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with other conditions, has been surging (Cragg and Newman, 2013). More recently,
several research institutions have been displaying interest in plant extracts due to
advancements in natural product screening techniques, including liquid chromatography (LC)/mass spectrometry (MS), LC/ultraviolet spectroscopy, LC/nuclear
magnetic resonance spectroscopy, high performance liquid chromatograpy–MS/
MS, high-resolution Fourier transform mass spectrometry, and photo-diode arrays,
providing ample structural congurations, elucidation for lead compound identication (Hostettmann et al, 2001)
Drug discovery strategies include phenotypic- and target-based computer-aided
drug design approaches, with the target-based strategy involving target identication
related to disease state. While these investigations drive potent chemical optimization of lead compounds, clinical trials may have limitations (Swinney, 2013; Zheng
et al, 2013). According to a recent study, invalidated illness targets result in many
unsuccessful medication candidates in Phase II and III clinical trials. Computational
technologies such as machine learning (ML) tools have been widely used to improve
the hit rate in drug development molecules (Jaén-Oltra et al, 2000; Marrero-Ponce
et al, 2005).
Singh and colleagues established a Bayesian classication model based on
structural ngerprints and physicochemical property descriptors. They applied
it to virtually screen an independent data set of 200k molecules, exhibiting that
the model can screen top hits of PubChem Bioassay actives with up to 76% accuracy. Computational approaches such as deep learning and ML have been highly
employed in improving drug discovery hit rates for many synthetic and naturally
derived drugs (Singh et al, 2012). Ekins and colleagues developed Bayesian models to predict compound activity toward Mycobacterium tuberculosis, then computationally screened 82,403 molecules and chose 550 for in vitro testing, yielding
124 actives against Mycobacterium tuberculosis. However, there has been little
study on categorization predictions for phenotypic screening of neuroprotective
drugs so far (Ekins et al, 2014).
The objective of this book chapter is to provide an overview of multiple natural
products and their diverse phytochemical constituent prole against neurotoxicity,
oxidative stress, and inammation. In addition, recent tactics of ML and deep learning in natural product screening against neuroprotection have also been emphasized.
NeuroPhytomedicine
11.2 PHYTOCHEMICAL CONSTITUENTS OF NATURAL
PLANT PRODUCTS
The majority of the bioactive components found in different parts (leaves, seeds,
owers, roots, and stems) of natural plants are reported to be avonoids, terpenes,
polyphenols, and CT, at varying concentrations. Phytochemical compounds display
multiple therapeutic mechanisms, including kinase-mediated aberrant signal transduction and antioxidant and anti-inammatory stimulation. Flavonoids are classied as secondary metabolites of polyphenolic nature, found mainly in plants, with
dietary consumption values. They have a generalized 15-carbon skeletal structure
consisting of a heterocyclic pyrane ring connecting (with an embedded O group)
two benzene rings, C6-C3-C6. Presently, nearly 6000 types of avonoids have been
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identied from several plant species, including proanthocyanins, avones, bioavonoids, avonol glycosides, and acylated avonol glycosides (Ullah et al, 2020).
Alteration in the structural skeleton affects and denes the structural basis for its
related derivatives. They exert several benecial effects in the prevention of cancer,
cardiovascular disorders, NDD, and diabetes (Safe et al, 2021). CT are a sub-class
of terpenoids, tetraterpenoids, producing organic pigments for plants, algae, and
certain fungi. They are further divided into two categories, carotenes (containing
hydrocarbons with no O-atoms) and xanthophylls (containing O-atom). They are
composed of four terpene units with ten carbon atoms each, providing a total of
40 carbon atoms, with their absorbance wavelengths ranging from 400 to 550 nM.
Data from several epidemiological studies suggest that carotenoid consumption in
humans and animal models appears to be protective against breast, prostate, head,
and neck cancer and Parkinson’s disease (PD) (Tan and Norhaizan, 2019). Terpenes
are unsaturated hydrocarbon-containing natural products produced by plants and
contain nearly 30,000 compounds. They are further classied by the number of carbon present, such as monoterpenes, diterpenes, and sesquiterpenes, and are regarded
as benecial phytocompounds for their anti-apoptotic, anti-platelet, anti-microbial,
and anti-inammatory activities (Ninkuu et al, 2021).
