Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery

Artificial neural network models driven novel virtual screening workflow for the identification and biological evaluation of BACE1 inhibitors

Beta-site amyloid-β precursor protein-cleaving enzyme 1 (BACE1) is a transmembrane aspartic protease and has shown potential as a possible therapeutic target for Alzheimer's disease. This aggravating disease involves the aberrant production of β amyloid plaques by BACE1 which catalyzes the rate-limiting step by cleaving the amyloid precursor protein (APP), generating the neurotoxic amyloid β protein that aggregates to form plaques leading to neurodegeneration. Therefore, it is indispensable to inhibit BACE1, thus modulating the APP processing. In this study, we present a workflow that utilizes a multi-stage virtual screening protocol for identifying potential BACE1 inhibitors by employing multiple artificial neural network-based models. Collectively, all the hyperparameter tuned models were assigned a task to virtually screen Maybridge library, thus yielding a consensus of 41 hits. The majority of these hits exhibited optimal pharmacokinetic properties confirmed by high central nervous system multiparameter optimization (CNS-MPO) scores. Further shortlisting of 8 compounds by molecular docking into the active site of BACE1 and their subsequent in-vitro evaluation identified 4 compounds as potent BACE1 inhibitors with IC50 values falling in the range 0.028-0.052 μM and can be further optimized with medicinal chemistry efforts to improve their activity.

A Medicinal Chemistry Perspective on Excitatory Amino Acid Transporter 2 Dysfunction in Neurodegenerative Diseases

The excitatory amino acid transporter 2 (EAAT2) plays a key role in the clearance and recycling of glutamate - the major excitatory neurotransmitter in the mammalian brain. EAAT2 loss/dysfunction triggers a cascade of neurodegenerative events, comprising glutamatergic excitotoxicity and neuronal death. Nevertheless, our current knowledge regarding EAAT2 in neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS) and Alzheimer's disease (AD), is restricted to post-mortem analysis of brain tissue and experimental models. Thus, detecting EAAT2 in the living human brain might be crucial to improve diagnosis/therapy for ALS and AD. This perspective article describes the role of EAAT2 in physio/pathological processes and provides a structure-activity relationship of EAAT2-binders, bringing two perspectives: therapy (activators) and diagnosis (molecular imaging tools).

Discovery of a Series of Substituted 1H-((1,2,3-Triazol-4-yl)methoxy)pyrimidines as Brain Penetrants and Potent GluN2B-Selective Negative Allosteric Modulators

Herein, we describe a series of substituted 1H-((1,2,3-triazol-4-yl)methoxy)pyrimidines as potent GluN2B negative allosteric modulators. Exploration of several five- and six-membered heterocycles led to the identification of O-linked pyrimidine analogues that possessed a balance of potency and desirable ADME profiles. Due to initial observations of metabolic saturation, early metabolite identification studies were conducted on compound 18, and the results drove further iterative optimization efforts to avoid the formation of undesired saturating metabolites. The comprehensive investigation of substitution on the pyrimidine moiety of the 1H-1,2,3-triazol-4-yl)methoxy)pyrimidines allowed for the identification of compound 31, which demonstrated high GluN2B receptor affinity, improved solubility, and a clean cardiovascular profile. Compound 31 was profiled in an ex vivo target engagement study in rats at a 10 mg/kg oral dose and achieved an ED₅₀ of 1.7 mg/kg.

'Chemistry at the speed of sound': automated 1536-well nanoscale synthesis of 16 scaffolds in parallel

Screening of large and diverse libraries is the 'bread and butter' in the first phase of the discovery of novel drugs. However, maintenance and periodic renewal of high-quality large compound collections pose considerable logistic, environmental and monetary problems. Here, we exercise an alternative, the 'on-the-fly' synthesis of large and diverse libraries on a nanoscale in a highly automated fashion. For the first time, we show the feasibility of the synthesis of a large library based on 16 different chemistries in parallel on several 384-well plates using the acoustic dispensing ejection (ADE) technology platform. In contrast to combinatorial chemistry, we produced 16 scaffolds at the same time and in a sparse matrix fashion, and each compound was produced by a random combination of diverse large building blocks. The synthesis, analytics, resynthesis of selected compounds, and chemoinformatic analysis of the library are described. The advantages of the herein described automated nanoscale synthesis approach include great library diversity, absence of library storage logistics, superior economics, speed of synthesis by automation, increased safety, and hence sustainable chemistry.

Pyrazole Ureas as Low Dose, CNS Penetrant Glucosylceramide Synthase Inhibitors for the Treatment of Parkinson's Disease

Parkinson's disease is the second most prevalent progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra. Loss-of-function mutations in GBA, the gene that encodes for the lysosomal enzyme glucosylcerebrosidase, are a major genetic risk factor for the development of Parkinson's disease potentially through the accumulation of glucosylceramide and glucosylsphingosine in the CNS. A therapeutic strategy to reduce glycosphingolipid accumulation in the CNS would entail inhibition of the enzyme responsible for their synthesis, glucosylceramide synthase (GCS). Herein, we report the optimization of a bicyclic pyrazole amide GCS inhibitor discovered through HTS to low dose, oral, CNS penetrant, bicyclic pyrazole urea GCSi's with in vivo activity in mouse models and ex vivo activity in iPSC neuronal models of synucleinopathy and lysosomal dysfunction. This was accomplished through the judicious use of parallel medicinal chemistry, direct-to-biology screening, physics-based rationalization of transporter profiles, pharmacophore modeling, and use a novel metric: volume ligand efficiency.

Dopamine D3/D2 Receptor Ligands Based on Cariprazine for the Treatment of Psychostimulant Use Disorders That May Be Dual Diagnosed with Affective Disorders

Highly selective dopamine D3 receptor (D3R) partial agonists/antagonists have been developed for the treatment of psychostimulant use disorders (PSUD). However, none have reached the clinic due to insufficient potency/efficacy or potential cardiotoxicity. Cariprazine, an FDA-approved drug for the treatment of schizophrenia and bipolar disorder, is a high-affinity D3R partial agonist (Ki = 0.22 nM) with 3.6-fold selectivity over the homologous dopamine D2 receptor (D2R). We hypothesized that compounds that are moderately D3R/D2R-selective partial agonists/antagonists may be effective for the treatment of PSUD. By systematically modifying the parent molecule, we discovered partial agonists/antagonists, as measured in bioluminescence resonance energy transfer (BRET)-based assays, with high D3R affinities (Ki = 0.14-50 nM) and moderate selectivity (<100-fold) over D2R. Cariprazine and two lead analogues, 13a and 13e, decreased cocaine self-administration (FR2; 1-10 mg/kg, i.p.) in rats, suggesting that partial agonists/antagonists with modest D3R/D2R selectivity may be effective in treating PSUD and potentially comorbidities with other affective disorders.

