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Cystic Fibrosis (CF) is an autosomal recessive genetic disease caused by mutations in the CFTR gene, coding for the CFTR chloride channel. About 10% of the CFTR gene mutations are "stop" mutations, which generate a Premature Termination Codon (PTC), thus synthesizing a truncated CFTR protein. A way to bypass PTC relies on ribosome readthrough, which is the ri-bosome’s capacity to skip a PTC, thus generating a full-length protein. “TRIDs” are molecules exerting ribosome readthrough; for some, the mechanism of action is still under debate. We in-vestigate a possible mechanism of action (MOA) by which our recently synthesized TRIDs, namely NV848, NV914, and NV930, could exert their readthrough activity by in silico analysis and in vitro studies. Our results suggest a likely inhibition of FTSJ1, a tryptophan tRNA-specific 2’-O-methyltransferase.

Immunoproteasome inhibition is a promising strategy for the treatment of hematological malignancies, autoimmune diseases, and inflammatory diseases. The design of non-covalent inhibitors of the immunoproteasome β1i/β5i catalytic subunits could be a novel approach to avoid the drawbacks of the known covalent inhibitors, such as toxicity due to off-target binding. In this work, we report the biological evaluation of thirty-four compounds selected from a commercially available collection. These hit compounds are the outcomes of a virtual screening strategy including a dynamic pharmacophore modeling approach onto the β1i subunit and a pharmacophore/docking approach onto the β5i subunit. The computational studies were first followed by in vitro enzymatic assays at 100 μM. Only compounds capable of inhibiting the enzymatic activity by more than 50% were characterized in detail using Tian continuous assays, determining the dissociation constant (Ki) of the non-covalent complex where Ki is also the measure of the binding affinity. Seven out of thirty-four hits showed to inhibit β1i and/or β5i subunit. Compound 3 is the most active on the β1i subunit with Ki = 11.84 ± 1.63 µM, and compound 17 showed Ki = 12.50 ± 0.77 µM on the β5i subunit. Compound 2 showed inhibitory activity on both subunits (Ki = 12.53 ± 0.18 and Ki = 31.95 ± 0.81 on the β1i subunit and β5i subunit, respectively). The induced fit docking analysis revealed interactions with Thr1 and Phe31 of β1i subunit and that represent new key residues as reported in our previous work. Onto β5i subunit, it interacts with the key residues Thr1, Thr21, and Tyr169. This last hit compound identified represents an interesting starting point for further optimization of β1i/β5i dual inhibitors of the immunoproteasome.

Cystic Fibrosis (CF) is an autosomal recessive genetic disease caused by mutations in the CFTR gene, coding for the CFTR chloride channel. About 10% of the CFTR gene mutations are “stop” mutations that generate a premature termination codon (PTC), thus synthesizing a truncated CFTR protein. A way to bypass PTC relies on ribosome readthrough, which is the ribosome’s capacity to skip a PTC, thus generating a full-length protein. “TRIDs” are molecules exerting ribosome readthrough; for some, the mechanism of action is still under debate. We investigate a possible mechanism of action (MOA) by which our recently synthesized TRIDs, namely NV848, NV914, and NV930, could exert their readthrough activity by in silico analysis and in vitro studies. Our results suggest a likely inhibition of FTSJ1, a tryptophan tRNA-specific 2′-O-methyltransferase.

BACKGROUND Migrants from Africa are vulnerable to viral infections during their journey. METHODS Migrants who arrived in western Sicily were offered early screening for hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus (HIV) infection. A questionnaire was administered to evaluate risk factors, and antiviral therapy was offered to subjects with active infection. A multiple regression analysis and adjusted odds ratio were obtained to evaluate risk factors. RESULTS Overall, 2,639 of 2,751 (95.9%) migrants who arrived between 2015 and 2017 accepted screening and 1,911 (72.4%) completed the questionnaire. HBsAg was positive in 257 (9.7%) migrants, 24 (0.9%) were anti-HCV positive and 57 (2.2%) had HIV infection. The prevalence of HBV infection was higher in women (aOR 2.47,95%CI 1.90-3.20),p = 0.003) and in people who endured physical and/or sexual violence (aOR 2.24,95%CI 1.87-3.55,p

