Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads

A novel motif in calcimembrin/C16orf74 dictates multimeric dephosphorylation by calcineurin

Calcineurin (CN), the only Ca 2+ -calmodulin activated protein phosphatase, dephosphorylates substrates within membrane-associated Ca 2+ microdomains. CN binds to substrates and regulators via short linear motifs (SLIMs), PxIxIT and LxVP. PxIxIT binding to CN is Ca 2+ independent and affects its distribution, while LxVP associates only with the active enzyme and promotes catalysis. 31 human proteins contain one or more composite 'LxVPxIxIT' motifs, whose functional properties have not been examined. Here we report studies of calcimembrin/C16orf74 (CLMB), a largely uncharacterized protein containing a composite motif that binds and directs CN to membranes. We demonstrate that CLMB associates with membranes via N-myristoylation and dynamic S-acylation and is dephosphorylated by CN on Thr44. The LxVP and PxIxIT portions of the CLMB composite sequence, together with Thr44 phosphorylation, confer high affinity PxIxIT-mediated binding to CN (KD∼8.9 nM) via an extended, 33 LxVPxIxITxx(p)T 44 sequence. This binding promotes CLMB-based targeting of CN to membranes, but also protects Thr44 from dephosphorylation. Thus, we propose that CN dephosphorylates CLMB in multimeric complexes, where one CLMB molecule recruits CN to membranes via PxIxIT binding, allowing others to engage through their LxVP motif for dephosphorylation. This unique mechanism makes dephosphorylation sensitive to CLMB:CN ratios and is supported by in vivo and in vitro analyses. CLMB overexpression is associated with poor prognoses for several cancers, suggesting that it promotes oncogenesis by shaping CN signaling.

Disordered clock protein interactions and charge blocks turn an hourglass into a persistent circadian oscillator

Organismal physiology is widely regulated by the molecular circadian clock, a feedback loop composed of protein complexes whose members are enriched in intrinsically disordered regions. These regions can mediate protein-protein interactions via SLiMs, but the contribution of these disordered regions to clock protein interactions had not been elucidated. To determine the functionality of these disordered regions, we applied a synthetic peptide microarray approach to the disordered clock protein FRQ in Neurospora crassa. We identified residues required for FRQ's interaction with its partner protein FRH, the mutation of which demonstrated FRH is necessary for persistent clock oscillations but not repression of transcriptional activity. Additionally, the microarray demonstrated an enrichment of FRH binding to FRQ peptides with a net positive charge. We found that positively charged residues occurred in significant "blocks" within the amino acid sequence of FRQ and that ablation of one of these blocks affected both core clock timing and physiological clock output. Finally, we found positive charge clusters were a commonly shared molecular feature in repressive circadian clock proteins. Overall, our study suggests a mechanistic purpose for positive charge blocks and yielded insights into repressive arm protein roles in clock function.

The molecular basis for cellular function of intrinsically disordered protein regions

Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.

ELM-the Eukaryotic Linear Motif resource-2024 update

Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.

High-throughput computational discovery of inhibitory protein fragments with AlphaFold

Peptides can bind to specific sites on larger proteins and thereby function as inhibitors and regulatory elements. Peptide fragments of larger proteins are particularly attractive for achieving these functions due to their inherent potential to form native-like binding interactions. Recently developed experimental approaches allow for high-throughput measurement of protein fragment inhibitory activity in living cells. However, it has thus far not been possible to predict de novo which of the many possible protein fragments bind their protein targets, let alone act as inhibitors. We have developed a computational method, FragFold, that employs AlphaFold to predict protein fragment binding to full-length protein targets in a high-throughput manner. Applying FragFold to thousands of fragments tiling across diverse proteins revealed peaks of predicted binding along each protein sequence. These predictions were compared with experimentally measured peaks of inhibitory activity in E. coli. We establish that our approach is a sensitive predictor of protein fragment function: Evaluating inhibitory fragments derived from known protein-protein interaction interfaces, we found 87% were predicted by FragFold to bind in a native-like mode. Across full protein sequences, 68% of FragFold-predicted binding peaks match experimentally measured inhibitory peaks. This is true even when the underlying inhibitory mechanism is unclear from existing structural data, and we find FragFold is able to predict novel binding modes for inhibitory fragments of unknown structure, explaining previous genetic and biochemical data for these fragments. The success rate of FragFold demonstrates that this computational approach should be broadly applicable for discovering inhibitory protein fragments across proteomes.

