Notes

Structurel evaluation from the bioplastic (poly-3-hydroxybutyrate) created by Bacillus flexus Azu-A2 through cheeses whey protein valorization.
Beginning with opium itself, natural and synthetic opioids have been used as analgesics for over 8000 years and were likely abused as drugs of recreation for that long as well. However, the "opioid crisis" resulted in attempts to avoid or limit opioid analgesics in favor of other therapies and methods. Mu opioid agonists can be effective analgesics but suffer from addiction, tolerance, and dangerous, sometimes fatal, side effects. One exception to this generalization is dezocine (Dalgan), a mixed mu/kappa opioid partial agonist. Dezocine is at least as effective as morphine in reducing acute pain in animal models and clinical applications such as postoperative pain. And while dezocine was discontinued in western markets in 2011, it has become the favored opioid analgesic in China, capturing over 40% of the market. Additionally, dezocine possesses norepinephrine uptake inhibitory activity, which may synergize with mu agonism in the case of acute pain treatment and possibly endow the drug with antinociceptive activity in neuropathic pain conditions. This Innovations article summarizes the history and properties of dezocine and presents evidence and rationale for why dezocine has undergone a resurrection.Herein, we report a novel series of highly potent and selective triazolothiadiazole c-Met inhibitors. Starting with molecule 5, we have applied structure-based drug design principles to identify the triazolothiadiazole ring system. We successfully replaced the metabolically unstable phenolic moiety with a quinoline group. Further optimization around the 5,6 bicyclic moiety led to the identification of 21. Compound 21 suffered from PDE3 selectivity issues and subsequent, structurally informed design led to the discovery of compound 23. Compound 23 has exquisite kinase selectivity, excellent potency, favorable ADME profile, and showed dose-dependent antitumor efficacy in a SNU-5 gastric cancer xenograft model.Myotonic dystrophy type 1 originates from d(CTG·CAG) repeats that undergo aberrant expansion during normal processing because the d(CTG) repeat forms stable hairpin structures. Bidirectional transcription of d(CTG·CAG) yields two RNA transcripts that undergo repeat-associated non-ATG (RAN) translation to form homopolymeric proteins. Thus, both the r(CUG) transcript and the r(CAG) transcript are known to be toxic. We report a pairwise fragment-based, target-guided approach to screen for proximity-induced click dimers formed on the nucleic acid template. This screen uses an azide/alkyne clickable fragment library of nucleic acid-binding ligands incubated in parallel, pairwise reactions as an alternative to our previously reported one-pot screening method. MALDI-TOF mass spectroscopy was used to detect template assisted click products. Hit compounds inhibited the in vitro transcription of d(CTG·CAG)90 bidirectionally with IC50 values in the low micromolar range. This approach may be broadly applicable to other trinucleotide repeat diseases and in targeting other disease-associated nucleic acid sequences.Identifying potential ligand binding cavities is a critical step in structure-based screening of biomolecular targets. Cavity mapping methods can detect such binding cavities; however, for ribonucleic acid (RNA) targets, determining which of the detected cavities are "ligandable" remains an unsolved challenge. In this study, we trained a set of machine learning classifiers to distinguish ligandable RNA cavities from decoy cavities. Application of our classifiers to two independent test sets demonstrated that we could recover ligandable cavities from decoys with an AUC > 0.83. Interestingly, when we applied our classifiers to a library of modeled structures of the HIV-1 transactivation response (TAR) element RNA, we found that several of the conformers that harbored cavities with high ligandability scores resembled known holo-TAR structures. On the basis of our results, we envision that our classifiers could find utility as a tool to parse RNA structures and prospectively mine for ligandable binding cavities and, in so doing, facilitate structure-based virtual screening efforts against RNA drug targets.Site-specific incorporation of 2'-modifications and neutral linkages in the deoxynucleotide gap region of toxic phosphorothioate (PS) gapmer ASOs can enhance therapeutic index and safety. In this manuscript, we determined the effect of introducing 2',5'-linked RNA in the deoxynucleotide gap region on toxicity and potency of PS ASOs. Our results demonstrate that incorporation of 2',5'-linked RNA in the gap region dramatically improved hepatotoxicity profile of PS-ASOs without compromising potency and provide a novel alternate chemical approach for improving therapeutic index of ASO drugs.RNA targeting has gained traction over the past decade. It has become clear that dysregulation of RNA can be linked to many diseases, leading to a need for new scaffolds recognizing RNA specifically. Long noncoding RNAs are emerging as key controllers of gene expression and potential therapeutic targets. However, traditional targeting methods have overwhelmingly been focused on proteins. In this study, we used a protein computational tool and found several possible targetable pockets in a structurally characterized long noncoding RNA, MALAT1. Screening against those identified pockets revealed several hit compounds. We tested the binding of those compounds to MALAT1 RNA and tRNA as a negative control, using SPR. While several compounds were nonspecific binders, others were able to recognize MALAT1 specifically. One of them, MTC07, has an apparent affinity of 400.2 ± 14.4 μM. Although it has weak affinity, MTC07 is the first compound targeting MALAT1 originating from in silico docking.RNA contributes to disease pathobiology and is an important therapeutic target. The downstream biology of disease-causing RNAs can be