The VEGA suite of programs: an versatile platform for cheminformatics and drug design projects

Through-space H-F coupling in a series of 4-substituted-1H-1,2,3-triazoles

In the 1H-NMR spectra of a series of N-1 substituted 4-substituted-1H-1,2,3-triazoles that have been prepared, the lone heterocyclic ring hydrogen (H-5) appears as a singlet in all cases except those compounds that contain a 2-fluorophenyl moiety at Position 4. In those cases, H-5 is a doublet with J ~3.7 Hz. Based on computational chemistry results and geometric considerations, we attribute this splitting to through-space H-F coupling.

Preclinical alternative drug discovery programs for monogenic rare diseases. Should small molecules or gene therapy be used? The case of hereditary spastic paraplegias

Patients diagnosed with rare diseases and their and families search desperately to organize drug discovery campaigns. Alternative models that differ from default paradigms offer real opportunities. There are, however, no clear guidelines for the development of such models, which reduces success rates and raises costs. We address the main challenges in making the discovery of new preclinical treatments more accessible, using rare hereditary paraplegia as a paradigmatic case. First, we discuss the necessary expertise, and the patients' clinical and genetic data. Then, we revisit gene therapy, de novo drug development, and drug repurposing, discussing their applicability. Moreover, we explore a pool of recommended in silico tools for pathogenic variant and protein structure prediction, virtual screening, and experimental validation methods, discussing their strengths and weaknesses. Finally, we focus on successful case applications.

Thermodynamic Details of Pinholin S2168 Activation Revealed Using Alchemical Free Energy Simulations

Pinholin S2168 is a viral integral membrane protein whose function is to form nanoscopic "pinholes" in bacterial cell membranes to induce cell lysis as part of the viral replication cycle. Pinholin can transition from an inactive to an active conformation by exposing a transmembrane domain (TMD1) to the extracellular fluid. Upon activation, several copies of the protein assemble via interactions among a second transmembrane domain (TMD2) to form a single pore, thus hastening cell lysis and viral escape. The following experiments provide conformational descriptors of pinholin in active and inactive states and elucidate the molecular driving forces that control pinholin activity. In the present study, molecular dynamics (MD) simulations have been used to refine experimentally derived conformational descriptors into an atomistically detailed model of irsS2168, an antiholin mutant. To provide additional details about the thermodynamics of pinholin activation and to overcome large intrinsic kinetic barriers to activation, alchemical free energy simulations have been conducted. Alchemical mutations reveal the change in folding free energy upon mutation. The results suggest that alchemical mutations are an effective tool to rationalize experimental observations and predict the effects of site mutations on conformational states for proteins integrated into lipid bilayers. S16F, A17Q, A17Q+G21Q, and A17Q+G21Q+G14Q mutants reveal how changes in hydrophilicity and disruption of the glycine zipper motif influence pinholin's thermodynamic equilibrium, favoring the active conformation. These findings align with experimental observations from DEER spectroscopy, demonstrating that mutations increasing the hydrophilicity of TMD1 promote activation by making TMD1 more likely to exit the membrane and enter the extracellular fluid.

Growth of complete ammonia oxidizers on guanidine

Guanidine is a chemically stable nitrogen compound that is excreted in human urine and is widely used in manufacturing of plastics, as a flame retardant and as a component of propellants, and is well known as a protein denaturant in biochemistry1-3. Guanidine occurs widely in nature and is used by several microorganisms as a nitrogen source, but microorganisms growing on guanidine as the only substrate have not yet been identified. Here we show that the complete ammonia oxidizer (comammox) Nitrospira inopinata and probably most other comammox microorganisms can grow on guanidine as the sole source of energy, reductant and nitrogen. Proteomics, enzyme kinetics and the crystal structure of a N. inopinata guanidinase homologue demonstrated that it is a bona fide guanidinase. Incubation experiments with comammox-containing agricultural soil and wastewater treatment plant microbiomes suggested that guanidine serves as substrate for nitrification in the environment. The identification of guanidine as a growth substrate for comammox shows an unexpected niche of these globally important nitrifiers and offers opportunities for their isolation.

Staphylococcus aureus major cell division protein FtsZ assembly is inhibited by silibinin, a natural flavonolignan that also blocked bacterial growth and biofilm formation

The bacterial cell division protein FtsZ has been considered a potential therapeutic target due to its rapid treadmilling that induces cellular wall construction in bacteria. The current study discovered a novel antimicrobial compound, silibinin, a natural flavonolignan and its impact on the recombinant S. aureus FtsZ (SaFtsZ). Silibinin inhibited S. aureus Newman growth in a dose-dependent manner. The IC50 and MIC values for silibinin were 75 μM and 200 μM, respectively. It had no cytotoxicity against HEK293 cells in vitro. Silibinin also enlarged the bacterial cell morphology by ∼40 folds and showed antibiofilm property. It perturbed the S. aureus membrane potential both at IC50 conc. and at MIC conc. Further, it inhibited both the polymerization and GTPase activity of SaFtsZ. It did not inhibit tubulin assembly, a eukaryotic FtsZ homolog. A fluorescence quenching study yielded the Kd value for SaFtsZ-Silibinin interaction and binding stoichiometry 0.857 ± 0.188 μM and 1:1, respectively. Both in silico study and competition assay indicated that silibinin binds at the GTP binding site on SaFtsZ. The Ki value for the silibinin-mediated inhibition of SaFtsZ was 8.8 μM. Therefore, these findings have comprehensively shown the antimicrobial behavior of silibinin on S. aureus Newman cells targeting SaFtsZ.

An improved dataset of force fields, electronic and physicochemical descriptors of metabolic substrates

In silico prediction of xenobiotic metabolism is an important strategy to accelerate the drug discovery process, as candidate compounds often fail in clinical phases due to their poor pharmacokinetic profiles. Here we present MetaQM, a dataset of quantum-mechanical (QM) optimized metabolic substrates, including force field parameters, electronic and physicochemical properties. MetaQM comprises 2054 metabolic substrates extracted from the MetaQSAR database. We provide QM-optimized geometries, General Amber Force Field (FF) parameters for all studied molecules, and an extended set of structural and physicochemical descriptors as calculated by DFT and PM7 methods. The generated data can be used in different types of analysis. FF parameters can be applied to perform classical molecular mechanics calculations as exemplified by the validating molecular dynamics simulations reported here. The calculated descriptors can represent input features for developing improved predictive models for metabolism and drug design, as exemplified in this work. Finally, the QM-optimized molecular structures are valuable starting points for both ligand- and structure-based analyses such as pharmacophore mapping and docking simulations.

Synthesis and Antimicrobial Activity of Newly Synthesized Nicotinamides

Antioxidants are promising compounds with antimicrobial activity against drug-resistant pathogens, especially when combined with conventional antimicrobials. Our study aimed to characterize the structure of nicotinamides synthesized from nicotinic acid and thiocarbohydrazones and to evaluate their antibacterial and antifungal activity. Seven nicotinic acid hydrazides (NC 1-7) were synthesized using mono-thiocarbohydrazones with hydroxyl group substituents, along with quinolone, phenolic, and pyridine rings known for their antimicrobial activity. The in vitro antimicrobial activity of NC 1-7, at concentrations ranging from 0.001 to 1 mM, was tested against Staphylococcus aureus (ATCC 6538), Enterococcus faecalis (ATCC 29212), Pseudomonas aeruginosa (ATCC 27853), Klebsiella pneumoniae (NCIMB 9111), and Candida albicans (ATCC 24433) using the broth microdilution method per EUCAST 2024 guidelines. Microorganism survival percentages were calculated based on optical density, and target fishing using the PharmMapper database identified potential molecular targets. The results showed that P. aeruginosa was most susceptible to the compounds, while C. albicans was the least susceptible. NC 3 significantly inhibited P. aeruginosa and K. pneumoniae growth at 0.016 mM, while higher concentrations were required for S. aureus, E. faecalis, and C. albicans. NC 5 was most effective against gram-positive bacteria at 0.03 mM. Only NC 4 completely inhibited C. albicans below 1 mM. NC 3, with the lowest concentration for 50% growth inhibition (0.016-0.064 mM), showed promising antibacterial potential against specific AMR-related proteins (bleomycin resistance protein, HTH-type transcriptional regulator QacR, and streptogramin A acetyltransferase), suggesting that this class of compounds could enhance or restore the activity of established antibiotics.

