Early Diagnosis of Neurodegenerative Diseases: What Has Been Undertaken to Promote the Transition from PET to Fluorescence Tracers.

Alzheimer's Disease (AD) and Parkinson's Disease (PD) represent two among the most frequent neurodegenerative diseases worldwide. A common hallmark of these pathologies is the misfolding and consequent aggregation of amyloid proteins into soluble oligomers and insoluble ß-sheet-rich fibrils, which ultimately lead to neurotoxicity and cell death. After a hundred years of research on the subject, this is the only reliable histopathological feature in our hands. Since AD and PD are diagnosed only once neuronal death and the first symptoms have appeared, the early detection of these diseases is currently impossible. At present, there is no effective drug available, and patients are left with symptomatic and inconclusive therapies. Several reasons could be associated with the lack of effective therapeutic treatments. One of the most important factors is the lack of selective probes capable of detecting, as early as possible, the most toxic amyloid species involved in the onset of these pathologies. In this regard, chemical probes able to detect and distinguish among different amyloid aggregates are urgently needed. In this article, we will review and put into perspective results from ex vivo and in vivo studies performed on compounds specifically interacting with such early species. Following a general overview on the three different amyloid proteins leading to insoluble ß-sheet-rich amyloid deposits (amyloid ß1-42 peptide, Tau, and α-synuclein), a list of the advantages and disadvantages of the approaches employed to date is discussed, with particular attention paid to the translation of fluorescence imaging into clinical applications. Furthermore, we also discuss how the progress achieved in detecting the amyloids of one neurodegenerative disease could be leveraged for research into another amyloidosis. As evidenced by a critical analysis of the state of the art, substantial work still needs to be conducted. Indeed, the early diagnosis of neurodegenerative diseases is a priority, and we believe that this review could be a useful tool for better investigating this field.

LigAdvisor: a versatile and user-friendly web-platform for drug design.

Although several tools facilitating in silico drug design are available, their results are usually difficult to integrate with publicly available information or require further processing to be fully exploited. The rational design of multi-target ligands (polypharmacology) and the repositioning of known drugs towards unmet therapeutic needs (drug repurposing) have raised increasing attention in drug discovery, although they usually require careful planning of tailored drug design strategies. Computational tools and data-driven approaches can help to reveal novel valuable opportunities in these contexts, as they enable to efficiently mine publicly available chemical, biological, clinical, and disease-related data. Based on these premises, we developed LigAdvisor, a data-driven webserver which integrates information reported in DrugBank, Protein Data Bank, UniProt, Clinical Trials and Therapeutic Target Database into an intuitive platform, to facilitate drug discovery tasks as drug repurposing, polypharmacology, target fishing and profiling. As designed, LigAdvisor enables easy integration of similarity estimation results with clinical data, thereby allowing a more efficient exploitation of information in different drug discovery contexts. Users can also develop customizable drug design tasks on their own molecules, by means of ligand- and target-based search modes, and download their results. LigAdvisor is publicly available at https://ligadvisor.unimore.it/.

Structure-activity exploration of a small-molecule allosteric inhibitor of T790M/L858R double mutant EGFR.

EGFR is a protein kinase whose aberrant activity is frequently involved in the development of non-small lung cancer (NSCLC) drug resistant forms. The allosteric inhibition of this enzyme is currently one among the most attractive approaches to design and develop anticancer drugs. In a previous study, we reported the identification of a hit compound acting as type III allosteric inhibitor of the L858R/T790M double mutant EGFR. Herein, we report the design, synthesis and in vitro testing of a series of analogues of the previously identified hit with the aim of exploring the structure-activity relationships (SAR) around this scaffold. The performed analyses allowed us to identify two compounds 15 and 18 showing improved inhibition of double mutant EGFR with respect to the original hit, as well as interesting antiproliferative activity against H1975 NSCLC cancer cells expressing double mutant EGFR. The newly discovered compounds represent promising starting points for further hit-to-lead optimisation.

