Therapeutic Protein Targets Research Articles

EP.06B.14 Differential Expression in Potential Therapeutic Target Protein by Treatment in Small Cell Lung Cancer with and without Transformation

EP.06B.14 Differential Expression in Potential Therapeutic Target Protein by Treatment in Small Cell Lung Cancer with and without Transformation

Hexokinase 2 as an independent risk factor for worse patient survival in esophageal adenocarcinoma and as a potential therapeutic target protein: A retrospective, single‑center cohort study.

Cancer cells exhibit a distinct metabolic profile that features an upregulation of less efficient glycolysis accompanied by lactate production for energy generation, in contract to the characteristic metabolism of normal cells. Consequently, cancer research has focused on the enzymes that participate in these cancer metabolic pathways. Among them, hexokinase 2 (HK2) has an important position as the initial enzyme in the glycolytic pathway. Increased expression levels of HK2 have been correlated with an increased risk of poor patient outcomes and advanced tumor stages in a number of malignant tumors, such as gastric carcinoma. The present study aimed to investigate the specific role of HK2 in patients diagnosed with esophageal adenocarcinoma. A total of 643 patients with esophageal adenocarcinoma were included. Immunohistochemical staining and HK2 mRNA in situ probes were used to investigate the association of HK2 expression levels with clinical and molecular tumor characteristics. Patients who exhibited high HK2 expression levels demonstrated significantly reduced overall survival (OS) times compared with patients who exhibited low HK2 expression levels (29.6 vs. 39.9 months, respectively; P=0.027). Furthermore, high HK2 expression levels were demonstrated to be an independent risk factor for reduced patient survival (hazard ratio, 1.65; 95% CI, 1.09-2.50; P=0.018). Significantly reduced patient survival was also demonstrated in the subgroups of male patients, patients with primarily resected tumors, patients with HER2-negative tumors and patients with tumors exhibiting Y chromosome loss. Elevated expression of HK2 was identified as a risk factor for unfavorable patient survival in esophageal adenocarcinoma. This revelation suggests the potential for future diagnostic and therapeutic avenues tailored to this specific patient subset. Identifying patients with high HK2 expression may pinpoint a higher-risk cohort, paving the way for comprehensive prospective studies that could advocate for intensified monitoring and more aggressive therapeutic regimens. Furthermore, the targeted inhibition of HK2 could hold promise as a strategy to potentially enhance patient outcomes.

Unveiling the Mechanism of Compound Ku-Shen Injection in Liver Cancer Treatment through an Ingredient-Target Network Analysis.

Compound Ku-Shen Injection (CKI) is a traditional Chinese medicine preparation derived from Ku-Shen and Bai-Tu-Ling, commonly used in the adjunctive treatment of advanced cancers, including liver cancer. However, the underlying mechanisms of CKI's effectiveness in cancer treatment are not well defined. This study employs network pharmacology to investigate the traditional Chinese medicine (TCM) compatibility theory underlying CKI's action in treating liver cancer, with findings substantiated by molecular docking and in vitro experiments. Sixteen active components were identified from CKI, along with 193 potential targets for treating liver cancer. Key therapeutic target proteins, including EGFR and ESR1, were also identified. KEGG enrichment results showed that the neuroactive ligand-receptor interaction, cAMP signaling pathway, and serotonergic synapses make up the key pathway of CKI in the treatment of liver cancer. Molecular docking results confirmed that the key active ingredients effectively bind to the core targets. CCK-8 cytotoxic experiment results show that the CKI key components of oxymatrine and matrine can inhibit the growth of HepG2 liver cancer cell proliferation. A Western blot analysis revealed that oxymatrine suppresses the expression of EGFR, contributing to its therapeutic efficacy against liver cancer. our study elucidated the therapeutic mechanism of CKI in treating liver cancer and unveiled the underlying principles of its TCM compatibility through its mode of action.

Differential expression in potential therapeutic target protein by treatment in small cell lung cancer with and without transformation.