Structural Alterations of the "Address" Moiety of NAN Leading to the Discovery of a Novel Opioid Receptor Modulator with Reduced hERG Toxicity

The search for selective opioid ligands with desired pharmacological potency and improved safety profile has always been an area of interest. Our previous effort yielded a potent opioid modulator, NAN, a 6α-N-7'-indolyl-substituted naltrexamine derivative, which exhibited promising pharmacological activities both in vitro and in vivo. However, significant human ether-a-go-go-related gene (hERG) liability limited its further development. Therefore, a systematic structural modification on NAN was conducted in order to alleviate hERG toxicity while preserving pharmacological properties, which led to the discovery of 2'-methylindolyl derivative compound 21. Compared to NAN, compound 21 manifested overall improved pharmacological profiles. Follow-up hERG channel inhibition evaluation revealed a seven-fold decreased potency of compound 21 compared to NAN. Furthermore, several fundamental drug-like property evaluations suggested a reasonable ADME profile of 21. Collectively, compound 21 appeared to be a promising opioid modulator for further development as a novel therapeutic agent toward opioid use disorder treatments.

Comprehensive Characterization of a Systematic Library of Alkyl and Alicyclic Synthetic Cannabinoids Related to CUMYL-PICA, CUMYL-BUTICA, CUMYL-CBMICA, and CUMYL-PINACA

Over 200 synthetic cannabinoid receptor agonists (SCRAs) have been identified as new psychoactive substances. Effective monitoring and characterization of SCRAs are hindered by the rapid pace of structural evolution. Ahead of possible appearance on the illicit drug market, new SCRAs were synthesized to complete a systematic library of cumyl-indole- (e.g., CUMYL-CPrMICA, CUMYL-CPMICA) and cumyl-indazole-carboxamides (e.g., CUMYL-CPrMINACA, CUMYL-CPMINACA), encompassing butyl, pentyl, cyclopropylmethyl, cyclobutylmethyl, cyclopentylmethyl, and cyclohexylmethyl tails. Comprehensive pharmacological characterization was performed with three assay formats, monitoring the recruitment of either wild-type or C-terminally truncated (βarr2d366) β-arrestin2 to the activated cannabinoid 1 receptor (CB₁) or monitoring G_βγ-mediated membrane hyperpolarization. Altered compound characterization was observed when comparing derived potency (EC₅₀) and efficacy (E_max) values from both assays monitoring the same or a different signaling event, whereas ranges and ranking orders were similar. Structure-activity relationships (SAR) were assessed in threefold, resulting in the identification of the pendant tail as a critical pharmacophore, with the optimal chain length for CB₁ activation approximating an n-pentyl (e.g., cyclopentylmethyl or cyclohexylmethyl tail). The activity of the SCRAs encompassing cyclic tails decreased with decreasing number of carbons forming the cyclic moiety, with CUMYL-CPrMICA showing the least CB₁ activity in all assay formats. The SARs were rationalized via molecular docking, demonstrating the importance of the optimal steric contribution of the hydrophobic tail. While SAR conclusions remained largely unchanged, the differential compound characterization by both similar and different assay designs emphasizes the importance of detailing specific assay characteristics to allow adequate interpretation of potencies and efficacies.

High-content phenotypic screen to identify small molecule enhancers of Parkin-dependent ubiquitination and mitophagy

Mitochondrial dysfunction and aberrant mitochondrial homeostasis are key aspects of Parkinson's disease (PD) pathophysiology. Mutations in PINK1 and Parkin proteins lead to autosomal recessive PD, suggesting that defective mitochondrial clearance via mitophagy is key in PD etiology. Accelerating the identification and/or removal of dysfunctional mitochondria could therefore provide a disease-modifying approach to treatment. To that end, we performed a high-content phenotypic screen (HCS) of ∼125,000 small molecules to identify compounds that positively modulate mitochondrial accumulation of the PINK1-Parkin-dependent mitophagy initiation marker p-Ser65-Ub in Parkin haploinsufficiency (Parkin ^+/R275W) human fibroblasts. Following confirmatory counter-screening and orthogonal assays, we selected compounds of interest that enhance mitophagy-related biochemical and functional endpoints in patient-derived fibroblasts. Identification of inhibitors of the ubiquitin-specific peptidase and negative regulator of mitophagy USP30 within our hits further validated our approach. The compounds identified in this work provide a novel starting point for further investigation and optimization.

Naphthoquinones biflorin and bis-biflorin (Capraria biflora) as possible inhibitors of the fungus Candida auris polymerase: molecular docking, molecular dynamics, MM/GBSA calculations and in silico drug-likeness study

A new worldwide concern has emerged with the recent emergence of infections caused by Candida auris. This reflects its comparative ease of transmission, substantial mortality, and the increasing level of resistance seen in the three major classes of antifungal drugs. Efforts to create a better design for structure-based drugs that described numerous modifications and the search for secondary metabolic structures derived from plant species are likely to reduce the virulence of several fungal pathogens. In this context, the present work aimed to evaluate in silico two naphthoquinones isolated from the roots of Capraria biflora, biflorin, and its dimmer, bis-biflorin, as potential inhibitors of Candida auris polymerase. Based on the simulation performed with the two naphthoquinones, biflorin and bis-biflorin, it can be stated that bis-biflorin showed the best interactions with Candida auris polymerase. Still, biflorin also demonstrated favorable coupling energy. Predictive pharmacokinetic assays suggest that biflorin has high oral bioavailability and more excellent metabolic stability compared to the bis-biflorin analogue. constituting a promising pharmacological tool.Communicated by Ramaswamy H. Sarma.

Recent advances in dopamine D2 receptor ligands in the treatment of neuropsychiatric disorders

Dopamine is a biologically active amine synthesized in the central and peripheral nervous system. This biogenic monoamine acts by activating five types of dopamine receptors (D_1-5 Rs), which belong to the G protein-coupled receptor family. Antagonists and partial agonists of D₂ Rs are used to treat schizophrenia, Parkinson's disease, depression, and anxiety. The typical pharmacophore with high D₂ R affinity comprises four main areas, namely aromatic moiety, cyclic amine, central linker and aromatic/heteroaromatic lipophilic fragment. From the literature reviewed herein, we can conclude that 4-(2,3-dichlorophenyl), 4-(2-methoxyphenyl)-, 4-(benzo[b]thiophen-4-yl)-1-substituted piperazine, and 4-(6-fluorobenzo[d]isoxazol-3-yl)piperidine moieties are critical for high D₂ R affinity. Four to six atoms chains are optimal for D₂ R affinity with 4-butoxyl as the most pronounced one. The bicyclic aromatic/heteroaromatic systems are most frequently occurring as lipophilic appendages to retain high D₂ R affinity. In this review, we provide a thorough overview of the therapeutic potential of D₂ R modulators in the treatment of the aforementioned disorders. In addition, this review summarizes current knowledge about these diseases, with a focus on the dopaminergic pathway underlying these pathologies. Major attention is paid to the structure, function, and pharmacology of novel D₂ R ligands, which have been developed in the last decade (2010-2021), and belong to the 1,4-disubstituted aromatic cyclic amine group. Due to the abundance of data, allosteric D₂ R ligands and D₂ R modulators from patents are not discussed in this review.