Controlling Chirogenic Effects in Porphyrin Based Supramolecular Systems: Theoretical Analysis Versus Experimental Observations

Electronic circular dichroism (ECD) spectroscopy is a widely employed method for studying chiral analysis, requiring the presence of a chromophore close to a chiral centre. Porphyrinoids are found to be one of the best chromophoric systems serving for this purpose and enabling the application of ECD spectroscopy for chirality determination across diverse classes of organic compounds. Consequently, it is crucial to understand the induction mechanisms of ECD in the porphyrin-based complexes. The present study explores systematically the influence of secondary chromophores, bonded to an achiral zinc porphyrin or to chiral guest molecules, on the B-region of ECD spectra using the time-dependent density functional theory (TD-DFT) calculations. The study analyses the impact of change in both the conformation of achiral porphyrin (host) and change in position and conformation of chiral organic molecule (guest) on the B-band of ECD spectra (energy, intensity, sign of Cotton effect). Finally, conclusions made on model complexes are applied to published experimental data, contributing to a deeper understanding of various factors influencing ECD spectra in chiral systems. In addition, a computer program aimed to help rationalise ECD spectra by visualizing corresponding orbital energies, rotatory strengths, electric and magnetic transition moments, and angles between them, is presented.

A novel source of biologically active compounds - The leaves of Serbian herbaceous peonies

In order to gain further insight into how various extraction techniques (maceration, microwave-, and ultrasound-assisted extractions) affect the chemical profile and biological activities of leaf extracts from Paeonia tenuifolia L., Paeonia peregrina Mill., and Paeonia officinalis L., this research was performed. The targeted chemical characterization of the extracts was achieved using the Ultra-High-Performance-Liquid-Chromatography-Linear-Trap-Mass-Spectrometry OrbiTrap instrumental technique, while Fourier Transform Infrared Spectroscopy was conducted to investigate the structural properties of the examined leaf extracts. According to the results, the species P. officinalis, Božurna locality as the origin of the plant material, and microwave-assisted extraction produced the maximum polyphenol yield, (491.9 ± 2.7 mg gallic acid equivalent (GAE)/mL). The ethanolic extracts exhibited moderate antioxidant activity as evaluated by DPPH (2,2-diphenyl-1-picrylhydrazyl) and phosphomolybdenum tests. With MIC values of 0.125 mg/mL, the leaf extracts produced by ultrasound-assisted extraction and maceration (Deliblato sands and Bogovo gumno) had the best antibacterial activity against Pseudomonas aeruginosa and Salmonella Typhimurium. Ultrasound-assisted extraction has proven to produce the most effective antimicrobial agents. Inhibitory potential towards glucosidase, amylase, cholinesterases, and tyrosinase was evaluated in enzyme inhibition assays and molecular docking simulations. Results show that leaves of P. tenuifolia L. obtained by ultrasound-assisted extraction had the highest acetylcholinesterase and butyrylcholinesterase inhibitory activity. Namely, the complexity of the polyphenol structures, the extraction method, the used locality, and the different mechanisms of the reactions between bioactives from leaf extracts and other components (free radicals, microorganisms, and enzymes) are the main factors that influence the results of the antioxidant tests, as well as the antibacterial and enzyme-inhibitory activities of the extracts. Hydroxymethyl-phenyl pentosyl-hexoside and acetyl-hydroxyphenyl-hexoside were the first time identified in the leaf extract of the Paeonia species. Due to their proven biological activities and the confirmed existence of bioactive compounds, leaf extracts may find use in foodstuffs, functional foods, and pharmaceutical products.

3-O-Substituted Quercetin: an Antibiotic-Potentiating Agent against Multidrug-Resistant Gram-Negative Enterobacteriaceae through Simultaneous Inhibition of Efflux Pump and Broad-Spectrum Carbapenemases

The discovery of safe and efficient inhibitors against efflux pumps as well as metallo-β-lactamases (MBL) is one of the main challenges in the development of multidrug-resistant (MDR) reversal agents which can be utilized in the treatment of carbapenem-resistant Gram-negative bacteria. In this study, we have identified that introduction of an ethylene-linked sterically demanding group at the 3-OH position of the previously reported MDR reversal agent di-F-Q endows the resulting compounds with hereto unknown multitarget inhibitory activity against both efflux pumps and broad-spectrum β-lactamases including difficult-to-inhibit MBLs. A molecular docking study of the multitarget inhibitors against efflux pump, as well as various classes of β-lactamases, revealed that the 3-O-alkyl substituents occupy the novel binding sites in efflux pumps as well as carbapenemases. Not surprisingly, the multitarget inhibitors rescued the antibiotic activity of a carbapenem antibiotic, meropenem (MEM), in NDM-1 (New Delhi Metallo-β-lactamase-1)-producing carbapenem-resistant Enterobacteriaceae (CRE), and they reduced MICs of MEM more than four-fold (synergistic effect) in 8-9 out of 14 clinical strains. The antibiotic-potentiating activity of the multitarget inhibitors was also demonstrated in CRE-infected mouse model. Taken together, these results suggest that combining inhibitory activity against two critical targets in MDR Gram-negative bacteria, efflux pumps, and β-lactamases, in one molecule is possible, and the multitarget inhibitors may provide new avenues for the discovery of safe and efficient MDR reversal agents.

Phytochemical Analysis, Biological Activities, and Molecular Docking Studies of Root Extracts from Paeonia Species in Serbia

Without being aware of their chemical composition, many cultures have used herbaceous peony roots for medicinal purposes. Modern phytopreparations intended for use in human therapy require specific knowledge about the chemistry of peony roots and their biological activities. In this study, ethanol-water extracts were prepared by maceration and microwave- and ultrasound-assisted extractions (MAE and UAE, respectively) in order to obtain bioactive molecules from the roots of Paeonia tenuifolia L., Paeonia peregrina Mill., and Paeonia officinalis L. wild growing in Serbia. Chemical characterization; polyphenol and flavonoid content; antioxidant, multianti-enzymatic, and antibacterial activities of extracts; and in vitro gastrointestinal digestion (GID) of hot water extracts were performed. The strongest anti-cholinesterase activity was observed in PT extracts. The highest anti-ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) radical potential was observed in PP extracts, whereas against DPPH (2,2-diphenyl-1-picrylhydrazyl radicals), the best results were achieved with PO extracts. Regarding antibacterial activity, extracts were strongly potent against Bacillus cereus. A molecular docking simulation was conducted to gather insights into the binding affinity and interactions of polyphenols and other Paeonia-specific molecules in the active sites of tested enzymes. In vitro GID of Paeonia teas showed a different recovery and behavior of the individual bioactives, with an increased recovery of methyl gallate and digallate and a decreased recovery of paeoniflorin and its derivatives. PT (Gulenovci) and PP (Pirot) extracts obtained by UAE and M were more efficient in the majority of the bioactivity assays. This study represents an initial step toward the possible application of Paeonia root extracts in pharmacy, medicine, and food technologies.

