Exploring novel MYH7 gene variants using in silico analyses in Korean patients with cardiomyopathy.

BACKGROUND: Pathogenic variants of MYH7, which encodes the beta-myosin heavy chain protein, are major causes of dilated and hypertrophic cardiomyopathy. METHODS: In this study, we used whole-genome sequencing data to identify MYH7 variants in 397 patients with various cardiomyopathy subtypes who were participating in the National Project of Bio Big Data pilot study in Korea. We also performed in silico analyses to predict the pathogenicity of the novel variants, comparing them to known pathogenic missense variants. RESULTS: We identified 27 MYH7 variants in 41 unrelated patients with cardiomyopathy, consisting of 20 previously known pathogenic/likely pathogenic variants, 2 variants of uncertain significance, and 5 novel variants. Notably, the pathogenic variants predominantly clustered within the myosin motor domain of MYH7. We confirmed that the novel identified variants could be pathogenic, as indicated by high prediction scores in the in silico analyses, including SIFT, Mutation Assessor, PROVEAN, PolyPhen-2, CADD, REVEL, MetaLR, MetaRNN, and MetaSVM. Furthermore, we assessed their damaging effects on protein dynamics and stability using DynaMut2 and Missense3D tools. CONCLUSIONS: Overall, our study identified the distribution of MYH7 variants among patients with cardiomyopathy in Korea, offering new insights for improved diagnosis by enriching the data on the pathogenicity of novel variants using in silico tools and evaluating the function and structural stability of the MYH7 protein.

The emulsifying capacity and stability of potato proteins and peptides: A comprehensive review.

The potato has recently attracted more attention as a promising protein source. Potato proteins are commonly extracted from potato fruit juice, a byproduct of starch production. Potato proteins are characterized by superior techno-functional properties, such as water solubility, gel-forming, emulsifying, and foaming properties. However, commercially isolated potato proteins are often denatured, leading to a loss of these functionalities. Extensive research has explored the influence of different conditions and techniques on the emulsifying capacity and stability of potato proteins. However, there has been no comprehensive review of this topic yet. This paper aims to provide an in-depth overview of current research progress on the emulsifying capacity and stability of potato proteins and peptides, discussing research challenges and future perspectives. This paper discusses genetic diversity in potato proteins and various methods for extracting proteins from potatoes, including thermal and acid precipitation, salt precipitation, organic solvent precipitation, carboxymethyl cellulose complexation, chromatography, and membrane technology. It also covers enzymatic hydrolysis for producing potato-derived peptides and methods for identifying potato protein-derived emulsifying peptides. Furthermore, it reviews the influence of factors, such as physicochemical properties, environmental conditions, and food-processing techniques on the emulsifying capacity and stability of potato proteins and their derived peptides. Finally, it highlights chemical modifications, such as acylation, succinylation, phosphorylation, and glycation to enhance emulsifying capacity and stability. This review provides insight into future research directions for utilizing potato proteins as sustainable protein sources and high-value food emulsifiers, thereby contributing to adding value to the potato processing industry.

A Novel Workflow for In Silico Prediction of Bioactive Peptides: An Exploration of Solanum lycopersicum By-Products.

Resource-intensive processes currently hamper the discovery of bioactive peptides (BAPs) from food by-products. To streamline this process, in silico approaches present a promising alternative. This study presents a novel computational workflow to predict peptide release, bioactivity, and bioavailability, significantly accelerating BAP discovery. The computational flowchart has been designed to identify and optimize critical enzymes involved in protein hydrolysis but also incorporates multi-enzyme screening. This feature is crucial for identifying the most effective enzyme combinations that yield the highest abundance of BAPs across different bioactive classes (anticancer, antidiabetic, antihypertensive, anti-inflammatory, and antimicrobial). Our process can be modulated to extract diverse BAP types efficiently from the same source. Here, we show the potentiality of our method for the identification of diverse types of BAPs from by-products generated from Solanum lycopersicum, the widely cultivated tomato plant, whose industrial processing generates a huge amount of waste, especially tomato peel. In particular, we optimized tomato by-products for bioactive peptide production by selecting cultivars like Line27859 and integrating large-scale gene expression. By integrating these advanced methods, we can maximize the value of by-products, contributing to a more circular and eco-friendly production process while advancing the development of valuable bioactive compounds.

In silico and biological analyses of missense variants of the human biliary efflux transporter ABCC2: effects of novel rare missense variants.

BACKGROUND AND PURPOSE: The ATP-dependent biliary efflux transporter ABCC2, also known as multidrug resistance protein 2 (MRP2), is essential for the cellular disposition and detoxification of various xenobiotics including drugs as well as endogenous metabolites. Common functionally relevant ABCC2 genetic variants significantly alter drug responses and contribute to side effects. The aim of this study was to determine functional consequences of rare variants identified in subjects with European ancestry using in silico tools and in vitro analyses. EXPERIMENTAL APPROACH: Targeted next-generation sequencing of the ABCC2 gene was used to identify novel variants in European subjects (n = 143). Twenty-six in silico tools were used to predict functional consequences. For biological validation, transport assays were carried out with membrane vesicles prepared from cell lines overexpressing the newly identified ABCC2 variants and estradiol ß-glucuronide and carboxydichlorofluorescein as the substrates. KEY RESULTS: Three novel rare ABCC2 missense variants were identified (W227R, K402T, V489F). Twenty-five in silico tools predicted W227R as damaging and one as potentially damaging. Prediction of functional consequences was not possible for K402T and V489F and for the common linked variants V1188E/C1515Y. Characterisation in vitro showed increased function of W227R, V489F and V1188E/C1515Y for both substrates, whereas K402T function was only increased for carboxydichlorofluorescein. CONCLUSION AND IMPLICATIONS: In silico tools were unable to accurately predict the substrate-dependent increase in function of ABCC2 missense variants. In vitro biological studies are required to accurately determine functional activity to avoid misleading consequences for drug therapy.

In Silico Deciphering of the Potential Impact of Variants of Uncertain Significance in Hereditary Colorectal Cancer Syndromes.

Colorectal cancer (CRC) ranks third in terms of cancer incidence worldwide and is responsible for 8% of all deaths globally. Approximately 10% of CRC cases are caused by inherited pathogenic mutations in driver genes involved in pathways that are crucial for CRC tumorigenesis and progression. These hereditary mutations significantly increase the risk of initial benign polyps or adenomas developing into cancer. In recent years, the rapid and accurate sequencing of CRC-specific multigene panels by next-generation sequencing (NGS) technologies has enabled the identification of several recurrent pathogenic variants with established functional consequences. In parallel, rare genetic variants that are not characterized and are, therefore, called variants of uncertain significance (VUSs) have also been detected. The classification of VUSs is a challenging task because each amino acid has specific biochemical properties and uniquely contributes to the structural stability and functional activity of proteins. In this scenario, the ability to computationally predict the effect of a VUS is crucial. In particular, in silico prediction methods can provide useful insights to assess the potential impact of a VUS and support additional clinical evaluation. This approach can further benefit from recent advances in artificial intelligence-based technologies. In this review, we describe the main in silico prediction tools that can be used to evaluate the structural and functional impact of VUSs and provide examples of their application in the analysis of gene variants involved in hereditary CRC syndromes.

The investigation of the toxicity of organophosphorus flame retardants (OPFRs) by using in silico toxicity prediction platform ProTox- 3.0.

