Small Molecule Drug Candidates Research Articles

Establishment and Validation of the Diagnostic Value of Oligodendrocyte-related Genes in Alzheimer's Disease.

AD is a demyelinating disease. Myelin damage initiates the pathological process of AD, resulting in abnormal synaptic function and cognitive decline. The myelin sheath formed by oligodendrocytes (OL) is a crucial component of white matter. Investigating AD from the perspective of OL may offer novel diagnostic and therapeutic perspectives. This study aimed to analyze the association between OL-related genes and Alzheimer's disease (AD) using bioinformatics and verify this association via molecular biology experiments. The AD datasets were acquired from the Gene Expression Omnibus (GEO) database of NCBI. Consensus clustering was employed to determine the subtypes of AD, followed by evaluating the clinical characteristics of these subtypes. Subsequently, immune infiltration analysis of relevant genes and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identify modules and hub genes associated with AD progression. The intersection of genes obtained was analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. To narrow down the scope and identify OL-related genes with diagnostic potential, three machine learning algorithms were utilized. In addition, the eXtreme Sum (XSum) algorithm was used to screen small molecule drug candidates based on the connectivity map (CMAP) database. Finally, these identified genes were validated using Real-time fluorescence quantitative PCR (RT-qPCR). Among the three subtypes of AD, Cluster A and Cluster C exhibited increased levels of Braak and neurofibrillary tangles compared to Cluster B. The proportion of females was greater than that of males among the three subclasses of AD. There were no significant differences in age among the three subclasses, but significant differences in gene expression existed. Through WGCNA analysis, 108 genes were identified. Among these, 16 genes were identified as shared genes by the least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machines (SVM) algorithms, and logistic regression further determined 11 genes. The establishment of a nomogram demonstrated the significance of these 11 genes in AD. The "XSum" algorithm revealed five drugs with therapeutic potential for AD. qPCR analysis revealed the upregulation and downregulation of the highlighted genes. According to this study, 11 genes related to OL were also found to be associated with immune cell infiltration in AD patients. These genes demonstrated potential diagnostic value for AD. Additionally, we screened five small molecular drugs that exhibit potential therapeutic effects on AD. This research provides a new perspective for personalized clinical management and treatment of AD.

Targeted Polymer-Peptide Conjugates for E-Selectin Blockade in Renal Injury.

Leukocytes play a significant role in both acute kidney injury (AKI) and chronic kidney disease (CKD), contributing to pathogenesis and tissue damage. The process of leukocyte infiltration into the inflamed tissues is mediated by the interactions between the leukocytes and cell adhesion molecules (CAMs, i.e., E-selectin, P-selectin, and VCAM-1) present on the inner surface of the inflamed vasculature. Directly interfering with these interactions is a viable strategy to limit the extent of excessive inflammation; however, several small-molecule drug candidates failed during clinical translation. We hypothesized that a synthetic polymer presenting multiple copies of the high-affinity E-selecting binding peptide (P-Esbp) could block E-selectin-mediated functions and decrease leukocytes infiltration, thus reducing the extent of inflammatory kidney injury. P-Esbp was synthesized by conjugating E-selecting binding peptide (Esbp) to N-(2-hydroxypropyl)methacrylamide (HPMA) copolymer with reactive ester groups via aminolysis. The effects of P-Esbp treatment on kidney injury were investigated in two different models: AKI model (renal ischemia-reperfusion injury-RIRI) and CKD model (adenine-induced kidney injury). We found that the mRNA levels of E-selectin were up-regulated in the kidney following acute and chronic tissue injury. P-Esbp demonstrated an extended half-life time in the bloodstream, and the polymer accumulated significantly in the liver, lungs, and kidneys within 4 h post injection. Treatment with P-Esbp suppressed the up-regulation of E-selectin in mice with RIRI and attenuated the inflammatory process. In the adenine-induced CKD model, the use of the E-selectin blocking copolymer had little impact on the progression of kidney injury, owing to the compensating function of P-selectin and VCAM-1. Our findings provide valuable insights into the interconnection between CAMs and compensatory mechanisms in controlling leukocyte migration in AKI and CKD. The combination of multiple CAM blockers, given simultaneously, may provide protective effects for preventing excessive leukocyte infiltration and control renal injury.

