Molecular mimicry of short linear interaction motifs has emerged as a key mechanism for viral proteins binding host domains and hijacking host cell processes. Here, we examine the role of RNA-virus sequence diversity in the dynamics of the virus-host interface, by analyzing the uniquely vast sequence record of viable SARS-CoV-2 species with focus on the multi-functional nucleocapsid protein. We observe the abundant presentation of motifs encoding several essential host protein interactions, alongside a majority of possibly non-functional and randomly occurring motif sequences absent in subsets of viable virus species. A large number of motifs emerge ex nihilo through transient mutations relative to the ancestral consensus sequence. The observed mutational landscape implies an accessible motif space that spans at least 25% of known eukaryotic motifs. This reveals motif mimicry as a highly dynamic process with the capacity to broadly explore host motifs, allowing the virus to rapidly evolve the virus-host interface.

Interactions between proteins are fundamental for every biological process and especially important in cell signaling pathways. Biochemical techniques that evaluate these protein-protein interactions (PPIs), such as in vitro pull downs and coimmunoprecipitations, have become popular in most laboratories and are essential to identify and validate novel protein binding partners. Most PPIs occur through small domains or motifs, which are challenging and laborious to map by using standard biochemical approaches because they generally require the cloning of several truncation mutants. Moreover, these classical methodologies provide limited resolution of the interacting interface. Here, we describe the development of an alternative technique to overcome these limitations termed "Protein Domain mapping using Yeast 2 Hybrid-Next Generation Sequencing" (DoMY-Seq), which leverages both yeast two-hybrid and next-generation sequencing techniques. In brief, our approach involves creating a library of fragments derived from an open reading frame of interest and enriching for the interacting fragments using a yeast two-hybrid reporter system. Next-generation sequencing is then subsequently employed to read and map the sequence of the interacting fragment, yielding a high-resolution plot of the binding interface. We optimized DoMY-Seq by taking advantage of the well-described and high-affinity interaction between KRAS and CRAF, and we provide high-resolution domain mapping on this and other protein-interacting pairs, including CRAF-MEK1, RIT1-RGL3, and p53-MDM2. Thus, DoMY-Seq provides an unbiased alternative method to rapidly identify the domains involved in PPIs by advancing the use of yeast two-hybrid technology.

Mitogen-activated protein kinases (MAPK) are broadly used regulators of cellular signaling. However, how these enzymes can be involved in such a broad spectrum of physiological functions is not understood. Systematic discovery of MAPK networks both experimentally and in silico has been hindered because MAPKs bind to other proteins with low affinity and mostly in less-characterized disordered regions. We used a structurally consistent model on kinase-docking motif interactions to facilitate the discovery of short functional sites in the structurally flexible and functionally under-explored part of the human proteome and applied experimental tools specifically tailored to detect low-affinity protein-protein interactions for their validation in vitro and in cell-based assays. The combined computational and experimental approach enabled the identification of many novel MAPK-docking motifs that were elusive for other large-scale protein-protein interaction screens. The analysis produced an extensive list of independently evolved linear binding motifs from a functionally diverse set of proteins. These all target, with characteristic binding specificity, an ancient protein interaction surface on evolutionarily related but physiologically clearly distinct three MAPKs (JNK, ERK, and p38). This inventory of human protein kinase binding sites was compared with that of other organisms to examine how kinase-mediated partnerships evolved over time. The analysis suggests that most human MAPK-binding motifs are surprisingly new evolutionarily inventions and newly found links highlight (previously hidden) roles of MAPKs. We propose that short MAPK-binding stretches are created in disordered protein segments through a variety of ways and they represent a major resource for ancient signaling enzymes to acquire new regulatory roles.