Phosphatase specificity principles uncovered by MRBLE:Dephos and global substrate identification

Phosphoprotein phosphatases (PPPs) regulate major signaling pathways, but the determinants of phosphatase specificity are poorly understood. This is because methods to investigate this at scale are lacking. Here, we develop a novel in vitro assay, MRBLE:Dephos, that allows multiplexing of dephosphorylation reactions to determine phosphatase preferences. Using MRBLE:Dephos, we establish amino acid preferences of the residues surrounding the dephosphorylation site for PP1 and PP2A-B55, which reveals common and unique preferences. To compare the MRBLE:Dephos results to cellular substrates, we focused on mitotic exit that requires extensive dephosphorylation by PP1 and PP2A-B55. We use specific inhibition of PP1 and PP2A-B55 in mitotic exit lysates coupled with phosphoproteomics to identify more than 2,000 regulated sites. Importantly, the sites dephosphorylated during mitotic exit reveal key signatures that are consistent with MRBLE:Dephos. Furthermore, integration of our phosphoproteomic data with mitotic interactomes of PP1 and PP2A-B55 provides insight into how binding of phosphatases to substrates shapes dephosphorylation. Collectively, we develop novel approaches to investigate protein phosphatases that provide insight into mitotic exit regulation.

Designing Cyclic-Constrained Peptides to Inhibit Human Phosphoglycerate Dehydrogenase

Although loop epitopes at protein-protein binding interfaces often play key roles in mediating oligomer formation and interaction specificity, their binding sites are underexplored as drug targets owing to their high flexibility, relatively few hot spots, and solvent accessibility. Prior attempts to develop molecules that mimic loop epitopes to disrupt protein oligomers have had limited success. In this study, we used structure-based approaches to design and optimize cyclic-constrained peptides based on loop epitopes at the human phosphoglycerate dehydrogenase (PHGDH) dimer interface, which is an obligate homo-dimer with activity strongly dependent on the oligomeric state. The experimental validations showed that these cyclic peptides inhibit PHGDH activity by directly binding to the dimer interface and disrupting the obligate homo-oligomer formation. Our results demonstrate that loop epitope derived cyclic peptides with rationally designed affinity-enhancing substitutions can modulate obligate protein homo-oligomers, which can be used to design peptide inhibitors for other seemingly intractable oligomeric proteins.

The next wave of interactomics: Mapping the SLiM-based interactions of the intrinsically disordered proteome

Short linear motifs (SLiMs) are a unique and ubiquitous class of protein interaction modules that perform key regulatory functions and drive dynamic complex formation. For decades, interactions mediated by SLiMs have accumulated through detailed low-throughput experiments. Recent methodological advances have opened this previously underexplored area of the human interactome to high-throughput protein-protein interaction discovery. In this article, we discuss that SLiM-based interactions represent a significant blind spot in the current interactomics data, introduce the key methods that are illuminating the elusive SLiM-mediated interactome of the human cell on a large scale, and discuss the implications for the field.

Evaluation of affinity-purification coupled to mass spectrometry approaches for capture of short linear motif-based interactions

Low affinity and transient protein-protein interactions, such as short linear motif (SLiM)-based interactions, require dedicated experimental tools for discovery and validation. Here, we evaluated and compared biotinylated peptide pulldown and protein interaction screen on peptide matrix (PRISMA) coupled to mass-spectrometry (MS) using a set of peptides containing interaction motifs. Eight different peptide sequences that engage in interactions with three distinct protein domains (KEAP1 Kelch, MDM2 SWIB, and TSG101 UEV) with a wide range of affinities were tested. We found that peptide pulldown can be an effective approach for SLiM validation, however, parameters such as protein abundance and competitive interactions can prevent the capture of known interactors. The use of tandem peptide repeats improved the capture and preservation of some interactions. When testing PRISMA, it failed to provide comparable results for model peptides that successfully pulled down known interactors using biotinylated peptide pulldown. Overall, in our hands, we find that albeit more laborious, biotin-peptide pulldown was more successful in terms of validation of known interactions. Our results highlight that the tested affinity-capture MS-based methods for validation of SLiM-based interactions from cell lysates are suboptimal, and we identified parameters for consideration for method development.

Ranking Peptide Binders by Affinity with AlphaFold

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.