Designing the structure of cationic star-shaped trimeric surfactants most active in micelle formation using molecular connectivity indices

A model expressing the relationship between the logarithm of critical micelle concentration of cationic star-shaped trimeric surfactants and topological indices was obtained using only molecular connectivity indices. Based on the obtained model, the exemplary compound most active in micelle formation was designed. The analysis of the influence of various structural factors on the value of the critical micelle concentration was supported by atomic charge studies. The obtained model will be used to design new star-shaped trimeric surfactants that are more active in formation of micelle as well as to predict their critical micelle concentration.

Will we ever be able to accurately predict solubility?

Accurate prediction of thermodynamic solubility by machine learning remains a challenge. Recent models often display good performances, but their reliability may be deceiving when used prospectively. This study investigates the origins of these discrepancies, following three directions: a historical perspective, an analysis of the aqueous solubility dataverse and data quality. We investigated over 20 years of published solubility datasets and models, highlighting overlooked datasets and the overlaps between popular sets. We benchmarked recently published models on a novel curated solubility dataset and report poor performances. We also propose a workflow to cure aqueous solubility data aiming at producing useful models for bench chemist. Our results demonstrate that some state-of-the-art models are not ready for public usage because they lack a well-defined applicability domain and overlook historical data sources. We report the impact of factors influencing the utility of the models: interlaboratory standard deviation, ionic state of the solute and data sources. The herein obtained models, and quality-assessed datasets are publicly available.

Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data

The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.

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.

"DompeKeys": a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable. To meet additional needs, such descriptors should also be interpretable by medicinal chemists, and suitable for indexing databases with trillions of compounds. To this end, we developed-as integral part of EXSCALATE, Dompé's end-to-end drug discovery platform-the DompeKeys (DK), a new substructure-based descriptor set, which encodes the chemical features that characterize compounds of pharmaceutical interest. DK represent an exhaustive collection of curated SMARTS strings, defining chemical features at different levels of complexity, from specific functional groups and structural patterns to simpler pharmacophoric points, corresponding to a network of hierarchically interconnected substructures. Because of their extended and hierarchical structure, DK can be used, with good performance, in different kinds of applications. In particular, we demonstrate how they are very well suited for effective mapping of chemical space, as well as substructure search and virtual screening. Notably, the incorporation of DK yields highly performing machine learning models for the prediction of both compounds' activity and metabolic reaction occurrence. The protocol to generate the DK is freely available at https://dompekeys.exscalate.eu and is fully integrated with the Molecular Anatomy protocol for the generation and analysis of hierarchically interconnected molecular scaffolds and frameworks, thus providing a comprehensive and flexible tool for drug design applications.

Computational design of anti-cancer peptides tailored to target specific tumor markers

Anti-cancer peptides (ACPs) are short peptides known for their ability to inhibit tumor cell proliferation, migration, and the formation of tumor blood vessels. In this study, we designed ACPs to target receptors often overexpressed in cancer using a systematic in silico approach. Three target receptors (CXCR1, DcR3, and OPG) were selected for their significant roles in cancer pathogenesis and tumor cell proliferation. Our peptide design strategy involved identifying interacting residues (IR) of these receptors, with their natural ligands serving as a reference for designing peptides specific to each receptor. The natural ligands of these receptors, including IL8 for CXCR1, TL1A for DcR3, and RANKL for OPG, were identified from the literature. Using the identified interacting residues (IR), we generated a peptide library through simple permutation and predicted the structure of each peptide. All peptides were analyzed using the web-based prediction server for Anticancer peptides, AntiCP. Docking simulations were then conducted to analyze the binding efficiencies of peptides with their respective target receptors, using VEGA ZZ and Chimera for interaction analysis. Our analysis identified HPKFIKELR as the interacting residues (IR) of CXCR-IL8. For DcR3, we utilized three domains from TL1A (TDSYPEP, TKEDKTF, LGLAFTK) as templates, along with two regions (SIKIPSS and PDQDATYP) from RANKL, to generate a library of peptide analogs. Subsequently, peptides for each receptor were shortlisted based on their predicted anticancer properties as determined by AntiCP and were subjected to docking analysis. After docking, peptides that exhibited the least binding energy were further analyzed for their detailed interaction with their respective receptors. Among these, peptides C9 (HPKFELY) and C7 (HPKFEWL) for CXCR1, peptides D6 (ADSYPQP) and D18 (AFSYPFP) for DcR3, and peptides P19 (PDTYPQDP) and p16 (PDQDATYP) for OPG, demonstrated the highest affinity and stronger interactions compared to the other peptides. Although in silico predictions indicated a favorable binding affinity of the designed peptides with target receptors, further experimental validation is essential to confirm their binding affinity, stability and pharmacokinetic characteristics.

New Alpha9 nAChR Ligands Based on a 5-(Quinuclidin-3-ylmethyl)-1,2,4-oxadiazole Scaffold

Several lines of evidence have indicated that nicotinic acetylcholine receptors (nAChR) that contain α9 subunits, probably in combination with α10 subunits, may be valuable targets for the management of pain associated with inflammatory diseases through a cholinergic anti-inflammatory system (CAS), which has also been associated with α7 nAChR. Both α7- and α9-containing neuronal nAChR can be pharmacologically distinguished from the high-affinity nicotinic receptors of the brain by their sensitivity to α-bungarotoxin, but in other ways, they have quite distinct pharmacological profiles. The early association of α7 with CAS led to the development of numerous new ligands, variously characterized as α7 agonists, partial agonists, or silent agonists that desensitized α7 receptors without activation. Subsequent reinvestigation of one such family of α7 ligands based on an N,N-diethyl-N'-phenylpiperazine scaffold led to the identification of potent agonists and antagonists for α9. In this paper, we characterize the α9/α10 activity of a series of compounds based on a 5-(quinuclidin-3-ylmethyl)-1,2,4-oxadiazole (QMO) scaffold and identify two new potent ligands of α9, QMO-28, an agonist, and QMO-17, an antagonist. We separated the stereoisomers of these compounds to identify the most potent agonist and discovered that only the 3R isomer of QMO-17 was an α9 antagonist, permitting an in silico model of α9 antagonism to be developed. The α9 activity of these compounds was confirmed to be potentially useful for CAS management of inflammatory pain in cell-based assays of cytokine release.

Unraveling the parahormetic mechanism underlying the health-protecting effects of grapeseed procyanidins

Proanthocyanidins (PACs), the predominant constituents within Grape Seed Extract (GSE), are intricate compounds composed of interconnected flavan-3-ol units. Renowned for their health-affirming properties, PACs offer a shield against a spectrum of inflammation associated diseases, such as diabetes, obesity, degenerations and possibly cancer. While monomeric and dimeric PACs undergo some absorption within the gastrointestinal tract, their larger oligomeric and polymeric counterparts are not bioavailable. However, higher molecular weight PACs engage with the colonic microbiota, fostering the production of bioavailable metabolites that undergo metabolic processes, culminating in the emergence of bioactive agents capable of modulating physiological processes. Within this investigation, a GSE enriched with polymeric PACs was employed to explore in detail their impact. Through comprehensive analysis, the present study unequivocally verified the gastrointestinal-mediated transformation of medium to high molecular weight polymeric PACs, thereby establishing the bioaccessibility of a principal catabolite termed 5-(3',4'-dihydroxyphenyl)-γ-valerolactone (VL). Notably, our findings, encompassing cell biology, chemistry and proteomics, converge to the proposal of the notion of the capacity of VL to activate, upon oxidation to the corresponding quinone, the nuclear factor E2-related factor 2 (Nrf2) pathway-an intricate process that incites cellular defenses and mitigates stress-induced responses, such as a challenge brought by TNFα. This mechanistic paradigm seamlessly aligns with the concept of para-hormesis, ultimately orchestrating the resilience to stress and the preservation of cellular redox equilibrium and homeostasis as benchmarks of health.

