Heme is an iron ion-containing molecule found within hemoproteins such as hemoglobin and cytochromes that participates in diverse biological processes. Although excessive heme has been implicated in several diseases including malaria, sepsis, ischemiareperfusion, and disseminated intravascular coagulation, little is known about its regulatory and signaling functions. Furthermore, the limited understanding of heme's role in regulatory and signaling functions is in part due to the lack of curated pathway resources for heme cell biology. Here, we present two resources aimed to exploit this unexplored information to model heme biology. The first resource is a terminology covering heme-specific terms not yet included in standard controlled vocabularies. Using this terminology, we curated and modeled the second resource, a mechanistic knowledge graph representing the heme's interactome based on a corpus of 46 scientific articles. Finally, we demonstrated the utility of these resources by investigating the role of heme in the Toll-like receptor signaling pathway. Our analysis proposed a series of crosstalk events that could explain the role of heme in activating the TLR4 signaling pathway. In summary, the presented work opens the door to the scientific community for exploring the published knowledge on heme biology.
Background: The notion of heme as a regulator of many physiological processes via transient binding to proteins is one that is recently being acknowledged. The broad spectrum of the effects of heme makes it important to identify further heme-regulated proteins to understand physiological and pathological processes. Moreover, several proteins were shown to be functionally regulated by interaction with heme, yet, for some of them the hemebinding site(s) remain unknown. The presented application HeMoQuest enables identification and qualitative evaluation of such heme-binding motifs from protein sequences. Results: We present HeMoQuest, an online interface (http://bit.ly/hemoquest) to algorithms that provide the user with two distinct qualitative benefits. First, our implementation rapidly detects transient heme binding to nonapeptide motifs from protein sequences provided as input. Additionally, the potential of each predicted motif to bind heme is qualitatively gauged by assigning binding affinities predicted by an ensemble learning implementation, trained on experimentally determined binding affinity data. Extensive testing of our implementation on both existing and new manually curated datasets reveal that our method produces an unprecedented level of accuracy (92%) in identifying those residues assigned "heme binding" in all of the datasets used. Next, the machine learning implementation for the prediction and qualitative assignment of binding affinities to the predicted motifs achieved 71% accuracy on our data. Conclusions: Heme plays a crucial role as a regulatory molecule exerting functional consequences via transient binding to surfaces of target proteins. HeMoQuest is designed to address this imperative need for a computational approach that enables rapid detection of heme-binding motifs from protein datasets. While most existing implementations attempt to predict sites of permanent heme binding, this application is to the best of our knowledge, the first of its kind to address the significance of predicting transient heme binding to proteins.
In hemolytic disorders, erythrocyte lysis results in massive release of hemoglobin and, subsequently, toxic heme. Hemopexin is the major protective factor against heme toxicity in human blood and currently considered for therapeutic use. It has been widely accepted that hemopexin binds heme with extraordinarily high affinity of <1 pM in a 1:1 ratio. However, several lines of evidence point to a higher stoichiometry and lower affinity than determined 50 years ago. Here we re-analyzed this data. SPR and UV/Vis spectroscopy were used to monitor the interaction of heme with the human protein. The heme-binding sites of hemopexin were characterized using hemopexin-derived peptide models and competitive displacement assays. We obtained a KD value of 0.32 ± 0.04 nM and the ratio for the interaction was determined to be 1:1 at low heme concentrations and at least 2:1 (heme:hemopexin) at high concentrations. We were able to identify two yet unknown potential heme-binding sites on hemopexin. Furthermore, molecular modelling with a newly created homology model of human hemopexin suggested a possible recruiting mechanism by which heme could consecutively bind several histidine residues on its way into the binding pocket. Our findings have direct implications for the potential administration of hemopexin in hemolytic disorders.
Thrombosis is one of the leading causes of death worldwide. As such, it also occurs as one of the major complications in hemolytic diseases, like hemolytic uremic syndrome, hemorrhage and sickle cell disease. Under these conditions, red blood cell lysis finally leads to the release of large amounts of labile heme into the vascular compartment. This, in turn, can trigger oxidative stress and proinflammatory reactions. Moreover, the heme-induced activation of the blood coagulation system was suggested as a mechanism for the initiation of thrombotic events under hemolytic conditions. Studies of heme infusion and subsequent thrombotic reactions support this assumption. Furthermore, several direct effects of heme on different cellular and protein components of the blood coagulation system were reported. However, these effects are controversially discussed or not yet fully understood. This review summarizes the existing reports on heme and its interference in coagulation processes, emphasizing the relevance of considering heme in the context of the treatment of thrombosis in patients with hemolytic disorders.
The SARS-CoV-2 outbreak has been declared a worldwide pandemic in 2020. Infection triggers the respiratory tract disease COVID-19, which is accompanied by serious changes of clinical biomarkers such as hemoglobin and interleukins. The same parameters are altered during hemolysis, which is characterized by an increase in labile heme. We present two computational-experimental approaches that aim at analyzing a potential link between heme-related and COVID-19 pathophysiologies. Herein, we performed a detailed analysis of the common pathways induced by heme and SARS-CoV-2 by superimposition of knowledge graphs covering heme biology and COVID-19 pathophysiology. Focus was laid on inflammatory pathways and distinct biomarkers as the linking elements. In a second approach, four COVID-19-related proteins, the host cell proteins ACE2 and TMPRSS2 as well as the viral protein 7a and S protein, were computationally analyzed as potential heme-binding proteins with an experimental validation. The results contribute to the understanding of the progression of COVID-19 infections in patients with different clinical backgrounds and might allow for a more individual diagnosis and therapy in the future.
Many research institutions, clinical diagnostic laboratories, and blood banks are desperately searching for a possibility to identify and quantify heme in different physiological and pathological settings as well as various research applications. The reasons for this are the toxicity of the heme and the fact that it acts as a hemolytic and pro-inflammatory molecule. Heme only exerts these severe and undesired effects when it is not incorporated in hemoproteins. Upon release from the hemoproteins, it enters a biologically available state (labile heme), in which it is loosely associated with proteins, lipids, nucleic acids, or other molecules. While the current methods and procedures for quantitative determination of heme have been used for many years in different settings, their value is limited by the challenging chemical properties of heme. A major cause of inadequate quantification is the separation of labile and permanently bound heme and its high aggregation potential. Thus, none of the current methods are utilized as a generally applicable, standardized approach. The aim of this Feature is to describe and summarize the most common and frequently used chemical, analytical, and biochemical methods for the quantitative determination of heme. Based on this overview, the most promising approaches for future solutions to heme quantification are highlighted.
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