Small-molecule LRRK2 inhibitors for PD therapy: Current achievements and future perspectives

Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases

Neurodegenerative diseases (NDs) are one of the prominent health challenges facing contemporary society, and many efforts have been made to overcome and (or) control it. In this research paper, we described a practical one-pot two-step three-component reaction between 3,4-dihydronaphthalen-1(2H)-one (1), aryl(or heteroaryl)glyoxal monohydrates (2a-h), and hydrazine monohydrate (NH2NH2•H2O) for the regioselective preparation of some 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnoline derivatives (3a-h). After synthesis and characterization of the mentioned cinnolines (3a-h), the in silico multi-targeting inhibitory properties of these heterocyclic scaffolds have been investigated upon various Homo sapiens-type enzymes, including hMAO-A, hMAO-B, hAChE, hBChE, hBACE-1, hBACE-2, hNQO-1, hNQO-2, hnNOS, hiNOS, hPARP-1, hPARP-2, hLRRK-2(G2019S), hGSK-3β, hp38α MAPK, hJNK-3, hOGA, hNMDA receptor, hnSMase-2, hIDO-1, hCOMT, hLIMK-1, hLIMK-2, hRIPK-1, hUCH-L1, hPARK-7, and hDHODH, which have confirmed their functions and roles in the neurodegenerative diseases (NDs), based on molecular docking studies, and the obtained results were compared with a wide range of approved drugs and well-known (with IC50, EC50, etc.) compounds. In addition, in silico ADMET prediction analysis was performed to examine the prospective drug properties of the synthesized heterocyclic compounds (3a-h). The obtained results from the molecular docking studies and ADMET-related data demonstrated that these series of 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines (3a-h), especially hit ones, can really be turned into the potent core of new drugs for the treatment of neurodegenerative diseases (NDs), and/or due to the having some reactionable locations, they are able to have further organic reactions (such as cross-coupling reactions), and expansion of these compounds (for example, with using other types of aryl(or heteroaryl)glyoxal monohydrates) makes a new avenue for designing novel and efficient drugs for this purpose.

Concurrent Optimizations of Efficacy and Blood-Brain Barrier Permeability in New Macrocyclic LRRK2 Inhibitors for Potential Parkinson's Disease Therapeutics

The elevated activity of leucine-rich repeat kinase 2 (LRRK2) is implicated in the pathogenesis of Parkinson's disease (PD). The quest for effective LRRK2 inhibitors has been impeded by the formidable challenge of crossing the blood-brain barrier (BBB). We leveraged structure-based de novo design and developed robust three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict BBB permeability, enhancing the likelihood of the inhibitor's brain accessibility. Our strategy involved the synthesis of macrocyclic molecules by linking the two terminal nitrogen atoms of HG-10-102-01 with an alkyl chain ranging from 2 to 4 units, laying the groundwork for innovative LRRK2 inhibitor designs. Through meticulous computational and synthetic optimization of both biochemical efficacy and BBB permeability, 9 out of 14 synthesized candidates demonstrated potent low-nanomolar inhibition and significant BBB penetration. Further assessments of in vitro and in vivo effectiveness, coupled with pharmacological profiling, highlighted 8 as the promising new lead compound for PD therapeutics.

Data-driven disease progression model of Parkinson's disease and effect of sex and genetic variants

As Parkinson's disease (PD) progresses, there are multiple biomarker changes, and sex and genetic variants may influence the rate of progression. Data-driven, long-term disease progression model analysis may provide precise knowledge of the relationships between these risk factors and progression and would allow for the selection of appropriate diagnosis and treatment according to disease progression. To construct a long-term disease progression model of PD based on multiple biomarkers and evaluate the effects of sex and leucine-rich repeat kinase 2 (LRRK2) mutations, a technique derived from the nonlinear mixed-effects model (Statistical Restoration of Fragmented Time course [SReFT]) was applied to datasets of patients provided by the Parkinson's Progression Markers Initiative. Four biomarkers, including the Unified PD Rating Scale, were used, and a covariate analysis was performed to investigate the effects of sex and LRRK2-related mutations. A model of disease progression over ~30 years was successfully developed using patient data with a median of 6 years. Covariate analysis suggested that female sex and LRRK2 G2019S mutations were associated with 21.6% and 25.4% significantly slower progression, respectively. LRRK2 rs76904798 mutation also tended to delay disease progression by 10.4% but the difference was not significant. In conclusion, a long-term PD progression model was successfully constructed using SReFT from relatively short-term individual patient observations and depicted nonlinear changes in relevant biomarkers and their covariates, including sex and genetic variants.

Pharmacology of LRRK2 with type I and II kinase inhibitors revealed by cryo-EM

LRRK2 is one of the most promising drug targets for Parkinson's disease. Though type I kinase inhibitors of LRRK2 are under clinical trials, alternative strategies like type II inhibitors are being actively pursued due to the potential undesired effects of type I inhibitors. Currently, a robust method for LRRK2-inhibitor structure determination to guide structure-based drug discovery is lacking, and inhibition mechanisms of available compounds are also unclear. Here we present near-atomic-resolution structures of LRRK2 with type I (LRRK2-IN-1 and GNE-7915) and type II (rebastinib, ponatinib, and GZD-824) inhibitors, uncovering the structural basis of LRRK2 inhibition and conformational plasticity of the kinase domain with molecular dynamics (MD) simulations. Type I and II inhibitors bind to LRRK2 in active-like and inactive conformations, so LRRK2-inhibitor complexes further reveal general structural features associated with LRRK2 activation. Our study provides atomic details of LRRK2-inhibitor interactions and a framework for understanding LRRK2 activation and for rational drug design.

