This research focused on the modification of the functional groups of oseltamivir as neuraminidase inhibitor against influenza A virus subtype H1N1.Interactions of three of the best ligands were evaluated in the hydra...This research focused on the modification of the functional groups of oseltamivir as neuraminidase inhibitor against influenza A virus subtype H1N1.Interactions of three of the best ligands were evaluated in the hydrated state using molecular dynamics simulation at two different temperatures.The docking result showed that AD3BF2 D ligand（N-[（1S,6R）-5-amino-5-{[（2R,3S,4S）-3,4-dihydroxy-4-（hydroxymethyl） tetrahydrofuran-2-yl]oxy}-4-formylcyclohex-3-en-1-yl]acetamide-3-（1-ethylpropoxy）-1-cyclohexene-1-carboxylate） had better binding energy values than standard oseltamivir.AD3BF2 D had several interactions,including hydrogen bonds,with the residues in the catalytic site of neuraminidase as identified by molecular dynamics simulation.The results showed that AD3BF2 D ligand can be used as a good candidate for neuraminidase inhibitor to cope with influenza A virus subtype H1N1.展开更多
MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of b...MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of biological functions such as regulation of innate and adaptive immunity,cell differentiation and development as well as展开更多
The functional impact of several long intergenic non-coding RNAs (lincRNAs) has been characterized in previous studies. However, it is difficult to identify lincRNAs on a large-scale and to ascertain their functions o...The functional impact of several long intergenic non-coding RNAs (lincRNAs) has been characterized in previous studies. However, it is difficult to identify lincRNAs on a large-scale and to ascertain their functions or predict their structures in laboratory experiments because of the diversity, lack of knowledge and specificity of expression of lincRNAs. Furthermore, although there are a few well-characterized examples of lincRNAs associated with cancers, these are just the tip of the iceberg owing to the complexity of cancer. Here, by combining RNA-Seq data from several kinds of human cell lines with chromatin-state maps and human expressed sequence tags, we successfully identified more than 3000 human lincRNAs, most of which were new ones. Subsequently, we predicted the functions of 105 lincRNAs based on a coding-non-coding gene co-expression network. Finally, we propose a genetic mediator and key regulator model to unveil the subtle relationships between lincRNAs and lung cancer. Twelve lincRNAs may be principal players in lung tumorigenesis. The present study combines large-scale identification and functional prediction of human lincRNAs, and is a pioneering work in characterizing cancer-associated lincRNAs by bioinformatics.展开更多
The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of Tcells.To date,the complete landscape and systematic characterization of long noncoding RNAs(lncRNAs)i...The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of Tcells.To date,the complete landscape and systematic characterization of long noncoding RNAs(lncRNAs)in T cells in cancer immunity are lacking.Here,by systematically analyzing full-length single-cell RNA sequencing(scRNA-seq)data of more than 20,000 libraries of T cells across three cancer types,we provided the first comprehensive catalog and the functional repertoires of lncRNAs in human T cells.Specifically,we developed a custom pipeline for de novo transcriptome assembly and obtained a novel lncRNA catalog containing 9433 genes.This increased the number of current human lncRNA catalog by 16%and nearly doubled the number of lncRNAs expressed in T cells.We found that a portion of expressed genes in single T cells were lncRNAs which had been overlooked by the majority of previous studies.Based on metacell maps constructed by the MetaCell algorithm that partitions scRNA-seq datasets into disjointed and homogenous groups of cells(metacells),154 signature lncRNA genes were identified.They were associated with effector,exhausted,and regulatory T cell states.Moreover,84 of them were functionally annotated based on the co-expression networks,indicating that lncRNAs might broadly participate in the regulation of T cell functions.Our findings provide a new point of view and resource for investigating the mechanisms of T cell regulation in cancer immunity as well as for novel cancer-immune biomarker development and cancer immunotherapies.展开更多
Mammals and other complex organisms can transcribe an abundance of long non-coding RNAs(lncRNAs)that fulfill a wide variety of regulatory roles in many biological processes.These roles,including as scaffolds and as gu...Mammals and other complex organisms can transcribe an abundance of long non-coding RNAs(lncRNAs)that fulfill a wide variety of regulatory roles in many biological processes.These roles,including as scaffolds and as guides for protein-coding genes,mainly depend on the structure and expression level of lncRNAs.In this review,we focus on the current methods for analyzing lncRNA structure and expression,which is basic but necessary information for in-depth,large-scale analysis of lncRNA functions.展开更多
Translational medicine is a new discipline aiming to elimi- nate the barrier between preclinical and clinical medicine . It converts promising laboratory discoveries into clini-cal applications and elucidates clinical...Translational medicine is a new discipline aiming to elimi- nate the barrier between preclinical and clinical medicine . It converts promising laboratory discoveries into clini-cal applications and elucidates clinical questions with the use of benchwork, aiming to facilitate prediction, preven-tion, diagnosis, and treatment of diseases . The Director of US National Institutes of Health （NIH）, Dr.展开更多
Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis.However,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the cu...Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis.However,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available software.Here,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data analysis.Results show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin nodes.In comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat node.CloudLCA can be run on one multiprocessor node or a cluster.It is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following analysis.Moreover,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.展开更多
RNA sequencing(RNA-seq) has greatly facilitated the exploring of transcriptome landscape for diverse organisms.However,transcriptome reconstruction is still challenging due to various limitations of current tools and ...RNA sequencing(RNA-seq) has greatly facilitated the exploring of transcriptome landscape for diverse organisms.However,transcriptome reconstruction is still challenging due to various limitations of current tools and sequencing technologies.Here,we introduce an efficient tool,QuaPra(Quadratic Programming combined with Apriori),for accurate transcriptome assembly and quantification.QuaPra could detect at least 26.5% more low abundance(0.1–1 FPKM) transcripts with over 2.7% increase of sensitivity and precision on simulated data compared to other currently popular tools.Moreover,around one-quarter more known transcripts were correctly assembled by QuaPra than other assemblers on real sequencing data.QuaPra is freely available at http://www.megabionet.org/QuaPra/.展开更多
Eukaryotic mRNAs consist of two forms of transcripts:poly(A)+ and poly(A),based on the presence or absence of poly(A) tails at the 3 end.Poly(A)+ mRNAs are mainly protein coding mRNAs,whereas the functions of poly(A) ...Eukaryotic mRNAs consist of two forms of transcripts:poly(A)+ and poly(A),based on the presence or absence of poly(A) tails at the 3 end.Poly(A)+ mRNAs are mainly protein coding mRNAs,whereas the functions of poly(A) mRNA are largely unknown.Previous studies have shown that a significant proportion of gene transcripts are poly(A) or bimorphic(containing both poly(A)+ and poly(A) transcripts).We compared the expression levels of poly(A) and poly(A)+ RNA mRNAs in normal and cancer cell lines.We also investigated the potential functions of these RNA transcripts using an integrative workflow to explore poly(A)+ and poly(A) transcriptome sequences between a normal human mammary gland cell line(HMEC) and a breast cancer cell line(MCF-7),as well as between a normal human lung cell line(NHLF) and a lung cancer cell line(A549).The data showed that normal and cancer cell lines differentially express these two forms of mRNA.Gene ontology(GO) annotation analyses hinted at the functions of these two groups of transcripts and grouped the differentially expressed genes according to the form of their transcript.The data showed that cell cycle-,apoptosis-,and cell death-related functions corresponded to most of the differentially expressed genes in these two forms of transcripts,which were also associated with the cancers.Furthermore,translational elongation and translation functions were also found for the poly(A) protein-coding genes in cancer cell lines.We demonstrate that poly(A) transcripts play an important role in cancer development.展开更多
Highly Pathogenic Avian Influenza（HPAI） H5N1 has attracted much attention as a potential pandemic virus in humans, which makes death inevitable in humans. Neuraminidase（NA） has an important role in viral replicati...Highly Pathogenic Avian Influenza（HPAI） H5N1 has attracted much attention as a potential pandemic virus in humans, which makes death inevitable in humans. Neuraminidase（NA） has an important role in viral replication. Thus, it is an attractive target when designing anti-influenza virus drug. However, evolving viruses cause some anti-viral drugs to be ineffective, as they show resistance to them. Selection of peptides as drug candidates is important for the peptide-receptor activity and good selectivity. Cyclic bonds in the peptide ligand design aim to improve the stability of the system and remove the obstacles in drug metabolism. The design is based on the polarity of the ligand and amino acid residues in the active site of NA. The results are 4200 cyclic pentapeptides as potential lead compounds. Docking simulations were conducted using MOE 2008.10 and were screened based on the value of the binding energy（？Gbinding）. ADME-Tox prediction assay was conducted on the selected ligands.Intra- and inter-molecular interactions, as well as changes in the form of bonds, were tested by molecular dynamics simulations at temperatures of 310 K and 312 K. The results of the docking simulations and toxicity prediction assay show that there are two ligands that have a residual interaction with the target protein： CLDRC and CIWRC. These two ligands have ？Gbindingvalues of –40.5854 and –39.9721 kcal/mol（1 kcal/mol = 4.18 k J/mol）. These ligands are prone to be mutagenic and carcinogenic, and they have a good oral bioavailability. The results show that the molecular dynamics of both ligand CLDRC and CIWRC are more feasible at the temperature of 312 K. At the end,both CIWRC and CLDRC ligands can be used as the drug candidates against H5N1 virus.展开更多
文摘This research focused on the modification of the functional groups of oseltamivir as neuraminidase inhibitor against influenza A virus subtype H1N1.Interactions of three of the best ligands were evaluated in the hydrated state using molecular dynamics simulation at two different temperatures.The docking result showed that AD3BF2 D ligand（N-[（1S,6R）-5-amino-5-{[（2R,3S,4S）-3,4-dihydroxy-4-（hydroxymethyl） tetrahydrofuran-2-yl]oxy}-4-formylcyclohex-3-en-1-yl]acetamide-3-（1-ethylpropoxy）-1-cyclohexene-1-carboxylate） had better binding energy values than standard oseltamivir.AD3BF2 D had several interactions,including hydrogen bonds,with the residues in the catalytic site of neuraminidase as identified by molecular dynamics simulation.The results showed that AD3BF2 D ligand can be used as a good candidate for neuraminidase inhibitor to cope with influenza A virus subtype H1N1.
