Principles of assembly reveal a periodic table of protein complexes

Open Problems in Computational Historical Linguistics

Problems constitute the starting point of all scientific research. The essay reflects on the different kinds of problems that scientists address in their research and discusses a list of 10 problems for the field of computational historical linguistics, that was proposed throughout 2019 in a series of blog posts (see http://phylonetworks.blogspot.com/). In contrast to problems identified in different contexts, these problems were considered to be solvable, but no solution could be proposed back then. By discussing the problems in the light of developments that have been made in the field during the past five years, a modified list is proposed that takes new insights into account but also finds that the majority of the problems has not yet been solved.

Discovering optimal kinetic pathways for self-assembly using automatic differentiation

Macromolecular complexes are often composed of diverse subunits. The self-assembly of these subunits is inherently nonequilibrium and must avoid kinetic traps to achieve high yield over feasible timescales. We show how the kinetics of self-assembly benefits from diversity in subunits because it generates an expansive parameter space that naturally improves the "expressivity" of self-assembly, much like a deeper neural network. By using automatic differentiation algorithms commonly used in deep learning, we searched the parameter spaces of mass-action kinetic models to identify classes of kinetic protocols that mimic biological solutions for productive self-assembly. Our results reveal how high-yield complexes that easily become kinetically trapped in incomplete intermediates can instead be steered by internal design of rate-constants or external and active control of subunits to efficiently assemble. Internal design of a hierarchy of subunit binding rates generates self-assembly that can robustly avoid kinetic traps for all concentrations and energetics, but it places strict constraints on selection of relative rates. External control via subunit titration is more versatile, avoiding kinetic traps for any system without requiring molecular engineering of binding rates, albeit less efficiently and robustly. We derive theoretical expressions for the timescales of kinetic traps, and we demonstrate our optimization method applies not just for design but inference, extracting intersubunit binding rates from observations of yield-vs.-time for a heterotetramer. Overall, we identify optimal kinetic protocols for self-assembly as a powerful mechanism to achieve efficient and high-yield assembly in synthetic systems whether robustness or ease of "designability" is preferred.

Emergence of fractal geometries in the evolution of a metabolic enzyme

Fractals are patterns that are self-similar across multiple length-scales1. Macroscopic fractals are common in nature2-4; however, so far, molecular assembly into fractals is restricted to synthetic systems5-12. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into Sierpiński triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution.

An atlas of protein homo-oligomerization across domains of life

Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalable strategy based on AlphaFold2 to predict homo-oligomeric assemblies across four proteomes spanning the tree of life. Our results suggest that approximately 45% of an archaeal proteome and a bacterial proteome and 20% of two eukaryotic proteomes form homomers. Our predictions accurately capture protein homo-oligomerization, recapitulate megadalton complexes, and unveil hundreds of homo-oligomer types, including three confirmed experimentally by structure determination. Integrating these datasets with omics information suggests that a majority of known protein complexes are symmetric. Finally, these datasets provide a structural context for interpreting disease mutations and reveal coiled-coil regions as major enablers of quaternary structure evolution in human. Our strategy is applicable to any organism and provides a comprehensive view of homo-oligomerization in proteomes.

Protein-based bioactive coatings: from nanoarchitectonics to applications

Protein-based bioactive coatings have emerged as a versatile and promising strategy for enhancing the performance and biocompatibility of diverse biomedical materials and devices. Through surface modification, these coatings confer novel biofunctional attributes, rendering the material highly bioactive. Their widespread adoption across various domains in recent years underscores their importance. This review systematically elucidates the behavior of protein-based bioactive coatings in organisms and expounds on their underlying mechanisms. Furthermore, it highlights notable advancements in artificial synthesis methodologies and their functional applications in vitro. A focal point is the delineation of assembly strategies employed in crafting protein-based bioactive coatings, which provides a guide for their expansion and sustained implementation. Finally, the current trends, challenges, and future directions of protein-based bioactive coatings are discussed.

Agglomeration: when folded proteins clump together

Protein self-association is a widespread phenomenon that results in the formation of multimeric protein structures with critical roles in cellular processes. Protein self-association can lead to finite protein complexes or open-ended, and potentially, infinite structures. This review explores the concept of protein agglomeration, a process that results from the infinite self-assembly of folded proteins. We highlight its differences from other better-described processes with similar macroscopic features, such as aggregation and liquid-liquid phase separation. We review the sequence, structural, and biophysical factors influencing protein agglomeration. Lastly, we briefly discuss the implications of agglomeration in evolution, disease, and aging. Overall, this review highlights the need to study protein agglomeration for a better understanding of cellular processes.

The Smallest Infectious Substructure Encoding the Prion Strain Structural Determinant Revealed by Spontaneous Dissociation of Misfolded Prion Protein Assemblies

It is commonly accepted that the prion replicative propensity and strain structural determinant (SSD) are encoded in the fold of PrPSc amyloid fibril assemblies. By exploring the quaternary structure dynamicity of several prion strains, we revealed that all mammalian prion assemblies exhibit the generic property of spontaneously generating two sets of discreet infectious tetrameric and dimeric species differing significantly by their specific infectivity. By using perturbation approaches such as dilution and ionic strength variation, we demonstrated that these two oligomeric species were highly dynamic and evolved differently in the presence of chaotropic agents. In general, our observations of seven different prion strains from three distinct species highlight the high dynamicity of PrPSc assemblies as a common and intrinsic property of mammalian prions. The existence of such small infectious PrPSc species harboring the SSD indicates that the prion infectivity and the SSD are not restricted only to the amyloid fold but can also be encoded in other alternative quaternary structures. Such diversity in the quaternary structure of prion assemblies tends to indicate that the structure of PrPSc can be divided into two independent folding domains: a domain encoding the strain structural determinant and a second domain whose fold determines the type of quaternary structure that could adopt PrPSc assemblies.

