Drug Development Research Articles

The Promise use of Hybrid PET/MRI

Hybrid PET/MRI is a cutting-edge imaging modality that integrates the molecular imaging capabilities of Positron Emission Tomography (PET) with the superior anatomical and functional imaging strengths of Magnetic Resonance Imaging (MRI). This integration offers significant promise in enhancing diagnostic accuracy, reducing radiation exposure, and providing comprehensive imaging in a single session. Clinically, hybrid PET/MRI has shown particular value in oncology, neurology, and cardiology, offering improved tumor characterization, early detection of neurodegenerative diseases, and detailed cardiac assessments. In the research domain, it provides critical insights into physiological and pathological processes, aiding drug development and the study of disease mechanisms. Despite its high cost, complexity, and limited availability, ongoing technological advancements and the integration of artificial intelligence are expected to expand its clinical applications and improve its practicality. Hybrid PET/MRI thus represents a promising advancement in medical imaging, with the potential to significantly impact personalized and precision medicine.

Norovirus-mediated translation repression promotes macrophage cell death.

Norovirus infection is characterised by a rapid onset of disease and the development of debilitating symptoms including projectile vomiting and diffuse diarrhoea. Vaccines and antivirals are sorely lacking and developments in these areas are hampered by the lack of an adequate cell culture system to investigate human norovirus replication and pathogenesis. Herein, we describe how the model norovirus, Mouse norovirus (MNV), produces a viral protein, NS3, with the functional capacity to attenuate host protein translation which invokes the activation of cell death via apoptosis. We show that this function of NS3 is conserved between human and mouse viruses and map the protein domain attributable to this function. Our study highlights a critical viral protein that mediates crucial activities during replication, potentially identifying NS3 as a worthy target for antiviral drug development.

DNAJB6 is expressed in neurons and oligodendrocytes of the human brain.

DNAJB6 is a suppressor of α-synuclein aggregation in vivo and in vitro. DNAJB6 is strongly expressed in the brain, and its overall protein expression is altered in neurodegenerative conditions such as Parkinson's Disease (PD) and Multiple System Atrophy (MSA). These two diseases are characterized by accumulation of aggregated α-synuclein in neurons and oligodendrocytes, respectively. To further explore this, we employed post-mortem normal human brain material to investigate the regional and cell type specific protein expression of DNAJB6. We found that the DNAJB6 protein is ubiquitously expressed across various regions of the brain. Notably, we demonstrate for the first time that DNAJB6 is present in nearly half (41%-53%) of the oligodendrocyte population and in the majority (68%-80%) of neurons. However, DNAJB6 was only sparsely present in other cell types such as astrocytes and microglia. Given that α-synuclein aggregation in oligodendrocytes is a hallmark of MSA, we investigated DNAJB6 presence in MSA brains compared to control brains. We found no significant difference in the percentage of oligodendrocytes where DNAJB6 was present in MSA brains relative to control brains. In conclusion, our results reveal an expression of the DNAJB6 protein across various regions of the human brain, and that DNAJB6 is almost exclusively present in neurons and oligodendrocytes. Since prior studies have shown that PD and MSA brains have altered levels of DNAJB6 relative to control brains, DNAJB6 may be an interesting target for drug development.

Sex-dependent metabolic remodeling of kidneys revealed by arteriovenous metabolomics.

Sex is a fundamental biological variable important in biomedical research, drug development, clinical trials, and prevention approaches. Among many organs, kidneys are known to exhibit remarkable structural, histological, and pathological differences between sexes. However, whether and how kidneys display distinct metabolic activities between sexes is poorly understood. By developing kidney-specific arteriovenous (AV) metabolomics combined with transcriptomics, we report striking sex differences in both basal metabolic activities and adaptive metabolic remodeling of kidneys after a fat-enriched ketogenic diet (KD), a regimen known to mitigate kidney diseases and improve immunotherapy for renal cancer. At the basal state, female kidneys show highly accumulated aldosterone and various acylcarnitines. In response to the KD, aldosterone levels remain high selectively in females but the sex difference in acylcarnitines disappears. AV data revealed that, under KD, female kidneys avidly take up circulating fatty acids and release 3-hydroxybutyrate (3-HB) whereas male kidneys barely absorb fatty acids but consistently take up 3-HB. Although both male and female kidneys take up gluconeogenic substrates such as glycerol, glutamine and lactate, only female kidneys exhibit net glucose release. Kidney transcriptomics data incompletely predict these sex differences, suggesting post-transcriptional/translational regulation mechanisms. This study provides foundational insights into the sex-dependent and diet-elicited metabolic flexibility of the kidneys in vivo, serving as a unique resource for understanding variable disease prevalence and drug responses between male and female kidneys.