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11.3 ALZHEIMER’S DISEASE – A CRITICAL PROSPECT
OF NEUROTOXICITY
Alzheimer’s disease (AD) is a neurological condition that gradually deteriorates
cognition and perception prior to progressing to advanced dementia. The underlying pathogenic cause of AD is considered to be neurobrillary tangles (NFTs) and
amyloid-β (Aβ) brils. The clinical effectiveness of natural plants for treating neural conditions can be achieved by the evaluation of these two pathological protein
aggregates in the brain tissue. Numerous studies suggest that bioactive plants and
plant extracts such as curcumin, Ginkgo biloba, and resveratrol are known to pos-
sess potent anti-AD activities for their varied constitution of bioactive phytochemicals
(Shareena and Kumar, 2022). EGB 761-treated P301S TG micedepicted declining
levels of p-tau, enhanced learning retention, spatial memory, mitigated p38, glycogen
synthase kinase-3-beta (GSK-3β) signaling, rescued cyclic AMP-response element
binding protein phosphorylation, and synaptophysin loss in cultured cortical neurons
(Qin et al, 2018). Further, dietary EGb-treated-TF/CRND8 AD mice were shown to
mitigate AD pathology via downregulating Aβ aggregate formation and modulation
of β-secretase enzyme activity while reducing Aβ -induced proinammatory cytokine release, such as tumor necrosis factor alpha (TNF-α), interleukin (IL)-1β, pre-
venting Aβ-mediated aberrant microglial activation (Colciaghi et al, 2004). In human
SH-SY5Y neuroblastoma cell lines, curcumin suppresses Aβ-mediated tau and GSK3β phosphorylation at Ser396, Thr231, and Ser9 residues and ameliorates HDAC6
overexpression and Aβ toxicity. However, the neuroprotective impact of curcumin
on Aβ-mediated GSK-3β dephosphorylation is not directly associated with oxidative
stress. It abolishes Aβ-induced downregulation of Ak strain transforming (AKT) and
PDPK1 phosphorylation at Thr308, Ser473, and Ser241, respectively, suggesting that
the second response, phosphatidylinositol (3,4,5)-trisphosphate (PIP3), consists of
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curcumin-protective signaling. Likewise, insulin receptor (IR)/phosphatidylinositol3-kinase (PI3K) pathway, as a regulatory response signal of PIP3, does not involve
Aβ-mediated AKT deactivation (Thr308, Ser473 dephosphorylation). In addition, Aβ
expression leads to increased levels of phosphatase and tensin homolog (PTEN), a
negative PIP3 regulator, which is suppressed by curcumin treatment, implying that
curcumin is effectively Aβ-mediated tau phosphorylation engaging PTEN/AKT/
GSK-3β pathway (Huang et al, 2014). In another study, curcumin, in combination
with resveratrol, downregulates ROS generation, ameliorates oxidative stress, prevents tau hyperphosphorylation at T181 and T205 residue sites, and exhibits neuroprotective actions on SH-SY5Y cells from Aβ oligomer damage (Yu et al, 2022).
In P301L/rTg4510 mice, cornel iridoid glycoside (CIG) treatment improves memory
capabilities, spatial learning, and cognitive impairment, represses synapse, and neuronal loss, mitigates brain atrophy, enhances synaptic proteins, preserves cytoskeleton,
prevents tau hyperphosphorylation, aggregation in rTg4510 mice’s cerebral tissues.
Mechanistically, CIG enhances the PP2A activity, upregulates PP2Ac methylation at
Leu309, reduces PP2Ac phosphorylation at Tyr307, and promotes protein expressions
of PTPA, PTP1B, and LCMT-1 in the brain (Various plant products and their extract’s
potent anti-AD activity is represented in Figure 11.1) (Ma et al, 2019). Novel osmotin
FIGURE 11.1 The schematic diagram displays the therapeutic effect of natural plant products, such as curcumin, resveratrol, and osmotin, on the pathogenic AD species: Tau and aβ
protein species, preventing NFT hyperphosphorylation, aggregation, aβ-oligomer toxicity,
synaptic dysfunctions, neuronal death, interneuronal aβ and Tau species migration, oxidative
stress, cytokine release, in addition to suppressing activated microglia and astrocytes.
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extract signicantly inhibits Aβ1-42-mediated synaptic decits, memory impairment,
BACE-1 expression, synaptotoxicity, and Aβ protein aggregates and accumulation.