Discovery of 4-aminoindole carboxamide derivatives to curtail alpha-synuclein and tau isoform 2N4R oligomer formation

Alzheimer's disease (AD) is a multifactorial, chronic neurodegenerative disease characterized by the presence of extracellular β-amyloid (Aβ) plaques, intraneuronal neurofibrillary tangles (NFTs), activated microglial cells, and an inflammatory state (involving reactive oxygen species production) in the brain. NFTs are comprised of misfolded and hyperphosphorylated forms of the microtubule-binding protein tau. Interestingly, the trimeric form of the 2N4R splice isoform of tau has been found to be more toxic than the trimeric 1N4R isoform in neuron precursor cells. Few drug discovery programs have focused on specific tau isoforms. The present drug discovery project is centered on the anti-aggregation effect of a series of seventeen 4- or 5-aminoindole carboxamides on the 2N4R isoform of tau. The selection of the best compounds was performed using α-synuclein (α-syn). The anti-oligomer and -fibril activities of newly synthesized aminoindole carboxamide derivatives were evaluated with biophysical methods, such as thioflavin T fluorescence assays, photo-induced cross-linking of unmodified proteins, and transmission electron microscopy. To evaluate the reduction of inclusions and cytoprotective effects, M17D neuroblastoma cells expressing inclusion-forming α-syn were treated with the best amide representatives. The 4-aminoindole carboxamide derivatives exhibited a better anti-fibrillar activity compared to their 5-aminoindole counterparts. The amide derivatives 2, 8, and 17 exerted anti-oligomer and anti-fibril activities on α-syn and the 2N4R isoform of tau. At a concentration of 40 μM, compound 8 reduced inclusion formation in M17D neuroblastoma cells expressing inclusion-prone αSynuclein3K::YFP. Our results demonstrate the potential of 4-aminoindole carboxamide derivatives with regard to inhibiting the oligomer formation of α-syn and tau (2N4R isoform) for further optimization prior to pre-clinical studies.

Human-in-the-loop assisted de novo molecular design

A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still needs to design the goal, expressed as a scoring function for the molecules that captures the designer's implicit knowledge about the optimization task. Little support for this task exists and, consequently, a chemist usually resorts to iteratively building the objective function of multi-parameter optimization (MPO) in de novo design. We propose a principled approach to use human-in-the-loop machine learning to help the chemist to adapt the MPO scoring function to better match their goal. An advantage is that the method can learn the scoring function directly from the user's feedback while they browse the output of the molecule generator, instead of the current manual tuning of the scoring function with trial and error. The proposed method uses a probabilistic model that captures the user's idea and uncertainty about the scoring function, and it uses active learning to interact with the user. We present two case studies for this: In the first use-case, the parameters of an MPO are learned, and in the second use-case a non-parametric component of the scoring function to capture human domain knowledge is developed. The results show the effectiveness of the methods in two simulated example cases with an oracle, achieving significant improvement in less than 200 feedback queries, for the goals of a high QED score and identifying potent molecules for the DRD2 receptor, respectively. We further demonstrate the performance gains with a medicinal chemist interacting with the system.

Identification and Prioritization of PET Neuroimaging Targets for Microglial Phenotypes Associated with Microglial Activity in Alzheimer's Disease

Activation of microglial cells accompanies the progression of many neurodegenerative disorders, including Alzheimer's disease (AD). Development of molecular imaging tools specific to microglia can help elucidate the mechanism through which microglia contribute to the pathogenesis and progression of neurodegenerative disorders. Through analysis of published genetic, transcriptomic, and proteomic data sets, we identified 19 genes with microglia-specific expression that we then ranked based on association with the AD characteristics, change in expression, and potential druggability of the target. We believe that the process we used to identify and rank microglia-specific genes is broadly applicable to the identification and evaluation of targets in other disease areas and for applications beyond molecular imaging.

Discovery of small molecule mechanistic target of rapamycin inhibitors as anti-aging and anti-cancer therapeutics

To date, the most studied drug in anti-aging research is the mTOR inhibitor - rapamycin. Despite its almost perfect anti-aging profile, rapamycin exerts one significant limitation - inappropriate physicochemical properties. Therefore, we have decided to utilize virtual high-throughput screening and fragment-based design in search of novel mTOR inhibiting scaffolds with suitable physicochemical parameters. Seven lead compounds were selected from the list of obtained hits that were commercially available (4, 5, and 7) or their synthesis was feasible (1, 2, 3, and 6) and evaluated in vitro and subsequently in vivo. Of all these substances, only compound 3 demonstrated a significant cytotoxic, senolytic, and senomorphic effect on normal and cancerous cells. Further, it has been confirmed that compound 3 is a direct mTORC1 inhibitor. Last but not least, compound 3 was found to exhibit anti-SASP activity concurrently being relatively safe within the test of in vivo tolerability. All these outstanding results highlight compound 3 as a scaffold worthy of further investigation.

B-cell Lymphoma 6 (BCL6): From Master Regulator of Humoral Immunity to Oncogenic Driver in Pediatric Cancers

B-cell lymphoma 6 (BCL6) is a protooncogene in adult and pediatric cancers, first identified in diffuse large B-cell lymphoma (DLBCL) where it acts as a repressor of the tumor suppressor TP53, conferring survival, protection, and maintenance of lymphoma cells. BCL6 expression in normal B cells is fundamental in the regulation of humoral immunity, via initiation and maintenance of the germinal centers (GC). Its role in B cells during the production of high affinity immunoglobins (that recognize and bind specific antigens) is believed to underpin its function as an oncogene. BCL6 is known to drive the self-renewal capacity of leukemia-initiating cells (LIC), with high BCL6 expression in acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and glioblastoma (GBM) associated with disease progression and treatment resistance. The mechanisms underpinning BCL6-driven therapy resistance are yet to be uncovered; however, high activity is considered to confer poor prognosis in the clinical setting. BCL6's key binding partner, BCL6 corepressor (BCOR), is frequently mutated in pediatric cancers and appears to act in concert with BCL6. Using publicly available data, here we show that BCL6 is ubiquitously overexpressed in pediatric brain tumors, inversely to BCOR, highlighting the potential for targeting BCL6 in these often lethal and untreatable cancers. In this review, we summarize what is known of BCL6 (role, effect, mechanisms) in pediatric cancers, highlighting the two sides of BCL6 function, humoral immunity, and tumorigenesis, as well as to review BCL6 inhibitors and highlight areas of opportunity to improve the outcomes of patients with pediatric cancer.

