Publications

Parkinson's disease (PD) is characterized by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key enzyme in the kynurenine pathway (KP), has been implicated in these disturbances. TDO's regulation of tryptophan metabolism outside the central nervous system (CNS) plays a critical role in maintaining the balance between serotonin and kynurenine-derived metabolites, with its dysfunction contributing to the worsening of PD symptoms. Recent studies suggest that targeting TDO may help alleviate non-motor symptoms of PD, providing an alternative to conventional dopamine replacement therapies. In this study, a data-driven computational pipeline was employed to identify natural products as potential TDO inhibitors. Machine learning and convolutional neural network-based QSAR models were developed to predict TDO inhibitory activity. Molecular docking revealed strong binding affinities for several compounds, with scores ranging from −9.6 to −10.71 kcal/mol, surpassing that of tryptophan (−6.86 kcal/mol), and indicating favorable interactions. ADMET profiling assessed pharmacokinetic properties, confirming that the selected compounds could cross the blood–brain barrier (BBB), suggesting potential CNS activity. Molecular dynamics (MD) simulations provided further insight into the binding stability and dynamic behavior of the top candidates within the TDO active site under physiological conditions. Notably, Peniciherquamide C maintained stronger and more stable interactions than the native substrate tryptophan throughout the simulation. MM/PBSA decomposition analysis highlighted the energetic contributions of van der Waals, electrostatic, and solvation forces, supporting the binding stability of key compounds. This integrated computational approach highlights the potential of natural products as TDO inhibitors, identifying promising leads that address PD symptoms beyond traditional dopamine-centric therapies. Nonetheless, experimental validation is necessary to confirm these findings.

In recent years, the increasing spread of antibiotic-resistant bacteria has become one of the most significant public health problems. This resistance is largely due to the formation of biofilms and the expression of virulence factors, which are primarily controlled by a cell communication system called quorum sensing (QS). Therefore, screening a range of compounds for anti-biofilm or anti-QS activities is essential. In *Pseudomonas aeruginosa* (*P. aeruginosa*), a Gram-negative opportunistic human pathogen and one of the leading causes of hospital-acquired infections, QS is regulated by six proteins: LasR, LasI, RhlR, RhlI, PqsR, and PqsA. *Stachys* species are known for their antimicrobial activity. This study aimed to screen natural molecules from the *Stachys* database as potential inhibitors of these proteins. A total of 186 molecules from the *Stachys* database were virtually screened against the selected target proteins. Molecules that qualified were filtered based on Lipinski's rule of five and ADMET properties. Ten potential QS-inhibiting biomolecules were identified: 5-demethylnobiletin, chrysosplenetin, 3'-methoxycalycoptarin, 8-methoxycirsilinol, calycoptarin, casticin, 5- hydroxyauranetin, 5,3',4'-trihydroxy-3,6,7,8-tetramethoxyflavone, syringic acid, and vanillic acid. These molecules were further docked against the six proteins using AutoDockTools to understand the molecular interactions and identify the most effective inhibitor among them. Based on the docking results, chrysosplenetin (ID 5281608) for LasI, 5-demethoxyflavone (ID 358832) for LasR, syringic acid (ID 10742) for RhlR, and 5,3',4'-trihydroxy-3,6,7,8-tetramethoxyflavone (ID 54799) for the proteins RhlI, PqsA, and PqsR were proposed as the best candidates for quorum sensing inhibition in terms of energy and interactions.

The exact cause of Parkinson's disease is unknown, and there is currently no cure for the disease. However, there are several treatment options available to help manage its symptoms. The prevalence of PD has been increasing globally, including in Morocco. This study investigated the potential of Aloysia citriodora, also known as lemon verbena, for treating Parkinson's disease. Lemon verbena is a plant commonly used in Morocco for treating central nervous system related diseases. It has been traditionally used as a relaxant and sedative, and its antioxidant and antimicrobial properties have been documented. In this study, we employed molecular docking against multiple targets associated with PD to evaluate the binding affinities of the phytochemicals present in lemon verbena and elucidate their interaction profiles. Interestingly, catechin emerged as a promising bioactive molecule, outperforming reference drugs in interactions with four proteins. Pharmacokinetic/toxicity predictions were conducted to evaluate the drug-likeness of the phytocompounds. Finally, molecular dynamics simulations were performed to evaluate the stability of the protein-ligand complexes over time. By integrating computational methods, this investigation aimed to uncover the therapeutic potential of Aloysia citriodora compounds in Parkinson's disease management and provide valuable insights into their molecular interactions and pharmacokinetic properties. The findings of this study suggest that Aloysia citriodora, particularly its constituent catechin, has the potential to be a therapeutic agent for PD. Further research is needed to validate these findings in experimental and clinical settings.