Cystic Fibrosis (CF) is an autosomal recessive genetic disease caused by mutations in the CFTR gene, coding for the CFTR chloride channel. About 10 % of the mutations affecting the CFTR gene are "stop" mutations, which generate a Premature Termination Codon (PTC), thus resulting in the synthesis of a truncated CFTR protein. A way to bypass PTC relies on ribosome readthrough, that is the capacity of the ribosome to skip a PTC, thus generating a full-length protein. “TRIDs” are molecules exerting ribosome readthrough and for some of them the mechanism of action is still under debate. By in silico analysis as well as in vitro studies, we investigate a possible mechanism of action (MOA) by which our recently synthesized TRIDs, namely NV848, NV914 and NV930, could exert their readthrough activity. Our results suggest a likely inhibition of FTSJ1, a tryptophan tRNA-specific 2’-O-methyltransferase. In addition, we report that our TRIDs do not exert readthrough on natural termination codons.

Objectives Sex differences in COVID-19 severity and mortality have been described. Key aims of this analysis were to compare the risk of invasive mechanical ventilation (IMV) and mortality by sex and to explore whether variation in specific biomarkers could mediate this difference. Methods This was a retrospective, observational cohort study among patients with severe COVID-19 pneumonia. A survival analysis was conducted to compare time to the composite endpoint of IMV or death by sex. Interaction was formally tested to compare the risk difference by sex in subsets. Mediation analysis with a binary endpoint IMV or death (yes/no) by end of follow-up for a number of inflammation/coagulation biomarkers in the context of counterfactual prediction was also conducted. Results Among 415 patients, 134 were females (32%) and 281 males (67%), median age 66 years (IQR 54-77). At admission, females showed a significantly less severe clinical and respiratory profiles with a higher PaO2/FiO2 (254 mmHg vs 191 mmHg; p=0.023). By 28 days from admission, 49.2% (95% CI: 39.6-58.9%) of males vs. 31.7% (17.9-45.4%) of females underwent IMV or death (log-rank p-value Conclusions Our analysis confirms a difference in the risk of COVID-19 clinical progression by sex and provides a hypothesis for potential mechanisms leading to this. CRP showed a predominant role to mediate the difference in risk by sex.

Cyclin Dependent Kinases-2 (CDK2) are members of serine/threonine protein kinases family. They play an important role in the regulation events of the eukaryotic cell division cycle, especially during the G1 to S phase transition. Experimental evidence indicate that excessive expression of CDK2s should cause abnormal cell cycle regulation. Therefore, since a long time, CDK2s have been considered potential therapeutic targets for cancer therapy. In this work, onehundred and forty-nine complexes of inhibitors bound in the CDK2-ATP pocket were submitted to short MD simulations (10ns) and free energy calculation. Comparison with experimental data (Ki, Kd and pIC50) revealed that short simulations are exhaustive to examine the crucial ligand-protein interactions within the complexes. Information collected on MD simulations of protein-ligand complexes has been used to perform a molecular modelling approach that incorporates flexibility into structure-based pharmacophore modelling (Common Hits Approach, CHA). The high number of pharmacophore models resulting from the MD simulation was thus reduced to a few representative groups of pharmacophore models. The performance of the models has been assessed by using the ROC curves analysis. This definitive set of validated pharmacophore models could be used to screen in-house and/or commercial datasets for detection of new CDK-2 inhibitors. We provide the models to all the researchers involved in this field.

Oleanolic acid (OA) and Lupeol (LU) belong to the class of natural triterpenes and are endowed with a wide range of biological activities, including cytotoxicity toward several cancer cell lines. In this context, we investigated a set of compounds obtained from the two natural precursors for the cytotoxicity against leukemia HL60 cells and the multidrug-resistant (MDR) variant HL60R. Six new semi-synthetic triterpenes have been synthetized, fully characterized, and were investigated together with other triterpenes compounds for their pharmacological mechanism of action. The interaction of the more cytotoxic compounds with the nuclear factor kappa B (NF-κB) pathway has been also evaluated with the aid of docking. The lupane-like compounds were more active than the precursor, while the oleane-like compounds showed more complex behavior. Both OA and LU derivatives possess a similar interaction pattern with the p65 subunit of NF-κB, justifying the similar trend in their ability to inhibit the binding of p65 to DNA. Further, some of the derivatives tested were able to increase IκB-α levels preventing the translocation of NF-κB to the nucleus. In conclusion, this study offers a deeper insight on the pharmacological action of triterpenes toward leukemia cells, and it improves the background useful for the development of new anti-cancer drugs.