Structural insight into synergistic activation of human 3-methylcrotonyl-CoA carboxylase.

The enzymes 3-methylcrotonyl-coenzyme A (CoA) carboxylase (MCC), pyruvate carboxylase and propionyl-CoA carboxylase belong to the biotin-dependent carboxylase family located in mitochondria. They participate in various metabolic pathways in human such as amino acid metabolism and tricarboxylic acid cycle. Many human diseases are caused by mutations in those enzymes but their structures have not been fully resolved so far. Here we report an optimized purification strategy to obtain high-resolution structures of intact human endogenous MCC, propionyl-CoA carboxylase and pyruvate carboxylase in different conformational states. We also determine the structures of MCC bound to different substrates. Analysis of MCC structures in different states reveals the mechanism of the substrate-induced, multi-element synergistic activation of MCC. These results provide important insights into the catalytic mechanism of the biotin-dependent carboxylase family and are of great value for the development of new drugs for the treatment of related diseases.

Identification of ribosome biogenesis genes and subgroups in ischaemic stroke.

Ischaemic stroke is a leading cause of death and severe disability worldwide. Given the importance of protein synthesis in the inflammatory response and neuronal repair and regeneration after stroke, and that proteins are acquired by ribosomal translation of mRNA, it has been theorised that ribosome biogenesis may have an impact on promoting and facilitating recovery after stroke. However, the relationship between stroke and ribosome biogenesis has not been investigated. In the present study, a ribosome biogenesis gene signature (RSG) was developed using Cox and least absolute shrinkage and selection operator (LASSO) analysis. We classified ischaemic stroke patients into high-risk and low-risk groups using the obtained relevant genes, and further elucidated the immune infiltration of the disease using ssGSEA, which clarified the close relationship between ischaemic stroke and immune subgroups. The concentration of related proteins in the serum of stroke patients was determined by ELISA, and the patients were divided into groups to evaluate the effect of the ribosome biogenesis gene on patients. Through bioinformatics analysis, we identified potential IS-RSGs and explored future therapeutic targets, thereby facilitating the development of more effective therapeutic strategies and novel drugs against potential therapeutic targets in ischaemic stroke. We obtained a set of 12 ribosome biogenesis-related genes (EXOSC5, MRPS11, MRPS7, RNASEL, RPF1, RPS28, C1QBP, GAR1, GRWD1, PELP1, UTP, ERI3), which play a key role in assessing the prognostic risk of ischaemic stroke. Importantly, risk grouping using ribosome biogenesis-related genes was also closely associated with important signaling pathways in stroke. ELISA detected the expression of C1QBP, RPS28 and RNASEL proteins in stroke patients, and the proportion of neutrophils was significantly increased in the high-risk group. The present study demonstrates the involvement of ribosomal biogenesis genes in the pathogenesis of ischaemic stroke, providing novel insights into the underlying pathogenic mechanisms and potential therapeutic strategies for ischaemic stroke.

QSAR Studies on a Class of Benzofuranene Cyanide Derivatives as Potential Inhibitors Targeting Staphylococcus aureus Sortase A.

