在a^2与(a+1)~2间至少有二个素数

本文依据同余理论将λ + 1(λ 1)个连续整数构成的整数段D[b]λ={b ,b + 1,Λ ,b +λ}(b∈Z)划归为模π′n=P2 P3ΛPn的最小非负完全剩余段系D[Bn]λ,并引进了“n维筛法” ,从而证得本文主要结论 :在a2 与 (a + 1) 2

In Silico Screening for Microsatellite Markers from Expressed Sequence Tags of Porphyra yezoensis (Bangiales, Rhodophyta)

The genomic resources of Porphyra yezoensis expressed sequence tags (ESTs) were utilized to identify simple sequence repeats (SSRs), or microsatellites. This method took the advantage of using ESTs and microsatellites either for the establishment of gene identities or for the acquisition of high polymorphism. The microsatellites can be used as gene markers when microsatellites are tagged to genes. Revealed by bioinformatics analysis, 1 162 out of 21 954 ESTs contained microsatellites and cluster analysis indi- cated that 984 of these ESTs fell into 112 contigs, while the other 178 ESTs were singletons. A total of 290 unique SSR-containing genes were identified. The AAC SSRs were the most populous type of microsatellites. GC-rich microsatellites were predominant among all the microsatellites.

New lead discovery for novel M_1 agonists:pharmacophore model based on DISCO computation and virtual screening

To discover new lead compounds for M1 agonists. Ten typical M1 agonists were superimposed to build a M1 agonists 3D-pharmacophore model using distance-comparisons （DISCO） method without the previous knowledge of the three-dimensional structure of M1 receptor. Virtual screening strategy was used to analyze the Available Chemicals Directory-Screening Compounds （ACD-SC） to identify possible new hits. Twenty-two compounds which fit the pharmacophore model well and are not similar with known M1 agonists were purchased in order to evaluate their M1 receptor agonist activity. One of them shows M1 receptor agonist activity with EC50 of 4.90 μmol/L and maximum response. Multiple of 10.0 which shows it worthy of further study as a new lead compound for M1 agonists.

Virtual Screening of Human O-GIcNAc Transferase Inhibitors

O-GlcNAc transferase （OGT） is one of essential mammalian enzymes, which catalyze the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine （UDP-GlcNAc） to hydroxyl groups of serines and threonines （Ser/Thr） in proteins. Dysregulations of cellular O-GlcNAc have been implicated in diabetes, neurodegenerative disease, and cancer, which brings great interest in developing potent and specific small-molecular OGT inhibitors. In this work, we performed virtual screening on OGT catalytic site to identify potential inhibitors. 7134792 drug-like compounds from ZINC （a free database of commercially available compounds for virtual screening） and 4287550 compounds generated by FOG （fragment optimized growth program） were screened and the top 116 compounds ranked by docking score were analyzed. By comparing the screening results, we found FOG program can generate more compounds with better docking scores than ZINC. The top ZINC compounds ranked by docking score were grouped into two classes, which held the binding positions of UDP and GlcNAc of UDP- GlcNAc. Combined with individual fragments in binding pocket, de novo compounds were designed and proved to have better docking score. The screened and designed compounds may become a starting point for developing new drugs.

A virtual test of screening technology based on the AGEIA PhysX

The authors have created a virtual test of vibration particle-screening using Autodesk's 3ds Max software,the MAXScript scripting language and the AGEIA PhysX physics processing unit(PPU).The affect of various parameters on screening efficiency were modeled.The parameters included vibration amplitude,frequency and direction.The length and inclination of the vibrating surface were also varied.The virtual experiment is in basic agreement with results predicted from screening theory.This shows that the virtual screener can be used for preliminary investigations and the results used to evaluate screen design.In addition it can help with theoretical research.

Structural Dynamics of Amyloid β Peptide Binding to Acetylcholine Receptor and Virtual Screening for Effective Inhibitors

The interaction between Amyloid β(Aβ) peptide and acetylcholine receptor is the key for our understanding of how Aβ fragments block the ion channels within the synapses and thus induce Alzheimer’s disease.Here,molecular docking and molecular dynamics(MD)simulations were performed for the structural dynamics of the docking complex consisting of Aβ and α7-n ACh R(α7 nicotinic acetylcholine receptor),and the inter-molecular interactions between ligand and receptor were revealed.The results show that Aβ_(25-35) is bound toα7-n ACh R through hydrogen bonds and complementary shape,and the Aβ_(25-35) fragments would easily assemble in the ion channel of α7-n ACh R,then block the ion transfer process and induce neuronal apoptosis.The simulated amide-I band of Aβ_(25-35) in the complex is located at 1650.5 cm^(-1),indicating the backbone of Aβ_(25-35) tends to present random coil conformation,which is consistent with the result obtained from cluster analysis.Currently existing drugs were used as templates for virtual screening,eight new drugs were designed and semi-flexible docking was performed for their performance.The results show that,the interactions between new drugs and α7-n ACh R are strong enough to inhibit the aggregation of Aβ_(25-35) fragments in the ion channel,and also be of great potential in the treatment of Alzheimer’s disease.

Identification of Potential Flavonoid Inhibitors of the SARS-CoV-2 Main Protease 6YNQ:A Molecular Docking Study

Objective Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),the causative agent for coronavirus disease 2019(COVID-19),is responsible for the recent global pandemic.As there are no effective drugs or vaccines available for SARS-CoV-2,we investigated the potential of flavonoids against SARS-CoV-2 main protease 6YNQ.Methods In silico molecular simulation study against SARS-CoV-2 main protease 6YNQ.Results Among the 21 selected flavonoids,rutin demonstrated the highest binding energy(−8.7 kcal/mol)and displayed perfect binding with the catalytic sites.Conclusions Our study demonstrates the inhibitory potential of flavonoids against SARS-CoV-2 main protease 6YNQ.These computational simulation studies support the hypothesis that flavonoids might be helpful for the treatment of COVID-19.