Euphorbia species have a large spectrum of traditional medicinal uses. We tested the biological activities of the essential oil (EO) of Euphorbia intisy Drake in an acquired multidrug resistance leukemia model to assess whether the EO obtained by hydrodistillation of stems was able to reverse the resistant phenotype. HL-60R cell lines are characterized by the overexpression of P-glycoprotein (P-gp), inhibitors of apoptosis proteins (IAPs) and constitutive expression of NF-κB. EO chemical composition was determined by GC/MS analysis, cytotoxic activity of EO by MTS assay alone or in combination with doxorubicin, pro-apoptotic effect and doxorubicin accumulation were analyzed by flow cytometry, P-gp ATPase activity was measured by P-gp-Glo™ assay systems kit. The ability to inhibit NF-κB and its target genes was also assessed. E. intisy EO exhibited a comparable cytotoxic effect and ability to block P-gp in both the HL-60 and its MDR variant HL-60R. In addition, EO suppressed P-gp protein expression and significantly downregulated MDR1 mRNA level, as well as some IAPs proteins, probably through the inhibition of NF-κB. Our results suggest that E. intisy EO could reverse P-gp-mediated drug resistance in tumor cells acting as a chemosensitizing agent.

Background: Indicaxanthin, a betaxanthin belonging to the betalain class of compounds, has been recently demonstrated to exert significant antiproliferative effects inducing apoptosis of human melanoma cells through the inhibition of NF-κB as the predominant pathway. Specifically, Indicaxanthin inhibited IκBα degradation in A375 cells. In resting cells, NF-κB is arrested in the cytoplasm by binding to its inhibitor protein IκBα. Upon stimulation, IκBα is phosphorylated by the IKK complex, and degraded by the proteasome, liberating free NF-κB into the nucleus to initiate target gene transcription. Inhibition of the IKK complex leads to the arrest of the NF-κB pathway.Methods: To acquire details at the molecular level of Indicaxanthin’s inhibitory activity against hIKKβ, molecular modeling and simulation techniques including induced-fit docking (IFD), binding pose metadynamics (BPMD), molecular dynamics simulations, and MM-GBSA (molecular mechanics-generalized Born surface area continuum solvation) have been performed.Results: The computational calculations performed on the active and inactive form, and the allosteric binding site of hIKKβ, revealed that Indicaxanthin inhibits prevalently the active form of the hIKKβ. MM-GBSA computations provide further evidence of Indicaxanthin’s stability inside the active binding pocket with a binding free energy of −22.2 ± 4.3 kcal/mol with respect to the inactive binding pocket with a binding free energy of −20.7 ± 4.7 kcal/mol. BPMD and MD simulation revealed that Indicaxanthin is likely not an allosteric inhibitor of hIKKβ.Conclusion: As a whole, these in silico pieces of evidence show that Indicaxanthin can inhibit the active form of the hIKKβ adding novel mechanistic insights on its recently discovered ability to impair NF-κB signaling in melanoma A375 cells. Moreover, our results suggest the phytochemical as a new lead compound for novel, more potent IKKβ inhibitors to be employed in the treatment of cancer and inflammation-related conditions.

The selective inhibition of immunoproteasome is a valuable strategy to treat autoimmune, inflammatory diseases, and hematologic malignancies. Recently, a new series of amide derivatives as non-covalent inhibitors of the β1i subunit with Ki values in the low/submicromolar ranges have been identified. Here, we investigated the binding mechanism of the most potent and selective inhibitor, N-benzyl-2-(2-oxopyridin-1(2H)-yl)propanamide (1), to elucidate the steps from the ligand entrance into the binding pocket to the ligand-induced conformational changes. We carried out a total of 400 ns of MD-binding analyses, followed by 200 ns of plain MD. The trajectories clustering allowed identifying three representative poses evidencing new key interactions with Phe31 and Lys33 together in a flipped orientation of a representative pose. Further, Binding Pose MetaDynamics (BPMD) studies were performed to evaluate the binding stability, comparing 1 with four other inhibitors of the β1i subunit: N-benzyl-2-(2-oxopyridin-1(2H)-yl)acetamide (2), N-cyclohexyl-3-(2-oxopyridin-1(2H)-yl)propenamide (3), N-butyl-3-(2-oxopyridin-1(2H)-yl)propanamide (4), and (S)-2-(2-oxopyridin-1(2H)-yl)-N,4-diphenylbutanamide (5). The obtained results in terms of free binding energy were consistent with the experimental values of inhibition, confirming 1 as a lead compound of this series. The adopted methods provided a full dynamic description of the binding events, and the information obtained could be exploited for the rational design of new and more active inhibitors.

