Discovery of a septin-4 covalent binder with antimetastatic activity in a mouse model of melanoma.

Cancer spreading through metastatic processes is one of the major causes of tumour-related mortality. Metastasis is a complex phenomenon which involves multiple pathways ranging from cell metabolic alterations to changes in the biophysical phenotype of cells and tissues. In the search for new effective anti-metastatic agents, we modulated the chemical structure of the lead compound AA6, in order to find the structural determinants of activity, and to identify the cellular target responsible of the downstream anti-metastatic effects observed. New compounds synthesized were able to inhibit in vitro B16-F10 melanoma cell invasiveness, and one selected compound, CM365, showed in vivo anti-metastatic effects in a lung metastasis mouse model of melanoma. Septin-4 was identified as the most likely molecular target responsible for these effects. This study showed that CM365 is a promising molecule for metastasis prevention, remarkably effective alone or co-administered with drugs normally used in cancer therapy, such as paclitaxel.

New potent muscarinic receptor ligands bearing the 1,4-dioxane nucleus: Investigation on the nature of the substituent in position 2.

A new series of muscarinic acetylcholine receptor (mAChR) ligands obtained by inserting different substituents in position 2 of the potent 6,6-diphenyl-1,4-dioxane antagonists 4 and 5 was designed and synthesized to investigate the influence of steric bulk on the mAChR affinity. Specifically, the insertion of a 2-methyl group, affording compounds 6 and 9, resulted as the most favorable modification in terms of affinity for all muscarinic subtypes. As supported by computational studies performed on the hM1 receptor, this substituent may contribute to stabilize the ligand within the binding site by favoring the formation of stable interactions between the cationic head of the ligand and the residue D105. The increase of steric bulk, obtained by replacing the methyl group with an ethyl (7 and 10) and especially a phenyl substituent (8 and 11), caused a marked decrease of mAChR affinity, demonstrating the crucial role played by the steric bulk of the 2-substituent in the mAChR interaction. The most intriguing result was obtained with the tertiary amine 9, which, surprisingly, showed two different pKi values for all mAChRs, with preferential subpicomolar affinities for the M1, M3, and M4 subtypes. Interestingly, biphasic curves were also observed with both the eutomer (S)-(-)-9 and the distomer (R)-( + )-9.

Screening of Mpro Protease (SARS-CoV-2) Covalent Inhibitors from an Anthocyanin-Rich Blueberry Extract Using an HRMS-Based Analytical Platform.

BACKGROUND: The viral main protease (Mpro) of SARS-CoV-2 has been recently proposed as a key target to inhibit virus replication in the host. Therefore, molecules that can bind the catalytic site of Mpro could be considered as potential drug candidates in the treatment of SARS-CoV-2 infections. Here we proposed the application of a state-of-the-art analytical platform which combines metabolomics and protein structure analysis to fish-out potential active compounds deriving from a natural matrix, i.e., a blueberry extract. METHODS: The experiments focus on finding MS covalent inhibitors of Mpro that contain in their structure a catechol/pyrogallol moiety capable of binding to the nucleophilic amino acids of the enzyme's catalytic site. RESULTS: Among the potential candidates identified, the delphinidin-3-glucoside showed the most promising results. Its antiviral activity has been confirmed in vitro on Vero E6 cells infected with SARS-CoV-2, showing a dose-dependent inhibitory effect almost comparable to the known Mpro inhibitor baicalin. The interaction of delphinidin-3-glucoside with the Mpro pocket observed was also evaluated by computational studies. CONCLUSIONS: The HRMS analytical platform described proved to be effective in identifying compounds that covalently bind Mpro and are active in the inhibition of SARS-CoV-2 replication, such as delphinidin-3-glucoside.

Synthesis, molecular docking and antibacterial activity of an oxadiazole-based lipoteichoic acid inhibitor and its metabolites.

Amongst drug resistant Gram-positive bacteria, Staphylococcus aureus is a pathogen of great concern as it is the leading cause of life-threatening nosocomial and community acquired infections which are often associated with implanted medical devices. The biosynthesis of lipotheicoic acid (LTA) by S. aureus has been recognized as a promising antibacterial target, owing its critical role in the growth and survival of Gram-positive bacteria. Here we report for the first time the chemical synthesis and characterisation of an oxadiazole based compound (1771), previously described as an inhibitor of LTA biosynthesis by targeting Lta synthase enzyme (LtaS). To investigate its controversial mode of action, we also performed molecular docking studies, which indicated that 1771 behaves as a competitive inhibitor against LtaS. We also synthesised and evaluated the antimicrobial activity of 1771 metabolites which we have identified from its decomposition in mouse serum, proving that the biological activity was caused by intact 1771.