Non-invasive Imaging of Antisense Oligonucleotides in the Brain via In Vivo Click Chemistry

PURPOSE

The treatment of complex neurological diseases often requires the administration of large therapeutic drugs, such as antisense oligonucleotide (ASO), by lumbar puncture into the intrathecal space in order to bypass the blood-brain barrier. Despite the growing number of ASOs in clinical development, there are still uncertainties regarding their dosing, primarily around their distribution and kinetics in the brain following intrathecal injection. The challenge of taking measurements within the delicate structures of the central nervous system (CNS) necessitates the use of non-invasive nuclear imaging, such as positron emission tomography (PET). Herein, an emergent strategy known as "pretargeted imaging" is applied to image the distribution of an ASO in the brain by developing a novel PET tracer, [¹⁸F]F-537-Tz. This tracer is able to undergo an in vivo "click" reaction, covalently binding to a trans-cyclooctene conjugated ASO.

PROCEDURES

A novel small molecule tracer for pretargeted PET imaging of ASOs in the CNS is developed and tested in a series of in vitro and in vivo experiments, including biodistribution in rats and non-human primates.

RESULTS

In vitro data and extensive in vivo rat data demonstrated delivery of the tracer to the CNS, and its successful ligation to its ASO target in the brain. In an NHP study, the slow tracer kinetics did not allow for specific binding to be determined by PET.

CONCLUSION

A CNS-penetrant radioligand for pretargeted imaging was successfully demonstrated in a proof-of-concept study in rats, laying the groundwork for further optimization.

Structural Requirements for the Neuroprotective and Anti-Inflammatory Activities of the Flavanone Sterubin

Alzheimer's disease (AD) is the most frequent age-associated disease with no treatments that can prevent, delay, slow, or stop its progression. Thus, new approaches to drug development are needed. One promising approach is the use of phenotypic screening assays that can identify compounds that have therapeutic efficacy in target pathways relevant to aging and cognition, as well as AD pathology. Using this approach, we identified the flavanone sterubin, from Yerba santa (Eriodictyon californicum), as a potential drug candidate for the treatment of AD. Sterubin is highly protective against multiple initiators of cell death that activate distinct death pathways, potently induces the antioxidant transcription factor Nrf2, and has strong anti-inflammatory activity. Moreover, in a short-term model of AD, it was able to prevent decreases in short- and long-term memory. In order to better understand which key chemical functional groups are essential to the beneficial effects of sterubin, we compared the activity of sterubin to that of seven closely related flavonoids in our phenotypic screening assays. Surprisingly, only sterubin showed both potent neuroprotective activity against multiple insults as well as strong anti-inflammatory activity against several distinct inducers of inflammation. These effects correlated directly with the ability of sterubin to strongly induce Nrf2 in both nerve and microglial cells. Together, these results define the structural requirements underlying the neuroprotective and anti-inflammatory effects of sterubin and they provide the basis for future studies on new compounds based on sterubin.

Synthesis and Evaluation of 18F-Labeled Chalcone Analogue for Detection of α-Synuclein Aggregates in the Brain Using the Mouse Model

In the brains of patients with synucleinopathies such as Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy, α-synuclein (α-syn) aggregates deposit abnormally to induce neurodegeneration, although the mechanism is unclear. Thus, in vivo imaging studies targeting α-syn aggregates have attracted much attention to guide medical intervention against synucleinopathy. In our previous study, a chalcone analogue, [¹²⁵I]PHNP-3, functioned as a feasible probe in terms of α-syn binding in vitro; however, it did not migrate to the mouse brain, and further improvement of brain uptake was required. In the present study, we designed and synthesized two novel ¹⁸F-labeled chalcone analogues, [¹⁸F]FHCL-1 and [¹⁸F]FHCL-2, using a central nervous system multiparameter optimization (CNS MPO) algorithm with the aim of improving blood-brain barrier permeation in the mouse brain. Then, we evaluated their utility for in vivo imaging of α-syn aggregates using a mouse model. In the competitive inhibition assay, both chalcone analogues exhibited high binding affinity for α-syn aggregates (K_i = 2.6 and 3.4 nM, respectively), while no marked amyloid β (Aβ)-binding was observed. The ¹⁸F-labeling reaction was successfully performed. In a biodistribution experiment, brain uptake of both chalcone analogues in normal mice (2.09 and 2.40% injected dose/gram (% ID/g) at 2 min postinjection, respectively) was higher than that of [¹²⁵I]PHNP-3, suggesting that the introduction of ¹⁸F into the chalcone analogue led to an improvement in brain uptake in mice while maintaining favorable binding ability for α-syn aggregates. Furthermore, in an ex vivo autoradiography experiment, [¹⁸F]FHCL-2 showed the feasibility of the detection of α-syn aggregates in the mouse brain in vivo. These preclinical studies demonstrated the validity of the design of α-syn-targeting probes based on the CNS MPO score and the possibility of in vivo imaging of α-syn aggregates in a mouse model using ¹⁸F-labeled chalcone analogues.

Synergistic Modulation by Halogens and Pyridine Crossing the Blood-Brain Barrier for In Situ Visualization of Thiol Flux in the Epileptic Brain

Epilepsy is a nervous system disease, and seizures are closely related to oxidative stress. Thiols, as the main antioxidant in an organism, play a key role in regulating the redox balance and defending from oxidative stress. As a result of the complexity of the brain structure, there is still a lack of suitable in situ detection methods of thiols to reveal the relationship between epilepsy and thiol level fluctuations. Therefore, by combining picolinate as the new recognition site for thiols, parallel synthesis, and the fluorescence rapid screening method, DCI-Br-3 was developed as a rapid, highly sensitive, and selective probe to monitor thiols in vitro and in vivo. It is worth noting that DCI-Br-3 effectively crossed the blood-brain barrier (BBB) to reveal the negative relationship between the level of thiols and the occurrence of epilepsy and may further provide important information for the prevention and treatment of thiol-related neurological diseases.

Design, Synthesis and Biological Evaluation of Biscarbamates as Potential Selective Butyrylcholinesterase Inhibitors for the Treatment of Alzheimer's Disease

As butyrylcholinesterase (BChE) plays a role in the progression of symptoms and pathophysiology of Alzheimer's disease (AD), selective inhibition of BChE over acetylcholinesterase (AChE) can represent a promising pathway in treating AD. The carbamate group was chosen as a pharmacophore because the carbamates currently or previously in use for the treatment of AD displayed significant positive effects on cognitive symptoms. Eighteen biscarbamates with different substituents at the carbamoyl and hydroxyaminoethyl chain were synthesized, and their inhibitory potential toward both cholinesterases and inhibition selectivity were determined. The ability of carbamates to cross the blood-brain barrier (BBB) by passive transport, their cytotoxic profile and their ability to chelate biometals were also evaluated. All biscarbamates displayed a time-dependent inhibition with inhibition rate constants within 10^-3-10^-6 M^-1 min^-1 range for both cholinesterases, with generally higher preference to BChE. For two biscarbamates, it was determined that they should be able to pass the BBB by passive transport, while for five biscarbamates, this ability was slightly limited. Fourteen biscarbamates did not exhibit a cytotoxic effect toward liver, kidney and neuronal cells. In conclusion, considering their high BChE selectivity, non-toxicity, ability to chelate biometals and pass the BBB, compounds 2 and 16 were pointed out as the most promising compounds for the treatment of middle and late stages of AD.