Trends and Applications in Computationally Driven Drug Repurposing.

Drug repurposing is a widely used approach originally developed to aid in the identification of new uses of already existing drugs outside the scope of the original medical indication [...].

Identification of Promising Drug Candidates against Prostate Cancer through Computationally-Driven Drug Repurposing.

Prostate cancer (PC) is one of the most common types of cancer in males. Although early stages of PC are generally associated with favorable outcomes, advanced phases of the disease present a significantly poorer prognosis. Moreover, currently available therapeutic options for the treatment of PC are still limited, being mainly focused on androgen deprivation therapies and being characterized by low efficacy in patients. As a consequence, there is a pressing need to identify alternative and more effective therapeutics. In this study, we performed large-scale 2D and 3D similarity analyses between compounds reported in the DrugBank database and ChEMBL molecules with reported anti-proliferative activity on various PC cell lines. The analyses included also the identification of biological targets of ligands with potent activity on PC cells, as well as investigations on the activity annotations and clinical data associated with the more relevant compounds emerging from the ligand-based similarity results. The results led to the prioritization of a set of drugs and/or clinically tested candidates potentially useful in drug repurposing against PC.

Insights into the Structural Conformations of the Tau Protein in Different Aggregation Status.

Tau is a protein characterized by large structural portions displaying extended conformational changes. Unfortunately, the accumulation of this protein into toxic aggregates in neuronal cells leads to a number of severe pathologies, collectively named tauopathies. In the last decade, significant research advancements were achieved, including a better understanding of Tau structures and their implication in different tauopathies. Interestingly, Tau is characterized by a high structural variability depending on the type of disease, the crystallization conditions, and the formation of pathologic aggregates obtained from in vitro versus ex vivo samples. In this review, we reported an up-to-date and comprehensive overview of Tau structures reported in the Protein Data Bank, with a special focus on discussing the connections between structural features, different tauopathies, different crystallization conditions, and the use of in vitro or ex vivo samples. The information reported in this article highlights very interesting links between all these aspects, which we believe may be of particular relevance for a more informed structure-based design of compounds able to modulate Tau aggregation.

Investigation of the effect of different linker chemotypes on the inhibition of histone deacetylases (HDACs).

Histone Deacetylases (HDACs) are among the most attractive and interesting targets in anticancer drug discovery. The clinical relevance of HDAC inhibitors (HDACIs) is testified by four FDA-approved drugs for cancer treatment. However, one of the main drawbacks of these drugs resides in the lack of selectivity against the different HDAC isoforms, resulting in severe side effects. Thus, the identification of selective HDACIs represents an exciting challenge for medicinal chemists. HDACIs are composed of a cap group, a linker region, and a metal-binding group interacting with the catalytic zinc ion. While the cap group has been extensively investigated, less information is available about the effect of the linker on isoform selectivity. To this aim, in this work, we explored novel linker chemotypes to direct isoform selectivity. A small library of 25 hydroxamic acids with hitherto unexplored linker chemotypes was prepared. In vitro tests demonstrated that, depending on the linker type, some candidates selectively inhibit HDAC1 over HDAC6 isoform or vice versa. Docking calculations were performed to rationalize the effect of the novel linker chemotypes on biologic activity. Moreover, four compounds were able to increase the levels of acetylation of histone H3 or tubulin. These compounds were also assayed in breast cancer MCF7 cells to test their antiproliferative effect. Three compounds showed a significant reduction of cancer proliferation, representing valuable starting points for further optimization.

Inhibitors of histone deacetylase 6 based on a novel 3-hydroxy-isoxazole zinc binding group.

