Synthesis and Biological Evaluations of Novel Human Parathyroid Hormone 1 Receptor (hPTHR1) Agonists Bearing Bicyclic Aromatic Moiety.

We have previously shown that the small molecule hPTHR1 agonist PCO371 (1) orally and dose-dependently induces PTH-like calcemic and hypophostemic activity in thyroparathyroidectomized rats. Compound 2a, bearing a bicyclic aromatic ring, was identified as a novel hPTHR1 agonist during hit to lead modification. It showed moderate PTHR1 agonistic activity with an EC20 value of 15 µM, and its metabolic stability in human liver microsome (hLM) as well as its solubility in phosphate buffer (PPb) and Fasted state simulated intestinal fluid (FaSSIF) were found to be poor. As results of the initial derivatization of 2a, we identified the indole derivatives as another scaffold. In this article, we report on the structure-activity relationship (SAR), structure-metabolism relationship (SMR), and structure-solubility relationship (SSR) of bicyclic aromatic derivatives, and the in vivo efficacy of 2j.

[Automation of Damage Detection and Damage Area Measurement of X-ray Protective Clothing Using Deep Learning].

PURPOSE: Damage to shielding sheets on X-ray protective clothing may be a cause of increased radiation exposure. To prevent increased radiation exposure, periodic quality control of shielding sheets is needed. For quality management, a record of the size of damage is required after checking for the existence of damage, and this requires a great deal of effort and time. Additionally, the detection model created from the images of the shielding sheets, limited by the number of samples, is predicted to have a low detection precision. The purpose of this study was to automate damage area detection and area measurement using artificial damage images and a damage detection model created using deep learning. METHOD: By synthesizing the X-ray protective clothing CT localizer image and the image simulating damage, we created an artificial damage image. We then found the detection precision of the damage detection model created by the artificial damage image and YOLOv5s, and error of the automatically measured damage area. RESULT: The accuracy rate of the damage detection model was 0.746, the precision was 0.645, the reproduction rate was 0.741, the F value was 0.690, and 48 mm2 or the detectable area of damage ranged from 2 mm2 to 113 mm2. The mean value of the damage area error was 7.58% for areas not including the hem and 43.39% for areas including the hem. In the areas not including the hem, with a detected damage area of 91%, the damage area error was 0%. Additionally, the process from damage area detection to damage area measurement was completed in 20 seconds. CONCLUSION: By using a damage detection model created with only artificial damage areas, it was possible to automate damage detection and damage area measurement, and this saved time for X-ray protective clothing management.

[Supplementing a Web-based Exposure Estimation System with Deep Learning for Automatic Classification of CT Images to Increase the Efficiency of Effective Dose Estimation].

PURPOSE: Web-based exposure estimation systems are advantageous for estimating exposure doses for computed tomography (CT) scans. However, such systems depend on the imaging conditions of the slices, and a considerable amount of time and effort is needed to select the slices and extract their imaging conditions from the relevant CT volume data. In this study, we used a convolutional neural network (CNN) to automatically classify specific slices from available CT volume data for use by a Web-based exposure estimation system. We also proposed a method to automatically obtain the imaging conditions of these classified slices. The objective of this study was to improve the efficiency of effective dose estimation. METHOD: We automatically classified specific slices from CT volume data using two different CNN architectures: VGG-16 and Xception. We organized the dataset into 5 categories corresponding to the contents of the specific slices. We also tested a 9-category version in which the slices were supplemented with their adjacent slices. We automatically obtained the imaging conditions from the DICOM tags of the specific slices that were classified from the CT volume data by the CNN and then estimated the effective exposure dose provided by the Web-based exposure estimation system. RESULT: Using the 5-category dataset approach, the error in the effective exposure dose was 13% for VGG16 and 6% for Xception. When the 9-category approach was used, the error in the effective exposure dose was 0.8% for VGG16 and 0.6% for Xception. In both the architectures, less than 5 minutes was needed in the classification of the specific slices, followed by the extraction of their imaging conditions; however, VGG16 required the shortest processing time. CONCLUSION: By supplementing a Web-based exposure estimation system with a CNN and adopting our proposed method, we were able to improve the efficiency of effective dose estimation.

