Integration of Molecular Docking Analysis and Molecular Dynamics Simulations for Studying Food Proteins and Bioactive Peptides

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Integration of Molecular Docking Analysis and Molecular Dynamics

Simulations for Studying Food Proteins and Bioactive Peptides

Abraham Vidal-Limon, JoséE. Aguilar-Toalá, and Andrea M. Liceaga*

Cite This: J. Agric. Food Chem. 2022, 70, 934−943

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ABSTRACT: In silico tools, such as molecular docking, are widely applied to study interactions and binding aﬃnity of biological

activity of proteins and peptides. However, restricted sampling of both ligand and receptor conformations and use of approximated

scoring functions can produce results that do not correlate with actual experimental binding aﬃnities. Molecular dynamics

simulations (MDS) can provide valuable information in deciphering functional mechanisms of proteins/peptides and other

biomolecules, overcoming the rigid sampling limitations in docking analysis. This review will discuss the information related to the

traditional use of in silico models, such as molecular docking, and its application for studying food proteins and bioactive peptides,

followed by an in-depth introduction to the theory of MDS and description of why these molecular simulation techniques are

important in the theoretical prediction of structural and functional dynamics of food proteins and bioactive peptides. Applications,

limitations, and future prospects of MDS will also be discussed.

KEYWORDS: molecular docking, molecular dynamics simulations, protein and peptides, molecular interactions

1. INTRODUCTION

In silico biology is a fast-growing ﬁeld that encompasses the

theory, programming, and application of computational

methodologies to model, predict, and elucidate biological

functions at the molecular level.

In silico methodologies are

widely recognized as useful tools with speciﬁc goals, from gene

and sequence identiﬁcation,

genome, transcriptome, pro-

teome, and metagenome assembly,

and de novo drug design.

In this regard, we can classify the in silico methodologies into

two groups. The ﬁrst group, also called bioinformatics,

comprises the organization of the data for access to the

information, development of tools that make the analysis

statistically robust, and the use of the data and analysis to

interpret and formulate the evolutionary hypothesis.

5−7

The

second group, biomolecular structure methodologies, also

called biomolecular simulations, are based on a fundamental

physicochemical description of particles (atoms and mole-

cules) with remarkable emphasis on how biomolecules, such as

proteins and peptides, move, ﬂuctuate, and physically interact.

Biomolecular simulations can supplement in vitro or in vivo

experiments with a molecular-level understanding of biological

processes because the simulated particles can be analyzed in

atomic detail, therefore, adding a new level of understanding

and interpretation of experimental data in terms of molecular

interactions.

9−11

Nowadays, there is an extensive diversity of biomolecular

simulation methodologies applicable to a wide range of

problems in structural biology, such as drug design. Tools

like molecular docking are biomolecular simulation method-

ologies based on integrated bioinformatic analysis, which

examine the interaction between molecules (e.g., proteins and

peptides) and predict their binding modes and aﬃnity at a

molecular or atomic level through computer programming.

12,13

They have been widely applied as theoretical simulation

strategies in drug discovery research and for virtual screening

studies dedicated to ﬁnd novel active biomolecules, such as

bioactive peptides. However, instrumental methods capable of

providing direct access to high-resolution molecular informa-

tion are required for complex food systems, such as in the case

of food emulsions with several interfaces in which the protein

is responding diﬀerently to each local environment.

As a

result of the dynamic nature of food proteins, it would be

logical that using high-performance computing, like molecular

dynamics simulations (MDS), could be applied to further

analyze their conformation as well as the conformational

rearrangement of the protein to changes in the external or

surrounding environment.

In contrast to traditional bio-

informatics and molecular docking tools, using high-perform-

ance computing has allowed for MDS to study the relationship

between dynamics and functions. In other words, MDS serves

as a powerful tool to deliver complementary information to

experiments and allow for an enhanced interpretation of the

changes to the secondary and tertiary structures of a protein

stimulated by adsorption at an interface.

This promising tool

is beginning to receive more attention from food scientists. For

example, Chen et al.

recently indicated a favorable trend

toward the use of MDS in the engineering of enzymes with

Received: September 29, 2021

Revised: November 22, 2021

Accepted: December 17, 2021

Published: January 6, 2022

Reviewpubs.acs.org/JAFC

American Chemical Society 934

https://doi.org/10.1021/acs.jafc.1c06110

J. Agric. Food Chem. 2022, 70, 934−943

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speciﬁc properties that would allow for their industrial-scale

application in the food industry.

This review will ﬁrst look at the information related to the

traditional use of biomolecular simulations applied for studying

food proteins and bioactive peptides and how these method-

ologies have served as a bridge between in silico and in vitro

analyses to deepen the study of the virtual structure of a

protein when encountered with complex environments, such as

those typically found in food matrices. We will also present an

in-depth introduction to MDS theory and applications and

explain why, moving forward, these molecular simulation

techniques are necessary to help predict and explain the

structural and functional dynamics of food proteins and

bioactive peptides.

2. COMMONLY USED IN SILICO METHODS

Diﬀerent in silico methodologies can be used to describe the

potential use of foods and their bioactive compounds. If the

main goal is to elucidate structure−activity relationships

between bioactive molecules and their potential targets, both

bioinformatic and biomolecular simulations can be supple-

mented with other methodologies. For example, chemo-

informatic methodologies include the analysis of chemical

information derived from structural information on biomole-

cules, such as secondary metabolites, peptides, and lipids,

among others.