Electrochemical α-C(sp3)-H/N-H Cross-Coupling of Isochromans and Azoles.

Isochroman and azole moieties are both present in a wide variety of biologically active molecules. Their efficient combination under mild reaction conditions is beneficial for obtaining small-molecule drug candidates. In this paper, we describe electrochemical α-C(sp3)-H/N-H cross-coupling reactions between isochromans and azoles, yielding products in moderate to excellent yields. This protocol does not require any catalysts or exogenous oxidants and can be performed at room temperature under air. Control experiments and cyclic voltammetry showed that the reaction may proceed through both radical coupling and nucleophilic addition processes.

Leucettinib-21, a DYRK1A Kinase Inhibitor as Clinical Drug Candidate for Alzheimer's Disease and Down Syndrome.

Alzheimer's disease (AD) and Down syndrome (DS) share a common therapeutic target, the dual-specificity, tyrosine phosphorylation activated kinase 1A (DYRK1A). Abnormally active DYRK1A is responsible for cognitive disorders (memory, learning, spatial localization) observed in both conditions. In DS, DYRK1A is overexpressed due to the presence of the DYRK1A gene on chromosome 21. In AD, calcium-activated calpains cleave full-length DYRK1A (FL-DYRK1A) into a more stable and more active, low molecular weight, kinase (LMW-DYRK1A). Genetic and pharmacological experiments carried out with animal models of AD and DS strongly support the idea that pharmacological inhibitors of DYRK1A might be able to correct memory/learning disorders in people with AD and DS. Starting from a marine sponge natural product, Leucettamine B, Perha Pharmaceuticals has optimized, through classical medicinal chemistry, and extensively characterized a small molecule drug candidate, Leucettinib-21. Regulatory preclinical safety studies in rats and minipigs have been completed and formulation of Leucettinib-21 has been optimized as immediate-release tablets. Leucettinib-21 is now undergoing a phase 1 clinical trial (120 participants, including 12 adults with DS and 12 patients with AD). The therapeutic potential of DYRK1A inhibitors in AD and DS is presented.

An integrated approach combining experimental, informatics and energetic methods for solid form derisking of PF-06282999

The landscapes of observed and predicted three-dimensional crystal packing arrangements of small-molecule drug candidates can be complex. The possible appearance of a more thermodynamically stable solid form during drug development has led to the digital workflow of informatics-based risk assessments, named a Solid Form Health Check. Herein, we describe the use of a combined approach consisting of experiments, informatics together with energetic calculations in analysis of four competing polymorphs of PF-06282999, a myeloperoxidase (MPO) inhibitor with conformational flexibility and multiple plausible hydrogen bond networks. This combined approach offered a comprehensive understanding of the solid form structure, properties, and performance, ensuring robust solid form derisking and selection.

SMTRI: A deep learning-based web service for predicting small molecules that target miRNA-mRNA interactions

Mature microRNAs are short, single-stranded RNAs that bind to target mRNAs and induce translational repression and gene silencing. Many microRNAs discovered in animals have been implicated in diseases and have recently been pursued as therapeutic targets. However, conventional pharmacological screening for candidate small-molecule drugs can be time-consuming and labor-intensive. Therefore, developing a computational program to assist mature microRNA-targeted drug discovery in silico is desirable. Our previous work (https://doi.org/10.1002/advs.201903451) revealed that the unique functional loops formed during Argonaute-mediated microRNA-mRNA interactions have stable structural characteristics and may serve as potential targets for small molecule drug discovery. Developing drugs specifically targeting disease-related mature microRNAs and their target mRNAs would avoid affecting unrelated ones. Here, we presented SMTRI, a convolutional neural network-based approach for efficiently predicting small molecules that target RNA secondary structural motifs formed by interactions between microRNAs and their target mRNAs. Measured on three additional testing sets, SMTRI outperformed state-of-the-art algorithms by 12.9-30.3% in AUC and 2.0-18.4% in Accuracy. Moreover, four case studies on the published experimentally validated RNA-targeted small molecules also revealed the reliability of SMTRI. Our method is available as a user-friendly web server at http://smtri.net.