Alternative inclusion of exons increases the functional diversity of proteins. Among alternatively spliced exons, tissue-specific exons play a critical role in maintaining tissue identity. This raises the question of how tissue-specific protein-coding exons influence protein function. Here we investigate the structural, functional, interaction, and evolutionary properties of constitutive, tissue-specific, and other alternative exons in human. We find that tissue-specific protein segments often contain disordered regions, are enriched in posttranslational modification sites, and frequently embed conserved binding motifs. Furthermore, genes containing tissue-specific exons tend to occupy central positions in interaction networks and display distinct interaction partners in the respective tissues, and are enriched in signaling, development, and disease genes. Based on these findings, we propose that tissue-specific inclusion of disordered segments that contain binding motifs rewires interaction networks and signaling pathways. In this way, tissue-specific splicing may contribute to functional versatility of proteins and increases the diversity of interaction networks across tissues.

LRRs (leucine rich repeats) are present in over 14,000 proteins. Non-LRR, island regions (IRs) interrupting LRRs are widely distributed. The present article reviews 19 families of LRR proteins having non-LRR IRs (LRR@IR proteins) from various plant species. The LRR@IR proteins are LRR-containing receptor-like kinases (LRR-RLKs), LRR-containing receptor-like proteins (LRR-RLPs), TONSOKU/BRUSHY1, and MJK13.7; the LRR-RLKs are homologs of TMK1/Rhg4, BRI1, PSKR, PSYR1, Arabidopsis At1g74360, and RPK2, while the LRR-RLPs are those of Cf-9/Cf-4, Cf-2/Cf-5, Ve, HcrVf, RPP27, EIX1, clavata 2, fascinated ear2, RLP2, rice Os10g0479700, and putative soybean disease resistance protein. The LRRs are intersected by single, non-LRR IRs; only the RPK2 homologs have two IRs. In most of the LRR-RLKs and LRR-RLPs, the number of repeat units in the preceding LRR block (N1) is greater than the number of the following block (N2); N1 » N2 in which N1 is variable in the homologs of individual families, while N2 is highly conserved. The five families of the LRR-RLKs except for the RPK2 family show N1 = 8 - 18 and N2 = 3 - 5. The nine families of the LRR-RLPs show N1 = 12 - 33 and N2 = 4; while N1 = 6 and N2 = 4 for the rice Os10g0479700 family and the N1 = 4 - 28 and N2 = 4 for the soybean protein family. The rule of N1 » N2 might play a common, significant role in ligand interaction, dimerization, and/or signal transduction of the LRR-RLKs and the LRR-RLPs. The structure and evolution of the LRR domains with non-LRR IRs and their proteins are also discussed.

PDZ motifs are protein-protein interaction domains that often bind to COOH-terminal peptide sequences. The two PDZ proteins characterized in skeletal muscle, syntrophin and neuronal nitric oxide synthase, occur in the dystrophin complex, suggesting a role for PDZ proteins in muscular dystrophy. Here, we identify actinin-associated LIM protein (ALP), a novel protein in skeletal muscle that contains an NH2-terminal PDZ domain and a COOH-terminal LIM motif. ALP is expressed at high levels only in differentiated skeletal muscle, while an alternatively spliced form occurs at low levels in the heart. ALP is not a component of the dystrophin complex, but occurs in association with alpha-actinin-2 at the Z lines of myofibers. Biochemical and yeast two-hybrid analyses demonstrate that the PDZ domain of ALP binds to the spectrin-like motifs of alpha-actinin-2, defining a new mode for PDZ domain interactions. Fine genetic mapping studies demonstrate that ALP occurs on chromosome 4q35, near the heterochromatic locus that is mutated in fascioscapulohumeral muscular dystrophy.