From the past to the present, many chemicals have been used for the purpose of flame retardant. Due to PBDEs' (Polybrominated diphenyl ether) lipophilic and accumulative properties, some of them are banned from the market. As an alternative to these chemicals, OPFRs (organophosphorus flame retardants) have started to be used as flame retardants. In this article, acute toxicity profiles, mutagenicity, carcinogenicity, blood-brain barrier permeability, ecotoxicity and nutritional toxicity as also AHR, ER affinity and MMP, aromatase affinity, CYP2C9, CYP3A4 interaction of the of 16 different compounds of the OPFRs were investigated using a computational toxicology method; ProTox- 3.0. According to our results, eight compounds were found to be active in terms of carcinogenic effect, whereas two compounds were found to be active for mutagenicity. On the other hand, all compounds were found to be active in terms of blood-barrier permeability. Fourteen compounds and four compounds are found to have ecotoxic and nutritional toxic potency, respectively. Eight compounds were determined as active to AhR, and four chemicals were found to be active in Estrogen Receptor alpha. Eight chemicals were found to be active in terms of mitochondrial membrane potency. Lastly, three chemicals were found to be active in aromatase enzymes. In terms of CYP interaction potencies, eight compounds were found to be active in both CYP2C9 and CYP3A4. This research provided novel insights into the potential toxic effects of OPFRs. However, further studies are needed to evaluate their toxicity. Moreover, these findings lay the groundwork for in vitro and in vivo toxicity research.

In vitro toxicity of latex, its terpenoidal fractions and isolated phorbol esters from Euphorbia umbellata (Pax) Bruyns on monocytic and melanoma cells.

In Brazil, latex from Euphorbia umbellata (African milk tree) has been increasingly used in folk medicine to treat several types of cancer, including melanoma. The effect of lyophilized latex (LL), its hydroethanolic extract (E80), triterpene (F-TRI)- and diterpene (F-DIT)-enriched fractions, along with six isolated phorbol esters from LL and phorbol 12-myristate 13-acetate (PMA) on J774A.1, THP-1, SK-MEL-28, and B16-F10 cell line viability were evaluated by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) method. The compounds were identified by 2D-NMR and HRESIMS. The effect of the LL, extract and fractions on cell viability was also assessed through a resazurin reduction assay. At 100 µg/ml, LL, and its fractions moderately inhibited J774A.1 (37.5-59.5%) and THP-1 (12.6-43.6%) metabolism. LL (IC50 70 µg/ml) and F-TRI (IC50 68 µg/ml) were barely more effective against B16-F10 cells, and only F-TRI exerted an inhibitory effect on SK-MEL-28 cells (IC50 66-75 µg/ml). The samples did not effectively inhibit THP-1 growth (IC50 69-87 µg/ml, assessed by MTT). B16-F10 was susceptible to PMA (IC50 53 µM) and two 12-phenylacetate esters (IC50 56-60 µM), while SK-MEL-28 growth was inhibited (IC50 58 µM) by one of these kinds of esters with an additional 4ß-deoxy structure. Synagrantol A (IC50 39 µM) was as effective as PMA (IC50 47 µM) in inhibiting J774A.1 growth in a dose-dependent manner. Furthermore, an in silico study with target receptors indicated a high interaction of the compounds with the PKC proteins. These results provide useful knowledge on the effect of tigliane-type diterpenes on tumor cell from the perspective of medicinal chemistry.

Identification, trace level quantification, and in silico assessment of potential genotoxic impurity in Famotidine.

Potential genotoxic impurities in medications are an increasing concern in the pharmaceutical industry and regulatory bodies because of the risk of human carcinogenesis. To prevent the emergence of these impurities, it is crucial to carefully examine not only the final product but also the intermediates and key starting material (KSM) used in drug synthesis. During the related substances analysis of KSM of Famotidine, an unknown impurity in the range of 0.5-1.0% was found prompting the need for isolation and characterization due to the possibility of its to infiltrate into the final product. In this study, the impurity was isolated and characterized as 5-(2-chloroethyl)-3,3-dimethyl-3,4-dihydro-2H-1,2,4,6-thiatriazine 1,1-dioxide using multiple instrumental analysis, uncovering a structural alert that raises concern. Considering the potential impact of impurity on human health, an in silico genotoxicity assessment was established using Derek and Sarah tool in accordance with ICH M7 guideline. Furthermore, molecular docking and molecular dynamics simulation were performed to evaluate the specific interaction of the impurity with DNA. The findings reveal consistent interaction of the impurity with the dG-rich region of the DNA duplex and binding at the minor groove. Both in silico prediction and molecular dynamic study confirmed the genotoxic character of the impurity. The newly discovered impurity in famotidine has not been reported previously, and there is currently no analytical method available for its identification and control. A highly sensitive HPLC-UV method was developed and validated in accordance with ICH requirements, enabling quantification of the impurity at trace level in famotidine ensuring its safe release.

