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16.1 Introduction
Neurodegenerative disorders are a group of chronic and progressive conditions characterized by
the gradual degeneration and loss of structure or function of nerve cells (neurons) in the central
nervous system. These disorders primarily affect the brain and, in some cases, the spinal cord.
Neurodegenerative diseases often result in cognitive decline, movement disorders, and various
neurological symptoms [1]. The exact causes of these disorders can vary, including genetic factors,
environmental influences, and a combination of both.
Some common neurodegenerative disorders include
1) Alzheimer’s disease (AD): AD disease accounts for a significant portion of age-related
cognitive decline, making it the most common cause of dementia. In this disease, beta-amyloid
plaques and tau tangles are among the abnormal protein aggregates found in the brain. AD
primarily affects memory, cognition, and behavior [2].
2) Parkinson’s disease (PD): In PD, dopamine-producing neurons in the brain gradually
degenerate. In turn, this leads to motor symptoms such as tremors, bradykinesia, and rigidity.
PD is characterized by abnormal protein deposits called Lewy bodies [3].
3) Huntington’s disorder (HD): A mutation in the huntingtin gene results in the inherited
condition known as Huntington’s disease. It causes the cerebral cortex and basal ganglia’s
neurons to degenerate. Involuntary motions, cognitive deterioration, and emotional difficulties
are among the symptoms [4].
4) Amyotrophic lateral sclerosis (ALS): The loss of both upper and lower motor neurons in the
brain and spinal cord is a hallmark of ALS, a motor neuron disease. This eventually results in
respiratory failure, paralysis, and increasing muscle weakness [5].
5) Multiple sclerosis (MS): The main feature of MS is the immune system targeting the
protective layer of myelin that covers nerve fibers for protection. As a result, there is a disruption
in the brain’s ability to communicate with the body, which can cause various neurological
symptoms like exhaustion, weak muscles, and poor coordination [6].
6) Frontotemporal dementia (FTD): A collection of illnesses known as frontal and/or temporal
lobe degeneration (FTD) are distinguished by their progressive nature. It may result in
modifications to behavior, personality, and linguistic skills [7].
16
Rational Design of Drugs for Neurodegenerative Disorders
Priyanka Kamaria
Department of Pharmaceutical Chemistry, KLE College of Pharmacy, Bangalore, India
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16.2 Common Mechanism of Neurodegeneration
Neurodegeneration in different neurodegenerative illnesses is attributed to some common
pathways. Mechanistic convergence can be divided into five main areas: (1) factors related to the
environment, including age, diet, and exercise; (2) metabolic stress, including mitochondrial
dysfunction and elevated reactive oxygen species (ROS); (3) genetic factors, including sex-linked
genetic contributions and risk alleles found through genome-wide association studies (GWAS);
(4) neurovascular coupling, which includes impaired neurovascular coupling and breakdown of
the blood–brain barrier; and (5) neurological inflammation, which is characterized by glial
reactivity and the infiltration of peripheral immune cells. Every mechanistic facet of degeneration
is influenced by environmental variables.
1) Environmental factors
Neurodegenerative disease progression is influenced by environmental variables in both cellular
and epigenetic aspects. Neurotoxic drugs, age, food, and exercise can exacerbate or initiate
underlying events. These elements play a crucial role in common degenerative processes. Age, a
primary risk factor across diseases, particularly affects postmitotic cells like neurons, making them
sensitive to aging effects like genomic instability and mitochondrial dysfunction. Exercise and
nutrition play a critical role in maintaining the health of the central nervous system, influencing
functions like immunological responses and mitochondrial ATP synthesis. Understanding the
influence of extrinsic variables on signaling pathways and their role in degeneration provides
prospective opportunities for novel therapeutic techniques in neurodegenerative illnesses [8].
2) Neuroinflammation
Neuroinflammation stands as a pervasive commonality in various neurodegenerative diseases.