The effectiveness of antibiotics against Pseudomonas aeruginosa (P. aeruginosa) infections is limited by inherent antimicrobial resistance, prompting researchers to seek advanced and cost-effective antibacterial agents. This opportunistic bacterium exhibits drug resistance and regulates its pathogenicity through quorum sensing (QS) mechanisms, suggesting that disrupting these systems could be a promising approach to treating P. aeruginosa infections. In this study, we investigated the antibacterial properties of silver nanoparticles (AgNPs), zinc oxide nanoparticles (ZnONPs), and copper oxide nanoparticles (CuONPs) in conjunction with QS systems, focusing on the LasI/R, RhlI/R, and PqsA/PqsR pathways. A computational approach was utilized to examine the interaction patterns between these nanoparticles and QS signaling proteins in P. aeruginosa through multiple bioinformatics techniques. The interaction of metals and metal oxides with acyl-homoserine-lactone synthases (LasI, RhlI, PqsA) can impede the binding of precursor molecules, thereby inhibiting the synthesis of functional signaling molecules. Moreover, the binding of nanoparticles to regulatory proteins (LasR, RhlR, PqsR) competes with functional signaling molecules, resulting in a reduced expression of QS-controlled genes. Among the nanoparticles studied, ZnONPs exhibited the highest affinity toward the selected targets. In particular, the PqsA-ZnONPs complex showed stable active binding sites and a high binding affinity (−3.83 kcal/mol), indicating strong interaction with the active pocket of the pathogen *P. aeruginosa* (PqsA: 5OE3). ZnO nanoparticles demonstrated significant potential as antimicrobial agents against *P. aeruginosa* by disrupting its QS systems. This approach presents a promising direction for developing therapeutic strategies to combat antibiotic-resistant bacteria, including P. aeruginosa.

Monoamine oxidase B (MAO-B) plays a pivotal role in the deamination process of monoamines, encompassing crucial neurotransmitters like dopamine and norepinephrine. The heightened interest in MAO-B inhibitors emerged after the revelation that this enzyme could potentially catalyze the formation of neurotoxic compounds from endogenous and exogenous sources. Computational screening methodologies serve as valuable tools in the quest for novel inhibitors, enhancing the efficiency of this pursuit. In this study, 43 acefylline derivatives were docked against the MAO-B enzyme for their chemotherapeutic potential and binding affinities that yielded GOLD fitness scores ranging from 33.21 to 75.22. Among them, five acefylline derivatives, namely, MAO-B14, MAO-B15, MAO-B16, MAO-B20, and MAO-B21, displayed binding affinities comparable to both standards istradefylline and safinamide. These derivatives exhibited hydrogen-bonding interactions with key amino acids Phe167 and Ile197/198, suggesting their strong potential as MAO-B inhibitors. Finally, molecular dynamics (MD) simulations were conducted to evaluate the stability of the examined acefylline derivatives over time. The simulations demonstrated that among the examined acefylline derivatives and standards, MAO-B21 stands out as the most stable candidate. Density functional theory (DFT) studies were also performed to optimize the geometries of the ligands, and molecular docking was conducted to predict the orientations of the ligands within the binding cavity of the protein and evaluate their molecular interactions. These results were also validated by simulation-based binding free energies via the molecular mechanics energies combined with generalized Born and surface area solvation (MM-GBSA) method. However, it is necessary to conduct in vitro and in vivo experiments to confirm and validate these findings in future studies.

Currently available treatments for Parkinson’s disease offer limited symptomatic relief to patients and do not halt the progress of the disease. Several studies have reported that the use of a multi-targeting approach for treating neurodegenerative diseases may prove more beneficial for patients. In this study, two successful drug targets for treating Parkinson’s disease known for their potential to slow down neuronal loss were selected. Natural products have long been known to be effective and safe in treating various diseases. Therefore, we used computational approaches to screen the North, East, and South African Natural Products databases for novel dual-targeting drug candidates against MAO-B and AA2AR. A hybrid virtual screening was performed through pharmacophore modelling and molecular docking followed by ADME/toxicity evaluation. Our results revealed two furanoisoflavones with equally favourable binding affinities and interaction profiles for MAO-B and AA2AR as well as desirable pharmacokinetic properties for drugs acting on the brain. Molecular dynamics simulations were conducted to assess the stability of the lead compounds and the reference drugs over time. The findings emphasized the notable stability of the suggested drugs in comparison to safinamide. Notably, 7,3’-dimethoxy-4’,5’-methylenedioxyisoflavone established a crucial hydrogen bond with Gln-206, a characteristic interaction observed in most MAO-B inhibitors. Regarding AA2AR, while the interaction strength with Asn-253 may not match that of the reference drug, simulation results indicated a parallel trend in protein interaction, suggesting its potential as an antagonist. The findings from this study could potentially act as starting points for refining and developing natural products into disease-modifying remedies for Parkinson’s disease patients. Nevertheless, it is imperative to conduct experimental assays to substantiate these discoveries.

