Application scenario-oriented molecule generation platform developed for drug discovery.

Design of molecules for candidate compound selection is one of the central challenges in drug discovery due to the complexity of chemical space and requirement of multi-parameter optimization. Here we present an application scenario-oriented platform (ID4Idea) for molecule generation in different scenarios of drug discovery. This platform utilizes both library or rule based and generative based algorithms (VAE, RNN, GAN, etc.), in combination with various AI learning types (pre-training, transfer learning, reinforcement learning, active learning, etc.) and input representations (1D SMILES, 2D graph, 3D shape, binding site, pharmacophore, etc.), to enable customized solutions for a given molecular design scenario. Besides the usual generation followed screening protocol, goal-directed molecule generation can also be conducted towards predefined goals, enhancing the efficiency of hit identification, lead finding, and lead optimization. We demonstrate the effectiveness of ID4Idea platform through case studies, showcasing customized solutions for different design tasks using various input information, such as binding pockets, pharmacophores, and compound representations. In addition, remaining challenges are discussed to unlock the full potential of AI models in drug discovery and pave the way for the development of novel therapeutics.

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

A Whole-Process Visible Strategy for the Preparation of Rhizomucor miehei Lipase with Escherichia coli Secretion Expression System and the Immobilization.

BACKGROUND: Rhizomucor miehei (RM) lipase is a regioselective lipase widely used in food, pharmaceutical and biofuel industries. However, the high cost and low purity of the commercial RM lipase limit its industrial applications. Therefore, it is necessary to develop cost-effective strategies for large-scale preparation of this lipase. The present study explored the high-level expression of RM lipase using superfolder green fluorescent protein (sfGFP)-mediated Escherichia coli secretion system. RESULTS: The sfGFP(-15) mutant was fused to the C-terminus of RM lipase to mediate its secretion expression. The yield of the fusion protein reached approximately 5.1 g/L with high-density fermentation in 5-L fermentors. Unlike conventional secretion expression methods, only a small portion of the target protein was secreted into the cell culture while majority of the fusion protein was still remained in the cytoplasm. However, in contrast to intracellular expression, the target protein in the cytoplasm could be transported efficiently to the supernatant through a simple washing step with equal volume of phosphate saline (PBS), without causing cell disruption. Hence, the approach facilitated the downstream purification step of the recombinant RM lipase. Moreover, contamination or decline of the engineered strain and degradation or deactivation of the target enzyme can be detected efficiently because they exhibited bright green fluorescence. Next, the target protein was immobilized with anion-exchange and macropore resins. Diethylaminoethyl sepharose (DEAE), a weak-basic anion-exchange resin, exhibited the highest bind capacity but inhibited the activity of RM lipase dramatically. On the contrary, RM lipase fixed with macropore resin D101 demonstrated the highest specific activity. Although immobilization with D101 didn't improve the activity of the enzyme, the thermostability of the immobilized enzyme elevated significantly. The immobilized RM lipase retained approximately 90% of its activity after 3-h incubation at 80 °C. Therefore, D101 was chosen as the supporting material of the target protein. CONCLUSION: The present study established a highly efficient strategy for large-scale preparation of RM lipase. This innovative technique not only provides high-purity RM lipase at a low cost but also has great potential as a platform for the preparation of lipases in the future.

Hit Identification Driven by Combining Artificial Intelligence and Computational Chemistry Methods: A PI5P4K-ß Case Study.

Computer-aided drug design (CADD), especially artificial intelligence-driven drug design (AIDD), is increasingly used in drug discovery. In this paper, a novel and efficient workflow for hit identification was developed within the ID4Inno drug discovery platform, featuring innovative artificial intelligence, high-accuracy computational chemistry, and high-performance cloud computing. The workflow was validated by discovering a few potent hit compounds (best IC50 is ∼0.80 µM) against PI5P4K-ß, a novel anti-cancer target. Furthermore, by applying the tools implemented in ID4Inno, we managed to optimize these hit compounds and finally obtained five hit series with different scaffolds, all of which showed high activity against PI5P4K-ß. These results demonstrate the effectiveness of ID4inno in driving hit identification based on artificial intelligence, computational chemistry, and cloud computing.

Maternal exposure to ambient PM2.5 perturbs the metabolic homeostasis of maternal serum and placenta in mice.