Impact of predicted HLA class I immunopeptidome on viral reservoir in a cohort of people living with HIV in Italy.

The class I HLA genotype has been widely recognized as a factor influencing HIV disease progression in treatment-naïve subjects. However, little is known regarding its role in HIV disease course and how it influences the size of the viral reservoir once anti-retroviral therapy (ART) is started. Here, leveraging on cutting-edge bioinformatic tools, we explored the relationship between HLA class I and the HIV reservoir in a cohort of 90 people living with HIV (PLWH) undergoing ART and who achieved viral suppression. Analysis of HLA allele distribution among patients with high and low HIV reservoir allowed us to document a predominant role of HLA-B and -C genes in regulating the size of HIV reservoir. We then focused on the analysis of HIV antigen (Ag) repertoire, by investigating immunogenetic parameters such as the degree of homozygosity, HLA evolutionary distance and Ag load. In particular, we used two different bioinformatic algorithms, NetMHCpan and MixMHCpred, to predict HLA presentation of immunogenic HIV-derived peptides and identified HLA-B*57:01 and HLA-B*58:01 among the highest ranking HLAs in terms of total load, suggesting that their previously reported protective role against HIV disease progression might be linked to a more effective viral recognition and presentation to Cytotoxic T lymphocytes (CTLs). Further, we speculated that some peptide-HLA complexes, including those produced by the interaction between HLA-B*27 and the HIV Gag protein, might be particularly relevant for the efficient regulation of HIV replication and containment of the HIV reservoir. Last, we provide evidence of a possible synergistic effect between the CCR5 ∆32 mutation and Ag load in controlling HIV reservoir.

BC CLC-Pred: a freely available web-application for quantitative and qualitative predictions of substance cytotoxicity in relation to human breast cancer cell lines.

In silico prediction of cell line cytotoxicity considerably decreases time and financial costs during drug development of new antineoplastic agents. (Q)SAR models for the prediction of drug-like compound cytotoxicity in relation to nine breast cancer cell lines (T47D, ZR-75-1, MX1, Hs-578T, MCF7-DOX, MCF7, Bcap37, MCF7R, BT-20) were created by GUSAR software based on the data from ChEMBL database (v. 30). The separate datasets related with IC50 and IG50 values were used for the creation of (Q)SAR models for each cell line. Based on leave-one-out and 5F CV procedures, 24 reasonable (Q)SAR models were selected for the creation of a freely available web-application (BC CLC-Pred: https://www.way2drug.com/bc/) to predict substance cytotoxicity in relation to human breast cancer cell lines. The mean accuracies of prediction r2, RMSE, Balance Accuracy for the selected (Q)SAR models calculated by 5F CV were 0.599, 0.679 and 0.875, respectively. As a result, BC CLC-Pred provides simultaneous quantitative and qualitative predictions of IC50 and IG50 values for most of the nine breast cancer cell lines, which may be helpful in selecting promising compounds and optimizing lead compounds during the development of new antineoplastic agents against breast cancer.

Identification and interpretation of TET2 noncanonical splicing site intronic variants in myeloid neoplasm patients.

Background: DNA hypermethylation and instability due to inactivation mutations in Ten-eleven translocation 2 (TET2) is a key biomarker of hematological malignancies. This study aims at characterizing two intronic noncanonical splice-site variants, c.3954+5_3954+8delGTTT and c.3954+5G>A. Methods: We used in silico prediction tools, reverse transcription (RT)-PCR, and Sanger sequencing on blood/bone marrow-derived RNA specimens to determine the aberrant splicing. Results: In silico prediction of both variants exhibited reduced splicing strength at the TET2 intron 7 splicing donor site. RT-PCR and Sanger sequencing identified a 62-bp deletion at the exon 7, producing a frameshift mutation, p.Cys1298*. Conclusion: This study provides functional evidence for two intronic TET2 variants that cause alternative splicing and frameshift mutation.

