Serine proteinase inhibitors (serpins), typically fold to a metastable native state and undergo a major conformational change in order to inhibit target proteases. However, conformational lability of the native serpin fold renders them susceptible to misfolding and aggregation, and underlies misfolding diseases such as α1-antitrypsin deficiency. Serpin specificity towards its protease target is dictated by its flexible and solvent exposed reactive centre loop (RCL), which forms the initial interaction with the target protease during inhibition. Previous studies have attempted to alter the specificity by mutating the RCL to that of a target serpin, but the rules governing specificity are not understood well enough yet to enable specificity to be engineered at will. In this paper, we use conserpin, a synthetic, thermostable serpin, as a model protein with which to investigate the determinants of serpin specificity by engineering its RCL. Replacing the RCL sequence with that from α1-antitrypsin fails to restore specificity against trypsin or human neutrophil elastase. Structural determination of the RCL-engineered conserpin and molecular dynamics simulations indicate that, although the RCL sequence may partially dictate specificity, local electrostatics and RCL dynamics may dictate the rate of insertion during protease inhibition, and thus whether it behaves as an inhibitor or a substrate. Engineering serpin specificity is therefore substantially more complex than solely manipulating the RCL sequence, and will require a more thorough understanding of how conformational dynamics achieves the delicate balance between stability, folding and function required by the exquisite serpin mechanism of action.
The enzyme glutamate decarboxylase (GAD) produces the neurotransmitter GABA, using pyridoxal-5'-phosphate. GAD exists as two isoforms, GAD65 and GAD67. Only GAD65 acts as a major autoantigen, with its autoantibodies frequently found in type 1 diabetes and other autoimmune diseases. Here we characterize the structure and dynamics of GAD65 and its interaction with the autoimmune polyendocrine syndrome type 2-associated autoantibody b96.11. Combining hydrogen-deuterium exchange mass spectrometry (HDX), X-ray crystallography, cryo-electron microscopy and computational approaches, we dissect the conformational dynamics of the inactive apo- and the active holo-forms of GAD65, as well as the structure of the GAD65-autoantibody complex. HDX reveals the time-resolved, local dynamics that accompany autoinactivation, with the catalytic loop playing a key role in promoting collective dynamics at the interface between CTD and PLP domains. In the GAD65-b96.11 complex, heavy chain CDRs dominate the interaction, with the relatively long CDRH3 at the interface centre and uniquely bridging the GAD65 dimer via extensive electrostatic interactions with the 260 PEVKEK 265 motif. The autoantibody bridges structural elements on GAD65 that contribute to conformational change in GAD65, thus connecting the unique and intrinsic conformational flexibility that governs the autoinactivation mechanism of the enzyme to its autoantigenicity. The intrinsic dynamics, rather than sequence differences within epitopes, appear to be responsible for the contrasting autoantigenicities of GAD65 and GAD67. Our data thus reveal insights into the structural and dynamic differences between GAD65 and GAD67 that dictate their contrasting autoantibody reactivities, provide a new structural rationalisation for the nature of the autoimmune response to GAD65, and may have broader implications for antigenicity in general.
Abstract Abacavir is an antiretroviral drug used to reduce human immunodeficiency virus (HIV) replication and decrease the risk of developing acquired immune deficiency syndrome (AIDS). However, its therapeutic value is diminished by the fact that it is associated with drug hypersensitivity reactions in up to 8% of treated patients. This hypersensitivity is strongly associated with patients carrying human leukocyte antigen (HLA)-B*57:01, but not patients carrying closely related alleles. Abacavir’s specificity to HLA-B*57:01 is attributed to its binding site within the peptide-binding cleft and subsequent influence of the repertoire of peptides that can bind HLA-B*57:01. To further our understanding of abacavir-induced hypersensitivity we used molecular dynamics (MD) to analyze the dynamics of three different peptides bound to HLA-B*57:01 in the presence and absence of abacavir or abacavir analogues. We found that abacavir and associated peptides bind to HLA-B*57:01 in a highly diverse range of conformations that are not apparent from static crystallographic snapshots. Further, the presence of abacavir has a direct impact on the dynamics and the conformational space available to peptides bound to HLA-B*57:01, likely influencing abacavir-induced immune self-reactivity. Our results support hypersensitivity models in which abacavir-binding alters the equilibrium proportions of neopeptide conformations in a manner favourable to TCR binding. Our findings highlight the need to also consider the role of dynamics in understanding drug-induced hypersensitivities at the molecular and mechanistic level. This additional insight can help inform the chemical modification of abacavir to prevent hypersensitivity reactions in HLA-B*57:01+ HIV patients whilst retaining potent antiretroviral activity.