Discovery of Novel Quinoline-Based Proteasome Inhibitors for Human African Trypanosomiasis (HAT)

Human African Trypanosomiasis (HAT) is a vector-borne disease caused by kinetoplastid parasites of the Trypanosoma genus. The disease proceeds in two stages, with a hemolymphatic blood stage and a meningo-encephalic brain stage. In the latter stage, the parasite causes irreversible damage to the brain leading to sleep cycle disruption and is fatal if untreated. An orally bioavailable treatment is highly desirable. In this study, we present a brain-penetrant, parasite-selective 20S proteasome inhibitor that was rapidly optimized from an HTS singleton hit to drug candidate compound 7 that showed cure in a stage II mouse efficacy model. Here, we describe hit expansion and lead optimization campaign guided by cryo-electron microscopy and an in silico model to predict the brain-to-plasma partition coefficient K_p as an important parameter to prioritize compounds for synthesis. The model combined with in vitro and in vivo experiments allowed us to advance compounds with favorable unbound brain-to-plasma ratios (K_p,uu) to cure a CNS disease such as HAT.

Strategies for targeting the P2Y12 receptor in the central nervous system

The purinergic 2Y type 12 receptor (P2Y₁₂R) is a well-known biological target for anti-thrombotic drugs due to its role in platelet aggregation and blood clotting. While the importance of the P2Y₁₂R in the periphery has been known for decades, much less is known about its expression and roles in the central nervous system (CNS), where it is expressed exclusively on microglia - the first responders to brain insults and neurodegeneration. Several seminal studies have shown that P2Y₁₂ is a robust, translatable biomarker for anti-inflammatory and neuroprotective microglial phenotypes in models of degenerative diseases such as multiple sclerosis and Alzheimer's disease. An enduring problem for studying this receptor in vivo, however, is the lack of selective, high-affinity small molecule ligands that can bypass the blood-brain barrier and accumulate in the CNS. In this Digest, we discuss previous attempts by researchers to target the P2Y₁₂R in the CNS and opine on strategies that may be employed to design and assess the suitability of novel P2Y₁₂ ligands for this purpose going forward.

HIF1 inhibition of the biflavonoids against pancreas cancer: drug-likeness, bioavailability, ADMET, PASS, molecular docking, molecular dynamics, and MM/GBSA calculations

Pancreatic cancer is an aggressive disease with a high death rate and is difficult to treat. This disease, in the most cases, is asymptomatic until it progresses to an advanced stage. Therefore, the search for bioactive molecules is urgent to combat pancreatic cancer. Then, this work analyzed the interaction potential of agathisflavone and amentoflavone molecules against the HIF1 target using the ADMET, molecular docking, and molecular dynamics simulations. More recent drug-likeness filters that combine physicochemical and physiological parameters have shown that high polar surface area (TPSA > 75 Ų) drives biflavonoids out of the toxic drug space of Pfizer dataset. Regarding the pharmacokinetic descriptors, it was possible to notice that Amentoflavone showed a better order of passive cell permeability (P_app = 8 × 10^-6cm/s) and better metabolic stability, biotransformed by aromatic hydroxylation reactions by the CYP3A4 isoenzyme on the human liver, that favor its hepatic clearance. The molecular docking and molecular dynamics simulations indicated the high interaction potential and stability between the ligands analyzed (highlighted the amentoflavone molecule), respectively. The MM/GBSA calculations showed that the amentoflavone ligand registered the highest ΔG binding value of -32.6957 kcal/mol with the HIF1 target. Then, this molecule may be used as a potential inhibitor of pancreatic cancer. In this perspective, the present work represents an initial step in the virtual bioprospecting a pharmacological tool for treating of pancreatic cancer.Communicated by Ramaswamy H. Sarma.

Drug Repurposing, a Fast-Track Approach to Develop Effective Treatments for Glioblastoma

Glioblastoma (GBM) remains one of the most difficult tumors to treat. The mean overall survival rate of 15 months and the 5-year survival rate of 5% have not significantly changed for almost 2 decades. Despite progress in understanding the pathophysiology of the disease, no new effective treatments to combine with radiation therapy after surgical tumor debulking have become available since the introduction of temozolomide in 1999. One of the main reasons for this is the scarcity of compounds that cross the blood-brain barrier (BBB) and reach the brain tumor tissue in therapeutically effective concentrations. In this review, we focus on the role of the BBB and its importance in developing brain tumor treatments. Moreover, we discuss drug repurposing, a drug discovery approach to identify potential effective candidates with optimal pharmacokinetic profiles for central nervous system (CNS) penetration and that allows rapid implementation in clinical trials. Additionally, we provide an overview of repurposed candidate drug currently being investigated in GBM at the preclinical and clinical levels. Finally, we highlight the importance of phase 0 trials to confirm tumor drug exposure and we discuss emerging drug delivery technologies as an alternative route to maximize therapeutic efficacy of repurposed candidate drug.

Synthesis, Pharmacokinetic Characterization and Antioxidant Capacity of Carotenoid Succinates and Their Melatonin Conjugates

Carotenoid succinates were synthesized from hydroxy carotenoids and were coupled to a commercially available derivative of melatonin via amide bond for producing more powerful anti-oxidants and yet new hybrid lipophilic bifunctional molecules with additional therapeutic effects. The coupling reactions produced conjugates in acceptable to good yields. Succinylation increased the water solubility of the carotenoids, while the conjugation with melatonin resulted in more lipophilic derivatives. The conjugates showed self-assembly in aqueous medium and yielded relatively stable colloidal solutions in phosphate-buffered saline. Antioxidant behavior was measured with ABTS and the FRAP methods for the carotenoids, the carotenoid succinates, and the conjugates with melatonin. A strong dependence on the quality of the solvent was observed. TEAC values of the new derivatives in phosphate-buffered saline were found to be comparable to or higher than those of parent carotenoids, however, synergism was observed only in FRAP assays.

Development of copper-catalyzed deaminative esterification using high-throughput experimentation

Repurposing of amine and carboxylic acid building blocks provides an enormous opportunity to expand the accessible chemical space, because amine and acid feedstocks are typically low cost and available in high diversity. Herein, we report a copper-catalyzed deaminative esterification based on C-N activation of aryl amines via diazonium salt formation. The reaction was specifically designed to complement the popular amide coupling reaction. A chemoinformatic analysis of commercial building blocks demonstrates that by utilizing aryl amines, our method nearly doubles the available esterification chemical space compared to classic Fischer esterification with phenols. High-throughput experimentation in microliter reaction droplets was used to develop the reaction, along with classic scope studies, both of which demonstrated robust performance against hundreds of substrate pairs. Furthermore, we have demonstrated that this new esterification is suitable for late-stage diversification and for building-block repurposing to expand chemical space.