The ongoing COVID-19 pandemic has highlighted the urgent need for effective antiviral treatments to combat the spread of the virus. Natural products have emerged as a valuable source of potential drug candidates, given their diverse chemical structures and ability to inhibit viral replication. In this study, we selected a dataset of 356 antiviral natural products from the Ambinter chemical library and screened them for their ability to inhibit the main protease (Mpro), a key target for drug development against SARS-CoV-2 using molecular docking in order to estimate their potential pharmacological activity. Furthermore, we evaluated the selected compounds' physicochemical properties and pharmacokinetic parameters to assess their drug-likeness. Finally, molecular dynamics simulations were conducted on the highest-ranking compounds to assess their stability and molecular interactions over time. Our findings indicate that the compounds Amb18482894 and Amb1953578 belonging to the flavones and the flavonolignans chemical classes exhibit strong affinity towards Mpro with binding scores of −8.4 and −8.0 kcal/mol, respectively, which were found to be higher than the reference compound, masitinib. Moreover, better stability was observed in the studied natural compounds in complex with Mpro, suggesting their potential as future drug candidates for COVID-19. This study contributes to the ongoing efforts to identify safe and effective treatments for this global health crisis.

Introduction Dendrobium nobile Lindl alkaloids, or DNLA for short, are the most active ingredients found in D.nobile, a top grade plant in Shen Nong Ben Cao Jing, with an extensive history of medicinal use in Chinese traditional medicine (TCM) as a multifunctional therapeutic agent. Recent evidence has emerged linking the neuroprotective and anti-aging effects of DNLA to their involvement in promoting autophagy of toxic amyloid-β (Aβ) plaques and modulation of key enzymes involved in the hyperphosphorylation of Tau proteins. Although amyloid buildup and the aggregation of Tau proteins are central to the onset of Alzheimer's disease (AD), evidence on how DNLA relate to other overlooked dysregulated AD-associated pathways is still lacking. Methods We intend on deciphering the underlying mechanisms driving the anti-AD effect of DNLA, using a combination of network analysis based on differentially expressed genes found in AD patients, target fishing, centrality analysis, enrichment analysis and hub genes identification. Results In total, 2069 genes were found differentially expressed in SRP181886 and a PPI network constructed with common targets between DNLA and AD. Five hub genes were identified having a discriminatory power greater than 0.7; HTR2A, GRIN2B, GABRA1, HTR2C, GRIN2A, with the former being the top bottleneck node in the network. Enrichment analysis found that DNLA exert an anti-AD effect through the regulation of the calcium signaling pathway and the serotonergic system, by modulating key receptors implicated in excitatory inhibitory neurotransmission. Additionally, DNLA were found to modulate two subunits of NMDA receptor involved in the release of pro-inflammatory cytokines, underlying the possible involvement of DNLA in neuroinflammation. Discussion This further emphasizes the therapeutic value of D.nobile and the multi-target, multi-pathway potential of DNLA to counteract the deleterious effects of calcium dysregulation and excitatory toxicity in AD, while providing evidence-based rationale behind the traditional use of D. nobile in TCM.

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from −7.8 to −7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections.

GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson’s disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer’s disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A.