Funneling modulatory peptide design with generative models: Discovery and characterization of disruptors of calcineurin protein-protein interactions

Design of peptide binders is an attractive strategy for targeting "undruggable" protein-protein interfaces. Current design protocols rely on the extraction of an initial sequence from one known protein interactor of the target protein, followed by in-silico or in-vitro mutagenesis-based optimization of its binding affinity. Wet lab protocols can explore only a minor portion of the vast sequence space and cannot efficiently screen for other desirable properties such as high specificity and low toxicity, while in-silico design requires intensive computational resources and often relies on simplified binding models. Yet, for a multivalent protein target, dozens to hundreds of natural protein partners already exist in the cellular environment. Here, we describe a peptide design protocol that harnesses this diversity via a machine learning generative model. After identifying putative natural binding fragments by literature and homology search, a compositional Restricted Boltzmann Machine is trained and sampled to yield hundreds of diverse candidate peptides. The latter are further filtered via flexible molecular docking and an in-vitro microchip-based binding assay. We validate and test our protocol on calcineurin, a calcium-dependent protein phosphatase involved in various cellular pathways in health and disease. In a single screening round, we identified multiple 16-length peptides with up to six mutations from their closest natural sequence that successfully interfere with the binding of calcineurin to its substrates. In summary, integrating protein interaction and sequence databases, generative modeling, molecular docking and interaction assays enables the discovery of novel protein-protein interaction modulators.

Proteome-wide screening for mitogen-activated protein kinase docking motifs and interactors

Essential functions of mitogen-activated protein kinases (MAPKs) depend on their capacity to selectively phosphorylate a limited repertoire of substrates. MAPKs harbor a conserved groove located outside of the catalytic cleft that binds to short linear sequence motifs found in substrates and regulators. However, the weak and transient nature of these "docking" interactions poses a challenge to defining MAPK interactomes and associated sequence motifs. Here, we describe a yeast-based genetic screening pipeline to evaluate large collections of MAPK docking sequences in parallel. Using this platform, we analyzed a combinatorial library based on the docking sequences from the MAPK kinases MKK6 and MKK7, defining features critical for binding to the stress-activated MAPKs JNK1 and p38α. Our screen of a library consisting of ~12,000 sequences from the human proteome revealed multiple MAPK-selective interactors, including many that did not conform to previously defined docking motifs. Analysis of p38α/JNK1 exchange mutants identified specific docking groove residues that mediate selective binding. Last, we verified that docking sequences identified in the screen functioned in substrate recruitment in vitro and in cultured cells. Together, these studies establish an approach to characterize MAPK docking sequences and provide a resource for future investigation of signaling downstream of p38 and JNK.

A cellular atlas of calcineurin signaling

Intracellular Ca2+ signals are temporally controlled and spatially restricted. Signaling occurs adjacent to sites of Ca2+ entry and/or release, where Ca2+-dependent effectors and their substrates co-localize to form signaling microdomains. Here we review signaling by calcineurin, the Ca2+/calmodulin regulated protein phosphatase and target of immunosuppressant drugs, Cyclosporin A and FK506. Although well known for its activation of the adaptive immune response via NFAT dephosphorylation, systematic mapping of human calcineurin substrates and regulators reveals unexpected roles for this versatile phosphatase throughout the cell. We discuss calcineurin function, with an emphasis on where signaling occurs and mechanisms that target calcineurin and its substrates to signaling microdomains, especially binding of cognate short linear peptide motifs (SLiMs). Calcineurin is ubiquitously expressed and regulates events at the plasma membrane, other intracellular membranes, mitochondria, the nuclear pore complex and centrosomes/cilia. Based on our expanding knowledge of localized CN actions, we describe a cellular atlas of Ca2+/calcineurin signaling.

Native holdup (nHU) to measure binding affinities from cell extracts

Characterizing macromolecular interactions is essential for understanding cellular processes, yet most methods currently used to detect protein interactions from cells are qualitative. Here, we introduce the native holdup (nHU) approach to estimate equilibrium binding constants of protein interactions directly from cell extracts. Compared to other pull-down-based assays, nHU requires less sample preparation and can be coupled to any analytical methods as readouts, such as Western blotting or mass spectrometry. We use nHU to explore interactions of SNX27, a cargo adaptor of the retromer complex and find good agreement between in vitro affinities and those measured directly from cell extracts using nHU. We discuss the strengths and limitations of nHU and provide simple protocols that can be implemented in most laboratories.

Towards rational computational peptide design

Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available-and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery.

The optimized core peptide derived from CABIN1 efficiently inhibits calcineurin-mediated T-cell activation

The C-terminal fragment of CABIN1 interacts with calcineurin and represses the transcriptional activity of the nuclear factor of activated T cells (NFAT). However, the specific sequences and mechanisms through which it binds to calcineurin are unclear. This study determined that decameric peptide (CABIN1 residues 2146–2155) is minimally required for binding to calcineurin. This peptide contains a unique “PPTP” C-terminal sequence and a “PxIxIT” N-terminal motif. Furthermore, p38MAPK phosphorylated the threonine residue of the “PPTP” sequence under physiological conditions, dramatically enhancing the peptide’s binding affinity to calcineurin. Therefore, the CABIN1 peptide inhibited the calcineurin-NFAT pathway and the activation of T cells more efficiently than the VIVIT peptide without affecting calcineurin’s phosphatase activity. The CABIN1 peptide could thus be a more potent calcineurin inhibitor and provide therapeutic opportunities for various diseases caused by the calcineurin-NFAT pathway.

