Abstract:Thrombin normally cleaves fibrinogen to promote coagulation; however, binding of thrombomodulin to thrombin switches the specificity of thrombin toward protein C, triggering the anticoagulation pathway. The W215A thrombin mutant was reported to have decreased activity toward fibrinogen without significant loss of activity toward protein C. To understand how mutation of Trp215 may alter thrombin specificity, hydrogen-deuterium exchange experiments (HDXMS), accelerated molecular dynamics (AMD) simulations, and a… Show more
“…7 B ). Encountering such a characteristic decision plot and structural distribution when using experimental data would motivate the use of enhanced-sampling methods to improve the reference pool of structures ( 62 , 63 , 64 , 65 ). Figure 7 Detection of critically insufficient conformational sampling in the input ensemble to be reweighted.…”
Hydrogen-deuterium exchange combined with mass spectrometry (HDX-MS) is a widely applied biophysical technique that probes the structure and dynamics of biomolecules without the need for site-directed modifications or bio-orthogonal labels. The mechanistic interpretation of HDX data, however, is often qualitative and subjective, owing to a lack of quantitative methods to rigorously translate observed deuteration levels into atomistic structural information. To help address this problem, we have developed a methodology to generate structural ensembles that faithfully reproduce HDX-MS measurements. In this approach, an ensemble of protein conformations is first generated, typically using molecular dynamics simulations. A maximum-entropy bias is then applied post hoc to the resulting ensemble such that averaged peptide-deuteration levels, as predicted by an empirical model, agree with target values within a given level of uncertainty. We evaluate this approach, referred to as HDX ensemble reweighting (HDXer), for artificial target data reflecting the two major conformational states of a binding protein. We demonstrate that the information provided by HDX-MS experiments and by the model of exchange are sufficient to recover correctly weighted structural ensembles from simulations, even when the relevant conformations are rarely observed. Degrading the information content of the target data—e.g., by reducing sequence coverage, by averaging exchange levels over longer peptide segments, or by incorporating different sources of uncertainty—reduces the structural accuracy of the reweighted ensemble but still allows for useful insights into the distinctive structural features reflected by the target data. Finally, we describe a quantitative metric to rank candidate structural ensembles according to their correspondence with target data and illustrate the use of HDXer to describe changes in the conformational ensemble of the membrane protein LeuT. In summary, HDXer is designed to facilitate objective structural interpretations of HDX-MS data and to inform experimental approaches and further developments of theoretical exchange models.
“…7 B ). Encountering such a characteristic decision plot and structural distribution when using experimental data would motivate the use of enhanced-sampling methods to improve the reference pool of structures ( 62 , 63 , 64 , 65 ). Figure 7 Detection of critically insufficient conformational sampling in the input ensemble to be reweighted.…”
Hydrogen-deuterium exchange combined with mass spectrometry (HDX-MS) is a widely applied biophysical technique that probes the structure and dynamics of biomolecules without the need for site-directed modifications or bio-orthogonal labels. The mechanistic interpretation of HDX data, however, is often qualitative and subjective, owing to a lack of quantitative methods to rigorously translate observed deuteration levels into atomistic structural information. To help address this problem, we have developed a methodology to generate structural ensembles that faithfully reproduce HDX-MS measurements. In this approach, an ensemble of protein conformations is first generated, typically using molecular dynamics simulations. A maximum-entropy bias is then applied post hoc to the resulting ensemble such that averaged peptide-deuteration levels, as predicted by an empirical model, agree with target values within a given level of uncertainty. We evaluate this approach, referred to as HDX ensemble reweighting (HDXer), for artificial target data reflecting the two major conformational states of a binding protein. We demonstrate that the information provided by HDX-MS experiments and by the model of exchange are sufficient to recover correctly weighted structural ensembles from simulations, even when the relevant conformations are rarely observed. Degrading the information content of the target data—e.g., by reducing sequence coverage, by averaging exchange levels over longer peptide segments, or by incorporating different sources of uncertainty—reduces the structural accuracy of the reweighted ensemble but still allows for useful insights into the distinctive structural features reflected by the target data. Finally, we describe a quantitative metric to rank candidate structural ensembles according to their correspondence with target data and illustrate the use of HDXer to describe changes in the conformational ensemble of the membrane protein LeuT. In summary, HDXer is designed to facilitate objective structural interpretations of HDX-MS data and to inform experimental approaches and further developments of theoretical exchange models.