Parkinson’s disease is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the midbrain. Current treatments provide limited symptomatic relief without halting disease progression. A multi-targeting approach has shown potential benefits in treating neurodegenerative diseases. In this study, we employed in silico approaches to explore the COCONUT natural products database and identify novel drug candidates with multi-target potential against relevant Parkinson’s disease targets. QSAR models were developed to screen for potential bioactive molecules, followed by a hybrid virtual screening approach involving pharmacophore modeling and molecular docking against MAO-B, AA2AR, and NMDAR. ADME evaluation was performed to assess drug-like properties. Our findings revealed 22 candidates that exhibited the desired pharmacophoric features. Particularly, two compounds: CNP0121426 and CNP0242698 exhibited remarkable binding affinities, with energies lower than −10 kcal/mol and promising interaction profiles with the chosen targets. Furthermore, all the ligands displayed desirable pharmacokinetic properties for brain-targeted drugs. Lastly, molecular dynamics simulations were conducted on the lead candidates, belonging to the dihydrochalcone and curcuminoid class, to evaluate their stability over a 100 ns timeframe and compare their dynamics with reference complexes. Our findings revealed the curcuminoid CNP0242698 to have an overall better stability with the three targets compared to the dihydrochalcone, despite the high ligand RMSD, the curcuminoid CNP0242698 showed better protein stability, implying ligand exploration of different orientations. Similarly, AA2AR exhibited higher stability with CNP0242698 compared to the reference complex, despite the high initial ligand RMSD due to the bulkier active site. In NMDAR, CNP0242698 displayed good stability and less fluctuations implying a more restricted conformation within the smaller active site of NMDAR. These results may serve as lead compounds for the development and optimization of natural products as multi-target disease-modifying natural remedies for Parkinson’s disease patients. However, experimental assays remain necessary to validate these findings.

Parkinson’s disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and accumulation of α-synuclein fibrils is considered a neuropathological hallmark of Parkinson’s disease. Several synthetic and natural compounds have been tested for their potency to inhibit the aggregation of α-synuclein. However, the molecular mechanisms responsible for the potency of these drugs to further rationalize their development and optimization are yet to be determined. To enhance our understanding of the structural requirements necessary for modulating the aggregation of α-synuclein fibrils, we retrieved a large dataset of α-synuclein inhibitors with their reported potency from the ChEMBL database to explore their chemical space and to generate QSAR models for predicting new bioactive compounds. The best performing QSAR model was applied to the LOTUS natural products database to screen for potential α-synuclein inhibitors followed by a pharmacophore design using the representative compounds sampled from each cluster in the ChEMBL dataset. Five natural products were retained after molecular docking studies displaying a binding affinity of − 6.0 kcal/mol or lower. ADMET analysis revealed satisfactory properties and predicted that all the compounds can cross the blood–brain barrier and reach their target. Finally, molecular dynamics simulations demonstrated the superior stability of LTS0078917 compared to the clinical candidate, Anle138b. We found that LTS0078917 shows promise in stabilizing the α-synuclein monomer by specifically binding to its hairpin-like coil within the N-terminal region. Our dynamic analysis of the inhibitor-monomer complex revealed a tendency towards a more compact conformation, potentially reducing the likelihood of adopting an elongated structure that favors the formation and aggregation of pathological oligomers. These findings offer valuable insights for the development of novel α-synuclein inhibitors derived from natural sources.

Coumarins are a highly privileged scaffold in medicinal chemistry. It is present in many natural products and is reported to display various pharmacological properties. A large plethora of compounds based on the coumarin ring system have been synthesized and were found to possess biological activities such as anticonvulsant, antiviral, anti-inflammatory, antibacterial, antioxidant as well as neuroprotective properties. Despite the wide activity spectrum of coumarins, its naturally occurring derivatives are yet to be investigated in detail. In the current study, a chemical library was created to assemble all chemical information related to naturally occurring coumarins from the literature. Additionally, a multi-stage virtual screening combining QSAR modeling, molecular docking, and ADMET prediction was conducted against monoamine oxidase B and acetylcholinesterase, two relevant targets known for their neuroprotective properties and ‘disease-modifying’ potential in Parkinson’s and Alzheimer’s disease. Our findings revealed ten coumarin derivatives that may act as dual-target drugs against MAO-B and AChE. Two coumarin candidates were selected from the molecular docking study: CDB0738 and CDB0046 displayed favorable interactions for both proteins as well as suitable ADMET profiles. The stability of the selected coumarins was assessed through 100 ns molecular dynamics simulations which revealed promising stability through key molecular interactions for CDB0738 to act as dual inhibitor of MAO-B and AChE. However, experimental studies are necessary to evaluate the bioactivity of the proposed candidate. The current results may generate an increasing interest in bioprospecting naturally occurring coumarins as potential candidates against relevant macromolecular targets by encouraging virtual screening studies against our chemical library.