A peptide with therapeutic potential binds strongly to the cellular enzyme calcineurin and may prove valuable in anti-cancer and autoimmune disease treatments. Many cancers and autoimmune diseases are linked with overactivation of a key calcineurin-related pathway which is heavily involved in T cell activation. This pathway has long been a therapeutic target, but existing drugs show problems with stability and delivery, and can cause serious side effects. One known inhibitor of calcineurin is the protein CABIN1, but precisely how well it binds and how useful it may be is unclear. Now, Hong-Duk Youn at Seoul National University College of Medicine, South Korea, and co-workers have identified how one specific peptide from CABIN1 binds strongly to calcineurin. The CABIN1 peptide was stable and displayed greater efficiency at inhibiting calcineurin than another recently identified peptide candidate.

Computational Site Saturation Mutagenesis of Canonical and Non-Canonical Amino Acids to Probe Protein-Peptide Interactions

Technologies for discovering peptides as potential therapeutics have rapidly advanced in recent years with significant interest from both academic and pharmaceutical labs. These advancements in turn drive the need for new computational tools to design peptides for purposes of advancing lead molecules into the clinic. Here we report the development and application of a new automated tool, AutoRotLib, for parameterizing a diverse set of non-canonical amino acids (NCAAs), N-methyl, or peptoid residues for use with the computational design program Rosetta. In addition, we developed a protocol for designing thioether-cyclized macrocycles within Rosetta, due to their common application in mRNA display using the RaPID platform. To evaluate the utility of these new computational tools, we screened a library of canonical and NCAAs on both a linear peptide and a thioether macrocycle, allowing us to quickly identify mutations that affect peptide binding and subsequently measure our results against previously published data. We anticipate in silico screening of peptides against a diverse chemical space will be a fundamental component for peptide design and optimization, as more amino acids can be explored in a single in silico screen than an in vitro screen. As such, these tools will enable maturation of peptide affinity for protein targets of interest and optimization of peptide pharmacokinetics for therapeutic applications.

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's phylogenetic history and gives rise to concurrent variation between protein sequences that is not driven by selection for function. Here, we introduce a background model for phylogenetic contributions of statistical coupling that separates the coevolution signal due to inter-clade and intra-clade sequence comparisons and demonstrate that coevolution can be measured on multiple phylogenetic timescales within a single protein. Our method, nested coevolution (NC), can be applied as an extension to any coevolution metric. We use NC to demonstrate that poorly conserved residues can nonetheless have important roles in protein function. Moreover, NC improved the structural-contact predictions of several coevolution-based methods, particularly in subsampled alignments with fewer sequences. NC also lowered the noise in detecting functional sectors of collectively coevolving residues. Sectors of coevolving residues identified after application of NC were more spatially compact and phylogenetically distinct from the rest of the protein, and strongly enriched for mutations that disrupt protein activity. Thus, our conceptualization of the phylogenetic separation of coevolution provides the potential to further elucidate relationships among protein evolution, function, and genetic diseases.

Orchestrating serine/threonine phosphorylation and elucidating downstream effects by short linear motifs

Cellular function is based on protein-protein interactions. A large proportion of these interactions involves the binding of short linear motifs (SLiMs) by folded globular domains. These interactions are regulated by post-translational modifications, such as phosphorylation, that create and break motif binding sites or tune the affinity of the interactions. In addition, motif-based interactions are involved in targeting serine/threonine kinases and phosphatases to their substrate and contribute to the specificity of the enzymatic actions regulating which sites are phosphorylated. Here, we review how SLiM-based interactions assist in determining the specificity of serine/threonine kinases and phosphatases, and how phosphorylation, in turn, affects motif-based interactions. We provide examples of SLiM-based interactions that are turned on/off, or are tuned by serine/threonine phosphorylation and exemplify how this affects SLiM-based protein complex formation.