Epidemiological and animal studies have shown that maternal fine particulate matters (PM2.5) exposure correlates with various adverse pregnancy outcomes such as low birth weight (LBW) of offspring. However, the underlying biological mechanisms have not been fully understood. In this study, female C57Bl/6 J mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CAP) during pregestational and gestational periods, and metabolomics was performed to analyze the metabolic features in maternal serum and placenta by liquid chromatography-mass spectrometry (LC-MS). The partial least squares discriminate analysis (PLS-DA) displayed evident clustering of FA- and CAP-exposed samples for both maternal serum and placenta. In addition, pathway analysis identified that vitamin digestion and absorption was perturbed in maternal serum, while metabolic pathways including arachidonic acid metabolism, serotonergic synapse, 2-oxocarboxylic acid metabolism and cAMP signaling pathway were perturbed in placenta. Further analysis indicated that CAP exposure influenced the nutrient transportation capacity of placenta, by not only changing the ratios of some critical metabolites in placenta to maternal serum but also significantly altering the expressions of nutrition transporters in placenta. These findings reaffirm the importance of protecting women from PM2.5 exposure, and also advance our understanding of the toxic actions of ambient PM2.5.

Methane hydrate phase equilibrium considering dissolved methane concentrations and interfacial geometries from molecular simulations.

Natural gas hydrates, mainly existing in permafrost and on the seabed, are expected to be a new energy source with great potential. The exploitation technology of natural gas hydrates is one of the main focuses of hydrate-related studies. In this study, a large-size liquid aqueous solution wrapping a methane hydrate system was established and molecular dynamics simulations were used to investigate the phase equilibrium conditions of methane hydrate at different methane concentrations and interfacial geometries. It is found that the methane concentration of a solution significantly affects the phase equilibrium of methane hydrates. Different methane concentrations at the same temperature and pressure can lead to hydrate formation or decomposition. At the same temperature and pressure, in a system reaching equilibrium, the size of spherical hydrate clusters is coupled to the solution concentration, which is proportional to the Laplace pressure at the solid-liquid interface. Lower solution concentrations reduce the phase equilibrium temperature of methane hydrates at the same pressure; as the concentration increases, the phase equilibrium temperature gradually approaches the actual phase equilibrium temperature. In addition, the interfacial geometry of hydrates affects the thermodynamic stability of hydrates. The spherical hydrate particles have the highest stability for the same volume. Through this study, we provide a stronger foundation to understand the principles driving hydrate formation/dissociation relevant to the exploitation of methane hydrates.

Effects of ice and supercooled water on the metastability of methane hydrate: DSC analysis and MD simulations.

Methane hydrate (MH) has been viewed as a potential abundant clean energy resource worldwide. Its related technologies play important roles in applications of gas and energy storage, flow assurance of natural gas pipelines etc. Unlike the well-researched stability and decomposition of MH at temperatures above 273 K, the metastability of MH below the ice freezing point, i.e. the anomalous slow decomposition out of thermodynamically stable regions, remains to be unravelled. Studies regarding the influences of ice and supercooled water (SW) on the metastable properties of MH led to varied conclusions, i.e. the as-proposed self-preservation effect and metastable MH-SW-gas equilibrium. In this study, a series of DSC experiments were performed to investigate the thermal stability boundaries and the associated metastable behaviours of MH-ice-gas and MH-SW-gas samples in porous medium. The DSC analysis probed accurate thermal stabilities and characterized decomposition behaviors of the samples, contributing to the hypothesis of potential influences from SW and ice on the metastability of MH. MD simulations were also validated and performed. Active guest-host interactions by the SW layers between MH and gas phases were identified, suggesting probable microscopic configurations related to the metastability of the MH-SW-gas system. Indications of the DSC and MD simulation results call for future high-resolution in situ experimental validations.

Flurochloridone induced abnormal spermatogenesis by damaging testicular Sertoli cells in mice.

