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.

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 β-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 β-sheet-rich amyloid deposits (amyloid β1-42 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.

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 [...].

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.

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.

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.

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 ERβ 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.

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.

Synthesis of potent and selective HDAC6 inhibitors led to unexpected opening of a quinazoline ring

Histone deacetylase (HDAC) inhibitors are highly involved in the regulation of many pharmacological responses, which results in anti-inflammatory and anti-cancer effects. In the present work, chemoinformatic analyses were performed to obtain two potent and selective aminotriazoloquinazoline-based HDAC6 inhibitors. We unexpectedly obtained an aminotriazole from a water-driven ring opening of the triazoloquinazoline scaffold. Both compounds were evaluated as HDAC6 inhibitors, resulting in subnanomolar inhibitory activity and high selectivity with respect to class I HDAC1 and HDAC8. Importantly, the compounds were about 3- and 15-fold more potent compared to the reference compound trichostatin A. Additionally, the predicted binding modes were investigated with docking. Considering that the aminotriazole scaffold has never been embedded into the chemical structure of HDAC6 inhibitors, the present study suggests that both the aminotriazoloquinazoline and aminotriazole classes of compounds could be excellent starting points for further optimization of potential anticancer compounds, introducing such novel groups into a relevant and new area of investigation.

Potent and selective inhibitors of HDAC6 have been designed, synthesized and tested. An unexpected opening of the quinazoline ring led to both aminotriazoloquinazoline and aminotriazole compounds with potent activity and isoform selectivity.

Identification of potential biological targets of oxindole scaffolds via in silico repositioning strategies

Background: Drug repurposing is an alternative strategy to traditional drug discovery that aims at predicting new uses for already existing drugs or clinical candidates. Drug repurposing has many advantages over traditional drug development, such as reduced attrition rates, time and costs. This is especially the case considering that most drugs investigated for repurposing have already been assessed for their safety in clinical trials. Repurposing campaigns can also be designed for libraries of already synthesized molecules at different levels of biological experimentation, from null to in vitro and in vivo. Such an extension of the "repurposing" concept is expected to provide significant advantages for the identification of novel drugs, as the synthetic accessibility of the desired compounds is often one of the limiting factors in the traditional drug discovery pipeline. Methods: In this work, we performed a computational repurposing campaign on a library of previously synthesized oxindole-based compounds, in order to identify potential new targets for this versatile scaffold. To this aim, ligand-based approaches were firstly applied to evaluate the similarity degree of the investigated compound library, with respect to ligands extracted from the DrugBank, Protein Data Bank (PDB) and ChEMBL databases. In particular, the 2D fingerprint-based and 3D shape-based similarity profiles were evaluated and compared for the oxindole derivates. Results: The analyses predicted a set of potential candidate targets for repurposing, some of them emerging by consensus of different computational analyses. One of the identified targets, i.e., the vascular endothelial growth factor receptor 2 (VEGFR-2) kinase, was further investigated by means of docking calculations, followed by biological testing of one candidate. Conclusions: While the compound did not show potent inhibitory activity towards VEGFR-2, the study highlighted several other possibilities of therapeutically relevant targets that may be worth of consideration for drug repurposing.

Design and Synthesis of Hsp90 Inhibitors with B-Raf and PDHK1 Multi-Target Activity

The design of multi-target ligands has become an innovative approach for the identification of effective therapeutic treatments against complex diseases, such as cancer. Recent studies have demonstrated that the combined inhibition of Hsp90 and B-Raf provides synergistic effects against several types of cancers. Moreover, it has been reported that PDHK1, which presents an ATP-binding pocket similar to that of Hsp90, plays an important role in tumor initiation, maintenance and progression, participating also to the senescence process induced by B-Raf oncogenic proteins. Based on these premises, the simultaneous inhibition of these targets may provide several benefits for the treatment of cancer. In this work, we set up a design strategy including the assembly and integration of molecular fragments known to be important for binding to the Hsp90, PDHK1 and B-Raf targets, aided by molecular docking for the selection of a set of compounds potentially able to exert Hsp90-B-Raf-PDHK1 multi-target activities. The designed compounds were synthesized and experimentally validated in vitro. According to the in vitro assays, compounds 4 a, 4 d and 4 e potently inhibited Hsp90 and moderately inhibited the PDHK1 kinase. Finally, molecular dynamics simulations were performed to provide further insights into the structural basis of their multi-target activity.

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.