Staphylococcus aureus is a widely distributed and highly pathogenic zoonotic bacterium. Sortase A represents a crucial target for the research and development of novel antibacterial drugs. This study aims to establish quantitative structure-activity relationship models based on the chemical structures of a class of benzofuranene cyanide derivatives. The models will be used to screen new antibacterial agents and predict the properties of these molecules. The compounds were randomly divided into a training set and a test set. A large number of descriptors were calculated using the software, and then the appropriate descriptors were selected to build the models through the heuristic method and the gene expression programming algorithm. In the heuristic method, the determination coefficient, determination coefficient of cross-validation, F-test, and mean squared error values were 0.530, 0.395, 9.006, and 0.047, respectively. In the gene expression programming algorithm, the determination coefficient and the mean squared error values in the training set were 0.937 and 0.008, respectively, while in the test set, they were 0.849 and 0.035. The results showed that the minimum bond order of a C atom and the relative number of benzene rings had a significant positive contribution to the activity of compounds. In this study, two quantitative structure-activity relationship models were successfully established to predict the inhibitory activity of a series of compounds targeting Staphylococcus aureus Sortase A, providing insights for further development of novel anti-Staphylococcus aureus drugs.

Progress towards understanding risk factor mechanisms in the development of autism spectrum disorders.

Autism spectrum disorders (ASD) are a heterogenous set of syndromes characterised by social impairment and cognitive symptoms. Currently, there are limited treatment options available to help people with ASD manage their symptoms. Understanding the biological mechanisms that result in ASD diagnosis and symptomatology is an essential step in developing new interventional strategies. Human genetic studies have identified common gene variants of small effect and rare risk genes and copy number variants (CNVs) that substantially increase the risk of developing ASD. Reverse translational studies using rodent models based on these genetic variants provide new insight into the biological basis of ASD. Here we review recent findings from three ASD associated CNV mouse models (16p11.2, 2p16.3 and 22q11.2 deletion) that show behavioural and cognitive phenotypes relevant to ASD. These models have identified disturbed excitation-inhibition neurotransmitter balance, evidenced by dysfunctional glutamate and GABA signalling, as a key aetiological mechanism. These models also provide emerging evidence for serotoninergic neurotransmitter system dysfunction, although more work is needed to clarify the nature of this. At the brain network level, prefrontal cortex (PFC) dysfunctional connectivity is also evident across these models, supporting disturbed PFC function as a key nexus in ASD aetiology. Overall, published data highlight the utility and valuable insight gained into ASD aetiology from preclinical CNV mouse models. These have identified key aetiological mechanisms that represent putative novel therapeutic targets for the treatment of ASD symptoms, making them useful translational models for future drug discovery, development and validation.

DTI-LM: language model powered drug-target interaction prediction.

The identification and understanding of drug-target interactions (DTIs) play a pivotal role in the drug discovery and development process. Sequence representations of drugs and proteins in computational model offer advantages such as their widespread availability, easier input quality control, and reduced computational resource requirements. These make them an efficient and accessible tools for various computational biology and drug discovery applications. Many sequence-based DTI prediction methods have been developed over the years. Despite the advancement in methodology, cold start DTI prediction involving unknown drug or protein remains a challenging task, particularly for sequence-based models. Introducing DTI-LM, a novel framework leveraging advanced pretrained language models, we harness their exceptional context-capturing abilities along with neighborhood information to predict DTIs. DTI-LM is specifically designed to rely solely on sequence representations for drugs and proteins, aiming to bridge the gap between warm start and cold start predictions. Large-scale experiments on four datasets show that DTI-LM can achieve state-of-the-art performance on DTI predictions. Notably, it excels in overcoming the common challenges faced by sequence-based models in cold start predictions for proteins, yielding impressive results. The incorporation of neighborhood information through a graph attention network further enhances prediction accuracy. Nevertheless, a disparity persists between cold start predictions for proteins and drugs. A detailed examination of DTI-LM reveals that language models exhibit contrasting capabilities in capturing similarities between drugs and proteins. Source code is available at: https://github.com/compbiolabucf/DTI-LM.

Ameliorative Effects of Essential Oils on Diabetes Mellitus: A Review.