Energetics of β-lactoglobulin-flavor compounds interactions

Interaction of bovine β-lactoglobulin (BLG) with several flavor compounds (FC) (2-methylpyrazine, vanillin, 2-acetylpyridine, 2- and 3-acetylthiophene, methyl isoamyl ketone, heptanone, octanone, and nonanone) was studied by high-sensitivity differential scanning calorimetry. The denaturation temperature, enthalpy, and heat capacity increment were determined at different FC concentrations. It was found that the denaturation temperature and heat capacity increment do not depend on the FC concentration, while the denaturation enthalpy decreases linearly with the FC concentration. These thermodynamic effects disclose the preferential FC binding to the unfolded form of BLG. By the obtained calorimetric data, the free energies of FC binding vs. the FC concentrations were calculated. These dependences were shown to be linear. Their slope relates closely to the overall FC affinity for the unfolded BLG in terms of the Langmuir binding model. The overall BLG affinity for FC varies from 20 M-1 (2-methylpyrazine) up to 360 M-1(nonanone). The maximal stoichiometry of the BLG-FC complexes was roughly estimated as a ratio of the length of the unfolded BLG to the molecular length of FC. Using these estimates, the apparent BLG-FC binding constants were determined. They are in the range of 0.3-8.0 M-1 and correlated strictly with the FC lipophilicity descriptor (logP).

Potentiation of Antibiotic Activity of Aztreonam against Metallo-β-Lactamase-Producing Multidrug-Resistant Pseudomonas aeruginosa by 3-O-Substituted Difluoroquercetin Derivatives

The combination of aztreonam (ATM) and ceftazidime-avibactam (CAZ-AVI; CZA) has shown therapeutic potential against serine-β-lactamase (SBL)- and metallo-β-lactamase (MBL)-producing Enterobacterales. However, the ability of CZA to restore the antibiotic activity of ATM is severely limited in MBL-producing multidrug-resistant (MDR) Pseudomonas aeruginosa strains because of the myriad of intrinsic and acquired resistance mechanisms associated with this pathogen. We reasoned that the simultaneous inhibition of multiple targets associated with multidrug resistance mechanisms may potentiate the antibiotic activity of ATM against MBL-producing P. aeruginosa. During a search for the multitarget inhibitors through a molecular docking study, we discovered that di-F-Q, the previously reported efflux pump inhibitor of MDR P. aeruginosa, binds to the active sites of the efflux pump (MexB), as well as various β-lactamases, and these sites are open to the 3-O-position of di-F-Q. The 3-O-substituted di-F-Q derivatives were thus synthesized and showed hereto unknown multitarget MDR inhibitory activity against various ATM-hydrolyzing β-lactamases (AmpC, KPC, and New Delhi metallo-β-lactamase (NDM)) and the efflux pump of P. aeruginosa, presumably by forming additional hydrophobic contacts with the targets. The multitarget MDR inhibitor 27 effectively potentiated the antimicrobial activity of ATM and reduced the MIC of ATM more than four-fold in 19 out of 21 MBL-producing P. aeruginosa clinical strains, including the NDM-producing strains which were highly resistant to various combinations of ATM with β-lactamase inhibitors and/or efflux pump inhibitors. Our findings suggest that the simultaneous inhibition of multiple MDR targets might provide new avenues for the discovery of safe and efficient MDR reversal agents which can be used in combination with ATM against MBL-producing MDR P. aeruginosa.

Curated mode-of-action data and effect concentrations for chemicals relevant for the aquatic environment

Chemicals in the aquatic environment can be harmful to organisms and ecosystems. Knowledge on effect concentrations as well as on mechanisms and modes of interaction with biological molecules and signaling pathways is necessary to perform chemical risk assessment and identify toxic compounds. To this end, we developed criteria and a pipeline for harvesting and summarizing effect concentrations from the US ECOTOX database for the three aquatic species groups algae, crustaceans, and fish and researched the modes of action of more than 3,300 environmentally relevant chemicals in literature and databases. We provide a curated dataset ready to be used for risk assessment based on monitoring data and the first comprehensive collection and categorization of modes of action of environmental chemicals. Authorities, regulators, and scientists can use this data for the grouping of chemicals, the establishment of meaningful assessment groups, and the development of in vitro and in silico approaches for chemical testing and assessment.

Evaluation of in vitro SARS-CoV-2 inactivation by a new quaternary ammonium compound: Bromiphen bromide

The pneumonia (COVID-19) outbreak caused by the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which unpredictably exploded in late December of 2019 has stressed the importance of being able to control potential pathogens with the aim of limiting their spread. Although vaccines are well known as a powerful tool for ensuring public health and controlling the pandemic, disinfection and hygiene habits remain crucial to prevent infection from spreading and maintain the barrier, especially when the microorganism can persist and survive on textiles, surfaces, and medical devices. During the coronavirus disease pandemic, around half of the disinfectants authorized by the US Environmental Protection Agency contained quaternary ammonium compounds (QACs); their effectiveness had not been proven. Herein, the in vitro SARS-CoV-2 inactivation by p-bromodomiphen bromide, namely bromiphen (BRO), a new, potent, and fast-acting QAC is reported. This study demonstrates that BRO, with a dose as low as 0.02%, can completely inhibit SARS-CoV-2 replication in just 30 s. Its virucidal activity was 10- and 100-fold more robust compared to other commercially available QACs, namely domiphen bromide and benzalkonium chloride. The critical micellar concentration and the molecular lipophilicity potential surface area support the relevance of the lipophilic nature of these molecules for their activity.

Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative

Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction. In detail, the docking simulations submitted to the MEDIATE initiative are utilized to predict the viral targets involved in the hits retrieved by a recently published cytopathic screening. Multiple docking results are combined by the EFO approach to develop target-specific consensus models. The combination of multiple docking simulations enhances the performances of the developed consensus models (average increases in EF1% value of 40% and 25% when combining three and two docking runs, respectively). These models are able to propose reliable targets for about half of the retrieved hits (31 out of 59). Thus, the study emphasizes that docking simulations might be effective in target identification and provide a convincing validation for the collaborative strategies that inspire the MEDIATE initiative. Disappointingly, cross-target and cross-program correlations suggest that common scoring functions are not specific enough for the simulated target.

Investigation of the Potential of Selected Food-Derived Antioxidants to Bind and Stabilise the Bioactive Blue Protein C-Phycocyanin from Cyanobacteria Spirulina

Blue C-phycocyanin (C-PC), the major Spirulina protein with innumerable health-promoting benefits, is an attractive colourant and food supplement. A crucial obstacle to its more extensive use is its relatively low stability. This study aimed to screen various food-derived ligands for their ability to bind and stabilise C-PC, utilising spectroscopic techniques and molecular docking. Among twelve examined ligands, the protein fluorescence quenching revealed that only quercetin, coenzyme Q10 and resveratrol had a moderate affinity to C-PC (Ka of 2.2 to 3.7 × 105 M-1). Docking revealed these three ligands bind more strongly to the C-PC hexamer than the trimer, with the binding sites located at the interface of two (αβ)3 trimers. UV/VIS absorption spectroscopy demonstrated the changes in the C-PC absorption spectra in a complex with quercetin and resveratrol compared to the spectra of free protein and ligands. Selected ligands did not affect the secondary structure content, but they induced changes in the tertiary protein structure in the CD study. A fluorescence-based thermal stability assay demonstrated quercetin and coenzyme Q10 increased the C-PC melting point by nearly 5 °C. Our study identified food-derived ligands that interact with C-PC and improve its thermal stability, indicating their potential as stabilising agents for C-PC in the food industry.

