Convolutional architectures for virtual screening

Background: A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results: A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% in high precision discrimination). Conclusion: The proposed architecture outperforms state-of-the-art ML approaches, and some interesting insights on molecular fingerprints are devised

Resolving a guanine-quadruplex structure in the SARS-CoV-2 genome through circular dichroism and multiscale molecular modeling

The genome of SARS-CoV-2 coronavirus is made up of a single-stranded RNA fragment that can assume a specific secondary structure, whose stability can influence the virus's ability to reproduce. Recent studies have identified putative guanine quadruplex sequences in SARS-CoV-2 genome fragments that are involved in coding for both structural and non-structural proteins. In this contribution, we focus on a specific G-rich sequence referred to as RG-2, which codes for the non-structural protein 10 (Nsp10) and assumes a guanine-quadruplex (G4) arrangement. We provide the secondary structure of RG-2 G4 at atomistic resolution by molecular modeling and simulation, validated by the superposition of experimental and calculated electronic circular dichroism spectra. Through both experimental and simulation approaches, we have demonstrated that pyridostatin (PDS), a widely recognized G4 binder, can bind to and stabilize RG-2 G4 more strongly than RG-1, another G4 forming sequence that was previously proposed as a potential target for antiviral drug candidates. Overall, this study highlights RG-2 as a valuable target to inhibit the translation and replication of SARS-CoV-2, paving the way towards original therapeutic approaches against emerging RNA viruses.Parallel or hybrid? A combination of multiscale molecular modeling and circular dichroism is used to predict a G-quadruplex structure at atomistic resolution in the SARS-CoV-2 genome

A New Family of Jumonji C Domain-Containing KDM Inhibitors Inspired by Natural Product Purpurogallin

Aberrant epigenetic modifications are involved in cancer development. Jumonji C domain-containing histone lysine demethylases (KDMs) are found mainly up-regulated in breast, prostate, and colon cancer. Currently, growing interest is focusing on the identification and development of new inhibitors able to block the activity of KDMs and thus reduce tumor progression. KDM4A is known to play a role in several cellular physiological processes, and was recently found overexpressed in a number of pathological states, including cancer. In this work, starting from the structure of purpurogallin 9aa, previously identified as a natural KDM4A inhibitor, we synthesized two main sets of compound derivatives in order to improve their inhibitory activity against KDM4A in vitro and in cells, as well as their antitumor action. Based on the hypothetical biogenesis of the 5-oxo-5H-benzo[7]annulene skeleton of the natural product purpurogallin (Salfeld, 1960; Horner et al., 1961; Dürckheimer and Paulus, 1985; Tanaka et al., 2002; Yanase et al., 2005) the pyrogallol and catechol units were first combined with structural modifications at different positions of the aryl ring using enzyme-mediated oxidative conditions, generating a series of benzotropolone analogs. Two of the synthetic analogs of purpurogallin, 9ac and 9bc, showed an efficient inhibition (50 and 80%) of KDM4A in enzymatic assays and in cells by increasing levels of its specific targets, H3K9me3/2 and H3K36me3. However, these two compounds/derivatives did not induce cell death. We then synthesized a further set of analogs of these two compounds with greater structural diversification. The most potent of these analogs, 9bf, displayed the highest KDM4A inhibitory enzymatic activity in vitro (IC50 of 10.1 and 24.37 μM) in colon cancer cells, and the strongest antitumor action in several solid and hematological human cancer cell lines with no toxic effect in normal cells. Our findings suggest that further development of this compound and its derivatives may lead to the identification of new therapeutic antitumor agents acting through inhibition of KDM4A

3-(6-Phenylimidazo [2,1-b][1,3,4]thiadiazol-2-yl)-1HIndole derivatives as new anticancer agents in the treatment of pancreatic ductal adenocarcinoma

A new series of imidazo[2,1-b][1,3,4]thiadiazole derivatives was efficiently synthesized and screened for their in vitro antiproliferative activity on a panel of pancreatic ductal adenocarcinoma (PDAC) cells, including SUIT-2, Capan-1 and Panc-1. Compounds 9c and 9l, showed relevant in vitro antiproliferative activity on all three pre-clinical models with half maximal inhibitory concentration (IC50) ranging from 5.11 to 10.8 μM, while the compounds 9e and 9n were active in at least one cell line. In addition, compound 9c significantly inhibited the migration rate of SUIT-2 and Capan-1 cells in the scratch wound-healing assay. In conclusion, our results will support further studies to increase the library of imidazo [2,1-b][1,3,4] thiadiazole derivatives for deeper understanding of the relationship between biological activity of the compounds and their structures in the development of new antitumor compounds against pancreatic diseases

Validation of a HLA-A2 tetramer flow cytometric method, IFNgamma real time RT-PCR, and IFNgamma ELISPOT for detection of immunologic response to gp100 and MelanA/MART-1 in melanoma patients