Harnessing protein folding neural networks for peptide-protein docking

Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been developed for the in silico folding of protein monomers, AlphaFold2 also enables quick and accurate modeling of peptide-protein interactions. Our simple implementation of AlphaFold2 generates peptide-protein complex models without requiring multiple sequence alignment information for the peptide partner, and can handle binding-induced conformational changes of the receptor. We explore what AlphaFold2 has memorized and learned, and describe specific examples that highlight differences compared to state-of-the-art peptide docking protocol PIPER-FlexPepDock. These results show that AlphaFold2 holds great promise for providing structural insight into a wide range of peptide-protein complexes, serving as a starting point for the detailed characterization and manipulation of these interactions.

The Eukaryotic Linear Motif resource: 2022 release

Almost twenty years after its initial release, the Eukaryotic Linear Motif (ELM) resource remains an invaluable source of information for the study of motif-mediated protein-protein interactions. ELM provides a comprehensive, regularly updated and well-organised repository of manually curated, experimentally validated short linear motifs (SLiMs). An increasing number of SLiM-mediated interactions are discovered each year and keeping the resource up-to-date continues to be a great challenge. In the current update, 30 novel motif classes have been added and five existing classes have undergone major revisions. The update includes 411 new motif instances mostly focused on cell-cycle regulation, control of the actin cytoskeleton, membrane remodelling and vesicle trafficking pathways, liquid-liquid phase separation and integrin signalling. Many of the newly annotated motif-mediated interactions are targets of pathogenic motif mimicry by viral, bacterial or eukaryotic pathogens, providing invaluable insights into the molecular mechanisms underlying infectious diseases. The current ELM release includes 317 motif classes incorporating 3934 individual motif instances manually curated from 3867 scientific publications. ELM is available at: http://elm.eu.org.

Calcineurin in the heart: New horizons for an old friend

Calcineurin, also known as PP2B or PPP3, is a member of the PPP family of protein phosphatases that also includes PP1 and PP2A. Together these three phosphatases carryout the majority of dephosphorylation events in the heart. Calcineurin is distinct in that it is activated by the binding of calcium/calmodulin (Ca2+/CaM) and therefore acts as a node for integrating Ca2+ signals with changes in phosphorylation, two fundamental intracellular signaling cascades. In the heart, calcineurin is primarily thought of in the context of pathological cardiac remodeling, acting through the Nuclear Factor of Activated T-cell (NFAT) family of transcription factors. However, calcineurin activity is also essential for normal heart development and homeostasis in the adult heart. Furthermore, it is clear that NFAT-driven changes in transcription are not the only relevant processes initiated by calcineurin in the setting of pathological remodeling. There is a growing appreciation for the diversity of calcineurin substrates that can impact cardiac function as well as the diversity of mechanisms for targeting calcineurin to specific sub-cellular domains in cardiomyocytes and other cardiac cell types. Here, we will review the basics of calcineurin structure, regulation, and function in the context of cardiac biology. Particular attention will be given to: the development of improved tools to identify and validate new calcineurin substrates; recent studies identifying new calcineurin isoforms with unique properties and targeting mechanisms; and the role of calcineurin in cardiac development and regeneration.

MRBLE-pep Measurements Reveal Accurate Binding Affinities for B56, a PP2A Regulatory Subunit

Signal transduction pathways rely on dynamic interactions between protein globular domains and short linear motifs (SLiMs). The weak affinities of these interactions are essential to allow fast rewiring of signaling pathways and downstream responses but also pose technical challenges for interaction detection and measurement. We recently developed a technique (MRBLE-pep) that leverages spectrally encoded hydrogel beads to measure binding affinities between a single protein of interest and 48 different peptide sequences in a single small volume. In prior work, we applied it to map the binding specificity landscape between calcineurin and the PxIxIT SLiM (Nguyen, H. Q. et al. Elife 2019, 8). Here, using peptide sequences known to bind the PP2A regulatory subunit B56α, we systematically compare affinities measured by MRBLE-pep or isothermal calorimetry (ITC) and confirm that MRBLE-pep accurately quantifies relative affinity over a wide dynamic range while using a fraction of the material required for traditional methods such as ITC.

A functionally divergent intrinsically disordered region underlying the conservation of stochastic signaling

Stochastic signaling dynamics expand living cells' information processing capabilities. An increasing number of studies report that regulators encode information in their pulsatile dynamics. The evolutionary mechanisms that lead to complex signaling dynamics remain uncharacterized, perhaps because key interactions of signaling proteins are encoded in intrinsically disordered regions (IDRs), whose evolution is difficult to analyze. Here we focused on the IDR that controls the stochastic pulsing dynamics of Crz1, a transcription factor in fungi downstream of the widely conserved calcium signaling pathway. We find that Crz1 IDRs from anciently diverged fungi can all respond transiently to calcium stress; however, only Crz1 IDRs from the Saccharomyces clade support pulsatility, encode extra information, and rescue fitness in competition assays, while the Crz1 IDRs from distantly related fungi do none of the three. On the other hand, we find that Crz1 pulsing is conserved in the distantly related fungi, consistent with the evolutionary model of stabilizing selection on the signaling phenotype. Further, we show that a calcineurin docking site in a specific part of the IDRs appears to be sufficient for pulsing and show evidence for a beneficial increase in the relative calcineurin affinity of this docking site. We propose that evolutionary flexibility of functionally divergent IDRs underlies the conservation of stochastic signaling by stabilizing selection.