Applications of artificial intelligence in clinical laboratory genomics.

The transition from analog to digital technologies in clinical laboratory genomics is ushering in an era of "big data" in ways that will exceed human capacity to rapidly and reproducibly analyze those data using conventional approaches. Accurately evaluating complex molecular data to facilitate timely diagnosis and management of genomic disorders will require supportive artificial intelligence methods. These are already being introduced into clinical laboratory genomics to identify variants in DNA sequencing data, predict the effects of DNA variants on protein structure and function to inform clinical interpretation of pathogenicity, link phenotype ontologies to genetic variants identified through exome or genome sequencing to help clinicians reach diagnostic answers faster, correlate genomic data with tumor staging and treatment approaches, utilize natural language processing to identify critical published medical literature during analysis of genomic data, and use interactive chatbots to identify individuals who qualify for genetic testing or to provide pre-test and post-test education. With careful and ethical development and validation of artificial intelligence for clinical laboratory genomics, these advances are expected to significantly enhance the abilities of geneticists to translate complex data into clearly synthesized information for clinicians to use in managing the care of their patients at scale.

Clinical Trial on the Safety and Tolerability of Personalized Cancer Vaccines Using Human Platelet Lysate-Induced Antigen-Presenting Cells.

Research and development of personalized cancer vaccines as precision medicine are ongoing. We predicted human leukocyte antigen (HLA)-compatible cancer antigen candidate peptides based on patient-specific cancer genomic profiles and performed a Phase I clinical trial for the safety and tolerability of cancer vaccines with human platelet lysate-induced antigen-presenting cells (HPL-APCs) from peripheral monocytes. Among the five enrolled patients, two patients completed six doses per course (2-3 × 107 cells per dose), and an interim analysis was performed based on the immune response. An immune response was detected by enzyme-linked immunosorbent spot (ELISpot) assays to HLA-A*33:03-matched KRASWT, HLA-DRB1*09:01-compliant KRASWT or G12D, or HLA-A*31:01-matched SMAD4WT, and HLA-DRB1*04:01-matched SMAD4G365D peptides in two completed cases, respectively. Moreover, SMAD4WT-specific CD8+ effector memory T cells were amplified. However, an attenuation of the acquired immune response was observed 6 months after one course of cancer vaccination as the disease progressed. This study confirmed the safety and tolerability of HPL-APCs in advanced and recurrent cancers refractory to standard therapy and is the first clinical report to demonstrate the immunoinducibility of personalized cancer vaccines using HPL-APCs. Phase II clinical trials to determine immune responses with optimized adjuvant drugs and continued administration are expected to demonstrate efficacy.

Combining virtual screening with cis-/trans-cleavage enzymatic assays effectively reveals broad-spectrum inhibitors that target the main proteases of SARS-CoV-2 and MERS-CoV.

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication, which suggests that the Mpro is a critical target in the development of small molecules to treat COVID-19. This study used an in-silico prediction approach to investigate the complex structure of SARS-CoV-2 Mpro in compounds from the United States National Cancer Institute (NCI) database, then validate potential inhibitory compounds against the SARS-CoV-2 Mpro in cis- and trans-cleavage proteolytic assays. Virtual screening of ∼280,000 compounds from the NCI database identified 10 compounds with highest site-moiety map scores. Compound NSC89640 (coded C1) showed marked inhibitory activity against the SARS-CoV-2 Mpro in cis-/trans-cleavage assays. C1 strongly inhibited SARS-CoV-2 Mpro enzymatic activity, with a half maximal inhibitory concentration (IC50) of 2.69 µM and a selectivity index (SI) of >74.35. The C1 structure served as a template to identify structural analogs based on AtomPair fingerprints to refine and verify structure-function associations. Mpro-mediated cis-/trans-cleavage assays conducted with the structural analogs revealed that compound NSC89641 (coded D2) exhibited the highest inhibitory potency against SARS-CoV-2 Mpro enzymatic activity, with an IC50 of 3.05 µM and a SI of >65.57. Compounds C1 and D2 also displayed inhibitory activity against MERS-CoV-2 with an IC50 of <3.5 µM. Thus, C1 shows potential as an effective Mpro inhibitor of SARS-CoV-2 and MERS-CoV. Our rigorous study framework efficiently identified lead compounds targeting the SARS-CoV-2 Mpro and MERS-CoV Mpro.