Heterocyclic Compounds as Synthetic Tyrosinase Inhibitors: Recent Advances.

Tyrosinase is a copper-containing enzyme which is widely distributed in nature (e.g., bacteria, mammals, fungi) and involved in two consecutive steps of melanin biosynthesis. In humans, an excessive production of melanin can determine hyperpigmentation disorders as well as neurodegenerative processes in Parkinson's disease. The development of molecules able to inhibit the high activity of the enzyme remain a current topic in medicinal chemistry, because the inhibitors reported so far present several side effects. Heterocycle-bearing molecules are largely diffuse in this sense. Due to their importance as biologically active compounds, we decided to report a comprehensive review of synthetic tyrosinase inhibitors possessing heterocyclic moieties reported within the last five years. For the reader's convenience, we classified them as inhibitors of mushroom tyrosinase (Agaricus bisporus) and human tyrosinase.

Interaction of Aggregated Cationic Porphyrins with Human Serum Albumin.

The interaction of an equilibrium mixture of monomeric and aggregated cationic trans-5,15-bis(N-methylpyridinium-4-yl)-10,15-bis-diphenylporphine (t-H2Pagg) chloride salt with human serum albumin (HSA) has been investigated through UV/Vis absorption, fluorescence emission, circular dichroism and resonant light scattering techniques. The spectroscopic evidence reveals that both the monomeric t-H2Pagg and its aggregates bind instantaneously to HSA, leading to the formation of a tight adduct in which the porphyrin is encapsulated within the protein scaffold (S430) and to clusters of aggregated porphyrins in electrostatic interaction with the charged biomolecules. These latter species eventually interconvert into the final S430 species following pseudo-first-order kinetics. Molecular docking simulations have been performed to get some insights into the nature of the final adduct. Analogously to hemin bound to HSA, the obtained model supports favorable interactions of the porphyrin in the same 1B subdomain of the protein. Hydrophobic and van der Waals energy terms are the main contributions to the calculated ΔGbind value of -117.24 kcal/mol.

Ligand-Based Discovery of a Small Molecule as Inhibitor of α-Synuclein Amyloid Formation.

α-Synuclein (α-Syn) aggregates are implicated in Parkinson's disease (PD), so inhibitors of α-Syn aggregation have been intensively explored. It has been demonstrated that small molecules might be able to reduce α-Syn aggregation in fibrils, thus exerting neuroprotective effects in models of PD. To expand our knowledge about the structural requirements for blocking the recognition process into the oligomeric assembly of α-Syn aggregates, we performed a ligand-based virtual screening procedure using two well-known α-Syn aggregation inhibitors, SynuClean-D and ZPD-2, as query compounds. A collection of thirty-four compounds bearing distinct chemical functionalities and mutual chemical features were studied in a Th-T fluorescence test, thus identifying 5-(2,6-dinitro-4-(trifluoromethyl)benzyl)-1-methyl-1H-tetrazole (named MeSC-04) as a potent α-Syn amyloid formation inhibitor that demonstrated similar behavior when compared to SynuClean-D in the thioflavin-T-monitored kinetic assays, with both molecules reducing the number and size of amyloid fibrils, as evidenced by electron microscopy. Molecular modeling studies suggested the binding mode of MeSC-04 through the identification of putative druggable pockets on α-syn fibrils and a subsequent consensus docking methodology. Overall, this work could furnish new insights in the development of α-Syn amyloid inhibitors from synthetic sources.

Investigation on Hydrazonobenzenesulfonamides as Human Carbonic Anhydrase I, II, IX and XII Inhibitors.

A small series of hydrazonobenzenesulfonamides was designed, synthesized and studied for their human carbonic anhydrase (hCA) inhibitory activity. The synthesized compounds were evaluated against hCA I, II, IX and XII isoforms using acetazolamide (AAZ) as the standard inhibitor. Various hydrazonosulfonamide derivatives showed inhibitory activity at low nanomolar levels with selectivity against the cytosolic hCA II isoform, as well as the transmembrane, tumor-associated enzymes hCA IX and XII. The most potent and selective hydrazones 8, 9, 10, 11, 19 and 24 were docked into isoforms I, II, IX and XII to better understand their activity and selectivity for the different CA isoforms.

Exploration of the 2,3-dihydroisoindole pharmacophore for inhibition of the influenza virus PA endonuclease.

