Dynamic allostery: linkers are not merely flexible

Leveraging Bidirectional Nature of Allostery To Inhibit Protein-Protein Interactions (PPIs): A Case Study of PCSK9-LDLR Interaction

The protein PCSK9 (proprotein convertase subtilisin/Kexin type 9) negatively regulates the recycling of LDLR (low-density lipoprotein receptor), leading to an elevated plasma level of LDL. Inhibition of PCSK9-LDLR interaction has emerged as a promising therapeutic strategy to manage hypercholesterolemia. However, the large interaction surface area between PCSK9 and LDLR makes it challenging to identify a small molecule competitive inhibitor. An alternative strategy would be to identify distal cryptic sites as targets for allosteric inhibitors that can remotely modulate PCSK9-LDLR interaction. Using several microseconds long molecular dynamics (MD) simulations, we demonstrate that on binding with LDLR, there is a significant conformational change (population shift) in a distal loop (residues 211-222) region of PCSK9. Consistent with the bidirectional nature of allostery, we establish a clear correlation between the loop conformation and the binding affinity with LDLR. Using a thermodynamic argument, we establish that the loop conformations predominantly present in the apo state of PCSK9 would have lower LDLR binding affinity, and they would be potential targets for designing allosteric inhibitors. We elucidate the molecular origin of the allosteric coupling between this loop and the LDLR binding interface in terms of the population shift in a set of salt bridges and hydrogen bonds. Overall, our work provides a general strategy toward identifying allosteric hotspots: compare the conformational ensemble of the receptor between the apo and bound states of the protein and identify distal conformational changes, if any. The inhibitors should be designed to bind and stabilize the apo-specific conformations.

Glycosylation of cellulase: a novel strategy for improving cellulase

Protein glycosylation is the most complex posttranslational modification process. Most cellulases from filamentous fungi contain N-glycosylation and O-glycosylation. Here, we discuss the potential roles of glycosylation on the characteristics and function of cellulases. The use of certain cultivation, inducer, and alteration of engineering glycosylation pathway can enable the rational control of cellulase glycosylation. Glycosylation does not occur arbitrarily and may tend to modify the 3D structure of cellulases by using specially distributed glycans. Therefore, glycoengineering should be considered comprehensively along with the spatial structure of cellulases. Cellulase glycosylation may be an evolution phenomenon, which has been considered as an economical way for providing different functions from identical proteins. In addition to gene and transcription regulations, glycosylation may be another regulation on the protein expression level. Enhanced understanding of the potential regulatory role of cellulase glycosylation will enable synthetic biology approaches for the development of commercial cellulase.

MD simulations indicate Omicron P132H of SARS-CoV-2 Mpro is a potential allosteric mutant involved in modulating the dynamics of catalytic site entry loop

The SARS-CoV-2 main protease Mpro, essential for viral replication is an important drug target. It plays a critical role in processing viral polyproteins necessary for viral replication assembly. One of the predominant SARS-CoV-2 Mpro mutations of Omicron variant is Pro132His. Structurally, this mutation site is located ∼22 Å away from the catalytic site. The solved crystal structure of this mutant in complex with inhibitors as well as its reported catalytic efficiency did not show any difference with respect to the wild type. Thus, the mutation was concluded to be non-allosteric. Based on microsecond long MD simulation of the Pro132His mutant and wild type, we show that Pro132His mutation affects the conformational equilibrium with more population of conformational substates having open catalytic site, modulated by the dynamics of the catalytic site entry loop, implying the allosteric nature of this mutation. The structural analysis indicates that rearrangement of hydrogen bonds between His132 and adjacent residues enhances the dynamics of the linker, which in turn is augmented by the inherent dynamic flexibility of the catalytic pocket entry site due to the presence of charged residues. The altered dynamics leading to loss of secondary structures corroborate well with the reported compromised thermal stability.

Subdomain dynamics enable chemical chain reactions in non-ribosomal peptide synthetases

Many peptide-derived natural products are produced by non-ribosomal peptide synthetases (NRPSs) in an assembly-line fashion. Each amino acid is coupled to a designated peptidyl carrier protein (PCP) through two distinct reactions catalysed sequentially by the single active site of the adenylation domain (A-domain). Accumulating evidence suggests that large-amplitude structural changes occur in different NRPS states; yet how these molecular machines orchestrate such biochemical sequences has remained elusive. Here, using single-molecule Förster resonance energy transfer, we show that the A-domain of gramicidin S synthetase I adopts structurally extended and functionally obligatory conformations for alternating between adenylation and thioester-formation structures during enzymatic cycles. Complementary biochemical, computational and small-angle X-ray scattering studies reveal interconversion among these three conformations as intrinsic and hierarchical where intra-A-domain organizations propagate to remodel inter-A-PCP didomain configurations during catalysis. The tight kinetic coupling between structural transitions and enzymatic transformations is quantified, and how the gramicidin S synthetase I A-domain utilizes its inherent conformational dynamics to drive directional biosynthesis with a flexibly linked PCP domain is revealed.

Relation between flexibility and intrinsically disorder regions in thermosensitive TRP channels reveal allosteric effects

How a protein propagates the conformational changes throughout its structure remains largely unknown. In thermosensitive TRP channels, this allosteric communication is triggered by ligand interaction or in response to temperature changes. Because dynamic allostery suggests a dynamic role of disordered regions, in this work we set out to thoroughly evaluate these regions in six thermosensitive TRP channels. Thus, by contrasting the intrinsic flexibility of the transmembrane region as a function of the degree of disorder in those proteins, we discovered several residues that do not show a direct correlation in both parameters. This kind of structural discrepancy revealed residues that are either reported to be dynamic, functionally relevant or are involved in signal propagation and probably part of allosteric networks. These discrepant, potentially dynamic regions are not exclusive of TRP channels, as this same correlation was found in the Kv Shaker channel.

Conformational Distribution of a Multidomain Protein Measured by Single-Pair Small-Angle X-ray Scattering

The difficulty in evaluating the conformational distribution of proteins in solution often hinders mechanistic insights. One possible strategy for visualizing conformational distribution is distance distribution measurement by single-pair small-angle X-ray scattering (SAXS), in which the scattering interference from only a specific pair of atoms in the target molecule is extracted. Despite this promising concept, with few applications in synthetic small molecules and DNA, technical difficulties have prevented its application in protein conformational studies. This study used a synthetic tag to fix the lanthanide ion at desired sites on the protein and used single-pair SAXS with contrast matching to evaluate the conformational distribution of the multidomain protein enzyme MurD. These data highlighted the broad conformational and ligand-driven distribution shifts of MurD in solution. This study proposes an important strategy in solution structural biology that targets dynamic proteins, including multidomain and intrinsically disordered proteins.

