Changes In Protein-protein Interactions Research Articles

Exploring the Conformational Ensembles of Protein-Protein Complex with Transformer-Based Generative Model.

Protein-protein interactions are the basis of many protein functions, and understanding the contact and conformational changes of protein-protein interactions is crucial for linking the protein structure to biological function. Although difficult to detect experimentally, molecular dynamics (MD) simulations are widely used to study the conformational ensembles and dynamics of protein-protein complexes, but there are significant limitations in sampling efficiency and computational costs. In this study, a generative neural network was trained on protein-protein complex conformations obtained from molecular simulations to directly generate novel conformations with physical realism. We demonstrated the use of a deep learning model based on the transformer architecture to explore the conformational ensembles of protein-protein complexes through MD simulations. The results showed that the learned latent space can be used to generate unsampled conformations of protein-protein complexes for obtaining new conformations complementing pre-existing ones, which can be used as an exploratory tool for the analysis and enhancement of molecular simulations of protein-protein complexes.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes.

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Elexacaftor/VX-445–mediated CFTR interactome remodeling reveals differential correction driven by mutation-specific translational dynamics

Cystic fibrosis (CF) is one of the most prevalent lethal genetic diseases with over 2000 identified mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Pharmacological chaperones such as lumacaftor (VX-809), tezacaftor (VX-661), and elexacaftor (VX-445) treat mutation-induced defects by stabilizing CFTR and are called correctors. These correctors improve proper folding and thus facilitate processing and trafficking to increase the amount of functional CFTR on the cell surface. Yet, CFTR variants display differential responses to each corrector. Here, we report that variants P67L and L206W respond similarly to VX-809 but divergently to VX-445 with P67L exhibiting little rescue when treated with VX-445. We investigate the underlying cellular mechanisms of how CFTR biogenesis is altered by correctors in these variants. Affinity purification-mass spectrometry multiplexed with isobaric tandem mass tags was used to quantify CFTR protein-protein interaction changes between variants P67L and L206W. VX-445 facilitates unique proteostasis factor interactions especially in translation, folding, and degradation pathways in a CFTR variant-dependent manner. A number of these interacting proteins knocked down by siRNA, such as ribosomal subunit proteins, moderately rescued fully glycosylated P67L. Importantly, these knockdowns sensitize P67L to VX-445 and further enhance the trafficking correction of this variant. Partial inhibition of protein translation also mildly sensitizes P67L CFTR to VX-445 correction, supporting a role for translational dynamics in the rescue mechanism of VX-445. Our results provide a better understanding of VX-445 biological mechanism of action and reveal cellular targets that may sensitize nonresponsive CFTR variants to known and available correctors.

Exploring protein - protein interaction in cell physiology by reviewing the role of dynein-dynactin interaction as a representative example

"Protein-protein interactions are essential for the normal function of cells and are involved in various cellular processes. These interactions can occur through a variety of mechanisms, including hydrogen bonding, ionic interactions, and hydrophobic interactions. Changes in protein-protein interactions can alter the normal function of the cell and lead to various diseases. Understanding protein-protein interactions is important for the development of therapeutic approaches targeting these interactions for the treatment of diseases. In this article, I will discuss the role of protein-protein interactions in normal cellular function, the consequences of changes in these interactions, and the importance and significance of understanding these interactions by using the example of dynein-dynactin. Keywords: protein-protein interactions, dynein, dynactin, dysregulation, cargo transport "

Proteomic discovery of chemical probes that perturb protein complexes in human cells

Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.

