Identifying murburn mechanisms and parsing murzymes: Meta-analysis of structural, theoretical and experimental features in hemeprotein systems

Murburn concept is a decade-old theorization for explaining several cellular redox metabolic and electrophysiological outcomes. It stems from “mured burning”, connoting delocalized processes, involving diffusible reactive species (DRS). Traditionally, DRS like reactive oxygen species (ROS, a subset of DRS) have been seen as toxic wastes in cells. Over the last decade, DRS-based murburn models have been proposed to explain the thermodynamic-kinetic-mechanistic (TKM) aspects of several cellular activities (Manoj et al., AIP Advances, 2023; Manoj, J Cell Physiol, 2024). Therefore, it is now opportune to systematically study and delineate the various features of a protein/metabolic system that generates, modulates/stabilizes or utilizes DRS. In the current work, we meta-analyze three simple/single heme-protein systems: (1) extracellular heme-haloperoxidase, (2) membrane-bound cyclooxygenase, and (3) soluble haemoglobin; and also two complex/multi-protein systems (with hemes): (4) the hepatocyte xenobiotic metabolism proteins on endoplasmic reticulum, and (5) the mitochondrial oxidative phosphorylation machinery. We first tabulate an 8-point comparison of the classical mechanistic models in literature with the murburn model for these five systems; also carry out an internal consistency check for the classical models. Thereafter, we compare 8 distinct postulates of both models and avail an Ockham’s razor based algorithm for preferred mechanistic model. Further, based on 20 (structural, theoretical and experimental) parameters, we employ decision-tree/random-forest (AI-ML) methods to delineate murzymes with ~100% accuracy. Finally, using only text-descriptors in PDB (RCSB) files, an LLM-SVM based model to demarcate murzymes (with ~84% accuracy) is presented. These novel mechanistic and algorithmic analyses shall fuel research in redox enzymology.