Effector proteins are bacterial virulence factors secreted directly into host cells and, through extensive interactions with host proteins, rewire host signaling pathways to the advantage of the pathogen. Despite the crucial role of globular domains as mediators of protein-protein interactions (PPIs), previous structural studies of bacterial effectors are primarily focused on individual domains, rather than domain-mediated PPIs, which limits their ability to uncover systems-level molecular recognition principles governing host-bacteria interactions. Here, we took an interaction-centric approach and systematically examined the potential of structural components within bacterial proteins to engage in or target eukaryote-specific domain-domain interactions (DDIs). Our results indicate that: 1) effectors are about six times as likely as non-effectors to contain host-like domains that mediate DDIs exclusively in eukaryotes; 2) the average domain in effectors is about seven times as likely as that in non-effectors to co-occur with DDI partners in eukaryotes rather than in bacteria; and 3) effectors are about nine times as likely as non-effectors to contain bacteria-exclusive domains that target host domains mediating DDIs exclusively in eukaryotes. Moreover, in the absence of host-like domains or among pathogen proteins without domain assignment, effectors harbor a higher variety and density of short linear motifs targeting host domains that mediate DDIs exclusively in eukaryotes. Our study lends novel quantitative insight into the structural basis of effector-induced perturbation of host-endogenous PPIs and may aid in the design of selective inhibitors of host-pathogen interactions.

Cohesin is a macromolecular complex that links sister chromatids together at the metaphase plate during mitosis. The links are formed during DNA replication and destroyed during the metaphase-to-anaphase transition. In budding yeast, the 14S cohesin complex comprises at least two classes of SMC (structural maintenance of chromosomes) proteins - Smc1 and Smc3 - and two SCC (sister-chromatid cohesion) proteins - Scc1 and Scc3. The exact function of these proteins is unknown.

The goal of text mining is to make the information conveyed in scientific publications accessible to structured search and automatic analysis. Two important subtasks of text mining are entity mention normalization - to identify biomedical objects in text - and extraction of qualified relationships between those objects. We describe a method for identifying genes and relationships between proteins.

Cholesterol is essential for the proper organization of the biological membrane. Therefore, predicting which proteins can bind cholesterol is important in understanding how proteins participate in lateral membrane organization. In this study, a simple bioinformatics approach was used to establish whether MPP1, a member of the MAGUK protein family, is capable of binding cholesterol. Modelled and experimentally-validated fragment structures were mined from online resources and searched for CRAC and CRAC-like motifs. Several of these motifs were found in the primary structure of MPP1, and these were structurally visualized to see whether they localized to the protein surface. Since all of the CRAC and CRAC-like motifs were found at the surface of MPP1 domains, in silico docking experiments were performed to assess the possibility of interaction between CRAC motifs and cholesterol. The results obtained show that MPP1 can bind cholesterol via CRAC and CRAC-like motifs with moderate to high affinity (KI in the nano- to micro-molar range). It was also found that palmitoylation-mimicking mutations (C/F or C/M) did not affect the affinity of MPP1 towards cholesterol. Data presented here may help to understand at least one of the molecular mechanisms via which MPP1 affects lateral organization of the membrane.

Diacylglycerol kinase (DGK) α, which is activated by Ca(2+), contains a recoverin homology (RVH) domain, tandem repeats of two Ca(2+)-binding EF-hand motifs, two cysteine-rich C1 domains and the catalytic domain. We previously found that a DGKα mutant lacking the RVH domain and EF-hands was constitutively active and that the N-terminal region of DGKα, consisting of the RVH domain and EF-hand motifs, interacted intra-molecularly with the C-terminal region containing the C1 and catalytic domains. In this study, we narrowed down the interaction regions of DGKα. At the C-terminal region, the C1 domains are responsible for the intra-molecular interaction. At the N-terminal region, the EF-hand motifs mainly contribute to the interaction. Moreover, using highly purified EF-hand motifs and C1 domains, we demonstrate that they directly bind to each other. The co-precipitation of these two domains was clearly attenuated by the addition of Ca(2+). These results indicate that the Ca(2+)-induced dissociation of the intra-molecular interaction between the EF-hand motifs and the C1 domains of DGKα is the key event that regulates the activity of the enzyme.