Dual Targeting Strategies On Histone Deacetylase 6 (HDAC6) And Heat Shock Protein 90 (Hsp90)

The design of multi-target drugs acting simultaneously on multiple signaling pathways is a growing field in medicinal chemistry, especially for the treatment of complex diseases such as cancer. Histone deacetylase 6 (HDAC6) is an established anticancer drug target involved in tumor cells transformation. Being an epigenetic enzyme at the interplay of many biological processes, HDAC6 has become an attractive target for polypharmacology studies aimed at improving therapeutic efficacy of anticancer drugs. For example, the molecular chaperone Heat shock protein 90 (Hsp90) is a substrate of HDAC6 deacetylation, and several lines of evidence demonstrate that simultaneous inhibition of HDAC6 and Hsp90 promote synergistic antitumor effects on different cancer cell lines, highlighting the potential benefits of developing a single molecule endowed with multi-target activity. This review will summarize the complex interplay between HDAC6 and Hsp90, providing also useful hints for multi-target drug design and discovery approaches in this field. To this end, crystallographic structures of HDAC6 and Hsp90 complexes will be extensively reviewed in the light of discussing binding pockets features and pharmacophore requirements and providing useful guidelines for the design of dual inhibitors. The few examples of multi-target inhibitors obtained so far, mostly based on chimeric approaches, will be summarized and put into context. Finally, the main features of HDAC6 and Hsp90 inhibitors will be compared, and ligand- and structure-based strategies potentially useful for the development of small molecular weight dual inhibitors will be proposed and discussed.

Hydroxamic Acid Derivatives: From Synthetic Strategies to Medicinal Chemistry Applications

Since the approval of three hydroxamic acid-based HDAC inhibitors as anticancer drugs, such functional groups acquired even more notoriety in synthetic medicinal chemistry. The ability of hydroxamic acids (HAs) to chelate metal ions makes this moiety an attractive metal binding group-in particular, Fe(III) and Zn(II)-so that HA derivatives find wide applications as metalloenzymes inhibitors. In this minireview, we will discuss the most relevant features concerning hydroxamic acid derivatives. In a first instance, the physicochemical characteristics of HAs will be summarized; then, an exhaustive description of the most relevant methods for the introduction of such moiety into organic substrates and an overview of their uses in medicinal chemistry will be presented.

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.

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/.

Promising Non-cytotoxic Monosubstituted Chalcones to Target Monoamine Oxidase-B

A library of monosubstituted chalcones (1-17) bearing electron-donating and electron-withdrawing groups on both aromatic rings were selected. The cell viability on human tumor cell lines was evaluated first. The compounds unable to induce detectable cytotoxicity (1, 13, and 14) were tested using the monoamine oxidase (MAO) activity assay. Interestingly, they inhibit MAO-B, acting as competitive inhibitors, with 13 and 14 showing the best profiles. In particular, 13 exhibited a potency higher than that of safinamide, taken as a reference. Docking studies and crystallographic analysis showed that in human MAO-B 13 binds with the halogen-substituted aromatic ring in the entrance cavity, similar to safinamide, whereas 14 is accommodated in the opposite way. The main conclusion of this cell biology, biochemistry, and structural study is to highlights 13 as a chalcone derivative that is worth consideration for the development of novel MAO-B-selective inhibitors for the treatment of neurodegenerative diseases.

Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models

The development of selective inhibitors of the clinically relevant human Carbonic Anhydrase (hCA) isoforms IX and XII has become a major topic in drug research, due to their deregulation in several types of cancer. Indeed, the selective inhibition of these two isoforms, especially with respect to the homeostatic isoform II, holds great promise to develop anticancer drugs with limited side effects. Therefore, the development of in silico models able to predict the activity and selectivity against the desired isoform(s) is of central interest. In this work, we have developed a series of machine learning classification models, trained on high confidence data extracted from ChEMBL, able to predict the activity and selectivity profiles of ligands for human Carbonic Anhydrase isoforms II, IX and XII. The training datasets were built with a procedure that made use of flexible bioactivity thresholds to obtain well-balanced active and inactive classes. We used multiple algorithms and sampling sizes to finally select activity models able to classify active or inactive molecules with excellent performances. Remarkably, the results herein reported turned out to be better than those obtained by models built with the classic approach of selecting an a priori activity threshold. The sequential application of such validated models enables virtual screening to be performed in a fast and more reliable way to predict the activity and selectivity profiles against the investigated isoforms.