“…Pozzi et al 30 proposed the electrostatics at the W215−E217 segment as key factor, since mutations that stabilize the E* form predominantly lower the negative charge. Peacock et al 31 focused specifically on effects caused by mutations of the residues W215 and F227. Using activity assays, hydrogen-deuterium exchange experiments and accelerated MD simulations, they found that the π-stacking interactions between the two residues are essential to maintain an optimally active conformation.…”
the equilibrium between active e and inactive e* forms of thrombin is assumed to be governed by the allosteric binding of a na + ion. Here we use molecular dynamics simulations and Markov state models to sample transitions between active and inactive states. With these calculations we are able to compare thermodynamic and kinetic properties depending on the presence of na +. For the first time, we directly observe sodium-induced conformational changes in long-timescale computer simulations. thereby, we are able to explain the resulting change in activity. We observe a stabilization of the active form in presence of na + and a shift towards the inactive form in na +-free simulations. We identify key structural features to quantify and monitor this conformational shift. These include the accessibility of the S1 pocket and the reorientation of W215, of R221a and of the Na + loop. the structural characteristics exhibit dynamics at various timescales: conformational changes in the na + binding loop constitute the slowest observed movement. Depending on its orientation, it induces conformational shifts in the nearby substrate binding site. Only after this shift, residue W215 is able to move freely, allowing thrombin to adopt a binding-competent conformation. The serine protease thrombin plays a key role in the blood coagulation cascade as it catalyses the cleavage of fibrinogen, which ultimately leads to the formation of blood clots 1-4. Due to its central role for the blood coagulation, it is a compelling drug target and its structure has been examined thoroughly, with the first X-ray structure published in 1989 5. Thrombin is fully active in the presence of Na + , leading to the description of thrombin as allosterically regulated by Na + binding 6. This leads to the common distinction between 'slow' Na +-free, and 'fast' Na +-bound thrombin 7. While the fast form cleaves fibrinogen and protease-activated receptors, the slow form is more specific towards protein C, imparting an anticoagulant effect to it 8. The ratio between fast and slow forms was estimated to be 3:2 at physiologic temperature and salt concentration 8,9. Na + binds over 15 Å away from the catalytic triad, embedded in the Na + binding loop and coordinated by two backbone carbonyl oxygen atoms and four buried water molecules 10,11. Based on stopped-flow fluorescence measurements, a two-step mechanism of thrombin activation has been proposed 9,12. The active form E can bind to Na + to build the fully active E:Na + form, while the E* form cannot bind Na +. Na + binding stabilizes the E form and thus shifts the equilibrium towards active thrombin 9,13,14. Under physiological conditions the E* form is barely present 9 but it can be stabilized in mutants. Thus, X-ray structures of E* often feature mutations 15,16 , which allow structural interpretation of their observed catalytic inactivity. E* structures typically display a disarrayed conformation of substrate binding site residues W215−E217, which hinders substrate binding. Particularly, the sidechain of ...
“…The HDXMS data showed that the W215A mutant had increased dynamics in the 170s CT loop, the 220s CT loop, and the N-terminus of the heavy chain (Fig. 1) (15). The AMD simulations predicted increases in dynamics in the same regions of the protein as were observed to exchange more in the HDXMS experiments.…”
Amide hydrogen/deuterium exchange mass spectrometry (HDXMS) of proteins has become extremely popular for identifying ligand-binding sites, protein-protein interactions, intrinsic disorder, and allosteric changes upon protein modification. Such phenomena are revealed when amide exchange is measured in the fast limit, that is, within a few minutes of exchange in deuterated buffer. The HDXMS data have a resolution of the length of peptides and are difficult to interpret because many different phenomena lead to changes in hydrogen/deuterium exchange. We present a quantitative analysis of accelerated molecular dynamics simulations that provides impressive agreement with peptide-length HDXMS data. Comparative analysis of thrombin and a single-point mutant reveals that the simulation analysis can distinguish the subtle differences in exchange due to mutation. In addition, the results provide a deeper understanding of the underlying changes in dynamics revealed by the HDXMS that extend far from the site of mutation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
