VenomPred 2.0: A Novel In Silico Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particularly in lead optimization and ADMET studies, and to meet the principles of the 3Rs, which calls for the replacement, reduction, and refinement of animal testing. In this context, we herein present the development of VenomPred 2.0 (http://www.mmvsl.it/wp/venompred2/), the new and improved version of our free of charge web tool for toxicological predictions, which now represents a powerful web-based platform for multifaceted and human-interpretable in silico toxicity profiling of chemicals. VenomPred 2.0 presents an extended set of toxicity endpoints (androgenicity, skin irritation, eye irritation, and acute oral toxicity, in addition to the already available carcinogenicity, mutagenicity, hepatotoxicity, and estrogenicity) that can be evaluated through an exhaustive consensus prediction strategy based on multiple ML models. Moreover, we also implemented a new utility based on the Shapley Additive exPlanations (SHAP) method that allows human interpretable toxicological profiling of small molecules, highlighting the features that strongly contribute to the toxicological predictions in order to derive structural toxicophores.

Watermelon: setup and validation of an in silico fragment-based approach.

We present a new computational approach, named Watermelon, designed for the development of pharmacophore models based on receptor structures. The methodology involves the sampling of potential hotspots for ligand interactions within a protein target's binding site, utilising molecular fragments as probes. By employing docking and molecular dynamics (MD) simulations, the most significant interactions formed by these probes within distinct regions of the binding site are identified. These interactions are subsequently transformed into pharmacophore features that delineates key anchoring sites for potential ligands. The reliability of the approach was experimentally validated using the monoacylglycerol lipase (MAGL) enzyme. The generated pharmacophore model captured features representing ligand-MAGL interactions observed in various X-ray co-crystal structures and was employed to screen a database of commercially available compounds, in combination with consensus docking and MD simulations. The screening successfully identified two new MAGL inhibitors with micromolar potency, thus confirming the reliability of the Watermelon approach.

MolBook UNIPI─Create, Manage, Analyze, and Share Your Chemical Data for Free.

Here, we present MolBook UNIPI, freely available and user-friendly software specifically designed for medicinal chemists as a powerful tool for the easy management of virtual libraries of chemical compounds. With MolBook UNIPI, it is possible to create, store, handle, and share molecular databases in a very simple and intuitive way. The software allows users to rapidly generate libraries of bioactive ligands, building blocks, or commercial compounds by either manually creating single molecules or automatically importing compounds from public databases and pre-existing libraries. MolBook UNIPI databases can be enriched with all kinds of data and can be filtered based on molecular structures or properties, allowing the desired molecules, along with their structures and features, to be easily accessible in just a few clicks. Moreover, new molecular properties and potential toxicological effects of compounds can be rapidly and reliably predicted. Notably, all of these functions can be easily mastered even by inexperienced users, with no prior cheminformatics knowledge or programming skills, which makes MolBook UNIPI an invaluable tool for medicinal chemists. MolBook UNIPI can be downloaded free of charge from the project web page https://molbook.farm.unipi.it/.

Tau protein quantification in skin biopsies differentiates tauopathies from alpha-synucleinopathies.

Abnormal accumulation of microtubule-associated protein tau (τ) is a characteristic feature of atypical parkinsonisms with tauopathies, such as progressive supranuclear palsy and corticobasal degeneration. However, pathological τ has also been observed in α-synucleinopathies like Parkinson's disease and multiple system atrophy. Based on the involvement of the peripheral nervous system in several neurodegenerative diseases, we characterized and compared τ expression in skin biopsies of patients clinically diagnosed with Parkinson's disease, multiple system atrophy, progressive supranuclear palsy and corticobasal degeneration and in healthy control subjects. In all groups, τ protein was detected along both somatosensory and autonomic nerve fibres in the epidermis and dermis by immunofluorescence. We found by western blot the presence of mainly two different bands at 55 and 70 kDa, co-migrating with 0N4R/1N3R and 2N4R isoforms, respectively. At the RNA level, the main transcript variants were 2N and 4R, and both were more expressed in progressive supranuclear palsy/corticobasal degeneration by real-time PCR. Enzyme-linked immunosorbent assay demonstrated significantly higher levels of total τ protein in skin lysates of progressive supranuclear palsy/corticobasal degeneration compared to the other groups. Multivariate regression analysis and receiver operating characteristics curve analysis of τ amount at both sites showed a clinical association with tauopathies diagnosis and high diagnostic value for progressive supranuclear palsy/corticobasal degeneration versus Parkinson's disease (sensitivity 90%, specificity 69%) and progressive supranuclear palsy/corticobasal degeneration versus multiple system atrophy (sensitivity 90%, specificity 86%). τ protein increase correlated with cognitive impairment in progressive supranuclear palsy/corticobasal degeneration. This study is a comprehensive characterization of τ in the human cutaneous peripheral nervous system in physiological and pathological conditions. The differential expression of τ, both at transcript and protein levels, suggests that skin biopsy, an easily accessible and minimally invasive exam, can help in discriminating among different neurodegenerative diseases.