Co-evolution at protein-protein interfaces guides inference of stoichiometry of oligomeric protein complexes by de novo structure prediction

The quaternary structure with specific stoichiometry is pivotal to the specific function of protein complexes. However, determining the structure of many protein complexes experimentally remains a major bottleneck. Structural bioinformatics approaches, such as the deep learning algorithm Alphafold2-multimer (AF2-multimer), leverage the co-evolution of amino acids and sequence-structure relationships for accurate de novo structure and contact prediction. Pseudo-likelihood maximization direct coupling analysis (plmDCA) has been used to detect co-evolving residue pairs by statistical modeling. Here, we provide evidence that combining both methods can be used for de novo prediction of the quaternary structure and stoichiometry of a protein complex. We achieve this by augmenting the existing AF2-multimer confidence metrics with an interpretable score to identify the complex with an optimal fraction of native contacts of co-evolving residue pairs at intermolecular interfaces. We use this strategy to predict the quaternary structure and non-trivial stoichiometries of Bacillus subtilis spore germination protein complexes with unknown structures. Co-evolution at intermolecular interfaces may therefore synergize with AI-based de novo quaternary structure prediction of structurally uncharacterized bacterial protein complexes.

Recent advances on the construction of long-wavelength emissive supramolecular coordination complexes for photo-diagnosis and therapy

Recently, metal-based drugs have attracted relentless interest in the biomedical field. However, their short excitation/emission wavelengths and unsatisfactory therapeutic efficiency limit their biological applications in vivo. Currently, the second near-infrared window (NIR-II, 1000-1700 nm) provides more accurate imaging and therapeutic options. Thus, there has been a constant focus on developing multifunctional NIR metal agents for imaging and therapy that have deeper tissue penetration. Fortunately, supramolecular coordination complexes (SCCs) formed by the coordination-driven self-assembly of NIR-II emissive ligands can address the above issues. Importantly, metal receptors with chemotherapeutic properties in SCCs can bind to luminescent ligands, thus becoming a versatile therapeutic platform for chemotherapy, imaging and phototherapy. In this context, we systematically summarize the evolution of NIR-II emissive SCCs for biomedical applications and discuss future challenges and prospects.

Diacylglycerol-dependent hexamers of the SNARE-assembling chaperone Munc13-1 cooperatively bind vesicles

Munc13-1 is essential for vesicle docking and fusion at the active zone of synapses. Here, we report that Munc13-1 self-assembles into molecular clusters within diacylglycerol-rich microdomains present in phospholipid bilayers. Although the copy number of Munc13-1 molecules in these clusters has a broad distribution, a systematic Poisson analysis shows that this is most likely the result of two molecular species: monomers and mainly hexameric oligomers. Each oligomer is able to capture one vesicle independently. Hexamers have also been observed in crystals of Munc13-1 that form between opposed phospholipid bilayers [K. Grushin, R. V. Kalyana Sundaram, C. V. Sindelar, J. E. Rothman, Proc. Natl. Acad. Sci. U.S.A. 119, e2121259119 (2022)]. Mutations targeting the contacts stabilizing the crystallographic hexagons also disrupt the isolated hexamers, suggesting they are identical. Additionally, these mutations also convert vesicle binding from a cooperative to progressive mode. Our study provides an independent approach showing that Munc13-1 can form mainly hexamers on lipid bilayers each capable of vesicle capture.

Recent Advances in the Development of Biomimetic Materials

In this review, we focused on recent efforts in the design and development of materials with biomimetic properties. Innovative methods promise to emulate cell microenvironments and tissue functions, but many aspects regarding cellular communication, motility, and responsiveness remain to be explained. We photographed the state-of-the-art advancements in biomimetics, and discussed the complexity of a "bottom-up" artificial construction of living systems, with particular highlights on hydrogels, collagen-based composites, surface modifications, and three-dimensional (3D) bioprinting applications. Fast-paced 3D printing and artificial intelligence, nevertheless, collide with reality: How difficult can it be to build reproducible biomimetic materials at a real scale in line with the complexity of living systems? Nowadays, science is in urgent need of bioengineering technologies for the practical use of bioinspired and biomimetics for medicine and clinics.

Discovering optimal kinetic pathways for self-assembly using automatic differentiation

During self-assembly of macromolecules ranging from ribosomes to viral capsids, the formation of long-lived intermediates or kinetic traps can dramatically reduce yield of the functional products. Understanding biological mechanisms for avoiding traps and efficiently assembling is essential for designing synthetic assembly systems, but learning optimal solutions requires numerical searches in high-dimensional parameter spaces. Here, we exploit powerful automatic differentiation algorithms commonly employed by deep learning frameworks to optimize physical models of reversible self-assembly, discovering diverse solutions in the space of rate constants for 3-7 subunit complexes. We define two biologically-inspired protocols that prevent kinetic trapping through either internal design of subunit binding kinetics or external design of subunit titration in time. Our third protocol acts to recycle intermediates, mimicking energy-consuming enzymes. Preventative solutions via interface design are the most efficient and scale better with more subunits, but external control via titration or recycling are effective even for poorly evolved binding kinetics. Whilst all protocols can produce good solutions, diverse subunits always helps; these complexes access more efficient solutions when following external control protocols, and are simpler to design for internal control, as molecular interfaces do not need modification during assembly given sufficient variation in dimerization rates. Our results identify universal scaling in the cost of kinetic trapping, and provide multiple strategies for eliminating trapping and maximizing assembly yield across large parameter spaces.

The sharp structural switch of covalent cages mediated by subtle variation of directing groups

It is considered a more formidable task to precisely control the self-assembled products containing purely covalent components, due to a lack of intrinsic templates such as transition metals to suppress entropy loss during self-assembly. Here, we attempt to tackle this challenge by using directing groups. That is, the self-assembly products of condensing a 1:2 mixture of a tetraformyl and a biamine can be precisely controlled by slightly changing the substituent groups in the aldehyde precursor. This is because different directing groups provide hydrogen bonds with different modes to the adjacent imine units, so that the building blocks are endowed with totally different conformations. Each conformation favors the formation of a specific product that is thus produced selectively, including chiral and achiral cages. These results of using a specific directing group to favor a target product pave the way for accomplishing atom economy in synthesizing purely covalent molecules without relying on toxic transition metal templates.