Histone deacetylase 6 (HDAC6) is an established drug target for cancer treatment. Inhibitors of HDAC6 based on a hydroxamic acid zinc binding group (ZBG) are often associated with undesirable side effects. Herein, we describe the identification of HDAC6 inhibitors based on a completely new 3-hydroxy-isoxazole ZBG. A series of derivatives decorated with different aromatic or heteroaromatic linkers, and various cap groups were synthesised and biologically tested. In vitro tests demonstrated that some compounds are able to inhibit HDAC6 with good potency, the best candidate reaching an IC50 of 700 nM. Such good potency obtained with a completely new ZBG make these compounds particularly attractive. The effect of the most active inhibitors on the acetylation levels of histone H3 and α- tubulin and their anti-proliferative activity of DU145 cells were also investigated. Docking studies were performed to evaluate the binding mode of these new derivatives and discuss structure-activity relationships.

Antifungal Activity and DNA Topoisomerase Inhibition of Hydrolysable Tannins from Punica granatum L.

Punica granatum L. (pomegranate) fruit is known to be an important source of bioactive phenolic compounds belonging to hydrolysable tannins. Pomegranate extracts have shown antifungal activity, but the compounds responsible for this activity and their mechanism/s of action have not been completely elucidated up to now. The aim of the present study was the investigation of the inhibition ability of a selection of pomegranate phenolic compounds (i.e., punicalagin, punicalin, ellagic acid, gallic acid) on both plant and human fungal pathogens. In addition, the biological target of punicalagin was identified here for the first time. The antifungal activity of pomegranate phenolics was evaluated by means of Agar Disk Diffusion Assay and minimum inhibitory concentration (MIC) evaluation. A chemoinformatic analysis predicted for the first time topoisomerases I and II as potential biological targets of punicalagin, and this prediction was confirmed by in vitro inhibition assays. Concerning phytopathogens, all the tested compounds were effective, often similarly to the fungicide imazalil at the label dose. Particularly, punicalagin showed the lowest MIC for Alternaria alternata and Botrytis cinerea, whereas punicalin was the most active compound in terms of growth control extent. As for human pathogens, punicalagin was the most active compound among the tested ones against Candida albicans reference strains, as well as against the clinically isolates. UHPLC coupled with HRMS indicated that C. albicans, similarly to the phytopathogen Coniella granati, is able to hydrolyze both punicalagin and punicalin as a response to the fungal attack. Punicalagin showed a strong inhibitory activity, with IC50 values of 9.0 and 4.6 µM against C. albicans topoisomerases I and II, respectively. Altogether, the results provide evidence that punicalagin is a valuable candidate to be further exploited as an antifungal agent in particular against human fungal infections.

Chemoinformatics Analyses of Tau Ligands Reveal Key Molecular Requirements for the Identification of Potential Drug Candidates against Tauopathies.

Tau is a highly soluble protein mainly localized at a cytoplasmic level in the neuronal cells, which plays a crucial role in the regulation of microtubule dynamic stability. Recent studies have demonstrated that several factors, such as hyperphosphorylation or alterations of Tau metabolism, may contribute to the pathological accumulation of protein aggregates, which can result in neuronal death and the onset of a number of neurological disorders called Tauopathies. At present, there are no available therapeutic remedies able to reduce Tau aggregation, nor are there any structural clues or guidelines for the rational identification of compounds preventing the accumulation of protein aggregates. To help identify the structural properties required for anti-Tau aggregation activity, we performed extensive chemoinformatics analyses on a dataset of Tau ligands reported in ChEMBL. The performed analyses allowed us to identify a set of molecular properties that are in common between known active ligands. Moreover, extensive analyses of the fragment composition of reported ligands led to the identification of chemical moieties and fragment combinations prevalent in the more active compounds. Interestingly, many of these fragments were arranged in recurring frameworks, some of which were clearly present in compounds currently under clinical investigation. This work represents the first in-depth chemoinformatics study of the molecular properties, constituting fragments and similarity profiles, of known Tau aggregation inhibitors. The datasets of compounds employed for the analyses, the identified molecular fragments and their combinations are made publicly available as supplementary material.