Unveiling the treatment-driven secondary risks of pharmaceuticals: New lessons from calcium channel blocker transformation by multiple oxidants.

The worldwide detection of numerous pharmaceuticals and their transformation products (TPs) in different environmental matrices has gained considerable concern about their potential ecological hazards. Increasing evidence suggested that calcium channel blockers (CCBs) are ubiquitous pharmaceutical pollutants in natural waters. However, their TPs, reaction pathways, and secondary risks have been limitedly known during oxidative water treatment. This study systematically assessed the TP formation and transformation mechanisms of two typical CCBs (i.e., amlodipine, AML; verapamil, VER) oxidized by ferrate(VI), permanganate, and ozone, as well as the in silico prediction on the TPs' properties. The high-resolution mass spectrometer analysis suggested a total of 16 TPs of AML and 8 TPs of VER identified for these reaction systems. Transformation of AML mainly proceeded through hydroxylation of the aromatic ring, ether bond cleavage, NH2 substitution by a hydroxyl group, and H-abstraction, while VER was oxidized via hydroxylation/opening of the aromatic ring and cleavage of the CN bond. Notably, certain TPs of both CCBs were estimated with low biodegradation, multi-endpoint toxicity, and high persistence and bioaccumulation, suggesting their severe risks to aquatic ecosystems. This study has implications for understanding the environmental behaviors, fate, and secondary risks of the globally prevalent and concerned CCBs under oxidative water treatment scenarios.

Functional attributes of bioactive peptides of bovine milk origin and application of in silico approaches for peptide prediction and functional annotations.

Bovine milk peptides are the protein fragments with diverse bioactive properties having antioxidant, anticarcinogenic, other therapeutic and nutraceutical potentials. These peptides are formed in milk by enzymatic hydrolysis, gastrointestinal digestion and fermentation processes. They have significant health impact with high potency and low toxicity making them a suitable natural alternative for preventing and managing diseases. Antibiotic resistance has increased the quest for better peptide candidates with antimicrobial effects. This article presents a comprehensive review on well documented antimicrobial, immunological, opioid, and anti-hypertensive activities of bovine milk peptides. It also covers the usage of computational biology tools and databases for prediction and analysis of the food-derived bioactive peptides. In silico analysis of amino acid sequences of Bos taurus milk proteins have been predicted to generate peptides with dipeptidyl peptidase IV inhibitory and ACE inhibitory properties, making them favorable candidates for developing blood sugar lowering drugs and anti-hypertensives. In addition to the prediction of new bioactive peptides, application of bioinformatics tools to predict novel functions of already known peptides is also discussed. Overall, this review focuses on the reported as well as predicted biologically active peptide of casein and whey proteins of bovine milk that can be utilized to develop therapeutic agents.

A new molecular subclassification and in silico predictions for diagnosis and prognosis of papillary thyroid cancer by alternative splicing profile.