Screening Libraries to Discover Molecular Design Principles for the Targeted Delivery of mRNA with One-Component Ionizable Amphiphilic Janus Dendrimers Derived from Plant Phenolic Acids

Viral and synthetic vectors to deliver nucleic acids were key to the rapid development of extraordinarily efficient COVID-19 vaccines. The four-component lipid nanoparticles (LNPs), containing phospholipids, PEG-conjugated lipids, cholesterol, and ionizable lipids, co-assembled with mRNA via a microfluidic technology, are the leading nonviral delivery vector used by BioNTech/Pfizer and Moderna to access COVID-19 mRNA vaccines. LNPs exhibit a statistical distribution of their four components when delivering mRNA. Here, we report a methodology that involves screening libraries to discover the molecular design principles required to realize organ-targeted mRNA delivery and mediate activity with a one-component ionizable multifunctional amphiphilic Janus dendrimer (IAJD) derived from plant phenolic acids. IAJDs co-assemble with mRNA into monodisperse dendrimersome nanoparticles (DNPs) with predictable dimensions, via the simple injection of their ethanol solution in a buffer. The precise location of the functional groups in one-component IAJDs demonstrated that the targeted organs, including the liver, spleen, lymph nodes, and lung, are selected based on the hydrophilic region, while activity is associated with the hydrophobic domain of IAJDs. These principles, and a mechanistic hypothesis to explain activity, simplify the synthesis of IAJDs, the assembly of DNPs, handling, and storage of vaccines, and reduce price, despite employing renewable plant starting materials. Using simple molecular design principles will lead to increased accessibility to a large diversity of mRNA-based vaccines and nanotherapeutics.

Head or tail? A molecular dynamics approach to the complex structure of TNF-associated factor TRAF2

Tumor necrosis factor receptor-associated factor proteins (TRAFs) are trimeric proteins that play a fundamental role in signaling, acting as intermediaries between the tumor necrosis factor (TNF) receptors and the proteins that transmit the downstream signal. The monomeric subunits of all the TRAF family members share a common tridimensional structure: a C-terminal globular domain and a long coiled-coil tail characterizing the N-terminal section. In this study, the dependence of the TRAF2 dynamics on the length of its tail was analyzed in silico. In particular, we used the available crystallographic structure of a C-terminal fragment of TRAF2 (168 out of 501 a.a.), TRAF2-C, and that of a longer construct, addressed as TRAF2-plus, that we have re-constructed using the AlphaFold2 code. The results indicate that the longer N-terminal tail of TRAF2-plus has a strong influence on the dynamics of the globular regions in the protein C-terminal head. In fact, the quaternary interactions among the TRAF2-C subunits change asymmetrically in time, while the movements of TRAF2-plus monomers are rather limited and more ordered than those of the shorter construct. Such findings shed a new light on the dynamics of TRAF subunits and on the protein mechanism in vivo, since TRAF monomer-trimer equilibrium is crucial for several reasons (receptor recognition, membrane binding, hetero-oligomerization).

Modular Nucleic Acid Scaffolds for Synthesizing Monodisperse and Sequence-Encoded Antibody Oligomers

Synthesizing protein oligomers that contain exact numbers of multiple different proteins in defined architectures is challenging. DNA-DNA interactions can be used to program protein assembly into oligomers; however, existing methods require changes to DNA design to achieve different numbers and oligomeric sequences of proteins. Herein, we develop a modular DNA scaffold that uses only six synthetic oligonucleotides to organize proteins into defined oligomers. As a proof-of-concept, model proteins (antibodies) are oligomerized into dimers and trimers, where antibody function is retained. Illustrating the modularity of this technique, dimer and trimer building blocks are then assembled into pentamers containing three different antibodies in an exact stoichiometry and oligomeric sequence. In sum, this report describes a generalizable method for organizing proteins into monodisperse, sequence-encoded oligomers using DNA. This advance will enable studies into how oligomeric protein sequences affect material properties in areas spanning pharmaceutical development, cascade catalysis, synthetic photosynthesis, and membrane transport.

Density-tunable pathway complexity in a minimalistic self-assembly model

An open challenge in self-assembly is learning how to design systems that can be conditionally guided towards different target structures depending on externally-controlled conditions. Using a theoretical and numerical approach, here we discuss a minimalistic self-assembly model that can be steered towards different types of ordered constructs at the equilibrium by solely tuning a facile selection parameter, namely the density of building blocks. Metadynamics and Langevin dynamics simulations allow us to explore the behavior of the system in and out of equilibrium conditions. We show that the density-driven tunability is encoded in the pathway complexity of the system, and specifically in the competition between two different main self-assembly routes. A comprehensive set of simulations provides insight into key factors allowing to make one self-assembling pathway prevailing on the other (or vice versa), determining the selection of the final self-assembled products. We formulate and validate a practical criterion for checking whether a specific molecular design is predisposed for such density-driven tunability of the products, thus offering a new, broader perspective to realize and harness this facile extrinsic control of conditional self-assembly.

Simple mechanisms for the evolution of protein complexity

Proteins are tiny models of biological complexity: specific interactions among their many amino acids cause proteins to fold into elaborate structures, assemble with other proteins into higher-order complexes, and change their functions and structures upon binding other molecules. These complex features are classically thought to evolve via long and gradual trajectories driven by persistent natural selection. But a growing body of evidence from biochemistry, protein engineering, and molecular evolution shows that naturally occurring proteins often exist at or near the genetic edge of multimerization, allostery, and even new folds, so just one or a few mutations can trigger acquisition of these properties. These sudden transitions can occur because many of the physical properties that underlie these features are present in simpler proteins as fortuitous by-products of their architecture. Moreover, complex features of proteins can be encoded by huge arrays of sequences, so they are accessible from many different starting points via many possible paths. Because the bridges to these features are both short and numerous, random chance can join selection as a key factor in explaining the evolution of molecular complexity.