Moreover, osmotin-treated Aβ1-42-mice attenuates Aβ1-42-mediated tau protein
hyperphosphorylation at Ser413 via regulation of aberrant p-GSK-3β (Ser9), p-PI3K,
p-AKT (Ser473) phosphorylation, prevents neuronal apoptosis via p53-induced
caspase-associated apoptotic pathway and neurodegeneration along with alleviating
cellular neurotoxicity (Ali et al, 2015).
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11.4 COGNITION
A common characteristic of many pathological conditions is cognitive decline
or impairment. Memory, learning, thinking, and information processing are primarily affected by the physiological changes that result in the body. For their
abilities to improve cognition, many plant extracts have been used extensively in
conditions like dementia, AD, and PD related to memory loss as the body ages
(Eckert, 2010). Angelica gigas (AG), in combination with Bombyx mori silkworm (SW), notably protects hippocampal neuronal cells from H202-mediated
cell death in HT22 mouse cell lines. It recovers Scopolamine-induced cognitive
impairment and spatial learning. In specic, it upregulates mRNA and protein
levels of phosphorylated p38 and extracellular signal-regulated kinase (ERK)1/2
and reduces Bax/Bcl2 apoptotic index expression (Guo et al, 2021). Gypenoside
LXXV, derived from Gynostemma pentaphyllum, substantially alleviated cognitive decits in db/db mice and enhanced lipid metabolism and glucose tolerance. It drastically improved glucose uptake by the brain and markedly elevated
p-AKT/total AKT, GLUT4, and PPARγ expressions with a negative impact
on p-IRS-1/total IRS-1 levels (Meng et al, 2022). Dihydromyricetin (DHM)
decreased protein carbonyl, lipid peroxidation levels, augmented catalase, and
superoxide dismutase in the brain tissue in Pb-mediated mice. It mitigated
Pb-mediated cell apoptosis, with an evident reduction in cleaved caspase-3, Bax.
DHM facilitated AMP-activated protein kinase (AMPK) phosphorylation, prevented activation of TLR4, p38, MyD88, and GSK-3, inhibited inammatory
cytokines (iNOS, IL-6, TNF-α, and COX-2), Aβ levels, and NF-κB nuclear translocation, indicating that DHM could enhance cognitive functional prole via
prevention of oxidative stress, inammation, and apoptosis (Meng et al, 2022).
Salidroside, obtained from Rhodiola rosea, prevents cognitive impairment due
to hypoperfusion, and cerebral hypoxia, which was attributed to alteration of
PI3K, NF-κB, HIFα, mitogen-activated protein kinase (MAPK), and matrix
metalloproteinases (MMPs) signaling pathways. It enhances lipopolysaccharides
(LPS)-mediated learning impairment, memory decit, and neuroinammation
via modulating the SIRT-1dependent nuclear factor erythroid 2–related factor 2
(NRF-2)/HO-1/NF-κB pathway. Salidroside improves cognitive prole in orthopedic surgery-mediated cognitive impairment mice, decreasing the expressions
of M1 marker genes (CCL5, CD16, CXCL1, CXCL10, IFN-γ, and TNF-α), elevating M2 marker genes (Arg1, TGF-β, YM1, IL-4, and IL-10) and activating
AMPK kinase/PPARγ pathway (Pan et al, 2022).