Coumarins are considered a highly privileged and versatile scaffold by medicinal chemists. A considerable number of studies have highlighted the synthesis and the various pharmacological activities of coumarins as promising drug candidates for treating neurodegenerative diseases such as Parkinson’s and Alzheimer’s disease. A wide range of compounds based on the coumarin ring system have been found to possess biological activities such as anticonvulsant, antiviral, anti-inflammatory, antibacterial, antioxidant as well as monoamine oxidase inhibitory properties. Their promise as a novel drug for neurodegenerative diseases is demonstrated by many drug candidates that made it to clinical trials such as nodakenin that have been potent for demoting memory impairment. This study focuses on some synthesized alkynyl-coumarinyl ethers with promising MAO-B inhibitory activity and selectivity and aims to elucidates the molecular interactions of ether-connected coumarins behind obtaining remarkably high MAO-B selectivity using molecular docking. Structure-activity relationship analysis revealed a common interaction between the selective coumarin inhibitors consisting of hydrogen bonding with Tyr-188 and Cys-172. Our findings might open new opportunities to explore for developing novel highly selective MAO-B inhibitors for the treatment of neurodegenerative diseases.

In the current report, 3D structures of the enzyme Lathyrus aphaca Ribulose bisphosphate carboxylase (LArbcL) was modeled using homology modeling. The structures of the synthesized β-amino carbonyl derivatives were made by means of “Chem Draw ultra-12.0”, ADMET prediction were conducted to compute physicochemical properties. Pharmacokinetics studies and the molecular docking study of the synthesized compounds were performed against Lathyrus aphaca Ribulose bisphosphate carboxylase. Docking experiments verified a significant Docking Score values between 6.2 to 7.3 kcal mol−1. The highest-ranking complexes obtained from docking results were subjected to 100 ns Molecular Dynamics simulations using Gromacs program to investigate the constancy of the docked “protein–ligand complexes” as well as the oscillation and conformational variations that occur during protein–ligand interaction. The synthesized derivatives were screened for pre-emergence and post-emergence herbicidal activity adjacent to weed species named Lathyrus aphaca with concentrations of “0.005 M, 0.01 M and 0.02 M”, and the activity was compared with Butachlor and penoxulum which are standard herbicide. Every single synthesized compounds show good to moderate activity.

Parkinson’s disease is considered the second most frequent neurodegenerative disease. It is described by the loss of dopaminergic neurons in the mid-brain. For many decades, L-DOPA has been considered as the gold standard for treating Parkinson’s disease motor symptoms, however, due to the decrease of efficacy, in the long run, there is an urgent need for novel antiparkinsonian drugs. Caffeine derivatives have been reported several times for their neuroprotective properties and dual blockade of monoamine oxidase (MAO) and adenosine A2A receptors (AA2AR). Natural products are currently attracting more focus due to structural diversity and safety in contrast to synthetic drugs. In the present work, computational studies were conducted on natural product-like caffeine derivatives to search for novel potent candidates acting as dual MAO-B inhibitors/AA2AR antagonists for Parkinson’s disease. Our findings revealed two natural products among the top hits: CNP0202316 and CNP0365210 fulfill the requirements of drugs acting on the brain. The selected lead compounds were further studied using molecular dynamics simulation to assess their stability with MAO-B. Current findings might shift the interest towards natural-based compounds and could be exploited to further optimize caffeine derivatives into a successful dual-target-directed drug for managing and halting the neuronal damage in Parkinson’s disease patients.

Monoamine Oxidase B is considered a successful target for developing antiparkinsonian drugs. Due to the side effects of current MAO-B inhibitors, there’s an urgent need for novel potent and highly selective MAO-B inhibitors. A recent study has shown that coumarins tend to be more selective towards MAO-B than MAO-A when connected to a hex-5-ynyloxy chain at position 6 in contrast to their C7-isomers. The present study describes the mode of interaction of the C6 and C7-substituted coumarin isomers characterized by their difference in selectivity towards MAO-B through molecular docking and molecular dynamics simulations in an effort to elucidate the structural components and molecular interactions that may be responsible for MAO-B selectivity. Three isomeric coumarin pairs connected to ether chain at position 6 or 7 were taken from the literature and modelled according to their IUPAC nomenclature. Molecular docking study revealed one π- π stacking interaction with Tyr-326 in common between the selective coumarin C6-isomers. Resulting complexes of one isomeric coumarin pair that displayed the highest selectivity shift towards MAO-B were subject to 100 ns molecular dynamics simulations study to analyze the stability of the docked complexes. Molecular dynamics revealed that the C7-isomer is relatively stable in both MAO isoforms through the simulation duration, whereas the C6-isomer deemed unstable for MAO-A which may be due to the bulky Phe-208 residue in MAO-A. Our results might be applied for further development and optimization of coumarin derivatives into a successful drug against Parkinson’s disease.