Advances of Predicting Allosteric Mechanisms Through Protein Contact in New Technologies and Their Application

Allostery is an intriguing phenomenon wherein the binding activity of a biological macromolecule is modulated via non-canonical binding site, resulting in synchronized functional changes. The mechanics underlying allostery are relatively complex and this review is focused on common methodologies used to study allostery, such as X-ray crystallography, NMR spectroscopy, and HDXMS. Different methodological approaches are used to generate data in different scenarios. For example, X-ray crystallography provides high-resolution structural information, NMR spectroscopy offers dynamic insights into allosteric interactions in solution, and HDXMS provides information on protein dynamics. The residue transition state (RTS) approach has emerged as a critical tool in understanding the energetics and conformational changes associated with allosteric regulation. Allostery has significant implications in drug discovery, gene transcription, disease diagnosis, and enzyme catalysis. Enzymes' catalytic activity can be modulated by allosteric regulation, offering opportunities to develop novel therapeutic alternatives. Understanding allosteric mechanisms associated with infectious organisms like SARS-CoV and bacterial pathogens can aid in the development of new antiviral drugs and antibiotics. Allosteric mechanisms are crucial in the regulation of a variety of signal transduction and cell metabolism pathways, which in turn govern various cellular processes. Despite progress, challenges remain in identifying allosteric sites and characterizing their contribution to a variety of biological processes. Increased understanding of these mechanisms can help develop allosteric systems specifically designed to modulate key biological mechanisms, providing novel opportunities for the development of targeted therapeutics. Therefore, the current review aims to summarize common methodologies that are used to further our understanding of allosteric mechanisms. In conclusion, this review provides insights into the methodologies used for the study of allostery, its applications in in silico modeling, the mechanisms underlying antibody allostery, and the ongoing challenges and prospects in advancing our comprehension of this intriguing phenomenon.

Potential Self-Peptide Inhibitors of the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in viral replication, cleaving viral polyproteins into functional proteins. This makes Mpro an important drug target. Mpro consists of an N-terminal catalytic domain and a C-terminal α-helical domain (MproC). Previous studies have shown that peptides derived from a given protein sequence (self-peptides) can affect the folding and, in turn, the function of that protein. Since the SARS-CoV-1 MproC is known to stabilize its Mpro and regulate its function, we hypothesized that SARS-CoV-2 MproC-derived self-peptides may modulate the folding and the function of SARS-CoV-2 Mpro. To test this, we studied the folding of MproC in the presence of various self-peptides using coarse-grained structure-based models and molecular dynamics simulations. In these simulations of MproC and one self-peptide, we found that two self-peptides, the α1-helix and the loop between α4 and α5 (loop4), could replace the equivalent native sequences in the MproC structure. Replacement of either sequence in full-length Mpro should, in principle, be able to perturb Mpro function albeit through different mechanisms. Some general principles for the rational design of self-peptide inhibitors emerge: The simulations show that prefolded self-peptides are more likely to replace native sequences than those which do not possess structure. Additionally, the α1-helix self-peptide is kinetically stable and once inserted rarely exchanges with the native α1-helix, while the loop4 self-peptide is easily replaced by the native loop4, making it less useful for modulating function. In summary, a prefolded α1-derived peptide should be able to inhibit SARS-CoV-2 Mpro function.

Evidence of variable human Fcγ receptor-Fc affinities across differentially-complexed IgG

Antibody-mediated effector functions are widely considered to unfold according to an associative model of IgG-Fcγ receptor (FcγR) interactions. The associative model presupposes that Fc receptors cannot discriminate antigen-bound IgG from free IgG in solution and have equivalent affinities for each. Therefore, the clustering of Fcγ receptors (FcγR) in the cell membrane, cross-activation of intracellular signaling domains, and the formation of the immune synapse are all the result of avid interactions between the Fc region of IgG and FcγRs that collectively overcome the individually weak, transient interactions between binding partners. Antibody allostery, specifically conformational allostery, is a competing model in which antigen-bound antibody molecules undergo a physical rearrangement that causes them to stand out from the background of free IgG by virtue of greater FcγR affinity. Various evidence exists in support of this model of antibody allostery, but it remains controversial. We report observations from multiplexed, label-free kinetic experiments in which the affinity values of FcγR were characterized for covalently immobilized, captured, and antigen-bound IgG. Across the strategies tested, receptors had greater affinity for the antigen-bound mode of IgG presentation. This phenomenon was observed across multiple FcγRs and generalized to multiple antigens, antibody specificities, and subclasses. Furthermore, the thermodynamic signatures of FcγR binding to free or immune-complexed IgG in solution differed when measured by an orthogonal label-free method, but the failure to recapitulate the trend in overall affinity leaves open questions as to what additional factors may be at play.

Modeling of SARS-CoV-2 Virus Proteins: Implications on Its Proteome

COronaVIrus Disease 19 (COVID-19) is a severe acute respiratory syndrome (SARS) caused by a group of beta coronaviruses, SARS-CoV-2. The SARS-CoV-2 virus is similar to previous SARS- and MERS-causing strains and has infected nearly six hundred and fifty million people all over the globe, while the death toll has crossed the six million mark (as of December, 2022). In this chapter, we look at how computational modeling approaches of the viral proteins could help us understand the various processes in the viral life cycle inside the host, an understanding of which might provide key insights in mitigating this and future threats. This understanding helps us identify key targets for the purpose of drug discovery and vaccine development.

Structure-Based Function and Regulation of NCX Variants: Updates and Challenges

The plasma-membrane homeostasis Na⁺/Ca²⁺ exchangers (NCXs) mediate Ca²⁺ extrusion/entry to dynamically shape Ca²⁺ signaling/in biological systems ranging from bacteria to humans. The NCX gene orthologs, isoforms, and their splice variants are expressed in a tissue-specific manner and exhibit nearly 10⁴-fold differences in the transport rates and regulatory specificities to match the cell-specific requirements. Selective pharmacological targeting of NCX variants could benefit many clinical applications, although this intervention remains challenging, mainly because a full-size structure of eukaryotic NCX is unavailable. The crystal structure of the archaeal NCX_Mj, in conjunction with biophysical, computational, and functional analyses, provided a breakthrough in resolving the ion transport mechanisms. However, NCX_Mj (whose size is nearly three times smaller than that of mammalian NCXs) cannot serve as a structure-dynamic model for imitating high transport rates and regulatory modules possessed by eukaryotic NCXs. The crystal structures of isolated regulatory domains (obtained from eukaryotic NCXs) and their biophysical analyses by SAXS, NMR, FRET, and HDX-MS approaches revealed structure-based variances of regulatory modules. Despite these achievements, it remains unclear how multi-domain interactions can decode and integrate diverse allosteric signals, thereby yielding distinct regulatory outcomes in a given ortholog/isoform/splice variant. This article summarizes the relevant issues from the perspective of future developments.