Unbound Brain-to-Plasma Partition Coefficient, Kp,uu,brain-a Game Changing Parameter for CNS Drug Discovery and Development

PURPOSE

More than 15 years have passed since the first description of the unbound brain-to-plasma partition coefficient (Kp,uu,brain) by Prof. Margareta Hammarlund-Udenaes, which was enabled by advancements in experimental methodologies including cerebral microdialysis. Since then, growing knowledge and data continue to support the notion that the unbound (free) concentration of a drug at the site of action, such as the brain, is the driving force for pharmacological responses. Towards this end, Kp,uu,brain is the key parameter to obtain unbound brain concentrations from unbound plasma concentrations.

METHODS

To understand the importance and impact of the Kp,uu,brain concept in contemporary drug discovery and development, a survey has been conducted amongst major pharmaceutical companies based in Europe and the USA. Here, we present the results from this survey which consisted of 47 questions addressing: 1) Background information of the companies, 2) Implementation, 3) Application areas, 4) Methodology, 5) Impact and 6) Future perspectives.

RESULTS AND CONCLUSIONS

From the responses, it is clear that the majority of the companies (93%) has established a common understanding across disciplines of the concept and utility of Kp,uu,brain as compared to other parameters related to brain exposure. Adoption of the Kp,uu,brain concept has been mainly driven by individual scientists advocating its application in the various companies rather than by a top-down approach. Remarkably, 79% of all responders describe the portfolio impact of Kp,uu,brain implementation in their companies as 'game-changing'. Although most companies (74%) consider the current toolbox for Kp,uu,brain assessment and its validation satisfactory for drug discovery and early development, areas of improvement and future research to better understand human brain pharmacokinetics/pharmacodynamics translation have been identified.

Graph-based molecular Pareto optimisation

Computer-assisted design of small molecules has experienced a resurgence in academic and industrial interest due to the widespread use of data-driven techniques such as deep generative models. While the ability to generate molecules that fulfil required chemical properties is encouraging, the use of deep learning models requires significant, if not prohibitive, amounts of data and computational power. At the same time, open-sourcing of more traditional techniques such as graph-based genetic algorithms for molecular optimisation [Jensen, Chem. Sci., 2019, 12, 3567-3572] has shown that simple and training-free algorithms can be efficient and robust alternatives. Further research alleviated the common genetic algorithm issue of evolutionary stagnation by enforcing molecular diversity during optimisation [Van den Abeele, Chem. Sci., 2020, 42, 11485-11491]. The crucial lesson distilled from the simultaneous development of deep generative models and advanced genetic algorithms has been the importance of chemical space exploration [Aspuru-Guzik, Chem. Sci., 2021, 12, 7079-7090]. For single-objective optimisation problems, chemical space exploration had to be discovered as a useable resource but in multi-objective optimisation problems, an exploration of trade-offs between conflicting objectives is inherently present. In this paper we provide state-of-the-art and open-source implementations of two generations of graph-based non-dominated sorting genetic algorithms (NSGA-II, NSGA-III) for molecular multi-objective optimisation. We provide the results of a series of benchmarks for the inverse design of small molecule drugs for both the NSGA-II and NSGA-III algorithms. In addition, we introduce the dominated hypervolume and extended fingerprint based internal similarity as novel metrics for these benchmarks. By design, NSGA-II, and NSGA-III outperform a single optimisation method baseline in terms of dominated hypervolume, but remarkably our results show they do so without relying on a greater internal chemical diversity.

Hearing loss drug discovery and medicinal chemistry: Current status, challenges, and opportunities

Hearing loss is a severe high unmet need condition affecting more than 1.5 billion people globally. There are no licensed medicines for the prevention, treatment or restoration of hearing. Prosthetic devices, such as hearing aids and cochlear implants, do not restore natural hearing and users struggle with speech in the presence of background noise. Hearing loss drug discovery is immature, and small molecule approaches include repurposing existing drugs, combination therapeutics, late-stage discovery optimisation of known chemotypes for identified molecular targets of interest, phenotypic tissue screening and high-throughput cell-based screening. Hearing loss drug discovery requires the integration of specialist therapeutic area biology and otology clinical expertise. Small molecule drug discovery projects in the global clinical portfolio for hearing loss are here collated and reviewed. An overview is provided of human hearing, inner ear anatomy, inner ear delivery, types of hearing loss and hearing measurement. Small molecule experimental drugs in clinical development for hearing loss are reviewed, including their underpinning biology, discovery strategy and activities, medicinal chemistry, calculated physicochemical properties, pharmacokinetics and clinical trial status. SwissADME BOILED-Egg permeability modelling is applied to the molecules reviewed, and these results are considered. Non-small molecule hearing loss assets in clinical development are briefly noted in this review. Future opportunities in hearing loss drug discovery for human genomics and targeted protein degradation are highlighted.

Design of SARS-CoV-2 Main Protease Inhibitors Using Artificial Intelligence and Molecular Dynamic Simulations

Drug design is a time-consuming and cumbersome process due to the vast search space of drug-like molecules and the difficulty of investigating atomic and electronic interactions. The present paper proposes a computational drug design workflow that combines artificial intelligence (AI) methods, i.e., an evolutionary algorithm and artificial neural network model, and molecular dynamics (MD) simulations to design and evaluate potential drug candidates. For the purpose of illustration, the proposed workflow was applied to design drug candidates against the main protease of severe acute respiratory syndrome coronavirus 2. From the ∼140,000 molecules designed using AI methods, MD analysis identified two molecules as potential drug candidates.

4-Aminoquinoline-Based Adamantanes as Potential Anticholinesterase Agents in Symptomatic Treatment of Alzheimer's Disease

Considering that acetylcholinesterase (AChE) inhibition is the most important mode of action expected of a potential drug used for the treatment of symptoms of Alzheimer’s disease (AD), our previous pilot study of 4-aminoquinolines as potential human cholinesterase inhibitors was extended to twenty-two new structurally distinct 4-aminoquinolines bearing an adamantane moiety. Inhibition studies revealed that all of the compounds were very potent inhibitors of AChE and butyrylcholinesterase (BChE), with inhibition constants (K_i) ranging between 0.075 and 25 µM. The tested compounds exhibited a modest selectivity between the two cholinesterases; the most selective for BChE was compound 14, which displayed a 10 times higher preference, while compound 19 was a 5.8 times more potent inhibitor of AChE. Most of the compounds were estimated to be able to cross the blood–brain barrier (BBB) by passive transport. Evaluation of druglikeness singled out fourteen compounds with possible oral route of administration. The tested compounds displayed modest but generally higher antioxidant activity than the structurally similar AD drug tacrine. Compound 19 showed the highest reducing power, comparable to those of standard antioxidants. Considering their simple structure, high inhibition of AChE and BChE, and ability to cross the BBB, 4-aminoquinoline-based adamantanes show promise as structural scaffolds for further design of novel central nervous system drugs. Among them, two compounds stand out: compound 5 as the most potent inhibitor of both cholinesterases with a K_i constant in low nano molar range and the potential to cross the BBB, and compound 8, which met all our requirements, including high cholinesterase inhibition, good oral bioavailability, and antioxidative effect. The QSAR model revealed that AChE and BChE inhibition was mainly influenced by the ring and topological descriptors MCD, Nnum, RP, and RSIpw3, which defined the shape, conformational flexibility, and surface properties of the molecules.