BACKGROUND: Flurochloridone (FLC), a selective herbicide used on a global scale, has been reported to have male reproductive toxicity whose evidence is limited, but its mechanism remains unclear. The present study was conducted to systematically explore the male reproductive toxicity of FLC, including sperm quality, spermatogenesis, toxicity targets, and potential mechanisms. METHODS: Male C57BL/6 mice aged 6-7 weeks received gavage administration of FLC (365/730 mg/kg/day) for 28 consecutive days. Then, the tissue and sperm of mice were collected for analysis. We measured the gonadosomatic index and analyzed sperm concentration, motility, malformation rate, and mitochondrial membrane potential (MMP). Spermatocyte immunofluorescence staining was performed to analyze meiosis. We also performed pathological staining on the testis and epididymis tissue and TUNEL staining, immunohistochemical analysis, and ultrastructural observation on the testicular tissue. RESULTS: Results showed that FLC caused testicular weight reduction, dysfunction, and architectural damage in mice, but no significant adverse effect was found in the epididymis. The exposure interfered with spermatogonial proliferation and meiosis, affecting sperm concentration, motility, kinematic parameters, morphology, and MMP, decreasing sperm quality. Furthermore, mitochondrial damage and apoptosis of testicular Sertoli cells were observed in mice treated with FLC. CONCLUSION: We found that FLC has significant adverse effects on spermatogonial proliferation and meiosis. Meanwhile, apoptosis and mitochondrial damage may be the potential mechanism of Sertoli cell damage. Our study demonstrated that FLC could induce testicular Sertoli cell damage, leading to abnormal spermatogenesis, which decreased sperm quality. The data provided references for the toxicity risk and research methods of FLC application in the environment.

Concentrated ambient fine particles exposure affects ovarian follicle development in mice.

BACKGROUND: Ambient fine particles (PM2.5) are known to cause various reproductive and developmental diseases. However, the potential mechanisms of PM2.5 exposure induced female reproductive damage remain unclear. METHODS: Four weeks old female C57BL/6 J mice were exposed to filtered air (FA, n = 10) or concentrated ambient PM2.5 (CAP, n = 10) using a versatile aerosol concentration enrichment system. After 9 weeks of the exposure, mice were sacrificed under sevoflurane anesthesia and tissue samples were collected. Immunohistochemical analysis, enzyme-linked immunosorbent assay, quantitative polymerase chain reaction, and RNA-sequencing were performed to analyze the effects of PM2.5 exposure on follicle development and elucidate its potential mechanisms. RESULTS: Chronic PM2.5 exposure resulted in follicular dysplasia. Compared to the FA-exposed group, follicular atresia in the CAP-exposed mice were significantly increased. Further studies confirmed that CAP induced apoptosis in granulosa cells, accompanied by a distortion of hormone homeostasis. In addition, RNA-sequencing data demonstrated that CAP exposure induced the alteration of ovarian gene expressions and was associated with inflammatory response. CONCLUSIONS: Chronic exposure to CAP can induce follicular atresia, which was associated with hormone modulation and inflammation.

Maternal exposure to ambient PM2.5 causes fetal growth restriction via the inhibition of spiral artery remodeling in mice.

BACKGROUND: Maternal exposure to ambient fine particulate matters (PM2.5) is associated with low birth weight (LBW) in offspring, but the underlying biological mechanisms are not yet fully understood. As the bridge that connects mother and fetus, the placenta plays a crucial role in fetal development by providing the fetus with nutrients and oxygen. However, whether PM2.5 exposure would impact the placental development and the related mechanisms are unclear. RESULTS: In the present study, female C57Bl/6j mice were exposed to filtered air (FA) or concentrated ambient PM2.5 (CAP) during pregestational and gestational periods, and the fetal development and placental structure were investigated. Our results showed that maternal exposure to CAP induced fetal growth restriction (FGR) and LBW. The placenta from CAP-exposed mice exhibited abnormal development including significant decrease of surface area, smaller junctional zone and impaired spiral artery remodeling. Meanwhile, CAP exposure altered trophoblast lineage differentiation and disrupted the balance between angiogenic and angiostatic factors in placenta. In addition, the inflammatory cytokines levels in lung, placenta and serum were significantly increased after ambient PM2.5 exposure. CONCLUSION: Our findings indicate that maternal exposure to PM2.5 disrupts normal structure and spiral artery remodeling of placenta and further induces FGR and LBW. This effect may be caused by the placental inflammation response subsequent to the pulmonary and systemic inflammation induced by ambient PM2.5 exposure.

Engineered exosomes loaded with miR-449a selectively inhibit the growth of homologous non-small cell lung cancer.

As an efficient drug carrier, exosome has been widely used in the delivery of genetic drugs, chemotherapeutic drugs, and anti-inflammatory drugs. As a genetic drug carrier, exosomes are beneficial to improve transfection efficiency and weaken side effects at the same time. Here, we use genetic engineering to prepare engineered exosomes (miR-449a Exo) that can actively deliver miR-449a. It was verified that miR-449a Exo had good homology targeting capacity and was specifically taken up by A549 cells. Moreover, miR-449a Exo had high delivery efficiency of miR-449a in vitro and in vivo. We demonstrated that miR-449a Exo effectively inhibited the proliferation of A549 cells and promoted their apoptosis. In addition, miR-449a Exo was found to control the progression of mouse tumors and prolong their survival in vivo. Our research provides new ideas for exosomes to efficiently and actively load gene drugs, and finds promising methods for the treatment of non-small cell lung cancer.