Abstract A structural characterization of the interaction between T cell receptors (TCR) and cognate peptide-MHC (pMHC) is central to understanding adaptive T cell mediated immunity. X-ray crystallography, although the source of much structural data, traditionally provides only a static snapshot of the protein. Given the emerging evidence for the important role of conformational dynamics in protein function, we interrogated 309 crystallographic structures of pMHC complexes using ensemble refinement, a technique that can extract dynamic information from the X-ray data. We found that in a large number of systems ensemble methods were able to uncover previously hidden evidence of significant conformational plasticity, thereby revealing additional information that can build upon and significantly enhance functional interpretations that are based on a single static structure. Notable examples include the interpretation of differences in the disease association of HLA subtypes, the relationship between peptide prominence and TCR recognition, the role of conformational flexibility in vaccine design, and discriminating between induced fit and conformational selection models of TCR binding. We show that the currently widespread practise of analyzing pMHC interactions via the study of a single crystallographic structure does not make use of pertinent and easily accessible information from X-ray data concerning alternative protein conformations. This new analysis therefore not only highlights the capacity for ensemble methods to significantly enrich the interpretation of decades of structural data, but also provides previously missing information concerning the dynamics of existing characterized TCR-pMHC interactions.
Abstract A structural characterization of the interaction between αβ TCRs and cognate peptide–MHC (pMHC) is central to understanding adaptive T cell–mediated immunity. X-ray crystallography, although the source of much structural data, traditionally provides only a static snapshot of the protein. Given the emerging evidence for the important role of conformational dynamics in protein function, we interrogated 309 crystallographic structures of pMHC complexes using ensemble refinement, a technique that can extract dynamic information from the x-ray data. Focusing on a subset of human pMHC class I systems, we found that in many cases, ensemble methods were able to uncover previously hidden evidence of significant conformational plasticity, thereby revealing additional information that can build upon and significantly enhance functional interpretations that are based on a single static structure. Notable examples include the interpretation of differences in the disease association of HLA subtypes, the relationship between peptide prominence and TCR recognition, the role of conformational flexibility in vaccine design, and the discrimination between induced fit and conformational selection models of TCR binding. We show that the currently widespread practice of analyzing pMHC interactions via the study of a single crystallographic structure does not make use of pertinent and easily accessible information from x-ray data concerning alternative protein conformations. This new analysis therefore not only highlights the capacity for ensemble methods to significantly enrich the interpretation of decades of structural data but also provides previously missing information concerning the dynamics of existing characterized TCR–pMHC interactions.
Network motifs are connectivity structures that occur with significantly higher frequency than chance, and are thought to play important roles in complex biological networks, for example in gene regulation, interactomes, and metabolomes. Network motifs may also become pivotal in the rational design and engineering of complex biological systems underpinning the field of synthetic biology. Distinguishing true motifs from arbitrary substructures, however, remains a challenge. Here we demonstrate both theoretically and empirically that implicit assumptions present in mainstream methods for motif identification do not necessarily hold, with the ramification that motif studies using these mainstream methods are less able to effectively differentiate between spurious results and events of true statistical significance than is often presented. We show that these difficulties cannot be overcome without revising the methods of statistical analysis used to identify motifs. The implications of these findings are therefore far-reaching across diverse areas of biology.
Abstract Background Network motifs are connectivity structures that occur with significantly higher frequency than chance, and are thought to play important roles in complex biological networks, for example in gene regulation, interactomes, and metabolomes. Network motifs may also become pivotal in the rational design and engineering of complex biological systems underpinning the field of synthetic biology. Distinguishing true motifs from arbitrary substructures, however, remains a challenge. Results Here we demonstrate both theoretically and empirically that implicit assumptions present in mainstream methods for motif identification do not necessarily hold, with the ramification that motif studies using these mainstream methods are less able to effectively differentiate between spurious results and events of true statistical significance than is often presented. We show that these difficulties cannot be overcome without revising the methods of statistical analysis used to identify motifs. Conclusions Present-day methods for the discovery of network motifs, and, indeed, even the methods for defining what they are, are critically reliant on a set of incorrect assumptions, casting a doubt on the scientific validity of motif-driven discoveries. The implications of these findings are therefore far-reaching across diverse areas of biology.