Rapid, Accurate, Ranking of Protein-Ligand Binding Affinities with VM2, the Second-Generation Mining Minima Method.

The structure-based technologies most widely used to rank the affinities of candidate small molecule drugs for proteins range from faster but less reliable docking methods to slower but more accurate explicit solvent free energy methods. In recent years, we have advanced another technology, which is called mining minima because it "mines" out the main contributions to the chemical potentials of the free and bound molecular species by identifying and characterizing their main local energy minima. The present study provides systematic benchmarks of the accuracy and computational speed of mining minima, as implemented in the VeraChem Mining Minima Generation 2 (VM2) code, across two well-regarded protein-ligand benchmark data sets, for which there are already benchmark data for docking, free energy, and other computational methods. A core result is that VM2's accuracy approaches that of explicit solvent free energy methods at a far lower computational cost. In finer-grained analyses, we also examine the influence of various run settings, such as the treatment of crystallographic water molecules, on the accuracy, and define the costs in time and dollars of representative runs on Amazon Web Services (AWS) compute instances with various CPU and GPU combinations. We also use the benchmark data to determine the importance of VM2's correction from generalized Born to finite-difference Poisson-Boltzmann results for each energy well and find that this correction affords a remarkably consistent improvement in accuracy at a modest computational cost. The present results establish VM2 as a distinctive technology for early-stage drug discovery, which provides a strong combination of efficiency and predictivity.

Bioinformatics analysis of potential pathogenesis and risk genes of neuroinflammation-promoted brain injury in intracerebral hemorrhage

IntroductionSpontaneous (non-traumatic) intracerebral hemorrhage (ICH) is one of the major causes of global death. The purpose of our bioinformatics analysis was to detect viable pathophysiological targets and small-molecule drug candidates and to identify the precise secondary mechanisms of brain injury in ICH. Material and methodsThe GSE24265 dataset, consisting of data from four perihematomal brain tissues and seven contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH. Online analysis tool GEO2R and Drug Susceptibility Assessment Module within the ACBI Bioinformation tool was used for data differential expression analysis. TargetScan, miRDB, and RNA22 were used to investigate the miRNAs regulating the DEGs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG). DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. Enrichment analysis was performed for delving the molecular mechanism of DEGs, and protein–protein interaction (PPI) networks and microRNA (miRNA)-messenger RNA (mRNA) networks were used to reveal the hub nodes and the related interaction relationships. Hub genes and miRNA-mRNA interaction of PPI network were identified by STRING version 12.0 online software and Cytoscape. Next, the DEGs were analyzed using the L1000CDS2 database to identify small-molecule compounds with potential therapeutic effects. ResultsA total of 325 upregulated genes and 103 downregulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to cytokine-cytokine receptor interaction and MAPK signaling pathway. A PPI network consisting of 188 nodes and 563 edges was constructed using STRING, and 27 hub genes were identified with Cytoscape software. The miRNA-mRNA network with high connectivity contained key 27 mRNAs (from C-C motif chemokine ligand 5 (CCL5), C-C motif chemokine ligand 8 (CCL8), …., to dishevelled-associated activator of morphogenesis 1 (DAAM1), and FRAT regulator of WNT signaling pathway 1 (FRAT1)) and 135 candidate miRNAs. These genes and miRNAs are closely related to secondary brain injury induced by ICH. In addition, a L1000CDS2 analysis of six small-molecule compounds revealed their therapeutic potential. ConclusionsOur study explores the pathogenesis of brain tissue injury promoted by neuroinflammation in ICH and extends the clinical utility of its key genes. At the same time, we constructed a miRNA-mRNA network which may play crucial roles in the pathogenesis of ICH. In addition, we obtained six small molecule compounds that will have anti-inflammatory effects on ICH, including Geldanamycin, Dasatinib, BMS-345541, Saracatinib, and Afatinib.

