• Metalloenzymes are omnipresent and play critical roles in many essential processes for life to exist.

    H-cluster, an active center of the [Fe-Fe] hydrogenase

     Knowledge of their active-site structures and their mechanisms of catalysis is not only valuable from the perspective of fundamental science, but could also instruct the development of new applications and processes that have interesting biomedical, chemical and energy-related applications. Currently, our laboratory focuses on [Fe-Fe] hydrogenase, a class of enzymes that catalyzes reversible splitting of molecular hydrogen. Understanding the determining factors that govern functionality of this class of enzymes will open doors to industrial applications of these systems directly and inspire inorganic catalyst designs. Our laboratory is currently investigating a set of [Fe-Fe] hydrogenases from various Clostridia, which show aberrations in their behavior under oxygenic environment. We perform protein film voltammetry, IR, and EPR spectroscopic experiments in conjunction with site-specific amino acid substitutions, to derive factors that can lead to understanding how oxygen damages the active center and how we can impose oxygen tolerance onto the oxygen-sensitive [Fe-Fe] hydrogenases.


  • An outline of the workflow for the proposed DEPR-based structural prediction methodology.

    Development of novel methods aiming to obtain structural determinants of misfolded and intrinsically disordered proteins using EPR-based structural methods. Measuring distances between two strategically placed spin-labels on proteins can provide unique information on structure and dynamics of proteins, especially in systems that are not readily accessible by conventional structural methods, such as intrinsically disordered proteins and amyloidogenic proteins. Currently, we research into maximizing the information that could be obtained from a single spin-labeling experiment using a variety of advanced pulse EPR methods.


The complete list of publications could be obtained at Google Scholars: