cation-π interactions to droplet stability increases with increasing ionic strength, suggesting a trade-off between cation-π and electrostatic interactions. Cation-π interactions, therefore, can compensate for reduced electrostatic interactions, such as occurs at higher salt concentrations and in sequences with less charged residue content or clustering. Designing condensates with desired biophysical characteristics therefore requires quantification not only of the individual interactions but also cross-talks involving charge-charge, π-π, and cation-π interactions.

Flanking regions, amyloid cores, and polymorphism: the potential interplay underlying structural diversity

The β-sheet-rich amyloid core is the defining feature of protein aggregates associated with neurodegenerative disorders. Recent investigations have revealed that there exist multiple examples of the same protein, with the same sequence, forming a variety of amyloid cores with distinct structural characteristics. These structural variants, termed as polymorphs, are hypothesized to influence the pathological profile and the progression of different neurodegenerative diseases, giving rise to unique phenotypic differences. Thus, identifying the origin and properties of these structural variants remain a focus of studies, as a preliminary step in the development of therapeutic strategies. Here, we review the potential role of the flanking regions of amyloid cores in inducing polymorphism. These regions, adjacent to the amyloid cores, show a preponderance for being structurally disordered, imbuing them with functional promiscuity. The dynamic nature of the flanking regions can then manifest in the form of conformational polymorphism of the aggregates. We take a closer look at the sequences flanking the amyloid cores, followed by a review of the polymorphic aggregates of the well-characterized proteins amyloid-β, α-synuclein, Tau, and TDP-43. We also consider different factors that can potentially influence aggregate structure and how these regions can be viewed as novel targets for therapeutic strategies by utilizing their unique structural properties.

Distinguishing features of fold-switching proteins

Though many folded proteins assume one stable structure that performs one function, a small-but-increasing number remodel their secondary and tertiary structures and change their functions in response to cellular stimuli. These fold-switching proteins regulate biological processes and are associated with autoimmune dysfunction, severe acute respiratory syndrome coronavirus-2 infection, and more. Despite their biological importance, it is difficult to computationally predict fold switching. With the aim of advancing computational prediction and experimental characterization of fold switchers, this review discusses several features that distinguish fold-switching proteins from their single-fold and intrinsically disordered counterparts. First, the isolated structures of fold switchers are less stable and more heterogeneous than single folders but more stable and less heterogeneous than intrinsically disordered proteins (IDPs). Second, the sequences of single fold, fold switching, and intrinsically disordered proteins can evolve at distinct rates. Third, proteins from these three classes are best predicted using different computational techniques. Finally, late-breaking results suggest that single folders, fold switchers, and IDPs have distinct patterns of residue-residue coevolution. The review closes by discussing high-throughput and medium-throughput experimental approaches that might be used to identify new fold-switching proteins.

Conformational Analysis of Charged Homo-Polypeptides

Many proteins have intrinsically disordered regions (IDRs), which are often characterized by a high fraction of charged residues with polyampholytic (i.e., mixed charge) or polyelectrolytic (i.e., uniform charge) characteristics. Polyelectrolytic IDRs include consecutive positively charged Lys or Arg residues (K/R repeats) or consecutive negatively charged Asp or Glu residues (D/E repeats). In previous research, D/E repeats were found to be about five times longer than K/R repeats and to be much more common in eukaryotes. Within these repeats, a preference is often observed for E over D and for K over R. To understand the greater prevalence of D/E over K/R repeats and the higher abundance of E and K, we simulated the conformational ensemble of charged homo-polypeptides (polyK, polyR, polyD, and polyE) using molecular dynamics simulations. The conformational preferences and dynamics of these polyelectrolytic polypeptides change with changes in salt concentration. In particular, polyD and polyE are more sensitive to salt than polyK and polyR, as polyD and polyE tend to adsorb more divalent cations, which leads to their having more compact conformations. We conclude with a discussion of biophysical explanations for the relative abundance of charged amino acids and particularly for the greater abundance of D/E repeats over K/R repeats.

Chemical tools for study and modulation of biomolecular phase transitions

Biomolecular phase transitions play an important role in organizing cellular processes in space and time. Methods and tools for studying these transitions, and the intrinsically disordered proteins (IDPs) that often drive them, are typically less developed than tools for studying their folded protein counterparts. In this perspective, we assess the current landscape of chemical tools for studying IDPs, with a specific focus on protein liquid-liquid phase separation (LLPS). We highlight methodologies that enable imaging and spectroscopic studies of these systems, including site-specific labeling with small molecules and the diverse range of capabilities offered by inteins and protein semisynthesis. We discuss strategies for introducing post-translational modifications that are central to IDP and LLPS function and regulation. We also investigate the nascent field of noncovalent small-molecule modulators of LLPS. We hope that this review of the state-of-the-art in chemical tools for interrogating IDPs and LLPS, along with an associated perspective on areas of unmet need, can serve as a valuable and timely resource for these rapidly expanding fields of study.

Analytical Formulation and Field-Theoretic Simulation of Sequence-Specific Phase Separation of Protein-Like Heteropolymers with Short- and Long-Spatial-Range Interactions

A theory for sequence-dependent liquid-liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs) in the study of biomolecular condensates is formulated by extending the random phase approximation (RPA) and field-theoretic simulation (FTS) of heteropolymers with spatially long-range Coulomb interactions to include the fundamental effects of short-range, hydrophobic-like interactions between amino acid residues. To this end, short-range effects are modeled by Yukawa interactions between multiple nonelectrostatic charges derived from an eigenvalue decomposition of pairwise residue-residue contact energies. Chain excluded volume is afforded by incompressibility constraints. A mean-field approximation leads to an effective Flory-Huggins χ parameter, which, in conjunction with RPA, accounts for the contact-interaction effects of amino acid composition and the sequence-pattern effects of long-range electrostatics in IDP LLPS, whereas FTS based on the formulation provides full sequence dependence for both short- and long-range interactions. This general approach is illustrated here by applications to variants of a natural IDP in the context of several different amino-acid interaction schemes as well as a set of different model hydrophobic-polar sequences sharing the same composition. Effectiveness of the methodology is verified by coarse-grained explicit-chain molecular dynamics simulations.