Computer-aided engineering of staphylokinase toward enhanced affinity and selectivity for plasmin

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Publikace nespadá pod Ústav výpočetní techniky, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.

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NIKITIN Dmitri MIČAN Jan TOUL Martin BEDNÁŘ David PEŠKOVÁ Michaela KITTOVÁ Patrícia THALEROVÁ Sandra VÍTEČEK Jan DAMBORSKÝ Jiří MIKULÍK Robert FLEISHMAN Sarel J. PROKOP Zbyněk MAREK Martin

Rok publikování 2022
Druh Článek v odborném periodiku
Časopis / Zdroj Computational and Structural Biotechnology Journal
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://www.sciencedirect.com/science/article/pii/S2001037022000794?via%3Dihub
Doi http://dx.doi.org/10.1016/j.csbj.2022.03.004
Klíčová slova Acute myocardial infarction; Stroke treatments; Thrombolytics; Plasminogen activators; Staphylokinase; Rational design; Affinity engineering; Enzyme kinetics; AffiLib
Přiložené soubory
Popis Cardio-and cerebrovascular diseases are leading causes of death and disability, resulting in one of the highest socio-economic burdens of any disease type. The discovery of bacterial and human plasminogen activators and their use as thrombolytic drugs have revolutionized treatment of these pathologies. Fibrin specific agents have an advantage over non-specific factors because of lower rates of deleterious side effects. Specifically, staphylokinase (SAK) is a pharmacologically attractive indirect plasminogen activator protein of bacterial origin that forms stoichiometric noncovalent complexes with plasmin, promoting the conversion of plasminogen into plasmin. Here we report a computer-assisted re-design of the molecular surface of SAK to increase its affinity for plasmin. A set of computationally designed SAK mutants was produced recombinantly and biochemically characterized. Screening revealed a pharmacologically interesting SAK mutant with-7-fold enhanced affinity toward plasmin,-10-fold improved plasmin selectivity and moderately higher plasmin-generating efficiency in vitro. Collectively, the results obtained provide a framework for SAK engineering using computational affinity-design that could pave the way to next-generation of effective, highly selective, and less toxic thrombolytics.
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