<p>Abstract</p> <p>Background</p> <p>HLA-A2 tetramer flow cytometry, IFNγ real time RT-PCR and IFNγ ELISPOT assays are commonly used as surrogate immunological endpoints for cancer immunotherapy. While these are often used as research assays to assess patient's immunologic response, assay validation is necessary to ensure reliable and reproducible results and enable more accurate data interpretation. Here we describe a rigorous validation approach for each of these assays prior to their use for clinical sample analysis.</p> <p>Methods</p> <p>Standard operating procedures for each assay were established. HLA-A2 (A*0201) tetramer assay specific for gp100_209(210M)and MART-1_26–35(27L), IFNγ real time RT-PCR and ELISPOT methods were validated using tumor infiltrating lymphocyte cell lines (TIL) isolated from HLA-A2 melanoma patients. TIL cells, specific for gp100 (TIL 1520) or MART-1 (TIL 1143 and TIL1235), were used alone or spiked into cryopreserved HLA-A2 PBMC from healthy subjects. TIL/PBMC were stimulated with peptides (gp100₂₀₉, gp100_pool, MART-1_27–35, or influenza-M1 and negative control peptide HIV) to further assess assay performance characteristics for real time RT-PCR and ELISPOT methods. Validation parameters included specificity, accuracy, precision, linearity of dilution, limit of detection (LOD) and limit of quantification (LOQ). In addition, distribution was established in normal HLA-A2 PBMC samples. Reference ranges for assay controls were established.</p> <p>Results</p> <p>The validation process demonstrated that the HLA-A2 tetramer, IFNγ real time RT-PCR, and IFNγ ELISPOT were highly specific for each antigen, with minimal cross-reactivity between gp100 and MelanA/MART-1. The assays were sensitive; detection could be achieved at as few as 1/4545–1/6667 cells by tetramer analysis, 1/50,000 cells by real time RT-PCR, and 1/10,000–1/20,000 by ELISPOT. The assays met criteria for precision with %CV < 20% (except ELISPOT using high PBMC numbers with %CV < 25%) although flow cytometric assays and cell based functional assays are known to have high assay variability. Most importantly, assays were demonstrated to be effective for their intended use. A positive IFNγ response (by RT-PCR and ELISPOT) to gp100 was demonstrated in PBMC from 3 melanoma patients. Another patient showed a positive MART-1 response measured by all 3 validated methods.</p> <p>Conclusion</p> <p>Our results demonstrated the tetramer flow cytometry assay, IFNγ real-time RT-PCR, and INFγ ELISPOT met validation criteria. Validation approaches provide a guide for others in the field to validate these and other similar assays for assessment of patient T cell response. These methods can be applied not only to cancer vaccines but to other therapeutic proteins as part of immunogenicity and safety analyses.</p

Common Gene Therapy Viral Vectors Do Not Efficiently Penetrate Sputum from Cystic Fibrosis Patients

Norwalk virus and human papilloma virus, two viruses that infect humans at mucosal surfaces, have been found capable of rapidly penetrating human mucus secretions. Viral vectors for gene therapy of Cystic Fibrosis (CF) must similarly penetrate purulent lung airway mucus (sputum) to deliver DNA to airway epithelial cells. However, surprisingly little is known about the rates at which gene delivery vehicles penetrate sputum, including viral vectors used in clinical trials for CF gene therapy. We find that sputum spontaneously expectorated by CF patients efficiently traps two viral vectors commonly used in CF gene therapy trials, adenovirus (d∼80 nm) and adeno-associated virus (AAV serotype 5; d∼20 nm), leading to average effective diffusivities that are ∼3,000-fold and 12,000-fold slower than their theoretical speeds in water, respectively. Both viral vectors are slowed by adhesion, as engineered muco-inert nanoparticles with diameters as large as 200 nm penetrate the same sputum samples at rates only ∼40-fold reduced compared to in pure water. A limited fraction of AAV exhibit sufficiently fast mobility to penetrate physiologically thick sputum layers, likely because of the lower viscous drag and smaller surface area for adhesion to sputum constituents. Nevertheless, poor penetration of CF sputum is likely a major contributor to the ineffectiveness of viral vector based gene therapy in the lungs of CF patients observed to date

IgG4-Related Diseases and the Liver

IgG4-related disease (IgG4-RD) is a systemic illness including autoimmune pancreatitis and IgG4-related sclerosing cholangitis (IgG4-SC). Although hepatic presentation of IgG4-RD has been reported, whether intrahepatic small bile ducts and hepatocytes are direct targets of IgG4-RD is uncertain. IgG4-RD is pathologically characterized by the numerous IgG4+ cells found in affected organs, but this IgG4 positivity is also frequently found in extrahepatic cholangiocarcinoma and is prominent, albeit rarely, in other hepatobiliary diseases including primary sclerosing cholangitis and autoimmune hepatitis. Moreover, cholangiocarcinoma arising from precedent IgG4-SC and IgG4-SC accompanying precursor lesions of cholangiocarcinoma (biliary intraepithelial neoplasia) are also reported. Diagnostic criteria for IgG-RD and IgG4-SC were recently proposed, but each individual case should be diagnosed clinicopathologically on the basis of its individual features. © Springer Japan 2016.[Book Chapter

Exploring the SARS-CoV-2 proteome in the search of potential inhibitors via structure-based pharmacophore modeling/docking approach

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