Bioprospecting and Rational Drug Design of Antihypertensive Peptides from Underexplored Nigerian Legumes: A Computational and Experimental Integration

Hypertension is the leading non-communicable disease risk factor in Nigeria, with pharmacological treatment frequently inaccessible to rural and low-income populations due to cost and supply chain constraints. Antihypertensive bioactive peptides derived from food protein hydrolysates represent an emerging class of functional food ingredients and nutraceutical candidates. Underexplored Nigerian legumes represent an untapped reservoir of such peptides. This study conducted systematic bioprospecting and rational drug design of angiotensin-converting enzyme inhibitory peptides from protein hydrolysates of three underexplored Nigerian legumes: Vigna unguiculata (cowpea) from Kano State, Cajanus cajan (pigeon pea) from Plateau State, and Sphenostylis stenocarpa (African yam bean) from Benue State. Protein hydrolysates were generated using sequential pepsin-pancreatin digestion. Peptide fractions were separated by ultrafiltration and reverse-phase HPLC. ACE inhibitory activity was determined by the spectrophotometric hippuric acid release method. Peptide sequences from the most active fractions were identified by LC-MS/MS, and novel sequences were subjected to in silico docking against the human ACE crystal structure. Selected peptides were synthesised by solid-phase methods and evaluated for ACE inhibition, stability to gastrointestinal proteases, and antihypertensive effect in spontaneously hypertensive rats. Fourteen novel ACE inhibitory peptides were identified. Three synthetic pentapeptides from V. unguiculata hydrolysate demonstrated IC50 values below 50 micromolar and significant blood pressure reduction in animal models following oral administration. These findings identify Nigerian legume-derived peptides as original candidates for functional food and nutraceutical antihypertensive product development. Keywords: antihypertensive peptides, ACE inhibition, Nigerian legumes, bioprospecting, computational drug design.