Hallucinating symmetric protein assemblies

Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of seven designs are very similar to the computational models (median root mean square deviation: 0.6 angstroms), as are three cryo-electron microscopy structures of giant 10-nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning and pave the way for the design of increasingly complex components for nanomachines and biomaterials.

Understanding Supramolecular Assembly of Supercharged Proteins

Ordered supramolecular assemblies have recently been created using electrostatic interactions between oppositely charged proteins. Despite recent progress, the fundamental mechanisms governing the assembly of oppositely supercharged proteins are not fully understood. Here, we use a combination of experiments and computational modeling to systematically study the supramolecular assembly process for a series of oppositely supercharged green fluorescent protein variants. We show that net charge is a sufficient molecular descriptor to predict the interaction fate of oppositely charged proteins under a given set of solution conditions (e.g., ionic strength), but the assembled supramolecular structures critically depend on surface charge distributions. Interestingly, our results show that a large excess of charge is necessary to nucleate assembly and that charged residues not directly involved in interprotein interactions contribute to a substantial fraction (∼30%) of the interaction energy between oppositely charged proteins via long-range electrostatic interactions. Dynamic subunit exchange experiments further show that relatively small, 16-subunit assemblies of oppositely charged proteins have kinetic lifetimes on the order of ∼10-40 min, which is governed by protein composition and solution conditions. Broadly, our results inform how protein supercharging can be used to create different ordered supramolecular assemblies from a single parent protein building block.

Slow Evolution toward “Super-Aggregation” of the Oligomers Formed through the Swapping of RNase A N-Termini: A Wish for Amyloidosis?

Natively monomeric RNase A can oligomerize upon lyophilization from 40% acetic acid solutions or when it is heated at high concentrations in various solvents. In this way, it produces many dimeric or oligomeric conformers through the three-dimensional domain swapping (3D-DS) mechanism involving both RNase A N- or/and C-termini. Here, we found many of these oligomers evolving toward not negligible amounts of large derivatives after being stored for up to 15 months at 4 °C in phosphate buffer. We call these species super-aggregates (SAs). Notably, SAs do not originate from native RNase A monomer or from oligomers characterized by the exclusive presence of the C-terminus swapping of the enzyme subunits as well. Instead, the swapping of at least two subunits’ N-termini is mandatory to produce them. Through immunoblotting, SAs are confirmed to derive from RNase A even if they retain only low ribonucleolytic activity. Then, their interaction registered with Thioflavin-T (ThT), in addition to TEM analyses, indicate SAs are large and circular but not “amyloid-like” derivatives. This confirms that RNase A acts as an “auto-chaperone”, although it displays many amyloid-prone short segments, including the 16–22 loop included in its N-terminus. Therefore, we hypothesize the opening of RNase A N-terminus, and hence its oligomerization through 3D-DS, may represent a preliminary step favoring massive RNase A aggregation. Interestingly, this process is slow and requires low temperatures to limit the concomitant oligomers’ dissociation to the native monomer. These data and the hypothesis proposed are discussed in the light of protein aggregation in general, and of possible future applications to contrast amyloidosis.

Direct observation of the molecular mechanism underlying protein polymerization

Protein assembly is a main route to generating complexity in living systems. Revealing the relevant molecular details is challenging because of the intrinsic heterogeneity of species ranging from few to hundreds of molecules. Here, we use mass photometry to quantify and monitor the full range of actin oligomers during polymerization with single-molecule sensitivity. We find that traditional nucleation-based models cannot account for the observed distributions of actin oligomers. Instead, the key step of filament formation is a slow transition between distinct states of an actin filament mediated by cation exchange or ATP hydrolysis. The resulting model reproduces important aspects of actin polymerization, such as the critical concentration for filament formation and bulk growth behavior. Our results revise the mechanism of actin nucleation, shed light on the role and function of actin-associated proteins, and introduce a general and quantitative means to studying protein assembly at the molecular level.

Large protein complex interfaces have evolved to promote cotranslational assembly

Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

Designing Protease-Triggered Protein Cages

Proteins that self-assemble into enclosed polyhedral cages, both naturally and by design, are garnering attention for their prospective utility in the fields of medicine and biotechnology. Notably, their potential for encapsulation and surface display are attractive for experiments that require protection and targeted delivery of cargo. The ability to control their opening or disassembly would greatly advance the development of protein nanocages into widespread molecular tools. Toward the development of protein cages that disassemble in a systematic manner and in response to biologically relevant stimuli, here we demonstrate a modular protein cage system that is opened by highly sequence-specific proteases, based on sequence insertions at strategically chosen loop positions in the protein cage subunits. We probed the generality of the approach in the context of protein cages built using the two prevailing methods of construction: genetic fusion between oligomeric components and (non-covalent) computational interface design between oligomeric components. Our results suggest that the former type of cage may be more amenable than the latter for endowing proteolytically controlled disassembly. We show that a successfully designed cage system, based on oligomeric fusion, is modular with regard to its triggering protease. One version of the cage is targeted by an asparagine protease implicated in cancer and Alzheimer's disease, whereas the second version is responsive to the blood-clotting protease, thrombin. The approach demonstrated here should guide future efforts to develop therapeutic vectors to treat disease states where protease induction or mis-regulation occurs.

