Aim: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. Methods: The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. Results: The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Conclusion: Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.

The photodegradation mechanism of recombinant human interferon-alpha2a (IFNalpha2a) has been investigated using absorption, fluorescence, and circular dichroism (CD) spectroscopies, and fluorescence photobleaching kinetics measurements under various conditions. After photobleaching, the absorption profile of aromatic amino acid residues in IFNalpha2a was almost absent, and an absorption profile showing a monotonic increase toward short wavelengths was observed. According to the CD spectrum analysis, partial unfolding of IFNalpha2a was accompanied by a complete loss of fluorescence. This unfolding was attributed to tryptophan-mediated photoinduced disulfide bond cleavage. Photooxygenation and photoionization of tryptophan (Trp) residues followed by subsequent radical reactions were the main photodegradation pathways of IFNalpha2a. Photobleaching kinetics was faster in acidic solution (pH 2.5) than in neutral solution (pH 7.4). The variation of photobleaching kinetics seemed to be caused by the structural differences in IFNalpha2a according to the solution pH. The relationship between the protein conformation and photobleaching rate could be explained based on the competition between excited state energy transfer and the photoionization process in Trp residues.

Protein modifications of recombinant pharmaceuticals have been observed both in vitro and in vivo. These modifications may result in lower efficacy, as well as bioavailability changes and antigenicity among the protein pharmaceuticals. Therefore, the contents of modification should be monitored for the quality and efficacy of protein pharmaceuticals. The interface of EPO and its receptor was visualized, and potential amino acids interacting on the interface were also listed. Two different types of modifications on the interface were identified in the preparation of rHu-EPO BRP. A UPLC/Q-TOF MS method was used to evaluate the modification at those variants. The modification of the oxidized variant was localized on the Met54 and the deamidated variants were localized on the Asn47 and Asn147. The extent of oxidation at Met54 was 3.0% and those of deamidation at Asn47 and Asn147 were 2.9% and 4.8%, respectively.

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.

No abstract

A variant peak was detected in the analysis of RP-HPLC of rHu-EPO, which has about 7% relative content. Fractions of the main and the variant peaks were pooled separately and further analyzed to identify the molecular structure of the variant peak. Total mass analysis for each peak fraction using ESI-TOF MS shows differences in molecular mass. The fraction of the main peak tends to result in higher molecular masses than the fraction of the variant. The detected masses for the variant are about 600–1000 Da smaller than those for the main peak. Peptide mapping analysis for each peak fraction using Asp-N and Glu-C shows differences in O-glycopeptide profiles at Ser126. The O-glycopeptides were not detected in the fraction of the variant. It is concluded that the variant peak is non-O-glycosylated rHu-EPO and the main peak is fully O-glycosylated rHu-EPO at Ser126.

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the PPARγ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to PPARγ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.

No abstract