Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Pharmacological doses of melatonin impede cognitive decline in tau‐related Alzheimer models,once tauopathy is initiated,by restoring the autophagic flux

Alterations in autophagy are increasingly being recognized in the pathogenesis of proteinopathies like Alzheimer's disease (AD). This study was conducted to evaluate whether melatonin treatment could provide beneficial effects in an Alzheimer model related to tauopathy by improving the autophagic flux and, thereby, prevent cognitive decline. The injection of AAV‐hTau^P301L viral vectors and treatment/injection with okadaic acid were used to achieve mouse and human ex vivo, and in vivo tau‐related models. Melatonin (10 μmol/L) impeded oxidative stress, tau hyperphosphorylation, and cell death by restoring autophagy flux in the ex vivo models. In the in vivo studies, intracerebroventricular injection of AAV‐hTau^P301L increased oxidative stress, neuroinflammation, and tau hyperphosphorylation in the hippocampus 7 days after the injection, without inducing cognitive impairment; however, when animals were maintained for 28 days, cognitive decline was apparent. Interestingly, late melatonin treatment (10 mg/kg), starting once the alterations mentioned above were established (from day 7 to day 28), reduced oxidative stress, neuroinflammation, tau hyperphosphorylation, and caspase‐3 activation; these observations correlated with restoration of the autophagy flux and memory improvement. This study highlights the importance of autophagic dysregulation in tauopathy and how administration of pharmacological doses of melatonin, once tauopathy is initiated, can restore the autophagy flux, reduce proteinopathy, and prevent cognitive decline. We therefore propose exogenous melatonin supplementation or the development of melatonin derivatives to improve autophagy flux for the treatment of proteinopathies like AD.     

Accuracy of MRI-guided Versus Systematic Prostate Biopsy in Patients Under Active Surveillance: A Systematic Review and Meta-analysis

This meta-analysis focuses on the accuracy of upgrading to clinically significant prostate cancer (PCa) by multiparametric magnetic resonance imaging-targeted biopsy (MRI-TB) versus systematic biopsy (SB). We searched the Medline, Embase, Cochrane Central Register of Controlled Trials, Web of Science, Scopus, and Literatura Latino Americana em Ciências da Saúde databases through January 2020 for comparative, retrospective/prospective, paired-cohort, and randomized clinical trials with paired comparisons. The population consisted of patients with low-risk PCa in active surveillance with at least 1 index lesion on imaging. We evaluated the quality of evidence by using the Quality Assessment of Diagnostic Accuracy Studies-2 score. Group comparisons considered the differences between the area under the curve summary receiver operating characteristic curve in a 2-tailed method. We also compared the positive predictive value of the best single method (MRI-TB or SB) and the referral study test (combined biopsy, a combination of MRI-TB and SB). The meta-analysis included 6 studies enrolling 741 patients. The pooled sensitivity for the 2 groups was 0.79 (95% confidence interval, 0.74-0.83; I² = 75%) and 0.67 (95% confidence interval, 0.63-0.74; I² = 55.4%), respectively. The area under the curve for the MRI-TB and SB groups were 0.99 and 0.92 (P < .001), respectively. The positive predictive value for the MRI-TB and combined biopsy groups were similar. The accumulated evidence suggests better results for MRI-TB compared with SB. Therefore, use of MRI-TB alone may be preferable in patients in active surveillance harboring low-risk PCa.     

Computer-Aided Diagnosis of Vertebral Compression Fractures Using Convolutional Neural Networks and Radiomics

Journal of Digital Imaging - Vertebral Compression Fracture (VCF) occurs when the vertebral body partially collapses under the action of compressive forces. Non-traumatic VCFs can be secondary to...