Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities
Departments of Chemistry and Biochemistry and Pharmacology, Howard Hughes Medical Institute, and San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA 92093. Proceedings of the National Academy of Sciences
(Impact Factor: 9.67).
11/2012; 109(52). DOI: 10.1073/pnas.1218414109
The serine protease α-thrombin is a dual-action protein that mediates the blood-clotting cascade. Thrombin alone is a procoagulant, cleaving fibrinogen to make the fibrin clot, but the thrombin-thrombomodulin (TM) complex initiates the anticoagulant pathway by cleaving protein C. A TM fragment consisting of only the fifth and sixth EGF-like domains (TM56) is sufficient to bind thrombin, but the presence of the fourth EGF-like domain (TM456) is critical to induce the anticoagulant activity of thrombin. Crystallography of the thrombin-TM456 complex revealed no significant structural changes in thrombin, suggesting that TM4 may only provide a scaffold for optimal alignment of protein C for its cleavage by thrombin. However, a variety of experimental data have suggested that the presence of TM4 may affect the dynamic properties of the active site loops. In the present work, we have used both conventional and accelerated molecular dynamics simulation to study the structural dynamic properties of thrombin, thrombin:TM56, and thrombin:TM456 across a broad range of time scales. Two distinct yet interrelated allosteric pathways are identified that mediate both the pro- and anticoagulant activities of thrombin. One allosteric pathway, which is present in both thrombin:TM56 and thrombin:TM456, directly links the TM5 domain to the thrombin active site. The other allosteric pathway, which is only present on slow time scales in the presence of the TM4 domain, involves an extended network of correlated motions linking the TM4 and TM5 domains and the active site loops of thrombin.
Available from: Shaoyong Lu
- "Statistical coupling analysis (SCA)  is a sequence-based technique that uses a multiple sequence alignment (MSA) to identify networks of co-evolving residues in a protein family; such networks, also termed as protein sectors, provide a structural basis for allosteric communication between functional and allosteric sites   . Thus, allosteric sites can be predicted by identifying surface sites that are in direct contact with protein sectors. "
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ABSTRACT: Allosteric modulators have the potential to fine-tune protein functional activity. Therefore, the targeting of allosteric sites, as a strategy in drug design, is gaining increasing attention. Currently, it is not trivial to find and characterize new allosteric sites by experimental approaches. Alternatively, computational approaches are useful in helping researchers analyze and select potential allosteric sites for drug discovery. Here, we review state-of-the-art computational approaches directed at predicting putative allosteric sites in proteins, along with examples of successes in identifying allosteric sites utilizing these methods. We also discuss the challenges in developing reliable methods for predicting allosteric sites and tactics to resolve demanding tasks.
Drug Discovery Today 08/2014; 19(10). DOI:10.1016/j.drudis.2014.07.012 · 6.69 Impact Factor
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ABSTRACT: The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads.
Biophysical chemistry 01/2013; 186. DOI:10.1016/j.bpc.2013.10.007 · 1.99 Impact Factor
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ABSTRACT: Thrombin participates in coagulation, anticoagulation, and initiation of platelet activation. To fulfill its diverse roles and maintain hemostasis, this serine protease is regulated via the extended active site region and anion binding exosites I and II (ABE I and ABE II). For the current project, amide proton hydrogen-deuterium exchange (HDX) coupled with MALDI-TOF mass spectrometry was used to characterize ligand binding to individual exosites and to investigate the presence of exosite-active site and exosite-exosite interactions. PAR3 (44-56) and PAR1 (49-62) were observed to bind to thrombin ABE I and then to exhibit long range effects over to ABE II. By contrast, Hirudin (54-65) focused more on ABE I and did not transmit influences over to ABE II. Although these three ligands were each directed to ABE I, they did not promote the same conformational consequences. PPACK inhibition at the thrombin active site led to further local and long range consequences to thrombin-ABE I ligand complexes with the autolysis loop often most affected. When Hirudin (54-65) was bound to ABE I, it was still possible to bind GpIbα (269-286) or fibrinogen γ' (410-427) to ABE II. Each ligand exerted its predominant influences on thrombin and also allowed inter-exosite communication. The results obtained support the proposal that thrombin is a highly dynamic protein. The transmission of ligand-specific local and long range conformational events is proposed to help regulate this multi-functional enzyme.
Journal of Biological Chemistry 02/2013; 288(12). DOI:10.1074/jbc.M112.410829 · 4.57 Impact Factor
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