Discovery of Inhibitory Fragments That Selectively Target Spire2-FMN2 Interaction

Here, we report the fragment-based drug discovery of potent and selective fragments that disrupt the Spire2-FMN2 but not the Spire1-FMN2 interaction. Hit fragments were identified in a differential scanning fluorimetry-based screen of an in-house library of 755 compounds and subsequently validated in multiple orthogonal biophysical assays, including fluorescence polarization, microscale thermophoresis, and 1H-15N HSQC nuclear magnetic resonance. Extensive structure-activity relationships combined with molecular docking followed by chemical optimization led to the discovery of compound 13, which exhibits micromolar potency and high ligand efficiency (LE = 0.38). Therefore, this fragment represents a validated starting point for the future development of selective chemical probes targeting the Spire2-FMN2 interaction.

Molecular Dynamics and Docking Simulations of Homologous RsmE Methyltransferases Hints at a General Mechanism for Substrate Release upon Uridine Methylation on 16S rRNA

In this study, molecular dynamics (MD) and docking simulations were carried out on the crystal structure of Neisseria Gonorrhoeae RsmE aiming at free energy of binding estimation (ΔGbinding) of the methyl transfer substrate S-adenosylmethionine (SAM), as well as its homocysteine precursor S-adenosylhomocysteine (SAH). The mechanistic insight gained was generalized in view of existing homology to two other crystal structures of RsmE from Escherichia coli and Aquifex aeolicus. As a proof of concept, the crystal poses of SAM and SAH were reproduced reflecting a more general pattern of molecular interaction for bacterial RsmEs. Our results suggest that a distinct set of conserved residues on loop segments between β12, α6, and Met169 are interacting with SAM and SAH across these bacterial methyltransferases. Comparing molecular movements over time (MD trajectories) between Neisseria gonorrhoeae RsmE alone or in the presence of SAH revealed a hitherto unknown gatekeeper mechanism by two isoleucine residues, Ile171 and Ile219. The proposed gating allows switching from an open to a closed state, mimicking a double latch lock. Additionally, two key residues, Arg221 and Thr222, were identified to assist the exit mechanism of SAH, which could not be observed in the crystal structures. To the best of our knowledge, this study describes for the first time a general catalytic mechanism of bacterial RsmE on theoretical ground.

Improved Antibacterial Activity of 1,3,4-Oxadiazole-Based Compounds That Restrict Staphylococcus aureus Growth Independent of LtaS Function

The lipoteichoic acid (LTA) biosynthesis pathway has emerged as a promising antimicrobial therapeutic target. Previous studies identified the 1,3,4 oxadiazole compound 1771 as an LTA inhibitor with activity against Gram-positive pathogens. We have succeeded in making six 1771 derivatives and, through subsequent hit validation, identified the incorporation of a pentafluorosulfanyl substituent as central in enhancing activity. Our newly described derivative, compound 13, showed a 16- to 32-fold increase in activity compared to 1771 when tested against a cohort of multidrug-resistant Staphylococcus aureus strains while simultaneously exhibiting an improved toxicity profile against mammalian cells. Molecular techniques were employed in which the assumed target, lipoteichoic acid synthase (LtaS), was both deleted and overexpressed. Neither deletion nor overexpression of LtaS altered 1771 or compound 13 susceptibility; however, overexpression of LtaS increased the MIC of Congo red, a previously identified LtaS inhibitor. These data were further supported by comparing the docking poses of 1771 and derivatives in the LtaS active site, which indicated the possibility of an additional target(s). Finally, we show that both 1771 and compound 13 have activity that is independent of LtaS, extending to cover Gram-negative species if the outer membrane is first permeabilized, challenging the classification that these compounds are strict LtaS inhibitors.

Structure of human TRPM8 channel

TRPM8 is a non-selective cation channel permeable to both monovalent and divalent cations that is activated by multiple factors, such as temperature, voltage, pressure, and changes in osmolality. It is a therapeutic target for anticancer drug development, and its modulators can be utilized for several pathological conditions. Here, we present a cryo-electron microscopy structure of a human TRPM8 channel in the closed state that was solved at 2.7 Å resolution. Our structure comprises the most complete model of the N-terminal pre-melastatin homology region. We also visualized several lipids that are bound by the protein and modeled how the human channel interacts with icilin. Analyses of pore helices in available TRPM structures showed that all these structures can be grouped into different closed, desensitized and open state conformations based on the register of the pore helix S6 which positions particular amino acid residues at the channel constriction.

Screening Campaign and Docking Investigations in Identifying New Hit Compounds as Inhibitors of Human Carbonic Anhydrases Expressed In Tumour Cells

The tumor-expressed human carbonic anhydrase (hCA) isoforms hCA IX and hCA XII have been extensively studied to develop anticancer agents targeting solid tumors in combined therapy. These CA  isoforms are considered key factors in controlling tumor microenvironment (TME) of cancer lines that develop high metastatic activity. Herein, we report the discovery of potent hCA IX/hCA XII inhibitors that were disclosed through a screening campaign on an in-house collection of arylsulfonamides preliminary tested toward other hCAs. Among them, the N-(4-sulfamoylphenyl)naphthalene-2-carboxamide (12) and N-(4-sulfamoylphenyl)-3,4-dihydroisoquinoline-2(1H)-carbothioamide (15) proved to be the most intriguing hCA IX/hCA XII inhibitors displaying favourable selectivity ratios over widespread hCA I and hCA II isoforms. To explore their binding mode, we conducted docking studies that described the poses of the best inhibitors in the catalytic site of hCA IX and hCA XII, thus suggesting the privileged pattern of interactions. These structural findings might further improve the knowledge for a successful identification of new sulfonamides as adjuvant agents in cancer management.

Arylureidoaurones: Synthesis, in vitro α-glucosidase, and α-amylase inhibition activity

Because of the colossal global burden of diabetes, there is an urgent need for more effective and safer drugs. We designed and synthesized a new series of aurone derivatives possessing phenylureido or bis-phenylureido moieties as α-glucosidase and α-amylase inhibitors. Most of the synthesized phenylureidoaurones have demonstrated superior inhibition activities (IC50s of 9.6-339.9 μM) against α-glucosidase relative to acarbose (IC50 = 750.0 μM) as the reference drug. Substitution of aurone analogues with two phenylureido substituents at the 5-position of the benzofuranone moiety and the 3' or 4' positions of the 2-phenyl ring resulted in compounds with almost 120-180 times more potent inhibitory activities than acarbose. The aurone analogue possessing two phenylureido substitutions at 5 and 4' positions (13) showed the highest inhibition activity with an IC50 of 4.2 ± 0.1 μM. Kinetic studies suggested their inhibition mode to be competitive. We also investigated the binding mode of the most potent compounds using the consensually docked 4D-QSAR methodology. Furthermore, these analogues showed weak-to-moderate non-competitive inhibitory activity against α-amylase. 5-Methyl substituted aurone with 4'-phenylureido moiety (6e) demonstrated the highest inhibition activity on α-amylase with an IC50 of 142.0 ± 1.6 μM relative to acarbose (IC50 = 108 ± 1.2 μM). Our computational studies suggested that these analogues interact with a hydrophilic allosteric site in α-amylase, located far from the enzyme active site at the N-terminal.