Evolution of homo-oligomerization of methionine S-adenosyltransferases is replete with structure-function constrains

Homomers are prevalent in bacterial proteomes, particularly among core metabolic enzymes. Homomerization is often key to function and regulation, and interfaces that facilitate the formation of homomeric enzymes are subject to intense evolutionary change. However, our understanding of the molecular mechanisms that drive evolutionary variation in homomeric complexes is still lacking. How is the diversification of protein interfaces linked to variation in functional regulation and structural integrity of homomeric complexes? To address this question, we studied quaternary structure evolution of bacterial methionine S‐adenosyltransferases (MATs)—dihedral homotetramers formed along a large and conserved dimeric interface harboring two active sites, and a small, recently evolved, interdimeric interface. Here, we show that diversity in the physicochemical properties of small interfaces is directly linked to variability in the kinetic stability of MAT quaternary complexes and in modes of their functional regulation. Specifically, hydrophobic interactions within the small interface of Escherichia coli MAT render the functional homotetramer kinetically stable yet impose severe aggregation constraints on complex assembly. These constraints are alleviated by electrostatic interactions that accelerate dimer‐dimer assembly. In contrast, Neisseria gonorrhoeae MAT adopts a nonfunctional dimeric state due to the low hydrophobicity of its small interface and the high flexibility of its active site loops, which perturbs small interface integrity. Remarkably, in the presence of methionine and ATP, N. gonorrhoeae MAT undergoes substrate‐induced assembly into a functional tetrameric state. We suggest that evolution acts on the interdimeric interfaces of MATs to tailor the regulation of their activity and stability to unique organismal needs.

PDB Code(s): 7R2W;7R3B;

Shape Complementary Coordination Self-Assembly of a Redox-Active Heteroleptic Complex

We present here the coordination self-assembly of a new heteroleptic (bpyPd)₄L¹L₂² coordination complex (1) from one novel pyridinium-functionalized bis-2,4,6-tris(pyridin-3-yl)-1,3,5-triazine (bis-3-TPT, L¹) macrocyclic ligand, two separate 3-TPT (L²) ligands, and four cis-blocking bpyPd(NO₃)₂ (bpy = 2,2'-bipyridine). While homoleptic self-assemblies with either L¹ or L² gave dynamic mixtures of products, a single thermodynamic heteroleptic complex was obtained driven by the shape complementarity of building blocks. Moreover, the redox-active nature of the heteroleptic assembly facilitates the highly efficient catalytic aerobic photo-oxidation of aromatic secondary alcohols under mild conditions.

Native Mass Spectrometry: Recent Progress and Remaining Challenges

Native mass spectrometry (nMS) has emerged as an important tool in studying the structure and function of macromolecules and their complexes in the gas phase. In this review, we cover recent advances in nMS and related techniques including sample preparation, instrumentation, activation methods, and data analysis software. These advances have enabled nMS-based techniques to address a variety of challenging questions in structural biology. The second half of this review highlights recent applications of these technologies and surveys the classes of complexes that can be studied with nMS. Complementarity of nMS to existing structural biology techniques and current challenges in nMS are also addressed.

Surface-induced Dissociation Mass Spectrometry as a Structural Biology Tool

Native mass spectrometry (nMS) is evolving into a workhorse for structural biology. The plethora of online and offline preparation, separation, and purification methods as well as numerous ionization techniques combined with powerful new hybrid ion mobility and mass spectrometry systems has illustrated the great potential of nMS for structural biology. Fundamental to the progression of nMS has been the development of novel activation methods for dissociating proteins and protein complexes to deduce primary, secondary, tertiary, and quaternary structure through the combined use of multiple MS/MS technologies. This review highlights the key features and advantages of surface collisions (surface-induced dissociation, SID) for probing the connectivity of subunits within protein and nucleoprotein complexes and, in particular, for solving protein structure in conjunction with complementary techniques such as cryo-EM and computational modeling. Several case studies highlight the significant role SID, and more generally nMS, will play in structural elucidation of biological assemblies in the future as the technology becomes more widely adopted. Cases are presented where SID agrees with solved crystal or cryoEM structures or provides connectivity maps that are otherwise inaccessible by "gold standard" structural biology techniques.

Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution

SignificanceWhy does evolution favor symmetric structures when they only represent a minute subset of all possible forms? Just as monkeys randomly typing into a computer language will preferentially produce outputs that can be generated by shorter algorithms, so the coding theorem from algorithmic information theory predicts that random mutations, when decoded by the process of development, preferentially produce phenotypes with shorter algorithmic descriptions. Since symmetric structures need less information to encode, they are much more likely to appear as potential variation. Combined with an arrival-of-the-frequent mechanism, this algorithmic bias predicts a much higher prevalence of low-complexity (high-symmetry) phenotypes than follows from natural selection alone and also explains patterns observed in protein complexes, RNA secondary structures, and a gene regulatory network.

The Unexpected Importance of the Primary Structure of the Hydrophobic Part of One-Component Ionizable Amphiphilic Janus Dendrimers in Targeted mRNA Delivery Activity

Viral and synthetic vectors for delivery of nucleic acids impacted genetic nanomedicine by aiding the rapid development of the extraordinarily efficient Covid-19 vaccines. Access to targeted delivery of nucleic acids is expected to expand the field of nanomedicine beyond most expectations. Both viral and synthetic vectors have advantages and disadvantages. The major advantage of the synthetic vectors is their unlimited synthetic capability. The four-component lipid nanoparticles (LNPs) are the leading nonviral vector for mRNA used by Pfizer and Moderna in Covid-19 vaccines. Their synthetic capacity inspired us to develop a one-component multifunctional sequence-defined ionizable amphiphilic Janus dendrimer (IAJD) delivery system for mRNA. The first experiments on IAJDs provided, through a rational-library design combined with orthogonal-modular accelerated synthesis and sequence control in their hydrophilic part, some of the most active synthetic vectors for the delivery of mRNA to lung. The second experiments employed a similar strategy, generating, by a less complex hydrophilic structure, a library of IAJDs targeting spleen, liver, and lung. Here, we report preliminary studies designing the hydrophobic region of IAJDs by using dissimilar alkyl lengths and demonstrate the unexpectedly important role of the primary structure of the hydrophobic part of IAJDs by increasing up to 90.2-fold the activity of targeted delivery of mRNA to spleen, lymph nodes, liver, and lung. The principles of the design strategy reported here and in previous publications indicate that IAJDs could have a profound impact on the future of genetic nanomedicine.