Mechanistic insights into the nickel-dependent allosteric response of the Helicobacter pylori NikR transcription factor

In Helicobacter pylori, the nickel-responsive NikR transcription factor plays a key role in regulating intracellular nickel concentrations, which is an essential process for survival of this pathogen in the acidic human stomach. Nickel binding to H. pylori NikR (HpNikR) allosterically activates DNA binding to target promoters encoding genes involved in nickel homeostasis and acid adaptation, to either activate or repress their transcription. We previously showed that HpNikR adopts an equilibrium between an open conformation and DNA-binding competent cis and trans states. Nickel binding slows down conformational exchange between these states and shifts the equilibrium toward the binding-competent states. The protein then becomes stabilized in a cis conformation upon binding the ureA promoter. Here, we investigate how nickel binding creates this response and how it is transmitted to the DNA-binding domains. Through mutagenesis, DNA-binding studies, and computational methods, the allosteric response to nickel was found to be propagated from the nickel-binding sites to the DNA-binding domains via the β-sheets of the metal-binding domain and a network of residues at the inter-domain interface. Our computational results suggest that nickel binding increases protein rigidity to slow down the conformational exchange. A thymine base in the ureA promoter sequence, known to be critical for high affinity DNA binding by HpNikR, was also found to be important for the allosteric response, while a modified version of this promoter further highlighted the importance of the DNA sequence in modulating the response. Collectively, our results provide insights into regulation of a key protein for H. pylori survival.

The chameleonic behavior of p53 in health and disease: the transition from a client to an aberrant condensate scaffold in cancer

In 1972, the Weber statement, “The multiplicity of interactions and the variety of effects that follow from them show that multimer proteins are unlikely to be limited to a minimal number of allowed conformations,” first addressed the dynamic nature of proteins. This idea serves as a foundation for understanding why several macromolecules, such as p53, exhibit the properties of a molecular chameleon. Functionally competent states comprise a myriad of p53 three-dimensional arrangements depending on the stimuli. For instance, the interaction of p53 with nuclear components could induce liquid–liquid phase separation (LLPS) and the formation of membraneless organelles. The functional or deleterious role of p53 in liquid droplets is still unclear. Functional aspects display p53 interconverting between droplets and tetramer with its functional abilities maintained. In contrast, the aberrant phase separation is likely to fuel the aggregation path, usually associated with the onset and progression of age-related neurodegenerative diseases and cancer. Here, we gathered the most relevant aspects that lead p53 to phase separation and the resulting structural effects, attempting to understand p53’s functional and disease-relevant processes. Aberrant phase separation and aggregation of mutant p53 have become important therapeutic targets against cancer.

Natural and engineered inflammasome adapter proteins reveal optimum linker length for self-assembly

The inflammasome is a multiprotein complex that triggers the activation of proinflammatory cytokines. The adapter ASC and its isoform ASCb mediate inflammasome assembly via self-association and oligomerization with other inflammasome proteins by homotypic interactions of their two identical Death Domains, PYD and CARD, connected by a linker of different length: 23 (ASC) and 4 (ASCb) amino acids long. However, ASC is a more potent inflammasome activator compared to ASCb. Thus, adapter isoforms might be involved in the regulation of the inflammatory response. As previously reported, ASC's faster and less polydisperse self-association compared to ASCb points to interdomain flexibility resulting from the linker length as a key factor in inflammasome regulation. To test the influence of linker length in self-association, we have engineered the isoform ASC3X with identical PYD and CARD connected by a 69 amino acid-long linker (i.e., three-times longer than ASC's linker). Real-time NMR and dynamic light scattering data indicate that ASC3X polymerization is less effective and more polydisperse compared to ASC or ASCb. However, transmission electron micrographs show that ASC3X can polymerize into filaments. Comparative interdomain dynamics of the three isoforms obtained from NMR relaxation data reveal that ASCb tumbles as a rod, whereas the PYD and CARD of ASC and ASC3X tumble independently with marginally higher interdomain flexibility in ASC3X. Altogether, our data suggest that ASC's linker length is optimized for self-association by allowing enough flexibility to favor intermolecular homotypic interactions but simultaneously keeping both domains sufficiently close for essential participation in filament formation.

Protein Function Analysis through Machine Learning

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein–ligand binding, including allosteric effects, protein–protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.

Insight into the Tumor Suppression Mechanism from the Structure of Human Polypyrimidine Splicing Factor (PSF/SFPQ) Complexed with a 30mer RNA from Murine Virus-like 30S Transcript-1

Human polypyrimidine-binding splicing factor (PSF/SFPQ) is a tumor suppressor protein that regulates the gene expression of several proto-oncogenes and binds to the 5'-polyuridine negative-sense template (5'-PUN) of some RNA viruses. The activity of PSF is negatively regulated by long-noncoding RNAs, human metastasis associated in lung adenocarcinoma transcript-1 and murine virus-like 30S transcript-1 (VL30-1). PSF is a 707-amino acid protein that has a DNA-binding domain and two RNA recognition motifs (RRMs). Although the structure of the apo-truncated PSF is known, how PSF recognizes RNA remains elusive. Here, we report the 2.8 Å and 3.5 Å resolution crystal structures of a biologically active truncated construct of PSF (sPSF, consisting of residues 214-598) alone and in a complex with a 30mer fragment of VL30-1 RNA, respectively. The structure of the complex reveals how the 30mer RNA is recognized at two U-specific induced-fit binding pockets, located at the previously unrecognized domain-swapped, inter-subunit RRM1 (of the first subunit)-RRM2 (of the second subunit) interfaces that do not exist in the apo structure. Thus, the sPSF dimer appears to have two conformations in solution: one in a low-affinity state for RNA binding, as seen in the apo-structure, and the other in a high-affinity state for RNA binding, as seen in the sPSF-RNA complex. PSF undergoes an all or nothing transition between having two or no RNA-binding pockets. We predict that the RNA binds with a high degree of positive cooperativity. These structures provide an insight into a new regulatory mechanism that is likely involved in promoting malignancies and other human diseases.