In Silico Approaches for Addressing Challenges in CNS Radiopharmaceutical Design

Positron emission tomography (PET) is a highly sensitive and versatile molecular imaging modality that leverages radiolabeled molecules, known as radiotracers, to interrogate biochemical processes such as metabolism, enzymatic activity, and receptor expression. The ability to probe specific molecular and cellular events longitudinally in a noninvasive manner makes PET imaging a particularly powerful technique for studying the central nervous system (CNS) in both health and disease. Unfortunately, developing and translating a single CNS PET tracer for clinical use is typically an extremely resource-intensive endeavor, often requiring synthesis and evaluation of numerous candidate molecules. While existing in vitro methods are beginning to address the challenge of derisking molecules prior to costly in vivo PET studies, most require a significant investment of resources and possess substantial limitations. In the context of CNS drug development, significant time and resources have been invested into the development and optimization of computational methods, particularly involving machine learning, to streamline the design of better CNS therapeutics. However, analogous efforts developed and validated for CNS radiotracer design are conspicuously limited. In this Perspective, we overview the requirements and challenges of CNS PET tracer design, survey the most promising computational methods for in silico CNS drug design, and bridge these two areas by discussing the potential applications and impact of computational design tools in CNS radiotracer design.

New Phenylglycinamide Derivatives with Hybrid Structure as Candidates for New Broad-Spectrum Anticonvulsants

In the present study, a focused combinatorial chemistry approach was applied to merge structural fragments of well-known TRPV1 antagonists with a potent anticonvulsant lead compound, KA-104, that was previously discovered by our group. Consequently, a series of 22 original compounds has been designed, synthesized, and characterized in the in vivo and in vitro assays. The obtained compounds showed robust in vivo antiseizure activity in the maximal electroshock (MES) test and in the 6 Hz seizure model (using both 32 and 44 mA current intensities). The most potent compounds 53 and 60 displayed the following pharmacological profile: ED₅₀ = 89.7 mg/kg (MES), ED₅₀ = 29.9 mg/kg (6 Hz, 32 mA), ED₅₀ = 68.0 mg/kg (6 Hz, 44 mA), and ED₅₀ = 73.6 mg/kg (MES), ED₅₀ = 24.6 mg/kg (6 Hz, 32 mA), and ED₅₀ = 56.3 mg/kg (6 Hz, 44 mA), respectively. Additionally, 53 and 60 were effective in the ivPTZ seizure threshold and had no influence on the grip strength and body temperature in mice. The in vitro binding and functional assays indicated a multimodal mechanism of action for 53 and 60. These molecules, beyond TRPV1 antagonism, inhibited calcium currents and fast sodium currents in patch-clamp assays. Further studies proved beneficial in vitro ADME-Tox properties for 53 and 60 (i.e., high metabolic stability, weak influence on CYPs, no neurotoxicity, etc.). Overall, 53 and 60 seem to be interesting candidates for future preclinical development in epilepsy and pain indications due to their interaction with the TRPV1 channel.

An In Silico Explainable Multiparameter Optimization Approach for De Novo Drug Design against Proteins from the Central Nervous System

The aim of drug design and development is to produce a drug that can inhibit the target protein and possess a balanced physicochemical and toxicity profile. Traditionally, this is a multistep process where different parameters such as activity and physicochemical and pharmacokinetic properties are optimized sequentially, which often leads to high attrition rate during later stages of drug design and development. We have developed a deep learning-based de novo drug design method that can design novel small molecules by optimizing target specificity as well as multiple parameters (including late-stage parameters) in a single step. All possible combinations of parameters were optimized to understand the effect of each parameter over the other parameters. An explainable predictive model was used to identify the molecular fragments responsible for the property being optimized. The proposed method was applied against the human 5-hydroxy tryptamine receptor 1B (5-HT1B), a protein from the central nervous system (CNS). Various physicochemical properties specific to CNS drugs were considered along with the target specificity and blood-brain barrier permeability (BBBP), which act as an additional challenge for CNS drug delivery. The contribution of each parameter toward molecule design was identified by analyzing the properties of generated small molecules from optimization of all possible parameter combinations. The final optimized generative model was able to design similar inhibitors compared to known inhibitors of 5-HT1B. In addition, the functional groups of the generated small molecules that guide the BBBP predictive model were identified through feature attribution techniques.

Radiosynthesis and In Vivo Evaluation of Four Positron Emission Tomography Tracer Candidates for Imaging of Melatonin Receptors

Melatonin is a neurohormone that modulates several physiological functions in mammals through the activation of melatonin receptor type 1 and 2 (MT₁ and MT₂). The melatonergic system is an emerging therapeutic target for new pharmacological interventions in the treatment of sleep and mood disorders; thus, imaging tools to further investigate its role in the brain are highly sought-after. We aimed to develop selective radiotracers for in vivo imaging of both MT₁ and MT₂ by positron emission tomography (PET). We identified four previously reported MT ligands with picomolar affinities to the target based on different scaffolds which were also amenable for radiolabeling with either carbon-11 or fluorine-18. [¹¹C]UCM765, [¹¹C]UCM1014, [¹⁸F]3-fluoroagomelatine ([¹⁸F]3FAGM), and [¹⁸F]fluoroacetamidoagomelatine ([¹⁸F]FAAGM) have been synthesized in high radiochemical purity and evaluated in wild-type rats. All four tracers showed moderate to high brain permeability in rats with maximum standardized uptake values (SUV_max of 2.53, 1.75, 3.25, and 4.47, respectively) achieved 1-2 min after tracer administration, followed by a rapid washout from the brain. Several melatonin ligands failed to block the binding of any of the PET tracer candidates, while in some cases, homologous blocking surprisingly resulted in increased brain retention. Two ¹⁸F-labeled agomelatine derivatives were brought forward to PET scans in non-human primates and autoradiography on human brain tissues. No specific binding has been detected in blocking studies. To further investigate pharmacokinetic properties of the putative tracers, microsomal stability, plasma protein binding, log D, and membrane bidirectional permeability assays have been conducted. Based on the results, we conclude that the fast first pass metabolism by the enzymes in liver microsomes is the likely reason of the failure of our PET tracer candidates. Nevertheless, we showed that PET imaging can serve as a valuable tool to investigate the brain permeability of new therapeutic compounds targeting the melatonergic system.

