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Abstract Background Icaritin is an aglycone of flavonoid glycosides from Herba Epimedii. It has good performance in the treatment of hepatocellular carcinoma in clinical trials. However, the natural icaritin content of Herba Epimedii is very low. At present, the icaritin is mainly prepared from flavonoid glycosides by α-L-rhamnosidases and β-glucosidases in two-step catalysis process. However, one-pot icaritin production required reported enzymes to be immobilized or bifunctional enzymes to hydrolyze substrate with long reaction time, which caused complicated operations and high costs. To improve the production efficiency and reduce costs, we explored α-L-rhamnosidase SPRHA2 and β-glucosidase PBGL to directly hydrolyze icariin to icaritin in one-pot, and developed the whole-cell catalytic method for efficient icaritin production. Results The SPRHA2 and PBGL were expressed in Escherichia coli, respectively. One-pot production of icaritin was achieved by co-catalysis of SPRHA2 and PBGL. Moreover, whole-cell catalysis was developed for icariin hydrolysis. The mixture of SPRHA2 cells and PBGL cells transformed 200 g/L icariin into 103.69 g/L icaritin (yield 95.23%) in 4 h in whole-cell catalysis under the optimized reaction conditions. In order to further increase the production efficiency and simplify operations, we also constructed recombinant E. coli strains that co-expressed SPRHA2 and PBGL. Crude icariin extracts were also efficiently hydrolyzed by the whole-cell catalytic system. Conclusions Compared to previous reports on icaritin production, in this study, whole-cell catalysis showed higher production efficiency of icaritin. This study provides promising approach for industrial production of icaritin in the future.

Abstract. The LIM domain only 1 (LMO1) gene belongs to the LMO family of genes that encodes a group of transcriptional cofactors. This group of transcriptional cofactors regulates gene transcription by acting as a key “connector” or “scaffold” in transcription complexes. All LMOs, including LMO1, are important players in the process of tumorigenesis. Unique biological features of LMO1 distinct from other LMO members, such as its tissue-specific expression patterns, interacting proteins, and transcriptional targets, have been increasingly recognized. Studies indicated that LMO1 plays a critical oncogenic role in various types of cancers, including T-cell acute lymphoblastic leukemia, neuroblastoma, gastric cancer, lung cancer, and prostate cancer. The molecular mechanisms underlying such functions of LMO1 have also been investigated, but they are currently far from being fully elucidated. Here, we focus on reviewing the current findings on the role of LMO1 in tumorigenesis, the mechanisms of its oncogenic action, and the mechanisms that drive its aberrant activation in cancers. We also briefly review its roles in the development process and non-cancer diseases. Finally, we discuss the remaining questions and future investigations required for promoting the translation of laboratory findings to clinical applications, including cancer diagnosis and treatment.

Abstract It’s a challenge for detecting the therapeutic targets of a polypharmacological drug from variations in the responsed networks in the differentiated populations with complex diseases, as stable coronary heart disease. Here, in an adaptive, 31-center, randomized, double-blind trial involving 920 patients with moderate symptomatic stable angina treated by 14-day Danhong injection(DHI), a kind of polypharmacological drug with high quality control, or placebo (0.9% saline), with 76-day following-up, we firstly confirmed that DHI could increase the proportion of patients with clinically significant changes on angina-frequency assessed by Seattle Angina Questionnaire (ΔSAQ-AF ≥ 20) (12.78% at Day 30, 95% confidence interval [CI] 5.86–19.71%, P = 0.0003, 13.82% at Day 60, 95% CI 6.82–20.82%, P = 0.0001 and 8.95% at Day 90, 95% CI 2.06–15.85%, P = 0.01). We also found that there were no significant differences in new-onset major vascular events (P = 0.8502) and serious adverse events (P = 0.9105) between DHI and placebo. After performing the RNA sequencing in 62 selected patients, we developed a systemic modular approach to identify differentially expressed modules (DEMs) of DHI with the Zsummary value less than 0 compared with the control group, calculated by weighted gene co-expression network analysis (WGCNA), and sketched out the basic framework on a modular map with 25 functional modules targeted by DHI. Furthermore, the effective therapeutic module (ETM), defined as the highest correlation value with the phenotype alteration (ΔSAQ-AF, the change in SAQ-AF at Day 30 from baseline) calculated by WGCNA, was identified in the population with the best effect (ΔSAQ-AF ≥ 40), which is related to anticoagulation and regulation of cholesterol metabolism. We assessed the modular flexibility of this ETM using the global topological D value based on Euclidean distance, which is correlated with phenotype alteration (r 2: 0.8204, P = 0.019) by linear regression. Our study identified the anti-angina therapeutic module in the effective population treated by the multi-target drug. Modular methods facilitate the discovery of network pharmacological mechanisms and the advancement of precision medicine. (ClinicalTrials.gov identifier: NCT01681316).