Identification of New GSK3ß Inhibitors through a Consensus Machine Learning-Based Virtual Screening.

Glycogen synthase kinase-3 beta (GSK3ß) is a serine/threonine kinase that plays key roles in glycogen metabolism, Wnt/ß-catenin signaling cascade, synaptic modulation, and multiple autophagy-related signaling pathways. GSK3ß is an attractive target for drug discovery since its aberrant activity is involved in the development of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. In the present study, multiple machine learning models aimed at identifying novel GSK3ß inhibitors were developed and evaluated for their predictive reliability. The most powerful models were combined in a consensus approach, which was used to screen about 2 million commercial compounds. Our consensus machine learning-based virtual screening led to the identification of compounds G1 and G4, which showed inhibitory activity against GSK3ß in the low-micromolar and sub-micromolar range, respectively. These results demonstrated the reliability of our virtual screening approach. Moreover, docking and molecular dynamics simulation studies were employed for predicting reliable binding modes for G1 and G4, which represent two valuable starting points for future hit-to-lead and lead optimization studies.

VenomPred: A Machine Learning Based Platform for Molecular Toxicity Predictions.

The use of in silico toxicity prediction methods plays an important role in the selection of lead compounds and in ADMET studies since in vitro and in vivo methods are often limited by ethics, time, budget and other resources. In this context, we present our new web tool VenomPred, a user-friendly platform for evaluating the potential mutagenic, hepatotoxic, carcinogenic and estrogenic effects of small molecules. VenomPred platform employs several in-house Machine Learning (ML) models developed with datasets derived from VEGA QSAR, a software that includes a comprehensive collection of different toxicity models and has been used as a reference for building and evaluating our ML models. The results showed that our models achieved equal or better performance than those obtained with the reference models included in VEGA QSAR. In order to improve the predictive performance of our platform, we adopted a consensus approach combining the results of different ML models, which was able to predict chemical toxicity better than the single models. This improved method was thus implemented in the VenomPred platform, a freely accessible webserver that takes the SMILES (Simplified Molecular-Input Line-Entry System) strings of the compounds as input and sends the prediction results providing a probability score about their potential toxicity.

Machine Learning-Based Virtual Screening for the Identification of Cdk5 Inhibitors.

Cyclin-dependent kinase 5 (Cdk5) is an atypical proline-directed serine/threonine protein kinase well-characterized for its role in the central nervous system rather than in the cell cycle. Indeed, its dysregulation has been strongly implicated in the progression of synaptic dysfunction and neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), and also in the development and progression of a variety of cancers. For this reason, Cdk5 is considered as a promising target for drug design, and the discovery of novel small-molecule Cdk5 inhibitors is of great interest in the medicinal chemistry field. In this context, we employed a machine learning-based virtual screening protocol with subsequent molecular docking, molecular dynamics simulations and binding free energy evaluations. Our virtual screening studies resulted in the identification of two novel Cdk5 inhibitors, highlighting an experimental hit rate of 50% and thus validating the reliability of the in silico workflow. Both identified ligands, compounds CPD1 and CPD4, showed a promising enzyme inhibitory activity and CPD1 also demonstrated a remarkable antiproliferative activity in ovarian and colon cancer cells. These ligands represent a valuable starting point for structure-based hit-optimization studies aimed at identifying new potent Cdk5 inhibitors.

Identification of Human Dihydroorotate Dehydrogenase Inhibitor by a Pharmacophore-Based Virtual Screening Study.