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NeuroPhytomedicine
11.5 BIOACTIVITIES OF NATURALLY DERIVED
PHYTOCONSTITUENTS
11.5.1 PolyPhenols
Numerous polyphenolic compounds are a class of natural products that can exhibit
potent anti-tumor, antioxidant, and anti-inammatory properties through modulation of ROS levels, ER stress, Ca+2 levels, and autophagy. B16-F10 cells, on treatment
with P2Et, (Caesalpinia spinosa extract), mediated ER stress and apoptosis in mela-
noma cells. P2Et extract mediated ER stress signaling via (PKR)-like endoplasmic
reticulum kinase (PERK) kinase phosphorylation, which can modulate Ca+2 levels
and promote anti-tumor responses. It induced expression of ICD-associated DAMPs
(ATP, Ecto-CRT, and HMGB1) release in a PERK-dependent manner (Prieto et al,
2019). Dietary supplementation of green tea-derived EGCG rescues synaptic devel-
opment and dendritic defect in CDKL5-KO mice neurons. It restored the spine and
brain maturation density, along with attenuating defective spine maturation and
PSD95+ puncta cell population (Trovò et al, 2020). EGCG-treated BAEC cells
resulted in increased NO production and phosphorylation of AKT, eNOS, and Fyn,
depicting that ECGC has potent endothelial-dependent vasodilatory effects mediated
by ROS and Fyn-dependent intracellular pathways, which lead to PI3K/AKT, eNOS
activation. Mulberry polyphenol extracts (MPE) substantially suppressed phosphorylated ERK, RAS, and Β-galactosidase levels and enhanced NO and iNOS synthase
levels. NO increased the activation of AMPK and reduced HMG-CoA reductase
activity via its phosphorylation. It promoted the association of cyclins to their CDK
kinases and hyperphosphorylated RB. MPE prevented K-Ras-mediated A7r5 vascular smooth muscle cell senescence via enhancing AMPK and iNOS-dependent pathways, suggesting its powerful role in mitigating age-induced atherosclerosis (Chen
et al, 2022). In p53/wild-type HCT116 colorectal cancer cells, Artemisia annua
L. polyphenols (pKAL) induced late apoptosis, morphological changes in cancer
cells, associated with elevated acidic vesicles, loss of Golgi integrity, reduced DNA
content via upregulation and downregulation of γ-H2AX/p53/p21/Bak cleavage/
phospho-c-Jun N-terminal kinases (JNK)/p62/MAPK1/LC3B-I axis and AKT/β-
catenin/cyclophilin A/GM130, respectively, implying that p-KAL plays an essential
survival role in HCT116 cell lines, via p-JNK/p62 signaling and by inhibiting ROSindependent p53-dependent cell death signaling (Jung et al, 2021). Annurca apple
polyphenols selectively prevent malondialdehyde (MDA)-MB-231 cell proliferation
and viability. APE promoted G2/M phase cell cycle arrest, correlated with p-cdc25C
and p27 upregulation, along with p21 decrement. It also reduced the expression of
several oncoproteins, including β-catenin, NF-κB, and c-myc, and suppressed AKT
activation. Moreover, it lowered Dusp-1 levels, enhanced ROS production, and JNKc-Jun phosphorylation, portraying the underlying pathways of APE-mediated cell
death in MDA-MB-231 TNBC cell lines (Martino et al, 2019).
11.5.2 sAPonin
Hederoside C (HedC), a pentacyclic triterpene saponin isolated from P. Koreana,
demonstrated potent anti-cancer properties toward MG63, and U20S osteosarcoma
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cell lines wherein HedC prevented proliferative activity of both U20S and MG63
cell lines, and induced apoptosis (downregulation of cleaved poly(ADP-ribose)
polymerase (PARP), terminal deoxynucleotidyl transferase dUTP nick end
labeling–positive cells, cleaved caspase-9 and -3), in time- and dose-dependent manner. HedC-treated cells exhibited elevated p21, p53, Bax, and lowered Bcl-2, whereas
HedC-induced apoptosis was followed by reduced STAT3, MAPKs (JNK, ERK1/2,
and p38) phosphorylation. In in vivo xenograft mouse model, HedC showed an antimetastatic effect via suppression of neoplastic migration and invasion, ameliorated
and enhanced expressions of p-STAT3, PCNA, and p53, cleaved caspase-3, respectively, asserting that HedC has anti-metastatic, anti-tumor potentials (Park et al,
2021). Ginsenoside Ro (GRo) (Panax ginseng’s oleanolic saponin) notably attenuates
LPS-mediated lung injury and proinammatory mediators, including IL-6, IL-1β,
TNF-α. In addition, it inhibits the binding of LPS488 (uorescence-labeled LPS) to
membranes of RAW264.7 macrophages, suppresses MAPK, NF-κB phosphorylation, p65 nuclear translocation, dose-dependently. Moreover, docking and molecular
dynamics (MD) simulation analysis suggest that GRo is effectively docked into LPS
binding regions of MD2/TLR4 complex with stable binding conformation, implying
that GRo serves as a therapeutic anti-inammatory agent (Xu et al, 2022). Findings
display that cycloastragenol-treated mice brains were evaluated for their effects
against Aβ-mediated neurogenic dysfunctions, mitochondrial apoptosis, and oxidative stress. Treatment with cycloastragenol effectively inhibited expressions of MAP
kinases such as p-p38, p-JNK, and ERK1/2, reduced inammatory markers (Iba-1,
IL-1β, TNF-α, and GFAP), mitigated activated microglia and astrocytes. It improved
Aβ-mediated cognitive impairment, regulated anti-apoptotic effects, upregulating
and downregulating Bcl-2, Bax, Bim, and Casp-3, respectively, and promoted neuronal nuclei (NeuN), p-CREB expressions in the frontal cortex and hippocampal
regions of mice’s brains, conrming its neuronal survival effect (Ikram et al, 2021).