Characterized by increased glial reactivity and infiltration of peripheral immune cells, it fuels
pathological processes. The inflammatory response, triggered by diverse factors like genetic
predisposition and environmental influences, contributes significantly to neuronal damage and
dysfunction. In conditions like Parkinson’s, Alzheimer’s, and MS, neuroinflammation is a
shared hallmark, amplifying disease progression. Understanding and targeting this inflamma-
tory cascade presents a promising avenue for therapeutic interventions, offering potential strat-
egies to mitigate the impact of neuroinflammation on neural tissues and improve outcomes in
the realm of neurodegenerative disorders [9, 10].
3) Neurovascular coupling
It appears as a common mechanism among several neurodegenerative conditions. It entails the
complex interaction between cerebral blood flow control and neuronal activity. Dysfunction in
this coupling, characterized by blood–brain barrier breakdown and impaired neurovascular
interactions, contributes to pathological processes. In conditions like Alzheimer’s, stroke, and
vascular dementia, compromised neurovascular coupling accelerates cognitive decline and
exacerbates neuronal damage. Disruptions in nutrient and oxygen supply to the brain further
amplify the degenerative cascade. Recognizing the pivotal role of neurovascular coupling in
various disorders offers valuable insights for targeted therapeutic strategies, aiming to restore
vascular integrity and alleviate the impact of impaired neurovascular interactions on neurologi-
cal health [11].
4) Metabolic stress
It emerges as a prevalent mechanism across various neurodegenerative diseases. Manifesting as
mitochondrial dysfunction and increased levels of ROS, it inflicts cellular damage and exacer-
bates neurodegeneration. The compromised energy production and oxidative stress lead to a
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cascade of detrimental effects on neurons. PD, AD, and HD all exhibit links to metabolic stress,
further underscoring its significance. Understanding and addressing this shared mechanism pro-
vides a promising avenue for therapeutic interventions. Mitigating metabolic stress-induced dam-
age holds the potential for alleviating the progression of neurodegenerative disorders, offering a
targeted approach to enhance cellular resilience and maintain neurological well-being [12].
5) Genetic contributors
It constitutes a pivotal common mechanism in the landscape of neurodegenerative diseases.
GWAS unveil risk alleles associated with conditions like Parkinson’s, Alzheimer’s, and ALS,
elucidating genetic underpinnings. Sex-linked genetic influences also play a role in disease
susceptibility. The identified genetic markers contribute to altered protein functions, impaired
cellular processes, and neuronal vulnerability, collectively shaping the course of
neurodegeneration. Recognizing these genetic nuances across diverse disorders opens avenues
for targeted therapeutic interventions, offering potential strategies to modify the underlying
genetic factors and mitigate the impact of inherited predispositions on the onset and progression
of neurodegenerative diseases [13].
16.3 Brief Overview of Computational Methods in Drug Design
Computational methods play a pivotal role in drug design, revolutionizing the way researchers
identify and optimize potential drug candidates. These methods leverage computational power to
analyze biological systems, predict molecular interactions, and streamline the drug discovery pro-
cess. Here is a brief overview of computational methods in drug design:
1) Molecular docking
Computational method called “molecular docking” is used in drug discovery to determine a
ligand’s preferred orientation when it binds to a target protein receptor. It involves exploring the
potential interactions and binding conformations between the ligand and receptor to estimate
the binding affinity and potential efficacy of a drug candidate. By simulating the molecular
interactions at the atomic level, docking algorithms help to identify promising drug candidates
with high binding affinity, aiding in the rational design of new pharmaceuticals. This approach
accelerates the drug discovery process by facilitating the selection of compounds most likely to
exhibit desired biological activity [14].
2) Quantitative structure–activity relationship (QSAR)
QSAR is a computational modeling technique in chemistry and pharmacology used to predict
the biological activity of molecules based on their chemical structure. QSAR establishes
mathematical relationships between chemical descriptors representing molecular structure
and experimental biological activity. By analyzing these relationships, QSAR models can
forecast the activity of new compounds, aiding in drug design and environmental toxicity
assessment. QSAR models are crucial in rational drug design, enabling the identification of
lead compounds with desired pharmacological properties and reducing the time and resources
needed for experimental testing. They play a significant role in optimizing molecular structures
to enhance desired biological effects [15].
