First-in-Class Isonipecotamide-Based Thrombin and Cholinesterase Dual Inhibitors with Potential for Alzheimer Disease

Recently, the direct thrombin (thr) inhibitor dabigatran has proven to be beneficial in animal models of Alzheimer’s disease (AD). Aiming at discovering novel multimodal agents addressing thr and AD-related targets, a selection of previously and newly synthesized potent thr and factor Xa (fXa) inhibitors were virtually screened by the Multi-fingerprint Similarity Searching aLgorithm (MuSSeL) web server. The N-phenyl-1-(pyridin-4-yl)piperidine-4-carboxamide derivative 1, which has already been experimentally shown to inhibit thr with a Ki value of 6 nM, has been flagged by a new, upcoming release of MuSSeL as a binder of cholinesterase (ChE) isoforms (acetyl- and butyrylcholinesterase, AChE and BChE), as well as thr, fXa, and other enzymes and receptors. Interestingly, the inhibition potency of 1 was predicted by the MuSSeL platform to fall within the low-to-submicromolar range and this was confirmed by experimental Ki values, which were found equal to 0.058 and 6.95 μM for eeAChE and eqBChE, respectively. Thirty analogs of 1 were then assayed as inhibitors of thr, fXa, AChE, and BChE to increase our knowledge of their structure-activity relationships, while the molecular determinants responsible for the multiple activities towards the target enzymes were rationally investigated by molecular cross-docking screening

Exploitation of grape marc as functional substrate for lactic acid bacteria and bifidobacteria growth and enhanced antioxidant activity

This study aimed at using grape marc for the growth of lactic acid bacteria and bifidobacteria with the perspective of producing a functional ingredient having antioxidant activity. Lactobacillus plantarum 12A and PU1, Lactobacillus paracasei 14A, and Bifidobacterium breve 15A showed the ability to grow on grape marc (GM) based media. The highest bacterial cell density (>9.0 CFU/g) was found in GM added of 1% of glucose (GMG). Compared to un-inoculated and incubated control fermented GMG showed a decrease of carbohydrates and citric acid together with an increase of lactic acid. The content of several free amino acids and phenol compounds differed between samples. Based on the survival under simulated gastro-intestinal conditions, GMG was a suitable carrier of lactic acid bacteria and bifidobacteria strains. Compared to the control, cell-free supernatant (CFS) of fermented GMG exhibited a marked antioxidant activity in vitro. The increased antioxidant activity was confirmed using Caco-2 cell line after inducing oxidative stress, and determining cell viability and radical scavenging activity through MTT and DCFH-DA assays, respectively. Supporting these founding, the SOD-2 gene expression of Caco-2 cells also showed a lowest pro-oxidant effect induced by the four CFS of GMG fermented by lactic acid bacteria and bifidobacteria

Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer's Disease

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer's disease. The newly synthesized molecules spanned their IC50 values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the 'active' compounds from the 'inactive' (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of 'active' compounds, i.e., those achieving finite IC50 values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q2 = 0.596) and in the external test set (n = 14, r2ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein

KRAS Mutations Testing in Colorectal Carcinoma Patients in Italy: From Guidelines to External Quality Assessment