Modulation of Amyloid and Tau Aggregation to Alleviate Cognitive Impairment in a Transgenic Mouse Model of Alzheimer's Disease.

Aggregation of misfolded amyloid-β (Aβ) and hyperphosphorylated tau proteins to plaques and tangles, respectively, is the major drug target of Alzheimer's disease (AD), as the former is an onset biomarker and the latter is associated with neurodegeneration. Thus, we report a small molecule drug candidate, DN5355, with a dual-targeting function toward aggregates of both Aβ and tau. DN5355 was selected through a series of four screenings assessing 52 chemicals for their functions to inhibit and reverse the aggregation of Aβ and tau by utilizing thioflavin T. When orally administered to AD transgenic mouse model 5XFAD, DN5355 significantly reduced cerebral Aβ plaques and hyperphosphorylated tau tangles. In Y-maze spontaneous alteration and contextual fear conditioning tests, 5XFAD mice showed amelioration of cognitive deficits upon the oral administration of DN5355.

Peptide Drug Design Using Alchemical Free Energy Calculation: An Application and Validation on Agonists of Ghrelin Receptor.

With recent large-scale applications and validations, the relative binding free energy (RBFE) calculated using alchemical free energy methods has been proven to be an accurate measure to probe the binding of small-molecule drug candidates. On the other hand, given the flexibility of peptides, it is of great interest to find out whether sufficient sampling could be achieved within the typical time scale of such calculation, and a similar level of accuracy could be reached for peptide drugs. However, the systematic evaluation of such calculations on protein-peptide systems has been less reported. Most reported studies of peptides were restricted to a limited number of data points or lacking experimental support. To demonstrate the applicability of the alchemical free energy method for protein-peptide systems in a typical real-world drug discovery project, we report an application of the thermodynamic integration (TI) method to the RBFE calculation of ghrelin receptor and its peptide agonists. Along with the calculation, the synthesis and in vitro EC50 activity of relamorelin and 17 new peptide derivatives were also reported. A cost-effective criterion to determine the data collection time was proposed for peptides in the TI simulation. The average of three TI repeats yielded a mean absolute error of 0.98 kcal/mol and Pearson's correlation coefficient (R) of 0.77 against the experimental free energy derived from the in vitro EC50 activity, showing good repeatability of the proposed method and a slightly better agreement than the results obtained from the arbitrary time frames up to 20 ns. Although it is limited by having one target and a deduced binding pose, we hope that this study can add some insights into alchemical free energy calculation of protein-peptide systems, providing theoretical assistance to the development of peptide drugs.

Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response.

Skin cutaneous melanoma (SKCM), a form of skin cancer, ranks among the most formidable and lethal malignancies. Exploring tumor microenvironment (TME)-based prognostic indicators would help improve the efficacy of immunotherapy for SKCM patients. This study analyzed SKCM scRNA-seq data to cluster non-malignant cells that could be used to explore the TME into nine immune/stromal cell types, including B cells, CD4 T cells, CD8 T cells, dendritic cells, endothelial cells, Fibroblasts, macrophages, neurons, and natural killer (NK) cells. Using data from The Cancer Genome Atlas (TCGA), we employed SKCM expression profiling to identify differentially expressed immune-associated genes (DEIAGs), which were then incorporated into weighted gene co-expression network analysis (WGCNA) to investigate TME-associated hub genes. Discover candidate small molecule drugs based on pivotal genes. Tumor immune microenvironment-associated genes (TIMAGs) for constructing TIMAS were identified and validated. Finally, the characteristics of TIAMS subgroups and the ability of TIMAS to predict immunotherapy outcomes were analyzed. We identified five TIMAGs (CD86, CD80, SEMA4D, C1QA, and IRF1) and used them to construct TIMAS. In addition, five potential SKCM drugs were identified. The results showed that TIMAS-low patients were associated with immune-related signaling pathways, high MUC16 mutation frequency, high T cell infiltration, and M1 macrophages, and were more favorable for immunotherapy. Collectively, TIMAS constructed by comprehensive analysis of scRNA-seq and bulk RNA-seq data is a promising marker for predicting ICI treatment outcomes and improving individualized therapy for SKCM patients.