Facilitating structural elucidation of small environmental solutes in RPLC-HRMS by retention index prediction

Implementing effective environmental management strategies requires a comprehensive understanding of the chemical composition of environmental pollutants, particularly in complex mixtures. Utilizing innovative analytical techniques, such as high-resolution mass spectrometry and predictive retention index models, can provide valuable insights into the molecular structures of environmental contaminants. Liquid Chromatography-High-Resolution Mass Spectrometry is a powerful tool for the identification of isomeric structures in complex samples. However, there are some limitations that can prevent accurate isomeric structure identification, particularly in cases where the isomers have similar mass and fragmentation patterns. Liquid chromatographic retention, determined by the size, shape, and polarity of the analyte and its interactions with the stationary phase, contains valuable 3D structural information that is vastly underutilized. Therefore, a predictive retention index model is developed which is transferrable to LC-HRMS systems and can assist in the structural elucidation of unknowns. The approach is currently restricted to carbon, hydrogen, and oxygen-based molecules <500 g mol-1. The methodology facilitates the acceptance of accurate structural formulas and the exclusion of erroneous hypothetical structural representations by leveraging retention time estimations, thereby providing a permissible tolerance range for a given elemental composition and experimental retention time. This approach serves as a proof of concept for the development of a Quantitative Structure-Retention Relationship model using a generic gradient LC approach. The use of a widely used reversed-phase (U)HPLC column and a relatively large set of training (101) and test compounds (14) demonstrates the feasibility and potential applicability of this approach for predicting the retention behaviour of compounds in complex mixtures. By providing a standard operating procedure, this approach can be easily replicated and applied to various analytical challenges, further supporting its potential for broader implementation.

Chemoenzymatic approach towards the synthesis of the antitumor and antileishmanial marine metabolite (+)-Harzialactone A via the stereoselective, biocatalyzed reduction of a prochiral ketone

As a rich source of biological active compounds, marine natural products have been increasingly screened as candidates for developing new drugs. Among the several marine products and metabolites, (+)-Harzialactone A has drawn considerable attention for its antitumor and antileishmanial activity. In this work a chemoenzymatic approach has been implemented for the preparation of the marine metabolite (+)-Harzialactone A. The synthesis involved a stereoselective, biocatalyzed reduction of the prochiral ketone 4-oxo-5-phenylpentanoic acid or the corresponding esters, all generated by chemical reactions. A collection of different promiscuous oxidoreductases (both wild-type and engineered) and diverse microorganism strains were investigated to mediate the bioconversions. After co-solvent and co-substrate investigation in order to enhance the bioreduction performance, T. molischiana in presence of NADES (choline hydrochloride-glucose) and ADH442 were identified as the most promising biocatalysts, allowing the obtainment of the (S)-enantiomer with excellent ee (97% to > 99% respectively) and good to excellent conversion (88% to 80% respectively). The successful attempt in this study provides a new chemoenzymatic approach for the synthesis of (+)-Harzialactone A.

Application of solid-phase microextraction arrows for characterizing volatile organic compounds from 3D printing of acrylonitrile-styrene-acrylate filament

3D printing is an extensively used manufacturing technique that can pose specific health concerns due to the emission of volatile organic compounds (VOC). Herein, a detailed characterization of 3D printing-related VOC using solid-phase microextraction-gas chromatography/mass spectrometry (SPME-GC/MS) is described for the first time. The VOC were extracted in dynamic mode during the printing from the acrylonitrile-styrene-acrylate filament in an environmental chamber. The effect of extraction time on the extraction efficiency of 16 main VOC was studied for four different commercial SPME arrows. The volatile and semivolatile compounds were the most effectively extracted by carbon wide range-containing and polydimethyl siloxane arrows, respectively. The differences in extraction efficiency between arrows were further correlated to the molecular volume, octanol-water partition coefficient, and vapour pressure of observed VOC. The repeatability of SPME arrows towards the main VOC was assessed from static mode measurements of filament in headspace vials. In addition, we performed a group analysis of 57 VOC classified into 15 categories according to their chemical structure. Divinylbenzene-polydimethyl siloxane arrow turned out to be a good compromise between the total extracted amount and its distribution among tested VOC. Thus, this arrow was used to demonstrate the usefulness of SPME for the qualification of VOC emitted during printing in a real-life environment. A presented methodology can serve as a fast and reliable method for the qualification and semi-quantification of 3D printing-related VOC.

MetaSpot: A General Approach for Recognizing the Reactive Atoms Undergoing Metabolic Reactions Based on the MetaQSAR Database

The prediction of drug metabolism is attracting great interest for the possibility of discarding molecules with unfavorable ADME/Tox profile at the early stage of the drug discovery process. In this context, artificial intelligence methods can generate highly performing predictive models if they are trained by accurate metabolic data. MetaQSAR-based datasets were collected to predict the sites of metabolism for most metabolic reactions. The models were based on a set of structural, physicochemical, and stereo-electronic descriptors and were generated by the random forest algorithm. For each considered biotransformation, two types of models were developed: the first type involved all non-reactive atoms and included atom types among the descriptors, while the second type involved only non-reactive centers having the same atom type(s) of the reactive atoms. All the models of the first type revealed very high performances; the models of the second type show on average worst performances while being almost always able to recognize the reactive centers; only conjugations with glucuronic acid are unsatisfactorily predicted by the models of the second type. Feature evaluation confirms the major role of lipophilicity, self-polarizability, and H-bonding for almost all considered reactions. The obtained results emphasize the possibility of recognizing the sites of metabolism by classification models trained on MetaQSAR database. The two types of models can be synergistically combined since the first models identify which atoms can undergo a given metabolic reactions, while the second models detect the truly reactive centers. The generated models are available as scripts for the VEGA program.

MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions

INTRODUCTION

Collaborative computing has attracted great interest in the possibility of joining the efforts of researchers worldwide. Its relevance has further increased during the pandemic crisis since it allows for the strengthening of scientific collaborations while avoiding physical interactions. Thus, the E4C consortium presents the MEDIATE initiative which invited researchers to contribute via their virtual screening simulations that will be combined with AI-based consensus approaches to provide robust and method-independent predictions. The best compounds will be tested, and the biological results will be shared with the scientific community.

AREAS COVERED

In this paper, the MEDIATE initiative is described. This shares compounds' libraries and protein structures prepared to perform standardized virtual screenings. Preliminary analyses are also reported which provide encouraging results emphasizing the MEDIATE initiative's capacity to identify active compounds.

EXPERT OPINION

Structure-based virtual screening is well-suited for collaborative projects provided that the participating researchers work on the same input file. Until now, such a strategy was rarely pursued and most initiatives in the field were organized as challenges. The MEDIATE platform is focused on SARS-CoV-2 targets but can be seen as a prototype which can be utilized to perform collaborative virtual screening campaigns in any therapeutic field by sharing the appropriate input files.

Insight on the mechanism of hexameric Pseudin-4 against bacterial membrane-mimetic environment

As an alternative to antibiotics, Antimicrobial Peptides (AMPs) possess unique properties including cationic, amphipathic and their abundance in nature, but the exact characteristics of AMPs against bacterial membranes are still undetermined. To estimate the structural stability and functional activity of AMPs, the Pseudin AMPs (Pse-1, Pse-2, Pse-3, and Pse-4) from Hylid frog species, Pseudis paradoxa, an abundantly discovered source for AMPs were examined. We studied the intra-peptide interactions and thermal denaturation stability of peptides, as well as the geometrical parameters and secondary structure profiles of their conformational trajectories. On this basis, the peptides were screened out and the highly stable peptide, Pse-4 was subjected to membrane simulation in order to observe the changes in membrane curvature formed by Pse-4 insertion. Monomeric Pse-4 was found to initiate the membrane disruption; however, a stable multimeric form of Pse-4 might be competent to counterbalance the helix-coil transition and to resist the hydrophobic membrane environment. Eventually, hexameric Pse-4 on membrane simulation exhibited the hydrogen bond formation with E. coli bacterial membrane and thereby, leading to the formation of membrane spanning pore that allowed the entry of excess water molecules into the membrane shell, thus causing membrane deformation. Our report points out the mechanism of Pse-4 peptide against the bacterial membrane for the first time. Relatively, Pse-4 works on the barrel stave model against E. coli bacterial membrane; hence it might act as a good therapeutic scaffold in the treatment of multi-drug resistant bacterial strains.