BACKGROUND: Monoclonal antibodies directed against the epidermal growth factor receptor (EGFR) have been approved for the treatment of patients with metastatic colorectal carcinoma (mCRC) that do not carry KRAS mutations. Therefore, KRAS testing has become mandatory to chose the most appropriate therapy for these patients. METHODOLOGY/PRINCIPAL FINDINGS: In order to guarantee the possibility for mCRC patients to receive an high quality KRAS testing in every Italian region, the Italian Association of Medical Oncology (AIOM) and the Italian Society of Pathology and Cytopathology -Italian division of the International Academy of Pathology (SIAPEC-IAP) started a program to improve KRAS testing. AIOM and SIAPEC identified a large panel of Italian medical oncologists, pathologists and molecular biologists that outlined guidelines for KRAS testing in mCRC patients. These guidelines include specific information on the target patient population, the biological material for molecular analysis, the extraction of DNA, and the methods for the mutational analysis that are summarized in this paper. Following the publication of the guidelines, the scientific societies started an external quality assessment scheme for KRAS testing. Five CRC specimens with known KRAS mutation status were sent to the 59 centers that participated to the program. The samples were validated by three referral laboratories. The participating laboratories were allowed to use their own preferred method for DNA extraction and mutational analysis and were asked to report the results within 4 weeks. The limit to pass the quality assessment was set at 100% of true responses. In the first round, only two centers did not pass (3%). The two centers were offered to participate to a second round and both centers failed again to pass. CONCLUSIONS: The results of this first Italian quality assessment for KRAS testing suggest that KRAS mutational analysis is performed with good quality in the majority of Italian centers

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022)

De Novo Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization

Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated de novo design of compounds as a result of a humanlike creative process. In the present study, we conceived a novel pair-based multiobjective approach implemented in an adapted SMILES generative algorithm based on recurrent neural networks for the automated de novo design of new molecules whose overall features are optimized by finding the best trade-offs among relevant physicochemical properties (MW, logP, HBA, HBD) and additional similarity-based constraints biasing specific biological targets. In this respect, we carried out the de novo design of chemical libraries targeting neuraminidase, acetylcholinesterase, and the main protease of severe acute respiratory syndrome coronavirus 2. Several quality metrics were employed to assess drug-likeness, chemical feasibility, diversity content, and validity. Molecular docking was finally carried out to better evaluate the scoring and posing of the de novo generated molecules with respect to X-ray cognate ligands of the corresponding molecular counterparts. Our results indicate that artificial intelligence and multiobjective optimization allow us to capture the latent links joining chemical and biological aspects, thus providing easy-to-use options for customizable design strategies, which are especially effective for both lead generation and lead optimization. The algorithm is freely downloadable at https://github.com/alberdom88/moo-denovo and all of the data are available as Supporting Information

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning

: The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CB1R and CB2R, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CB1R and CB2R, generating subtype-selective ligands is still an open challenge. In this work, the Cannabinoid Iterative Revaluation for Classification and Explanation (CIRCE) compound prediction platform has been generated based on explainable machine learning to support the design of selective CB1R and CB2R ligands. Multilayer classifiers were combined with Shapley value analysis to facilitate explainable predictions. In test calculations, CIRCE predictions reached ∼80% accuracy and structural features determining ligand predictions were rationalized. CIRCE was designed as a web-based prediction platform that is made freely available as a part of our study

Clinical validation of atlas-based auto-segmentation of pelvic volumes and normal tissue in rectal tumors using auto-segmentation computed system

To evaluate in two different settings - clinical practice and education/training - the reliability, time efficiency and the ideal sequence of an atlas-based auto-segmentation system in pelvic delineation of locally advanced rectal cancer

Rational Discovery of Antiviral Whey Protein-Derived Small Peptides Targeting the SARS-CoV-2 Main Protease

In the present work, and for the first time, three whey protein-derived peptides (IAEK, IPAVF, MHI), endowed with ACE inhibitory activity, were examined for their antiviral activity against the SARS-CoV-2 3C-like protease (3CLpro) and Human Rhinovirus 3C protease (3Cpro) by employing molecular docking. Computational studies showed reliable binding poses within 3CLpro for the three investigated small peptides, considering docking scores as well as the binding free energy values. Validation by in vitro experiments confirmed these results. In particular, IPAVF exhibited the highest inhibitory activity by returning an IC50 equal to 1.21 μM; it was followed by IAEK, which registered an IC50 of 154.40 μM, whereas MHI was less active with an IC50 equal to 2700.62 μM. On the other hand, none of the assayed peptides registered inhibitory activity against 3Cpro. Based on these results, the herein presented small peptides are introduced as promising molecules to be exploited in the development of “target-specific antiviral” agents against SARS-CoV-2