Rethinking therapeutic strategies of dual-target drugs: An update on pharmacological small-molecule compounds in cancer.

Oncogenes and tumor suppressors are well-known to orchestrate several signaling cascades, regulate extracellular and intracellular stimuli, and ultimately control the fate of cancer cells. Accumulating evidence has recently revealed that perturbation of these key modulators by mutations or abnormal protein expressions are closely associated with drug resistance in cancer therapy; however, the inherent drug resistance or compensatory mechanism remains to be clarified for targeted drug discovery. Thus, dual-target drug development has been widely reported to be a promising therapeutic strategy for improving drug efficiency or overcoming resistance mechanisms. In this review, we provide an overview of the therapeutic strategies of dual-target drugs, especially focusing on pharmacological small-molecule compounds in cancer, including small molecules targeting mutation resistance, compensatory mechanisms, synthetic lethality, synergistic effects, and other new emerging strategies. Together, these therapeutic strategies of dual-target drugs would shed light on discovering more novel candidate small-molecule drugs for the future cancer treatment.

In Silico Screening of Some Active Phytochemicals to Identify Promising Inhibitors Against SARS-CoV-2 Targets.

There are very few small-molecule drug candidates developed against SARS-CoV-2 that have been revealed since the epidemic began in November 2019. The typical medicinal chemistry discovery approach requires more than a decade of the year of painstaking research and development and a significant financial guarantee, which is not feasible in the challenge of the current epidemic. This current study proposes to find and identify the most effective and promising phytomolecules against SARS-CoV-2 in six essential proteins (3CL protease, Main protease, Papain- Like protease, N-protein RNA binding domain, RNA-dependent RNA polymerase, and Spike receptor binding domain target through in silico screening of 63 phytomolecules from six different Ayurveda medicinal plants. The phytomolecules and SARS-CoV-2 proteins were taken from public domain databases such as PubChem and RCSB Protein Data Bank. For in silico screening, the molecular interactions, binding energy, and ADMET properties were investigated. The structure-based molecular docking reveals some molecules' greater affinity towards the target than the co-crystal ligand. Our results show that tannic acid, cyanidin-3-rutinoside, zeaxanthin, and carbolactone are phytomolecules capable of inhibiting SARS-CoV-2 target proteins in the least energy conformations. Tannic acid had the least binding energy of -8.8 kcal/mol, which is better than the binding energy of its corresponding co-crystal ligand (-7.5 kcal/mol) against 3 CL protease. Also, it has shown the least binding energy of -9.9 kcal/mol with a more significant number of conventional hydrogen bond interactions against the RdRp target. Cyanidin-3-rutinoside showed binding energy values of -8.8 and -7.6 kcal/mol against Main protease and Papain-like protease, respectively. Zeaxanthin was the top candidate in the N protein RBD with a binding score of - 8.4 kcal/mol, which is slightly better when compared to a co-crystal ligand (-8.2 kcal/mol). In the spike, carbolactone was the suitable candidate with the binding energy of -7.2 kcal/mol and formed a conventional hydrogen bond and two hydrophobic interactions. The best binding affinity-scored phytomolecules were selected for the MD simulations studies. The present in silico screening study suggested that active phytomolecules from medicinal plants could inhibit SARS-CoV-2 targets. The elite docked compounds with drug-like properties have a harmless ADMET profile, which may help to develop promising COVID-19 inhibitors.