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11.5.3 cArotenoiDs (ct)
CTs are a class of tetraterpenoids, constituting conjugated polyene chains with eight
units of C5 isoprenoids. CTs are found in several sources, such as photosynthetic and
non-photosynthetic plants, animals, and aquatic sources. With the presence of varied
functional groups, number of conjugated double bonds, and cumulative polarities, CT
exerts potent ROS scavenging, antioxidant, anti-inammatory, neuroprotective, antidrug resistance, and anti-cancer properties (Kabir et al, 2022). Carotenoid, identied
from Spondias mombin, exhibits potent anti-angiogenic, anti-proliferative activities in 7,12-dimethylbenz[a]-anthracene breast cancer models in female Wistar rats.
Carotenoid isolate treatment remarkably downregulates the expressions of MMP-2,
HIF-1, VEGF, VEGFR, and EGFR in mammary tumors while upregulating mRNA
levels of CHD-1. The binding of astaxanthin produced the DFG-out conformation,
7,7′,8,8′-tetrahydro-β, -β-carotene, and β-carotene-15,15′-epoxide to the ATP binding
domain, with interaction energies of −8.2, −10.3, and −10.5 kcal/mol, respectively
(Metibemu et al, 2021). Synergistic dosing of doxorubicin, in tandem with dietary
carotenoid fucoxanthin (FUC), drastically enhances DOX’s cytotoxicity prole and
limits the dose of DOX (FR) in DOX-resistant cancer cell lines, including HepG-2/
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ADR (HCC), MCF-7/ADR (BC) and SKOV-3/ADR (ovarian cancer) by 6.28, 8.42,
and 4.56-fold, respectively, FUC elevates DOX accumulation in resistant cells, in contrast to verapamil, FUC, and DOX together, increase Rho123 build-up, p53 caspases
(CASP8, CASP3) activity, decrease the expressions of ABCB1, ABCC1, and ABCG2
along with PXR, GST, and CUP3A4 in resistant cancer cells, respectively (Eid et al,
2020). A low DOX dose with carotenoid substantially promoted anti-proliferation and
cytotoxicity in treated MCF-7 and MDA-MV-231 cell lines, compared with high-dose
DOX treatment alone. It caused G0/G1 phase cell cycle arrest, promoted selective
ROS-induced apoptosis, prevented mitochondrial dysfunctions, and downregulated
protein expressions of p21, p27, p53, Bcl-2, Bax, and cyclin D1, thereby improving
cancer therapy. In MDA-MB-231 cell lines, β-carotenes were reported to display signicant antitumoral actions by suppressing cell proliferation, migration, and invasion ability. β-carotene promotes apoptosis by interfering with S-phase cell arrest and
upregulates 3H-deoxy-D-glucose uptake, while it does not affect either 3H-folic acid
or 3H-glutamine uptake and oxidative stress. Β-carotene’s anti-proliferative effect
involves JNK intracellular signaling and did not impact cell viability, cell cycle, proliferation, and migration capabilities of MCF12-A non-tumoral cell lines, asserting
that β-carotene exhibits cancer cell-selective actions (Antunes et al, 2022).
NeuroPhytomedicine
11.5.4 flAvonoiDs
Flavonoids are a group of polyphenolic secondary bioactive metabolites that are
found in plants and are commonly consumed as dietary supplements due to their
immense therapeutic benets. A citrus avonoid, diosmetin displays a range of
therapeutic impacts for its antioxidant, anti-bacterial, and anti-inammatory effects.
