New drug discovery strategies for the treatment of benznidazole-resistance in Trypanosoma cruzi, the causative agent of Chagas disease.

INTRODUCTION: Benznidazole, the drug of choice for treating Chagas Disease (CD), has significant limitations, such as poor cure efficacy, mainly in the chronic phase of CD, association with side effects, and parasite resistance. Understanding parasite resistance to benznidazole is crucial for developing new drugs to treat CD. AREAS COVERED: Here, the authors review the current understanding of the molecular basis of benznidazole resistance. Furthermore, they discuss the state-of-the-art methods and critical outcomes employed to evaluate the efficacy of potential drugs against T. cruzi, aiming to select better compounds likely to succeed in the clinic. Finally, the authors describe the different strategies employed to overcome resistance to benznidazole and find effective new treatments for CD. EXPERT OPINION: Resistance to benznidazole is a complex phenomenon that occurs naturally among T. cruzi strains. The combination of compounds that inhibit different metabolic pathways of the parasite is an important strategy for developing a new chemotherapeutic protocol.

SETDB1 as a cancer target: challenges and perspectives in drug design.

Genome stability is governed by chromatin structural dynamics, which modify DNA accessibility under the influence of intra- and inter-nucleosomal contacts, histone post-translational modifications (PTMs) and variations, besides the activity of ATP-dependent chromatin remodelers. These are the main ways by which chromatin dynamics are regulated and connected to nuclear processes, which when dysregulated can frequently be associated with most malignancies. Recently, functional crosstalk between histone modifications and chromatin remodeling has emerged as a critical regulatory method of transcriptional regulation during cell destiny choice. Therefore, improving therapeutic outcomes for patients by focusing on epigenetic targets dysregulated in malignancies should help prevent cancer cells from developing resistance to anticancer treatments. For this reason, SET domain bifurcated histone lysine methyltransferase 1 (SETDB1) has gained a lot of attention recently as a cancer target. SETDB1 is a histone lysine methyltransferase that plays an important role in marking euchromatic and heterochromatic regions. Hence, it promotes the silencing of tumor suppressor genes and contributes to carcinogenesis. Some studies revealed that SETDB1 was overexpressed in various human cancer types, which enhanced tumor growth and metastasis. Thus, SETDB1 appears to be an attractive epigenetic target for new cancer treatments. In this review, we have discussed the effects of its overexpression on the progression of tumors and the development of inhibitor drugs that specifically target this enzyme.

Binding Evolution of the Dengue Virus Envelope Against DC-SIGN: A Combined Approach of Phylogenetics and Molecular Dynamics Analyses Over 30 Years of Dengue Virus in Brazil.

The Red Queen Hypothesis (RQH), derived from Lewis Carroll's "Through the Looking-Glass", postulates that organisms must continually adapt in response to each other to maintain relative fitness. Within the context of host-pathogen interactions, the RQH implies an evolutionary arms race, wherein viruses evolve to exploit hosts and hosts evolve to resist viral invasion. This study delves into the dynamics of the RQH in the context of virus-cell interactions, specifically focusing on virus receptors and cell receptors. We observed multiple virus-host systems and noted patterns of co-evolution. As viruses evolved receptor-binding proteins to effectively engage with cell receptors, cells countered by altering their receptor genes. This ongoing mutual adaptation cycle has influenced the molecular intricacies of receptor-ligand interactions. Our data supports the RQH as a driving force behind the diversification and specialization of both viral and host cell receptors. Understanding this co-evolutionary dance offers insights into the unpredictability of emerging viral diseases and potential therapeutic interventions. Future research is crucial to dissect the nuanced molecular changes and the broader ecological consequences of this ever-evolving battle. Here, we combine phylogenetic inferences, structural modeling, and molecular dynamics analyses to describe the epidemiological characteristics of major Brazilian DENV strains that circulated from 1990 to 2022 from a combined perspective, thus providing us with a more detailed picture on the dynamics of such interactions over time.

Convergent QSAR Models for the Prediction of Cruzain Inhibitors.