Human Hemoglobin and Antipsychotics Clozapine, Ziprasidone and Sertindole: Friends or Foes?

Packed with hemoglobin, an essential protein for oxygen transport, human erythrocytes are a suitable model system for testing the pleiotropic effects of lipophilic drugs. Our study investigated the interaction between antipsychotic drugs clozapine, ziprasidone, sertindole, and human hemoglobin under simulated physiological conditions. Analysis of protein fluorescence quenching at different temperatures and data obtained from the van't Hoff diagram and molecular docking indicate that the interactions are static and that the tetrameric human hemoglobin has one binding site for all drugs in the central cavity near αβ interfaces and is dominantly mediated through hydrophobic forces. The association constants were lower-moderate strength (~10⁴ M^-1), the highest observed for clozapine (2.2 × 10⁴ M^-1 at 25 °C). The clozapine binding showed "friendly" effects: increased α-helical content, a higher melting point, and protein protection from free radical-mediated oxidation. On the other hand, bound ziprasidone and sertindole had a slightly pro-oxidative effect, increasing ferrihemoglobin content, a possible "foe". Since the interaction of proteins with drugs plays a vital role in their pharmacokinetic and pharmacodynamic properties, the physiological significance of the obtained findings is briefly discussed.

Thermodynamics of d(GGGGCCCC) Binding to Neomycin-Class Aminoglycosides

DNA adopts a number of conformations that can affect its binding to other macromolecules. The conformations (A, B, Z) can be sequence- and/or solution-dependent. While AT-rich DNA sequences generally adopt a Canonical B-form structure, GC-rich sequences are more promiscuous. Recognition of GC-rich nucleic acids by small molecules has been much more challenging than the recognition of AT-rich duplexes. Spectrophotometric and calorimetric techniques were used to characterize the binding of neomycin-class aminoglycosides to a GC-rich DNA duplex, G₄C₄, in various ionic and pH conditions. Our results reveal that binding enhances the thermal stability of G₄C₄, with thermal enhancement decreasing with increasing pH and/or Na⁺ concentration. Although G₄C₄ bound to aminoglycosides demonstrated a mixed A- and B-form conformation, circular dichroism studies indicate that binding induces a conformational shift toward A-form DNA. Isothermal titration calorimetry studies reveal that aminoglycoside binding to G₄C₄ is linked to the uptake of protons at pH = 7.0 and that this uptake is pH-dependent. Increased pH and/or Na⁺ concentration results in a decrease in G₄C₄ affinity for the aminoglycosides. The binding affinities of the aminoglycosides follow the expected hierarchy: neomycin > paromomycin > ribostamycin. The salt dependence of DNA binding affinities of aminoglycosides is consistent with at least two drug NH₃⁺ groups participating in electrostatic interactions with G₄C₄. These studies further embellish our understanding of the many factors facilitating recognition of GC-rich DNA structures as guided by their optimum charge and shape complementarity for small-molecule amino sugars.

Targeting the Human Influenza a Virus: The Methods, Limitations, and Pitfalls of Virtual Screening for Drug-like Candidates Including Scaffold Hopping and Compound Profiling

In this study, we describe the input data and processing steps to find antiviral lead compounds by a virtual screen. Two-dimensional and three-dimensional filters were designed based on the X-ray crystallographic structures of viral neuraminidase co-crystallized with substrate sialic acid, substrate-like DANA, and four inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir). As a result, ligand-receptor interactions were modeled, and those necessary for binding were utilized as screen filters. Prospective virtual screening (VS) was carried out in a virtual chemical library of over half a million small organic substances. Orderly filtered moieties were investigated based on 2D- and 3D-predicted binding fingerprints disregarding the "rule-of-five" for drug likeness, and followed by docking and ADMET profiling. Two-dimensional and three-dimensional screening were supervised after enriching the dataset with known reference drugs and decoys. All 2D, 3D, and 4D procedures were calibrated before execution, and were then validated. Presently, two top-ranked substances underwent successful patent filing. In addition, the study demonstrates how to work around reported VS pitfalls in detail.

New insights into the neuroprotective and beta-secretase1 inhibitor profiles of tirandamycin B isolated from a newly found Streptomyces composti sp. nov

Tirandamycin (TAM B) is a tetramic acid antibiotic discovered to be active on a screen designed to find compounds with neuroprotective activity. The producing strain, SBST2-5^T, is an actinobacterium that was isolated from wastewater treatment bio-sludge compost collected from Suphanburi province, Thailand. Taxonomic characterization based on a polyphasic approach indicates that strain SBST2-5^T is a member of the genus Streptomyces and shows low average nucleotide identity (ANI) (81.7%), average amino-acid identity (AAI) (78.5%), and digital DNA-DNA hybridization (dDDH) (25.9%) values to its closest relative, Streptomyces thermoviolaceus NBRC 13905^T, values that are significantly below the suggested cut-off values for the species delineation, indicating that strain SBST2-5^T could be considered to represent a novel species of the genus Streptomyces. The analysis of secondary metabolites biosynthetic gene clusters (smBGCs) in its genome and chemical investigation led to the isolation of TAM B. Interestingly, TAM B at 20 µg/mL displayed a suppressive effect on beta-secretase 1 (BACE1) with 68.69 ± 8.84% inhibition. Molecular docking simulation reveals the interaction mechanism between TAM B and BACE1 that TAM B was buried in the pocket of BACE-1 by interacting with amino acids Thr231, Asp 228, Gln73, Lys 107 via hydrogen bond and Leu30, Tyr71, Phe108, Ile118 via hydrophobic interaction, indicating that TAM B represents a potential active BACE1 inhibitor. Moreover, TAM B can protect the neuron cells significantly (% neuron viability = 83.10 ± 9.83% and 112.72 ± 6.83%) from oxidative stress induced by serum deprivation and Aβ_1-42 administration models at 1 ng/mL, respectively, without neurotoxicity on murine P19-derived neuron cells nor cytotoxicity against Vero cells. This study was reportedly the first study to show the neuroprotective and BACE1 inhibitory activities of TAM B.

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.

SERS-based detection of 5-S-cysteinyl-dopamine as a novel biomarker of Parkinson's disease in artificial biofluids

The early detection of Parkinson's disease (PD) can significantly improve treatment and quality of life in patients. 5-S-Cysteinyl-dopamine (CDA) is a key metabolite of high relevance for the early detection of PD. Therefore, its sensitive detection with fast and robust methods can improve its use as a biomarker. In this work we show the potentialities of label-free SERS spectroscopy in detecting CDA in aqueous solutions and artificial biofluids, with a simple, fast and sensitive approach. We present a detailed experimental SERS band assignment of CDA employing silver nanoparticle (AgNP) substrates in aqueous media, which was supported by theoretical calculations and simulated Raman and SERS spectra. The tentative orientation of CDA over the AgNP was also studied, indicating that catechol and carboxylic acid play a key role in the metallic surface adsorption. Moreover, we showed that SERS can allow us to identify CDA in aqueous media at low concentration, leading to the identification of some of its characteristic bands in pure water and in synthetic cerebrospinal fluid (SCSF) below 1 × 10^-8 M, while its band identification in simulated urine (SUR) can be reached at 1 × 10^-7 M. In conclusion, we show that CDA can be suitably detected by means of label-free SERS spectroscopy, which can significantly improve its sensitive detection for further analytical studies as a novel biomarker and further clinical diagnosis in PD patients.