Calmodulin's Interdomain Linker Is Optimized for Dynamics Signal Transmission and Calcium Binding

Linkers are ubiquitous in multidomain proteins. These linkers are integral to protein functions, and accumulating evidence suggests that the linkers' versatile roles are encoded in their sequences. However, a molecular picture of how amino acid differences in the linker influence protein function is still lacking. By using extensive Gaussian-accelerated MD coupled with dynamic network analysis, we reveal the molecular bases underlying the linker's role in Calmodulin (CaM), a highly conserved Ca²⁺-signaling hub in eukaryotes. Three CaM constructs comprising a wild-type linker, a flexible linker (four glycines at position D78-S81), and a rigid linker (four prolines at position D78-S81) were simulated. We show that the flexible linker resembles the wild type in allowing CaM to sample a large ensemble of conformations while the rigid linker confines the sampling. Our simulations recapture experimental observations that target binding enhances the Ca²⁺ affinity to CaM's EF-hand sites at the N-domain. However, only the wild-type linker can both correctly capture the Ca²⁺ binding order and maintain the α-helical structure of the domain. The other two constructs either bind Ca²⁺ in an incorrect order or exhibit unfolding of an N-domain helix. We demonstrate that the wild-type linker achieves these outcomes by transmitting interdomain dynamics efficiently. This was evidenced by stronger (anti)correlations among the linker residues, decoupling of the hydrogen bonds between A1-A15 and V35-E45, and structuring of the N-domain for Ca²⁺ binding. This decoupling was not evident for the other two constructs. Lastly, we show that the wild-type linker's optimal transmission stems from its thermodynamically favorable strain and solvation relative to the other two constructs. Our results show how the linker sequence tunes CaM function, suggesting possible mechanisms for changes in linker properties such as mutations or post-translational modifications to modulate protein/substrate binding.

Inter-subunit crosstalk via PDZ synergistically governs allosteric activation of proapoptotic HtrA2

The mitochondrial serine protease High-temperature requirement A2 (HtrA2) is associated with various diseases including neurodegenerative disorders and cancer. Despite availability of structural details, the reports on HtrA2's mechanistic regulation that varies with the type of activation signals still remain non-concordant. To expound the role of regulatory PDZ (Postsynaptic density-95/Discs large/Zonula occludens-1) domains in multimodal activation of HtrA2, we generated heterotrimeric HtrA2 variants comprising different numbers of PDZs and/or active-site mutations. Sequential deletion of PDZs from the trimeric ensemble significantly affected its residual activity in a way that proffered a hypothesis advocating inter-molecular allosteric crosstalk via PDZs in HtrA2. Furthermore, structural and computational snapshots affirmed the role of PDZs in secondary structural element formation around the regulatory loops and coordinated reorganization of the N-terminal region. Therefore, apart from providing cues for devising structure-guided therapeutic strategies, this study establishes a physiologically relevant working model of complex allosteric regulation through a trans-mediated cooperatively shared energy landscape.

Prediction of Allosteric Communication Pathways in Proteins

MOTIVATION

Allostery in proteins is an essential phenomenon in biological processes. In this paper, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form.

RESULTS

Predictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large Bcl-xL, Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase DHFR, HRas GTPase, and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or preexistence of some other functional states. Our model is computationally fast and simple, and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Regulation of the EphA2 receptor intracellular region by phosphomimetic negative charges in the kinase-SAM linker

Eph receptor tyrosine kinases play a key role in cell-cell communication. Lack of structural information on the entire multi-domain intracellular region of any Eph receptor has hindered understanding of their signaling mechanisms. Here, we use integrative structural biology to investigate the structure and dynamics of the EphA2 intracellular region. EphA2 promotes cancer malignancy through a poorly understood non-canonical form of signaling involving serine/threonine phosphorylation of the linker connecting its kinase and SAM domains. We show that accumulation of multiple linker negative charges, mimicking phosphorylation, induces cooperative changes in the EphA2 intracellular region from more closed to more extended conformations and perturbs the EphA2 juxtamembrane segment and kinase domain. In cells, linker negative charges promote EphA2 oligomerization. We also identify multiple kinases catalyzing linker phosphorylation. Our findings suggest multiple effects of linker phosphorylation on EphA2 signaling and imply that coordination of different kinases is necessary to promote EphA2 non-canonical signaling.

Eph receptor tyrosine kinases and their ephrin ligands mediate cell-cell communication. Here, the authors assess the structure and dynamics of the EphA2 intracellular region and uncover complex effects of phosphorylation within the linker region between EphA2 kinase and SAM domains.

Folded domain charge properties influence the conformational behavior of disordered tails

Intrinsically disordered proteins and protein regions (IDRs) make up around 30% of the human proteome where they play essential roles in dictating and regulating many core biological processes. While IDRs are often studied as isolated domains, in naturally occurring proteins most IDRs are found adjacent to folded domains, where they exist as either N- or C-terminal tails or as linkers connecting two folded domains. Prior work has shown that charge properties of IDRs can influence their conformational behavior, both in isolation and in the context of folded domains. In contrast, the converse scenario is less well-explored: how do the charge properties of folded domains influence IDR conformational behavior? To answer this question, we combined a large-scale structural bioinformatics analysis with all-atom implicit solvent simulations of both rationally designed and naturally occurring proteins. Our results reveal three key takeaways. Firstly, the relative position and accessibility of charged residues across the surface of a folded domain can dictate IDR conformational behavior, overriding expectations based on net surface charge properties. Secondly, naturally occurring proteins possess multiple charge patches that are physically accessible to local IDRs. Finally, even modest changes in the local electrostatic environment of a folded domain can substantially modulate IDR-folded domain interactions. Taken together, our results suggest that folded domain surfaces can act as local determinants of IDR conformational behavior.

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Intrinsically disordered regions (IDRs) are mostly found adjacent to folded domains.

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Here we propose that the folded domain surface properties influence IDR behavior.

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We combine all-atom simulations and sequence design of IDRs and folded domains.

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IDR conformational behavior is determined by a complex combination of factors.

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Folded domains can substantially alter IDR conformational biases.

The intramolecular allostery of GRB2 governing its interaction with SOS1 is modulated by phosphotyrosine ligands

Growth factor receptor-bound protein 2 (GRB2) is a trivalent adaptor protein and a key element in signal transduction. It interacts via its flanking nSH3 and cSH3 domains with the proline-rich domain (PRD) of the RAS activator SOS1 and via its central SH2 domain with phosphorylated tyrosine residues of receptor tyrosine kinases (RTKs; e.g. HER2). The elucidation of structural organization and mechanistic insights into GRB2 interactions, however, remain challenging due to their inherent flexibility. This study represents an important advance in our mechanistic understanding of how GRB2 links RTKs to SOS1. Accordingly, it can be proposed that (1) HER2 pYP-bound SH2 potentiates GRB2 SH3 domain interactions with SOS1 (an allosteric mechanism); (2) the SH2 domain blocks cSH3, enabling nSH3 to bind SOS1 first before cSH3 follows (an avidity-based mechanism); and (3) the allosteric behavior of cSH3 to other domains appears to be unidirectional, although there is an allosteric effect between the SH2 and SH3 domains.

