Human sirtuin 2 inhibitors, their mechanisms and binding modes.

The silent information regulator (sirtuin) is a family of enzymes involved in epigenetic processes with lysine deacetylase activity, having as substrates histones and other proteins. They participate in a wide range of cellular and pathologic processes, such as gene expression, cell division and motility, oxidative-induced stress management, metabolic control and carcinogenesis, among others, thus presenting as interesting therapeutic targets. In this article, the authors describe the inhibitory mechanisms and binding modes of the human sirtuin 2 (hSIRT2) inhibitors, which had their complexes with the enzyme structurally characterized. The results help pave the way for the rational designing of new hSIRT2 inhibitors and the development of novel therapeutic agents targeting this epigenetic enzyme.

Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors.

Major depressive disorder (MDD) is characterized by a series of disabling symptoms like anhedonia, depressed mood, lack of motivation for daily tasks and self-extermination thoughts. The monoamine deficiency hypothesis states that depression is mainly caused by a deficiency of monoamine at the synaptic cleft. Thus, major efforts have been made to develop drugs that inhibit serotonin (SERT), norepinephrine (NET) and dopamine (DAT) transporters and increase the availability of these monoamines. Current gold standard treatment of MDD uses drugs that target one or more monoamine transporters. Triple reuptake inhibitors (TRIs) can target SERT, NET, and DAT simultaneously, and are believed to have the potential to be early onset antidepressants. Quantitative structure-activity relationship models were developed using machine learning algorithms in order to predict biological activities of a series of triple reuptake inhibitor compounds that showed in vitro inhibitory activity against multiple targets. The results, using mostly interpretable descriptors, showed that the internal and external predictive ability of the models are adequate, particularly of the DAT and NET by Random Forest and Support Vector Machine models. The current work shows that models developed from relatively simple, chemically interpretable descriptors can predict the activity of TRIs with similar structure in the applicability domain using ML methods.Communicated by Ramaswamy H. Sarma.

Hydroquinone Exposure Worsens Rheumatoid Arthritis through the Activation of the Aryl Hydrocarbon Receptor and Interleukin-17 Pathways.

Rheumatoid arthritis (RA) development is strongly associated with cigarette smoke exposure, which activates the aryl hydrocarbon receptor (AhR) as a trigger for Th17 inflammatory pathways. We previously demonstrated that the exposure to hydroquinone (HQ), one of the major compounds of cigarette tar, aggravates the arthritis symptomatology in rats. However, the mechanisms related to the HQ-related RA still remain elusive. Cell viability, cytokine secretion, and gene expression were measured in RA human fibroblast-like synoviocytes (RAHFLS) treated with HQ and stimulated or not with TNF-α. Antigen-induced arthritis (AIA) was also elicited in wild type (WT), AhR -/- or IL-17R -/- C57BL/6 mice upon daily exposure to nebulized HQ (25ppm) between days 15 to 21. At day 21, mice were challenged with mBSA and inflammatory parameters were assessed. The in vitro HQ treatment up-regulated TNFR1, TNFR2 expression, and increased ROS production. The co-treatment of HQ and TNF-α enhanced the IL-6 and IL-8 secretion. However, the pre-incubation of RAHFLS with an AhR antagonist inhibited the HQ-mediated cell proliferation and gene expression profile. About the in vivo approach, the HQ exposure worsened the AIA symptoms (edema, pain, cytokines secretion and NETs formation) in WT mice. These AIA effects were abolished in HQ-exposed AhR -/- and IL-17R -/- animals though. Our data demonstrated the harmful HQ influence over the onset of arthritis through the activation and proliferation of synoviocytes. The HQ-related RA severity was also associated with the activation of AhR and IL-17 pathways, highlighting how cigarette smoke compounds can contribute to the RA progression.

Parasitic sirtuin 2 as an opportunity in drug discovery.

Infections caused by protozoans remain a public health issue, especially in tropical countries. Serious adverse events, lack of efficacy at the different stages of the infection and routes of administration that have a negative impact on treatment adherence are some of the problems with currently available therapy against these diseases. Here we describe an epigenetic target, sirtuin 2 and its related proteins, that is promising given the results in phenotypic assays and in vivo models against Sir2 of Plasmodium falciparum, Leishmania donovani, Leishmania infantum, Schistosoma mansoni, Trypanosoma brucei and Trypanosoma cruzi parasites. The results we present highlight how this target can be extensively explored and how its inhibitors might be employed in the clinic.

Insights into Newly Approved Drugs from a Medicinal Chemistry Perspective.

The development of new drugs is becoming notably harder each decade. To overcome the present pitfalls in the drug development pipeline, such as those related to potency, selectivity, or absorption, distribution, metabolism, excretion and toxicity properties, medicinal chemistry strategies need to be in continuous evolution and need to become even more multidisciplinary. In this review, we present how structure-based, ligand-based, and fragment-based drug design (SBDD, LBDD, and FBDD, respectively) and their respective techniques were used for the design and optimization of successful cases of New Molecular Entities (NMEs) approved by the Food and Drug Administration (FDA).

Antiplasmodial activity of sulfonylhydrazones: in vitro and in silico approaches.

Malaria is still a life-threatening public health issue, and the upsurge of resistant strains requires continuous generation of active molecules. In this work, 35 sulfonylhydrazone derivatives were synthesized and evaluated against Plasmodium falciparum chloroquine-sensitive (3D7) and resistant (W2) strains. The most promising compound, 5b, had an IC50 of 0.22 µM against W2 and was less cytotoxic and 26-fold more selective than chloroquine. The structure-activity relationship model, statistical analysis and molecular modeling studies suggested that antiplasmodial activity was related to hydrogen bond acceptor count, molecular weight and partition coefficient of octanol/water and displacement of frontier orbitals to the heteroaromatic ring beside the imine bond. This study demonstrates that the synthesized molecules with a simple scaffold allow the hit-to-lead process for new antimalarials to commence.

Ligand and structure-based virtual screening applied to the SARS-CoV-2 main protease: an in silico repurposing study.

Aim: The identification of drugs for the coronavirus disease-19 pandemic remains urgent. In this manner, drug repurposing is a suitable strategy, saving resources and time normally spent during regular drug discovery frameworks. Essential for viral replication, the main protease has been explored as a promising target for the drug discovery process. Materials & methods: Our virtual screening pipeline relies on the known 3D properties of noncovalent ligands and features of crystalized complexes, applying consensus analyses in each step. Results: Two oral (bedaquiline and glibenclamide) and one buccal drug (miconazole) presented 3D similarity to known ligands, reasonable predicted binding modes and micromolar predicted binding affinity values. Conclusion: We identified three approved drugs as promising inhibitors of the main viral protease and suggested design insights for future studies for development of novel selective inhibitors.

Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases.

Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs.