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Highlights • Thioredoxin reductase (TrxR), a seleno enzyme, regulates cellular redox. • Several human cancers are known to overexpress TrxR. • Inhibitors of TrxR have enhanced radiation induced cytotoxicity in multiple cancers. • TrxR could be a potential target during radiotherapy of cancer patients., Novel agents are required to increase the radiosensitivity of cancer and improve the outcome of radiotherapy. Thioredoxin (Trx) and thioredoxin reductase (TrxR) reduce the oxidized cysteine thiols in several proteins, which regulate cellular redox, survival, proliferation, DNA synthesis, transcription factor activity and apoptosis. TrxR is essential for maintaining a conducive redox state for tumor growth, survival and resistance to therapy. Therefore, it is an appealing pharmacological target for the radiosensitization of tumors. Ionizing radiation (IR) is known to cause cytotoxicity through ROS, oxidative stress and DNA damage. Inhibition of thioredoxin system augments IR induced oxidative stress and potentiates cytotoxic effects. However, TrxR also regulates several critical cellular processes in normal cells. Here, we highlight the pre-clinical research and pharmacological studies to surmise possible utility of different TrxR inhibitors for radiosensitization. This review provides a succinct perspective on the role of TrxR inhibitors during the radiotherapy of cancer., Graphical abstract Image, graphical abstract

In this contribution, the classification of protein binding sites using the physicochemical properties exposed to their pockets is presented. We recently introduced Cavbase, a method for describing and comparing protein binding pockets on the basis of the geometrical and physicochemical properties of their active sites. Here, we present algorithmic and methodological enhancements in the Cavbase property description and in the cavity comparison step. We give examples of the Cavbase similarity analysis detecting pronounced similarities in the binding sites of proteins unrelated in sequence. A similarity search using SARS M(pro) protease subpockets as queries retrieved ligands and ligand fragments accommodated in a physicochemical environment similar to that of the query. This allowed the characterization of the protease recognition pockets and the identification of molecular building blocks that can be incorporated into novel antiviral compounds. A cluster analysis procedure for the functional classification of binding pockets was implemented and calibrated using a diverse set of enzyme binding sites. Two relevant protein families, the alpha-carbonic anhydrases and the protein kinases, are used to demonstrate the scope of our cluster approach. We propose a relevant classification of both protein families, on the basis of the binding motifs in their active sites. The classification provides a new perspective on functional properties across a protein family and is able to highlight features important for potency and selectivity. Furthermore, this information can be used to identify possible cross-reactivities among proteins due to similarities in their binding sites.