Ubiquitin Interacting Motifs: Duality Between Structured and Disordered Motifs

Ubiquitin is a small protein at the heart of many cellular processes, and several different protein domains are known to recognize and bind ubiquitin. A common motif for interaction with ubiquitin is the Ubiquitin Interacting Motif (UIM), characterized by a conserved sequence signature and often found in multi-domain proteins. Multi-domain proteins with intrinsically disordered regions mediate interactions with multiple partners, orchestrating diverse pathways. Short linear motifs for binding are often embedded in these disordered regions and play crucial roles in modulating protein function. In this work, we investigated the structural propensities of UIMs using molecular dynamics simulations and NMR chemical shifts. Despite the structural portrait depicted by X-crystallography of stable helical structures, we show that UIMs feature both helical and intrinsically disordered conformations. Our results shed light on a new class of disordered UIMs. This group is here exemplified by the C-terminal domain of one isoform of ataxin-3 and a group of ubiquitin-specific proteases. Intriguingly, UIMs not only bind ubiquitin. They can be a recruitment point for other interactors, such as parkin and the heat shock protein Hsc70-4. Disordered UIMs can provide versatility and new functions to the client proteins, opening new directions for research on their interactome.

The diversity of molecular interactions involving intrinsically disordered proteins: A molecular modeling perspective

Intrinsically Disordered Proteins and Regions (IDPs/IDRs) are key components of a multitude of biological processes. Conformational malleability enables IDPs/IDRs to perform very specialized functions that cannot be accomplished by globular proteins. The functional role for most of these proteins is related to the recognition of other biomolecules to regulate biological processes or as a part of signaling pathways. Depending on the extent of disorder, the number of interacting sites and the type of partner, very different architectures for the resulting assemblies are possible. More recently, molecular condensates with liquid-like properties composed of multiple copies of IDPs and nucleic acids have been proven to regulate key processes in eukaryotic cells. The structural and kinetic details of disordered biomolecular complexes are difficult to unveil experimentally due to their inherent conformational heterogeneity. Computational approaches, alone or in combination with experimental data, have emerged as unavoidable tools to understand the functional mechanisms of this elusive type of assemblies. The level of description used, all-atom or coarse-grained, strongly depends on the size of the molecular systems and on the timescale of the investigated mechanism. In this mini-review, we describe the most relevant architectures found for molecular interactions involving IDPs/IDRs and the computational strategies applied for their investigation.

Global Dynamics Renders Protein Sites with High Functional Response

Deep mutational scanning enables examination of the effects of many mutations at each amino acid position in a query protein, readily disclosing positions that are particularly sensitive. Mutations in these positions alter protein function the most. Here, on the premise that dynamics underlie function, we explore to what extent the measured sensitivity to mutations could be linked to-perhaps be explained by-the structural dynamics of the protein. We employ a minimalist perturbation-response approach based on the Gaussian Network Model (GNM) on a data set of seven proteins with deep mutational scanning data. The analysis shows that the mutation-sensitive positions are often of capacity to modulate the global dynamics and to intermediate allosteric interactions in the structure. With that, upon strain perturbation, these positions decrease residue fluctuations the most, affecting function via entropy changes. This is particularly relevant for positions that are distant from binding sites or other functional regions of the protein and are sensitive to mutations, nevertheless. Our results indicate that mutations in these positions allosterically manipulate protein function.

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.

Transcription factor allosteric regulation through substrate coordination to zinc

The development of new synthetic biology circuits for biotechnology and medicine requires deeper mechanistic insight into allosteric transcription factors (aTFs). Here we studied the aTF UxuR, a homodimer of two domains connected by a highly flexible linker region. To explore how ligand binding to UxuR affects protein dynamics we performed molecular dynamics simulations in the free protein, the aTF bound to the inducer D-fructuronate or the structural isomer D-glucuronate. We then validated our results by constructing a sensor plasmid for D-fructuronate in Escherichia coli and performed site-directed mutagenesis. Our results show that zinc coordination is necessary for UxuR function since mutation to alanines prevents expression de-repression by D-fructuronate. Analyzing the different complexes, we found that the disordered linker regions allow the N-terminal domains to display fast and large movements. When the inducer is bound, UxuR can sample an open conformation with a more pronounced negative charge at the surface of the N-terminal DNA binding domains. In opposition, in the free and D-glucuronate bond forms the protein samples closed conformations, with a more positive character at the surface of the DNA binding regions. These molecular insights provide a new basis to harness these systems for biological systems engineering.

Entropic Inhibition: How the Activity of a AAA+ Machine Is Modulated by Its Substrate-Binding Domain

ClpB is a tightly regulated AAA+ disaggregation machine. Each ClpB molecule is composed of a flexibly attached N-terminal domain (NTD), an essential middle domain (MD) that activates the machine by tilting, and two nucleotide-binding domains. The NTD is not well-characterized structurally and is commonly considered to serve as a dispensable substrate-binding domain. Here, we use single-molecule FRET spectroscopy to directly monitor the real-time dynamics of ClpB's NTD and reveal its unexpected autoinhibitory function. We find that the NTD fluctuates on the microsecond time scale, and these dynamics result in steric hindrance that limits the conformational space of the MD to restrict its tilting. This leads to significantly inhibited ATPase and disaggregation activities of ClpB, an effect that is alleviated upon binding of a substrate protein or the cochaperone DnaK. This entropic inhibition mechanism, which is mediated by ultrafast motions of the NTD and is not dependent on any strong interactions, might be common in related ATP-dependent proteases and other multidomain proteins to ensure their fast and reversible activation.