The properties of human disease mutations at protein interfaces

The assembly of proteins into complexes and their interactions with other biomolecules are often vital for their biological function. While it is known that mutations at protein interfaces have a high potential to be damaging and cause human genetic disease, there has been relatively little consideration for how this varies between different types of interfaces. Here we investigate the properties of human pathogenic and putatively benign missense variants at homomeric (isologous and heterologous), heteromeric, DNA, RNA and other ligand interfaces, and at different regions in proteins with respect to those interfaces. We find that different types of interfaces vary greatly in their propensity to be associated with pathogenic mutations, with homomeric heterologous and DNA interfaces being particularly enriched in disease. We also find that residues that do not directly participate in an interface, but are close in three-dimensional space, show a significant disease enrichment. Finally, we observe that mutations at different types of interfaces tend to have distinct property changes when undergoing amino acid substitutions associated with disease, and that this is linked to substantial variability in their identification by computational variant effect predictors.

Nearly all proteins interact with other molecules as part of their biological function. For example, proteins can interact with other copies of the same type of protein, with different proteins, with DNA, or with small ligand molecules. Many mutations at protein interfaces, the regions of proteins that interact with other molecules, are known to cause human genetic disease. In this study, we first investigate how different types of protein interfaces have different tendencies to be associated with disease. We also show that the closer a mutation is to an interface, the more likely it is to cause disease. Finally, we study how mutations at different types of interfaces tend to be associated with different changes in amino acid properties, which appears to influence our ability to computationally predict the effects of mutations. Ultimately, we hope that consideration of protein interface properties will eventually improve our ability to identify new disease-causing mutations.

Uncoupling Proteins and Regulated Proton Leak in Mitochondria

Higher concentration of protons in the mitochondrial intermembrane space compared to the matrix results in an electrochemical potential causing the back flux of protons to the matrix. This proton transport can take place through ATP synthase complex (leading to formation of ATP) or can occur via proton transporters of the mitochondrial carrier superfamily and/or membrane lipids. Some mitochondrial proton transporters, such as uncoupling proteins (UCPs), transport protons as their general regulating function; while others are symporters or antiporters, which use the proton gradient as a driving force to co-transport other substrates across the mitochondrial inner membrane (such as phosphate carrier, a symporter; or aspartate/glutamate transporter, an antiporter). Passage (or leakage) of protons across the inner membrane to matrix from any route other than ATP synthase negatively impacts ATP synthesis. The focus of this review is on regulated proton transport by UCPs. Recent findings on the structure and function of UCPs, and the related research methodologies, are also critically reviewed. Due to structural similarity of members of the mitochondrial carrier superfamily, several of the known structural features are potentially expandable to all members. Overall, this report provides a brief, yet comprehensive, overview of the current knowledge in the field.

Carbodiimide-fueled catalytic reaction cycles to regulate supramolecular processes

Using molecular self-assembly, supramolecular chemists can create Gigadalton-structures with angstrom precision held together by non-covalent interactions. However, despite relying on the same molecular toolbox for self-assembly, these synthetic structures lack the complexity and sophistication of biological assemblies. Those assemblies are non-equilibrium structures that rely on the constant consumption of energy transduced from the hydrolysis of chemical fuels like ATP and GTP, which endows them with dynamic properties, e.g., temporal and spatial control and self-healing ability. Thus, to synthesize life-like materials, we have to find a reaction cycle that converts chemical energy to regulate self-assembly. We and others recently found that this can be done by a reaction cycle that hydrates carbodiimides. This feature article aims to provide an overview of how the energy transduced from carbodiimide hydration can alter the function of molecules and regulate molecular assemblies. The goal is to offer the reader design considerations for carbodiimide-driven reaction cycles to create a desired morphology or function of the assembly and ultimately to push chemically fueled self-assembly further towards the bottom-up synthesis of life.

Contact-Based Analysis of Aggregation of Intrinsically Disordered Proteins

We review the contact-based description of aggregation of intrinsically disordered proteins in coarse-grained and all-atom models. We consider polyglutamines and polyalanines at various concentrations of the peptides. We also study associations of two chains of α-synuclein and up to 20 chains of a 12-residue-long segment of protein tau. We demonstrate that the total number of two-chain association events (in an aggregate that comprises at least two chains) provides a useful measure of the propensity to aggregate. This measure is consistent, for instance, with the previously reported mass spectroscopy data. The distribution of the number of association events is given essentially by a power law as a function of the duration of these events. The corresponding exponent depends on the protein and the temperature but not on the concentration of the proteins.

Protein Assembly by Design

Proteins are nature's primary building blocks for the construction of sophisticated molecular machines and dynamic materials, ranging from protein complexes such as photosystem II and nitrogenase that drive biogeochemical cycles to cytoskeletal assemblies and muscle fibers for motion. Such natural systems have inspired extensive efforts in the rational design of artificial protein assemblies in the last two decades. As molecular building blocks, proteins are highly complex, in terms of both their three-dimensional structures and chemical compositions. To enable control over the self-assembly of such complex molecules, scientists have devised many creative strategies by combining tools and principles of experimental and computational biophysics, supramolecular chemistry, inorganic chemistry, materials science, and polymer chemistry, among others. Owing to these innovative strategies, what started as a purely structure-building exercise two decades ago has, in short order, led to artificial protein assemblies with unprecedented structures and functions and protein-based materials with unusual properties. Our goal in this review is to give an overview of this exciting and highly interdisciplinary area of research, first outlining the design strategies and tools that have been devised for controlling protein self-assembly, then describing the diverse structures of artificial protein assemblies, and finally highlighting the emergent properties and functions of these assemblies.