We have previously shown that the V-ATPase a2-subunit isoform interacts specifically, and in an intra-endosomal acidification-dependent manner, with the Arf-GEF ARNO. In the present study, we examined the molecular mechanism of this interaction using synthetic peptides and purified recombinant proteins in protein-association assays. In these experiments, we revealed the involvement of multiple sites on the N-terminus of the V-ATPase a2-subunit (a2N) in the association with ARNO. While six a2N-derived peptides interact with wild-type ARNO, only two of them (named a2N-01 and a2N-03) bind to its catalytic Sec7-domain. However, of these, only the a2N-01 peptide (MGSLFRSESMCLAQLFL) showed specificity towards the Sec7-domain compared to other domains of the ARNO protein. Surface plasmon resonance kinetic analysis revealed a very strong binding affinity between this a2N-01 peptide and the Sec7-domain of ARNO, with dissociation constant KD=3.44x10(-7) M, similar to the KD=3.13x10(-7) M binding affinity between wild-type a2N and the full-length ARNO protein. In further pull-down experiments, we also revealed the involvement of multiple sites on ARNO itself in the association with a2N. However, while its catalytic Sec7-domain has the strongest interaction, the PH-, and PB-domains show much weaker binding to a2N. Interestingly, an interaction of the a2N to a peptide corresponding to ARNO's PB-domain was abolished by phosphorylation of ARNO residue Ser392. The 3D-structures of the non-phosphorylated and phosphorylated peptides were resolved by NMR spectroscopy, and we have identified rearrangements resulting from Ser392 phosphorylation. Homology modeling suggests that these alterations may modulate the access of the a2N to its interaction pocket on ARNO that is formed by the Sec7 and PB-domains. Overall, our data indicate that the interaction between the a2-subunit of V-ATPase and ARNO is a complex process involving various binding sites on both proteins. Importantly, the binding affinity between the a2-subunit and ARNO is in the same range as those previously reported for the intramolecular association of subunits within V-ATPase complex itself, indicating an important cell biological role for the interaction between the V-ATPase and small GTPase regulatory proteins.

Neuronal nitric oxide synthase (nNOS) is concentrated at synaptic junctions in brain and motor endplates in skeletal muscle. Here, we show that the N-terminus of nNOS, which contains a PDZ protein motif, interacts with similar motifs in postsynaptic density-95 protein (PSD-95) and a related novel protein, PSD-93.nNOS and PSD-95 are coexpressed in numerous neuronal populations, and a PSD-95/nNOS complex occurs in cerebellum. PDZ domain interactions also mediate binding of nNOS to skeletal muscle syntrophin, a dystrophin-associated protein. nNOS isoforms lacking a PDZ domain, identified in nNOSdelta/delta mutant mice, do not associate with PSD-95 in brain or with skeletal muscle sarcolemma. Interaction of PDZ-containing domains therefore mediates synaptic association of nNOS and may play a more general role in formation of macromolecular signaling complexes.

The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75% at sensitivity of 10%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.

Identification of small molecule ligands that bind to proteins is a critical step in drug discovery. Computational methods have been developed to accelerate the prediction of protein-ligand binding, but often depend on 3D protein structures. As only a limited number of protein 3D structures have been resolved, the ability to predict protein-ligand interactions without relying on a 3D representation would be highly valuable. We use an interpretable confidence-rated boosting algorithm to predict protein-ligand interactions with high accuracy from ligand chemical substructures and protein 1D sequence motifs, without relying on 3D protein structures. We compare several protein motif definitions, assess generalization of our model's predictions to unseen proteins and ligands, demonstrate recovery of well established interactions and identify globally predictive protein-ligand motif pairs. By bridging biological and chemical perspectives, we demonstrate that it is possible to predict protein-ligand interactions using only motif-based features and that interpretation of these features can reveal new insights into the molecular mechanics underlying each interaction. Our work also lays a foundation to explore more predictive feature sets and sophisticated machine learning approaches as well as other applications, such as predicting unintended interactions or the effects of mutations.