Human dihydroorotate dehydrogenase (hDHODH) is an enzyme belonging to a flavin mononucleotide (FMN)-dependent family involved in de novo pyrimidine biosynthesis, a key biological pathway for highly proliferating cancer cells and pathogens. In fact, hDHODH proved to be a promising therapeutic target for the treatment of acute myelogenous leukemia, multiple myeloma, and viral and bacterial infections; therefore, the identification of novel hDHODH ligands represents a hot topic in medicinal chemistry. In this work, we reported a virtual screening study for the identification of new promising hDHODH inhibitors. A pharmacophore-based approach combined with a consensus docking analysis and molecular dynamics simulations was applied to screen a large database of commercial compounds. The whole virtual screening protocol allowed for the identification of a novel compound that is endowed with promising inhibitory activity against hDHODH and is structurally different from known ligands. These results validated the reliability of the in silico workflow and provided a valuable starting point for hit-to-lead and future lead optimization studies aimed at the development of new potent hDHODH inhibitors.

Resveratrol Analogues as Dual Inhibitors of Monoamine Oxidase B and Carbonic Anhydrase VII: A New Multi-Target Combination for Neurodegenerative Diseases?

Neurodegenerative diseases (NDs) are described as multifactorial and progressive syndromes with compromised cognitive and behavioral functions. The multi-target-directed ligand (MTDL) strategy is a promising paradigm in drug discovery, potentially leading to new opportunities to manage such complex diseases. Here, we studied the dual ability of a set of resveratrol (RSV) analogs to inhibit two important targets involved in neurodegeneration. The stilbenols 1−9 were tested as inhibitors of the human monoamine oxidases (MAOs) and carbonic anhydrases (CAs). The studied compounds displayed moderate to excellent in vitro enzyme inhibitory activity against both enzymes at micromolar/nanomolar concentrations. Among them, the best compound 4 displayed potent and selective inhibition against the MAO-B isoform (IC50 MAO-A 0.43 µM vs. IC50 MAO-B 0.01 µM) with respect to the parent compound resveratrol (IC50 MAO-A 13.5 µM vs. IC50 MAO-B > 100 µM). It also demonstrated a selective inhibition activity against hCA VII (KI 0.7 µM vs. KI 4.3 µM for RSV). To evaluate the plausible binding mode of 1−9 within the two enzymes, molecular docking and dynamics studies were performed, revealing specific and significant interactions in the active sites of both targets. The new compounds are of pharmacological interest in view of their considerably reduced toxicity previously observed, their physicochemical and pharmacokinetic profiles, and their dual inhibitory ability. Compound 4 is noteworthy as a promising lead in the development of MAO and CA inhibitors with therapeutic potential in neuroprotection.

Deep brain stimulation in Parkinson's disease patients and routine 6-OHDA rodent models: Synergies and pitfalls.

The history of deep brain stimulation for Parkinson's disease (PD) represented a paradigmatic cross-talk between mammalian disease models and clinical evidence in humans. Fascinating were the results achieved by high frequency stimulation (HFS) into the subthalamic nucleus (STN) of MPTP-treated primates. An analogous strategy relieved tremor and hypokinetic parameters in PD patients. The 6-hydroxydopamine (6-OHDA) rodent model has mastered decades of research, contributing to understanding of the PD pathology. However, this review wonders about the actual synergy between the routine neurotoxic models and PD patients underlying STN-DBS. At first, some findings collected following 6-OHDA, promoted dogmatic visions, as the wrong contention that suppression of STN glutamate was the key therapeutic player. Instead, changes of glutamate release are negligible in humans during transition to ON-state. Besides, the imbalance of basal ganglia endogenous band frequencies, the beta (ß) band increase and the cortical-basal ganglia synchronization, undisputedly shared by models and PD patients, do not govern the whole spectrum of non-motor PD signs, difficult to investigate in rodents. Furthermore, the tonic release of dopamine, inferred during HFS in rodents, was not replicated in humans. Finally, neurotoxic rodent models describe a 'pure' dopamine depletion sparing pathways crucial in parkinsonian phenotypes, that is, noradrenergic and cholinergic ones. Although the utilization of neurotoxic models is still providing major advancements, we pore over these contradictions and try to support possible amendments of neurotoxic models (advocating modern 'in vivo' approaches and recordings extending towards motor thalamus) for pursing the development of new DBS technology.