Diabetes mellitus (DM) is a metabolic disorder and is responsible for the death of more than 4.2 million people in 2019. Synthetic drugs for DM like metformin have been reported to induce numerous complications and side effects. Reports suggested that essential plant oil has been used as an herbal remedy to lower blood glucose levels. Essential oils (EOs) are complex combinations of small molecules obtained from plants via the process of steam distillation and several solvents. EOs have already shown great efficacy as antimicrobials, anti-inflammatory, hepatoprotective, and anti-hypertensive. This review aims to summarize some potential EOs that have been reported to have anti-diabetic activity both in preclinical and clinical aspects while summarizing the probable mechanism of action. The authors went through a vast number of articles from various scientific databases like Google Scholar, PubMed, and Web of Science. It was found that EO from a total of 20 plants has been pre-clinically investigated to have anti-diabetic potential. Besides this, clinical studies have reported the antidiabetic efficacy of EOs from Nigella sativa and Cuminum cyminum at different concentrations. Bioactive phytoconstituents like carvacrol, thymol, α- pinene, via . obtained from EOs ameliorate DM by inhibiting α-GLUC, α-amylase, lipase enzymes and increasing GLUT-4 expression, AKT phosphorylation, via . Although fewer in number, EOs from plant sources have demonstrated significant efficacy in DM. Proper elucidation of the anti-diabetic efficacy of the EOs may open up new avenues for drug discovery and development subjected to clinical studies.

Liver-targeting chimeras as a potential modality for the treatment of liver diseases

Liver diseases pose significant challenges to global public health. In the realm of drug discovery and development, overcoming ‘on-target off-tissue’ effects remains a substantial barrier for various diseases. In this study, we have pioneered a Liver-Targeting Chimera (LIVTAC) approach using a proteolysis-targeting chimera (PROTAC) molecule coupled to the liver-specific asialoglycoprotein receptor (ASGPR) through an innovative linker attachment strategy for the precise induction of target protein degradation within the liver. As a proof-of-concept study, we designed XZ1606, a mammalian bromodomain and extra-terminal domain (BET)-targeting LIVTAC agent, which not only demonstrated enduring tumor suppression (over 2 months) in combination with sorafenib but also an improved safety profile, notably ameliorating the incidence of thrombocytopenia, a common and severe on-target dose-limiting toxic effect associated with conventional BET inhibitors. These encouraging results highlight the potential of LIVTAC as a versatile platform for addressing a broad spectrum of liver diseases.

Recent Advances in Nanocatalyzed One-Pot Sustainable Synthesis of Bioactive N, N-Heterocycles with Anticancer Activities: An Outlook of Medicinal Chemistry.

N-heterocycles represent a predominant and unique class of organic chemistry. They have received a lot of attention due to their important chemical, biomedical, and industrial uses. Food and Drug Administration (FDA) approved about 75% of drugs containing N-based heterocycles, which are currently available in the market. N-Heterocyclic compounds exist as the backbone of numerous natural products and act as crucial intermediates for the construction of pharmaceuticals, veterinary items, and agrochemicals frequently. Among N-based heterocyclic compounds, bioactive N,N-heterocycles constitute a broad spectrum of applications in modern drug discovery and development processes. Cefozopran (antibiotic), omeprazole (antiulcer), enviradine (antiviral), liarozole (anticancer), etc., are important drugs containing N,N-heterocycles. The synthesis of N,Nheterocyclic compounds under sustainable conditions is one of the most active fields because of their significant physiological and biological properties as well as synthetic utility. Current research is demanding the development of greener, cheaper, and milder protocols for the synthesis of N,N-heterocyclic compounds to save mother nature by avoiding toxic metal catalysts, extensive application of energy, and the excessive use of hazardous materials. Nanocatalysts play a profound role in sustainable synthesis because of their larger surface area, tiny size, and minimum energy; they are eco-friendly and safe, and they provide higher yields with selectivity in comparison to conventional catalysts. It is increasingly demanding research to design and synthesize novel bioactive compounds that may help to combat cancer since the major causes of death worldwide are due to cancer. Hence, the important uses of nanocatalysts for the one-pot synthesis of biologically potent N,N-heterocycles with anticancer activities have been presented in this review.

