Screening Of Drug Candidates Research Articles

Computation of Absolute Binding Free Energies for Noncovalent Inhibitors with SARS-CoV-2 Main Protease.

Accurate, routine calculation of absolute binding free energies (ABFEs) for protein-ligand complexes remains a key goal of computer-aided drug design since it can enable screening and optimization of drug candidates. For development and testing of related methods, it is important to have high-quality datasets. To this end, from our own experimental studies, we have selected a set of 16 inhibitors of the SARS-CoV-2 main protease (Mpro) with structural diversity and well-distributed BFEs covering a 5 kcal/mol range. There is also minimal structural uncertainty since X-ray crystal structures have been deposited for 12 of the compounds. For methods testing, we report ABFE results from 2 μs molecular dynamics (MD) simulations using free energy perturbation (FEP) theory. The correlation of experimental and computed results is encouraging, with a Pearson's r2 of 0.58 and a Kendall τ of 0.24. The results indicate that current FEP-based ABFE calculations can be used for identification of active compounds (hits). While their accuracy for lead optimization is not yet sufficient, this activity remains addressable in separate lead series by relative BFE calculations.

Inhibitors of Farnesyl Diphosphate Synthase and Squalene Synthase: Potential Source for Anti-Trypanosomatidae Drug Discovery

Trypanosomatids are mainly responsible for leishmaniasis, sleeping sickness, and Chagas disease, which are the most challenging among the neglected tropical diseases due to the problem of drug resistance. Although problems of target deconvolution and polypharmacology are encountered, a target-based approach is a rational method for screening drug candidates targeting a biomolecule that causes infections. The present study aims to summarize the latest information regarding potential inhibitors of squalene synthase and farnesyl phosphate synthase with anti-Trypanosomatidae activity. The information was obtained by referencing textbooks and major scientific databases from their inception until April 2023. Based on in vitro experiments, more than seventy compounds were reported to inhibit squalene synthase and farnesyl diphosphate synthase. Among these compounds, more than 30 were found to be active in vitro against Trypanosomatidae, inferring that these compounds can be used as scaffolds to develop new drugs against trypanosomatid-related infections. Overall, natural and synthetic products can inhibit enzymes that are crucial for the survival and virulence of trypanosomatids. Moreover, in vitro experiments have confirmed the activity of more than half of these inhibitors using cell-based assays. Nevertheless, additional studies on the cytotoxicity, pharmacokinetics, and lead optimization of potent anti-Trypanosomatid compounds should be investigated.

CMMS-GCL: Cross-Modality Metabolic Stability Prediction with Graph Contrastive Learning.

Metabolic stability plays a crucial role in the early stages of drug discovery and development. Accurately modeling and predicting molecular metabolic stability has great potential for the efficient screening of drug candidates as well as the optimization of lead compounds. Considering wet-lab experiment is time-consuming, laborious, and expensive, in silico prediction of metabolic stability is an alternative choice. However, few computational methods have been developed to address this task. In addition, it remains a significant challenge to explain key functional groups determining metabolic stability. To address these issues, we develop a novel cross-modality graph contrastive learning model named CMMS-GCL for predicting the metabolic stability of drug candidates. In our framework, we design deep learning methods to extract features for molecules from two modality data, i.e., SMILES sequence and molecule graph. In particular, for the sequence data, we design a multi-head attention BiGRU-based encoder to preserve the context of symbols to learn sequence representations of molecules. For the graph data, we propose a graph contrastive learning-based encoder to learn structure representations by effectively capturing the consistencies between local and global structures. We further exploit fully connected neural networks to combine the sequence and structure representations for model training. Extensive experimental results on two datasets demonstrate that our CMMS-GCL consistently outperforms seven state-of-the-art methods. Furthermore, a collection of case studies on sequence data and statistical analyses of the graph structure module, strengthens the validation of the interpretability of crucial functional groups recognized by CMMS-GCL. Overall, CMMS-GCL can serve as an effective and interpretable tool for predicting metabolic stability, identifying critical functional groups, and thus facilitating the drug discovery process and lead compound optimization. The code and data underlying this article are freely available at https://github.com/dubingxue/CMMS-GCL. Supplementary data are available at Bioinformatics online.