Background: The study analysed risk factors for bacterial and fungal co-infection in patients with COVID-19 and the impact on mortality.Methods: This is a single-center retrospective study conducted on 387 patients with confirmed COVID-19 pneumonia admitted to an Italian Tertiary-care hospital, between 21 February 2020 and 31 May 2020. Bacterial/fungal coinfection was determined by the presence of characteristic clinical features and positive culture results. Multivariable logistic regression was used to analyze risk factors for the development of bacterial/fungal co-infection after adjusting for demographic characteristics and comorbidities. Thirty-day survival of the patients with or without co-infections was analysed by Kaplan-Meier method.Results: In 53/387 (13.7%) patients with COVID-19 pneumonia, 67 episodes of bacterial/fungal co-infection occurred (14 presented >1 episode). Pneumonia was the most frequent co-infection (47.7%), followed by BSI (34.3%) and UTI (11.9%). S. aureus was responsible for 24 episodes (35.8%), E. coli for 7 (10.4%), P. aerugionsa and Enterococcus spp. for 5 episodes each (7.4%). Five (7.4%) pulmonary aspergillosis, 3 (4.4%) pneumocystosis and 5 (7.4%) invasive candidiases were observed. Multivariable analysis showed a higher risk of infection in patients with an age>65 years (csHR 2.680; 95%CI: 1.254 - 5.727; p=0.054), with cancer (csHR 5.243; 95%CI: 1.173-23.423; p=0.030), with a LOS>10 days (csHR 12.507; 95%CI: 2.659 – 58.830; p=0.001), early (within 48h) admitted in ICU (csHR 11.766; 95% CI: 4.353-31.804; p5 (csHR 3.397; 95% CI: 1.091 - 10.581; p=0.035). Estimated cumulative risk of developing at least 1 bacterial/fungal co-infection episode was of 15% and 27% after 15 and 30 days from admission, respectively. Kaplan-Meier estimated a higher cumulative probability of death in patients with bacterial/fungal co-infection (log-rank=0.031). Thirty-day mortality rate of patients with pneumonia was 38.7%, higher than those with BSI (30.4%).Conclusions: Bacterial and fungal infections are a serious complication affecting the survival of patients with COVID-19-related pneumonia. Some issues need to be investigated, such as the best empirical antibiotic therapy and the need for possible antifungal prophylaxis.

Over the latest years phytochemical consumption has been associated to a decreased risk of both the onset and the development of a number of pathological conditions. In this context indicaxanthin, a betalain pigment from Opuntia ficus-indica fruit, has been the object of sound research. Explored, at first, for its mere antioxidant potential, Indicaxanthin is now regarded as a redox-active compound able to exert significant poly-pharmacological effects against several targets in a number of experimental conditions both in vivo and in vitro. This paper aims to provide an overview on the therapeutical effects of indicaxanthin, ranging from the anti-inflammatory to the neuro-modulatory and anti-tumoral ones and favored by its high bioavailability. Moreover, biochemical and molecular modelling investigations are aimed to identify the pharmacological targets the compound is able to interact with and to address the challenging development in the future research.