202 Background: Small cell lung cancer (SCLC) is a disease with a poor prognosis. Besides combination strategy with immune checkpoint inhibitors (ICIs) and cytotoxic agents, antibody-drug conjugates (ADCs) and bispecific T-cell engagers (BiTE) are being developed. These drugs target tumor-associated surface protein. Whether prior treatment affect the transition of protein expression has not been fully investigated especially in the era of ICIs. The purpose of this study is to evaluate changes in protein expression in SCLC tissues before and after treatment. Methods: We included patients diagnosed with SCLC by surgery or biopsy and underwent re-biopsy after treatment (non-transformed group) at the National Cancer Center Hospital between 2014 and 2023. Patients who were initially diagnosed with non-small cell lung cancer and underwent transformation to SCLC (transformed group) were also included. Tissues were obtained by surgery, bronchoscopy, or CT-guided biopsy with an interval of at least 100 days. We investigated clinicopathological features in paired specimens focusing on DLL3, ASCL1, NEUROD1, POU2F3, and YAP1, which have been reported to be expressed in SCLC, as well as tumor-associated surface proteins potentially related to novel drug development. Results: Fourteen non-transformed group cases and 9 transformed group cases were included. Of these, pathology specimens were evaluable in a total of 15 cases: 9 for the non-transformed group and 6 for the transformed group. The median age was 68 years, 11 (73%) were male, 11 (73%) were smokers, 8 (53%) were in clinical stages I-IIIA, 1 (7%) in stages IIIB and 6 (40%) in stage IV. Among the transformed group, 4 of them were treated by Osimertinib before transformation. Progression free survival from first-line therapy was 298 days (255-446) vs. 314 days (245-NA) and overall survival was 1239 days (567-NA) vs. NA days (517-NA), respectively for non-transformed group and transformed group. For both these group of cases, we have evaluated several protein expressions as described above. The transition of these proteins within each group is presented in the conference. Conclusions: In this study, we focused not only on proteins already reported to be expressed in SCLC, but also on proteins that are potential new therapeutic targets and evaluated changes in protein expression. [Table: see text]

Enhanced Declustering Enables Native Top-Down Analysis of Membrane Protein Complexes using Ion-Mobility Time-Aligned Fragmentation.

Native mass spectrometry (MS) is proving to be a disruptive technique for studying the interactions of proteins, necessary for understanding the functional roles of these biomolecules. Recent research is expanding the application of native MS towards membrane proteins directly from isolated membrane preparations or from purified detergent micelles. The former results in complex spectra comprising several heterogeneous protein complexes; the latter enables therapeutic protein targets to be screened against multiplexed preparations of compound libraries. In both cases, the resulting spectra are increasingly complex to assign/interpret, and the key to these new directions of native MS research is the ability to perform native top-down analysis, which allows unambiguous peak assignment. To achieve this, detergent removal is necessary prior to MS analyzers, which allow selection of specific m/z values, representing the parent ion for downstream activation. Here, we describe a novel, enhanced declustering (ED) device installed into the first pumping region of a cyclic IMS-enabled mass spectrometry platform. The device enables declustering of ions prior to the quadrupole by imparting collisional activation through an oscillating electric field applied between two parallel plates. The positioning of the device enables liberation of membrane protein ions from detergent micelles. Quadrupole selection can now be utilized to isolate protein-ligand complexes, and downstream collision cells enable the dissociation and identification of binding partners. We demonstrate that ion mobility (IM) significantly aids in the assignment of top-down spectra, aligning fragments to their corresponding parent ions by means of IM drift time. Using this approach, we were able to confidently assign and identify a novel hit compound against PfMATE, obtained from multiplexed ligand libraries.

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen’s genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Proteome-wide Mendelian randomization identifies therapeutic targets for ankylosing spondylitis.

Ankylosing Spondylitis (AS) is a chronic inflammatory disorder which can lead to considerable pain and disability. Mendelian randomization (MR) has been extensively applied for repurposing licensed drugs and uncovering new therapeutic targets. Our objective is to pinpoint innovative therapeutic protein targets for AS and assess the potential adverse effects of druggable proteins. We conducted a comprehensive proteome-wide MR study to assess the causal relationships between plasma proteins and the risk of AS. The plasma proteins were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) database, encompassing GWAS data for 2,940 plasma proteins. Additionally, GWAS data for AS were extracted from the R9 version of the Finnish database, including 2,860 patients and 270,964 controls. The colocalization analysis was executed to identify shared causal variants between plasma proteins and AS. Finally, we examined the potential adverse effects of druggable proteins for AS therapy by conducting a phenome-wide association study (PheWAS) utilizing the extensive Finnish database in version R9, encompassing 2,272 phenotypes categorized into 46 groups. The findings revealed a positive genetic association between the predicted plasma levels of six proteins and an elevated risk of AS, while two proteins exhibited an inverse association with AS risk (P fdr < 0.05). Among these eight plasma proteins, colocalization analysis identified AIF1, TNF, FKBPL, AGER, ALDH5A1, and ACOT13 as shared variation with AS(PPH3+PPH4>0.8), suggesting that they represent potential direct targets for AS intervention. Further phenotype-wide association studies have shown some potential side effects of these six targets (P fdr < 0.05). Our investigation examined the causal connections between six plasma proteins and AS, providing a comprehensive understanding of potential therapeutic targets.