HCS-Splice: A High-Content Screening Method to Advance the Discovery of RNA Splicing-Modulating Therapeutics.

Nucleic acid therapeutics have demonstrated an impressive acceleration in recent years. They work through multiple mechanisms of action, including the downregulation of gene expression and the modulation of RNA splicing. While several drugs based on the former mechanism have been approved, few target the latter, despite the promise of RNA splicing modulation. To improve our ability to discover novel RNA splicing-modulating therapies, we developed HCS-Splice, a robust cell-based High-Content Screening (HCS) assay. By implementing the use of a two-colour (GFP/RFP) fluorescent splicing reporter plasmid, we developed a versatile, effective, rapid, and robust high-throughput strategy for the identification of potent splicing-modulating molecules. The HCS-Splice strategy can also be used to functionally confirm splicing mutations in human genetic disorders or to screen drug candidates. As a proof-of-concept, we introduced a dementia-related splice-switching mutation in the Microtubule-Associated Protein Tau (MAPT) exon 10 splicing reporter. We applied HCS-Splice to the wild-type and mutant reporters and measured the functional change in exon 10 inclusion. To demonstrate the applicability of the method in cell-based drug discovery, HCS-Splice was used to evaluate the efficacy of an exon 10-targeting siRNA, which was able to restore the correct alternative splicing balance.

The potential of phenothiazinium dyes as cytotoxicity markers in cisplatin-treated cells

Assessing the in vitro toxicity of compounds on cell cultures is an important step during the screening of candidate molecules for diverse applications. Among the strategies employed to determine cytotoxicity, MTT, neutral red, and resazurin are commonly used. Methylene blue (MB), a phenothiazinium salt, has several uses, such as dye, redox indicator, and even as treatment for human disease and health conditions, such as malaria and methemoglobinemia. However, MB has only been sparsely used as a cellular toxicity indicator. As a viability indicator, MB is mostly applied to fixed cultures at high concentrations, especially when compared to MTT or neutral red. Here we show that MB and its related compounds new methylene blue (NMB), toluidine blue O (TBO), and dimethylmethylene blue (DMMB) can be used as cytotoxicity indicators in live (non-fixed) cells treated for 72 h with DMSO and cisplatin. We compared dye uptake between phenothiazinium dyes and neutral red by analyzing supernatant and cell content via visible spectra scanning and microscopy. All dyes showed a similar ability to assess cell toxicity compared to either MTT or neutral red. Our method represents a cost-effective alternative to in vitro cytotoxicity assays using cisplatin or DMSO, indicating the potential of phenothiazinium dyes for the screening of candidate drugs and other applications.

Rational Design of Trident Aptamer Scaffold for Rapid and Accurate Monitoring of 25-Hydroxyvitamin D3 Metabolism in Living Cells.

The level of 25-hydroxyvitamin D3 [25(OH)VD3] in human blood is considered as the best indicator of vitamin D status, and its deficiency or excess can lead to various health problems. Current methods for monitoring 25(OH)VD3 metabolism in living cells have limitations in terms of sensitivity and specificity and are often expensive and time-consuming. To address these issues, an innovative trident scaffold-assisted aptasensor (TSA) system has been developed for the online quantitative monitoring of 25(OH)VD3 in complex biological environments. Through the computer-aided design, the TSA system includes an aptamer molecule recognition layer that is uniformly oriented, maximizing binding site availability, and enhancing sensitivity. The TSA system achieved the direct, highly sensitive, and selective detection of 25(OH)VD3 over a wide concentration range (17.4-12,800 nM), with a limit of detection of 17.4 nM. Moreover, we evaluated the efficacy of the system in monitoring the biotransformation of 25(OH)VD3 in human liver cancer cells (HepG2) and normal liver cells (L-02), demonstrating its potential as a platform for drug-drug interaction studies and candidate drug screening.

Emerging trends in organ-on-a-chip systems for drug screening.