3) Pharmacophore modeling
Pharmacophore modeling is a computational method employed in drug discovery to identify
and characterize essential structural features of molecules that are crucial for binding to a bio-
logical target. It involves analyzing the spatial arrangement of functional groups and atoms
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within active ligands to create a 3D representation of the pharmacophore, which serves as a
blueprint for designing new drug candidates. By elucidating key interactions between ligands
and target receptors, pharmacophore modeling guides the rational design of compounds with
enhanced binding affinity and specificity. This approach accelerates the drug discovery process
by facilitating the identification of lead compounds and optimization of their pharmacological
properties [16, 17].
4) Virtual screening
Virtual screening is a computational technique employed in drug discovery to efficiently sift
through large libraries of chemical compounds and predict their potential to interact with a
target protein or receptor. Using molecular docking, pharmacophore modeling, or similarity
searching, virtual screening evaluates the likelihood of compounds binding to the target based
on their structural and chemical properties. By prioritizing the most promising candidates for
experimental testing, virtual screening accelerates the drug discovery process, saving time and
resources. It plays a vital role in identifying lead compounds with desired biological activity,
ultimately aiding in the development of new drugs and therapeutic interventions [18].
5) Molecular dynamics simulation
Molecular dynamics (MD) is a computational simulation method used in physics and chemistry
to study the motion and behavior of atoms and molecules over time. It employs classical
mechanics principles to model the trajectories of individual atoms as they interact within a
defined system, accounting for forces such as electrostatics and van der Waals interactions. By
numerically solving Newton’s equations of motion, MD simulations provide insight into the
dynamic behavior of complex molecular systems, revealing information on structural changes,
thermodynamic properties, and molecular interactions. Widely applied in fields like materials
science, biochemistry, and drug design, MD simulations contribute to understanding
fundamental molecular processes and guiding experimental research [19].
6) Machine learning in drug design
Machine learning (ML) in drug design leverages algorithms to analyze large datasets of chemical
compounds and biological targets, aiding in the identification of potential drug candidates. ML
models predict molecular properties, bioactivity, and toxicity, guiding the selection and optimiza-
tion of lead compounds. Techniques such as QSAR, molecular docking, and virtual screening
utilize ML to expedite the drug discovery process by prioritizing compounds for experimental
validation. By integrating diverse sources of data, including chemical structures, genomic infor-
mation, and experimental results, ML enhances the efficiency and accuracy of drug design, facili-
tating the development of novel therapeutics with improved efficacy and safety profiles [20].
7) Fragment-based drug design (FBDD)
FBDD is a strategy in medicinal chemistry that utilizes small molecular fragments as starting
points for developing drug candidates. These fragments, typically low-molecular-weight com-
pounds, bind to specific regions on target proteins with high affinity. Through techniques like
X-ray crystallography and NMR spectroscopy, fragments’ binding interactions are analyzed,
guiding the assembly of larger compounds that retain the essential binding motifs. FBDD
allows for efficient exploration of chemical space, facilitating the design of compounds with
improved potency, selectivity, and pharmacokinetic properties. It has emerged as a powerful
approach in drug discovery, particularly for challenging targets, offering promise in developing
novel therapeutics for various diseases [21].
8) De novo drug design
De novo drug design is a computational approach in medicinal chemistry aimed at designing
novel drug molecules from scratch, rather than modifying existing compounds. It involves the
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generation of molecular structures that possess desired pharmacological properties and are
optimized for target specificity, efficacy, and safety. Using computational methods such as
molecular docking, MD simulations, and quantum chemistry calculations, de novo drug design
explores chemical space to identify lead compounds with the potential to interact favorably
with target proteins. This method accelerates the drug discovery process by providing innova-
tive solutions for addressing unmet medical needs and developing therapeutics with tailored
properties [22, 23].
These computational methods significantly accelerate the drug discovery and development pro-
cess, helping researchers to identify potential drug candidates more efficiently and cost-effectively.
They also contribute to a deeper understanding of the molecular mechanisms underlying diseases,
paving the way for more targeted and effective therapeutic interventions. Different approaches
used for computer-aided drug design (CADD) are depicted in Figure 16.1.