Fluorochloridone induces autophagy in TM4 Sertoli cells: involvement of ROS-mediated AKT-mTOR signaling pathway.

BACKGROUND: Fluorochloridone (FLC), a selective pyrrolidone herbicide, has been recognized as a potential endocrine disruptor and reported to induce male reproductive toxicity, but the underlying mechanism is unclear. The aim of this study was to investigate the mechanism of FLC-induced reproductive toxicity on male mice with particular emphasis on the role of autophagy in mice' TM4 Sertoli cells. METHODS: Adult C57BL/6 mice were divided into one control group (0.5% sodium carboxymethyl cellulose), and four FLC-treated groups (3,15,75,375 mg/kg). The animals (ten mice per group) received gavage for 28 days. After treatment, histological analysis, sperm parameters, the microstructure of autophagy and the expression of autophagy-associated proteins in testis were evaluated. Furthermore, to explore the autophagy mechanism, TM4 Sertoli cells were treated with FLC (0,40,80,160 µM) in vitro for 24 h. Cell activity and cytoskeletal changes were measured by MTT assay and F-actin immunofluorescence staining. The formation of autophagosome, accumulation of reactive oxygen species (ROS), expression of autophagy marker proteins (LC3, Beclin-1 and P62) and AKT-related pathway proteins (AKT, mTOR) were observed. The ROS scavenger N-acetylcysteine (NAC) and AKT agonist (SC79) were used to treat TM4 cells to observe the changes of AKT-mTOR pathway and autophagy. RESULTS: In vivo, it showed that FLC exposure caused testicular injuries, abnormality in epididymal sperm. Moreover, FLC increased the formation of autophagosomes, the accumulation of LC3II/LC3I, Beclin-1 and P62 protein, which is related to the degradation of autophagy. In vitro, FLC triggered TM4 cell autophagy by increasing the formation of autophagosomes and upregulating of LC3II/LC3I, Beclin-1 and P62 levels. In addition, FLC induced ROS production and inhibited the activities of AKT and mTOR kinases. The Inhibition of AKT/mTOR signaling pathways and the activation of autophagy induced by FLC could be efficiently reversed by pretreatment of NAC. Additionally, decreased autophagy and increased cell viability were observed in TM4 cells treated with SC79 and FLC, compared with FLC alone, indicating that FLC-induced autophagy may be pro-death. CONCLUSION: Taken together, our study provided the evidence that FLC promoted autophagy in TM4 Sertoli cells and that this process may involve ROS-mediated AKT/mTOR signaling pathways.

Enhancing Demulsification Performance for Oil-Water Separation through Encapsulating Ionic Liquids in the Pore of MIL-100(Fe).

Emulsion poses a greater challenge for the remediation of oily wastewater, which can be effectively resolved by the metal-organic framework of MIL-100(Fe). The formula Fe3O(H2O)2(OH) (BTC)2 pronounces that MIL-100(Fe) suffers from an intrinsic defect of less charged atoms, which limits its demulsification performance for oil-water separation. Herein, cations of the ionic liquid (1-allyl-3-methylimidazolium, Amim+) were encapsulated in the micropore of MIL-100(Fe) in situ to increase the positive charge density of MIL-100(Fe). Zeta potential demonstrated that the encapsulation of Amim+ increased the positive charge amount of MIL-100(Fe). N2 probe isothermal adsorption/desorption and spectral measurements (X-ray photoelectron spectroscopy, ultraviolet-visible diffuse reflection spectroscopy, and attenuated total-reflectance infrared spectroscopy) revealed the host-guest interactions of π···Fe complexation and π···cation electrostatic attraction between Amim+ and MIL-100(Fe) for the composite materials. Amim+ encapsulation greatly enhanced the demulsification performance of MIL-100(Fe) for oil-in-water (O/W) emulsion stabilized by sodium dodecyl sulfate. Amim+-encapsulated MIL-100(Fe) with an Amim+/Fe3+ molar ratio of 1:1 [Amim@MIL-100(Fe)-3:3] showed a demulsification efficiency (DE) of 94% within 30 s, compared with MIL-100(Fe) within 30 min. The maximum DE of Amim@MIL-100(Fe)-3:3 was found to be more than 98% within 5 min. The DE lost by MIL-100(Fe) at the third run decreased from 36 to 17% after encapsulating Amim+. The analysis of surface charge and interfacial tension implied a demulsification mechanism of capturing-fusion, which could be promoted by the greater electrostatic attraction. Finally, the role of Amim+ on the outstanding demulsification performance by Amim+-encapsulated MIL-100(Fe) could be explained by the enhanced nonbonded interaction of electrostatic attraction and van der Waals based on the molecular dynamics simulation.