New drug discovery is under growing pressure to satisfy the demand from a wide range of domains, especially from the pharmaceutical industry and healthcare services. Assessment of drug efficacy and safety prior to human clinical trials is a crucial part of drug development, which deserves greater emphasis to reduce the cost and time in drug discovery. Recent advances in microfabrication and tissue engineering have given rise to organ-on-a-chip, an invitro model capable of recapitulating human organ functions invivo and providing insight into disease pathophysiology, which offers a potential alternative to animal models for more efficient pre-clinical screening of drug candidates. In this review, we first give a snapshot of general considerations for organ-on-a-chip device design. Then, we comprehensively review the recent advances in organ-on-a-chip for drug screening. Finally, we summarize some key challenges of the progress in this field and discuss future prospects of organ-on-a-chip development. Overall, this review highlights the new avenue that organ-on-a-chip opens for drug development, therapeutic innovation, and precision medicine.

Exploration of potential molecular mechanisms and genotoxicity of anti-cancer drugs using next generation knowledge discovery methods.

Accurate identification of molecular and toxicological functions of potential drug candidates is crucial for drug discovery and development. This may aid in the evaluation of the risks of genotoxicity and carcinogenesis. In addition, in silico characterization of existing and new drugs might offer clues for future investigations and aid in the development of anticancer treatments. Using next-generation knowledge discovery (NGKD) methodology, we endeavored to establish a risk assessment of anticancer drugs for their molecular mechanism(s) and genotoxicity. This study was performed at the Faculty of Applied Medical Sciences, King Abdulaziz University (KAU), Jeddah, Saudi Arabia, in November 2022. Using innovative in silico model systems, we assessed the molecular mechanism of action and toxicity of around 20 distinct substances such as Deguelin, Etoposide, Camptothecin, Cytarabine (Ara-C), Cisplatin, Hydroxyurea, Trichostain A, Antimycin, Colchicine, 2-deoxyglucose, Tunicamycin, Thapsigargin, Vinblastin, Docetaxel, Oxaliplatin, Methotrexate, 5-flurouracil, Bleomycin, Taxol (Paclitaxel), and Apicidin. Using the Ingenuity Pathway Analysis (IPA) knowledge base, the number of targets for each compound was determined in silico. Subsequently, they were examined using Fisher's exact test and Benjamini Hochberg Multiple Testing Correction (P<0.05) and submitted to core analysis with IPA to decode the biological and toxicological activities differently controlled by these drugs. In addition, a multiple comparison module in IPA was used to compare the core analyses of each molecule. In addition, we obtained the top 100 protein targets of Etoposide, Camptothecin, and Ara-C using SwissTargetPrediction, as well as the key pathways and gene ontologies affected by these drugs and disease associations using the WebGestalt tool. We identified distinct toxicological signatures and canonical signaling pathways in tumor cell lines regulated by these 20 anticancer drugs. These signaling pathways included cell death and apoptosis in addition to molecular processes, p53 signaling, and aryl hydrocarbon receptor signaling. The TP53 signaling pathway is utilized by these agents to effectively trigger cell death and apoptosis, and p53 functions as a master regulator in a variety of cellular stress responses, including genotoxic stress. Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and effectiveness of treatment. Our mechanism based "NGKD" tools have more relevance for the identification of safer therapies and has the potential to lead to the rational screening of drug candidates targeting specific molecular networks and canonical pathways implicated in cancer and genotoxicity. In addition, the combination of protein, microRNA and metabolome profiles may be essential for the development of translatable biomarkers for the safety and efficacy of pharmacotherapeutic agents.Our research has laid the groundwork for the discovery of additional biomarkers that assess both the safety and the effectiveness of a treatment.

Simple Coumarins from Peucedanum luxurians Fruits: Evaluation of Anxiolytic Activity and Influence on Gene Expression Related to Anxiety in Zebrafish Model.

