Virtual Natural Product Libraries
Up-to-date, only the COlleCtion of Open Natural prodUcTs (COCONUT:
https://coconut.naturalproducts.net, accessed on 11 April 2022), a free of charge and open access natural compounds database, efficiently aggregates the natural compounds chemical structures collected from various open sources (most compounds were added from the Ayurveda, Alkamid, CMNPD, and CyanoMetDB databases). Particularly, COCONUT contains 406,747 unique natural compounds in a readable format (.SMILES file) which are easily and quickly downloaded. Apart from chemical structures, COCONUT provides information about the stereochemical forms, organisms, natural geographical presence, and diverse pre-computed molecular properties of natural compounds
[17].
The Natural Products Atlas (NPAtlas:
https://www.npatlas.org/, accessed on 11 April 2022) constitutes another recently created open-access database, incorporating 24,594 natural compounds. It is a well-annotated database, including detailed information (structure, name, organisms source, isolation references, total syntheses, and cases of structural reassignment) about natural compounds, but unfortunately, it involves only microbial natural compounds
[18].
The FooDB (
https://foodb.ca/, accessed on 11 April 2022), a food-related chemical database, obtains >23,000 food chemicals in a searchable and downloadable format. Up to today, it is the most informative public resource of food ingredients, offering a unique opportunity for the identification of dietary components by performing virtual screening methods
[19].
Based on the proven beneficial effects of functionally useful plants, as food and medicine, the Collective Molecular Activities of Useful Plants database (CMAUP:
http://bidd.group/CMAUP/index.html, accessed on 11 April 2022) collected and classified in a downloadable format 47,645 plant ingredients derived from 5645 plants. The novelty of the aforementioned freely available database is that it possesses information not only for the chemical structure, name, and predicted physicochemical properties of the ingredients but also reports the ZINC code pointing out potential suppliers
[20].
Marine natural products (MNPs) are considered important sources of biologically active agents that regulate a variety of biological functions, offering a major impact on human health
[21][22][23][24]. The Comprehensive Marine Natural Products database (CMNPD:
https://www.cmnpd.org/, accessed on 11 April 2022) is a freely available database that provides abundant information. The complete dataset could be downloaded via
https://docs.cmnpd.org/downloads (accessed on 11 April 2022) in a ready-to-use format for virtual screening
[25].
Another database conveniently downloadable in a readable format is the South African Natural Compounds Database (SANCDB:
https://sancdb.rubi.ru.ac.za/, accessed on 11 April 2022), comprising more than 1000 compounds isolated from the plant and marine life in South Africa. Compared to other natural databases, SANCDB incorporates available analogues from MolPort (
https://www.molport.com/, accessed on 11 April 2022) and Mcule (
https://mcule.com/, accessed on 11 April 2022), two commercially available vendors, overcoming the major problem of the commercial availability of the compounds. Additionally, it facilitates virtual screening, including chemical scaffolds in a ready-to-dock format
[26].
Physical Natural Product Libraries
The ZINC 15 database (http://zinc15.docking.org, accessed on 11 April 2022) constitutes the most comprehensive resource, which includes readily purchasable compounds (over 230 million compounds in a ready-to-dock format), overcoming the limitations of the compounds’ commercial availability. Particularly, the field of natural compounds consists of over 80,000 ready-to-use compounds, derived from a plethora of vendors.
Analyticon Discovery (https://ac-discovery.com/, accessed on 11 April 2022) is a free access database, that provides a continuously growing collection of purified natural compounds. In particular, the library could be divided into the following subsets: (a) MEGx which offers about 5000 purified natural compounds originating from plants and microorganisms, (b) MACROx comprises over of 1800 macrocycle compounds, and (c) FRGx with over 200 fragments.
Ambinter (
https://www.ambinter.com/, accessed on 11 April 2022) and Greenpharma (
www.greenpharma.com, accessed on 11 April 2022) constitute two collaborative companies, offering a set of ~8000 natural compounds (alkaloids, phenols, phenolic acids, terpenoids, and others) in .SDF format ready to use for virtual screening. Additionally, the above-mentioned companies propose more than 11,000 semi-synthetic derivatives of natural compounds
[27].