A Cloud Computing Platform for Scalable Relative and Absolute Binding Free Energy Predictions: New Opportunities and Challenges for Drug Discovery.

Free energy perturbation (FEP) has become widely used in drug discovery programs for binding affinity prediction between candidate compounds and their biological targets. However, limitations of FEP applications also exist, including, but not limited to, high cost, long waiting time, limited scalability, and breadth of application scenarios. To overcome these problems, we have developed XFEP, a scalable cloud computing platform for both relative and absolute free energy predictions using optimized simulation protocols. XFEP enables large-scale FEP calculations in a more efficient, scalable, and affordable way, for example, the evaluation of 5000 compounds can be performed in 1 week using 50-100 GPUs with a computing cost roughly equivalent to the cost for the synthesis of only one new compound. By combining these capabilities with artificial intelligence techniques for goal-directed molecule generation and evaluation, new opportunities can be explored for FEP applications in the drug discovery stages of hit identification, hit-to-lead, and lead optimization based not only on structure exploitation within the given chemical series but also including evaluation and comparison of completely unrelated molecules during structure exploration in a larger chemical space. XFEP provides the basis for scalable FEP applications to become more widely used in drug discovery projects and to speed up the drug discovery process from hit identification to preclinical candidate compound nomination.

Flurochloridone induces Sertoli cell apoptosis through ROS-dependent mitochondrial pathway.

Flurochloridone (FLC), a selective herbicide used on a global scale, has been reported to have male reproductive toxicity which underlying mechanism is still largely unknown. The present study was conducted to determine the effects of FLC on Sertoli cell and explore its mechanism by using normal mouse Sertoli (TM4) cell line. Our data indicate that FLC suppressed proliferation of TM4 cells in a dose- and time-dependent manner. Further studies confirmed that FLC induced apoptosis in TM4 cells, accompanied by reactive oxygen species (ROS) accumulation, intracellular calcium increase, opening of mitochondrial permeability transition pore, depolarization of the mitochondrial membrane potential (MMP) and decrease of adenosine triphosphate (ATP) level. Meanwhile, changes of B-cell lymphoma-2 (Bcl-2) family proteins expression, release of cytochrome c and the activation of caspase-9 and caspase-3 were also confirmed. These results indicate that FLC induces TM4 cells apoptosis through the mitochondrial apoptotic pathway. In addition, pretreatment with ROS scavenger N-acetyl-L-cysteine (NAC), could significantly alleviate FLC-induced TM4 cells apoptosis and MMP depolarization. In conclusion, our results suggested that FLC induced TM4 cells apoptosis and it was regulated by mitochondrial dysfunction and oxidative stresses.

Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability.

Pairwise-based methods such as the free energy perturbation (FEP) method have been widely deployed to compute the binding free energy differences between two similar host-guest complexes. The calculated pairwise free energy difference is either directly adopted or transformed to absolute binding free energy for molecule rank ordering. We investigated, through both analytic derivations and simulations, how the selection of pairs in the experiment could impact the overall prediction precision. Our studies showed that (1) the estimated absolute binding free energy ( ΔG^ ) derived from calculated pairwise differences (ΔΔG) through weighted least squares fitting is more precise in prediction than the pairwise difference values when the number of pairs is more than the number of ligands and (2) prediction precision is influenced by both the total number of pairs and the specifically selected pairs, the latter being critically important when the number of calculated pairs is limited. Furthermore, we applied optimal experimental design in pair selection and found that the optimally selected pairs can outperform randomly selected pairs in prediction precision. In an illustrative example, we showed that, upon weighing ligand structure similarity into design optimization, the weighted optimal designs are more efficient than the literature reported designs. This work provides a new approach to assess retrospective pairwise-based prediction results, and a method to design new prospective pairwise-based experiments for molecular lead optimization. © 2019 Wiley Periodicals, Inc.