Anxiety is one of the most common central nervous system disorders, affecting at least one-quarter of the worldwide population. The medications routinely used for the treatment of anxiety (mainly benzodiazepines) are a cause of addiction and are characterized by many undesirable side effects. Thus, there is an important and urgent need for screening and finding novel drug candidates that can be used in the prevention or treatment of anxiety. Simple coumarins usually do not show side effects, or these effects are much lower than in the case of synthetic drugs acting on the central nervous system (CNS). This study aimed to evaluate the anxiolytic activity of three simple coumarins from Peucedanum luxurians Tamamsch, namely officinalin, stenocarpin isobutyrate, and officinalin isobutyrate, in a 5 dpf larval zebrafish model. Moreover, the influence of the tested coumarins on the expression of genes involved in the neural activity (c-fos, bdnf) or dopaminergic (th1), serotoninergic (htr1Aa, htr1b, htr2b), GABA-ergic (gabarapa, gabarapb), enkephalinergic (penka, penkb), and galaninergic (galn) neurotransmission was assessed by quantitative PCR. All tested coumarins showed significant anxiolytic activity, with officinalin as the most potent compound. The presence of a free hydroxyl group at position C-7 and the lack of methoxy moiety at position C-8 might be key structural features responsible for the observed effects. In addition, officinalin and its isobutyrate upregulated the expression of genes involved in neurotransmission and decreased the expression of genes connected with neural activity. Therefore, the coumarins from P. luxurians might be considered as promising drug candidates for the therapy of anxiety and related disorders.

Retraction: Screening of drug candidates against Endothelin-1 to treat hypertension using computational based approaches: Molecular docking and dynamics simulation.

Retraction: Screening of drug candidates against Endothelin-1 to treat hypertension using computational based approaches: Molecular docking and dynamics simulation.

1419 Pre-clinical in-vitro assays for high throughput screening of drug candidates for protection and restoration of immune privilege in alopecia areata

1419 Pre-clinical in-vitro assays for high throughput screening of drug candidates for protection and restoration of immune privilege in alopecia areata

1126 A pilot of a microdevice for in situ candidate drug screening in cutaneous lesions of T-cell lymphoma

1126 A pilot of a microdevice for in situ candidate drug screening in cutaneous lesions of T-cell lymphoma

HIV-1/HBV Coinfection Accurate Multitarget Prediction Using a Graph Neural Network-Based Ensemble Predicting Model.

HIV and HBV infection are both serious public health challenges. There are more than approximately 4 million patients coinfected with HIV and HBV worldwide, and approximately 5% to 15% of those infected with HIV are coinfected with HBV. Disease progression is more rapid in patients with coinfection, which significantly increases the likelihood of patients progressing from chronic hepatitis to cirrhosis, end-stage liver disease, and hepatocellular carcinoma. HIV treatment is complicated by drug interactions, antiretroviral (ARV) hepatotoxicity, and HBV-related immune reconditioning and inflammatory syndromes. Drug development is a highly costly and time-consuming procedure with traditional experimental methods. With the development of computer-aided drug design techniques, both machine learning and deep learning have been successfully used to facilitate rapid innovations in the virtual screening of candidate drugs. In this study, we proposed a graph neural network-based molecular feature extraction model by integrating one optimal supervised learner to replace the output layer of the GNN to accurately predict the potential multitargets of HIV-1/HBV coinfections. The experimental results strongly suggested that DMPNN + GBDT may greatly improve the accuracy of binary-target predictions and efficiently identify the potential multiple targets of HIV-1 and HBV simultaneously.

A Novel Tool to Identify Bactericidal Compounds against Vulnerable Targets in Drug-Tolerant M. tuberculosis found in Caseum.

