ReviewProbiotics and antimicrobial proteins2026
Selective α-Amylase Inhibition by Plant Defensins: Structural Determinants, Engineering Strategies, and Translational Prospects.
Review in Probiotics and antimicrobial proteins, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Plant defensins are best known as antimicrobial peptides, yet their capacity to inhibit α-amylase, a property relevant to both crop protection and the management of postprandial hyperglycaemia, remains comparatively uncharacterized. These cysteine-rich peptides adopt a conserved cysteine-stabilized αβ fold whose disulfide network confers resistance to proteolysis and thermal denaturation, properties compatible with sustained enzyme inhibition in the insect gut or the human gastrointestinal tract. A small subset shows isoform preference: the cowpea defensin VuD1 inhibits storage-pest enzymes more strongly, though not absolutely, than human isoforms, whereas the 12-residue fragment F3 from Capsicum chinense inhibits human salivary α-amylase. Evidence that a human-active profile is accessible within an intact defensin scaffold therefore remains limited. This review examines how loop architecture and γ-core geometry govern that selectivity. Its central argument is that the limiting problem is selectivity rather than potency, since discriminating insect from mammalian α-amylase is the prerequisite for safe crop protection and for therapeutic use alike. Progress is constrained less by conceptual gaps than by evidentiary ones. Most reported inhibition derives from single-concentration endpoint assays that cannot distinguish competitive from non-competitive mechanisms; formal kinetic parameters exist for one defensin-enzyme pair only, and the mechanism established there is non-competitive; direct binding measurements and co-crystal structures are absent; and in vivo validation is scarce. Mechanistic claims therefore rest largely on molecular docking. We separate what is experimentally established from what is computationally inferred, evaluate engineering and expression strategies against that evidence, and define the kinetic, structural and translational gaps that must be closed.
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