In DNCB-mediated atopic dermatitis (AD) mouse models, diosmetin remarkably
lowers epidermis thickness, dermatitis score, and mast cell population compared
with untreated groups. It mitigates the macrophage inltration into AD lesions,
with the observed reduction in IL-4, IL-1β, and TNF-α. Further, diosmetin ham-
pers nitric oxide production, downregulates iNOS expression, suppresses MAPKs
(JNK, p38, ERK1/2), and JAK/STAT3 signaling phosphorylation and activation,
respectively, in raw 264.7 mouse macrophage cell line (Lee et al, 2020). Oral dosing of setin (FIS) in HFD-fed mice ameliorates HFD-induced cardiac dysregulations and metabolic disorders by reducing insulin levels, insulin resistance, body
weight, and fasting blood glucose. FIS supplementation substantially prevents the
pathology of dyslipidemia in both mouse cardiomyocytes and the heart, triggered by
metabolic stress. Moreover, FIS treatment represses HFD-mediated inammatory
responses in cardiac tissues via lowered Tnfr-1/Tnfr-2 signaling and downstream
target expressions. It promotes a robust reduction in brosis-associated genes, attributing to attenuation of brosis by inactivating TGF-β1/Smads/ERK1/2 signaling (Hu
et al, 2020). Dietary avonoid galangin prevents metastatic features such as TPAmediated HepG2 cell migration and invasion via inhibiting TPA-mediated PKC-δ,
PKC-α, phospho-IkBα, c-Jun, C-Fos, and NF-κB, thus showcasing its applications
in anti-metastatic clinical therapy. Myricetin portrays potent anti-cancer, antioxidant, and anti-inammatory activities, serving as a potential therapeutic agent. In
U-86 MG cell lines, myricetin treatment depicts anti-glioblastoma, anti-proliferative
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effects, hampering cellular migration and invasion, and PTEN status independently.
The cytotoxic actions of myricetin are cell-sensitive, wherein it shows minimal
cytotoxicity to normal astrocytes, in contrast to the GBM cell line. Additionally,
it suppresses the synthesis of focal adhesions, membrane rufes, lamellipodia, and
vasculogenic mimicry and blocks the ROCK2 phosphorylation, cortactin, paxillin,
JNK, and PI3K/AKT signaling. Myricetin binds to various kinases and scaffold proteins such as 3-phosphoinositide-dependent kinase 1 (PDK1), c-Jun, JNK, vinculin,
VE-cadherin, and PI3K catalytical isoforms (p110α-γ) (Zhao et al, 2018).
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11.6 MACHINE LEARNING AND DEEP LEARNING
TACTICS IN NATURAL PRODUCT DRUG
DISCOVERY AND DEVELOPMENT
11.6.1 mAchine leArning APProAches
ML involves algorithms analyzing curated data to make decisions and build efcient models for different functions. So far, several ML tools and development kits
have been utilized, including TensorFlow, Random Forest, Waikato Environment
for Knowledge Analysis, Scikit-Learn, and Support vector machine. The benets of
using ML tools in a quantitative structure activity relationship (QSAR) study include
an accurate prediction of the inuence of a compound’s chemical structure on its
bioactivity and the modeling of drug toxicity and metabolism (Stitou et al, 2019).
Therefore, ML is considered an essential resource for discovering new drugs (Dara
et al, 2022).
Yang et al reported developing a neuroprotective ML model for identifying potent neuroprotective compounds in Xiaxuming decoction (XXMD) against
H202-mediated and Hypoxia-induced brain cell damage. The TCM prescription
Xiaoxuming decoction (XXMD) (made up of 12 herbs) has been a benecial remedy
for the therapy of stroke in clinical settings, as documented in the Tang Dynasty’s
Beiji Qianjin Yaofang. They constructed stacked naïve Bayesian models based on
molecular ngerprint descriptors and four distinct single classiers (AB, CT, kNN,
and RF). The nalized models were used for the virtual screening of neuroprotective
agents in XXMD and further selected for cell-based assay. Among the compounds,
two compounds substantially inhibited Na2S2O4-induced and H2O2-mediated neurotoxicity (Yang et al, 2019). Baicalein was discovered to be a potent neuroprotective
drug in this work, with effects on hypoxia and oxidative stress phenotypes. Baicalein
has gained signicant focus for its antioxidant and anti-inammatory effects as a
bioactive phenolic avonoid molecule. The validation of baicalein against two damage phenotypes suggests that it might be used as a promising neuroprotective agent
(Dinda et al, 2017).
Another study by Fang J and colleagues reported 28 compounds exhibiting neuroprotective properties against H2O2-mediated and monosodium glutamate-induced
neurotoxicity by ML approaches. The results suggested that techniques that integrated single classiers into combined Bayesian models could be a viable approach
to predicting neuroprotective compounds. On monosodium glutamate-induced and
H2O2-induced PC12 cells, three selected molecules (J14572, J27152, and J27114)
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demonstrate a favorable dose-response relation and cell viability. Cell survival for
model groups affected by 40 mM monosodium glutamate or 300 mM H2O2 was
signicantly lower than in the control group (P 0.01) (Fang et al, 2016).