Chagas disease is a parasitosis caused by Trypanosoma cruzi. Cruzain, the major cysteine protease from T. cruzi, is an excellent therapeutic target in the search for antichagasic drugs. It is important in the role of cell invasion, replication, differentiation, and metabolism of the parasite. In this work, we developed and assessed multiple quantitative structure-activity relationship (QSAR) models for a set of 61 cruzain inhibitors. These models include two-dimensional (2D) QSAR, three-dimensional (3D) QSAR, such as comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), and Hologram QSAR (HQSAR). In total, we generated 10 major and 114 minor model variations. Molecular docking was used to successfully align the molecules. All CoMFA and CoMSIA models, which incorporate multiple fields, demonstrated robustness in our analysis. Steric fields exhibited satisfactory convergence in the contour maps, while the electrostatic field converged into a single small region. The HQSAR model taking into consideration only Atoms and Connectivity, with fragment sizes ranging from two to five atoms, was considered the best of the HQSAR variations, despite exhibiting a higher level of deviance. In total, 78 model variations meet the minimum requirements to be considered acceptable. We found that using as few as five descriptors it is possible to obtain robust results with 2D-QSAR. Models such as Random Forest, Tree Ensemble, Linear Regression, and HQSAR are recommended for working with large data sets, while the 3D-QSAR models are intended to study the geometry of the ligands, to optimize them into new and better performing antichagasics. Virtual Screening of a set of hydrazones, guided by the top-performing models, identified promising candidates for experimental validation. Among them, dv007 and dv015 exhibited consistently high predicted pIC50 values (7.26 and 7.24, respectively), making them compelling candidates for further drug development.

Molecular targets for Chagas disease: validation, challenges and lead compounds for widely exploited targets.

INTRODUCTION: Chagas disease (CD) imposes social and economic burdens, yet the available treatments have limited efficacy in the disease's chronic phase and cause serious adverse effects. To address this challenge, target-based approaches are a possible strategy to develop new, safe, and active treatments for both phases of the disease. AREAS COVERED: This review delves into target-based approaches applied to CD drug discovery, emphasizing the studies from the last five years. We highlight the proteins cruzain (CZ), trypanothione reductase (TR), sterol 14 α-demethylase (CPY51), iron superoxide dismutase (Fe-SOD), proteasome, cytochrome b (Cytb), and cleavage and polyadenylation specificity factor 3 (CPSF3), chosen based on their biological and chemical validation as drug targets. For each, we discuss its biological relevance and validation as a target, currently related challenges, and the status of the most promising inhibitors. EXPERT OPINION: Target-based approaches toward developing potential CD therapeutics have yielded promising leads in recent years. We expect a significant advance in this field in the next decade, fueled by the new options for Trypanosoma cruzi genetic manipulation that arose in the past decade, combined with recent advances in computational chemistry and chemical biology.

Absorption matters: A closer look at popular oral bioavailability rules for drug approvals.

This study examines how two popular drug-likeness concepts used in early development, Lipinski Rule of Five (Ro5) and Veber's Rules, possibly affected drug profiles of FDA approved drugs since 1997. Our findings suggest that when all criteria are applied, relevant compounds may be excluded, addressing the harmfulness of blindly employing these rules. Of all oral drugs in the period used for this analysis, around 66 % conform to the RO5 and 85 % to Veber's Rules. Molecular Weight and calculated LogP showed low consistent values over time, apart from being the two least followed rules, challenging their relevance. On the other hand, hydrogen bond related rules and the number of rotatable bonds are amongst the most followed criteria and show exceptional consistency over time. Furthermore, our analysis indicates that topological polar surface area and total count of hydrogen bonds cannot be used as interchangeable parameters, contrary to the original proposal. This research enhances the comprehension of drug profiles that were FDA approved in the post-Lipinski period. Medicinal chemists could utilize these heuristics as a limited guide to direct their exploration of the oral bioavailability chemical space, but they must also steer the wheel to break these rules and explore different regions when necessary.

Trypanosoma cruzi Sirtuin 2 as a Relevant Druggable Target: New Inhibitors Developed by Computer-Aided Drug Design.

Trypanosoma cruzi, the etiological agent of Chagas disease, relies on finely coordinated epigenetic regulation during the transition between hosts. Herein we targeted the silent information regulator 2 (Sir2) enzyme, a NAD+-dependent class III histone deacetylase, to interfere with the parasites' cell cycle. A combination of molecular modelling with on-target experimental validation was used to discover new inhibitors from commercially available compound libraries. We selected six inhibitors from the virtual screening, which were validated on the recombinant Sir2 enzyme. The most potent inhibitor (CDMS-01, IC50 = 40 µM) was chosen as a potential lead compound.

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.

Aporphine and isoquinoline derivatives block glioblastoma cell stemness and enhance temozolomide cytotoxicity.