Background The benefit of tocilizumab on mortality and time to recovery in people with severe COVID pneumonia may depend on appropriate timing. The objective was to estimate the impact of tocilizumab administration on switching respiratory support states, mortality and time to recovery. Methods In an observational study, a continuous-time Markov multi-state model was used to describe the sequence of respiratory support states including: no respiratory support (NRS), oxygen therapy (OT), non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV), OT in recovery, NRS in recovery. Results Two hundred seventy-one consecutive adult patients were included in the analyses contributing to 695 transitions across states. The prevalence of patients in each respiratory support state was estimated with stack probability plots, comparing people treated with and without tocilizumab since the beginning of the OT state. A positive effect of tocilizumab on the probability of moving from the invasive and non-invasive mechanical NIV/IMV state to the OT in recovery state (HR = 2.6, 95% CI = 1.2–5.2) was observed. Furthermore, a reduced risk of death was observed in patients in NIV/IMV (HR = 0.3, 95% CI = 0.1–0.7) or in OT (HR = 0.1, 95% CI = 0.0–0.8) treated with tocilizumab. Conclusion To conclude, we were able to show the positive impact of tocilizumab used in different disease stages depicted by respiratory support states. The use of the multi-state Markov model allowed to harmonize the heterogeneous mortality and recovery endpoints and summarize results with stack probability plots. This approach could inform randomized clinical trials regarding tocilizumab, support disease management and hospital decision making.

The aim of this study was to evaluate both positive outcomes, including reduction of respiratory support aid and duration of hospital stay, and negative ones, including mortality and a composite of invasive mechanical ventilation or death, in patients with coronavirus disease 2019 (COVID-19) pneumonia treated with or without oral darunavir/cobicistat (DRV/c, 800/150 mg/day) used in different treatment durations. The secondary objective was to evaluate the percentage of patients treated with DRV/c who were exposed to potentially severe drug-drug interactions (DDIs) and died during hospitalization. This observational retrospective study was conducted in consecutive patients with COVID-19 pneumonia admitted to a tertiary care hospital in Modena, Italy. Kaplan-Meier survival curves and Cox proportional hazards regression were used to compare patients receiving standard of care with or without DRV/c. Adjustment for key confounders was applied. Two hundred seventy-three patients (115 on DRV/c) were included, 75.8% males, mean age was 64.6 (±13.2) years. Clinical improvement was similar between the groups, depicted by respiratory aid switch (p > .05). The same was observed for duration of hospital stay [13.2 (±8.9) for DRV/c vs. 13.4 (±7.2) days for no-DRV/c, p = .9]. Patients on DRV/c had higher rates of mortality (25.2% vs. 10.1%, p < .0001. The rate of composite outcome of mechanical ventilation and death was higher in the DRV/c group (37.4% vs. 25.3%, p = .03). Multiple serious DDI associated with DRV/c were observed in the 19 patients who died. DRV/c should not be recommended as a treatment option for COVID-19 pneumonia outside clinical trials.

Euphorbia species have a large spectrum of traditional medicinal uses. We tested the biological activities of the essential oil (EO) of Euphorbia intisy Drake in an acquired multidrug resistance leukemia model to assess whether the EO obtained by hydrodistillation of stems was able to reverse the resistant phenotype. HL-60R cell lines are characterized by the overexpression of P-glycoprotein (P-gp), inhibitors of apoptosis proteins (IAPs) and constitutive expression of NF-κB. EO chemical composition was determined by GC/MS analysis; cytotoxic activity of EO by MTS assay alone or in combination with doxorubicin; pro-apoptotic effect and doxorubicin accumulation were analyzed by flow cytometry; P-gp ATPase activity was measured by P-gp-Glo™ assay systems kit. The ability to inhibit NF-κB and its target genes was also assessed. E. intisy EO exhibited a comparable cytotoxic effect and ability to block P-gp in both the HL-60 and its MDR variant HL-60R. In addition, EO suppressed P-gp protein expression and significantly downregulated MDR1 mRNA level, as well as some IAPs proteins, probably through the inhibition of NF-κB. Our results suggest that E. intisy EO could reverse P-gp-mediated drug resistance in tumor cells acting as a chemosensitizing agent.