Abstract LB428: Discovery of KY-001:A Direct Inhibitor of TEAD-YAP Protein-Protein Interaction for the Treatment of Advanced Solid Tumors with Abnormal Hippo Signaling Pathway

Abstract Background:The Hippo signaling is an important pathway that plays a crucial role in the regulation of numerous biological processes. The binding of YAP/TAZ transcriptional coactivators to TEAD proteins is the core of Hippo signaling in regulating the expression of a variety of genes that mediate many cellular functions. Abnormalities of Hippo signaling including mutation deficiency, fusion and YAP/TAZ overexpression are often found in solid tumors associated with excessive proliferation, drug resistance, or tumor immune evasion. Blocking the Hippo transcription activation, particularly the TAP/TAZ and TEAD interaction, therefore is an attractive therapeutic strategy for the treatment of advanced solid tumors associated with Hippo dysregulation. Results:We have developed a small molecule inhibitor, KY-001, that can bind to TEAD protein and directly disrupt its interaction with YAP/TAZ, thereby blocking Hippo signaling pathway. KY-001 can bind to TEAD (1-4) proteins with strong YAP/TAZ competitive activities in biochemical assays and can inhibit TEAD-YAP mediated transcriptional signals in cell. KY-001 selectively and potently inhibits the proliferation of cancer cells harboring Hippo deficient mutations, such as mesothelioma, lung cancer and other cell lines. Importantly, KY-001 directly affects the expression of some target genes downstream of YAP/TAZ-TEAD transcription activation in cell. KY-001 can strongly inhibit tumor growth in a dose dependent manner against Hippo mutation mesothelioma cancers in two different xenograft mouse tumor models. In addition, KY-001 shows remarkable synergistic effects with EGFR or KRAS G12C inhibitors in mouse non-small lung cancer models, suggesting it may be a promise therapy for treating targeted therapy induced resistant tumors with Hippo dysregulation. Pre-clinical studies shows that KY-001 has good overall druggable profiles with good safety windows in several animal species. Collectively, KY-001 shows high potency and selectivity in vitro and strong anti-tumor activities against Hippo mutation deficient cancers in pre-clinical models. Conclusions:KY-001 is a small molecule drug candidate which directly inhibits the interactions between TEAD and YAP1/TAZ proteins, thereby blocking the transcriptional activation of downstream Hippo signaling. In various tumor models, KY-001 monotherapy shows good efficacy for Hippo mutation deficient tumors. KY-001 also synergizes with other targeted therapy such as EGFR or KRAS G12C inhibitors for treating non-small lung cancers. KY-001 is expected to enter clinical studies in H2, 2024 for the treatment of Hippo dysregulated solid tumors. Citation Format: Kehao Zhao, Yong Zhag, Yufang Shi, Jian Chen. Discovery of KY-001:A Direct Inhibitor of TEAD-YAP Protein-Protein Interaction for the Treatment of Advanced Solid Tumors with Abnormal Hippo Signaling Pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB428.

The Progress of Small Molecule Targeting BCR-ABL in the Treatment of Chronic Myeloid Leukemia.

Chronic myelogenous leukemia (CML) is a malignant myeloproliferative disease. According to the American Cancer Society's 2021 cancer data report, new cases of CML account for about 15% of all leukemias. CML is generally divided into three stages: chronic phase, accelerated phase, and blast phase. Nearly 90% of patients are diagnosed as a chronic phase. Allogeneic stem cell transplantation and chemotherapeutic drugs, such as interferon IFN-α were used as the earliest treatments for CML. However, they could generate obvious side effects, and scientists had to seek new treatments for CML. A new era of targeted therapy for CML began with the introduction of imatinib, the first-generation BCR-ABL kinase inhibitor. However, the ensuing drug resistance and mutant strains led by T315I limited the further use of imatinib. With the continuous advancement of research, tyrosine kinase inhibitors (TKI) and BCR-ABL protein degraders with novel structures and therapeutic mechanisms have been discovered. From biological macromolecules to classical target protein inhibitors, a growing number of compounds are being developed to treat chronic myelogenous leukemia. In this review, we focus on summarizing the current situation of a series of candidate small-molecule drugs in CML therapy, including TKIs and BCR-ABL protein degrader. The examples provided herein describe the pharmacology activity of small-molecule drugs. These drugs will provide new enlightenment for future treatment directions.