Glioblastoma (GBM) is the most aggressive and common primary malignant brain tumor with limited available therapeutic approaches. Despite improvements in therapeutic options for GBM patients, efforts to develop new successful strategies remain as major unmet medical needs. Based on the cytotoxic properties of aporphine compounds, we evaluated the biological effect of 12 compounds obtained through total synthesis of ( ±)-apomorphine hydrochloride (APO) against GBM cells. The compounds 2,2,2-trifluoro-1-(1-methylene-3,4-dihydroisoquinolin-2(1H)-yl)ethenone (A5) and ( ±)-1-(10,11-dimethoxy-6a,7-dihydro-4H-dibenzo[de,g]quinolin-6(5H)-yl)ethenone (C1) reduced the viability of GBM cells, with 50% inhibitory concentration ranging from 18 to 48 µM in patient-derived GBM cultures. Our data show that APO, A5 or C1 modulate the expression of DNA damage and apoptotic markers, impair 3D-gliomasphere growth and reduce the expression of stemness markers. Potential activity and protein targets of A5, C1 or APO were predicted in silico based on PASS and SEA software. Dopamine receptors (DRD1 and 5), CYP2B6, CYP2C9 and ABCB1, whose transcripts were differentially expressed in the GBM cells, were among the potential A5 or C1 target proteins. Docking analyses (HQSAR and 3D-QSAR) were performed to characterize possible interactions of ABCB1 and CYP2C9 with the compounds. Notably, A5 or C1 treatment, but not temozolomide (TMZ), reduced significantly the levels of extracellular ATP, suggesting ABCB1 negative regulation, which was correlated with stronger cytotoxicity induced by the combination of TMZ with A5 or C1 on GBM cells. Hence, our data reveal a potential therapeutic application of A5 and C1 as cytotoxic agents against GBM cells and predicted molecular networks that can be further exploited to characterize the pharmacological effects of these isoquinoline-containing substances.

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.

Role of a high centrality residue in protein dynamics and thermal stability.

Centralities determined from Residue Interaction Networks (RIN) in proteins have been used to predict aspects of their structure and dynamics. Here, we correlate the Eigenvector Centrality (Ec) with the rate constant for thermal denaturation (kden) of the HisF protein from Thermotoga maritima based on 12 single alanine substitution mutants. The molecular basis for this correlation was further explored by studying a mutant containing a replacement of a high Ec residue, Y182A, which displayed increased kden at 80 °C. The crystallographic structure of this mutant showed few changes, mostly in two flexible loops. The 1H-15N -HSQC showed only subtle changes of cross peak positions for residues located near the mutation site and scattered throughout the structure. However, the comparison of the RIN showed that Y182 is the vertex of a set of high centrality residues that spreads throughout the HisF structure, which is lacking in the mutant. Cross-correlation displacements of Cα calculated from a molecular dynamics simulation at different temperatures showed that the Y182A mutation reduced the correlated movements in the HisF structure above 70 °C. 1H-15N NMR chemical shift covariance using temperature as perturbation were consistent with these results. In conclusion the increase in temperature drives the structure of the mutant HisF-Y182A into a less connected state, richer in non-concerted motions, located predominantly in the C-terminal half of the protein where Y182 is placed. Conversely, wild-type HisF responds to increased temperature as a single unit. Hence the replacement of a high Ec residue alters the distribution of thermal energy through HisF structure.

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.

Antibodies Against the Plasmodium vivax Apical Membrane Antigen 1 From the Belem Strain Share Common Epitopes Among Other Worldwide Variants.