E’ noto in letteratura che Ataluren (acido 5-(fluorofenil)-1,2,4-ossadiazolil-benzoico) sia in grado di sopprimere le mutazioni non senso favorendo il readthrough dei codoni di stop prematuri, anche se il suo meccanismo di azione non risulta ancora chiaro. La probabile interazione tra Ataluren e CTFR-mRNA è stata precedentemente studiata mediante dinamica molecolare. In questo studio1, abbiamo esteso il modeling del probabile meccanismo di azione di Ataluren mediante approcci computazionali completementari, quali Induced Fit Docking (IFD), Quantum Polarized Ligand Docking (QPLD), metodi MM-GBSA e mutagenesi computazionale. Oltre a considerare il CTFR-mRNA, sono stati presi in considerazione altri target implicati nel processo di traduzione, quali la subunità 16S dell’rRNA batterico e la subunità 18S dell’rRNA eucariotico, che sono target comprovati di molti aminoglicosidi noti per la loro capacità di sopprimere l’attività di correzione svolta normalmente dal ribosoma; il fattore di rilascio eucariotico eRF1, per valutare la potenziale influenza di Ataluren sulla fine del processo di traduzione. Inoltre, è stato effettuato un confronto tra Ataluren, un suo nuovo promettente analogo NV2445 (acido 4-(5-(o-tolil)-1,3,4-ossadiazol-2-il)benzoico)2 e una serie di antibiotici aminoglicosidici. I risultati hanno confermato che mRNA è il più probabile target per Ataluren e i suoi derivati. I calcoli di energia libera di legame effettuati in seguito alla mutagenesi computazionale, hanno mostrato che il legame tra Ataluren e il codone di stop prematuro è fortemente influenzato dalla presenza di nucleotidi ausiliari nell’intorno genico.

Aims The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. Methods This was an observational prospective study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients’ medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio Results A total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth “boosted mixed model” included 20 variables was selected from the model 3, achieved the best predictive performance (AUC = 0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. Conclusion This study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.

To date, SARS-CoV-2 infectious disease, named COVID-19 by the World Health Organization (WHO) in February 2020, has caused millions of infections and hundreds of thousands of deaths. Despite the scientific community efforts, there are currently no approved therapies for treating this coronavirus infection. The process of new drug development is expensive and time-consuming, so that drug repurposing may be the ideal solution to fight the pandemic. In this paper, we selected the proteins encoded by SARS-CoV-2 and using homology modeling we identified the high-quality model of proteins. A structure-based pharmacophore modeling study was performed to identify the pharmacophore features for each target. The pharmacophore models were then used to perform a virtual screening against the DrugBank library (investigational, approved and experimental drugs). Potential inhibitors were identified for each target using XP docking and induced fit docking. MM-GBSA was also performed to better prioritize potential inhibitors. This study will provide new important comprehension of the crucial binding hot spots usable for further studies on COVID-19. Our results can be used to guide supervised virtual screening of large commercially available libraries.

Cystic fibrosis (CF) patients develop a severe form of the disease when the cystic fibrosis transmembrane conductance regulator (CFTR) gene is affected by nonsense mutations. Nonsense mutations are responsible for the presence of a premature termination codon (PTC) in the mRNA, creating a lack of functional protein. In this context, translational readthrough-inducing drugs (TRIDs) represent a promising approach to correct the basic defect caused by PTCs. By using computational optimization and biological screening, we identified three new small molecules showing high readthrough activity. The activity of these compounds has been verified by evaluating CFTR expression and functionality after treatment with the selected molecules in cells expressing nonsense&ndash, CFTR&ndash, mRNA. Additionally, the channel functionality was measured by the halide sensitive yellow fluorescent protein (YFP) quenching assay. All three of the new TRIDs displayed high readthrough activity and low toxicity and can be considered for further evaluation as a therapeutic approach toward the second major cause of CF.

Background Machine learning can assist clinicians in forecasting patients with COVID-19 who develop respiratory failure requiring mechanical ventilation. This analysis aimed to determine a 48 hours prediction of moderate to severe respiratory failure, as assessed with PaO2/FiO2 < 150 mmHg, in hospitalized patients with COVID-19 pneumonia. Methods This was an observational study that comprised all consecutive adult patients with COVID-19 pneumonia admitted to the Infectious Diseases Clinic of the University Hospital of Modena, Italy from 21 February to 6 April 2020. COVID-19 was confirmed with PCR positive nasopharyngeal swabs while the presence of pneumonia was radiologically confirmed. Patients received standard of care according to national guidelines for clinical management of SARS-CoV-2 infection. The patients' full medical history, demographic and epidemiological features, clinical data, complete blood count, coagulation, inflammatory and biochemical markers were routinely collected and aggregated in a clinically-oriented logical framework in order to build different datasets. The dataset was used to train a learning framework relying on Microsoft LightGBM and leveraging a hybrid approach, where clinical expertise is applied alongside a data-driven analysis. Shapley Additive exPlanations (SHAP) values were used to quantify the positive or negative impact of each variable included in the model on the predicted outcome. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio < 150 mmHg ([≥] 13.3 kPa) in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Results A total of 198 patients contributed to generate 1068 valuable observations which allowed to build 3 prediction models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth boosted mixed model which included 20 variables was selected from the model 3, achieved the best predictive performance (AUC=0.84). Its clinical performance was applied in a narrative case report as an example. Conclusion This study developed a machine learning algorithm, with a 84% prediction accuracy, which is potentially able to assist clinicians in decision making process with therapeutic implications.

