How Does Chirality Determine the Selective Inhibition of Histone Deacetylase 6? A Lesson from Trichostatin A Enantiomers Based on Molecular Dynamics

Liu

et al. 2020

Front. Chem.

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Vorinostat (SAHA) with great therapeutic potential has been approved by the FDA for the treatment of cutaneous T-cell lymphoma as the first HDACs inhibitor, but the drawbacks associated with hydroxamic acid group (poor stability, easy metabolism, weak binding ability to class IIa isozymes, and poor selectivity) have been exposed during the continuous clinical application. Based on the pharmacophore of HDAC inhibitors, two series of compounds with novel zinc binding group (ZBG) were designed and synthesized, and the antitumor bioactivities were evaluated in four human cancer cell lines (A549, Hela, HepG2, and MCF-7). Among the synthesized compounds, compounds a6, a9, a10, b8, and b9 exhibited promising inhibitory activities against the selected tumor cell lines, especially compounds a9 and b8 on Hela's cytostatic activity (a9: IC 50 = 11.15 ± 3.24 µM; b8: IC 50 = 13.68 ± 1.31 µM). The enzyme inhibition assay against Hela extracts and HDAC1&6 subtypes showed that compound a9 had a certain broad-spectrum inhibitory activity, while compound b8 had selective inhibitory activity against HDAC6, which was consistent with Western blot results. In addition, the inhibitory mechanism of compounds a9 and b8 in HDAC1&6 were both compared through computational approaches, and the binding interactions between the compounds and the enzymes target were analyzed from the perspective of energy profile and conformation. In summary, the compounds with novel ZBG exhibited certain antitumor activities, providing valuable hints for the discovery of novel HDAC inhibitors.

Section: Identifying the Key Residues For The Target-ligand Interactionsmentioning

confidence: 99%

Synthesis and Biological Evaluation of HDAC Inhibitors With a Novel Zinc Binding Group

Liu

et al. 2020

Front. Chem.

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“…To quantify the key amino acids contributing to the interaction between the selected compounds and HDAC8, the amino acids with higher decomposition free energy (≥0.1 kcal/mol) to the compounds’ binding were discovered . As illustrated in Figure , the energy contribution of the same amino acid in HDAC8 to different compounds’ binding varied greatly (taking ASP254 in HDAC8 as an example, it contributed −0.2, −2.3, −1.5 kcal/mol to the binding of compound 2c, compound 3n, compound 3g, respectively), and different amino acids had different decomposition free energy contribution (taking compound 2c in HDAC8 as an example, the energy contribution of GLY138 equaled to − 2.04 kcal/mol, nearly 13 times of LEU21's contribution (−0.16 kcal/mol)).…”

Section: Resultsmentioning

confidence: 99%

Exploring the binding mechanism of HDAC8 selective inhibitors: Lessons from the modification of Cap group

Zhang

Ying

J of Cellular Biochemistry

et al. 2020

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The abnormal expression of histone deacetylase 8 (HDAC8) has been reported to associate with various cancer entities (colon, breast cancer, pancreas, etc.) as well as parasitic diseases, making HDAC8 gradually develop into an attractive and potential therapeutic target. Among the various design strategies of selective HDAC8 inhibitors (modification of Cap, Linker, or zinc binding group regions), the optimization of Cap region has aroused great interest among the researchers. However, the detailed information underlying how the modification of Cap region influences the inhibitory activities is still unclear, and in this study, compounds 2c, 3g, and 3n were selected to explore the differences in binding mechanisms brought by Cap modifications via various computational approaches at the atomic level. Five residues (Y293, H167, D254, D165, and M261) have a large difference in energy contributions to the constructed systems, and the subpocket formed by Y293 and M261 could interact with Cap groups, triggering the differences in the energy contributions of the residues (H167, D254, and D165) located in metal-catalytic center. In summary, the compounds 2c, 3g, and 3n were selected as molecular probes to explore the binding mechanism, and the residues (Y293 and M261) forming the subpocket should be paid special attention in the design and synthesis of novel selective HDAC8 inhibitors. K E Y W O R D S

“…The performances of one study in predicting the SZ outcome of another and vice versa were critical criteria for assessing the reproducibility of the signatures identified from independent datasets . Thus, each of the nine independent datasets (Table ) was initially selected and used to identify SZ signature.…”

Section: Methodsmentioning

confidence: 99%

Identification of the gene signature reflecting schizophrenia’s etiology by constructing artificial intelligence‐based method of enhanced reproducibility

Yang

et al. 2019

CNS Neurosci Ther

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Aims As one of the most fundamental questions in modern science, “what causes schizophrenia (SZ)” remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies is found to be extremely low due to the incapability of available feature selection methods and the lack of measurement on validating signatures’ robustness. These irreproducible results have significantly limited our understanding of the etiology of SZ. Methods In this study, a new feature selection strategy was developed, and a comprehensive analysis was then conducted to ensure a reliable signature discovery. Particularly, the new strategy (a) combined multiple randomized sampling with consensus scoring and (b) assessed gene ranking consistency among different datasets, and a comprehensive analysis among nine independent studies was conducted. Results Based on a first‐ever evaluation of methods’ reproducibility that was cross‐validated by nine independent studies, the newly developed strategy was found to be superior to the traditional ones. As a result, 33 genes were consistently identified from multiple datasets by the new strategy as differentially expressed, which might facilitate our understanding of the mechanism underlying the etiology of SZ. Conclusion A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.