Drug Repurposing and Polypharmacology to Fight SARS-CoV-2 Through Inhibition of the Main Protease

The outbreak of a new coronavirus (SARS-CoV-2), which is responsible for the COVID-19 disease and is spreading rapidly around the world, urgently requires effective therapeutic treatments. In this context, drug repurposing represents a valuable strategy, as it enables accelerating the identification of drug candidates with already known safety profiles, possibly aiding in the late stages of clinical evaluation. Moreover, therapeutic treatments based on drugs with beneficial multi-target activities (polypharmacology) may show an increased antiviral activity or help to counteract severe complications concurrently affecting COVID-19 patients. In this study, we present the results of a computational drug repurposing campaign that aimed at identifying potential inhibitors of the main protease (Mpro) of the SARS-CoV-2. The performed in silico screening allowed the identification of 22 candidates with putative SARS-CoV-2 Mpro inhibitory activity. Interestingly, some of the identified compounds have recently entered clinical trials for COVID-19 treatment, albeit not being assayed for their SARS-CoV-2 antiviral activity. Some candidates present a polypharmacology profile that may be beneficial for COVID-19 treatment and, to the best of our knowledge, have never been considered in clinical trials. For each repurposed compound, its therapeutic relevance and potential beneficial polypharmacological effects that may arise due to its original therapeutic indication are thoroughly discussed.

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.

Breakthroughs in Medicinal Chemistry: New Targets and Mechanisms, New Drugs, New Hopes-7

Breakthroughs in Medicinal Chemistry [...].

Design of Dual Inhibitors of Histone Deacetylase 6 and Heat Shock Protein 90

Histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90) are widely investigated anticancer drug targets. Importantly, several lines of evidence indicate that their regulation and activity are intimately linked, and that their combined inhibition may lead to impressive therapeutic benefits. In this study, we developed and applied an integrated computational strategy to design dual inhibitors of HDAC6 and Hsp90. Although the two targets share very little homology, an integrated ligand-based and structure-based virtual screening approach indicated a subset of compounds possessing the key structural requirements for binding at both targets. In vitro tests demonstrated that some of the selected candidates are able to selectively inhibit HDAC6 over HDAC1, to increase the acetylation levels of tubulin on cell assays and to reduce cell proliferation. The discovered compounds represent valuable starting points for further hit optimization.

Microwave Spectroscopy Reveals the Quantum Geometric Tensor of Topological Josephson Matter

Quantization effects due to topological invariants such as Chern numbers have become very relevant in many systems, yet key quantities such as the quantum geometric tensor providing local information about quantum states remain experimentally difficult to access. Recently, it has been shown that multiterminal Josephson junctions constitute an ideal platform to synthesize topological systems in a controlled manner. We theoretically study properties of Andreev states in topological Josephson matter and demonstrate that the quantum geometric tensor of Andreev states can be extracted by synthetically polarized microwaves. The oscillator strength of the absorption rates provides direct evidence of topological quantum properties of the Andreev states.

Breakthroughs in Medicinal Chemistry: New Targets and Mechanisms, New Drugs, New Hopes-6

Breakthroughs in Medicinal Chemistry: New Targets and Mechanisms, New Drugs, New Hopes is a series of Editorials that is published on a biannual basis by the Editorial Board of the Medicinal Chemistry section of the journal Molecules [...].

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.

2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i ) values in the sub-micromolar range and a good selectivity index (K_i MAO-A /K_i MAO-B >50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.

Refinement and Rescoring of Virtual Screening Results

High-throughput docking is an established computational screening approach in drug design. This methodology enables a rapid identification of biologically active hit compounds, providing an efficient and cost-effective complement or alternative to experimental high-throughput screenings. However, limitations inherent to the methodology make docking results inevitably approximate. Two major Achille's heels include the use of approximated scoring functions and the limited sampling of the ligand-target complexes. Therefore, docking results require careful evaluation and further post-docking analyses. In this article, we will overview our approach to post-docking analysis in virtual screenings. BEAR (Binding Estimation After Refinement) was developed as a post-docking processing tool that refines docking poses by means of molecular dynamics (MD) and then rescores the ligands based on more accurate scoring functions (MM-PB(GB)SA). The tool has been validated and used prospectively in drug discovery applications. Future directions regarding refinement and rescoring in virtual screening are discussed.

Evaluation of Amides, Carbamates, Sulfonamides, and Ureas of 4-Prop-2-ynylidenecycloalkylamine as Potent, Selective, and Bioavailable Negative Allosteric Modulators of Metabotropic Glutamate Receptor 5

Negative allosteric modulators (NAMs) of the metabotropic glutamate receptor 5 (mGlu₅) hold great promise for the treatment of a variety of central nervous system disorders. We have recently reported that prop-2-ynylidenecycloalkylamine derivatives are potent and selective NAMs of the mGlu₅ receptor. In this work, we explored the amide, carbamate, sulfonamide, and urea derivatives of prop-2-ynylidenecycloalkylamine compounds with the aim of improving solubility and metabolic stability. In silico and experimental analyses were performed on the synthesized series of compounds to investigate structure-activity relationships. Compounds 12, 32, and 49 of the carbamate, urea, and amide classes, respectively, showed the most suitable cytochrome inhibition and metabolic stability profiles. Among them, compound 12 showed excellent selectivity, solubility, and stability profiles as well as suitable in vitro and in vivo pharmacokinetic properties. It was highly absorbed in rats and dogs and was active in anxiety, neuropathic pain, and lower urinary tract models.

