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Fodor, J.

Publications and source records attributed to Fodor, J..

4 recordsLinked to original sources

Reactive Centre Loop Dynamics and Serpin Specificity

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 1-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.

biochemistry

Intrinsic limitations in mainstream methods of identifying network motifs in biology

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.

systems biology

The Role of Conformational Dynamics in Abacavir-Induced Hypersensitivity Syndrome

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. Abacavirs 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.

immunology

Previously Hidden Dynamics at the TCR-pMHC Interface Revealed

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.

immunology