Abstract 3847: Target identification of a multi-pass transmembrane G protein coupled receptor using limited-proteolysis coupled mass spectrometry (LiP-MS)

Abstract In drug discovery, target identification (ID) after phenotypic screens is a resource-intensive endeavor aimed to understand compound’s mechanism of action. Target ID for membrane proteins is particularly challenging due to hurdles such as poor protein solubility, instability and low expression levels. Addressing these hurdles, recent proteomics-based strategies allow to analyze proteins in their native environment, and do not require compound modification or genetic manipulation of target cell lines. Limited proteolysis coupled to mass spectrometry (LiP-MS) is a peptide-centric strategy that exploits structural protein alterations and steric hindrances induced by drug to detect drug-protein interactions, estimate potency (EC50) and predict binding sites across the proteome. Our previous reports (AACR 2020 and 2021) showed the applicability of LiP-MS on cytosolic proteins such as kinases and phosphatases. Here, LiP-MS workflow was adapted for multi-pass membrane proteins which are often underrepresented in global, unbiased target ID approaches. For protein targets in the cytosol or intracellular organelles, LiP-MS deploys a dose-response (DR) analysis recorded by incubating cell lysates with a given compound. Here, to monitor proteins in plasma membrane, live cells were treated with the compound in a DR curve for a short period of time before lysis and subsequent LiP-MS analysis. Live cell treatment allows to achieve target ID by 1) locking the receptor in its native conformation to detect the structural difference between the drug-bound and unbound forms and; 2) detecting structural changes in downstream signaling cascades resulting from changes in protein-protein interactions, post-translational modifications or other mechanisms. We evaluated the performance of this workflow using a tool compound (IAX16840) targeting specific G-protein coupled receptors. Our unbiased LiP scoring identified atypical chemokine receptor 3 (ACKR3), the primary known compound target, among the top 3 hits. Additional 82 proteins were perturbed in drug-treated samples based on the LiP scores. Mapping the altered peptides on the GPCR signaling network showed enrichment of perturbations in ACKR3 downstream pathways, providing additional evidence of ACKR3 binding. Taken together, we demonstrate that the live cell LiP-MS is applicable for target ID of multi-pass membrane proteins. The approach also provides a system-level view of protein and pathway perturbations downstream of a signaling protein (e.g. GPCR), revealing possible mechanisms of its endogenous action. Further optimization of LiP-MS protocol is sought to accommodate different classes of receptors. Citation Format: Martin Soste, Dominique Kamber, Nadine Dobberstein, Mirjam Zimmermann, Aurelien Rizk, Yuehan Feng, Yaroslav Nikolaev, Nigel Beaton. Target identification of a multi-pass transmembrane G protein coupled receptor using limited-proteolysis coupled mass spectrometry (LiP-MS). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3847.

Modification of the structural stability of human serum albumin in rheumatoid arthritis.

Differential scanning calorimetry (DSC) can indicate changes in structure and/or concentration of the most abundant proteins in a biological sample via heat denaturation curves (HDCs). In blood serum for example, HDC changes result from either concentration changes or altered thermal stabilities for 7-10 proteins and has previously been shown capable of differentiating between sick and healthy human subjects. Here, we compare HDCs and proteomic profiles of 50 patients experiencing joint-inflammatory symptoms, 27 of which were clinically diagnosed with rheumatoid arthritis (RA). The HDC of all 50 subjects appeared significantly different from expected healthy curves, but comparison of additional differences between the RA and the non-RA subjects allowed more specific understanding of RA samples. We used mass spectrometry (MS) to investigate the reasons behind the additional HDC changes observed in RA patients. The HDC differences do not appear to be directly related to differences in the concentrations of abundant serum proteins. Rather, the differences can be attributed to modified thermal stability of some fraction of the human serum albumin (HSA) proteins in the sample. By quantifying differences in the frequency of artificially induced post translational modifications (PTMs), we found that HSA in RA subjects had a much lower surface accessibility, indicating potential ligand or protein binding partners in certain regions that could explain the shift in HSA melting temperature in the RA HDCs. Several low abundance proteins were found to have significant changes in concentration in RA subjects and could be involved in or related to binding of HSA. Certain amino acid sites clusters were found to be less accessible in RA subjects, suggesting changes in HSA structure that may be related to changes in protein-protein interactions. These results all support a change in behavior of HSA which may give insight into mechanisms of RA pathology.