Malaria is a human parasitic disease distributed in many tropical countries and caused by various Plasmodium species. Plasmodium vivax has the largest geographical distribution of the Plasmodium species and is predominant in the Americas, including Brazil. Only a small number of P. vivax vaccine formulations have successfully reached clinical trials relative to their P. falciparum counterparts. One of the candidate antigens for a blood-stage P. vivax vaccine is apical membrane antigen 1 (PvAMA-1). Due to the worldwide distribution of Plasmodium parasites, a high degree of variability has been detected in this antigen sequence, representing a considerable challenge to the development of a universal vaccine against malaria. In this study, we evaluated how PvAMA-1 polymorphisms influence vaccine-derived immune responses in P. vivax malaria. To this end, we expressed 9 recombinant protein representatives of different PvAMA-1 allelic variants in the yeast Pichia pastoris: Belem, Chesson I, Sal-1, Indonesia XIX, SK0814, TC103, PNG_05_ESP, PNG_62_MU, and PNG_68_MAS. After protein expression and purification, we evaluated the breadth of the immune responses derived from malaria-exposed individuals from the Amazon region. From 611 serum samples of malaria-exposed individuals, 53.68% of them reacted against the PvAMA-1 Belem through ELISA. Positive samples were further tested against recombinant proteins representing the other PvAMA-1 allelic variants. Whereas Sal-1, Chesson I and SK0814 variants were highly recognized by tested serum samples, Indonesia XIX, TC103, PNG_05_ESP, PNG_62_MU, and PNG_68_MAS were only slightly recognized. Moreover, polyclonal sera derived from C57BL/6 mice immunized with the PvAMA-1 Belem protein predominantly recognized Belem, Sal-1, Chesson I, SK0814, and Indonesia XIX through ELISA. Last, ELISA-based competition assays demonstrated that a previous interaction between anti-Belem polyclonal serum and Sal-1, Chesson I, SK0814, or Indonesia XIX proteins could further inhibit antibody binding to the Belem variant. Our human and mouse data suggest the presence of common epitopes or cross-reactivity between Belem, Sal-1, Chesson I, and SK0814 variants. Although the PvAMA-1 Belem variant induces strain-transcendent antibodies, PvAMA-1 variants from Thailand and Papua New Guinea may need to be included in a universal vaccine formulation to achieve protection against P. vivax malaria.

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.

Insights on 3D Structures of Potential Drug-targeting Proteins of SARS-CoV-2: Application of Cavity Search and Molecular Docking.

The emergence of the COVID-19 has caused public health problems worldwide and there is no effective pharmacological treatment for this disease. Research on 3D models of proteins and the search for active molecular sites are important tools to assist in the discovery of effective antiviral drugs to combat COVID-19. To address this problem, the 3D protein structures of SARS-CoV 2 were analyzed and submitted to cavities research, evaluation of their druggabillity and liganbility, and applied to molecular docking studies with potential ligand candidates actually assayed against COVID-19. Eight druggable potential cavity sites were determined in model structures' PDB code, 6W4B, 6VWW, 6W01, 6M3M, and 6VYO, and these are the good alternatives to be characterized as targets for antiviral compounds. The good cavity model of the protease 3D structure was used in molecular docking, and this allowed verifying the theoric interactions of this protein and lopinavir and ritonavir antiviral drugs. These results may assist in the use of 3D protein models in drug design studies aiming to develop drugs against the COVID-19 pandemic.

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.

Design, synthesis and biological activity of novel substituted 3-benzoic acid derivatives as MtDHFR inhibitors.

The enzyme dihydrofolate reductase from M.tuberculosis (MtDHFR) has a high unexploited potential to be a target for new drugs against tuberculosis (TB), due to its importance for pathogen survival. Preliminary studies have obtained fragment-like molecules with low affinity to MtDHFR which can potentially become lead compounds. Taking this into account, the fragment MB872 was used as a prototype for analogue development by bioisosterism/retro-bioisosterism, which resulted in 20 new substituted 3-benzoic acid derivatives. Compounds were active against MtDHFR, with IC50 values ranging from 7 to 40 µM, where compound 4e not only had the best inhibitory activity (IC50 = 7 µM), but also was 71-fold more active than the original fragment MB872. The 4e inhibition kinetics indicated an uncompetitive mechanism, which was supported by molecular modeling which suggested that the compounds can access an independent backpocket from the substrate and competitive inhibitors. Thus, based on these results, substituted 3-benzoic acid derivatives have strong potential to be developed as novel MtDHFR inhibitors and also anti-TB agents.

QSAR studies on the human sirtuin 2 inhibition by non-covalent 7,5,2-anilinobenzamide derivatives.

Sirtuin 2 is a key enzyme in gene expression regulation that is often associated with tumor proliferation control and therefore is a relevant anticancer drug target. Anilinobenzamide derivatives have been discussed as selective sirtuin 2 inhibitors and can be developed further. In the present study, hologram and three-dimensional quantitative structure-activity relationship (HQSAR and 3D-QSAR) analyses were employed for determining structural contributions of a compound series containing human sirtuin-2-selective inhibitors that were then correlated with structural data from the literature. The final QSAR models were robust and predictive according to statistical validation (q2 and r2pred values higher than 0.85 and 0.75, respectively) and could be employed further to generate fragment contribution and contour maps. 3D-QSAR models together with information about the chemical properties of sirtuin 2 inhibitors can be useful for designing novel bioactive ligands.Communicated by Ramaswamy H. Sarma.