Comparison and discovery of potential non-covalent CD38 inhibitors by virtual screening strategy based on natural substrates and known inhibitors

As a type II or III transmembrane glycoprotein, human CD38 is ubiquitously expressed in all mammalian tissues. CD38 is a multi-functional enzyme and a member of the ADP-ribosyl cyclase family, and it catalyzes nicotinamide adenine dinucleotide （NAD^＋） and nicotinamide adenine dinucleotide phosphate （NADP＋） to two distinct Ca^2＋ messengers as follows： cyclic ADP-ribose （cADPR） and nicotinic acid adenine dinucleotide phosphate （NAADP）, respectively. Moreover, both cADPR and NAADP mediate mobilization of intracellular Ca^2＋ targeting endoplasmic stores and the lysosomes, respectively. In this study, we combined ligand-based and structure-based virtual screening strategies to compare the inhibitor discovery efficacy based on natural substrates and the known inhibitors. The similarity queries towards SPECS database were carried out using ROCS and EON modules of OpenEye software. The hits were further docked to CD38 using AutoDock 4.05 program. In addition, ADME studies were also processed considering solubility in water and membrane permeability. Finally, we identified 17 compotmds-based on natural substrates and 10 compounds based on known inhibitor models. The results showed that the known inhibitor H2-based model was more efficient in virtual screening of CD38 non-covalent inhibitors.

Insights into the discovery of new 5-HT1A receptor ligands:receptor based pharmacophore

5-HT1A receptor is a crucial therapeutic target for the treatment of anxiety, depression, pain, etc. Design and preparation of potent 5-HT1A receptor ligands for drug discovery has attracted extensive attention in the past few years. In this paper, a three dimensional model of human 5-HT1A receptor was constructed by means of homology modeling. And the docking of MP349 to the receptor suggested a reliable binding mode for 5-HT1A receptor ligand. Based on this ligand-receptor binding mode, an elaborate receptor structure based pharmacophore model was established, which revealed many important features responsible for ligand and 5-HT1A receptor interactions. A virtual screening experiment verified the ability of this pharmacophore model to discover true 5-HT1A receptor ligand. The results of this research would provide important information for further optimizations of 5-HT1A receptor ligands and guide related new lead discoveries.

Designing natural product-like virtual libraries using deep molecule generative models

Natural products（NPs） have long been recognized as a valuable resource for drug discovery, and bringing NP-related features to virtual libraries is believed to be an effective way to increase the coverage of druggable chemical space. Here, deep learning-based molecule generative model, which is a recent technique in de novo molecule design, was applied to generate virtual libraries with NP-like properties. Results demonstrated that the model was effective in generating molecules that highly resemble NPs. Moreover, the model was also found to be capable of generating NP-like molecules that were also easy to synthesize, significantly increasing the practical value of the compound library.

Virtual screening and high-throughput testing of L1 metallo-β-lactamase inhibitor

As a zinc-dependent enzyme, metal-β-lactamase L1 contributes to the development of β-lactam antibiotic resistance. The metal-β-lactamase inhibitor can restore the efficacy of β-lactam antibiotics, and its development has attracted much attention. In the present study, we used four widely-used virtual screening programs to screen 7035 small molecules to identify potential L1 inhibitors, and a high-throughput experimental model of L1 inhibitors was established. In this high-throughput testing model, the inhibition rate of 163 compounds on L1 exceeded 40%. The results of virtual screening of 7035 small molecules using the following four programs showed that among the top 1.35% of the compounds, their hit rates were ranked as Schr?dinger’s(5.26%), DS(1.05%), and Sybyl-x 2.0(1.05%), and Smina(2.11%).

Virtual screening for triple-negative breast cancer cell inhibitors based on telomere G-quadruplex structure

Triple-negative breast cancer is an aggressive subtype that frequently develops resistance to chemotherapy. It is expected to develop new anti-tumor drugs through targeting the structure of G-quadruplexes of the genes associated with this tumor. In this work, by targeting the 21-mer telomere G-quadruplex structure, compounds VB07 and VC02 were identified to stabilize the telomere G-quadruplex through structure-based high-throughput virtual screening. Cell cytotoxicity assay showed that VB07 and VC02 exhibited inhibitory effect on triple-negative breast cancer cells at the concentration of 5 μM. This study showed that structure-based high-throughput virtual screening was able to successfully identify the proper compounds targeting the telomere G-quadruplex, which exhibited inhibitory effects against the triple-negative breast cancer cells.

MUTUAL ARTIFICIAL BEE COLONY ALGORITHM FOR MOLECULAR DOCKING

Molecular docking method plays an important role on the quest of potential drug candidates, which has been proven to be a valuable tool for virtual screening. Molecular docking is commonly referred to as a parameter optimization problem. During the last decade, some optimization algorithms have been introduced, such as Lamarckian genetic algorithm （LGA） and SODOCK embedded in the AutoDock program. On the basis of the latest docking software AutoDock4.2, we present a novel docking program ABCDock, which incorporates mutual artificial bee colony （MutualABC） into AutoDock. Computer simulation results demonstrate that ABCDock takes precedence over AutoDock and SODOCK, in terms of convergence performance, accuracy, and the lowest energy, especially for highly flexible ligands. It is noteworthy that ARCDock yields a higher success rate. Also, in comparison with the other state-of-the-art docking methods, namely GOLD, DOCK and FlexX, ABCDock provides the smallest RMSD in 27 of 37 cases.