[Volume Measurements of Post-transplanted Liver of Pediatric Recipients Using Workstations and Deep Learning].

PURPOSE: The purpose of this study was to propose a method for segmentation and volume measurement of graft liver and spleen of pediatric transplant recipients on digital imaging and communications in medicine (DICOM) -format images using U-Net and three-dimensional (3-D) workstations (3DWS) . METHOD: For segmentation accuracy assessments, Dice coefficients were calculated for the graft liver and spleen. After verifying that the created DICOM-format images could be imported using the existing 3DWS, accuracy rates between the ground truth and segmentation images were calculated via mask processing. RESULT: As per the verification results, Dice coefficients for the test data were as follows: graft liver, 0.758 and spleen, 0.577. All created DICOM-format images were importable using the 3DWS, with accuracy rates of 87.10±4.70% and 80.27±11.29% for the graft liver and spleen, respectively. CONCLUSION: The U-Net could be used for graft liver and spleen segmentations, and volume measurement using 3DWS was simplified by this method.

Lead Optimization and Avoidance of Reactive Metabolite Leading to PCO371, a Potent, Selective, and Orally Available Human Parathyroid Hormone Receptor 1 (hPTHR1) Agonist.

We have previously shown that the oral administration of the small molecule hPTHR1 agonist PCO371 and its lead compound, 1 (CH5447240) results in PTH-like calcemic and hypophostemic activity in thyroparathyroidectomized rats. However, 1 was converted to a reactive metabolite in a human liver microsome assay. In this article, we report on the modification path that led to an enhancement of PTHR1 agonistic activity and reduction in the formation of a reactive metabolite to result in a potent, selective, and orally active PTHR1 agonist 1-(3,5-dimethyl-4-(2-((4-oxo-2-(4-(trifluoromethoxy)phenyl)-1,3,8-triazaspiro[4.5]dec-1-en-8-yl)sulfonyl)ethyl)phenyl)-5,5-dimethylimidazolidine-2,4-dione (PCO371, 16c). This compound is currently being evaluated in a phase 1 clinical study for the treatment of hypoparathyroidism.

Development of a Novel Human Parathyroid Hormone Receptor 1 (hPTHR1) Agonist (CH5447240), a Potent and Orally Available Small Molecule for Treatment of Hypoparathyroidism.

During the course of derivatization of HTS hit 4a, we have identified a novel small-molecule hPTHR1 agonist, 1-(3,5-dimethyl-4-(2-((2-((1 R,4 R)-4-methylcyclohexyl)-4-oxo-1,3,8-triazaspiro[4.5]dec-1-en-8-yl)sulfonyl)ethyl)phenyl)-1-methylurea (CH5447240, 14l). Compound 14l exhibited a potent in vitro hPTHR1 agonist effect with EC20 of 3.0 µM and EC50 of 12 µM and showed excellent physicochemical properties, such as high solubility in fasted state simulated intestinal fluid and good metabolic stability in human liver microsomes. Importantly, 14l showed 55% oral bioavailability and a significantly elevated serum calcium level in hypocalcemic model rats.

Efficient asymmetric synthesis of novel gastrin receptor antagonist AG-041R via highly stereoselective alkylation of oxindole enolates.

An efficient method for asymmetric synthesis of the potent Gastrin/CCK-B receptor antagonist AG-041R was developed. Core oxindole stereochemistry was established by asymmetric alkylation of oxindole enolates with bromoacetic acid esters, using l-menthol as a chiral auxiliary. The key alkylation reaction of the oxindole enolates generated tetrasubstituted chiral intermediates with high diastereoselectivity. The stereoselective alkylation reactions are described in detail.