16.4 Parkinson’s Disease as Prevalent Neurodegenerative Disorder
Among the most common neurodegenerative diseases is Parkinson’s disease. It is characterized by
the gradual degeneration of brain neurons that produce dopamine, resulting in motor symptoms
such as bradykinesia (slowness of movement), stiffness, and postural instability. Additional
symptoms include sleep difficulties, gastrointestinal tract, bladder, and mental expressions. In
addition to dopaminergic (DA) neurons in the substantia nigra (SNc), PD impacts additional
neurological pathways. The genesis of PD can be caused by various variables, such as brain damage,
environmental factors, genetic background, age, or dietary inadequacies. By 2030, it is expected
that the number of adults over 65 with PD would have doubled. In the United States alone, PD is
the 14th most common cause of death, with approximately USD 25 billion spent annually on
treatment. While AD is generally recognized as the most common neurodegenerative disorder, PD
is among the top neurodegenerative conditions in terms of prevalence [24].
Computational approaches for
drug design
Molecular docking
and molecular
dynamics simulation
Virtual screening
Denovo drug design
and fragment
based drug design
Machine learning
approaches
Pharmacophore
mapping
Quantitative
structure activity
relationship (QSAR)
Figure 16.1 Different computational approaches commonly used in drug design process.
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16.4.1 Epidemiology of Parkinson’s Disease
PD is a neurological illness that affects people all over the world today. Regional variations exist in
the epidemiology of PD, and age, genetic susceptibility, and environmental exposures all have an
impact on the disease’s prevalence. The incidence of PD rises dramatically after age 60 and reaches
over 3% in those over the age of 80. Most often, men experience PD at a higher incidence than
women. Toxins in the environment can exacerbate PD symptoms, and eating habits might change
the likelihood of the condition. People who smoke and drink coffee frequently are at a higher
risk [25].
PD is reported to be less prevalent in India compared to Western countries, but the prevalence is
increasing as the population ages. Limited population-based studies on the prevalence of PD in
India are available, and the estimates vary. The reported prevalence in some studies ranges from 41
to 328 cases per 100,000 people, with variations across different regions [26].
16.4.1.1 Factors Influencing PD Epidemiology
1) Age: The risk of PD increases with age, and its prevalence is higher in older populations [27].
2) Genetics: Certain genetic factors can contribute to an increased risk of PD. Familial forms of
PD, although less common, are influenced by genetic mutations [28].
3) Environmental factors: Exposure to certain environmental factors, such as pesticides, well
water contaminants, and rural living, has been suggested to play a role in the risk of developing
PD [29].
16.4.2 Pathogenesis of PD
Several factors that play roles in the pathogenesis of PD are depicted in Figure 16.2. These factors
are as follows:
1) Accumulation of Lewy bodies in substantia nigra
PD is characterized by a number of pathophysiological alterations, one of which is the develop-
ment of Lewy bodies in the SNc. Abnormal protein deposits called Lewy bodies form in the
brain’s nerve cells. Alpha-synuclein is the main protein that makes them up. Lewy bodies are
mostly detected in the SNc, a part of the brain related to motor control, in PD. The buildup of
Lewy bodies in this region aids in the degeneration of dopamine-producing neurons, which
causes tremors, stiffness, and problems with balance and coordination that are characteristic of
PD. Lewy body buildup is thought to cause oxidative stress, inflammation, and disruption of
cellular processes, all of which can contribute to DA neuron degradation and ultimately death
occurs [30].
2) Mitochondrial dysfunction
Mitochondrial dysfunction is linked to PD, affecting energy production and leading to oxidative
stress. Mitochondria, responsible for ATP production, play a crucial role, and their impairment
compromises neuronal function. Dysfunctional mitochondria generate ROS, contributing to
PD’s neurodegenerative process. Alpha-synuclein, associated with PD pathology, disrupts mito-
chondrial function. Mutations in mitochondrial DNA observed in PD brains may impair effi-
ciency. Impaired mitophagy, responsible for removing damaged mitochondria, adds to cellular
stress in PD. Environmental toxins, like pesticides, impact mitochondrial function, potentially
contributing to dysfunction. Therapeutic strategies targeting mitochondrial function are
explored for PD treatment in ongoing research [31].