One of the largest natural compound libraries is InterBioScreen (
https://www.ibscreen.com/, accessed on 11 April 2022), listing over 68,000 well-annotated natural compounds derived from a variety of sources, such as plants and microorganisms. The presented library is easily and quickly downloaded in a readable format (.SMILES and .SDF)
[27].
The MolPort (
https://www.molport.com/, accessed on 11 April 2022) database is another natural compound vendor of paramount importance since it stores in downloadable files over 10,000 unique natural and over 100,000 natural-like products from a variety of suppliers (.SMILES and .SDF). Therefore, its usage facilitates in silico screening applications since it possesses available-to-purchase natural products.
A collection of more than 3000 natural compounds and 396 food additive-related compounds are supplied from MedChemExpress (
https://www.medchemexpress.com/, accessed on 11 April 2022). For data accessibility, a query is required, and purchasable compounds in .SDF format is received. The main advantage of the present database is that all compounds have indicated bioactivity and safety.
INDOFINE Chemical Company (
https://indofinechemical.com/, accessed on 11 April 2022) includes around 1900 NPs and semisynthetic compounds, in a ready-to-screen format (.SDF), focused on flavonoids. The library consists of flavonoids, flavones, isoflavones, flavanones, coumarins, chromones, chalcones, and lipids especially. The chemical scaffolds of Indofine are offered and are classified according to compound types.
3.2. Virtual Screening (VS) Techniques
As it is generally known, the identification of bioactive molecules constitutes an expensive, time-consuming, and laborious inter-disciplinary process. As a result, innovative approaches are continuously developed, aiming to optimize and simplify this procedure. Among them, Virtual Screening (VS) is one of the most important and widespread strategies that has been applied for the determination of potentially bioactive molecules. In recent years, a variety of tools and software that can be performed in VS were utilized to reduce the selection of promising compounds that will be tested experimentally. Particularly, VS objectives are to accelerate the discovery process, increase the number of compounds to be tested experimentally, and rationalize their choice
[28][29]. Additionally, the classification of NPs into libraries contributes effectively to VS, facing and tackling issues related to the extraction, purification, and purchasability of NPs
[27].
The most commonly used methods for VS of NP libraries include Molecular Docking, Quantitative Structure-Activity Models (QSAR), Molecular Docking, Pharmacophore Modeling, and Molecular Dynamics (MD) Simulations. The main advantage of these methods is that they lead to reducing the selection of compounds that will be tested experimentally
[30].
Quantitative Structure-Activity Relationship (QSAR)
In general, Quantitative Structure-Activity Relationship (QSAR) analysis is a ligand-based computational technique that attempts to correlate the structural properties (chemical structures) and the biological activity of a compounds’ dataset
[31]. The underlying principle of QSAR models is based on the hypothesis that structurally similar compounds may exhibit similar biological activities
[32]. The creation of QSAR models is causally linked with equations that relate a dependent variable (i.e., an observed activity) with a number of calculated descriptors, including physicochemical, constitutional, and topological properties
[33][34]. For this purpose, various multivariate statistical regression (Multiple Linear Regression—MLR, Principal Component Analysis—PCA, and Partial Least Square Analysis—PLS) and Machine Learning (ML) tools are applied in an effort to generate appropriate algorithms
[35]. Table 3 presents a list of available software for molecular descriptor calculations. The building of the model is followed by the validation process in which the accuracy of the method is verified. The produced model can be used as a prediction tool to prioritize compounds that have the potential to display biological activity and to reduce the number of the compounds that will be tested experimentally
[36]. Therefore, it is a widely used process with a broad spectrum of applications in the pharmaceutical landscape
[37]. Regarding nutraceuticals, the relationship between food ingredients and a variety of properties has already been studied on several occasions
[38].