How Blinking Affects Photon Correlations in Multichromophoric Nanoparticles

A single chromophore can only emit a maximum of one single photon per excitation cycle. This limitation results in a phenomenon commonly referred to as photon antibunching (pAB). When multiple chromophores contribute to the fluorescence measured, the degree of pAB has been used as a metric to "count" the number of chromophores. But the fact that chromophores can switch randomly between bright and dark states also impacts pAB and can lead to incorrect chromophore numbers being determined from pAB measurements. By both simulations and experiment, we demonstrate how pAB is affected by independent and collective chromophore blinking, enabling us to formulate universal guidelines for correct interpretation of pAB measurements. We use DNA-origami nanostructures to design multichromophoric model systems that exhibit either independent or collective chromophore blinking. Two approaches are presented that can distinguish experimentally between these two blinking mechanisms. The first one utilizes the different excitation intensity dependence on the blinking mechanisms. The second approach exploits the fact that collective blinking implies energy transfer to a quenching moiety, which is a time-dependent process. In pulsed-excitation experiments, the degree of collective blinking can therefore be altered by time gating the fluorescence photon stream, enabling us to extract the energy-transfer rate to a quencher. The ability to distinguish between different blinking mechanisms is valuable in materials science, such as for multichromophoric nanoparticles like conjugated-polymer chains as well as in biophysics, for example, for quantitative analysis of protein assemblies by counting chromophores.

Tracing protein and proteome history with chronologies and networks: folding recapitulates evolution

INTRODUCTION

While the origin and evolution of proteins remain mysterious, advances in evolutionary genomics and systems biology are facilitating the historical exploration of the structure, function and organization of proteins and proteomes. Molecular chronologies are series of time events describing the history of biological systems and subsystems and the rise of biological innovations. Together with time-varying networks, these chronologies provide a window into the past.

AREAS COVERED

Here, we review molecular chronologies and networks built with modern methods of phylogeny reconstruction. We discuss how chronologies of structural domain families uncover the explosive emergence of metabolism, the late rise of translation, the co-evolution of ribosomal proteins and rRNA, and the late development of the ribosomal exit tunnel; events that coincided with a tendency to shorten folding time. Evolving networks described the early emergence of domains and a late 'big bang' of domain combinations.

EXPERT OPINION

Two processes, folding and recruitment appear central to the evolutionary progression. The former increases protein persistence. The later fosters diversity. Chronologically, protein evolution mirrors folding by combining supersecondary structures into domains, developing translation machinery to facilitate folding speed and stability, and enhancing structural complexity by establishing long-distance interactions in novel structural and architectural designs.

Photobleaching step analysis for robust determination of protein complex stoichiometries

The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has been significantly improved with more-sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high-quality data. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labeling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated manner.

Nonrefoldability is Pervasive Across the E. coli Proteome

Decades of research on protein folding have primarily focused on a subset of small proteins that can reversibly refold from a denatured state. However, these studies have generally not been representative of the complexity of natural proteomes, which consist of many proteins with complex architectures and domain organizations. Here, we introduce an experimental approach to probe protein refolding kinetics for whole proteomes using mass spectrometry-based proteomics. Our study covers the majority of the soluble E. coli proteome expressed during log-phase growth, and among this group, we find that one-third of the E. coli proteome is not intrinsically refoldable on physiological time scales, a cohort that is enriched with certain fold-types, domain organizations, and other biophysical features. We also identify several properties and fold-types that are correlated with slow refolding on the minute time scale. Hence, these results illuminate when exogenous factors and processes, such as chaperones or cotranslational folding, might be required for efficient protein folding.

Structure and mechanistic features of the prokaryotic minimal RNase P

Endonucleolytic removal of 5'-leader sequences from tRNA precursor transcripts (pre-tRNAs) by ribonuclease P (RNase P) is essential for protein synthesis. Beyond RNA-based RNase P enzymes, protein-only versions of the enzyme exert this function in various eukarya (there termed PRORPs) and in some bacteria (Aquifex aeolicus and close relatives); both enzyme types belong to distinct subgroups of the PIN domain metallonuclease superfamily. Homologs of Aquifex RNase P (HARPs) are also expressed in some other bacteria and many archaea, where they coexist with RNA-based RNase P and do not represent the main RNase P activity. Here, we solved the structure of the bacterial HARP from Halorhodospira halophila by cryo-electron microscopy, revealing a novel screw-like dodecameric assembly. Biochemical experiments demonstrate that oligomerization is required for RNase P activity of HARPs. We propose that the tRNA substrate binds to an extended spike-helix (SH) domain that protrudes from the screw-like assembly to position the 5'-end in close proximity to the active site of the neighboring dimer. The structure suggests that eukaryotic PRORPs and prokaryotic HARPs recognize the same structural elements of pre-tRNAs (tRNA elbow region and cleavage site). Our analysis thus delivers the structural and mechanistic basis for pre-tRNA processing by the prokaryotic HARP system.

Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction

The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template‐based modeling and free docking. Structural templates were identified using sensitive sequence‐based searches. If sequence‐based searches failed, we performed structure‐based template searches using selected CASP server models. In the absence of reliable templates we applied free docking starting from monomers generated by CASP servers. We evaluated and ranked models of protein complexes using an improved version of our protein structure quality assessment method, VoroMQA, taking into account both interaction interface and global structure scores. If reliable templates could be identified, generally accurate models of protein assemblies were generated with the exception of an antibody‐antigen interaction. The success of free docking mainly depended on the accuracy of initial subunit models and on the scoring of docking solutions. To put our overall results in perspective, we analyzed our performance in the context of other CASP groups. Although the subunits in our assembly models often were not of the top quality, these models had, overall, the best‐predicted intersubunit interfaces according to several accuracy measures. We attribute our relative success primarily to the emphasis on the interaction interface when modeling and scoring.