Tilorone mitigates the propagation of α-synucleinopathy in a midbrain-like organoid model

BackgroundParkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of dopaminergic neurons and the accumulation of Lewy-body protein aggregates containing misfolded α-synuclein (α-syn) in a phosphorylated form. The lack of effective models for drug screens has hindered drug development studies for PD. However, the recent development of in vitro brain-like organoids provides a new opportunity for evaluating therapeutic agents to slow the progression of this chronic disease.MethodsIn this study, we used a 3D brain-like organoid model to investigate the potential of repurposing Tilorone, an anti-viral drug, for impeding the propagation of α-synucleinopathy. We assessed the effect of Tilorone on the uptake of fluorescently labeled α-syn preformed fibrils (sPFF) and sPFF-induced apoptosis using confocal microscopy. We also examined Tilorone’s impact on the phosphorylation of endogenous α-syn induced by pathogenic sPFF by immunoblotting midbrain-like organoid extracts. Additionally, quantitative RT-PCR and proteomic profiling of sPFF-treated organoids were conducted to evaluate the global impact of Tilorone treatment on tissue homeostasis in the 3D organoid model.ResultsTilorone inhibits the uptake of sPFF in both mouse primary neurons and human midbrain-like organoids. Tilorone also reduces the phosphorylation of endogenous α-syn induced by pathogenic α-syn fibrils and mitigates α-syn fibril-induced apoptosis in midbrain-like organoids. Proteomic profiling of fibril-treated organoids reveals substantial alterations in lipid homeostasis by α-syn fibrils, which are reversed by Tilorone treatment. Given its safety profile in clinics, Tilorone may be further developed as a therapeutic intervention to alleviate the propagation of synucleinopathy in PD patients.

Promising New Targets for the Treatment of Infections Caused by Acinetobacter baumannii: A Review.

Acinetobacter baumannii is a globally disseminated Gram-negative bacterium that causes several types of serious nosocomial infections, the most worrisome being ventilator-associated pneumonia and bacteremia related to using venous catheters. Due to its great ability to form biofilms, combined with its survival for prolonged periods on abiotic surfaces and its potential to acquire and control the genes that determine antibiotic resistance, A. baumannii is at the top of the World Health Organization's priority list of pathogens in urgent need of new therapies. In this sense, this review aimed to present and discuss new molecular targets present in A. baumannii with potential for promising treatment approaches. This review highlights crucial molecular targets, including cell division proteins, membrane synthesis enzymes, and biofilm-associated components, offering promising targets for novel antimicrobial drug development against A. baumannii infections.

Insights into medicinal attributes of imidazo[1,2-a]pyridine derivatives as anticancer agents.

Cancer ranks among the most life-threatening diseases worldwide and is continuously affecting all age groups. Consequently, many research studies are being carried out to develop new cancer treatments, but many of them experience resistance and cause severe toxicity to the patients. Therefore, there is a continuous need to design novel anticancer agents that are target-based, have a higher potency, and have minimal toxicity. The imidazo[1,2-a]pyridine (IP) pharmacophore has been found to be a prominent moiety in the field of medicinal chemistry due to its vast biological properties. Also, it holds immense potential for combating cancer with minimal side effects, depending on the substitution patterns of the core structure. IPs exhibit significant capability in regulating various cellular pathways, offering possibilities for targeted anticancer effects. The present review summarizes the anticancer profile of numerous IP derivatives synthesized and developed by various researchers from 2016 till now, as inhibitors of phosphoinositide-3-kinase/mammalian target of rapamycin (PI3K/mTOR), protein kinase B/mammalian target of rapamycin (Akt/mTOR), aldehyde dehydrogenase (ALDH), and tubulin polymerization. This review provides a comprehensive analysis of the anticancer activity afforded by the discussed IP compounds, emphasizing the structure-activity-relationships (SARs). The aim is also to underscore the potential therapeutic future of the IP moiety as a potent partial structure for upcoming cancer drug development and to aid researchers in the field of rational drug design.