Mapping the SLP76 interactome in T cells lacking each of the GRB2-family adaptors reveals molecular plasticity of the TCR signaling pathway.

The propagation and diversification of signals downstream of the T cell receptor (TCR) involve several adaptor proteins that control the assembly of multimolecular signaling complexes (signalosomes). The global characterization of changes in protein-protein interactions (PPI) following genetic perturbations is critical to understand the resulting phenotypes. Here, by combining genome editing techniques in T cells and interactomics studies based on affinity purification coupled to mass spectrometry (AP-MS) analysis, we determined and quantified the molecular reorganization of the SLP76 interactome resulting from the ablation of each of the three GRB2-family adaptors. Our data showed that the absence of GADS or GRB2 induces a major remodeling of the PPI network associated with SLP76 following TCR engagement. Unexpectedly, this PPI network rewiring minimally affects proximal molecular events of the TCR signaling pathway. Nevertheless, during prolonged TCR stimulation, GRB2- and GADS-deficient cells displayed a reduced level of activation and cytokine secretion capacity. Using the canonical SLP76 signalosome, this analysis highlights the plasticity of PPI networks and their reorganization following specific genetic perturbations.

Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

Dynamic changes in protein-protein interaction (PPI) networks underlie all physiological cellular functions and drive devastating human diseases. Profiling PPI networks can, therefore, provide critical insight into disease mechanisms and identify new drug targets. Kinases are regulatory nodes in many PPI networks; yet, facile methods to systematically study kinase interactome dynamics are lacking. We describe kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic method for rapid and highly multiplexed profiling of endogenous kinase interactomes. Using kiCCA, we identified 1,154 PPIs of 238 kinases across 18 diverse cancer lines, quantifying context-dependent kinase interactome changes linked to cancer type, plasticity, and signaling states, thereby assembling an extensive knowledgebase for cell signaling research. We discovered drug target candidates, including an endocytic adapter-associated kinase (AAK1) complex that promotes cancer cell epithelial-mesenchymal plasticity and drug resistance. Our data demonstrate the importance of kinase interactome dynamics for cellular signaling in health and disease.

Differential chromatin binding preference is the result of the neo-functionalization of the TB1 clade of TCP transcription factors in grasses.

The understanding of neo-functionalization of plant transcription factors (TFs) after gene duplication has been extensively focused on changes in protein-protein interactions, the expression pattern of TFs, or the variation of cis-elements bound by TFs. Yet, the main molecular role of a TF, that is, its specific chromatin binding for the direct regulation of target gene expression, continues to be mostly overlooked. Here, we studied the TB1 clade of the TEOSINTE BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTORS (TCP) TF family within the grasses (Poaceae). We identified an Asp/Gly amino acid replacement within the TCP domain, originated within a paralog TIG1 clade exclusive for grasses. The heterologous expression of Zea mays TB1 and its two paralogs BAD1 and TIG1 in Arabidopsis mutant plants lacking the TB1 ortholog BRC1 revealed distinct functions in plant development. Notably, the Gly acquired in the TIG1 clade does not impair TF homodimerization and heterodimerization, while it modulates chromatin binding preferences. We found that invivo TF recognition of target promoters depends on this Asp/Gly mutation and directly impacts downstream gene expression and subsequent plant development. These results provided new insights into how natural selection fine-tunes gene expression regulation after duplication of TFs to define plant architecture.

Changes in the C-terminal, N-terminal, and histidine regions of amelogenin reveal the role of oligomer quaternary structure on adsorption and hydroxyapatite mineralization.