Selection of protein conformations for structure-based polypharmacology studies

Several drugs exert their therapeutic effect through the modulation of multiple targets. Structure-based approaches hold great promise for identifying compounds with the desired polypharmacological profiles. These methods use knowledge of the protein binding sites to identify stereoelectronically complementary ligands. The selection of the most suitable protein conformations to be used in the design process is vital, especially for multitarget drug design in which the same ligand has to be accommodated in multiple binding pockets. Herein, we focus on currently available techniques for the selection of the most suitable protein conformations for multitarget drug design, compare the potential advantages and limitations of each method, and comment on how their combination could help in polypharmacology drug design.

Epidemiology and clinics of mushroom poisoning in Northern Italy: A 21-year retrospective analysis

Background:

Limited information exists about epidemiology and management of mushroom poisoning. We analyzed and described epidemiology, clinical presentation, and clinical course of mushroom-poisoned patients admitted to emergency departments (EDs) of the Province of Parma, Italy.

Methods:

Data from the database of mycological service were matched with clinical information retrieved from hospitals’ database, from January 1, 1996 to December 31, 2016.

Results:

Mycologist consultation was obtained in 379/443 identified mushroom poisonings. A remarkable seasonality was found, with significant peak in autumn. Thanks to the collaboration, the implicated species could be identified in 397 cases (89.6%); 108 cases (24.4%) were due to edible mushrooms, Boletus edulis being the most represented (63 cases). Overall, 408 (92%) cases presented with gastrointestinal toxicity. Twenty cases of amatoxin poisoning were recorded (11 Amanita phalloides and 9 Lepiota brunneoincarnata). One liver transplantation was needed. We observed 13 cases of cholinergic toxicity and 2 cases of hallucinogenic toxicity. Finally, 46 cases were due to “mixed” toxicities, and a total of 69 needed hospitalization.

Conclusions:

Early identification and management of potentially life-threatening cases is challenging in the ED, so that a mycologist service on call is highly advisable, especially during periods characterized by the highest incidence of poisoning.

The 1,2,3-triazole ring as a bioisostere in medicinal chemistry

1,2,3-Triazole is a well-known scaffold that has a widespread occurrence in different compounds characterized by several bioactivities, such as antimicrobial, antiviral, and antitumor effects. Moreover, the structural features of 1,2,3-triazole enable it to mimic different functional groups, justifying its wide use as a bioisostere for the synthesis of new active molecules. Here, we provide an overview of the 1,2,3-triazole ring as a bioisostere for the design of drug analogs, highlighting relevant recent examples.

On the Integration of In Silico Drug Design Methods for Drug Repurposing

Drug repurposing has become an important branch of drug discovery. Several computational approaches that help to uncover new repurposing opportunities and aid the discovery process have been put forward, or adapted from previous applications. A number of successful examples are now available. Overall, future developments will greatly benefit from integration of different methods, approaches and disciplines. Steps forward in this direction are expected to help to clarify, and therefore to rationally predict, new drug–target, target–disease, and ultimately drug–disease associations.

Promiscuity of inhibitors of human protein kinases at varying data confidence levels and test frequencies

Kinase inhibitors from screening data. Shown are two analogs that were tested against 10 (left) and 13 (right) different kinases. The inhibitor on the left was active against a single kinase and the one on the right against three kinases.

Heat shock protein 90 and serine/threonine kinase B-Raf inhibitors have overlapping chemical space

With the aid of computational design, we show that Hsp90 and B-Raf inhibitors have overlapping chemical space and we disclose the first-in-class dual inhibitors.

Ground-State Cooling of a Mechanical Oscillator by Interference in Andreev Reflection

We study the ground-state cooling of a mechanical oscillator linearly coupled to the charge of a quantum dot inserted between a normal metal and a superconducting contact. Such a system can be realized, e.g., by a suspended carbon nanotube quantum dot with a capacitive coupling to a gate contact. Focusing on the subgap transport regime, we analyze the inelastic Andreev reflections which drive the resonator to a nonequilibrium state. For small coupling, we obtain that vibration-assisted reflections can occur through two distinct interference paths. The interference determines the ratio between the rates of absorption and emission of vibrational energy quanta. We show that ground-state cooling of the mechanical oscillator can be achieved for many of the oscillator's modes simultaneously or for single modes selectively, depending on the experimentally tunable coupling to the superconductor.