Inhibition of Parkinson's disease-related LRRK2 by type I and type II kinase inhibitors: Activity and structures

Mutations in leucine-rich repeat kinase 2 (LRRK2) are a common cause of familial Parkinson's disease (PD) and a risk factor for the sporadic form. Increased kinase activity was shown in patients with both familial and sporadic PD, making LRRK2 kinase inhibitors a major focus of drug development efforts. Although much progress has been made in understanding the structural biology of LRRK2, there are no available structures of LRRK2 inhibitor complexes. To this end, we solved cryo-electron microscopy structures of LRRK2, wild-type and PD-linked mutants, bound to the LRRK2-specific type I inhibitor MLi-2 and the broad-spectrum type II inhibitor GZD-824. Our structures revealed an active-like LRRK2 kinase in the type I inhibitor complex, and an inactive DYG-out in the type II inhibitor complex. Our structural analysis also showed how inhibitor-induced conformational changes in LRRK2 are affected by its autoinhibitory N-terminal repeats. The structures provide a template for the rational development of LRRK2 kinase inhibitors covering both canonical inhibitor binding modes.

Recent advances in targeting leucine-rich repeat kinase 2 as a potential strategy for the treatment of Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease. Several single gene mutations involved in PD have been identified such as leucine-rich repeat kinase 2 (LRRK2), the most common cause of sporadic and familial PD. Its mutations have attracted much attention to therapeutically targeting this kinase. To date, many compounds including small chemical molecules with diverse scaffolds and RNA agents have been developed with significant amelioration in preclinical PD models. Currently, five candidates, DNL201, DNL151, WXWH0226, NEU-723 and BIIB094, have advanced to clinical trials for PD treatment. In this review, we describe the structure, pathogenic mutations and the mechanism of LRRK2, and summarize the development of LRRK2 inhibitors in preclinical and clinical studies, trying to provide an insight into targeting LRRK2 for PD intervention in future.

Leucine-rich repeat kinase 2 (LRRK2) inhibition upregulates microtubule-associated protein 1B to ameliorate lysosomal dysfunction and parkinsonism

Mutations in LRRK2 (encoding leucine-rich repeat kinase 2 protein, LRRK2) are the most common genetic risk factors for Parkinson's disease (PD), and increased LRRK2 kinase activity was observed in sporadic PD. Therefore, inhibition of LRRK2 has been tested as a disease-modifying therapeutic strategy using the LRRK2 mutant mice and sporadic PD. Here, we report a newly designed molecule, FL090, as a LRRK2 kinase inhibitor, verified in cell culture and animal models of PD. Using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mice and SNCA A53T transgenic mice, FL090 ameliorated motor dysfunctions, reduced LRRK2 kinase activity, and rescued loss in the dopaminergic neurons in the substantia nigra. Notably, by RNA-Seq analysis, we identified microtubule-associated protein 1 (MAP1B) as a crucial mediator of FL090's neuroprotective effects and found that MAP1B and LRRK2 co-localize. Overexpression of MAP1B rescued 1-methyl-4-phenylpyridinium induced cytotoxicity through rescuing the lysosomal function, and the protective effect of FL090 was lost in MAP1B knockout cells. Further studies may be focused on the in vivo mechanisms of MAP1B and microtubule function in PD. Collectively, these findings highlight the potential of FL090 as a therapeutic agent for sporadic PD and familial PD without LRRK2 mutations.

ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks

In recent years, drug design has been revolutionized by the application of deep learning techniques, and molecule generation is a crucial aspect of this transformation. However, most of the current deep learning approaches do not explicitly consider and apply scaffold hopping strategy when performing molecular generation. In this work, we propose ScaffoldGVAE, a variational autoencoder based on multi-view graph neural networks, for scaffold generation and scaffold hopping of drug molecules. The model integrates several important components, such as node-central and edge-central message passing, side-chain embedding, and Gaussian mixture distribution of scaffolds. To assess the efficacy of our model, we conduct a comprehensive evaluation and comparison with baseline models based on seven general generative model evaluation metrics and four scaffold hopping generative model evaluation metrics. The results demonstrate that ScaffoldGVAE can explore the unseen chemical space and generate novel molecules distinct from known compounds. Especially, the scaffold hopped molecules generated by our model are validated by the evaluation of GraphDTA, LeDock, and MM/GBSA. The case study of generating inhibitors of LRRK2 for the treatment of PD further demonstrates the effectiveness of ScaffoldGVAE in generating novel compounds through scaffold hopping. This novel approach can also be applied to other protein targets of various diseases, thereby contributing to the future development of new drugs. Source codes and data are available at https://github.com/ecust-hc/ScaffoldGVAE .

Autophagy in Parkinson's Disease

Parkinson's disease (PD) is a devastating disease associated with accumulation of α-synuclein (α-Syn) within dopaminergic neurons, leading to neuronal death. PD is characterized by both motor and non-motor clinical symptoms. Several studies indicate that autophagy, an important intracellular degradation pathway, may be involved in different neurodegenerative diseases including PD. The autophagic process mediates the degradation of protein aggregates, damaged and unneeded proteins, and organelles, allowing their clearance, and thereby maintaining cell homeostasis. Impaired autophagy may cause the accumulation of abnormal proteins. Incomplete or impaired autophagy may explain the neurotoxic accumulation of protein aggregates in several neurodegenerative diseases including PD. Indeed, studies have suggested the contribution of impaired autophagy to α-Syn accumulation, the death of dopaminergic neurons, and neuroinflammation. In this review, we summarize the recent literature on the involvement of autophagy in PD pathogenesis.