Structure-Based Virtual Screening and Protein–Protein Docking Analysis of ERBB2 and Associated Proteins for Pediatric Cancer Therapeutic Approaches

Abstract Introduction The Erythroblastosis Oncogene B homolog 2 (ERBB2) protein, also known as human epidermal growth factor receptor 2 (HER2), is a key player in cancer growth, especially in neuroblastoma and gastric cancers. Targeting ERBB2 has led to successful therapies, making it an important focus in cancer research with the potential to improve treatment for HER2-positive cancers. Objective The primary goal of this research is to employ a multifaceted computational approach to identify potential drug candidates targeting ERBB2. We aim to combine virtual screening, protein–protein docking, and functional partner prediction to provide insights into the molecular interactions and potential efficacy of the identified compounds. Additionally, we intend to assess the safety profiles of these compounds using advanced toxicity prediction tools. Methods Relevant protein sequence and structural data for ERBB2 and epidermal growth factor receptor (EGFR) were sourced from publicly available databases. Potential inhibitors from the Enamine and LifeChemicals databases were identified through virtual screening using AutoDock Vina. Functional partners of ERBB2 were explored using STRING, KEGG, and REACTOME servers. The identified compounds were subjected to toxicity prediction using the ProTox-II server. Results Virtual screening led to the selection of 10 compounds with favorable binding energies (–8.346 to –6.296 kcal/mol) and specific amino acid interactions (Thr5, Arg412, Leu414, and Ser441) with the receptor. On the other hand, EGFR was identified as the best functional partner for ERBB2. The EGFR residues Gln408, Lys463, Phe412, and Asp436 found key residues for the complex formation. The toxicity prediction analysis revealed that the majority of compounds exhibited acceptable safety profiles, although a subset of compounds showed lower prediction scores, suggesting the need for further consideration. Conclusion This comprehensive computational approach, integrating virtual screening, protein–protein docking, functional partner identification, and toxicity prediction, offers a systematic framework for efficient drug discovery. The identification of potential lead compounds targeting ERBB2, with emphasis on both binding affinity and safety, underscores the significance of such an approach in streamlining the drug development process. By prioritizing compounds with promising efficacy, functional relevance, and acceptable toxicity profiles, this study advances our understanding of potential therapeutic agents, enhancing the likelihood of successful translation from computational predictions to real-world drug candidates.

ToxDAR: A Workflow Software for Analyzing Toxicologically Relevant Proteomic and Transcriptomic Data, from Data Preparation to Toxicological Mechanism Elucidation.

Exploration of toxicological mechanisms is imperative for the assessment of potential adverse reactions to chemicals and pharmaceutical agents, the engineering of safer compounds, and the preservation of public health. It forms the foundation of drug development and disease treatment. High-throughput proteomics and transcriptomics can accurately capture the body's response to toxins and have become key tools for revealing complex toxicological mechanisms. Recently, a vast amount of omics data related to toxicological mechanisms have been accumulated. However, analyzing and utilizing these data remains a major challenge for researchers, especially as there is a lack of a knowledge-based analysis system to identify relevant biological pathways associated with toxicity from the data and to establish connections between omics data and existing toxicological knowledge. To address this, we have developed ToxDAR, a workflow-oriented R package for preprocessing and analyzing toxicological multi-omics data. ToxDAR integrates packages like NormExpression, DESeq2, and igraph, and utilizes R functions such as prcomp and phyper. It supports data preparation, quality control, differential expression analysis, functional analysis, and network analysis. ToxDAR's architecture also includes a knowledge graph with five major categories of mechanism-related biological entities and details fifteen types of interactions among them, providing comprehensive knowledge annotation for omics data analysis results. As a case study, we used ToxDAR to analyze a transcriptomic dataset on the toxicology of triphenyl phosphate (TPP). The results indicate that TPP may impair thyroid function by activating thyroid hormone receptor β (THRB), impacting pathways related to programmed cell death and inflammation. As a workflow-oriented data analysis tool, ToxDAR is expected to be crucial for understanding toxic mechanisms from omics data, discovering new therapeutic targets, and evaluating chemical safety.

Antimicrobial potential of Streptomyces sp. NP73 isolated from the forest soil of Northeast India against multi-drug resistant Escherichia coli.

