Structure⁻Activity Prediction of ACE Inhibitory/Bitter Dipeptides-A Chemometric Approach Based on Stepwise Regression.

Monika Hrynkiewicz,Piotr Minkiewicz,Małgorzata Darewicz,Justyna Bucholska,Anna Iwaniak

doi:10.3390/molecules24050950

Monika Hrynkiewicz, Piotr Minkiewicz + Show 3 more

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https://doi.org/10.3390/molecules24050950

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Abstract

Forward and backward stepwise regression (FR and BR, respectively) was applied for the structure–bioactivity prediction of angiotensin converting enzyme (ACE)-inhibitory/bitter-tasting dipeptides. The datasets used in this study consisted of 28 sequences and numerical variables reflecting dipeptides’ physicochemical nature. The data were acquired from the BIOPEP-UWM, Biological Magnetic Resonance Databank, ProtScale, and AAindex databases. The calculations were computed using STATISTICA®13.1. FR/BR models differed in R2 (0.91/0.76, respectively). The impact of C-atC(−) and N-Molw(+) on the dual function of dipeptides was observed. Positive (+) and negative (−) correlations with log IC50 are presented in parens. Moreover, C-Bur(+), N-atH(+), and N-Pol(−) were also found to be important in the FR model. The additional statistical significance of N-bul(−), N-Bur(−), and N-Hdr(+) was reported in the BR model. These attributes reflected the composition of the dipeptides. We report that the “ideal” bitter ACE inhibitor should be composed of P, Y, F (C-end) and G, V, I, L (N-end). Functions: log Rcaf. = f (observed log IC50) and log Rcaf. = f (predicted log IC50) revealed no direct relationships between ACE inhibition and the bitterness of the dipeptides. It probably resulted from some structural discrepancies between the ACE inhibitory/bitter peptides and/or the measure of activity describing one of the two bioactivities. Our protocol can be applicable for the structure–bioactivity prediction of other bioactivities peptides.

Highlights

It is well documented in the literature that peptides derived from food proteins exhibit diversity of bioactivities, such as antihypertensive, antioxidative, antithrombotic, antidiabetic, immunomodulating functions, etc. [1]
Two multilinear regression (MLR) models, namely forward regression (FR) and backward regression (BR), were carried out for two datasets composed of 28 peptidic bitter angiotensin converting enzyme (ACE) inhibitors and 20 variables each
An Fisher–Snedecor test (F-test) made for the analysis of significance of the estimated models led to rejecting the Hnull

Summary

Introduction

It is well documented in the literature that peptides derived from food proteins exhibit diversity of bioactivities, such as antihypertensive, antioxidative, antithrombotic, antidiabetic, immunomodulating functions, etc. [1]. It is well documented in the literature that peptides derived from food proteins exhibit diversity of bioactivities, such as antihypertensive, antioxidative, antithrombotic, antidiabetic, immunomodulating functions, etc. Peptides’ ability to inhibit angiotensin converting enzyme (ACE; EC 3.4.15.1). ACE-inhibiting peptides have been identified in proteins originating in practically all food sources [3]. ACE is involved in blood pressure regulation. It transforms angiotensin I, a decapeptide with the sequence DRVYIHPFHL, into angiotensin II (an octapeptide: DRVYIHPF) and. The transformation of angiotensin I into angiotensin II leads to vasoconstriction and to elevated blood pressure. ACE catalyzes the cleavage of vasodilating bradykinin (RPPGFSPFR). The products of this reaction are as follows: C-terminal

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