Balanced Permeability Index: A Multiparameter Index for Improved In Vitro Permeability.

The optimization of passive permeability is a key objective for orally available small molecule drug candidates. For drugs targeting the central nervous system (CNS), minimizing P-gp-mediated efflux is an additional important target for optimization. The physicochemical properties most strongly associated with high passive permeability and lower P-gp efflux are size, polarity, and lipophilicity. In this study, a new metric called the Balanced Permeability Index (BPI) was developed that combines these three properties. The BPI was found to be more effective than any single property in classifying molecules based on their permeability and efflux across a diverse range of chemicals and assays. BPI is easy to understand, allowing researchers to make decisions about which properties to prioritize during the drug development process.

The novel drug candidate S2/IAPinh improves survival in models of pancreatic and ovarian cancer

Cancer selective apoptosis remains a therapeutic challenge and off-target toxicity has limited enthusiasm for this target clinically. Sigma-2 ligands (S2) have been shown to enhance the cancer selectivity of small molecule drug candidates by improving internalization. Here, we report the synthesis of a novel drug conjugate, which was created by linking a clinically underperforming SMAC mimetic (second mitochondria-derived activator of caspases; LCL161), an inhibitor (antagonist) of inhibitor of apoptosis proteins (IAPinh) with the sigma-2 ligand SW43, resulting in the new chemical entity S2/IAPinh. Drug potency was assessed via cell viability assays across several pancreatic and ovarian cancer cell lines in comparison with the individual components (S2 and IAPinh) as well as their equimolar mixtures (S2 + IAPinh) both in vitro and in preclinical models of pancreatic and ovarian cancer. Mechanistic studies of S2/IAPinh-mediated cell death were investigated in vitro and in vivo using syngeneic and xenograft mouse models of murine pancreatic and human ovarian cancer, respectively. S2/IAPinh demonstrated markedly improved pharmacological activity in cancer cell lines and primary organoid cultures when compared to the controls. In vivo testing demonstrated a marked reduction in tumor growth rates and increased survival rates when compared to the respective control groups. The predicted mechanism of action of S2/IAPinh was confirmed through assessment of apoptosis pathways and demonstrated strong target degradation (cellular inhibitor of apoptosis proteins-1 [cIAP-1]) and activation of caspases 3 and 8. Taken together, S2/IAPinh demonstrated efficacy in models of pancreatic and ovarian cancer, two challenging malignancies in need of novel treatment concepts. Our data support an in-depth investigation into utilizing S2/IAPinh for the treatment of cancer.

Electroretinographical Analysis of the Effect of BGP-15 in Eyedrops for Compensating Global Ischemia-Reperfusion in the Eyes of Sprague Dawley Rats.

Retinal vascular diseases and consequential metabolic disturbances in the eye are major concerns for healthcare systems all around the world. BGP-15, a drug candidate small-molecule [O-(3-piperidino-2-hydroxy-1-propyl) nicotinic amidoxime dihydrochloride], has been formerly demonstrated by our workgroup to be retinoprotective both in the short and long term. Based on these results, the present study was performed to investigate the efficacy of BGP in an eyedrop formulation containing sulfobutylether-β-cyclodextrin (SBECD), which is a solubility enhancer as well. Electroretinographical evaluations were carried out and BGP was demonstrated to improve both scotopic and photopic retinal a- and b-waves, shorten their implicit times and restore oscillatory potentials after ischemia-reperfusion. It was also observed to counteract retinal thinning after ischemia-reperfusion in the eyes of Sprague Dawley rats. This small-molecule drug candidate is able to compensate for experimental global eye ischemia-reperfusion injury elicited by ligation of blood vessels in rats. We successfully demonstrated that BGP is able to exert its protective effects on the retina even if administered in the form of eyedrops.

