The cannabinoid receptor subtype 2 (CB2R) represents an interesting and new therapeutic target for its involvement in the first steps of neurodegeneration as well as in cancer onset and progression. ...Several studies, focused on different types of tumors, report a promising anticancer activity induced by CB2R agonists due to their ability to reduce inflammation and cell proliferation. Moreover, in neuroinflammation, the stimulation of CB2R, overexpressed in microglial cells, exerts beneficial effects in neurodegenerative disorders. With the aim to overcome current treatment limitations, new drugs can be developed by specifically modulating, together with CB2R, other targets involved in such multifactorial disorders. Building on successful case studies of already developed multitarget strategies involving CB2R, in this Perspective we aim at prompting the scientific community to consider new promising target associations involving HDACs (histone deacetylases) and σ receptors by employing modern approaches based on molecular hybridization, computational polypharmacology, and machine learning algorithms.
Organic thin film transistors (OTFT) are metal–insulator–semiconductor field-effect transistors in which the semiconductor is a conjugated organic material. They are the subject of intense industrial ...research because their fabrication process is less expensive when compared with inorganic TFTs. Among the others, the organic material mostly employed in their construction consists of two semiconductor polymers, namely poly(3-hexylthiophene) (P3HT) and poly(2,5-bis(3-alkylthiophen-2-yl)thieno3,2-bthiophene) (PBTTT). Despite the large amount of experimental efforts in the characterization of the electronic properties of these devices, several questions regarding their morphological arrangement in bulk and at interfaces remain wide open. Here, we report results obtained by classical molecular dynamics simulations of P3HT and PBTTT inspired by OTFT fabrication techniques. In particular, we investigate how the annealing fabrication process and the presence of residual solvent molecules left over after spin coating might modify the morphology and the dynamics of the amorphous phase of these two polymers. Simulations of both polymer deposits at 300 K after annealing show an increase in the number of interdigitation events between the alkyl chains of two polymeric macromolecules; moreover, we find that the increased stability of the π–π stacking is caused by an improved layering of the films, which may account for the better charge transport properties reported in experiments. Our results strongly suggest that thin semiconductor films are required to boost the performances of the devices and that a minimal presence of residual solvent does not alter dramatically the microscopic structure and stability of the polymeric films.
Dengue virus (DENV) causes 390 million infections per year. Infections can be asymptomatic or range from mild fever to severe haemorrhagic fever and shock syndrome. Currently, no effective antivirals ...or safe universal vaccine is available. In the present work we tested different gold nanoparticles (AuNP) coated with ligands ω-terminated with sugars bearing multiple sulfonate groups. We aimed to identify compounds with antiviral properties due to irreversible (virucidal) rather than reversible (virustatic) inhibition. The ligands varied in length, in number of sulfonated groups as well as their spatial orientation induced by the sugar head groups. We identified two candidates, a glucose- and a lactose-based ligand showing a low EC
(effective concentration that inhibit 50% of the viral activity) for DENV-2 inhibition, moderate toxicity and a virucidal effect in hepatocytes with titre reduction of Median Tissue Culture Infectious Dose log
TCID
2.5 and 3.1. Molecular docking simulations complemented the experimental findings suggesting a molecular rationale behind the binding between sulfonated head groups and DENV-2 envelope protein.
Background
Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally ...close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds.
Results
This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique.
Conclusions
Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain.
The development of small molecules that selectively target the cannabinoid receptor subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat neurodegeneration, as well as to ...contrast the onset and progression of cancer. In this context, in-silico tools able to predict CB2R affinity and selectivity with respect to the subtype 1 (CB1R), whose modulation is responsible for undesired psychotropic effects, are highly desirable. In this work, we developed a series of machine learning classifiers trained on high-quality bioactivity data of small molecules acting on CB2R and/or CB1R extracted from ChEMBL v30. Our classifiers showed strong predictive power in accurately determining CB2R affinity, CB1R affinity, and CB2R/CB1R selectivity. Among the built models, those obtained using random forest as algorithm proved to be the top-performing ones (AUC in validation ≥0.96) and were made freely accessible through a user-friendly web platform developed ad hoc and called ALPACA (https://www.ba.ic.cnr.it/softwareic/alpaca/). Due to its user-friendly interface and robust predictive power, ALPACA can be a valuable tool in saving both time and resources involved in the design of selective CB2R modulators.
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•CB2R modulators might be used to treat neurodegeneration and cancer.•We developed classifiers of CB2R affinity, CB1R affinity, and CB2R/CB1R selectivity.•Random Forest based models were proved to be the top-performing ones.•The ML-based classifiers were made freely accessible in a user-friendly web platform.