In the current setting of global containment, peritoneal dialysis (PD) and home haemodialysis are the best modalities of renal replacement therapy (RRT) to reduce the rate of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Considering the shorter and easier training programme of PD compared to home haemodialysis, PD appears a practical solution for patients with end-stage renal disease to reduce the risk of hospital-acquired infection. PD offers the advantage of minimizing the risk of viral transmission through interpersonal contact that commonly occurs during the haemodialysis session and while travelling from home to the haemodialysis facility using public transport services. To overcome barriers to health care access due to the containment measures for this emerging disease, telemedicine is a useful and reliable tool for delivering health care without exposing patients to the risk of contact. However, novel issues including handling of potentially infected dialysate, caregivers' infectious risk and adequacy of PD in critically ill patients with acute respiratory distress syndrome remain to be clarified. In conclusion, PD should be preferred to the other modalities of RRT during the coronavirus disease 2019 (COVID-19) outbreak because it can be a solution to cope with the increased number of infected patients worldwide.

[Image: see text] Translational readthrough-inducing drugs (TRIDs) rescue the functional full-length protein expression in genetic diseases, such as cystic fibrosis, caused by premature termination codons (PTCs). Small molecules have been developed as TRIDs to trick the ribosomal machinery during recognition of the PTC. Herein we report a computational study to identify new TRID scaffolds. A pharmacophore approach was carried out on compounds that showed readthrough activity. The pharmacophore model applied to screen different libraries containing more than 87000 compounds identified four hit-compounds presenting scaffolds with diversity from the oxadiazole lead. These compounds have been synthesized and tested using the Fluc reporter harboring the UGA PTC. Moreover, the cytotoxic effect and the expression of the CFTR protein were evaluated. These compounds, a benzimidazole derivative (NV2899), a benzoxazole derivative (NV2913), a thiazole derivative (NV2909), and a benzene-1,3-disulfonate derivative (NV2907), were shown to be potential new lead compounds as TRIDs, boosting further efforts to address the optimization of the chemical scaffolds.

We compared the performance of molecular dynamics (MD)-derived pharmacophore modeling approaches, Common Hit Approach (CHA), and the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach, with semi-flexible constrained/unconstrained docking. The aim of this work is to enrich the hit-list of a virtual screening on CDK-2 known inhibitors as a case study. Cyclin-dependent kinases (CDKs) deregulation is associated with cancer growth. CDKs are an attractive target for anticancer agents. MD-derived pharmacophore models have been obtained with LigandScout 4.2.1. Docking analysis has been performed through Glide 7.6. The results highlighted the MYSHAPE approach has a better performance when multiple target-ligand complexes are available (ROC5% = 0.99). Moreover, the use of short molecular dynamics simulations improves the performance of the screening (ROC5% = 0.98–0.99) with respect to docking (ROC5% = 0.89–0.94). Outcomes of this work indicate that these approaches are highly suitable for prospective screening by a non-expert, and could be useful for the identification of novel CDK-2 inhibitors.

Nonsense mutations in the CFTR gene prematurely terminate translation of the CFTR mRNA leading to the production of a truncated protein that lacks normal function causing a more severe form of the cystic fibrosis (CF) disease. About 10% of patients affected by CF show a nonsense mutation. A potential treatment of this alteration is to promote translational readthrough of premature termination codons (PTCs) by Translational Readthrough Inducing Drugs (TRIDs) such as PTC124. In this context we aimed to compare the activity of PTC124 with analogues differing in the heteroatoms position in the central heterocyclic core. By a validated protocol consisting of computational screening, synthesis and biological tests we identified a new small molecule (NV2445) with 1,3,4-oxadiazole core showing a high readthrough activity. Moreover, we evaluated the CFTR functionality after NV2445 treatment in CF model systems and in cells expressing a nonsense-CFTR-mRNA. Finally, we studied the supramolecular interactions between TRIDs and CFTR-mRNA to assess the biological target/mechanism and compared the predicted ADME properties of NV2445 and PTC124.