Molecular Docking
Molecular Docking is the most commonly used in silico technique, which predicts the interaction between a small molecule (ligand) and a protein (receptor) at the atomic level. This approach enables the characterization of the behavior of small molecules in the binding site of a target protein as well as the elucidation of the fundamental biochemical process behind this interaction
[39]. It is a structure-based approach which requires a high-resolution 3D illustration of the examined target derived from (a) X-ray crystallography
[40], (b) Nuclear Magnetic Resonance Spectroscopy
[41], and (c) Cryo-Electron Microscopy
[42].
Pharmacophore Modeling
A pharmacophore model illustrates in a 3D arrangement, the chemical features, which are crucial for the molecular recognition of a ligand by a macromolecule, offering a putative explanation for the binding affinity of structurally diverse ligands to a common target
[43]. It can be generated either in a structure-based way, by predicting the potential interactions between the target and the ligand, or in a ligand-based way, by overlaying a group of active molecules and creating common chemical features that may be responsible for their bioactivity
[44]. Currently, a variety of 3D pharmacophore modeling generators have been constructed, containing commercially available software and academic programs
[45].
Molecular Dynamics Simulations (MD simulation)
Molecular Dynamics Simulation is another powerful computational tool that captures the behavior of proteins, ligand-protein complexes, and other biomolecules in full atomic detail and at very fine temporal resolution
[46]. It is a well-established technique which provides a molecular perspective to observe the behavior of atoms, molecules, and particulates
[47]. Based on Newton’s equation of motion, MD predicts the physical movements of atoms and molecules using interatomic potentials or molecular mechanics force fields, offering the opportunity to comprehend the overall behavior of molecular systems during the motion of individual atoms
[46].
Applications of in Silico Screening Techniques in the Field of Nutraceuticals
Nowadays, the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a life-threatening disease causing thousands of deaths daily, is responsible for a current global health crisis. Therefore, the scientific community has the made treatment and prevention of SARS-CoV-2 infection its first priority
[48]. It has been proven that nutraceuticals contribute effectively to reducing the chances of SARS-CoV-2 infection, but also in alleviating COVID-19 symptoms
[49].
Towards this direction, Gyebi et al. (2021) performed a structure-based virtual screening to suggest inhibitors of 3-Chymotrypsin-Like Protease (3CL
pro) of SARS-CoV-2 from
Vernonia amygdalina and
Occinum gratissimum. In particular, they applied docking studies in the active site of 3CL
pro, aiming to predict the binding affinity of an in-house library, which includes 173 phytochemicals from
Vernonia amygdalina and
Occinum gratissimum. Docking results defined a hit list of 10 phytochemicals with strong binding affinities in the catalytic center of 3CL
pro from three related strains of coronavirus (SARS-CoV, MERS-CoV, and HKU4). Subsequently, drug-likeness prediction revealed two terpenoids, neoandrographolide and vernolide, as the most promising inhibitors of SARS-CoV-2 3CL
pro. The selected compounds were subjected to Molecular Dynamics simulations and the results showed that the examined terpenoid-enzyme complexes exhibited strong interactions and structural stability, which could be adapted in experimental models for the development of preventive nutraceuticals against coronavirus diseases
[50].
4. Nanotechnology: A Powerful Toolbox in the Field of Nutraceuticals
4.1. Nanonutraceuticals
Nanonutraceuticals outweigh traditional nutraceutical formulations since they can (a) enhance the solubility and stability of the encapsulated natural bioactive compounds and (b) increase their absorption and biological efficacy by diminishing the off-target release and minimizing their side effects
[7]. The up-to-date reported nanosized delivery systems include polymeric nanonutraceuticals (nanocapsules and nanospheres), carbon-based nanomaterials (i.e., fullerene and graphene particles), lipid-based formulations (solid lipid nanoparticles (SLNs), lipid nanocapsules, micelles, nanosuspensions, lipid–polymer hybrid nanoparticles, nanostructured lipid carriers, and liposomes), metal-based nanoparticles (silver and gold nanoparticles), dendrimers, nanoemulsions, exosomes, niosomes, quantom dots, nanoshells, nanofilms, and nanofibers. In the majority of cases, the therapeutic cargo of these nanocarriers is attributed to biologically active constituents, such as minerals, vitamins, polyphenols (i.e., resveratrol, rutin, tannins, anthocyanins, catechins and flavonoids, curcuminoids, berberine, etc.), carotenoids (lycopene, β-carotene, astaxanthin, etc.), ω-3 fatty acids, phytosterols, and probiotics (
Lactobacillus and
Bifidobacterium bacteria). When these nanovehicles are loaded with phytochemicals (i.e., curcumin, resveratrol, vitamin E, etc.), they are specified as nano-phytomedicines or nano-phytoceuticals. The first insights concerning these nanoformulations showed that they act as more efficient delivery systems of phytoconstituents
[51][52].