Abstract Endolysin enzymes from bacteriophage cause bacterial lysis by degrading the peptidoglycan cell wall. The streptococcal C1 phage endolysin PlyC, is the most potent endolysin described to date and can rapidly lyse group A, C, and E streptococci. PlyC is known to bind the Group A streptococcal cell wall, but the specific molecular target or the binding site within PlyC remain uncharacterized. Here we report for the first time, that the polyrhamnose backbone of the Group A streptococcal cell wall is the binding target of PlyC. We have also characterized the putative rhamnose binding groove of PlyC and found four key residues that were critical to either the folding or the cell wall binding action of PlyC. Based on our results, we suggest that the interaction between PlyC and the cell wall may not be a high‐affinity interaction as previously proposed, but rather a high avidity one, allowing for PlyC’s remarkable lytic activity. Resistance to our current antibiotics is reaching crisis levels and there is an urgent need to develop the antibacterial agents with new modes of action. A detailed understanding of this potent endolysin may facilitate future developments of PlyC as a tool against the rise of antibiotic resistance.
Abacavir is an antiretroviral drug used to reduce human immunodeficiency virus (HIV) replication and decrease the risk of developing acquired immune deficiency syndrome (AIDS). However, its therapeutic value is diminished by the fact that it is associated with drug hypersensitivity reactions in up to 8% of treated patients. This hypersensitivity is strongly associated with patients carrying human leukocyte antigen (HLA)-B*57:01, but not patients carrying closely related alleles. Abacavir's specificity to HLA-B*57:01 is attributed to its binding site within the peptide-binding cleft and subsequent influence of the repertoire of peptides that can bind HLA-B*57:01. To further our understanding of abacavir-induced hypersensitivity we used molecular dynamics (MD) to analyze the dynamics of three different peptides bound to HLA-B*57:01 in the presence and absence of abacavir or abacavir analogues. We found that abacavir and associated peptides bind to HLA-B*57:01 in a highly diverse range of conformations that are not apparent from static crystallographic snapshots, but observed no difference in either the conformations, nor degree of flexibility when compared to abacavir-unbound systems. Our results support hypersensitivity models in which abacavir-binding alters the conformational ensemble of neopeptides, so as to favour exposed peptide surfaces that are no longer recognized as self by circulating CD8+ T cells, and are conducive to TCR binding. Our findings highlight the need to also consider the role of dynamics in understanding drug-induced hypersensitivities at the molecular and mechanistic level. This additional insight can help inform the chemical modification of abacavir to prevent hypersensitivity reactions in HLA-B*57:01+ HIV patients whilst retaining potent antiretroviral activity.
Abstract Serine proteinase inhibitors (serpins), typically fold to a metastable native state and undergo a major conformational change in order to inhibit target proteases. However, conformational labiality of the native serpin fold renders them susceptible to misfolding and aggregation, and underlies misfolding diseases such as a1-antitrypsin deficiency. Serpin specificity towards its protease target is dictated by its flexible and solvent exposed reactive centre loop (RCL), which forms the initial interaction with the target protease during inhibition. Previous studies have attempted to alter the specificity by mutating the RCL to that of a target serpin, but the rules governing specificity are not understood well enough yet to enable specificity to be engineered at will. In this paper, we use conserpin , a synthetic, thermostable serpin, as a model protein with which to investigate the determinants of serpin specificity by engineering its RCL. Replacing the RCL sequence with that from α1-antitrypsin fails to restore specificity against trypsin or human neutrophil elastase. Structural determination of the RCL-engineered conserpin and molecular dynamics simulations indicate that, although the RCL sequence may partially dictate specificity, local electrostatics and RCL dynamics may dictate the rate of insertion during protease inhibition, and thus whether it behaves as an inhibitor or a substrate. Engineering serpin specificity is therefore substantially more complex than solely manipulating the RCL sequence, and will require a more thorough understanding of how conformational dynamics achieves the delicate balance between stability, folding and function required by the exquisite serpin mechanism of action.
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