Guiding Lead Optimization for Solubility Improvement with Physics-Based Modeling.

Although there are a number of computational approaches available for the aqueous solubility prediction, a majority of those models rely on the existence of a training set of thermodynamic solubility measurements or/and fail to accurately account for the lattice packing contribution to the solubility. The main focus of this study is the validation of the application of a physics-based aqueous solubility approach, which does not rely on any prior knowledge and explicitly describes the solid-state contribution, in order to guide the improvement of poor solubility during the lead optimization. A superior performance of a quantum mechanical (QM)-based thermodynamic cycle approach relative to a molecular mechanical (MM)-based one in application to the optimization of two pharmaceutical series was demonstrated. The QM-based model also provided insights into the source of poor solubility of the lead compounds, allowing the selection of the optimal strategies for chemical modification and formulation. It is concluded that the application of that approach to guide solubility improvement at the late discovery and/or early development stages of the drug design proves to be highly attractive.

Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations.

The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the "hotspot" residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis and also provide useful information for the design of antiviral drugs.

The application of DNA molecular markers in the study of Codonopsis species genetic variation, a review.

Codonopsis genus is comprised of species that are perennial plants primarily distributed across all east, southeast, and Central Asia. The most famous species of Codonopsis are C. tangshen, C. lanceolate, and C. pilosula. The records showed that they have a long story usage as traditional Chinese medicines, as they were alleged to be able to intensify the spleen and the lung as well as enriching blood and engendering liquid. Certain species have a culinary value in southern China and Southeast Asia, where they are considered as tea, wine, soup, plaster, and porridge. Codonopsis species were shown to be of great importance in medicine, due to their broad biological activity. Therefore, a clear understanding of their genetic diversity is needed.  Adequate distinctions and descriptions of those species are necessary to preserve plant reservoir, investigations of genes associated with desirable traits, and understanding of evolutionary relationships. Subsequently, various molecular marker techniques such as Random Amplified Polymorphic DNA (RAPD), Amplified Fragment Length Polymorphism (AFLP), Simple Sequence Repeats (SSR), and Inter Simple Sequence Repeat (ISSR), Single Nucleotide Polymorphism (SNP), internal transcribed spacer (ITS), and Sequence-Characterized Amplified Region (SCAR) have been improved to provide  detailed informations about genomes, that historically were  not possible to obtain based on only phenotypic methods. This review represents the usage of DNA molecular markers for molecular diversity analysis of medically important species belonging to the genus Codonopsis.

High-throughput Sequencing-based Analysis of Microbial Diversity in Rice Wine Koji from Different Areas.

Rice wine, a traditional fermented alcoholic beverage in China, is produced with grains such as rice, which are fermented with saccharifying starter-koji. Its flavor quality is closely associated to the starter culture-koji, which is made by mixing botanical materials with high-class glutinous rice in certain ecological context. However, there are few reports on the microbial community structure of rice wine koji. In this paper, bacterial community structures of rice wine koji were analyzed using 16S rRNA gene sequencing based on Illumina MiSeq high-throughput technology in 20 samples collected from Xiaogan area, Hubei province and Dazhu area, Sichuan province (10 from each area). We found rice wine koji flora mainly consisted of Weissella, Lactobacillus, Lactococcus, Bacillus, Enterococcus, and Cronobacter, with relative abundances of 29.49%, 10.93%, 8.85%, 4.75%, 1.16% and 1.15%, respectively, as well as an accumulative average relative abundance of 58.71%. They all belonged to Firmicutes and Proteobacteria-the two known dominant genus. Genus-level PCA (Principal component analysis) and OTU-level PCoA (Principal coordinates analysis) based on unweighted UniFrac distances showed that the bacterial community structure differed significantly between the samples from the 2 areas. 7 OTUs were detected in all samples, accounting for 4.4% of the total qualified assembly. Among the 7 OTUs, 3 OTUs were identified as Enterococcus, 2 OTUs were identified as Cronobacter, 1 OTU was identified as Bacillus and 1 OTU was identified as Alkaliphilus. Fifty-eight lactic acid bacteria (LAB) strains were isolated from the 20 koji samples with traditional microbial methods. Among them, Enterococcus faecium and Pediococcus pentosaceus were the dominant LAB isolates, with relative abundances of 51.72% and 31.03%. Despite the differences, a large number of shared bacteria were detected in samples from the two areas.