Identification of Target Associations for Polypharmacology from Analysis of Crystallographic Ligands of the Protein Data Bank.

The design of a chemical entity that potently and selectively binds to a biological target of therapeutic relevance has dominated the scene of drug discovery so far. However, recent findings suggest that multitarget ligands may be endowed with superior efficacy and be less prone to drug resistance. The Protein Data Bank (PDB) provides experimentally validated structural information about targets and bound ligands. Therefore, it represents a valuable source of information to help identifying active sites, understanding pharmacophore requirements, designing novel ligands, and inferring structure-activity relationships. In this study, we performed a large-scale analysis of the PDB by integrating different ligand-based and structure-based approaches, with the aim of identifying promising target associations for polypharmacology based on reported crystal structure information. First, the 2D and 3D similarity profiles of the crystallographic ligands were evaluated using different ligand-based methods. Then, activity data of pairs of similar ligands binding to different targets were inspected by comparing structural information with bioactivity annotations reported in the ChEMBL, BindingDB, BindingMOAD, and PDBbind databases. Afterward, extensive docking screenings of ligands in the identified cross-targets were made in order to validate and refine the ligand-based results. Finally, the therapeutic relevance of the identified target combinations for polypharmacology was evaluated from comparison with information on therapeutic targets reported in the Therapeutic Target Database (TTD). The results led to the identification of several target associations with high therapeutic potential for polypharmacology.

Repositioning Natural Products in Drug Discovery.

Drug repositioning (o repurposing) has become one of the most popular and successful strategies to reduce failures typically associated with drug discovery [...].

Molecular Docking: Shifting Paradigms in Drug Discovery.

Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.

In Silico Repositioning of Cannabigerol as a Novel Inhibitor of the Enoyl Acyl Carrier Protein (ACP) Reductase (InhA).

Cannabigerol (CBG) and cannabichromene (CBC) are non-psychoactive cannabinoids that have raised increasing interest in recent years. These compounds exhibit good tolerability and low toxicity, representing promising candidates for drug repositioning. To identify novel potential therapeutic targets for CBG and CBC, an integrated ligand-based and structure-based study was performed. The results of the analysis led to the identification of CBG as a low micromolar inhibitor of the Enoyl acyl carrier protein (ACP) reductase (InhA) enzyme.

Quantitative live cell imaging of a tauopathy model enables the identification of a polypharmacological drug candidate that restores physiological microtubule interaction.

Tauopathies such as Alzheimer's disease are characterized by aggregation and increased phosphorylation of the microtubule-associated protein tau. Tau's pathological changes are closely linked to neurodegeneration, making tau a prime candidate for intervention. We developed an approach to monitor pathological changes of aggregation-prone human tau in living neurons. We identified 2-phenyloxazole (PHOX) derivatives as putative polypharmacological small molecules that interact with tau and modulate tau kinases. We found that PHOX15 inhibits tau aggregation, restores tau's physiological microtubule interaction, and reduces tau phosphorylation at disease-relevant sites. Molecular dynamics simulations highlight cryptic channel-like pockets crossing tau protofilaments and suggest that PHOX15 binding reduces the protofilament's ability to adopt a PHF-like conformation by modifying a key glycine triad. Our data demonstrate that live-cell imaging of a tauopathy model enables screening of compounds that modulate tau-microtubule interaction and allows identification of a promising polypharmacological drug candidate that simultaneously inhibits tau aggregation and reduces tau phosphorylation.

Discovery of potent pyrrolo-pyrimidine and purine HDAC inhibitors for the treatment of advanced prostate cancer.