How much can physics do for protein design?

Physics and physical chemistry are an important thread in computational protein design, complementary to knowledge-based tools. They provide molecular mechanics scoring functions that need little or no ad hoc parameter readjustment, methods to thoroughly sample equilibrium ensembles, and different levels of approximation for conformational flexibility. They led recently to the successful redesign of a small protein using a physics-based folded state energy. Adaptive Monte Carlo or molecular dynamics schemes were discovered where protein variants are populated as per their ligand-binding free energy or catalytic efficiency. Molecular dynamics have been used for backbone flexibility. Implicit solvent models have been refined, polarizable force fields applied, and many physical insights obtained.

Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay

The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to the cell receptor and affect the potency of vaccines and antibodies. Here we used an in silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay results show that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated the in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit the development of broadly neutralizing vaccine and antibody.

High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants

Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quantitative characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 K_ds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiological binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochemical double-mutant cycles across the TF-DNA interface reveal molecular mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

MRBLES 2.0: High-throughput generation of chemically functionalized spectrally and magnetically encoded hydrogel beads using a simple single-layer microfluidic device

The widespread adoption of bead-based multiplexed bioassays requires the ability to easily synthesize encoded microspheres and conjugate analytes of interest to their surface. Here, we present a simple method (MRBLEs 2.0) for the efficient high-throughput generation of microspheres with ratiometric barcode lanthanide encoding (MRBLEs) that bear functional groups for downstream surface bioconjugation. Bead production in MRBLEs 2.0 relies on the manual mixing of lanthanide/polymer mixtures (each of which comprises a unique spectral code) followed by droplet generation using single-layer, parallel flow-focusing devices and the off-chip batch polymerization of droplets into beads. To streamline downstream analyte coupling, MRBLEs 2.0 crosslinks copolymers bearing functional groups on the bead surface during bead generation. Using the MRBLEs 2.0 pipeline, we generate monodisperse MRBLEs containing 48 distinct well-resolved spectral codes with high throughput (>150,000/min and can be boosted to 450,000/min). We further demonstrate the efficient conjugation of oligonucleotides and entire proteins to carboxyl MRBLEs and of biotin to amino MRBLEs. Finally, we show that MRBLEs can also be magnetized via the simultaneous incorporation of magnetic nanoparticles with only a minor decrease in the potential code space. With the advantages of dramatically simplified device fabrication, elimination of the need for custom-made equipment, and the ability to produce spectrally and magnetically encoded beads with direct surface functionalization with high throughput, MRBLEs 2.0 can be directly applied by many labs towards a wide variety of downstream assays, from basic biology to diagnostics and other translational research.

Comprehensive Analysis of G1 Cyclin Docking Motif Sequences that Control CDK Regulatory Potency In Vivo

Many protein-modifying enzymes recognize their substrates via docking motifs, but the range of functionally permissible motif sequences is often poorly defined. During eukaryotic cell division, cyclin-specific docking motifs help cyclin-dependent kinases (CDKs) phosphorylate different substrates at different stages, thus enforcing a temporally ordered series of events. In budding yeast, CDK substrates with Leu/Pro-rich (LP) docking motifs are recognized by Cln1/2 cyclins in late G1 phase, yet the key sequence features of these motifs were unknown. Here, we comprehensively analyze LP motif requirements in vivo by combining a competitive growth assay with deep mutational scanning. We quantified the effect of all single-residue replacements in five different LP motifs by using six distinct G1 cyclins from diverse fungi including medical and agricultural pathogens. The results uncover substantial tolerance for deviations from the consensus sequence, plus requirements at some positions that are contingent on the favorability of other motif residues. They also reveal the basis for variations in functional potency among wild-type motifs, and allow derivation of a quantitative matrix that predicts the strength of other candidate motif sequences. Finally, we find that variation in docking motif potency can advance or delay the time at which CDK substrate phosphorylation occurs, and thereby control the temporal ordering of cell cycle regulation. The overall results provide a general method for surveying viable docking motif sequences and quantifying their potency in vivo, and they reveal how variations in docking strength can tune the degree and timing of regulatory modifications.