The Odd Faces of Oligomers: The Case of TRAF2-C, A Trimeric C-Terminal Domain of TNF Receptor-Associated Factor

TNF Receptor Associated Factor 2 (TRAF2) is a trimeric protein that belongs to the TNF receptor associated factor family (TRAFs). The TRAF2 oligomeric state is crucial for receptor binding and for its interaction with other proteins involved in the TNFR signaling. The monomer-trimer equilibrium of a C- terminal domain truncated form of TRAF2 (TRAF2-C), plays also a relevant role in binding the membrane, causing inward vesiculation. In this study, we have investigated the conformational dynamics of TRAF2-C through circular dichroism, fluorescence, and dynamic light scattering, performing temperature-dependent measurements. The data indicate that the protein retains its oligomeric state and most of its secondary structure, while displaying a significative increase in the heterogeneity of the tyrosines signal, increasing the temperature from ≈15 to ≈35 °C. The peculiar crowding of tyrosine residues (12 out of 18) at the three subunit interfaces and the strong dependence on the trimer concentration indicate that such conformational changes mainly involve the contact areas between each pair of monomers, affecting the oligomeric state. Molecular dynamic simulations in this temperature range suggest that the interfaces heterogeneity is an intrinsic property of the trimer that arises from the continuous, asymmetric approaching and distancing of its subunits. Such dynamics affect the results of molecular docking on the external protein surface using receptor peptides, indicating that the TRAF2-receptor interaction in the solution might not involve three subunits at the same time, as suggested by the static analysis obtainable from the crystal structure. These findings shed new light on the role that the TRAF2 oligomeric state might have in regulating the protein binding activity in vivo.

Analysing the yeast complexome-the Complex Portal rising to the challenge

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.

Time-dependent communication between multiple amino acids during protein folding

Cooperativity is considered to be a key organizing principle behind biomolecular assembly, recognition and folding. However, it has remained very challenging to quantitatively characterize how cooperative processes occur on a concerted, multiple-interaction basis. Here, we address how and when the folding process is cooperative on a molecular scale. To this end, we analyze multipoint time-correlation functions probing time-dependent communication between multiple amino acids, which were computed from long folding simulation trajectories. We find that the simultaneous multiple amino-acid contact formation, which is absent in the unfolded state, starts to develop only upon entering the folding transition path. Interestingly, the transition state, whose presence is connected to the macrostate cooperative behavior known as the two-state folding, can be identified as the state in which the amino-acid cooperativity is maximal. Thus, our work not only provides a new mechanistic view on how protein folding proceeds on a multiple-interaction basis, but also offers a conceptually novel characterization of the folding transition state and the molecular origin of the phenomenological cooperative folding behavior. Moreover, the multipoint correlation function approach adopted here is general and can be used to expand the understanding of cooperative processes in complex chemical and biomolecular systems.

Cooperativity in contact formation among multiple amino acids starts to develop upon entering the folding transition path and attains a maximum at the folding transition state, providing the molecular origin of the two-state folding behavior.

Label-free, mass-sensitive single-molecule imaging using interferometric scattering microscopy

Single-molecule imaging has mostly been restricted to the use of fluorescence labelling as a contrast mechanism due to its superior ability to visualise molecules of interest on top of an overwhelming background of other molecules. Recently, interferometric scattering (iSCAT) microscopy has demonstrated the detection and imaging of single biomolecules based on light scattering without the need for fluorescent labels. Significant improvements in measurement sensitivity combined with a dependence of scattering signal on object size have led to the development of mass photometry, a technique that measures the mass of individual molecules and thereby determines mass distributions of biomolecule samples in solution. The experimental simplicity of mass photometry makes it a powerful tool to analyse biomolecular equilibria quantitatively with low sample consumption within minutes. When used for label-free imaging of reconstituted or cellular systems, the strict size-dependence of the iSCAT signal enables quantitative measurements of processes at size scales reaching from single-molecule observations during complex assembly up to mesoscopic dynamics of cellular components and extracellular protrusions. In this review, I would like to introduce the principles of this emerging imaging technology and discuss examples that show how mass-sensitive iSCAT can be used as a strong complement to other routine techniques in biochemistry.

Targeting protein self-association in drug design

Protein self-association is a universal phenomenon essential for stability and molecular recognition. Disrupting constitutive homomers constitutes an original and emerging strategy in drug design. Inhibition of homomeric proteins can be achieved through direct complex disruption, subunit intercalation, or by promoting inactive oligomeric states. Targeting self-interaction grants several advantages over active site inhibition because of the stimulation of protein degradation, the enhancement of selectivity, substoichiometric inhibition, and by-pass of compensatory mechanisms. This new landscape in protein inhibition is driven by the development of biophysical and biochemical tools suited for the study of homomeric proteins, such as differential scanning fluorimetry (DSF), native mass spectrometry (MS), Förster resonance energy transfer (FRET) spectroscopy, 2D nuclear magnetic resonance (NMR), and X-ray crystallography. In this review, we discuss the different aspects of this new paradigm in drug design.

Reprogramming the Specificity of a Protein Interface by Computational and Data-Driven Design

The formation of specific protein complexes in a cell is a non-trivial problem given the co-existence of thousands of different polypeptide chains. A particularly difficult case are two glutamine amidotransferase complexes (anthranilate synthase [AS] and aminodeoxychorismate synthase [ADCS]), which are composed of homologous pairs of synthase and glutaminase subunits. We have attempted to identify discriminating interface residues of the glutaminase subunit TrpG from AS, which are responsible for its specific interaction with the synthase subunit TrpEx and prevent binding to the closely related synthase subunit PabB from ADCS. For this purpose, TrpG-specific interface residues were grafted into the glutaminase subunit PabA from ADCS by two different approaches, namely a computational and a data-driven one. Both approaches resulted in PabA variants that bound TrpEx with higher affinity than PabB. Hence, we have accomplished a reprogramming of protein-protein interaction specificity that provides insights into the evolutionary adaptation of protein interfaces.