The development of drugs for the treatment of advanced prostate cancer (PCA) remains a challenging task. In this study we have designed, synthesized and tested twenty-nine novel HDAC inhibitors based on three different zinc binding groups (trifluoromethyloxadiazole, hydroxamic acid, and 2-mercaptoacetamide). These warheads were conveniently tethered to variously substituted phenyl linkers and decorated with differently substituted pyrrolo-pyrimidine and purine cap groups. Remarkably, most of the compounds showed nanomolar inhibitory activity against HDAC6. To provide structural insights into the Structure-Activity Relationships (SAR) of the investigated compounds, docking of representative inhibitors and molecular dynamics of HDAC6-inhibitor complexes were performed. Compounds of the trifluoromethyloxadiazole and hydroxamic acid series exhibited promising anti-proliferative activities, HDAC6 targeting in PCA cells, and in vitro tumor selectivity. Representative compounds of the two series were tested for solubility, cell permeability and metabolic stability, demonstrating favorable in vitro drug-like properties. The more interesting compounds were subjected to migration assays, which revealed that compound 13 and, to a lesser extent, compound 15 inhibited the invasive behaviour of androgen-sensitive and -insensitive advanced prostate cancer cells. Compound 13 was profiled against all HDACs and found to inhibit all members of class II HDACs (except for HDAC10) and to be selective with respect to class I and class IV HDACs. Overall, compound 13 combines potent inhibitory activity and class II selectivity with favorable drug-like properties, an excellent anti-proliferative activity and marked anti-migration properties on PCA cells, making it an excellent lead candidate for further optimization.

Discovery of a Potent Dual Inhibitor of Aromatase and Aldosterone Synthase.

Estrogen deficiency derived from inhibition of estrogen biosynthesis is a typical condition of postmenopausal women and breast cancer (BCs) patients undergoing antihormone therapy. The ensuing increase in aldosterone levels is considered to be the major cause for cardiovascular diseases (CVDs) affecting these patients. Since estrogen biosynthesis is regulated by aromatase (CYP19A1), and aldosterone biosynthesis is modulated by aldosterone synthase (CYP11B2), a dual inhibitor would allow the treatment of BC while reducing the cardiovascular risks typical of these patients. Moreover, this strategy would help overcome some of the disadvantages often observed in single-target or combination therapies. Following an in-depth analysis of a library of synthesized benzylimidazole derivatives, compound X21 was found to be a potent and selective dual inhibitor of aromatase and aldosterone synthase, with IC50 values of 2.3 and 29 nM, respectively. Remarkably, the compound showed high selectivity with respect to 11ß-hydroxylase (CYP11B1), as well as CYP3A4 and CYP1A2. When tested in cells, X21 showed potent antiproliferative activity against BC cell lines, particularly against the ER+ MCF-7 cells (IC50 of 0.26 ± 0.03 µM at 72 h), and a remarkable pro-apoptotic effect. In addition, the compound significantly inhibited mTOR phosphorylation at its IC50 concentration, thereby negatively modulating the PI3K/Akt/mTOR axis, which represents an escape for the dependency from ER signaling in BC cells. The compound was further investigated for cytotoxicity on normal cells and potential cardiotoxicity against hERG and Nav1.5 ion channels, demonstrating a safe biological profile. Overall, these assays demonstrated that the compound is potent and safe, thus constituting an excellent candidate for further evaluation.

Design, synthesis, biological evaluation and crystal structure determination of dual modulators of carbonic anhydrases and estrogen receptors.