Exploring promising natural compounds for breast cancer treatment: in silico molecular docking targeting WDR5-MYC protein interaction

Cancer is an aberrant differentiation of normal cells, characterized by uncontrolled growth and the potential to acquire invasive and aggressive properties that ultimately lead to metastasis. In the realm of scientific exploration, a multitude of pathways has been investigated and targeted by researchers, among which one specific pathway is recognized as WDR5-MYC. Continuous investigations and research show that WDR5-MYC is a therapeutic target protein. Hence, the discovery of naturally occurring compounds with anticancer properties has been suggested as a rapid and efficient alternative for the development of anticancerous therapeutics. A virtual screening approach was used to identify the most potent compounds from the NP-lib database at the MTiOpenScreen webserver against WDR5-MYC. This process yielded a total of 304 identified compounds. Subsequently, after screening, four potent compounds, namely Estrone (ZINC000003869899), Ethyl-1,2-benzanthracene (ZINC000003157052), Strychnine (ZINC000000119434) and 7H-DIBENZO [C, G] CARBAZOLE (ZINC000001562130), along with a cocrystallized 5-[4-(trifluoromethyl) phenyl]-1H-tetrazole inhibitor (QBP) as a reference ligand, were considered for stringent molecular docking. Thus, each compound exhibited significant docking energy between −8.2 and −7.7 kcal/mol and molecular contacts with essential residue Asn225, Lys250, Ser267 and Lys272 in the active pocket of WDR5-MYC against the QBP inhibitor (the native ligand QBP serves as a reference in the comparative analysis of docked complexes). The results support the potent compounds for drug-likeness and strong binding affinity with WDR5-MYC protein. Further, the stability of the selected compounds was predicted by molecular dynamics simulation (100 ns) contributed by intermolecular hydrogen bonds and hydrophobic interactions. This demonstrates the potential of the selected compounds to be used against breast cancer treatment. Communicated by Ramaswamy H. Sarma

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins.

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS.

Advances in machine learning (ML) methodologies, combined with multidisciplinary collaborations across biological and physical sciences, has the potential to propel drug discovery and development. Open Science fosters this collaboration by releasing datasets and methods into the public space; however, further education and widespread acceptance and adoption of Open Science approaches are necessary to tackle the plethora of known disease states. In addition to providing much needed insights into potential therapeutic protein targets, we also aim to demonstrate that small patient datasets have the potential to provide insights that usually require many samples (>5,000). There are many such datasets available and novel advancements in ML can provide valuable insights from these patient datasets. Using a public dataset made available by patient advocacy group AnswerALS and a multidisciplinary Open Science approach with a systems biology augmented ML technology, we aim to validate previously reported drug targets in ALS and provide novel insights about ALS subpopulations and potential drug targets using a unique combination of ML methods and graph theory. We use NetraAI to generate hypotheses about specific patient subpopulations, which were then refined and validated through a combination of ML techniques, systems biology methods, and expert input. We extracted 8 target classes, each comprising of several genes that shed light into ALS pathophysiology and represent new avenues for treatment. These target classes are broadly categorized as inflammation, epigenetic, heat shock, neuromuscular junction, autophagy, apoptosis, axonal transport, and excitotoxicity. These findings are not mutually exclusive, and instead represent a systematic view of ALS pathophysiology. Based on these findings, we suggest that simultaneous targeting of ALS has the potential to mitigate ALS progression, with the plausibility of maintaining and sustaining an improved quality of life (QoL) for ALS patients. Even further, we identified subpopulations based on disease onset. In the spirit of Open Science, this work aims to bridge the knowledge gap in ALS pathophysiology to aid in diagnostic, prognostic, and therapeutic strategies and pave the way for the development of personalized treatments tailored to the individual's needs.