Simultaneous determination of LY3214996, abemaciclib, and M2 and M20 metabolites in human plasma, cerebrospinal fluid, and brain tumor by LC-MS/MS

A sensitive and rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) method was established for the quantification of total and unbound concentrations of LY3214996, an extracellular signal-regulated kinase inhibitor; abemaciclib, a cyclin-dependent kinase 4/6 inhibitor; and abemaciclib active metabolites, M2 and M20, in human plasma, brain tumor, and cerebrospinal fluid samples. The method was validated over a concentration range of 0.2–500 nM within a total run time of 3.8 min using isocratic elution on a Kinetex™ F₅ column. Detection was performed on a Sciex QTRAP 6500+ mass spectrometer employing multiple reaction monitoring mode under positive electrospray ionization. The intra- and inter-batch accuracy as well as the precision of the method for all matrices was within ±20% and ≤20% at the lower limit of quantification, and within ±15% and ≤15% for other quality control levels for all analytes. The unbound fractions of drugs and metabolites in spiked and patient samples were determined using an optimized equilibrium dialysis. The validated method was successfully applied in a phase 0/2 clinical trial to assess the central nervous system penetration of LY3214996 and abemaciclib.

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The LC-MS/MS method was validated to measure LY3214996, abemaciclib, M2 and M20 in human plasma, brain tumor, and CSF.

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Unbound fractions of LY3214996, abemaciclib, M2 and M20 were established in human plasma, brain, and brain tumor.

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The total and unbound levels of LY3214996, abemaciclib, M2 and M20 in glioblastoma patients have been reported.

Discovery of a Novel Class of d-Amino Acid Oxidase Inhibitors Using the Schrödinger Computational Platform

d-Serine is a coagonist of the N-methyl d-aspartate (NMDA) receptor, a key excitatory neurotransmitter receptor. In the brain, d-serine is synthesized from its l-isomer by serine racemase and is metabolized by the D-amino acid oxidase (DAO, DAAO). Many studies have linked decreased d-serine concentration and/or increased DAO expression and enzyme activity to NMDA dysfunction and schizophrenia. Thus, it is feasible to employ DAO inhibitors for the treatment of schizophrenia and other indications. Powered by the Schrödinger computational modeling platform, we initiated a research program to identify novel DAO inhibitors with the best-in-class properties. The program execution leveraged an hDAO FEP+ model to prospectively predict compound potency. A new class of DAO inhibitors with desirable properties has been discovered from this endeavor. Our modeling technology on this program has not only enhanced the efficiency of structure-activity relationship development but also helped to identify a previously unexplored subpocket for further optimization.

Fluoroalkylation of Dextromethorphan Improves CNS Exposure and Metabolic Stability

Aryl-methyl ethers, while present in many bioactive compounds, are subject to rapid O-dealkylation, which can generate bioinactive or toxic metabolites. Such is the case for dextromethorphan, which readily undergoes P450 mediated O-dealkylation to provide the psychoactive phenolic metabolite dextrorphan, an N-methyl-d-aspartate (NMDA) receptor antagonist that causes hallucinations and encourages recreational abuse. As a general strategy to minimize this undesired degradation, both deuteration and fluorination strategies might be exploited, though such strategies have rarely been compared in matched series. In this manuscript, we designed, synthesized, and evaluated in vitro and in vivo new fluoroalkyl analogs of dextromethorphan and D₃-dextromethorphan that minimize metabolic degradation and increased CNS exposure relative to dextromethorphan and related deuterated analogs currently in clinical trials.

AutoDesigner, a De Novo Design Algorithm for Rapidly Exploring Large Chemical Space for Lead Optimization: Application to the Design and Synthesis of d-Amino Acid Oxidase Inhibitors

The lead optimization stage of a drug discovery program generally involves the design, synthesis, and assaying of hundreds to thousands of compounds. The design phase is usually carried out via traditional medicinal chemistry approaches and/or structure-based drug design (SBDD) when suitable structural information is available. Two of the major limitations of this approach are (1) difficulty in rapidly designing potent molecules that adhere to myriad project criteria, or the multiparameter optimization (MPO) problem, and (2) the relatively small number of molecules explored compared to the vast size of chemical space. To address these limitations, we have developed AutoDesigner, a de novo design algorithm. AutoDesigner employs a cloud-native, multistage search algorithm to carry out successive rounds of chemical space exploration and filtering. Millions to billions of virtual molecules are explored and optimized while adhering to a customizable set of project criteria such as physicochemical properties and potency. Additionally, the algorithm only requires a single ligand with measurable affinity and a putative binding model as a starting point, making it amenable to the early stages of an SBDD project where limited data are available. To assess the effectiveness of AutoDesigner, we applied it to the design of novel inhibitors of d-amino acid oxidase (DAO), a target for the treatment of schizophrenia. AutoDesigner was able to generate and efficiently explore over 1 billion molecules to successfully address a variety of project goals. The compounds generated by AutoDesigner that were synthesized and assayed (1) simultaneously met not only physicochemical criteria, clearance, and central nervous system (CNS) penetration (Kp,uu) cutoffs but also potency thresholds and (2) fully utilize structural data to discover and explore novel interactions and a previously unexplored subpocket in the DAO active site. The reported data demonstrate that AutoDesigner can play a key role in accelerating the discovery of novel, potent chemical matter within the constraints of a given drug discovery lead optimization campaign.

Machine Learning Analysis of Cocaine Addiction Informed by DAT, SERT, and NET-Based Interactome Networks

Cocaine addiction is a psychosocial disorder induced by the chronic use of cocaine and causes a large number of deaths around the world. Despite decades of effort, no drugs have been approved by the Food and Drug Administration (FDA) for the treatment of cocaine dependence. Cocaine dependence is neurological and involves many interacting proteins in the interactome. Among them, the dopamine (DAT), serotonin (SERT), and norepinephrine (NET) transporters are three major targets. Each of these targets has a large protein-protein interaction (PPI) network, which must be considered in the anticocaine addiction drug discovery. This work presents DAT, SERT, and NET interactome network-informed machine learning/deep learning (ML/DL) studies of cocaine addiction. We collected and analyzed 61 protein targets out of 460 proteins in the DAT, SERT, and NET PPI networks that have sufficiently large existing inhibitor datasets. Utilizing autoencoder (AE) and other ML/DL algorithms, including gradient boosting decision tree (GBDT) and multitask deep neural network (MT-DNN), we built predictive models for these targets with 115 407 inhibitors to predict drug repurposing potential and possible side effects. We further screened their absorption, distribution, metabolism, and excretion, and toxicity (ADMET) properties to search for leads having potential for developing treatments for cocaine addiction. Our approach offers a new systematic protocol for artificial intelligence (AI)-based anticocaine addiction lead discovery.