Multi-target compounds have become increasingly important for the development of safer and more effective drug candidates. In this work, we devised a combined ligand-based and structure-based multi-target repurposing strategy and applied it to a series of hexahydrocyclopenta[c]quinoline compounds synthesized previously. The in silico analyses identified human Carbonic Anhydrases (hCA) and Estrogen Receptors (ER) as top scoring candidates for dual modulation. hCA isoforms IX and XII, and ER subtypes ER⍺ and/or ERß are co-expressed in various cancer cell types, including breast and prostate cancer cells. ER⍺ is the primary target of anti-estrogen therapy in breast cancer, and the hCA IX isoform is a therapeutic target in triple-negative breast cancer. ER⍺-mediated transcriptional programs and hCA activity in cancer cells promote favorable microenvironments for cell proliferation. Interestingly, several lines of evidence indicate that the combined modulation of these two targets may provide significant therapeutic benefits. Moving from these first results, two additional hexahydrocyclopenta[c]quinoline derivatives bearing a sulfonamide zinc binding group (hCA) and a phenolic hydroxyl (ER) pharmacophoric group placed at the appropriate locations were designed and synthesized. Interestingly, these compounds were able to directly modulate the activities of both hCA and ER targets. In cell-based assays, they inhibited proliferation of breast and prostate cancer cells with micromolar potency and cell type-selective efficacy. The compounds inhibited hCA activity with nanomolar potency and isoform-selectivity. In transactivation assays, they reduced estrogen-driven ER activity with micro-molar potency. Finally, crystal structures of the synthesized ligands in complex with the two targets revealed that the compounds bind directly to the hCA active site, as well as to the ER ligand-binding domain, providing structural explanation to the observed activity and a rationale for optimization of their dual activity. To the best of our knowledge, this work describes the design, synthesis and biological characterization of the first dual modulators of hCA and ER, laying the ground for the structure-based optimization of their multi-target activity.

On the development of B-Raf inhibitors acting through innovative mechanisms.

B-Raf is a protein kinase participating to the regulation of many biological processes in cells. Recent studies have demonstrated that this protein is frequently overactivated in human cancers, especially when it bears activating mutations. In recent years, few ATP-competitive inhibitors of B-Raf have been marketed for the treatment of melanoma and are currently under clinical evaluation on a variety of other types of cancer. Although the introduction of drugs targeting B-Raf has provided significant advances in cancer treatment, responses to such ATP-competitive inhibitors remain limited, mainly due to selectivity issues, side effects, narrow therapeutic windows, and the insurgence of drug resistance. Impressive research efforts have been made so far towards the identification of novel ATP-competitive modulators with improved efficacy against cancers driven by mutant Raf monomers and dimers, some of them showing good premises. However, several limitations could still be envisioned for these compounds, according to recent literature data. Besides, increased attentions have recently arisen around approaches based on the design of allosteric modulators, polypharmacology, PROTACs and drug repurposing for the targeting of B-Raf proteins. The design of compounds acting through such innovative mechanisms is rather challenging. However, novel valuable therapeutic opportunities can be envisioned on these drugs, as they act through innovative mechanisms in which limitations typically observed for approved ATP-competitive B-Raf inhibitors are less prone to emerge. In this article, the most recent approaches adopted for the design of non-ATP competitive inhibitors targeting B-Raf are described, discussing also on the possibilities, ligands acting through such innovative mechanisms could provide for the obtainment of more effective therapies.

Development of machine learning classifiers to predict compound activity on prostate cancer cell lines.

Prostate cancer is the most common type of cancer in men. The disease presents good survival rates if treated at the early stages. However, the evolution of the disease in its most aggressive variant remains without effective therapeutic answers. Therefore, the identification of novel effective therapeutics is urgently needed. On these premises, we developed a series of machine learning models, based on compounds with reported highly homogeneous cell-based antiproliferative assay data, able to predict the activity of ligands towards the PC-3 and DU-145 prostate cancer cell lines. The data employed in the development of the computational models was finely-tuned according to a series of thresholds for the classification of active/inactive compounds, to the number of features to be implemented, and by using 10 different machine learning algorithms. Models' evaluation allowed us to identify the best combination of activity thresholds and ML algorithms for the classification of active compounds, achieving prediction performances with MCC values above 0.60 for PC-3 and DU-145 cells. Moreover, in silico models based on the combination of PC-3 and DU-145 data were also developed, demonstrating excellent precision performances. Finally, an analysis of the activity annotations reported for the ligands in the curated datasets were conducted, suggesting associations between cellular activity and biological targets that might be explored in the future for the design of more effective prostate cancer antiproliferative agents.