Background: In the study of biomolecular structures and interactions the polar hydrogen-p bonds (Hp-π) are an extensive molecular interaction type. In proteins 11 of 20 natural amino acids and in DNA (or RNA) all four nucleic acids are involved in this type interaction. Results: The Hp-p in proteins are studied using high level QM method CCSD/6-311 + G(d,p) + H-Bq (ghost hydrogen basis functions) in vacuum and in solutions (water, acetonitrile, and cyclohexane). Three quantum chemical methods (B3LYP, CCSD, and CCSD(T)) and three basis sets (6-311 + G(d,p), TZVP, and cc-pVTZ) are compared. The Hp-p donors include R2NH, RNH2, ROH, and C6H5OH; and the acceptors are aromatic amino acids, peptide bond unit, and small conjugate p-groups. The Hp-π interaction energies of four amino acid pairs (Ser-Phe, Lys-Phe, His-Phe, and Tyr-Phe) are quantitatively calculated. Conclusions: Five conclusion points are abstracted from the calculation results. (1) The common DFT method B3LYP fails in describing the Hp-p interactions. On the other hand, CCSD/6-311 + G(d,p) plus ghost atom H-Bq can yield better results, very close to the state-of-the-art method CCSD(T)/cc-pVTZ. (2) The Hp-π interactions are point to π-plane interactions, possessing much more interaction conformations and broader energy range than other interaction types, such as common hydrogen bond and electrostatic interactions. (3) In proteins the Hp-π interaction energies are in the range 10 to 30 kJ/mol, comparable or even larger than common hydrogen bond interactions. (4) The bond length of Hp-π interactions are in the region from 2.30 to 3.00 Å at the perpendicular direction to the π-plane, much longer than the common hydrogen bonds (∼1.9 Å). (5) Like common hydrogen bond interactions, the Hp-π interactions are less affected by solvation effects. [ABSTRACT FROM AUTHOR]

A gene encoding Uninv, an invertase active in the neutral pH range, was isolated from a metagenomic library and the enzyme was biochemically characterized. The enzyme had an optimum pH of 6.5 and an optimum temperature of 50°C. It showed maximal ~37% sequence identity to all invertases identified so far. Uninv displayed typical Michaelis-Menten kinetics with substrate inhibition of sucrose, but it retained 50% activity at sucrose concentrations up to 1,000 mM. Uninv had no transfructosylating activity even at high sucrose concentrations. These properties will make this enzyme useful in the food industry. [ABSTRACT FROM AUTHOR]

In cooperation with the fragment-based design a new drug design method, the so-called “fragment-based quantitative structure–activity relationship” (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure–activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009 [ABSTRACT FROM AUTHOR]

A new drug design method, the multiple field three-dimensional quantitative structure–activity relationship (MF-3D-QSAR), is proposed. It is a combination and development of classical 2D-QSAR and traditional 3D-QSAR. In addition to the electrostatic and van der Waals potentials, more potential fields (such as lipophilic potential, hydrogen bonding potential, and nonthermodynamic factors) are integrated in the MF-3D-QSAR. Meanwhile, a principal component analysis (PCA) and iterative double least square (IDLS) technique is developed for predicting the bioactivity of query drug candidates. As an example, the MF-3D-QSAR is applied to the design of neuraminidase inhibitor and to prove its predictive power, and some useful findings are obtained for developing drugs against influenza virus. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008 [ABSTRACT FROM AUTHOR]