Cell Biology: Deciphering the ABCs of SLiMs in G1-CDK Signaling

A new study uses an elegant in vivo assay to comprehensively characterize the LP docking motif, which determines G1-CDK substrate specificity in fungi. The authors show that LP-cyclin docking strength determines the timing of Sic1 degradation, a key cell cycle event.

Logomaker: beautiful sequence logos in Python

Summary

Sequence logos are visually compelling ways of illustrating the biological properties of DNA, RNA and protein sequences, yet it is currently difficult to generate and customize such logos within the Python programming environment. Here we introduce Logomaker, a Python API for creating publication-quality sequence logos. Logomaker can produce both standard and highly customized logos from either a matrix-like array of numbers or a multiple-sequence alignment. Logos are rendered as native matplotlib objects that are easy to stylize and incorporate into multi-panel figures.

Availability and implementation

Logomaker can be installed using the pip package manager and is compatible with both Python 2.7 and Python 3.6. Documentation is provided at http://logomaker.readthedocs.io; source code is available at http://github.com/jbkinney/logomaker.

Calcineurin

The serine/threonine phosphatase calcineurin acts as a crucial connection between calcium signaling the phosphorylation states of numerous important substrates. These substrates include, but are not limited to, transcription factors, receptors and channels, proteins associated with mitochondria, and proteins associated with microtubules. Calcineurin is activated by increases in intracellular calcium concentrations, a process that requires the calcium sensing protein calmodulin binding to an intrinsically disordered regulatory domain in the phosphatase. Despite having been studied for around four decades, the activation of calcineurin is not fully understood. This review largely focuses on what is known about the activation process and highlights aspects that are currently not understood. Video abstract.

Benchtop holdup assay for quantitative affinity-based analysis of sequence determinants of protein-motif interactions

Many protein-protein interactions are mediated by short linear peptide motifs binding to cognate proteins or protein domains. Such interactions often display affinities in the mid-micromolar range that are challenging to quantify accurately, especially when the motifs harbor single-point mutations. Here, we present a manual benchtop assay for determining affinities of weak interactions between a purified protein and a peptide array representing mutants of a target motif. The assay is based on the "holdup" principle, a chromatographic approach allowing sensitive detection of weak interactions at equilibrium and accurate estimation of their binding free energy. We tested two alternative setups using, as a readout, either capillary electrophoresis or fluorescence. Using this approach, we studied the amino acid sequence determinants of the interactions between HPV16 E6 viral oncoprotein and single-point mutants of its prototypical target LXXLL motif from the E3 ubiquitin ligase E6AP. Comparing SPOT peptide array and holdup approaches revealed a good agreement for most interactions except the weakest ones, which were only detected by holdup assay. In addition, the strongest interactions were validated by Surface-Plasmon Resonance. The manual holdup procedure proposed here can be readily adapted for accurate evaluation of a wide variety of protein-motif interactions displaying low to medium affinities.

Lanthanide-Based Optical Probes of Biological Systems

The unique photophysical properties of lanthanides, such as europium, terbium, and ytterbium, make them versatile molecular probes of biological systems. In particular, their long-lived photoluminescence, narrow bandwidth emissions, and large Stokes shifts enable experiments that are infeasible with organic fluorophores and fluorescent proteins. The ability of these metal ions to undergo luminescence resonance energy transfer, and photon upconversion further expands the capabilities of lanthanide probes. In this review, we describe recent advances in the design of lanthanide luminophores and their application in biological research. We also summarize the latest detection systems that have been developed to fully exploit the optical properties of lanthanide luminophores. We conclude with a discussion of remaining challenges and new frontiers in lanthanide technologies. The unprecedented levels of sensitivity and multiplexing afforded by rare-earth elements illustrate how chemistry can enable new approaches in biology.

Systematic Discovery of Short Linear Motifs Decodes Calcineurin Phosphatase Signaling

Short linear motifs (SLiMs) drive dynamic protein-protein interactions essential for signaling, but sequence degeneracy and low binding affinities make them difficult to identify. We harnessed unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN)/PP2B, the Ca²⁺-activated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in vivo SLiM-dependent proximity labeling, and in silico modeling of motif determinants uncovered unanticipated CN interactors, including NOTCH1, which we establish as a CN substrate. Unexpectedly, CN shows SLiM-dependent proximity to centrosomal and nuclear pore complex (NPC) proteins-structures where Ca²⁺ signaling is largely uncharacterized. CN dephosphorylates human and yeast NPC proteins and promotes accumulation of a nuclear transport reporter, suggesting conserved NPC regulation by CN. The CN network assembled here provides a resource to investigate Ca²⁺ and CN signaling and demonstrates synergy between experimental and computational methods, establishing a blueprint for examining SLiM-based networks.