The Role of Rigid Residues in Modulating TEM-1 β-Lactamase Function and Thermostability

The relationship between protein motions (i.e., dynamics) and enzymatic function has begun to be explored in β-lactamases as a way to advance our understanding of these proteins. In a recent study, we analyzed the dynamic profiles of TEM-1 (a ubiquitous class A β-lactamase) and several ancestrally reconstructed homologues. A chief finding of this work was that rigid residues that were allosterically coupled to the active site appeared to have profound effects on enzyme function, even when separated from the active site by many angstroms. In the present work, our aim was to further explore the implications of protein dynamics on β-lactamase function by altering the dynamic profile of TEM-1 using computational protein design methods. The Rosetta software suite was used to mutate amino acids surrounding either rigid residues that are highly coupled to the active site or to flexible residues with no apparent communication with the active site. Experimental characterization of ten designed proteins indicated that alteration of residues surrounding rigid, highly coupled residues, substantially affected both enzymatic activity and stability; in contrast, native-like activities and stabilities were maintained when flexible, uncoupled residues, were targeted. Our results provide additional insight into the structure-function relationship present in the TEM family of β-lactamases. Furthermore, the integration of computational protein design methods with analyses of protein dynamics represents a general approach that could be used to extend our understanding of the relationship between dynamics and function in other enzyme classes.

Engineering an Allosteric Control of Protein Function

Allosteric regulation in proteins is fundamental to many important biological processes. Allostery has been employed to control protein functions by regulating protein activity. Engineered allosteric regulation allows controlling protein activity in subsecond time scale and has a broad range of applications, from dissecting spatiotemporal dynamics in biochemical cascades to applications in biotechnology and medicine. Here, we review the concept of allostery in proteins and various approaches to identify allosteric sites and pathways. We then provide an overview of strategies and tools used in allosteric protein regulation and their utility in biological applications. We highlight various classes of proteins, where regulation is achieved through allostery. Finally, we analyze the current problems, critical challenges, and future prospective in achieving allosteric regulation in proteins.

A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins

The extraterminal (ET) domain of BRD3 is conserved among BET proteins (BRD2, BRD3, BRD4), interacting with multiple host and viral protein-protein networks. Solution NMR structures of complexes formed between the BRD3 ET domain and either the 79-residue murine leukemia virus integrase (IN) C-terminal domain (IN_329-408) or its 22-residue IN tail peptide (IN_386-407) alone reveal similar intermolecular three-stranded β-sheet formations. ¹⁵N relaxation studies reveal a 10-residue linker region (IN_379-388) tethering the SH3 domain (IN_329-378) to the ET-binding motif (IN_389-405):ET complex. This linker has restricted flexibility, affecting its potential range of orientations in the IN:nucleosome complex. The complex of the ET-binding peptide of the host NSD3 protein (NSD3_148-184) and the BRD3 ET domain includes a similar three-stranded β-sheet interaction, but the orientation of the β hairpin is flipped compared with the two IN:ET complexes. These studies expand our understanding of molecular recognition polymorphism in complexes of ET-binding motifs with viral and host proteins.

Research progress and the biotechnological applications of multienzyme complex

The multienzyme complex system has become a research focus in synthetic biology due to its highly efficient overall catalytic ability and has been applied to various fields. Multienzyme complexes are formed by cascading complexes, which are multiple functionally related enzymes that continuously and efficiently catalyze the production of substrates. Compared with current mainstream microbial cell catalytic systems, in vitro multienzyme molecular machines have many advantages, such as fewer side reactions, a high product yield, a fast reaction speed, easy product separation, a tolerable toxic environment, and robust system operability, showing increasing competitiveness in the field of biomanufacturing. In this review, the research progress of multienzyme complexes in nature and multienzyme cascades in vivo or in vitro will be introduced, and the discovered enzyme cascades concerning scaffolding proteins will also be discussed. This review is expected to provide a more theoretical basis for the modification of multienzyme complexes and broaden their application in the field of synthetic biology. KEY POINTS: • The cascade reactions of some natural multienzyme complexes are reviewed. • The main approaches of constructing artificial multienzyme complexes are summarized. • The structure and application of cellulosomes are discussed and prospected.

Synchronous and Asynchronous Response in Dynamically Perturbed Proteins

We present a dynamic perturbation-response model of proteins based on the Gaussian Network Model, where a residue is perturbed periodically, and the dynamic response of other residues is determined. The model shows that periodic perturbation causes a synchronous response in phase with the perturbation and an asynchronous response that is out of phase. The asynchronous component results from the viscous effects of the solvent and other dispersive factors in the system. The model is based on the solution of the Langevin equation in the presence of solvent, noise, and perturbation. We introduce several novel ideas: The concept of storage and loss compliance of the protein and their dependence on structure and frequency; the amount of work lost and the residues that contribute significantly to the lost work; new dynamic correlations that result from perturbation; causality, that is, the response of j when i is perturbed is not equal to the response of i when j is perturbed. As examples, we study two systems, namely, bovine rhodopsin and the class of nanobodies. The general results obtained are (i) synchronous and asynchronous correlations depend strongly on the frequency of perturbation, their magnitude decreases with increasing frequency, (ii) time-delayed mean-squared fluctuations of residues have only synchronous components. Asynchronicity is present only in cross correlations, that is, correlations between different residues, (iii) perturbation of loop residues leads to a large dissipation of work, (iv) correlations satisfy the hypothesis of pre-existing pathways according to which information transfer by perturbation rides on already existing equilibrium correlations in the system, (v) dynamic perturbation can introduce a selective response in the system, where the perturbation of each residue excites different sets of responding residues, and (vi) it is possible to identify nondissipative residues whose perturbation does not lead to dissipation in the protein. Despite its simplicity, the model explains several features of allosteric manipulation.

Candidate Binding Sites for Allosteric Inhibition of the SARS-CoV-2 Main Protease from the Analysis of Large-Scale Molecular Dynamics Simulations

We analyzed a 100 μs MD trajectory of the SARS-CoV-2 main protease by a non-parametric data analysis approach which allows characterizing a free energy landscape as a simultaneous function of hundreds of variables. We identified several conformations that, when visited by the dynamics, are stable for several hundred nanoseconds. We explicitly characterize and describe these metastable states. In some of these configurations, the catalytic dyad is less accessible. Stabilizing them by a suitable binder could lead to an inhibition of the enzymatic activity. In our analysis we keep track of relevant contacts between residues which are selectively broken or formed in the states. Some of these contacts are formed by residues which are far from the catalytic dyad and are accessible to the solvent. Based on this analysis we propose some relevant contact patterns and three possible binding sites which could be targeted to achieve allosteric inhibition.