Caseous necrosis is a hallmark of tuberculosis (TB) pathology and creates a niche for drug-tolerant persisters within the host. Cavitary TB and high bacterial burden in caseum require longer treatment duration. An in vitro model that recapitulates the major features of Mycobacterium tuberculosis (Mtb) in caseum would accelerate the identification of compounds with treatment-shortening potential. We have developed a caseum surrogate model consisting of lysed and denatured foamy macrophages. Upon inoculation of Mtb from replicating cultures, the pathogen adapts to the lipid-rich matrix and gradually adopts a nonreplicating state. We determined that the lipid composition of ex vivo caseum and the surrogate matrix are similar. We also observed that Mtb in caseum surrogate accumulates intracellular lipophilic inclusions (ILI), a distinctive characteristic of quiescent and drug-tolerant Mtb. Expression profiling of a representative gene subset revealed common signatures between the models. Comparison of Mtb drug susceptibility in caseum and caseum surrogate revealed that both populations are similarly tolerant to a panel of TB drugs. By screening drug candidates in the surrogate model, we determined that the bedaquiline analogs TBAJ876 and TBAJ587, currently in clinical development, exhibit superior bactericidal against caseum-resident Mtb, both alone and as substitutions for bedaquiline in the bedaquiline-pretomanid-linezolid regimen approved for the treatment of multidrug-resistant TB. In summary, we have developed a physiologically relevant nonreplicating persistence model that reflects the distinct metabolic and drug-tolerant state of Mtb in caseum. IMPORTANCE M. tuberculosis (Mtb) within the caseous core of necrotic granulomas and cavities is extremely drug tolerant and presents a significant hurdle to treatment success and relapse prevention. Many in vitro models of nonreplicating persistence have been developed to characterize the physiologic and metabolic adaptations of Mtb and identify compounds active against this treatment-recalcitrant population. However, there is little consensus on their relevance to in vivo infection. Using lipid-laden macrophage lysates, we have designed and validated a surrogate matrix that closely mimics caseum and in which Mtb develops a phenotype similar to that of nonreplicating bacilli in vivo. The assay is well suited to screen for bactericidal compounds against caseum-resident Mtb in a medium-throughput format, allowing for reduced reliance on resource intensive animal models that present large necrotic lesions and cavities. Importantly, this approach will aid the identification of vulnerable targets in caseum Mtb and can accelerate the development of novel TB drugs with treatment-shortening potential.

Abstract 1382: Expression and intracellular translocation of cancer biomarkers in hepatocarcinoma cells induced by changes in mitochondrial metabolism

Abstract Hepatocarcinoma is one of the most common cancer types in the U.S. with limited treatment options and poor survival rate. Recently, cancer bioenergetics emerged as a promising source of targets to develop novel anticancer agents. The identification of biomarkers is essential for screening and validation of small molecules proposed as chemotherapeutic agents. In this regard, there is a great need for high-throughput/high-content methods, which require short and reproducible sample preparation. In this project, we used the erastin-like compound X1 in the well-characterized SNU-449 hepatocarcinoma cell line. Erastin initially enhances mitochondrial function and ROS formation leading to subsequent mitochondrial dysfunction. As readout, we employed directly and indirectly labeled fluorescent antibodies to visualize and quantify expression of proliferative and antiproliferative markers Ki-67 and cytoskeleton-associated protein 4/p63 (CKAP4/p63), as well as expression and intracellular translocation of the tumor suppressor protein p53. Using the Agilent BioTek Cytation 5 cell imaging multimode reader and Agilent BioTek Gen5 microplate reader and imager software, we successfully validated these markers and the corresponding antibodies as tools to study long-term effects of xenobiotics on mitochondrial bioenergetics. The method allows for fast and reliable screening of potential drug candidates. Acknowledgement: This work was supported in part by the Chan Zuckerberg Initiative, Silicon Valley Community Foundation, and the NIH S10 OD028663 to M.G. and by the U.S. National Institutes of Health (NIH/NCI) R01 CA184456, and South Carolina Translational Research Pilot Project UL1 TR001450-SCTR to E.N.M. Citation Format: Bradley R. Larson, Monika Gooz, Eduardo Maldonado. Expression and intracellular translocation of cancer biomarkers in hepatocarcinoma cells induced by changes in mitochondrial metabolism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1382.

Abstract 199: Novel platform for automation of high throughput drug discovery using patient derived colorectal cancer organoids