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3) Genetic factors
Genetic factors significantly contribute to PD, encompassing both familial and sporadic cases.
Approximately 5–10% of PD cases exhibit a familial pattern, involving specific genetic mutations.
Among the genes associated with PD, SNCA (alpha-synuclein), LRRK2 (leucine-rich repeat
kinase 2), PARK2 (parkin), PINK1 (PTEN-induced kinase 1), and GBA (glucocerebrosidase) are
associated with an increased PD risk. Alpha-synuclein mutations influence Lewy body
formation, LRRK2 mutations are prevalent in certain populations, PARK2 mutations impact
protein degradation, and GBA mutations affect lipid metabolism. PD is a complex interplay of
genetic and environmental factors, emphasizing the need for a comprehensive understanding
in diagnosis and potential therapeutic development [32].
4) Neuroinflammation
Neuroinflammation plays a significant role in the pathogenesis of PD. It involves the activation
of the brain’s immune cells, such as microglia and astrocytes, in response to various triggers like
alpha-synuclein aggregates and cellular damage. While inflammation is a normal protective
response, chronic neuroinflammation in PD can become detrimental. Activated immune cells
release proinflammatory molecules, leading to oxidative stress and further damage to DA
neurons in the SNc. This inflammatory response may contribute to the progressive degeneration
seen in PD. Understanding and targeting neuroinflammation are areas of active research for
potential therapeutic interventions in PD [33].
5) Impaired protein handling
Impaired protein handling is integral to PD pathogenesis. Dysfunctional processes like the
ubiquitin-proteasome system and autophagy, responsible for clearing damaged proteins,
contribute to the accumulation of toxic protein aggregates, notably alpha-synuclein. Inefficient
Parkinson’s patient
Lewy bodies
accumulation
Mitochondrial
dysfunction
ROS
Mutation in
genes like
SNCA, LRRK2
Activated
microglia
Reactive
astrocytes
BBB Leakage and
Neuroinammation
Impaired protein
handling (dysfunction
in ubiquitin
proteasome system)
Proteasome
Figure 16.2 Pathogenesis of Parkinson’s disease.
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clearance leads to the formation of Lewy bodies, affecting DA neurons in the SNc. The presence
of these aggregates disrupts cellular function and contributes to neurodegeneration.
Understanding and addressing these disruptions in protein handling mechanisms are crucial
for developing therapeutic strategies to mitigate or prevent the progression of PD [34].
6) Oxidative stress
Increased production of ROS and oxidative stress play a role in the degeneration of DA neurons.
Oxidative damage to cellular components contributes to the neurodegenerative process in
PD [35].
7) Environmental toxins
Exposure to certain environmental toxins, including pesticides (rotenone, paraquat) and drugs
like maneb and epoxomycin, have been associated with the development of PD in animal stud-
ies. This suggests a potential link between exposure to these specific toxins and the initiation or
progression of PD-like symptoms in experimental research involving animals. Although the
translation of these results to human implications requires further investigation. These toxins
may contribute to mitochondrial dysfunction and oxidative stress [36].
16.4.3 Signaling Pathway of Parkinson’s Disease
Several signaling pathways are implicated in the PD pathogenesis. Some key pathways include:
1) DA signaling
Neurodegeneration can be brought on by abnormalities in the signaling system, which is
dependent on DA, the neurotransmitter found in DA neurons. DA neuron loss in PD results in
decreased dopamine in the striatum, which affects the nigrostriatal system and causes motor
abnormalities. Central to the development of PD are DA neuron loss, impaired dopamine
release, and altered neurotransmission. Alpha-synuclein aggregation, oxidative stress, ferropto-
sis, mitochondrial failure, and neuroinflammation are among the mechanisms linked to PD. PD
is caused by protein aggregation and mitochondrial failure in DA neurons. Environmental and
neurotoxin exposure can also induce mitochondrial impairment, leading to DA cell loss and PD
development. Thus, understanding the DA signaling pathway and associated mechanisms is
crucial for comprehending and addressing PD progression [37].
