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Unlimited growth of cancer cells requires an extensive nutrient supply. To meet this demand, cancer cells drastically upregulate glucose uptake and metabolism compared to normal cells. This difference has made the blocking of glycolysis a fascinating strategy to treat this malignant disease. α-enolase is not only one of the most upregulated glycolytic enzymes in cancer cells, but also associates with many cellular processes or conditions important to cancer cell survival, such as cell migration, invasion, and hypoxia. Targeting α-enolase could simultaneously disturb cancer cells in multiple ways and, therefore, is a good target for anticancer drug development. In the current study, more than 22 million chemical structures meeting the criteria of Lipinski’s rule of five from the ZINC database were docked to α-enolase by virtual screening. Twenty-four chemical structures with docking scores better than that of the enolase substrate, 2-phosphoglycerate, were further screened by the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties prediction. Four of them were classified as non-mutagenic, non-carcinogenic, and capable of oral administration where they showed steady interactions to α-enolase that were comparable, even superior, to the currently available inhibitors in molecular dynamics (MD) simulation. These compounds may be considered promising leads for further development of the α-enolase inhibitors and could help fight cancer metabolically.

The National Association of Real Estate Investment Trust (NAREIT) has suggested that Net Income (NI) might not be the best measure of operating performance for income-producing real estate, since depreciation measurement based on historical cost is inappropriate for income-producing real estate. Thus, the NAREIT purposes Funds From Operation (FFO) as a supplemental measure for operating performance of income-producing real estate. In Taiwan, Real Estate Investment Trusts (REITs) are a relatively new type of income-producing real estate investment. Since the data on REITs in Taiwan is not yet sufficient, this work uses hotel, tourism and department store industries, or real estate operating firms (REOCs), as a proxy for a preliminary study of REITs in Taiwan. The empirical results show that using a Contemporary Management Research 272 model incorporating both NI and FFO understates the explanatory power of two variables, since multicollinearity occurs. Therefore, the current study separately estimates the information content of NI and FFO, finding that the explanatory power of NI is higher than that of FFO, though the forecasting ability of FFO is higher than that of NI. But the differences between the explanatory power and forecasting ability of NI and FFO are very small. The results show that NI and FFO are both informative for income-producing real estate in Taiwan.