Abstract Most potential oncology drugs fail at the later stages of the drug development pipeline and in clinical trials, despite having promising data for their efficacy in vitro. This high failure rate is partly due to insufficient predictive models being used to screen drug candidates in the early stages of drug discovery. As such, there is a need to develop and utilize more representative models that are amendable for efficient testing of drug efficacy to discover new therapeutic targets. 3D cell models, specifically patient-derived organoids (PDOs), offer a promising solution to this problem. Cells grown in 3D can better mimic cell-cell interactions and the tissue microenvironment, including cancer stem cell niches. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the therapeutic value of using PDOs to improve therapeutic outcomes. However, challenges commonly associated with using these organoids, such as assay reproducibility, ability to scale up, and cost have limited their widespread adoption as a primary screening method in drug discovery. To address some of the hurdles associated with the use of PDOs in large scale screens, a semi-automated bioprocess has been developed for the controlled production of standardized PDOs at scale. PDOs cultured in the bioprocessor were uniform in size, show high viability and were produced in repeatable batches in an assay-ready format. In this study, patient-derived colorectal cancer (CRC) organoids were seeded in high density (96 or 384 well) microtiter plates manually. We also tested the feasibility of scaling up the use of these CRCs by using an automated liquid handler or a bioprinter to seed and culture the PDOs. CRC PDOs were treated with selected anti-cancer compounds at various concentrations. Compound effects were monitored over time using transmitted light imaging. For the analysis of organoid growth and development, a deep learning-based image segmentation model was developed to automate the segmentation of the organoids. Using this approach, we tracked the effects of the compounds on colorectal organoid size, morphology, texture, and additional morphological and phenotypic readouts. A viability assay was carried out using live/dead cell dyes and the PDOs were imaged in 3D on a high-content confocal imager. Out of the tested panel of known anti-cancer drugs, we found that PDOs treated with romidepsin and trametinib showed the most significant reduction in size, with a greater number of dead cells compared to the other compounds and controls. Overall, our results show the potential for the utility of PDOs in both precision medicine and high throughput drug discovery applications, when using automation with high-content imaging. Citation Format: Angeline Lim, Zhisong Tong, Prathyushakrishna Macha, Oksana Sirenkp. Novel platform for automation of high throughput drug discovery using patient derived colorectal cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 199.

Abstract 3873: Candidate drug screening for TP53-mutated AML

Abstract Acute myeloid leukemia (AML) is a clonal blood malignancy characterized by arrested maturation and abnormal proliferation of hematopoietic precursor cells. This paralysis of normal bone marrow function leads to severe decreased immune function and bleeding tendency, and if not treated, it is an acute disease that dies within a few months due to rapid progression of AML. TP53 mutations occur in 5% to 10% of patients with de-novo acute myeloid leukemia (AML), with higher frequency in patients with relapsed/refractory AML. The treatment approach for many years has used combination chemotherapy, with usually an anthracycline and cytarabine as the foundation. These induction therapy's complete response is achieved in 60 to 85% of adults who are 60 years of age or younger. In patients who are older than 60 years of age, complete response rates are inferior 40 to 60%. TP53 mutated acute myeloid leukemia (AML) responds poorly to the conventional induction therapy and has a short overall survival rate with a median of 5-9 months. Poor outcomes in TP53 mutated AML following chemotherapy have been observed and treatment options remain limited. Therefore, this study attempted to explore the drug candidates for effective treatment of TP53 mutated AML. To study the cellular response to TP53-targeted therapy, we used the human AML cell line Kasumi-1, which harbors a homozygous TP53 mutation. We treated Kasumi-1 cells with cytarabine and Idarubicin combi-treatment. And we produced Drug Tolerant Persisters (DTPs) which is a minor population of cancer cells may evade cell death from chemotherapy and targeted therapy by entering a reversible slow proliferation state. Similar to a previously described DTP phenotype the DTPs that survive cytarabine and Idarubicin combi-treatment displayed cell-cycle arrest and resistance to further cytarabine and Idarubicin combi-treatment. And we selected 125 drug candidates that would be effective for TP53 mutated AML through in silico analysis and therapy strategies targeting p53. The drug candidates are composed of Compounds with the ability to reactivate mutant p53, Compounds directly target mutant p53, Synthetic lethal partners with mutant p53, and Compounds with the ability to anti-Leukemic Stem Cell and antineoplastic. We single out 46 of the 125 compounds for functional validation in DTPs. We chose these compounds because many of them are similar subtypes, suggesting they may have a common effect and mechanism. Using in vitro Cytotoxicity assay, we screened 46 candidate compounds at multiple doses and confirmed several drugs that effectively eliminate DTPs. Collectively, our study indicates that the combination of conventional drug and validated drug has the potential to eliminate DTPs and therefore prevent minimal residual disease, mutational drug resistance, and relapse in TP53-mutant AML. Citation Format: Daehyeon Gwak, Dong Chan Kim, Heejun Jang, Jun Liu, Ja Min Byun, Junshik Hong, Dong Yeop Shin, Sung-Soo Yoon. Candidate drug screening for TP53-mutated AML. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3873.