The role of autophagy in RIP1 mediated cell death and intestinal inflammation.

Autophagy, a highly conserved catabolic process that targets various types of cellular cargoes to lysosomal degradation, is one of the most important biological mechanisms critical for cellular homeostasis. Components of these cellular cargoes can range from individual proteins to invading pathogens, and degrading these materials is important for maintaining organismal health and survival. The process of autophagy is carried out by complex molecular mechanisms, and a growing body of evidence indicates that these mechanisms intersect with those involved in the cell death pathways. In this review, we examine several emerging studies elucidating the role of autophagy in RIP1-mediated cell death signaling, with particular emphasis on impaired autophagy caused by ATG16L1 deficiency. We also discuss how autophagy in RIP1-mediated cell death affects intestinal homeostasis in preclinical models, and the implications of the intersection between RIP1 and autophagy for understanding the intestinal pathologies associated with inflammatory bowel disease (IBD). Finally, we highlight the potential benefits of therapeutic targeting of RIP1 and autophagy proteins, while also proposing areas of research that will likely elucidate new links between autophagy and cell death signaling.

In vitro and in silico biopotentials of phytochemical compositions and antistaphylococcal and antipseudomonal activities of volatile compounds of Argania spinosa (L.) seed oil.

Active components in medicinal plants provide unlimited useful and traditional medicines. Antimicrobial activities are found in secondary metabolites in plant extracts such as argan oil. This experimental investigation aims to determine argan oil's volatile compounds and examine their in vitro antimicrobial properties. In silico simulations, molecular docking, pharmacokinetics, and drug-likeness prediction revealed the processes underlying the in vitro biological possessions. Gas chromatography-mass spectrometry (GC/MS) was used to screen argan oil's primary components. In silico molecular docking studies were used to investigate the ability of the selected bioactive constituents of argan oil to act effectively against Pseudomonas aeruginosa and Staphylococcus aureus (S. aureus) isolated from infections. The goal was to study their ability to interact with both bacteria's essential therapeutic target protein. The 21 chemicals in argan oil were identified by GC/MS. Docking results for all compounds with S. aureus and P. aeruginosa protease proteins ranged from -5 to -9.4kcal/mol and -5.7 to -9.7kcal/mol, respectively, compared to reference ligands. Our docking result indicates that the 10-octadecenoic acid, methyl ester was the most significant compound with affinity scores of -9.4 and -9.7kcal/mol for S. aureus and P. aeruginosa proteins, respectively. The minimal bactericidal concentration (MBC) and minimal inhibitory concentration (MIC) of argan oil were 0.7 ± 0.03 and 0.5 ± 0.01 for S. aureus and 0.4 ± 0.01 and 0.3 ± 0.02 for P. aeruginosa, respectively. We confirmed the antimicrobial properties of argan oil that showed significant growth inhibition for S. aureus and P. aeruginosa.

Insight into a new discovery of SARS-CoV-2 inhibitor activated through Chloroquine derivatives

The inhibiting effect of chloroquine compounds (ChCs) on the SARS-CoV-2 virus represents a highly debated form of study owing to the emerging proposals of mechanistic implications for exploring the mode of action of ChCs on the virus. Keeping in view the emerging significance of chloroquine derivatives, the present study was performed to screen one hundred and ninety known chloroquine derivatives for their interaction with several SARS-CoV-2 target proteins by molecular docking and molecular dynamics simulations to obtain an in-depth understanding of the potential hits of these compounds against SARS-CoV-2. A total of 190 molecules from the chloroquine family were screened for the identification of potential new inhibitors of the three therapeutic target proteins of SARS-CoV-2, namely Mpro (master protease), PLpro (papain-like protease) and SGp-RBD (spike glycoprotein receptor binding domain). The ChCs bound to SARS-COV-2 Mpro, PLpro, and SGp-RBD were generated by molecular docking and molecular dynamics simulations. Herein, a comparative analysis of chloroquine family products and a well-known drug against SARS-CoV-2, called Remdesivir, has also been presented. This investigation is intended to study the mechanism of interaction between ChCs and the SARS-CoV-2 virus and explore the unprecedented areas associated with the inhibitory activity of ChCs against this virus.