Structure-based design of P3 moieties in the peptide mimetic factor VIIa inhibitor.

Selective factor VIIa-tissue factor complex (FVIIa/TF) inhibition is seen as a promising target for developing new anticoagulant drugs. Structure-based designs of the P3 moiety in the peptide mimetic factor VIIa inhibitor successfully lead to novel inhibitors with selectivity for FVIIa/TF and extrinsic coagulation the same as or even higher than those of previously reported peptide mimetic factor VIIa inhibitors. X-ray crystal structure analysis reveals that one of the novel inhibitors shows improved selectivity by forming interactions between the inhibitor and FVIIa as expected. Another of the novel inhibitors achieves improved selectivity through an unexpected hydrogen bond with Gln217, with a unique bent conformation in FVIIa/TF accompanied by conformational changes of the inhibitor and the protein.

Structure of human factor VIIa/tissue factor in complex with a peptide-mimetic inhibitor: high selectivity against thrombin by introducing two charged groups in P2 and P4.

The crystal structure of human factor VIIa/soluble tissue factor (FVIIa/sTF) in complex with a highly selective peptide-mimetic FVIIa inhibitor which shows 1670-fold selectivity against thrombin inhibition has been solved at 2.6 A resolution. The inhibitor is bound to FVIIa/sTF at the S1, S2 and S3 sites and at the additional S1 subsite. Two charged groups, the amidino group in P2 and the carboxylate group in P4, form ionic interactions with Asp60 and Lys192 of FVIIa, respectively. Structural comparisons between factor VIIa and thrombin show that thrombin has oppositely charged residues, Lys60F and Glu192, in the S2 site and the S1 subsites, respectively. These data suggest that the utilization of the differences of charge distribution in the S2 site and the S1 subsites between FVIIa and thrombin is critical for achieving high selectivity against thrombin inhibition. These results will provide valuable information for the structure-based drug design of specific inhibitors for FVIIa/TF.

Novel interactions of large P3 moiety and small P4 moiety in the binding of the peptide mimetic factor VIIa inhibitor.

Selective factor VIIa-tissue factor complex (FVIIa/TF) inhibition is seen as a promising target for developing new anticoagulant drugs. A novel peptide mimetic factor VIIa inhibitor, ethylsulfonamide-d-biphenylalanine-Gln-p-aminobenzamidine, shows 100-fold selectivity against thrombin in spite of its large P3 moiety, unlike previously reported FVIIa/TF selective inhibitors. X-ray crystal structure analysis reveals that the large P3 moiety, d-biphenylalanine, and the small P4 moiety, ethylsulfonamide, make novel interactions with the 170-loop and Lys192 of FVIIa/TF, respectively, accompanying ligand-induced conformational changes of the 170-loop, Gln217, and Lys192. Structural comparisons of FVIIa with thrombin and amino acid sequence comparisons among coagulation serine proteases suggest that these interactions play an important role in achieving selective inhibition for FVIIa/TF.

Crystal structure of human factor VIIa/tissue factor in complex with peptide mimetic inhibitor.

The 3D structure of human factor VIIa/soluble tissue factor in complex with a peptide mimetic inhibitor, propylsulfonamide-D-Thr-Met-p-aminobenzamidine, is determined by X-ray crystallography. As compared with the interactions between thrombin and thrombin inhibitors, the interactions at S2 and S3 sites characteristic of factor VIIa and factor VIIa inhibitors are revealed. The S2 site has a small pocket, which is filled by the hydrophobic methionine side chain in P2. The small S3 site fits the small size residue, D-threonine in P3. The structural data and SAR data of the peptide mimetic inhibitor show that these interactions in the S2 and S3 sites play an important role for the improvement of selectivity versus thrombin. The results will provide valuable information for the structure-based drug design of specific inhibitors for FVIIa/TF.