2) MAPK/ERK pathway
Cell growth, differentiation, and survival are all regulated by the essential cell signaling mecha-
nism known as the mitogen-activated protein kinase/extracellular signal-regulated kinase
(MAPK/ERK) pathway. Within the framework of PD, the pathophysiology and advancement of
the condition have been linked to the MAPK/ERK pathway. One important aspect of PD is the
destruction of DA neurons in the SNc, which may be facilitated by dysregulation of the MAPK/
ERK pathway. Dopamine is a neurotransmitter that is essential to motor function and is pro-
duced by DA neurons. Increased oxidative stress, inflammation, and apoptosis (programmed
cell death) in DA neurons may arise from abnormal activation of the MAPK/ERK pathway. It is
thought that these processes play a role in the neurodegenerative alterations seen in PD [38].
3) PI3K/Akt/mTOR pathway
Activation of the phosphoinositide 3-kinase (PI3K) enzyme is triggered by extracellular signals,
including growth factors. Phosphatidylinositol 3,4,5-trisphosphate (PIP3) is produced when
activated PI3K phosphorylates phosphatidylinositol 4,5-bisphosphate (PIP2). Akt (protein
kinase B): Upon binding to PIP3, the serine/threonine kinase Akt is drawn to the cell membrane.
Phosphorylation at the membrane causes Akt to become active. By phosphorylating several
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downstream targets, activated Akt promotes cell growth and survival. Mammalian target of
rapamycin, or mTOR, is a protein kinase that controls autophagy, cell division, and protein
synthesis by combining signals from the Akt and other pathways. There are two mTOR
complexes, mTORC1 and mTORC2, each of which has a different task [39].
The PI3K/Akt pathway has been linked to neuroprotection because it inhibits apoptosis, or
programmed cell death, and encourages cell survival. Autophagy is a cellular process that is
regulated by the mTOR pathway and is responsible for eliminating damaged or malfunctioning
cellular components. Alpha-synuclein is one of the misfolded proteins that accumulate and is
characteristic of PD; its buildup has been linked to dysregulation of autophagy. The control of
mitochondrial function depends upon the PI3K/Akt/mTOR pathway. A common characteristic
of neurodegenerative illnesses, such as PD, is mitochondrial malfunction. The PI3K/Akt/
mTOR pathway is being intensively studied by researchers as a potential PD treatment
approach [40].
4) Wnt/β-catenin pathway
The signaling molecules called Wnt proteins are released and start the Wnt pathway. Wnt
ligands come in various forms that can open the pathway. Cell surface receptors such as frizzled
(FZD) receptors and coreceptors such as low-density lipoprotein receptor-related protein (LRP)
are bound by Wnt ligands. Signaling cascades within cells are activated by this binding. β-Catenin
is typically the target of a protein complex that contains glycogen synthase kinase-3 beta
(GSK-3β) for destruction in the absence of Wnt signaling. β-Catenin is stabilized and accumulates
in the cytoplasm when Wnt signaling is activated. When stabilized β-catenin reaches the
nucleus, it combines with transcription factors belonging to the T-cell factor/lymphoid enhancer
factor (TCF/LEF) family to form a complex. Target genes implicated in various biological
functions have their transcription activated by this complex.
It has been suggested that the Wnt/β-catenin pathway aids in neuroprotection and neuronal
survival. It might contribute to preserving the integrity of the SNc’s DA neurons, which are lost
in a selective manner in PD. The formation of new neurons, or neurogenesis, has also been
linked to the activation of this pathway. In the treatment of neurodegenerative illnesses, this
mechanism may aid in the repair of neurons. The pathway is also connected to the control of
mitochondrial activity, which is essential for the production of energy and maintenance of cel-
lular homeostasis [41].
5) NF-κB (nuclear factor-κB) pathway
One important signaling mechanism that controls immunological responses, inflammation,
and cell survival is the NF-κB pathway. Regarding PD, disruption of the NF-κB pathway has
been connected to the neuroinflammatory mechanisms that accompany the disease’s
advancement. Generally, inhibitor proteins (IκBs) sequester NF-κB in the cytoplasm, rendering
it inactive. Proinflammatory signals are one of the many stimuli that might cause the pathway
to become active. Activation causes IκB proteins to get phosphorylated and then degrade, which
permits NF-κB to translocate into the nucleus. Upon entering the nucleus, NF-κB functions as
a transcription factor, controlling the expression of genes linked to immune response,
inflammation, and cell viability. The brain’s NF-κB pathway can be activated to enhance the
production of chemokines and cytokines that promote inflammation [42].