Molecular Docking of Fisetin as a Multi-target drug in the treatment of Alzheimer’s disease

Alzheimer’s disease is a slow deadly form of dementia occurring in almost 70% of the older generation. Throughout the world, there are approximately 47 million people affected. Countries that are mostly affected by Alzheimer’s disease with the highest are Turkey and Lebanon by 57% and 56% respectively. The lowest rates include India, Cambodia, Georgia, and Singapore. This includes symptoms such as disorientation, mood swings, behavioral issues, etc. ultimately leading to death. The primitive appearance of the alpha-beta plaques and neurofibrillary tangles in the different regions of the brain leads to the cause of AD progression. In this present study, Fisetin which is a plant flavonoid having neurotropic and neuroprotective properties is docked with the drug targets of Alzheimer’s disease. The study was focused on analysing the molecular interaction of Fisetin with potential drug targets of Alzheimer’s disease. The docking was performed using AutoDock 4.2. The minimum binding energy studies explain the efficiency of the ligand binding with the therapeutic target proteins. Proteins play a significant role in Alzheimer’s disease as it is responsible for various functions which also are the major attributes of Alzheimer's disease namely amyloid-β production, tau phosphorylation, synaptic function, neurogenesis, and memory which all are influenced by dysregulation of this enzyme. Four proteins were selected based on the action and function they play in the progression of Alzheimer’s disease namely FYN tyrosine kinase, Beta Secretase (BACE 1), Gamma secretase, and Glycogen synthase kinase 3-beta (GSK3-β). The minimum binding energy scores for the following 3D molecular structures were FYN tyrosine kinase = -8.2 kcal/mol, BACE1= -10.67kcal/mol, Gamma secretase = - 10.03kcal/mol, GSK3 Beta = -10.47kcal/mol; No. of hydrogen bonds: 12, 10, 10 and 21 respectively. From the 4 potential Alzheimer’s drug targets, Glycogen synthase kinase 3-beta (GSK3-β) and Beta Secretase, had the best interaction with Fisetin with the lowest binding energy. Along with this Fisetin was analyzed for its molecular properties, drug-likeness, biological activity, and toxicity using the Way2drug bio tool.

Genomic analysis of fibroblasts from marmosets carrying early‐onset Alzheimer’s disease mutations in PSEN1

AbstractBackgroundAlzheimer’s disease (AD) is the most prevalent form of dementia and remains generally untreatable. The slow, age‐related development of AD and inaccessibility of early‐stage brain tissue has limited our understanding of its origins and progression. Large‐scale genetic studies and molecular analysis of postmortem brain samples have nominated dozens of candidate genes and proteins for therapeutic targeting or diagnostic biomarkers, generating a need for in vivo systems to study the underlying biological dysfunction and perform preclinical testing. Here, we report on genetic, genomics, and proteomic analysis of fibroblast lines derived from a colony of marmosets genetically engineered with rare familial variants in the PSEN1 gene.MethodWe performed whole‐genome sequencing on 14 individuals, including six mutant carriers. We validated the presence of the PSEN1 mutations and assessed variation at multiple other Alzheimer’s disease loci. Fibroblast cultures were obtained from 12 animals and assayed using a Nanostring AD gene expression panel and label‐free proteomics. This allowed us to quantify 800 transcripts and 2165 proteins per sample.ResultWe detected differential gene expression for genes enriched in neuron development and amyloid‐beta regulation, providing strong evidence for the functional relevance of the engineered variants. We quantitatively compared changes in marmoset PSEN1 fibroblasts to similar molecular measures in postmortem brain tissue and induced pluripotent stem cells (iPSCs) from human AD studies. Both gene and protein expression changes in the undifferentiated fibroblasts correlated with changes in iPSCs from human AD carriers reprogrammed into neuronal lineages. We also observed both transcriptomic and proteomic changes in marmoset PSEN1 cells that match those in postmortem AD brains.ConclusionThese findings demonstrate that disease‐relevant pathways and processes are altered in fibroblasts from mutant marmosets, provide a roadmap for more advanced molecular studies of AD in aging marmosets and marmoset‐derived cell models, and outline a strategy to align marmoset models with human disease to facilitate robust translation.