Adsorption interactions between amelogenin and calcium phosphate minerals are believed to be important to amelogenin's function in enamel formation, however, the role of specific amino acid residues and domains within the protein in controlling adsorption is not well known. We synthesized "mechanistic probes" by systematically removing charged regions of amelogenin in order to elucidate their roles. The probes included amelogenin without the charged residues in the N-terminus (SEKR), without two, three, or eight histidines (H) in the central protein region (H2, H3, H8), or without the C-terminal residues (Delta). In-situ atomic force microscopy (AFM) adsorption studies onto hydroxyapatite (HAP) single crystals confirmed that the C-terminus was the dominant domain in promoting adsorption. We propose that subtle changes in protein-protein interactions for proteins with histidines and N-terminal residues removed resulted in changes in the oligomer quaternary size and structure that also affected protein adsorption. HAP mineralization studies revealed that the oligomer-HAP binding energy and protein layer thickness were factors in controlling the amorphous calcium phosphate (ACP) to HAP induction time. Our studies with mechanistic probes reveal the importance of the oligomer quaternary structure in controlling amelogenin adsorption and HAP mineralization.

Effect of Insulin and Pioglitazone on Protein Phosphatase 2A Interaction Partners in Primary Human Skeletal Muscle Cells Derived from Obese Insulin-Resistant Participants.

Skeletal muscle insulin resistance is a major contributor to type-2 diabetes (T2D). Pioglitazone is a potent insulin sensitizer of peripheral tissues by targeting peroxisome proliferator-activated receptor gamma. Pioglitazone has been reported to protect skeletal muscle cells from lipotoxicity by promoting fatty acid mobilization and insulin signaling. However, it is unclear whether pioglitazone increases insulin sensitivity through changes in protein-protein interactions involving protein phosphatase 2A (PP2A). PP2A regulates various cell signaling pathways such as insulin signaling. Interaction of the catalytic subunit of PP2A (PP2Ac) with protein partners is required for PP2A specificity and activity. Little is known about PP2Ac partners in primary human skeletal muscle cells derived from lean insulin-sensitive (Lean) and obese insulin-resistant (OIR) participants. We utilized a proteomics method to identify PP2Ac interaction partners in skeletal muscle cells derived from Lean and OIR participants, with or without insulin and pioglitazone treatments. In this study, 216 PP2Ac interaction partners were identified. Furthermore, 26 PP2Ac partners exhibited significant differences in their interaction with PP2Ac upon insulin treatments between the two groups. Multiple pathways and molecular functions are significantly enriched for these 26 interaction partners, such as nonsense-mediated decay, metabolism of RNA, RNA binding, and protein binding. Interestingly, pioglitazone restored some of these abnormalities. These results provide differential PP2Ac complexes in Lean and OIR in response to insulin/pioglitazone, which may help understand molecular mechanisms underpinning insulin resistance and the insulin-sensitizing effects of pioglitazone treatments, providing multiple targets in various pathways to reverse insulin resistance and prevent and/or manage T2D with less drug side effects.

Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer.

The Harvey rat sarcoma (HRAS) proto-oncogene belongs to the RAS family and is one of the pathogenic genes that cause cancer. Deleterious nsSNPs might have adverse consequences at the protein level. This study aimed to investigate deleterious nsSNPs in the HRAS gene in predicting structural alterations associated with mutants that disrupt normal protein-protein interactions. Functional and structural analysis was employed in analyzing the HRAS nsSNPs. Putative post-translational modification sites and the changes in protein-protein interactions, which included a variety of signal cascades, were also investigated. Five different bioinformatics tools predicted 33 nsSNPs as "pathogenic" or "harmful". Stability analysis predicted rs1554885139, rs770492627, rs1589792804, rs730880460, rs104894227, rs104894227, and rs121917759 as unstable. Protein-protein interaction analysis revealed that HRAS has a hub connecting three clusters consisting of 11 proteins, and changes in HRAS might cause signal cascades to dissociate. Furthermore, Kaplan-Meier bioinformatics analyses indicated that the HRAS gene deregulation affected the overall survival rate of patients with breast cancer, leading to prognostic significance. Thus, based on these analyses, our study suggests that the reported nsSNPs of HRAS may serve as potential targets for different proteomic studies, diagnoses, and therapeutic interventions focusing on cancer.