6) Autophagy-lysosomal pathway
This pathway is pivotal in PD, ensuring cellular homeostasis. It begins with autophagosome
formation, engulfing damaged components, including alpha-synuclein. Fusion with lysosomes
forms autolysosomes for degradation, preventing toxic protein aggregation. Dysregulation leads
to alpha-synuclein accumulation, contributing to Lewy bodies characteristic of Parkinson’s
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pathology. Proper autophagy-lysosomal function is vital for neuronal health, and therapeutic
strategies targeting this pathway may alleviate proteinopathy, offering a promising avenue for
PD interventions [43].
7) JNK (c-Jun N-terminal kinase) pathway
This pathway is implicated in neurodegeneration. Activated JNK contributes to DA neuronal
death, fostering inflammation, oxidative stress, and promoting alpha-synuclein aggregation.
These processes collectively drive the progression of PD pathology. Modulating the JNK path-
way emerges as a potential therapeutic strategy to impede neuroinflammation and apoptotic
cascades, offering avenues for disease intervention and neuroprotection in PD [44].
8) AMPK (AMP-activated protein kinase) pathway
This pathway is implicated in PD and is essential for maintaining cellular energy balance. In PD,
AMPK activation is associated with neuroprotection. Activated AMPK helps maintain cellular
energy balance, regulates mitochondrial function, and suppresses oxidative stress, contributing
to neuronal survival. Modulating the AMPK pathway presents a potential therapeutic avenue for
PD, aiming to enhance cellular resilience, improve energy metabolism, and mitigate
neurodegenerative processes. Understanding the intricate involvement of AMPK in PD
pathophysiology offers insights into novel strategies for disease-modifying interventions [45].
9) Nrf2 (nuclear factor erythroid 2-related factor 2) pathway
The Nrf2 pathway is crucial in cellular defense against oxidative stress and inflammation, and
its dysregulation is implicated in PD. In PD, diminished Nrf2 activity contributes to increased
oxidative damage and neuroinflammation. Nrf2 regulates the expression of antioxidant and
detoxification genes, promoting cellular resilience. Therapeutic strategies aiming to enhance
Nrf2 activation show promise in mitigating PD-related neurodegeneration. Understanding the
dynamics of the Nrf2 pathway offers insights into potential interventions to bolster cellular
defenses, reduce oxidative stress, and counteract the progression of PD [46].
Understanding these signaling pathways provides insights into the molecular mechanisms
underlying PD. Targeting specific pathways may offer therapeutic strategies to modify disease
progression.
16.4.4 Enzymatic Targets in Parkinson’s Disease
The targets for PD involve key enzymes or proteins associated with processes such as neurotrans-
mitter regulation, oxidative stress, and protein degradation. Some notable enzymatic targets and
their mechanism are depicted in Figure 16.3.
1) MAO-B (monoamine oxidase B)
MAO-B inhibition is a therapeutic strategy in PD management. In PD, DA neurons degenerate,
leading to dopamine deficiency. MAO-B, an enzyme, metabolizes dopamine, exacerbating its
depletion. Inhibiting MAO-B preserves dopamine levels, alleviating PD symptoms. Selegiline
and rasagiline are FDA-approved MAO-B inhibitors used as adjuncts to levodopa therapy,
enhancing its efficacy and extending its duration of action. By reducing oxidative stress and
neuroinflammation, MAO-B inhibition may also exert neuroprotective effects. Targeting
MAO-B offers symptomatic relief and potential disease-modifying benefits in PD, making it a
valuable enzymatic target in the management of this neurodegenerative disorder [47].
2) COMT (catechol-O-methyltransferase)
COMT inhibition is a therapeutic avenue in PD treatment. In PD, DA neurons degenerate, leading
to dopamine depletion. COMT, an enzyme, metabolizes levodopa, reducing its efficacy and