Introduction: Papillary thyroid cancer (PTC) is the most common endocrine malignancy. However, different PTC variants reveal high heterogeneity at histological, cytological, molecular and clinicopathological levels, which complicates the precise diagnosis and management of PTC. Alternative splicing (AS) has been reported to be potential cancer biomarkers and therapeutic targets. Method: Here, we aim to find a more sophisticated molecular subclassification and characterization for PTC by integrating AS profiling. Based on six differentially expressed alternative splicing (DEAS) events, a new molecular subclassification was proposed to reclassify PTC into three new groups named as Cluster0, Cluster1 and Cluster2 respectively. Results: An in silico prediction was performed for accurate recognition of new groups with the average accuracy of 91.2%. Moreover, series of analyses were implemented to explore the differences of clinicopathology, molecular and immune characteristics across them. It suggests that there are remarkable differences among them, but Cluster2 was characterized by poor prognosis, higher immune heterogeneity and more sensitive to anti-PD1 therapy. The splicing correlation networks proved the complicated regulation relationships between AS events and splicing factors (SFs). An independent prognostic indicator for PTC overall survival (OS) was established. Finally, three compounds (orantinib, tyrphostin-AG-1295 and AG-370) were discovered to be the potential therapeutic agents. Discussion: Overall, the six DEAS events are not only potential biomarkers for precise diagnosis of PTC, but also the probable prognostic predictors. This research would be expected to highlight the effect of AS events on PTC characterization and also provide new insights into refining precise subclassification and improving medical therapy for PTC patients.

Synthesis of N-[1-(2-Acetyl-4,5-dimethoxyphenyl)propan-2-yl]benzamide and Its Copper(II) Complex.

This paper represents a convenient method for the synthesis of N-[1-(2-acetyl-4,5-dimethoxyphenyl)propan-2-yl]benzamide and its Cu(II) complex. In silico analysis predicted spasmolytic activity for the compound. Based on the in silico calculations, the importance of the predicted ketoamide, and our previous experiments, we synthesized the ketoamide via ortho-acylation of N-[1-(3,4-dimethoxyphenyl)propan-2-yl]benzamide with acetic anhydride in polyphosphoric acid. We applied the title ketoamide in reaction with Cu(II) varying the solvents. We found that the reaction leads to the formation of a coordination compound when the ligand dissolved in DMSO reacts with a water solution of CuCl2 in an alkaline environment in a molar ratio M : L : OH- = 1 : 2 : 2. The structures of the new compounds are discussed based on their melting points, IR, 1H, 13C NMR and Raman spectral data.

Molecular Cloning and AlphaFold Modeling of Thyrotropin (ag-TSH) From the Amazonian Fish Pirarucu (Arapaima gigas).

Arapaima gigas, known as Pirarucu in Brazil, is one of the largest freshwater fish in the world. Some individuals could reach 3 m in length and weight up to 200 kg. Due to extinction risks and its economic value, the species has been a focus for preservation and reproduction studies. Thyrotropin (TSH) is a glycoprotein hormone formed by 2 subunits α and ß whose main activity is related to the synthesis of thyroid hormones (THs)-T3 and T4. In this work, we present a combination of bioinformatics tools to identify Arapaima gigas ßTSH (ag-ßTSH), modeling its molecular structure and express the recombinant heterodimer form in mammalian cells. Using the combination of computational biology, based on genome-related information, in silico molecular cloning and modeling led to confirm results of the ag-ßTSH sequence by reverse transcriptase-polymerase chain reaction (RT-PCR) and transient expression in human embryonic kidney (HEK293F) cells. Molecular cloning of ag-ßTSH retrieved 146 amino acids with a signal peptide of 21 amino acid residues and 6 disulfide bonds. The sequence has a similarity to 39 fish species, ranging between 43.1% and 81.6%, whose domains are extremely conserved, such as cystine knot motif and N-glycosylation site. The Arapaima gigas thyrotropin (ag-TSH) model, solved by AlphaFold, was used in molecular dynamics simulations with Scleropages formosus receptor, providing similar values of free energy ΔGbind and ΔGPMF in comparison with Homo sapiens model. The recombinant expression in HEK293F cells reached a yield of 25 mg/L, characterized via chromatographic and physical-chemical techniques. This work shows that other Arapaima gigas proteins could be studied in a similar way, using the combination of these techniques, recovering more information from its genome and improving the reproduction and preservation of this prehistoric fish.