A significant number of different exchange correlation functionals, ranging from generalized gradient approximations to double hybrids, has been tested on a difficult playground represented by proton ...transfer reactions. In order to have a complete picture of their performances, both energetics and structural features have been compared and the obtained ranking compared with those issued from the standard test for kinetics (i.e., the DBH24/08 set). Among all of the functionals, the ωB97X, BMK, B1LYP, and PBE0-DH approaches are those providing a good error balance on all four trials. Beyond these figures, the obtained results allow for some general considerations, such as those on the role of Hartree–Fock exchange in reaction barriers or the relation between structure and energetics.
Retrospective validation studies carried out on three benchmark databases containing a small fraction (that is 2.80%) of known tubulin binders permitted us to develop a computational platform very ...effective in selecting easier manageable subsets showing by far higher percentages of actives (about 25%). These studies relied on the hierarchical application of multilayer in silico screenings employing filters implying molecular shape similarity; a structure-based pharmacophore model and molecular docking campaigns. Building on this validated approach, we performed intensive prospective studies to screen a large chemical collection, including up to 3.7 millions of commercial compounds, to across an unexplored and patent space in the search of novel colchicine binding site inhibitors. Our investigation was successful in identifying a pool of 31 initial hits showing new molecular scaffolds (such as 4,5-dihydro-1H-pyrrolo3,4-cpyrazol-6-one and pyrazolo1,5-apyrimidine). This panel of new hits resulted antiproliferative activity in the low μM range towards MCF-7 human breast cancer, HepG2 human liver cancer, HeLa human ovarian cancer and SHSY5Y human glioblastoma cell lines as well as interesting concentration-dependent inhibition of tubulin polymerization assessed through fluorescence polymerization assays. Unlike typical tubulin inhibitors, a satisfactorily low sensitivity towards P-gp was also measured in bi-directional transport studies across MDCKII-MDR1 cells for a selected subset of seven compounds.
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•Development and validation of a hierarchical computational platform.•Identification of 31 structurally novel initial hits targeting tubulin at the Colchicine Binding Site.•Cytotoxicity measured on multiple cancer cell lines.•Concentration-dependent effects in inhibiting tubulin polymerization.•Bi-directional transport across MDCKII-MDR1 cells.
We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic ...potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.
Aiming at modulating two key enzymatic targets for Alzheimer’s disease (AD), i.e., acetylcholinesterase (AChE) and monoamine oxidase B (MAO B), a series of multitarget ligands was properly designed ...by linking the 3,4-dimethylcoumarin scaffold to 1,3- and 1,4-substituted piperidine moieties, thus modulating the basicity to improve the hydrophilic/lipophilic balance. After in vitro enzymatic inhibition assays, multipotent inhibitors showing potencies in the nanomolar and in the low micromolar range for hMAO B and eeAChE, respectively, were prioritized and evaluated in human SH-SY5Y cell-based models for their cytotoxicity and neuroprotective effect against oxidative toxins (H2O2, rotenone, and oligomycin-A). The present study led to the identification of a promising multitarget hit compound (5b) exhibiting high hMAO B inhibitory activity (IC50 = 30 nM) and good MAO B/A selectivity (selectivity index, SI = 94) along with a micromolar eeAChE inhibition (IC50 = 1.03 μM). Moreover, 5b behaves as a water-soluble, brain-permeant neuroprotective agent against oxidative insults without interacting with P-gp efflux system.
We present combined MD-DFT calculations to investigate the electronic, optical, and charge-transport properties of six triphenylamine-based hole-transporter materials (HTMs) used in solid-state ...dye-sensitized solar cells (ssDSSC), including the state-of-the-art material in this field, 2,2′,7,7′-tetrakis(N,N-di-4-methoxyphenylamino)-9,9′-spirobifluorene (spiro-OMeTAD). We find that all of the studied materials present typical features of a HTM: (1) delocalized highest occupied molecular orbital (HOMO); (2) hole reorganization energies higher than the electronic ones; and (3) transparency in the visible region of the electromagnetic spectrum. Among the investigated compounds, 4-(4-phenyl-4-α-naphthylbutadienyl)-N,N-di(4-tolyl)-phenylamine (HTM1) shows the most promising features: a low HOMO energy level that favors high open-circuit voltage in solar cells, high adiabatic ionization potential ensuring great stability in terms of resistance to ionization, and small exciton binding energy. Our results also indicate that the presence of a butadiene moiety in HTM1 is somehow responsible for a higher molecular flexibility, thus favoring the pore filling of the semiconductor in ssDSSC. Finally, its optimal charge delocalization favors the overlap of the atomic orbitals, thus enhancing the electronic couplings, while its low energetic disorder causes a high hole mobility in the amorphous phase. The obtained results are in qualitative and quantitative agreement with the experimental data and suggest that the current computational approach could be further employed to obtain valuable insights for the design of new HTMs aiming at improving the performances of presently available ssDSSC.
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