short-circuited with small molecules that recognize structured regions. The discovery and optimization of small molecules interacting with RNA is, however, challenging. PFK158 Herein, we demonstrate a massively parallel one-bead-one-compound methodology, employed to optimize the linker region of a dimeric compound that binds the toxic r(CUG) repeat expansion [r(CUG)exp] causative of myotonic dystrophy type 1 (DM1). Indeed, affinity selection on a 331,776-member library allowed the discovery of a compound with enhanced potency both in vitro (10-fold) and in DM1-patient-derived myotubes (5-fold). Molecular dynamics simulations revealed additional interactions between the optimized linker and the RNA, resulting in ca. 10 kcal/mol lower binding free energy. The compound was conjugated to a cleavage module, which directly cleaved the transcript harboring the r(CUG)exp and alleviated disease-associated defects.Targeting RNAs using small molecules is an emerging field of medicinal chemistry and holds promise for the discovery of efficient tools for chemical biology. MicroRNAs are particularly interesting targets since they are involved in a number of pathologies such as cancers. Indeed, overexpressed microRNAs in cancer are oncogenic and various series of inhibitors of microRNAs biogenesis have been developed in recent years. Here, we describe the structure-based design of new efficient inhibitors of microRNA-21. Starting from a previously identified hit, we performed biochemical studies and molecular docking to design a new series of optimized conjugates of neomycin aminoglycoside with artificial nucleobases and amino acids. Investigation about the mode of action and the site of the interaction of the newly synthesized compounds allowed for the description of structure-activity relationships and the identification of the most important parameters for miR-21 inhibition.Remodelin is a putative small molecule inhibitor of the RNA acetyltransferase NAT10 which has shown preclinical efficacy in models of the premature aging disease Hutchinson-Gilford Progeria Syndrome (HGPS). Here we evaluate remodelin's assay interference characteristics and effects on NAT10-catalyzed RNA cytidine acetylation. We find the remodelin chemotype constitutes a cryptic assay interference compound, which does not react with small molecule thiols but demonstrates protein reactivity in ALARM NMR and proteome-wide affinity profiling assays. Biophysical analyses find no direct evidence for interaction of remodelin with the NAT10 acetyltransferase active site. Cellular studies verify that N4-acetylcytidine (ac4C) is a nonredundant target of NAT10 activity in human cell lines and find that this RNA modification is not affected by remodelin treatment in several orthogonal assays. These studies display the potential for remodelin's chemotype to interact with multiple protein targets in cells and indicate remodelin should not be applied as a specific chemical inhibitor of NAT10-catalyzed RNA acetylation.MicroRNAs (miRNAs) are a family of small noncoding RNAs that regulate gene expression. Due to their important activity in the fine-tuning of protein translation, abnormal expression of miRNAs has been linked to many human diseases, making the targeting of miRNAs attractive as a novel therapeutic strategy. Accordingly, researchers have been heavily engaged in the discovery of small molecule modulators of miRNAs. With an interest in the identification of new chemical space for targeting miRNAs, we developed a high-throughput screening (HTS) technology, catalytic enzyme-linked click chemistry assay (cat-ELCCA), aimed at the discovery of small molecule ligands for pre-miR-21, a miRNA that is frequently overexpressed in human cancers. From our HTS campaign, we found that natural products, a source of many impactful human medicines, may be a promising source of potential pre-miR-21-selective maturation inhibitors. Herein we describe our first efforts in natural product inhibitor discovery leading to the identification of a depsipeptide class of natural products as RNA-binding inhibitors of Dicer-mediated miRNA processing.Not too long ago, the concept of selectively targeting mRNA with small molecules was perceived as a formidable scientific challenge. The discovery of small molecule splicing modifiers and the development of risdiplam for the treatment of spinal muscular atrophy (SMA) have firmly established proof of concept for this exciting new platform and transformed a scientific curiosity into a viable technology to target disease. Today, several approaches to target mRNA with small molecules, supported by biophysical and screening methods, are in place to deliver new drugs with high therapeutic relevance.
Using the MTN-020/ASPIRE HIV prevention trial as a motivating example, our objective is to construct a joint model for the HIV exposure process through vaginal intercourse and the time to HIV infection in a population of sexually active women. By modeling participants' HIV infection in terms of exposures, rather than time exposed, our aim is to obtain a valid estimate of the per-act efficacy of a preventive intervention.

Within the context of HIV prevention trials, in which the frequency of sex acts is self-reported periodically by the participants, we model the exposure process of the trial participants with a non-homogeneous Poisson process. This approach allows for variability in the rate of sexual contacts between participants as well as variability in the rate of sexual contacts over time. The time to HIV infection for each participant is modeled as the time to the exposure that results in HIV infection, based on the modeled sexual contact rate. We propose an empirical Bayes approach for estimation.

We report the results of a simulation study where we evaluate the performance of our proposed approachandcompareittothetraditionalapproachofestimatingtheoverallreductioninHIVincidenceusing a Proportional Hazards Cox model.
Read More: https://www.selleckchem.com/products/pfk158.html