NeuroPhytomedicine
11.6.2 DeeP leArning APProAches
Deep learning is a sub-eld of ML that utilizes articial neural cells to process data
in decision-making. It also applies to the drug discovery process besides computational elds such as pattern recognition. It is highly implemented in QSAR studies; virtual screening; absorption, distribution, metabolism, excretion, and toxicity
properties; and lead optimization. Earlier deep learning implementations propose
a wide range of disease detection and prediction screening models, including a
Densely connected convolutional neural network (CNN)-based automated COVID
screening model, drug-target interaction CNN models, and CNN RF models to analyze drug functions from chemical structure (Chakravarti and Alla, 2019; Kumari
and Subbarao, 2021). This novel approach has led to the discovery of several impactful techniques that could be effectively utilized in phytochemical drug screening
and their therapeutic and pharmacological targets in several chronic states, such as
neuroprotection, neurotoxicity, apoptosis, oxidative stress, and inammation. Hence,
several studies surrounding such have been described, showing a vast diversity of
models throughout its development phases (Shanmuganathan, 2016).
The algorithm for all the naturally derived drugs and compounds functions in
three steps: (A) Collection of natural compounds and drug information from the
public database. (B). Producing molecular interaction and chemical features from
collected data by text mining, network analysis, and chemical property analysis. (C)
Training the deep learning models on the elements of approved drugs and predicting
the medicinal properties based on the trained model. Deep learning can increase
prediction performance when the input characteristics are extensive and diversied by extracting high-level interpretation using low-level features. The mentioned
approach has four consecutive levels: Input, partially linked hidden layers, fully
coupled hidden layers, and output. The models are developed to forecast the likely
effects list utilizing the input attributes. Theoretical knowledge, molecular interaction, and chemical property data are generated for each drug or natural component
and used as inputs to the model. Hidden layers extended their outputs by detecting
nonlinear connections between low- and high-level data to provide a higher-level
representation than the last layer (Yoo et al, 2020).
Rodríguez FR and colleagues developed a computational strategy involving deep
learning, structural bioinformatics, and signaling pathway manual reconstruction to
predict eight novel nicotine analogs’ neuroprotective activity based on the PI3KAKT
pathway in the context of PD therapeutics. The model predicted the potential neuroprotective efcacy of seven novel nicotine analogs based on the binomial Bcl-2
response regulated by PI3K/AKT activation (Rojas-Rodríguez et al, 2020).
Further studies by Wang H and co-workers identied sclareol as a naturally
derived Cav1.3-neuroprotective antagonist in PD. While L-type voltage-gated calcium channel blockers treatment selectively alleviates Cav1.3 for PD, drug development is impeded due to a shortfall in high-throughput screening techniques allowing
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FIGURE 11.2 The above illustration depicts a contrasting feature between ML approaches
and deep learning techniques, utilized in drug discovery and development, virtual screening,
and SAR study of phytochemicals and natural products.
isoform-specic assessment of Cav-antagonistic activities. Integrated in silico virtual screening and deep learning models enabled the discovery of (6)-Gingerol and
sclareol as novel Cav1.3 antagonists. In silico analysis of 198 candidate molecules
produced 14 hits as the most promising Cav1.3 inhibitors.
Moreover, structure clustering analysis enabled a selection of ve phytoconstituents as potential structures. In addition, parallel articial intelligence–based validation showcased similar results, with a receiver operating characteristic curve–area
under curve value of 97.78%. Experimentations on the ve compounds with CaB-A
assay conrmed that sclareol and (6)-gingerol portrayed robust inhibition on Cav1.3.
Both molecules showed a more substantial antagonistic effect on Cav1.3-induced
reporter gene expression than the Cav1.3-dependent CaB system. Sclareol-treated
PD mouse models observed minimal loss in DA neurons, exhibited in vivo neuroprotective effects toward 6-ODHA-mediated neurodegeneration, prevented oversynchronization and locomotion decits of striatal neurons (the contrast between
ML and deep learning approaches are described in Figu re 11.2) (Wang et al, 2022).
11.7 CONCLUSION
The emergence of expanding disease conditions and the shortage of diseasemodulating or disease-alleviating therapies pose alarming challenges to research
institutions. Although diagnosing and treating the symptomatic events of chronic
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