Phenotypic Discovery of Thiocarbohydrazone with Anticancer Properties and Catalytic Inhibition of Human DNA Topoisomerase IIα

Phenotypic screening of α-substituted thiocarbohydrazones revealed promising activity of 1,5-bis(salicylidene)thiocarbohydrazide against leukemia and breast cancer cells. Supplementary cell-based studies indicated an impairment of DNA replication via the ROS-independent pathway. The structural similarity of α-substituted thiocarbohydrazone to previously published thiosemicarbazone catalytic inhibitors targeting the ATP-binding site of human DNA topoisomerase IIα prompted us to investigate the inhibition activity on this target. Thiocarbohydrazone acted as a catalytic inhibitor and did not intercalate the DNA molecule, which validated their engagement with this cancer target. A comprehensive computational assessment of molecular recognition for a selected thiosemicarbazone and thiocarbohydrazone provided useful information for further optimization of this discovered lead compound for chemotherapeutic anticancer drug discovery.

Importance of the 2,6-Difluorobenzamide Motif for FtsZ Allosteric Inhibition: Insights from Conformational Analysis, Molecular Docking and Structural Modifications

A conformational analysis and molecular docking study comparing 2,6-difluoro-3-methoxybenzamide (DFMBA) with 3-methoxybenzamide (3-MBA) has been undertaken for investigating the known increase of FtsZ inhibition related anti S. aureus activity due to fluorination. For the isolated molecules, the calculations reveal that the presence of the fluorine atoms in DFMBA is responsible for its non-planarity, with a dihedral angle of -27° between the carboxamide and the aromatic ring. When interacting with the protein, the fluorinated ligand can thus more easily adopt the non-planar conformation found in reported co-crystallized complexes with FtsZ, than the non-fluorinated one. Molecular docking studies of the favored non-planar conformation of 2,6-difluoro-3-methoxybenzamide highlights the strong hydrophobic interactions between the difluoroaromatic ring and several key residues of the allosteric pocket, precisely between the 2-fluoro substituent and residues Val203 and Val297 and between the 6-fluoro group and the residues Asn263. The docking simulation in the allosteric binding site also confirms the critical importance of the hydrogen bonds between the carboxamide group with the residues Val207, Leu209 and Asn263. Changing the carboxamide functional group of 3-alkyloxybenzamide and 3-alkyloxy-2,6-difluorobenzamide to a benzohydroxamic acid or benzohydrazide led to inactive compounds, confirming the importance of the carboxamide group.

X-ray structure of human aldo-keto reductase 1C3 in complex with a bile acid fused tetrazole inhibitor: experimental validation, molecular docking and structural analysis

Aldo-keto reductase 1C3 (AKR1C3) catalyzes the reduction of androstenedione to testosterone and reduces the effectiveness of chemotherapeutics. AKR1C3 is a target for treatment of breast and prostate cancer and AKR1C3 inhibition could be an effective adjuvant therapy in the context of leukemia and other cancers. In the present study, steroidal bile acid fused tetrazoles were screened for their ability to inhibit AKR1C3. Four C24 bile acids with C-ring fused tetrazoles were moderate to strong AKR1C3 inhibitors (37-88% inhibition), while B-ring fused tetrazoles had no effect on AKR1C3 activity. Based on a fluorescence assay in yeast cells, these four compounds displayed no affinity for estrogen receptor-α, or the androgen receptor, suggesting a lack of estrogenic or androgenic effects. A top inhibitor showed specificity for AKR1C3 over AKR1C2, and inhibited AKR1C3 with an IC₅₀ of ∼7 μM. The structure of AKR1C3·NADP⁺ in complex with this C-ring fused bile acid tetrazole was determined by X-ray crystallography at 1.4 Å resolution, revealing that the C24 carboxylate is anchored to the catalytic oxyanion site (H117, Y55); meanwhile the tetrazole interacts with a tryptophan (W227) important for steroid recognition. Molecular docking predicts that all four top AKR1C3 inhibitors bind with nearly identical geometry, suggesting that C-ring bile acid fused tetrazoles represent a new class of AKR1C3 inhibitors.

Synthesis of conjugates of (aR,7S)-colchicine with monoterpenoids and investigation of their biological activity

Conjugates of the natural alkaloid (aR,7S)-colchicine with bicyclic monoterpenoids and their derivatives were synthesized for the first time. Molecular docking of the synthesized agents in the active site of the main viral protease of the SARS-CoV-2 virus was carried out. The cytotoxic properties of the agents against different cell lines and the ability to inhibit the main viral protease 3CLPro were studied.

Identification of AHL Synthase in Desulfovibrio vulgaris Hildenborough Using an In-Silico Methodology

Sulfate-reducing bacteria (SRB) are anaerobic bacteria that form biofilm and induce corrosion on various material surfaces. The quorum sensing (QS) system that employs acyl homoserine lactone (AHL)-type QS molecules primarily govern biofilm formation. Studies on SRB have reported the presence of AHL, but no AHL synthase have been annotated in SRB so far. In this computational study, we used a combination of data mining, multiple sequence alignment (MSA), homology modeling and docking to decode a putative AHL synthase in the model SRB, Desulfovibrio vulgaris Hildenborough (DvH). Through data mining, we shortlisted 111 AHL synthase genes. Conserved domain analysis of 111 AHL synthase genes generated a consensus sequence. Subsequent MSA of the consensus sequence with DvH genome indicated that DVU_2486 (previously uncharacterized protein from acetyltransferase family) is the gene encoding for AHL synthase. Homology modeling revealed the existence of seven α-helices and six β sheets in the DvH AHL synthase. The amalgamated study of hydrophobicity, binding energy, and tunnels and cavities revealed that Leu99, Trp104, Arg139, Trp97, and Tyr36 are the crucial amino acids that govern the catalytic center of this putative synthase. Identifying AHL synthase in DvH would provide more comprehensive knowledge on QS mechanism and help design strategies to control biofilm formation.

Conformational Sampling Deciphers the Chameleonic Properties of a VHL-Based Degrader

Chameleonicity (the capacity of a molecule to adapt its conformations to the environment) may help to identify orally bioavailable drugs in the beyond-Rule-of-5 chemical space. Computational methods to predict the chameleonic behaviour of degraders have not yet been reported and the identification of molecular chameleons still relies on experimental evidence. Therefore, there is a need to tune predictions with experimental data. Here, we employ PROTAC-1 (a passively cell-permeable degrader), for which NMR and physicochemical data prove the chameleonic behaviour, to benchmark the capacity of two conformational sampling algorithms and selection schemes. To characterize the conformational ensembles in both polar and nonpolar environments, we compute three molecular properties proven to be essential for cell permeability: conformer shape (radius of gyration), polarity (3D PSA), and the number of intramolecular hydrogen bonds. Energetic criteria were also considered. Infographics monitored the simultaneous variation of those properties in computed and NMR conformers. Overall, we provide key points for tuning conformational sampling tools to reproduce PROTAC-1 chameleonicity according to NMR evidence. This study is expected to improve the design of PROTAC drugs and the development of computational sustainable strategies to exploit the potential of new modalities in drug discovery.