Recent Advances in In Silico Target Fishing.

In silico target fishing, whose aim is to identify possible protein targets for a query molecule, is an emerging approach used in drug discovery due its wide variety of applications. This strategy allows the clarification of mechanism of action and biological activities of compounds whose target is still unknown. Moreover, target fishing can be employed for the identification of off targets of drug candidates, thus recognizing and preventing their possible adverse effects. For these reasons, target fishing has increasingly become a key approach for polypharmacology, drug repurposing, and the identification of new drug targets. While experimental target fishing can be lengthy and difficult to implement, due to the plethora of interactions that may occur for a single small-molecule with different protein targets, an in silico approach can be quicker, less expensive, more efficient for specific protein structures, and thus easier to employ. Moreover, the possibility to use it in combination with docking and virtual screening studies, as well as the increasing number of web-based tools that have been recently developed, make target fishing a more appealing method for drug discovery. It is especially worth underlining the increasing implementation of machine learning in this field, both as a main target fishing approach and as a further development of already applied strategies. This review reports on the main in silico target fishing strategies, belonging to both ligand-based and receptor-based approaches, developed and applied in the last years, with a particular attention to the different web tools freely accessible by the scientific community for performing target fishing studies.

Development of a cheminformatics platform for selectivity analyses of carbonic anhydrase inhibitors.

The selectivity for a specific human Carbonic Anhydrase (hCA) isoform is an important property a hCA inhibitor (CAI) should be endowed with, in order to constitute a valuable therapeutic tool for the treatment of a desired pathology. In this context, we developed a chemoinformatic platform that allows the analysis of the structure and selectivity profile of known CAIs reported in literature, with the aim of identifying structural motifs connected to ligand selectivity, thus providing useful guidelines for the design of novel ligands selective for the desired hCA isoform. The platform is able to perform ultrafast structure and selectivity analyses through ligand fingerprint similarity, with no need of structural information about the target receptor and ligands' binding mode. It is easily accessible to the non-expert user through the implementation of a KNIME Analytic Platform workflow and could be extended to analyze the selectivity profile of known ligands of different target proteins.

Acute and Chronic Dopaminergic Depletion Differently Affect Motor Thalamic Function.

The motor thalamus (MTh) plays a crucial role in the basal ganglia (BG)-cortical loop in motor information codification. Despite this, there is limited evidence of MTh functionality in normal and Parkinsonian conditions. To shed light on the functional properties of the MTh, we examined the effects of acute and chronic dopamine (DA) depletion on the neuronal firing of MTh neurons, cortical/MTh interplay and MTh extracellular concentrations of glutamate (GLU) and gamma-aminobutyric acid (GABA) in two states of DA depletion: acute depletion induced by the tetrodotoxin (TTX) and chronic denervation obtained by 6-hydroxydopamine (6-OHDA), both infused into the medial forebrain bundle (MFB) in anesthetized rats. The acute TTX DA depletion caused a clear-cut reduction in MTh neuronal activity without changes in burst content, whereas the chronic 6-OHDA depletion did not modify the firing rate but increased the burst firing. The phase correlation analysis underscored that the 6-OHDA chronic DA depletion affected the MTh-cortical activity coupling compared to the acute TTX-induced DA depletion state. The TTX acute DA depletion caused a clear-cut increase of the MTh GABA concentration and no change of GLU levels. On the other hand, the 6-OHDA-induced chronic DA depletion led to a significant reduction of local GABA and an increase of GLU levels in the MTh. These data show that MTh is affected by DA depletion and support the hypothesis that a rebalancing of MTh in the chronic condition counterbalances the profound alteration arising after acute DA depletion state.

Deep brain stimulation of the pedunculopontine nucleus modulates subthalamic pathological oscillations.