Patient-Derived Blood-Brain Barrier Model for Screening Copper Bis(thiosemicarbazone) Complexes as Potential Therapeutics in Alzheimer's Disease.

Alzheimer's disease (AD) is the most prevalent cause of dementia characterized by a progressive cognitive decline. Addressing neuroinflammation represents a promising therapeutic avenue to treat AD; however, the development of effective antineuroinflammatory compounds is often hindered by their limited blood-brain barrier (BBB) permeability. Consequently, there is an urgent need for accurate, preclinical AD patient-specific BBB models to facilitate the early identification of immunomodulatory drugs capable of efficiently crossing the human AD BBB. This study presents a unique approach to BBB drug permeability screening as it utilizes the familial AD patient-derived induced brain endothelial-like cell (iBEC)-based model, which exhibits increased disease relevance and serves as an improved BBB drug permeability assessment tool when compared to traditionally employed in vitro models. To demonstrate its utility as a small molecule drug candidate screening platform, we investigated the effects of diacetylbis(N(4)-methylthiosemicarbazonato)copper(II) (CuII(atsm)) and a library of metal bis(thiosemicarbazone) complexes─a class of compounds exhibiting antineuroinflammatory therapeutic potential in neurodegenerative disorders. By evaluating the toxicity, cellular accumulation, and permeability of those compounds in the AD patient-derived iBEC, we have identified 3,4-hexanedione bis(N(4)-methylthiosemicarbazonato)copper(II) (CuII(dtsm)) as a candidate with good transport across the AD BBB. Furthermore, we have developed a multiplex approach where AD patient-derived iBEC were combined with immune modulators TNFα and IFNγ to establish an in vitro model representing the characteristic neuroinflammatory phenotype at the patient's BBB. Here, we observed that treatment with CuII(dtsm) not only reduced the expression of proinflammatory cytokine genes but also reversed the detrimental effects of TNFα and IFNγ on the integrity and function of the AD iBEC monolayer. This suggests a novel pathway through which copper bis(thiosemicarbazone) complexes may exert neurotherapeutic effects on AD by mitigating BBB neuroinflammation and related BBB integrity impairment. Together, the presented model provides an effective and easily scalable in vitro BBB platform for screening AD drug candidates. Its improved translational potential makes it a valuable tool for advancing the development of metal-based compounds aimed at modulating neuroinflammation in AD.

Methotrexate Inhibits the Binding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Receptor Binding Domain to the Host-Cell Angiotensin-Converting Enzyme-2 (ACE-2) Receptor.

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus mutates, finding effective drugs becomes more challenging. In this study, we use ultrasensitive frequency locked microtoroid optical resonators in combination with in silico screening to search for COVID-19 drugs that can stop the virus from attaching to the human angiotensin-converting enzyme 2 (hACE2) receptor in the lungs. We found 29 promising candidates that could block the binding site and selected four of them that were likely to bind very strongly. We tested three of these candidates using frequency locked optical whispering evanescent resonator (FLOWER), a label-free sensing method based on microtoroid resonators. FLOWER has previously been used for sensing single macromolecules. Here we show, for the first time, that FLOWER can provide accurate binding affinities and sense the inhibition effect of small molecule drug candidates without labels, which can be prohibitive in drug discovery. One of the candidates, methotrexate, showed binding to the spike protein 1.8 million times greater than that to the receptor binding domain (RBD) binding to hACE2, making it difficult for the virus to enter cells. We tested methotrexate against different variants of the SARS-CoV-2 virus and found that it is effective against all four of the tested variants. People taking methotrexate for other conditions have also shown protection against the original SARS-CoV-2 virus. Normally, it is assumed that methotrexate inhibits the replication and release of the virus. However, our findings suggest that it may also block the virus from entering cells. These studies additionally demonstrate the possibility of extracting candidate ligands from large databases, followed by direct receptor-ligand binding experiments on the best candidates using microtoroid resonators, thus creating a workflow that enables the rapid discovery of new drug candidates for a variety of applications.