Revisiting New Classes of Chalcones from Antidiabetic Perspectives

Elevated blood sugar levels and a plethora of other, more diverse diseases, including changes to protein, carbohydrate, and lipid metabolism, are the only hallmarks of diabetes mellitus. Recent research has shown that mice lacking PTP1B had better glucose tolerance, less diet-induced obesity, and insulin sensitivity in general. In the therapy of serious diabetic problems, natural chalcones have recently been discovered, which have superior selectivity and do not affect pharmacokinetics. This is in response to the present demand for improved PTP-1B inhibitors. No appropriate formulation has been developed for the inhibitors based on natural products chalcones as they have not been tested clinically for toxicological characteristics. The review article has extensively covered various unknown natural chalcone compounds, such as kuwanon J, kuwanon R, kuwanon V, isoliquiritigenin, xanthoangelol, xanthoangelol D, xanthoangelol E, xanthoangelolF, xanthoangelol K, 4-hydroxyderricin, 5,4’-dihydroxy-6,7- furanbavachalcone, licochalcone A, licochalcone B, licochalcone C, licochalcone D, licochalcone E, echinatin, laxichalcone, broussochalcone, macdentichalcone, (2E)1, 1-(5,7-dihydroxy-2,2-dimethyl-2H-benzopyran-8-yl)}3-phenyl-2-propen-1-one, often known as 2E(abyssinone-VI-4-O-methyl ether, 1-(5,7-dihydroxy-2,2,6-trimethyl-2H-benzopyran-8-yl)-3-(4-methoxyphenyl)- 2-propen-1-one) show great promise as a diabetic medication because it can inhibit insulin degradation by targeting the therapeutic target protein tyrosine phosphatase 1B (PTP-1B). These chalcone-based PTP-1B inhibitors derived from natural products are not currently used in clinical trials and have not attracted much interest from contemporary medicine due to a lack of clinical investigation into their toxicological profiles necessary to create an appropriate formulation. These chalcone-based PTP-1B inhibitors may soon unlock new opportunities in diabetotherapeutics.

Network Pharmacology Analysis of Cananga odorata as a Treatment for Anxiety Disorders

Anxiety disorder is a psychological disorder associated with the existence of mental disorders and experiencing constant anxiety. In C. odorata, part of the flower has the potential as a sedative for the nervous system and for dealing with anxiety. The study aims to analyze the potential compound content in Cananga odorata for treating anxiety disorders with In silico-based pharmacological network analysis. CO compound data from the KNApSAck database, Absorption, Distribution, Metabolism, and Excretion (ADME) screening using SwissADME, predicted target proteins using Swiss Target Prediction, GeneCards, Venny, String DB pharmacological network analysis, Visualization with Cytoscape version 3.10.0, and Way2drug. The results of the pharmacological tissue analysis of the compound content in C. odorata obtained 45 compounds, and 18 known active components meet the criteria of Absorption, Distribution, Metabolism, and Excretion (ADME) that correspond to the drug compounder (Drug Likeness/DL). Based on the pathway that correlates with anxiety disorder therapy are the neurotransmitter systems like serotonin receptors and dopamine receptors. The known therapeutic target proteins are HTR1A, HTR2A, SLC6A4, NR3C1, MAOA, DRD4, HSP90AA1, JUN, ten active compounds associated with C. odorata namely Anonaine, (+)-Reticuline, linalool, (-)-Coreximine, Micheline A, (-)-Ushinsunine beta-N-oxide, 4-Terpineol, alpha-Terpeneol, Sampangine, Anaxagoreine. Based on the results of research, C. odorata is potentially a treatment for anxiety disorder.

The Therapeutic Role of Olea europaea in Alcohol Dependence Base in Network Pharmacology Analysis

Alcohol dependence is a state of alcohol becoming a vital part of the life of a person who consumes it; when discontinued, it can lead to a wide range of physical and mental health disorders as well as a decrease in life productivity in people with alcohol dependence. Olea Europaea (OE) is a plant capable of treating alcohol dependence. The method used in silico-based pharmacological grid analysis to determine the ability of the OE compound to treat alcohol dependence. EO compound data is obtained from the KnapSack database, absorption, distribution, metabolism, and excretion (ADME) screening using SwissADME, target protein prediction using SwissTargetPrediction, Gene cards, venny, pharmacological grid analysis with String-DB, visualization with Cytoscape 3.10.0. Results are obtained from 63 OE compounds, and 17 have ADME criteria matching the drug compounder (Drug Likeness/DL). The pathways that correlate with therapy are dopamine receptors, dopamine transporter, serotonin receptor, gamma-aminobutyric acid receptor, and toll-like receptors for known therapeutic target proteins: OPRM1, DRD2, ALDH2, ADH1B, ADH1A, ADH1C, ADH4, ADH7, SLC6A3, CNR1, POMC, ARRB2, and NCS1. Compounds associated with alcohol dependency therapy include Hexanal, Nonadienal, Octanal, 3-Hexenal, 3-Methyl-butanal, Methyl nominate, Cinchonidine, cinchonine, (9S)-10,11-Dihydrocinchonan-9-ol, Oleuropeic acid, Butyl acetate, cis-3-hexenyl acetate, and (S)-2,3-Epoxysqualene. Based on the findings, OE is a potential drug candidate for alcohol dependence.