Seasonal influenza A and B viruses represent a global concern. Antiviral drugs are crucial to treat severe influenza in high-risk patients and prevent virus spread in case of a pandemic. The emergence of viruses showing drug resistance, in particular for the recently licensed polymerase inhibitor baloxavir marboxil, drives the need for developing alternative antivirals. The endonuclease activity residing in the N-terminal domain of the polymerase acidic protein (PAN) is crucial for viral RNA synthesis and a validated target for drug design. Its function can be impaired by molecules bearing a metal-binding pharmacophore (MBP) able to coordinate the two divalent metal ions in the active site. In the present work, the 2,3-dihydro-6,7-dihydroxy-1H-isoindol-1-one scaffold is explored for the inhibition of influenza virus PA endonuclease. The structure-activity relationship was analysed by modifying the substituents on the lipophilic moiety linked to the MBP. The new compounds exhibited nanomolar inhibitory activity in a FRET-based enzymatic assay, and a few compounds (15-17, 21) offered inhibition in the micromolar range, in a cell-based influenza virus polymerase assay. When investigated against a panel of PA-mutant forms, compound 17 was shown to retain full activity against the baloxavir-resistant I38T mutant. This was corroborated by docking studies providing insight into the binding mode of this novel class of PA inhibitors.

Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts.

The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents.

In Silico Identification of Potential Druggable Binding Sites on CIN85 SH3 Domain.

Protein-protein interactions (PPIs) play a pivotal role in the regulation of many physiological processes. The dysfunction of some PPIs interactions led to the alteration of different biological pathways causing various diseases including cancer. In this context, the inhibition of PPIs represents an attractive strategy for the design of new antitumoral agents. In recent years, computational approaches were successfully used to study the interactions between proteins, providing useful hints for the design of small molecules able to modulate PPIs. Targeting PPIs presents several challenges mainly due to the large and flat binding surface that lack the typical binding pockets of traditional drug targets. Despite these hurdles, substantial progress has been made in the last decade resulting in the identification of PPI modulators where some of them even found clinical use. This study focuses on MUC1-CIN85 PPI which is involved in the migration and invasion of cancer cells. Particularly, we investigated the presence of druggable binding sites on the CIN85 surface which provided new insights for the structure-based design of novel MUC1-CIN85 PPI inhibitors as anti-metastatic agents.

In Silico Strategy for Targeting the mTOR Kinase at Rapamycin Binding Site by Small Molecules.

Computer aided drug-design methods proved to be powerful tools for the identification of new therapeutic agents. We employed a structure-based workflow to identify new inhibitors targeting mTOR kinase at rapamycin binding site. By combining molecular dynamics (MD) simulation and pharmacophore modelling, a simplified structure-based pharmacophore hypothesis was built starting from the FKBP12-rapamycin-FRB ternary complex retrieved from RCSB Protein Data Bank (PDB code 1FAP). Then, the obtained model was used as filter to screen the ZINC biogenic compounds library, containing molecules derived from natural sources or natural-inspired compounds. The resulting hits were clustered according to their similarity; moreover, compounds showing the highest pharmacophore fit-score were chosen from each cluster. The selected molecules were subjected to docking studies to clarify their putative binding mode. The binding free energy of the obtained complexes was calculated by MM/GBSA method and the hits characterized by the lowest ΔGbind values were identified as potential mTOR inhibitors. Furthermore, the stability of the resulting complexes was studied by means of MD simulation which revealed that the selected compounds were able to form a stable ternary complex with FKBP12 and FRB domain, thus underlining their potential ability to inhibit mTOR with a rapamycin-like mechanism.

Discovery of a new potent inhibitor of mushroom tyrosinase (Agaricus bisporus) containing 4-(4-hydroxyphenyl)piperazin-1-yl moiety.

Tyrosinase (TYR, EC 1.14.18.1) plays a pivotal role in mammalian melanogenesis and enzymatic browning of plant-derived food. Therefore, tyrosinase inhibitors (TYRIs) can be of interest in cosmetics and pharmaceutical industries as depigmentation compounds as well as anti-browning agents. Starting from 4-benzylpiperidine derivatives that showed good inhibitory properties toward tyrosinase from Agaricus bisporus (TyM), we synthesized a new series of TYRIs named 3-(4-benzyl-1-piperidyl)-1-(4-phenylpiperazin-1-yl)propan-1-one and 2-(4-benzyl-1-piperidyl)-1-(4-phenylpiperazin-1-yl)ethanone derivatives. Among them, compound 4b proved to be the most potent inhibitor (IC50 = 3.80 µM) and it also showed a good antioxidant activity. These new data furnished additional information about the SAR for this class of TYRIs.