Low frequency deep brain stimulation (DBS) of the pedunculopontine nucleus area (PPNa) has been proposed as a novel surgical target for gait dysfunction in the late stage of Parkinson's disease (PD). Since the mid-2000s, we have shown that intrasurgical delivery of stimulation in the pontine tegmentum affects the firing activity in the subthalamic nucleus (STN), but its effect on STN oscillatory rhythms has not been studied. Neuronal oscillations detected by local field potential (LFPs) have great importance, since they express complex movement-related behavior such as locomotion. Therefore, we examined the effect of three PPNa-DBS stimulation protocols (at 10, 25 and 80 Hz) on the STN oscillatory activity of PD patients. We focused on the anti-kinetic beta (ß, 15-30 Hz), the pro-kinetic gamma (γ, 60-90 Hz) and "gait-related" alpha (α, 7-12 Hz) bands. We hypothesized that modulation of STN oscillations might have clinical relevance in the PPNa-mediated effects. PPNa stimulation at 25 and 80 Hz decreased the power of the STN ß band by 33.94 and 40.22%, respectively. PPNa-DBS did not affect the other two bands with a tendency to suppress α power, while γ oscillation increased. Our results suggest that the anti-kinetic ß band is the oscillation most sensitive to PPNa-DBS despite the negligible clinical efficacy on bradykinesia. However, how these changes interact reciprocally with the cortex or are counterbalanced by lower brainstem/spinal pathways remain to be elucidated. Our observation might turn out to be helpful in new protocols designed with adaptive DBS supporting the addition of PPN implantation in PD patients experiencing declining efficacy of STN-DBS.

Reciprocal interaction between monoaminergic systems and the pedunculopontine nucleus: Implication in the mechanism of L-DOPA.

The pedunculopontine nucleus (PPN) is part of the mesencephalic locomotor region (MLR) and has been involved in the control of gait, posture, locomotion, sleep, and arousal. It likely participates in some motor and non-motor symptoms of Parkinson's disease and is regularly proposed as a surgical target to ameliorate gait, posture and sleep disorders in Parkinsonian patients. The PPN overlaps with the monoaminergic systems including dopamine, serotonin and noradrenaline in the modulation of the above-mentioned functions. All these systems are involved in Parkinson's disease and the mechanism of the anti-Parkinsonian agents, mostly L-DOPA. This suggests that PPN interacts with monoaminergic neurons and vice versa. Some evidence indicates that the PPN sends cholinergic, glutamatergic and even gabaergic inputs to mesencephalic dopaminergic cells, with the data regarding serotonergic or noradrenergic cells being less well known. Similarly, the control exerted by the PPN on dopaminergic neurons, is multiple and complex, and more extensively explored than the other monoaminergic systems. The data on the influence of monoaminergic systems on PPN neuron activity are rather scarce. While there is evidence that the PPN influences the therapeutic response of L-DOPA, it is still difficult to discerne the reciprocal action of the PPN and monoaminergic systems in this action. Additional data are required to better understand the functional organization of monoaminergic inputs to the MLR including the PPN to get a clearer picture of their interaction.

Pedunculopontine nucleus: An integrative view with implications on Deep Brain Stimulation.

The pedunculopontine nucleus (PPN) is a reticular nucleus located in the mesencephalic and upper pontine tegmentum. Initially, characterized by its predominant cholinergic projection neurons, it was associated with the "mesencephalic locomotor region" and "reticular activating system". Furthermore, based on histopathological studies, the PPN was hypothesized to play a role in the manifestation of symptoms in movement disorders such as Parkinson's disease (PD). Since axial symptoms represent unmet needs of PD treatments, a series of pioneering experiments in Parkinsonian monkeys promoted the idea of a potential new target for deep brain stimulation (DBS) and much clinical interest was generated in the following years leading to a number of trials analysing the role of PPN for gait disorders. This review summarizes the historical background and more recent findings about the anatomy and function of the PPN and its implications in the basal ganglia network of the normal as well as diseased brain. Classical views on PPN function shall be challenged by more recent findings. Additionally, the current role and future perspectives of PPN DBS in PD patients shall be outlined.

Mechanisms of action underlying the efficacy of deep brain stimulation of the subthalamic nucleus in Parkinson's disease: central role of disease severity.