Melaleuca leucadendra Pharmacological Network for Identifying Potential Target of Alcohol Dependence

Melaleuca leucadendra (ML) contains a compound that is potentially a candidate for alcohol dependence. Alcohol dependence is defined by desire, tolerance, anxiety with alcohol, and continuing to drink even though the consequences are dangerous. The study aims to analyze the potential of the ML compound content for alcohol dependence therapy within silico-based pharmacological chain analysis. ML compound data is obtained from the Knapsack database, screening of absorption, distribution, metabolism, and excretion (ADME) of the compounds ML with SwissADME, prediction of the protein of the target compounder ML with the Swiss TargetpPrediction, Gene cards, venny, analysis of the pharmacological network with String-DB and its visualization with Cytoscape version 3.10.0. The pathways correlated with therapy are dopamine receptors, dopamine carriers, serotonin, gamma-aminobutyric acid receptors, and toll-like receptors for known therapeutic target proteins: OPRM1, DRD2, ALDH2, ADH1B, ADH1A, ADH1C, ADH4, SLC6A3, CNR1, POMC, ARRB2, and NCS1. Alcohol-dependent therapies include alpha-Campholenal, Benzaldehyde, trans-Pinocarveol, Borneol, linalool, alfa-Terpineol, (-)-alpha-Bisabolol oxide B, alphaterpine acetate, and Caryophylla-4(148),15-dien-5alphaol.

Pharmacophore-Based Screening, Molecular Docking, and Dynamic Simulation of Fungal Metabolites as Inhibitors of Multi-Targets in Neurodegenerative Disorders.

Neurodegenerative disorders, such as Alzheimer's disease (AD), negatively affect the economic and psychological system. For AD, there is still a lack of disease-altering treatments and promising cures due to its complex pathophysiology. In this study, we computationally screened the natural database of fungal metabolites against three known therapeutic target proteins of AD. Initially, a pharmacophore-based, drug-likeness category was employed for screening, and it filtered the 14 (A-N) best hits out of 17,544 fungal metabolites. The 14 best hits were docked individually against GSK-3β, the NMDA receptor, and BACE-1 to investigate the potential of finding a multitarget inhibitor. We found that compounds B, F, and L were immuno-toxic, whereas E, H, I, and J had a higher LD50 dose (5000 mg/kg). Among the examined metabolites, the Bisacremine-C (compound I) was found to be the most active molecule against GSK-3β (ΔG: -8.7 ± 0.2 Kcal/mol, Ki: 2.4 × 106 M-1), NMDA (ΔG: -9.5 ± 0.1 Kcal/mol, Ki: 9.2 × 106 M-1), and BACE-1 (ΔG: -9.1 ± 0.2 Kcal/mol, Ki: 4.7 × 106 M-1). It showed a 25-fold higher affinity with GSK-3β, 6.3-fold higher affinity with NMDA, and 9.04-fold higher affinity with BACE-1 than their native ligands, respectively. Molecular dynamic simulation parameters, such as RMSD, RMSF, Rg, and SASA, all confirmed that the overall structures of the targeted enzymes did not change significantly after binding with Bisacremine-C, and the ligand remained inside the binding cavity in a stable conformation for most of the simulation time. The most significant hydrophobic contacts for the GSK-3β-Bisacremine-C complex are with ILE62, VAL70, ALA83, and LEU188, whereas GLN185 is significant for H-bonds. In terms of hydrophobic contacts, TYR184 and PHE246 are the most important, while SER180 is vital for H-bonds in NMDA-Bisacremine-C. THR232 is the most crucial for H-bonds in BACE-1-Bisacremine-C and ILE110-produced hydrophobic contacts. This study laid a foundation for further experimental validation and clinical trials regarding the biopotency of Bisacremine-C.