Development of In Vitro Assays with the Canine Hookworm Uncinaria stenocephala and Assessment of Natural Plant Products for Anti-Parasitic Activity.

Enteric helminth infection is an increasing concern in companion animals due to reports of resistance to commonly used anthelmintic drugs. Thus, the assessment of new therapeutic options such as bioactive dietary additives is of high importance. Here, we adapted egg hatch, larval migration, and larval motility assays to screen extracts of several natural ingredients against the canine hookworm Uncinaria stenocephala, a prevalent parasite of dogs in northern Europe. Egg hatch and larval migration assays were established showing that the anthelmintic drugs levamisole and albendazole had strong anti-parasitic activity against U. stenocephala, validating the use of these assays for the assessment of novel anti-parasitic substances. Subsequently, we identified that extracts from the seaweed Saccharina latissima, but not extracts from grape seed or chicory, significantly inhibited both hatching and larval migration. Finally, we showed that α-linolenic acid, a putative anti-parasitic compound from S. latissima, also exhibited anti-parasitic activity. Collectively, our results established a platform for the screening for anthelmintic resistance or novel drug candidates against U. stenocephala and highlighted the potential use of seaweed extracts as a functional food component to help control hookworm infection in dogs.

Relationship between Monoclonal Gammopathy of undetermined significance and multiple myeloma via online database analysis.

To explore the relationship between Monoclonal Gammopathy of undetermined significance (MGUS) and Multiple Myeloma (MM) based on bioinformatics methods. In this study, we conducted bioinformatics to identify genes associated with MGUS and MM using the PubMed pubmed2ensemble (http://pubmed2ensembl.ls.manchester. ac.uk/) until 2021. Gene ontology function was used to label overlapping genes, and Kyoto Encyclopedia of Genes and Genomes analysis was used to identify enriched pathways. The cluster-1 genes obtained from Cytoscape were analyzed by Comparative Toxicogenomics Database (CTD, http://ctdbase.org/) and then used to screen candidate drugs using the DSigDB database (https://amp.pharm.mssm.edu/Enrichr/). In total, 227 genes were common to both MGUS and MM. These genes were significantly associated with cytokine-cytokine receptor interaction and the PI3K-Akt signaling pathway. The protein-protein interaction network revealed that TNF, IL-1B, IL-6, CSF2, CXCL8, and IL-10 were among the core genes of MM. Finally, eight candidate drugs showed maximum interaction with core genes, which could potentially prevent MGUS from progressing to MM. The progression of MGUS to MM is driven by aberrant cytokine secretion, which leads to inflammation immune dysfunction, and dysregulation of the PI3K/AKT/mTOR signaling pathway.

Natural Lipid Extracts as an Artificial Membrane for Drug Permeability Assay: In Vitro and In Silico Characterization

In vitro non-cellular permeability models such as the parallel artificial membrane permeability assay (PAMPA) are widely applied tools for early-phase drug candidate screening. In addition to the commonly used porcine brain polar lipid extract for modeling the blood-brain barrier's permeability, the total and polar fractions of bovine heart and liver lipid extracts were investigated in the PAMPA model by measuring the permeability of 32 diverse drugs. The zeta potential of the lipid extracts and the net charge of their glycerophospholipid components were also determined. Physicochemical parameters of the 32 compounds were calculated using three independent forms of software (Marvin Sketch, RDKit, and ACD/Percepta). The relationship between the lipid-specific permeabilities and the physicochemical descriptors of the compounds was investigated using linear correlation, Spearman correlation, and PCA analysis. While the results showed only subtle differences between total and polar lipids, permeability through liver lipids highly differed from that of the heart or brain lipid-based models. Correlations between the in silico descriptors (e.g., number of amide bonds, heteroatoms, and aromatic heterocycles, accessible surface area, and H-bond acceptor-donor balance) of drug molecules and permeability values were also found, which provides support for understanding tissue-specific permeability.