Synthetic protein switches: Combinatorial linker engineering with iFLinkC

Linker engineering constitutes a critical, yet frequently underestimated aspect in the construction of synthetic protein switches and sensors. Notably, systematic strategies to engineer linkers by predictive means remain largely elusive to date. This is primarily due to our insufficient understanding how the biophysical properties that underlie linker functions mediate the conformational transitions in artificially engineered protein switches and sensors. The construction of synthetic protein switches and sensors therefore heavily relies on experimental trial-and-error. Yet, methods for effectively generating linker diversity at the genetic level are scarce. Addressing this technical shortcoming, iterative functional linker cloning (iFLinkC) enables the combinatorial assembly of linker elements with functional domains from sequence verified repositories that are developed and stored in-house. The assembly process is highly scalable and given its recursive nature generates linker diversity in a combinatorial and exponential fashion based on a limited number of linker elements.

A Time-Dependent Quantum Approach to Allostery and a Comparison With Light-Harvesting in Photosynthetic Phenomenon

The allosteric effect is one of the most important processes in regulating the function of proteins, and the elucidation of this phenomenon plays a significant role in understanding emergent behaviors in biological regulation. In this process, a perturbation, generated by a ligand in a part of the macromolecule (the allosteric site), moves along this system and reaches a specific (active) site, dozens of Ångströms away, with a great efficiency. The dynamics of this perturbation in the macromolecule can model precisely the allosteric process. In this article, we will be studying the general characteristics of allostery, using a time-dependent quantum approach to obtain rules that apply to this kind of process. Considering the perturbation as a wave that moves within the molecular system, we will characterize the allosteric process with three of the properties of this wave in the active site: (1) t_a, the characteristic time for reaching that site, (2) A_a, the amplitude of the wave in this site, and (3) B_a, its corresponding spectral broadening. These three parameters, together with the process mechanism and the perturbation efficiency in the process, can describe the phenomenon. One of the main purposes of this paper is to link the parameters t_a, A_a, and B_a and the perturbation efficiency to the characteristics of the system. There is another fundamental process for life that has some characteristics similar to allostery: the light-harvesting (LH) process in photosynthesis. Here, as in allostery, two distant macromolecular sites are involved—two sites dozens of Ångströms away. In both processes, it is particularly important that the perturbation is distributed efficiently without dissipating in the infinite degrees of freedom within the macromolecule. The importance of considering quantum effects in the LH process is well documented in literature, and the quantum coherences are experimentally proven by time-dependent spectroscopic techniques. Given the existing similarities between these two processes in macromolecules, in this work, we suggest using Quantum Mechanics (QM) to study allostery.

Disorder driven allosteric control of protein activity

Studies of protein allostery increasingly reveal an involvement of the back and forth order-disorder transitions in this mechanism of protein activity regulation. Here, we investigate the allosteric mechanisms mediated by structural disorder using the structure-based statistical mechanical model of allostery (SBSMMA) that we have previously developed. We show that SBSMMA accounts for the energetics and causality of allosteric communication underlying dimerization of the BirA biotin repressor, activation of the sortase A enzyme, and inhibition of the Rac1 GTPase. Using the SBSMMA, we also show that introducing structural order or disorder in various regions of esterases can originate tunable allosteric modulation of the catalytic triad. On the basis of obtained results, we propose that operating with the order-disorder continuum allows one to establish an allosteric control scale for achieving desired modulation of the protein activity.

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Back and forth order-disorder transitions can induce allosteric signaling.

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Allosteric signaling originated by order/disorder follow universal rules.

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Allosteric control scale facilitates engineering of the protein activity regulation.

ivis Dimensionality Reduction Framework for Biomacromolecular Simulations

Molecular dynamics (MD) simulations have been widely applied to study macromolecules including proteins. However, the high dimensionality of the data sets produced by simulations makes thorough analysis difficult and further hinders a deeper understanding of biomacromolecules. To gain more insights into the protein structure-function relations, appropriate dimensionality reduction methods are needed to project simulations onto low-dimensional spaces. Linear dimensionality reduction methods, such as principal component analysis (PCA) and time-structure-based independent component analysis (t-ICA), could not preserve sufficient structural information. Though better than linear methods, nonlinear methods, such as t-distributed stochastic neighbor embedding (t-SNE), still suffer from the limitations in avoiding system noise and keeping inter-cluster relations. ivis is a novel deep learning-based dimensionality reduction method originally developed for single-cell data sets. Here, we applied this framework for the study of light, oxygen, and voltage (LOV) domains of diatom Phaeodactylum tricornutum aureochrome 1a (PtAu1a). Compared with other methods, ivis is shown to be superior in constructing a Markov state model (MSM), preserving information of both local and global distances, and maintaining similarity between high and low dimensions with the least information loss. Moreover, the ivis framework is capable of providing new perspectives for deciphering residue-level protein allostery through the feature weights in the neural network. Overall, ivis is a promising member of the analysis toolbox for proteins.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

Designing Chimeric Molecules for Drug Discovery by Leveraging Chemical Biology

After the first seed concept introduced in the 18th century, different disciplines have attributed different names to dual-functional molecules depending on their application, including bioconjugates, bifunctional compounds, multitargeting molecules, chimeras, hybrids, engineered compounds. However, these engineered constructs share a general structure: a first component that targets a specific cell and a second component that exerts the pharmacological activity. A stable or cleavable linker connects the two modules of a chimera. Herein, we discuss the recent advances in the rapidly expanding field of chimeric molecules leveraging chemical biology concepts. This Perspective is focused on bifunctional compounds in which one component is a lead compound or a drug. In detail, we discuss chemical features of chimeric molecules and their use for targeted delivery and for target engagement studies.

Does Ras Activate Raf and PI3K Allosterically?

The mechanism through which oncogenic Ras activates its effectors is vastly important to resolve. If allostery is at play, then targeting allosteric pathways could help in quelling activation of MAPK (Raf/MEK/ERK) and PI3K (PI3K/Akt/mTOR) cell proliferation pathways. On the face of it, allosteric activation is reasonable: Ras binding perturbs the conformational ensembles of its effectors. Here, however, we suggest that at least for Raf, PI3K, and NORE1A (RASSF5), that is unlikely. Raf's long disordered linker dampens effective allosteric activation. Instead, we suggest that the high-affinity Ras–Raf binding relieves Raf's autoinhibition, shifting Raf's ensemble from the inactive to the nanocluster-mediated dimerized active state, as Ras also does for NORE1A. PI3K is recruited and allosterically activated by RTK (e.g., EGFR) at the membrane. Ras restrains PI3K's distribution and active site orientation. It stabilizes and facilitates PIP₂ binding at the active site and increases the PI3K residence time at the membrane. Thus, RTKs allosterically activate PI3Kα; however, merging their action with Ras accomplishes full activation. Here we review their activation mechanisms in this light and draw attention to implications for their pharmacology.