Some of these methodologies also make use of

information deposited in databases to determine the frequency

of putative bioactive peptides in the primary structure of food

proteins.

18,19

Moreover, large databases of bioactive molecules

can be used to study the chemical space or chemical

similarities against well-known drugs. In addition, the use of

artiﬁcial intelligence (AI) techniques in bioinformatics and

biomolecular simulation exempliﬁes the integration of diﬀerent

ﬁelds under multivariate statistics, where the eﬀect of many

variables or chemical properties determine the bioactivity

proﬁle of speciﬁc targets.

20−22

Nevertheless, if the structure of

target bioactive compounds is unknown, diﬀerent models can

be built based on the information on a molecular reference

(i.e., ligands and substrates). Such methodologies are also

known as ligand-based methods, with the most applied

computational methods being the quantitative structure−

activity relationship (QSAR), quantitative structure−property

relationship (QSPR) analysis, and pharmacophore modeling.

Other methods, such as iBitter-SCM, are employed to

determine the bitterness of peptides (bitterness peptide

screening, https://camt.pythonanywhere.com/iBitter-SCM)

using the scoring card method (SCM). In addition, in silico

screening methods are widely used to study toxins, food-borne

pathogens, and trypsin inhibitors in foods at a molecular

level.

33,34

In foods for health research, in silico methods are used on

proteins and bioactive peptides to determine diﬀerent

parameters, such as their aﬃnity to bind speciﬁcally to their

targets, their probability to be bioactive, their intestinal

stability, and their ability to be retained in the circulatory

system, among others. Table 1 lists a summary of commonly

used software tools available for the in silico analysis of

bioactive peptides. Of the many in silico methods described,

molecular docking analysis is one of the most widely used tools

in drug design research and virtual screening studies to ﬁnd

novel active molecules derived from natural sources (e.g.,

plants), where this type of biomolecular simulation is used to

predict binding sites, elucidate the mechanism of molecular

recognition by simulating the spontaneous binding process of

biomolecules (e.g., proteins, carbohydrates, and lipids), and

explain their intermolecular interactions.

2.1. Overview of Molecular Docking Analysis in Food

Proteins and Bioactive Peptides. In the area of bioactive

peptides, molecular docking allows for characterization of the

behavior of peptides in the binding site of target proteins.

Because molecular docking is a structure-based method, it

enables it to delineate the structure−activity relationship of

peptides.

Overall, the molecular docking process includes

predicting the molecular orientation of a ligand within a

receptor and then calculating their complementarity inter-

action using a scoring function (i.e., binding aﬃnity).

Figure

1depicts the steps taken to carry out molecular docking

analysis of a bioactive peptide. For example, once bioactive

peptides have been successfully fractionated and identiﬁed (i.e.,

sequenced) and their bioactivity has been determined through

in vitro or in vivo assays, they undergo structural preparation for

docking. Next, the ligand is prepared for established target

receptor−ligand complex structures using docking simulation

software. Finally, the analysis of the data is performed by

predicting the binding modes and aﬃnities (i.e., scoring

functions) of a small molecule (i.e., bioactive peptide) within

the binding sites of target receptors (Figure 1).

In the case of food proteins, molecular docking has been

used mainly to study the relationship between enzymes and

substrates, which can help in the regulation of enzyme activity

in foods, as well as to study antinutritive compounds, such as

trypsin inhibitors.

For example, it was used to study the

binding interaction between egg white ovalbumin and

malachite green dye, a food additive with probable

carcinogenic potential, showing that the interaction between

ovalbumin and malachite occurred through hydrophobic and

van der Waals interactions.

Similarly, molecular docking was

used to determine that myrosinase, an enzyme found in

broccoli (Brassica oleracea var. italica), was able to catalyze the

conversion of glucosinolates to metabolites that possess health-

Table 1. Examples of Diﬀerent Tool Resources Employed for the In Silico Analysis of Bioactive Peptides

online in silico tool prediction function webserver link reference

Peptide Ranker bioactivity potential scoring http://distilldeep.ucd.ie/PeptideRanker 25

PreAIP anti-inﬂammatory peptide screening http://kurata14.bio.kyutech.ac.jp/PreAIP/ 26

iDPPIV-SCM DPP-IV inhibitor peptide https://camt.pythonanywhere.com/iDPPIV-SCM 27

AntiAngioPred anti-angiogenic peptide http://crdd.osdd.net/raghava/antiangiopred/ 28

AHTPIN antihypertensive peptide http://crdd.osdd.net/raghava/ahtpin/ 29

HLP intestinal stability http://crdd.osdd.net/raghava/hlp/ 30

PlifePred plasma stability https://webs.iiitd.edu.in/raghava/plifepred/ 31

ToxinPred toxicity screening https://webs.iiitd.edu.in/raghava/toxinpred 32

DPP-IV = dipeptidyl peptidase-IV.

Journal of Agricultural and Food Chemistry pubs.acs.org/JAFC Review

https://doi.org/10.1021/acs.jafc.1c06110

J. Agric. Food Chem. 2022, 70, 934−943

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