Functional Impact and Regulation of Alternative Splicing in Mouse Heart Development and Disease.

Alternative splicing (AS) plays a major role in the generation of transcript diversity. In the heart, roles have been described for some AS variants, but the global impact and regulation of AS patterns are poorly understood. Here, we studied the AS profiles in heart disease, their relationship with heart development, and the regulatory mechanisms controlling AS dynamics in the mouse heart. We found that AS profiles characterized the different groups and that AS and gene expression changes affected independent genes and biological functions. Moreover, AS changes, specifically in heart disease, were associated with potential protein-protein interaction changes. While developmental transitions were mainly driven by the upregulation of MBNL1, AS changes in disease were driven by a complex regulatory network, where PTBP1 played a central role. Indeed, PTBP1 over-expression was sufficient to induce cardiac hypertrophy and diastolic dysfunction, potentially by perturbing AS patterns.

Reconstitution of Membrane-associated Components of a G-protein Signaling Pathway on Membrane-coated Nanoparticles (Lipobeads).

G-protein coupled signaling pathways are organized into multi-protein complexes called signalosomes that are located within and on cellular membranes. We describe the use of silica nanoparticles coated with a unilamellar phospholipid bilayer (lipobeads) to reconstitute the activated photoreceptor G-protein α-subunit (Gtα*) with its cognate effector (phosphodiesterase-6; PDE6) for biochemical and structural studies of the activation mechanism regulating this GPCR signaling pathway. Lipobeads are prepared by resuspending dried-down phospholipid mixtures with monodisperse 70 nm silica particles, followed by extrusion through a 100 nm membrane filter. This uniform and supported liposomal preparation is easily sedimented, permitting the separation of soluble from membrane-associated proteins. Upon loading lipobeads with Gtα* and PDE6, we find that activation of PDE6 catalysis by Gtα* occurs much more efficiently than in the absence of membranes. Chemical cross-linking of membrane-confined proteins allows detection of changes in protein-protein interactions, resulting from G-protein activation of PDE6. The advantages of using lipobeads over partially purified membrane preparations or traditional liposomal preparations are generally applicable to the study of other membrane-confined signal transduction pathways.

Mass spectrometry-based protein-protein interaction networks for the study of human diseases.

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.

Using Magnetic Nanoparticles and Protein–Protein Interactions to Measure pH at the Nanoscale

Dynamic magnetization of magnetic nanoparticles provides ready access to passive sensing in nanometer scale environments. Here, we use commercially available streptavidin labeled 100 nm magnetic nanoparticles to develop a nanoscale pH sensor. The sensor works based on pH dependent binding of streptavidin to rat tail type-I collagen. The major protein-protein interactions in this case are well rationalized from zeta potential/mobility measurements, which yield a good measure of the relative pIs of the proteins. The pI is the pH at which the protein has zero overall surface charge. Nanoparticle streptavidin has a stable negative charge over the entire range of the measurements from pH 6 to 7.5 (pI ~2), whereas collagen has a steadily increasing positive charge as the pH drops below 7.5 (pI 7.8). Interactions between protein1 and NP-protein2 based on an initial pI difference allow sophisticated nanoscale sensors to be constructed that respond to small changes in pH via corresponding systematic changes in protein-protein interactions. More generally, any type of protein-protein interaction can in principle be measured using magnetic nanoparticles.