Protocol for Peptide Synthesis on Spectrally Encoded Beads for MRBLE-pep Assays

Every living cell relies on signal transduction pathways comprised of protein-protein interactions (PPIs). In many cases, these PPIs are between a folded protein domain and a short linear motif (SLiM) within an unstructured region of a protein. As a result of this small interaction interface (3-10 amino acids), the affinities of SLiM-mediated interactions are typically weak (K _ds of ~1-10 µM), allowing physiologically relevant changes in cellular concentrations of either protein partner to dictate changes in occupancy and thereby transmit cellular signals. However, these weak affinities also render detection and quantitative measurement of these interactions challenging and labor intensive. To address this, we recently developed MRBLE-pep, a technology that employs peptide libraries synthesized on spectrally encoded hydrogel beads to allow multiplexed affinity measurements between a protein and many different peptides in parallel. This approach dramatically reduces both the amount of protein and peptide as well as the time required to measure protein-peptide affinities compared to traditional methods. Here, we provide a detailed protocol describing how to: (1) functionalize polyethylene glycol diacrylate (PEG-DA) MRBLE beads with free amine groups, (2) synthesize peptide libraries on functionalized MRBLEs, (3) validate synthesized peptide sequences via MALDI mass spectrometry and quantify evenness of peptide coverage on MRBLEs, (4) use MRBLE-bound peptide libraries in multiplexed protein binding assays, and (5) analyze binding data to determine binding affinities. We anticipate that this protocol should prove useful for other researchers seeking to use MRBLE-pep in their own laboratories as well as for researchers broadly interested in solid-phase peptide synthesis and protein-protein binding assay development.

ELM-the eukaryotic linear motif resource in 2020

The eukaryotic linear motif (ELM) resource is a repository of manually curated experimentally validated short linear motifs (SLiMs). Since the initial release almost 20 years ago, ELM has become an indispensable resource for the molecular biology community for investigating functional regions in many proteins. In this update, we have added 21 novel motif classes, made major revisions to 12 motif classes and added >400 new instances mostly focused on DNA damage, the cytoskeleton, SH2-binding phosphotyrosine motifs and motif mimicry by pathogenic bacterial effector proteins. The current release of the ELM database contains 289 motif classes and 3523 individual protein motif instances manually curated from 3467 scientific publications. ELM is available at: http://elm.eu.org.

Leveraging New Definitions of the LxVP SLiM To Discover Novel Calcineurin Regulators and Substrates

The Phosphoprotein Phosphatase Calcineurin (CN, PP2B, PP3) recognizes and binds to two short linear motifs (SLiMs), PxIxIT and LxVP, in its regulators and substrates. These interactions enable CN function in many key biological processes. The identification of SLiMs is difficult because of their short, degenerate sequence and often low binding affinity. Here we combine Structure Based Shape Complementarity (SBSC) analysis and proteome-wide affinity purification-mass spectrometry to identify PxIxIT and LxVP containing CN interactors to expand and thereby redefine the LxVP motif. We find that the new πφ-LxVx primary sequence defines an ensemble of binding competent confirmations and thus the binding on-rate, making it difficult to predict the LxVP binding strength from its sequence. Our analysis confirms existing and, more importantly, identifies novel CN interactors, substrates, and thus biological functions of CN.

Quantitative mapping of protein-peptide affinity landscapes using spectrally encoded beads

Transient, regulated binding of globular protein domains to Short Linear Motifs (SLiMs) in disordered regions of other proteins drives cellular signaling. Mapping the energy landscapes of these interactions is essential for deciphering and perturbing signaling networks but is challenging due to their weak affinities. We present a powerful technology (MRBLE-pep) that simultaneously quantifies protein binding to a library of peptides directly synthesized on beads containing unique spectral codes. Using MRBLE-pep, we systematically probe binding of calcineurin (CN), a conserved protein phosphatase essential for the immune response and target of immunosuppressants, to the PxIxIT SLiM. We discover that flanking residues and post-translational modifications critically contribute to PxIxIT-CN affinity and identify CN-binding peptides based on multiple scaffolds with a wide range of affinities. The quantitative biophysical data provided by this approach will improve computational modeling efforts, elucidate a broad range of weak protein-SLiM interactions, and revolutionize our understanding of signaling networks.