Based on the latest scientific evidence, the role of nutraceuticals in the prevention and treatment of several pathologies is multifarious. The scope of health-related applications of nanonutraceuticals is extended from the display of antioxidant, antimicrobial, anti-inflammatory, wound healing, pain relief, and immunomodulatory properties to the management of age-related neurogenerative conditions (i.e., Alzheimer’s and Parkinson’s disease), cancer, diabetes, skin diseases and recently, of pre- and post-COVID-19 infections
[52][53].
Nonetheless, the research community should address some issues regarding the toxicity and safety implications as well as the manufacturing challenges of nanonutraceuticals. At first, these nanoformulations must be fully characterized on the basis of their physicochemical properties, especially their size and shape, which may induce tissue damage or inadvertent permeation of non-targeted cell membranes. In addition, further clinical data from in vivo animal models should be collected and evaluated to decipher the mechanisms of action of these nanoproducts, improve their absorption and metabolism by the gastroinstestinal (GI) tract, and eliminate any possible immunotoxicity. Furthermore, the commercialization of nanoproducts is strongly related to the establishment of scaled-up cost-effective processes, which ensure the reproducibility, reliability, and high quality of the final product. The outcomes of these trials will lead to the establishment of guidelines and standardized protocols for the safe monitoring of nanonutraceuticals, which, eventually, will curb the concerns of the consumers regarding their use
[7][54].
4.2. Nanonutraceuticals Applications
Indicative examples of the newest applications of nanoformulations, recorded in the last two years (2021–2022) are exhibited in Table 7.
Table 1. Examples of nanonutraceuticals reported in the last two years (2021–2022).
| Nanonutraceuticals |
Bioactive Compounds |
Properties |
References |
| Nanoemulsion of monoglyceride oleogels |
Curcumin |
Higher encapsulation efficiency/Decelerate curcumin release |
[55] |
| Nanoemulsion of PLGA and PVA natural polymers |
Thymoquinone |
Reduce cisplatin-induced kidney inflammation without hindering its anti-tumor activity |
[56] |
| Almond oil nanoemulsion |
Thymoquinone |
Gastroprotective activities |
[57] |
| α-Cyclodextrin nanoemulsion |
Costunolide |
Enhanced anticancer properties |
[58] |
| Oil-in-water nanoemulsions |
Resveratrol |
Improved solubility, bioavailability, in vivo efficacy, and cytotoxic activity |
[59] |
| Solid lipid nanoparticles |
Berberine |
Higher bioavailability and anticancer effect |
[60] |
| Ufasomes |
Oleuropein |
Higher antioxidant activity |
[61] |
| Liposomes |
Thymoquinone |
Reduced toxicity, increased cell absorption and permeability/enhanced bioavailability and anticancer efficacy |
[62][63] |
| Liposomes |
Quercetin and mint oil |
Protection against oral cavities |
[64] |
| Corn starch-sodium alginate nanofibers |
Bifidobacteria | and lactic acid bacteria |
Protection of their probiotic activity in a food model and a simulated gastrointestinal system |
[65][66] |
| Food-derived hydrogel nanostructures |
Lupin- and soybean glycinin-derived peptides |
Antioxidant activity/ DPP-IV and ACE inhibitors |
[67][68] |
| Nanoparticles |
Soy isoflavones |
Activity against the neurogenerative effect of D-galactose |
[69] |