A Unified Workflow to Identify Quaternary Structures and Changes in Protein-protein Interactions from Crosslinking-based Mass Spectrometry

Urinary tract infections (UTIs) constitute a tremendous public health burden estimated at $2.5 billion annually in the United States alone. The biofilm producing bacterium Escherichia coli (E. coli) is by far the most frequent causative agent of UTIs and is increasingly becoming antibiotic resistant. In order to develop more effective antimicrobial therapies, we must first understand the mechanisms by which these bacteria invade the host and defend themselves. Recently developed crosslinking-based mass spectrometry (XL-MS) approaches have the potential to revolutionize high-throughput mapping of protein-protein interactions (PPIs) due to: their lower false discovery rate, their ability to detect weak or transient interactions that may be missed with techniques like immuno-precipitation or affinity purification, and their ability to be applied in vivo under physiological conditions. Our goal is to further optimize the information that can be obtained from XL-MS data, by not only determining the identities of the residues in each protein that are interacting with partner proteins, but additionally, by building three-dimensional models of the interacting protein complexes informed by the XL-MS data. This would provide us with a powerful additional source of information regarding PPIs in any system of interest, allowing us to supplement proteomic profiling of microbial communities with experimentally derived, quaternary structural models of the identified statistically significant PPIs. Preliminary applications of our approaches to E. coli UTI89 biofilms provided quaternary structures consistent with existing high-resolution experimental data (where available), and also information on dozens of additional complexes potentially involved in biofilm development. We expect application of the tools developed during the course of this work will inform antimicrobial therapeutic development by allowing rapid identification of statistically key nodes in the protein-protein interactome of pathogenic bacterial strains such as E. coli UTI89.

Casposase structure and the mechanistic link between DNA transposition and spacer acquisition by CRISPR-Cas.

Key to CRISPR-Cas adaptive immunity is maintaining an ongoing record of invading nucleic acids, a process carried out by the Cas1-Cas2 complex that integrates short segments of foreign genetic material (spacers) into the CRISPR locus. It is hypothesized that Cas1 evolved from casposases, a novel class of transposases. We show here that the Methanosarcina mazei casposase can integrate varied forms of the casposon end in vitro, and recapitulates several properties of CRISPR-Cas integrases including site-specificity. The X-ray structure of the casposase bound to DNA representing the product of integration reveals a tetramer with target DNA bound snugly between two dimers in which single-stranded casposon end binding resembles that of spacer 3'-overhangs. The differences between transposase and CRISPR-Cas integrase are largely architectural, and it appears that evolutionary change involved changes in protein-protein interactions to favor Cas2 binding over tetramerization; this in turn led to preferred integration of single spacers over two transposon ends.

Resilience of BST-2/Tetherin structure to single amino acid substitutions.

Human tetherin, also known as BST-2 or CD317, is a dimeric, extracellular membrane-bound protein that consists of N and C terminal membrane anchors connected by an extracellular domain. BST-2 is involved in binding enveloped viruses, such as HIV, and inhibiting viral release in addition to a role in NF-kB signaling. Viral tethering by tetherin can be disrupted by the interaction with Vpu in HIV-1 in addition to other viral proteins. The structural mechanism of tetherin function is not clear and the effects of human tetherin mutations identified by sequencing consortiums are not known. To address this gap in the knowledge, we used data from the Ensembl database to construct and model known human missense mutations within the ectodomain to investigate how the structure of the ectodomain influences function. From the data, we identified an island of sequence stability within the ectodomain, which corresponds to a functionally and structurally important region identified in previous biochemical and biophysical studies. Most of the modeled mutations had little effect on the structure of the dimer and the coiled-coil, suggesting that the coiled-coil compensates for changes in primary structure. Thus, many of the functional defects observed in previous studies may not be due to changes in tetherin structure, but rather, due to in changes in protein-protein interactions or in aspects of tetherin not currently understood. The lack of structural effects by mutations known to decrease function further illustrates the need for more study of the structure-function connection for this system. Finally, apparent flexibility in tetherin sequence may allow for greater anti-viral activities with a larger number of viruses by reducing specific interactions with anti-tetherin proteins, while maintaining virus restriction.