Rational design of small molecules able to inhibit α-synuclein amyloid aggregation for the treatment of Parkinson's disease.

Parkinson's disease is one of the most common neurodegenerative disorders in elderly age. One of the mechanisms involved in the neurodegeneration appears related to the aggregation of the presynaptic protein alpha synuclein (α-syn) into toxic oligomers and fibrils. To date, no highly effective treatment is currently available; therefore, there is an increasing interest in the search of new therapeutic tools. The modulation of α-syn aggregation represents an emergent and promising disease-modifying strategy for reducing or blocking the neurodegenerative process. Herein, by combining in silico and in vitro screenings we initially identified 3-(cinnamylsulfanyl)-5-(4-pyridinyl)-1,2,4-triazol-4-amine (3) as α-syn aggregation inhibitor that was then considered a promising hit for the further design of a new series of small molecules. Therefore, we rationally designed new hit-derivatives that were synthesised and evaluated by biological assays. Lastly, the binding mode of the newer inhibitors was predicted by docking studies.

Syntheses, reactivity, and biological applications of coumarins.

This comprehensive review, covering 2021-2023, explores the multifaceted chemical and pharmacological potential of coumarins, emphasizing their significance as versatile natural derivatives in medicinal chemistry. The synthesis and functionalization of coumarins have advanced with innovative strategies. This enabled the incorporation of diverse functional fragments or the construction of supplementary cyclic architectures, thereby the biological and physico-chemical properties of the compounds obtained were enhanced. The unique chemical structure of coumarine facilitates binding to various targets through hydrophobic interactions pi-stacking, hydrogen bonding, and dipole-dipole interactions. Therefore, this important scaffold exhibits promising applications in uncountable fields of medicinal chemistry (e.g., neurodegenerative diseases, cancer, inflammation).

Discovery of a New Class of 1-(4-Sulfamoylbenzoyl)piperidine-4-carboxamides as Human Carbonic Anhydrase Inhibitors.

A series of 1-(4-sulfamoylbenzoyl)piperidine-4-carboxamides deriving from substituted piperazines/benzylamines was designed, synthesized, and tested on human carbonic anhydrase (hCA). The inhibitory activity of the new sulfonamides was analyzed using acetazolamide (AAZ) as a standard inhibitor against hCA I, II, IX, and XII. Several sulfonamides showed both inhibitory activity at low nanomolar concentrations and selectivity against the cytosolic hCA II isoform, and the same trend was observed on the tumor-associated hCA IX and XII. The benzenesulfonamido carboxamides 11 and 15 were the most potent of the piperazino- and benzylamino-based series, respectively. Docking and molecular dynamics studies related the high selectivity of compound 11 toward the tumor-associated hCA isoforms to its capability to participate in favorable interactions within hCA IX and hCA XII active sites, whereas no such interactions were detected within both hCA I and hCA II isoforms.

Human carnosinases: A brief history, medicinal relevance, and in silico analyses.

Carnosine, an endogenous dipeptide, has been found to have a plethora of medicinal properties, such as antioxidant, antiageing, and chelating effects, but with one downside: a short half-life. Carnosinases and two hydrolytic enzymes, which remain enigmatic, are responsible for these features. Hence, here we emphasize why research is valuable for better understanding crucial concepts like ageing, neurodegradation, and cancerogenesis, given that inhibition of carnosinases might significantly prolong carnosine bioavailability and allow its further use in medicine. Herein, we explore the literature regarding carnosinases and present a short in silico analysis aimed at elucidating the possible recognition pattern between CN1 and its ligands.

Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities.

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented.

The VEGA web service: multipurpose online tools for molecular modelling and docking analyses.

The paper presents the VEGA Online web service, which includes a set of freely available tools deriving from the development of the VEGA suite of programs. In detail, the paper is focused on two tools: the VEGA Web Edition (WE) and the Score tool. The former is a versatile file format converter including relevant features for 2D/3D conversion, for surface mapping and for editing/preparing input files. The Score application allows rescoring docking poses and in particular includes the MLP Interactions Scores (MLPInS) for describing hydrophobic interactions. To the best of our knowledge, this web service is the only available resource by which one can calculate both the virtual log P of a given input molecule according to the MLP approach plus the corresponding MLP surface.

Ensemble of structure and ligand-based classification models for hERG liability profiling.

Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.