This study reports the isolation and characterization of a Streptomyces sp. from soil, capable of producing bioactive secondary metabolites active against a variety of bacterial human pathogens. We targeted the antimicrobial activity against Escherichia coli ATCC-BAA 2469, a clinically relevant strain of bacteria harbouring resistance genes for carbapenems, extended spectrum beta-lactams, tetracyclines, fluoroquinones, etc. Preliminary screening using the spot inoculation technique identified Streptomyces sp. NP73 as the potent strain among the 74 isolated Actinomycetia strain. 16S rRNA gene and whole genome sequencing (WGS) confirmed its taxonomical identity and helped in the construction of the phylogenetic tree. WGS revealed the predicted pathways and biosynthetic gene clusters responsible for producing various types of antibiotics including the isolated compound. Bioactivity guided fractionation and chemical characterization of the active fraction, carried out using liquid chromatography, gas chromatography-mass spectrometry, infra-red spectroscopy, and nuclear magnetic resonance spectroscopy, led to the tentative identification of the active compound as Pyrrolo[1,2-a] pyrazine-1,4-dione, hexahydro-, a diketopiperazine molecule. This compound exhibited excellent antimicrobial and anti-biofilm properties against E. coli ATCC-BAA 2469 with an MIC value of 15.64µg ml-1, and the low cytotoxicity of the compound identified in this study provides hope for future drug development.

From Bench to Babies - Drug Development for Male Subfertility.

Infertility is estimated to affect more than 50 million couples around the world, with male factor accounting for half of these cases, yet there is a notable absence of effective treatment options for men, other than in-vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI). This review considers unlicensed and empirical treatments used for male subfertility, including hormonal therapy, phosphodiesterase inhibitors, and antioxidants. Compounds generally demonstrate variable improvements in sperm function but benefits for fertility are less clear. There is a pressing need for effective treatment options for subfertile men, however, our knowledge of sperm function is limited, restricting the identification of precise treatment targets. The traditional drug discovery pathway is also notorious for its extensive resource and time requirements, often extending over decades and demanding significant financial investment. Unfortunately, a substantial number of potential therapies fail before reaching the marketplace. Furthermore, reliance on mammalian models is not possible in the drug development process for male subfertility, due to significant variability between animals and man. We review recent breakthroughs and highlight novel methods aimed at improving the effectiveness and efficiency of drug discovery for male subfertility. High-throughput screening, combinatorial chemistry, and the repurposing of established medications have great potential. These strategies offer the promise of accelerating the pace of drug development, curbing the extensive demand for resources, and, in the case of drug repurposing, diminish the demand for comprehensive pharmacokinetic and pharmacodynamic studies. As these innovative approaches are adopted, the feasibility of addressing male subfertility through scientific advancements appears to be increasingly attainable.

Hansch analysis by QSAR model of curcumin and eight of its transformed derivatives with antimicrobial activity against Staphylococcus aureus

Context: In the last decade, antimicrobial resistance cases have been widespread. The discovery and development of new drugs need to be done to overcome the case. Some research has found that some compounds, which are curcumin transformation derivatives, are able to inhibit the growth of Staphylococcus aureus. Aims: To evaluate the development of antimicrobial candidates of curcumin versus S. aureus. Methods: The in silico approach method, along with the QSAR technique, plays an important role in the process of discovery and development of new drugs. In this study, we focused on developing curcumin transformation derivatives that are much more potent by making the best QSAR equation of curcumin and eight curcumin transformation derivatives that have been tested in vitro for their antimicrobial activity against Staphylococcus aureus. Results: The best QSAR equation was obtained from curcumin transformation derivatives as antimicrobial activity against S. aureus, with pMIC = 0.812 (± 0.162)EHOMO +5.443 (± 1.659) (n = 9; Sig = 0.002; R = 0.884; R2 = 0.782; F = 25.153; Q2 = 0.57. Conclusions: In this study, an increase in the antimicrobial activity of curcumin transformation derivatives against S. aureus by increasing EHOMO was observed. The best QSAR equation can be a tool to obtain a more potential new chemical structure model and reduce trials and errors.