Indicaxanthin is a bioactive and bioavailable betalain pigment extracted from Opuntia ficus indica fruits. Indicaxanthin has pharmacokinetics proprieties, rarely found in other phytochemicals, and it has been demonstrated that it provides a broad-spectrum of pharmaceutical activity, exerting antiproliferative, anti-inflammatory and neuromodulator effects. The discovery of the Indicaxanthin physiological targets plays an important role in understanding the biochemical mechanism. In this study, combined reverse pharmacophore mapping, reverse docking, and text-based database search identified Inositol Trisphosphate 3-Kinase (ITP3K-A), Glutamate carboxypeptidase II (GCPII), Leukotriene-A4 hydrolase (LTA4H), Phosphoserine phosphatase (HPSP), Phosphodiesterase 4D (PDE4D), AMPA receptor (GluA3 and GluA2 subunits) and Kainate receptor (GluK1 isoform) as potential targets for Indicaxanthin. These targets are implicated in neuromodulation, and inflammatory regulation, normally expressed mostly in the CNS, and expressed (or overexpressed) in cancer tissues (i.e. breast, thyroid and prostate cancer cells). Moreover, this study provides qualitative and quantitative information about dynamic interactions of Indicaxanthin at the binding site of target proteins, through molecular dynamics simulations and MM-GBSA.

Rationale The study of self-assembly process of surfactant molecules in gas phase is of actually interest for several theoretical and technological reasons related to their possible exploitation as drug carriers, protein shields and cleaning agents in gas phase. Methods Stability and fragmentation patterns of singly and multiply charged (either positively or negatively) aggregates of the surfactant (1R,2S)-dodecyl(2-hydroxy-1-methyl-2-phenylethyl) dimethyl ammonium bromide (DMEB) in gas phase have been studied by ion mobility mass spectrometry and tandem mass spectrometry. Molecular dynamics (MD) simulations of positively and negatively singly and multiply charged DMEB aggregates have been performed to get structural and energetics information. Finally, in order to get some clues on the DMEB growth mechanism, quantum mechanics calculations were carried out. Results It has been evidenced that positively and negatively singly charged aggregates at low collision energy decompose preferentially by loss of only one DMEB molecule. Increasing the collision energy, the loss of neutrals becomes increasingly abundant. Multiply charged DMEB aggregates are unstable and decompose forming singly charged monomers or dimers. MD simulations show reverse micelle like structures with polar heads somewhat segregated into the aggregate interior. Finally a good correlation between experimental and calculated collisional cross section was found. Conclusions The fragmentation pathways of DMEB charged species evidenced for singly charged aggregates features similar to that of other detergents aggregates, but multiply charged aggregates showed a system specific behavior. QM calculations on the optimized structures (21+, 31+, 11- and 21-) indicate that the most determinant interactions are due to an OH---Br hydrogen bonding that are also involved in the link between monomeric DMEB units. The MD models gave CCS values in good agreement with experimental ones, evidenced a less strict reverse micelle like structure and a quite spread bromine anion distribution.

Molecular dynamics (MD) simulations can be used, prior to virtual screening, to add flexibility to proteins and study them in a dynamic way. Furthermore, the use of multiple crystal structures of the same protein containing different co-crystallized ligands can help elucidate the role of the ligand on a protein's active conformation, and then explore the most common interactions between small molecules and the receptor. In this work, we evaluated the contribution of the combined use of MD on crystal structures containing the same protein but different ligands to examine the crucial ligand-protein interactions within the complexes. The study was carried out on peroxisome proliferator-activated receptor α (PPARα). Findings derived from the dynamic analysis of interactions were then used as features for pharmacophore generation and constraints for generating the docking grid for use in virtual screening. We found that information derived from short multiple MD simulations using different molecules within the binding pocket of the target can improve the early enrichment of active ligands in the virtual screening process for this receptor. In the end we adopted a consensus scoring based on docking score and pharmacophore alignment to rank our dataset. Our results showed an improvement in virtual screening performance in early recognition when screening was performed with the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach.

Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.

Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.