Molecular recognition of ubiquitin and Lys63-linked diubiquitin by STAM2 UIM-SH3 dual domain: the effect of its linker length and flexibility

Multidomain proteins represent a broad spectrum of the protein landscape and are involved in various interactions. They could be considered as modular building blocks assembled in distinct fashion and connected by linkers of varying lengths and sequences. Due to their intrinsic flexibility, these linkers provide proteins a subtle way to modulate interactions and explore a wide range of conformational space. In the present study, we are seeking to understand the effect of the flexibility and dynamics of the linker involved in the STAM2 UIM-SH3 dual domain protein with respect to molecular recognition. We have engineered several constructs of UIM-SH3 with different length linkers or domain deletion. By means of SAXS and NMR experiments, we have shown that the modification of the linker modifies the flexibility and the dynamics of UIM-SH3. Indeed, the global tumbling of both the UIM and SH3 domain is different but not independent from each other while the length of the linker has an impact on the ps-ns time scale dynamics of the respective domains. Finally, the modification of the flexibility and dynamics of the linker has a drastic effect on the interaction of UIM-SH3 with Lys63-linked diubiquitin with a roughly eight-time weaker dissociation constant.

Remodeling of the interdomain allosteric linker upon membrane binding of CCTα pulls its active site close to the membrane surface

The rate-limiting step in the biosynthesis of the major membrane phospholipid, phosphatidylcholine, is catalyzed by CTP:phosphocholine cytidylyltransferase (CCT), which is regulated by reversible membrane binding of a long amphipathic helix (domain M). The M domain communicates with the catalytic domain via a conserved ∼20-residue linker, essential for lipid activation of CCT. Previous analysis of this region (denoted as the αE_C/J) using MD simulations, cross-linking, mutagenesis, and solvent accessibility suggested that membrane binding of domain M promotes remodeling of the αE_C/J into a more compact structure that is required for enzyme activation. Here, using tryptophan fluorescence quenching, we show that the allosteric linker lies superficially on the membrane surface. Analyses with truncated CCTs show that the αE_C/J can interact with lipids independently of the M domain. We observed strong FRET between engineered tryptophans in the αE_C/J and vesicles containing dansyl-phosphatidylethanolamine that depended on the native J sequence. These data are incompatible with the extended conformation of the αE helix observed in the previously determined crystal structure of inactive CCT but support a bent αE helix conformation stabilized by J segment interactions. Our results suggest that the membrane-adsorbed, folded allosteric linker may partially cover the active site cleft and pull it close to the membrane surface, where cytidyl transfer can occur efficiently in a relatively anhydrous environment.

Unraveling the structural landscape of intra-chain domain interfaces: Implication in the evolution of domain-domain interactions

Intra-chain domain interactions are known to play a significant role in the function and stability of multidomain proteins. These interactions are mediated through a physical interaction at domain-domain interfaces (DDIs). With a motivation to understand evolution of interfaces, we have investigated similarities among DDIs. Even though interfaces of protein-protein interactions (PPIs) have been previously studied by structurally aligning interfaces, similar analyses have not yet been performed on DDIs of either multidomain proteins or PPIs. For studying the structural landscape of DDIs, we have used iAlign to structurally align intra-chain domain interfaces of domains. The interface alignment of spatially constrained domains (due to inter-domain linkers) showed that ~88% of these could identify a structural matching interface having similar C-alpha geometry and contact pattern despite that aligned domain pairs are not structurally related. Moreover, the mean interface similarity score (IS-score) is 0.307, which is higher compared to the average random IS-score (0.207) suggesting domain interfaces are not random. The structural space of DDIs is highly connected as ~84% of all possible directed edges among interfaces are found to have at most path length of 8 when 0.26 is IS-score threshold. At this threshold, ~83% of interfaces form the largest strongly connected component. Thus, suggesting that structural space of intra-chain domain interfaces is degenerate and highly connected, as has been found in PPI interfaces. Interestingly, searching for structural neighbors of inter-chain interfaces among intra-chain interfaces showed that ~86% could find a statistically significant match to intra-chain interface with a mean IS-score of 0.311. This implies that domain interfaces are degenerate whether formed within a protein or between proteins. The interface degeneracy is most likely due to limited possible ways of packing secondary structures. In principle, interface similarities can be exploited to accurately model domain interfaces in structure prediction of multidomain proteins.

Fold combinations in multi-domain proteins

Domain-domain interactions in multi-domain proteins play an important role in the combined function of individual domains for the overall biological activity of the protein. The functions of the tethered domains are often coupled and hence, limited numbers of domain architectures with defined folds are known in nature. Therefore, it is of interest to document the available fold-fold combinations and their preference in multi-domain proteins. Hence, we analyzed all multi-domain proteins with known structures in the protein databank and observed that only about 860 fold-fold combinations are present among them. Analyses of multi-domain proteins represented in sequence database result in recognition of 29,860 fold-fold combinations and it accounts for only 2.8% of the theoretically possible 1,036,080 (1439C2) fold-fold combinations. The observed preference for fold-fold combinations in multi-domain proteins is interesting in the context of multiple functions through structural adaptation by gene fusion.

Tracing the origin and evolution of pseudokinases across the tree of life

Protein phosphorylation by eukaryotic protein kinases (ePKs) is a fundamental mechanism of cell signaling in all organisms. In model vertebrates, ~10% of ePKs are classified as pseudokinases, which have amino acid changes within the catalytic machinery of the kinase domain that distinguish them from their canonical kinase counterparts. However, pseudokinases still regulate various signaling pathways, usually doing so in the absence of their own catalytic output. To investigate the prevalence, evolutionary relationships, and biological diversity of these pseudoenzymes, we performed a comprehensive analysis of putative pseudokinase sequences in available eukaryotic, bacterial, and archaeal proteomes. We found that pseudokinases are present across all domains of life, and we classified nearly 30,000 eukaryotic, 1500 bacterial, and 20 archaeal pseudokinase sequences into 86 pseudokinase families, including ~30 families that were previously unknown. We uncovered a rich variety of pseudokinases with notable expansions not only in animals but also in plants, fungi, and bacteria, where pseudokinases have previously received cursory attention. These expansions are accompanied by domain shuffling, which suggests roles for pseudokinases in plant innate immunity, plant-fungal interactions, and bacterial signaling. Mechanistically, the ancestral kinase fold has diverged in many distinct ways through the enrichment of unique sequence motifs to generate new families of pseudokinases in which the kinase domain is repurposed for noncanonical nucleotide binding or to stabilize unique, inactive kinase conformations. We further provide a collection of annotated pseudokinase sequences in the Protein Kinase Ontology (ProKinO) as a new mineable resource for the signaling community.