Despite consensus on some neurophysiological hallmarks of the Parkinsonian state (such as beta) band increase) a single mechanism is unlikely to explain the efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN). Most experimental evidence to date correlates with an extreme degree of nigral neurodegeneration and not with different stages of PD progression. It seems inappropriate to combine substantially different patients - newly diagnosed, early fluctuators or advanced dyskinetic individuals - within the same group. An efficacious STN-DBS imposes a new activity pattern within brain circuits, favouring alpha- and gamma-like neuronal discharge, and restores the thalamo-cortical transmission pathway through axonal activation. In addition, stimulation via the dorsal contacts of the macro-electrode may affect cortical activation antidromically. However, basal ganglia (BG) modulation remains cardinal for 'OFF'-'ON' transition (as revealed by cGMP increase occurring during STN-DBS in the substantia nigra pars reticulata and internal globus pallidus). New research promises to clarify to what extent STN-DBS restores striato-centric bidirectional plasticity, and whether non-neuronal cellular actions (microglia, neurovascular) play a part. Future studies will assess whether extremely anticipated DBS or lesioning in selected patients are capable of providing neuroprotection to the synuclein-mediated alterations of synaptic efficiency. This review addresses these open issues through the specific mechanisms prevailing in a given disease stage. In patients undergoing early protocol, alteration in endogenous transmitters and recovery of plasticity are concurrent players. In advanced stages, re-modulation of endogenous band frequencies, disruption of pathological pattern and/or antidromic cortical activation are, likely, the prominent modes.

Levodopa-induced dyskinesia in Parkinson disease: Sleep matters.

OBJECTIVE: The spectrum of clinical symptom changes during the course of Parkinson disease (PD). Levodopa therapy, while offering remarkable control of classical motor symptoms, causes abnormal involuntary movements as the disease progresses. This levodopa-induced dyskinesia (LID) has been associated with abnormal cortical plasticity. Because slow wave activity (SWA) of nonrapid eye movement (NREM) sleep underlies adjustment of cortical excitability, we sought to elucidate the relationship between this physiological process and LID. METHODS: Thirty-six patients at different stages of PD underwent whole-night video polysomnography-high-density electroencephalography (vPSG-hdEEG), preceded by 1 week of actigraphy. To represent the broad spectrum of the disease, patients were divided into 3 groups by disease stage-(1) de novo (n = 9), (2) advanced (n = 13), and (3) dyskinetic (DYS; n = 14)-were compared to an age-matched control group (n = 12). The SWA-NREM content of the vPSG-hdEEG was then temporally divided into 10 equal parts, from T1 to T10, and power and source analyses were performed. T2-T3-T4 were considered early sleep and were compared to T7-T8-T9, representing late sleep. RESULTS: We found that all groups, except the DYS group, manifested a clear-cut SWA decrease between early and late sleep. INTERPRETATION: Our data demonstrate a strong pathophysiological association between sleep and PD. Given that SWA may be a surrogate for synaptic strength, our data suggest that DYS patients do not have adequate synaptic downscaling. Further analysis is needed to determine the effect of drugs that can enhance cortical SWA in LID. Ann Neurol 2018;84:905-917.

Deep brain stimulation of the subthalamic nucleus: All that glitters isn't gold?

With the silver anniversary of deep brain stimulation (DBS) behind us, this would seem to be a good juncture to consider its successes and unanswered questions. Bilateral subthalamic nucleus (STN) stimulation has changed the clinical perspective of several thousand Parkinson's disease (PD) patients worldwide. A recent reappraisal animates the field with strong arguments in favor of an anticipation of the stereotactic approach in patients with as little as 5 to 6 years of disease history if they manifest motor complications. From what was once a no-choice option, STN-DBS is now becoming more and more attractive to neurologists dealing with movement disorders. Despite the development of new pharmacological treatment and renewed rehabilitation programs able to modify the severity of drug-related complications, a resurgence of stimulation therapy reminiscent of an old era of medicine with an attendant blinkered mindset has emerged. Yet, the DBS-mediated effects are modest on critical aspects such as gait impairment and extremely variable depending on the clinical phenotype and individual clinical profile. Hence, the indication for DBS should become more, and not less, individually tailored. Those physicians considering deep brain stimulation (DBS) as a therapeutic option need to evaluate results beyond short-term quality of life, giving the correct weight to the direct and indirect costs over the longer term as well as to life prognosis. Unequivocal recourse to early-stimulation surgery necessitates investigations not limited to a mere comparative assessment versus drug-mediated benefits, but instead showing evidence of a clear degree of disease-modifying effect or a rescue of basal ganglia plasticity.