Cotton leaf curl disease (CLCuD) caused by viruses of genus Begomovirus is a major constraint to cotton (Gossypium hirsutum) production in many cotton-growing regions of the world. Symptoms of the disease are caused by Cotton leaf curl Multan betasatellite (CLCuMB) that encodes a pathogenicity determinant protein, βC1. Here, we report the identification of interacting regions in βC1 protein by using computational approaches including sequence recognition, and binding site and interface prediction methods. We show the domain-level interactions based on the structural analysis of G. hirsutum SnRK1 protein and its domains with CLCuMB-βC1. To verify and validate the in silico predictions, three different experimental approaches, yeast two hybrid, bimolecular fluorescence complementation and pull down assay were used. Our results showed that ubiquitin-associated domain (UBA) and autoinhibitory sequence (AIS) domains of G. hirsutum-encoded SnRK1 are involved in CLCuMB-βC1 interaction. This is the first comprehensive investigation that combined in silico interaction prediction followed by experimental validation of interaction between CLCuMB-βC1 and a host protein. We demonstrated that data from computational biology could provide binding site information between CLCuD-associated viruses/satellites and new hosts that lack known binding site information for protein-protein interaction studies. Implications of these findings are discussed.

Inhibition of immune checkpoint receptor Programmed Death-1 (PD-1) via monoclonal antibodies is an established anticancer immunotherapeutic approach. This treatment has been largely successful; however, its high cost demands equally effective, more affordable alternatives. To date, the development of drugs targeting downstream players in the PD-1-dependent signaling pathway has been hampered by our poor understanding of the molecular details of the intermolecular interactions involved in the pathway. Activation of PD-1 leads to phosphorylation of two signaling motifs located in its cytoplasmic domain, the immune tyrosine inhibitory motif (ITIM) and immune tyrosine switch motif (ITSM), which recruit and activate protein tyrosine phosphatase SHP2. This interaction is mediated by the two Src homology 2 (SH2) domains of SHP2, termed N-SH2 and C-SH2, which recognize phosphotyrosines pY223 and pY248 of ITIM and ITSM, respectively. SHP2 then propagates the inhibitory signal, ultimately leading to suppression of T cell functionality. In order to facilitate mechanistic structural studies of this signaling pathway, we report the resonance assignments of the complexes formed by the signaling motifs of PD-1 and the SH2 domains of SHP2.

Genetic testing for BRCA1 and BRCA2 genes has led to the identification of many unique variants of uncertain significance (VUS). Multifactorial likelihood models that predict the odds ratio for VUS in favor or against cancer causality, have been developed, but their use is conditioned by the amount of necessary data, which are difficult to obtain if a variant is rare. As an alternative, variants mapping to the coding regions can be examined using in vitro functional assays. BRCA1 and BRCA2 proteins promote genome protection by interacting with different proteins. In this study, we assessed the functional effect of two sets of variants in BRCA genes by exploiting the green fluorescent protein (GFP)-reassembly in vitro assay, which was set-up to test the BRCA1/BARD1, BRCA1/UbcH5a, and BRCA2/DSS1 interactions. Based on the findings observed for the validation panels of previously classified variants, BRCA1/UbcH5a and BRCA2/DSS1 binding assays showed 100% sensitivity and specificity in identifying pathogenic and non-pathogenic variants. While the actual efficiency of these assays in assessing the clinical significance of BRCA VUS has to be verified using larger validation panels, our results suggest that the GFP-reassembly assay is a robust method to identify variants affecting normal protein functioning and contributes to the classification of VUS.

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 postsynaptic region is the receiving part of the synapse comprising thousands of proteins forming an elaborate and dynamically changing network indispensable for the molecular mechanisms behind fundamental phenomena such as learning and memory. Despite the growing amount of information about individual protein-protein interactions (PPIs) in this network, these data are mostly scattered in the literature or stored in generic databases that are not designed to display aspects that are fundamental to the understanding of postsynaptic functions. To overcome these limitations, we collected postsynaptic PPIs complemented by a high amount of detailed structural and biological information and launched a freely available resource, the Postsynaptic Interaction Database (PSINDB), to make these data and annotations accessible. PSINDB includes tens of thousands of binding regions together with structural features, mediating and regulating the formation of PPIs, annotated with detailed experimental information about each interaction. PSINDB is expected to be useful for various aspects of molecular neurobiology research, from experimental design to network and systems biology-based modeling and analysis of changes in the protein network upon various stimuli. Database URL https://psindb.itk.ppke.hu/.