文摘MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of biological functions such as regulation of innate and adaptive immunity,cell differentiation and development as well as
基金supported by Beijing Natural Science Foundation(5122029)
文摘The functional impact of several long intergenic non-coding RNAs (lincRNAs) has been characterized in previous studies. However, it is difficult to identify lincRNAs on a large-scale and to ascertain their functions or predict their structures in laboratory experiments because of the diversity, lack of knowledge and specificity of expression of lincRNAs. Furthermore, although there are a few well-characterized examples of lincRNAs associated with cancers, these are just the tip of the iceberg owing to the complexity of cancer. Here, by combining RNA-Seq data from several kinds of human cell lines with chromatin-state maps and human expressed sequence tags, we successfully identified more than 3000 human lincRNAs, most of which were new ones. Subsequently, we predicted the functions of 105 lincRNAs based on a coding-non-coding gene co-expression network. Finally, we propose a genetic mediator and key regulator model to unveil the subtle relationships between lincRNAs and lung cancer. Twelve lincRNAs may be principal players in lung tumorigenesis. The present study combines large-scale identification and functional prediction of human lincRNAs, and is a pioneering work in characterizing cancer-associated lincRNAs by bioinformatics.
基金This work was supported by the Science and Technology Project of Shenzhen,China(Grant Nos.JCYJ20190807145013281,JHZ20170310090257380,JCYJ20170413092711058,and JCYJ20170307095822325)the China Postdoctoral Science Foundation(Grant No.2019M663369)the National Natural Science Foundation of China(Grant No.31970636).
文摘The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of Tcells.To date,the complete landscape and systematic characterization of long noncoding RNAs(lncRNAs)in T cells in cancer immunity are lacking.Here,by systematically analyzing full-length single-cell RNA sequencing(scRNA-seq)data of more than 20,000 libraries of T cells across three cancer types,we provided the first comprehensive catalog and the functional repertoires of lncRNAs in human T cells.Specifically,we developed a custom pipeline for de novo transcriptome assembly and obtained a novel lncRNA catalog containing 9433 genes.This increased the number of current human lncRNA catalog by 16%and nearly doubled the number of lncRNAs expressed in T cells.We found that a portion of expressed genes in single T cells were lncRNAs which had been overlooked by the majority of previous studies.Based on metacell maps constructed by the MetaCell algorithm that partitions scRNA-seq datasets into disjointed and homogenous groups of cells(metacells),154 signature lncRNA genes were identified.They were associated with effector,exhausted,and regulatory T cell states.Moreover,84 of them were functionally annotated based on the co-expression networks,indicating that lncRNAs might broadly participate in the regulation of T cell functions.Our findings provide a new point of view and resource for investigating the mechanisms of T cell regulation in cancer immunity as well as for novel cancer-immune biomarker development and cancer immunotherapies.
基金supported by the National High Technology Research and Development Program of China(2012AA020402)National Natural Science Foundation of China(11074084,30970558)
文摘Mammals and other complex organisms can transcribe an abundance of long non-coding RNAs(lncRNAs)that fulfill a wide variety of regulatory roles in many biological processes.These roles,including as scaffolds and as guides for protein-coding genes,mainly depend on the structure and expression level of lncRNAs.In this review,we focus on the current methods for analyzing lncRNA structure and expression,which is basic but necessary information for in-depth,large-scale analysis of lncRNA functions.
基金supported by the National Natural Science Foundation of China (Grant Nos. 30970623 and 91229120)International Science and Technology Cooperation Projects (Grant Nos. 2010DFA31840 and 2010DFB33720)+1 种基金Program for New Century Excellent Talents in University (Grant No. NCET-11-0288)the Beijing Natural Science Foundation (Grant No. 5112030)
文摘Translational medicine is a new discipline aiming to elimi- nate the barrier between preclinical and clinical medicine . It converts promising laboratory discoveries into clini-cal applications and elucidates clinical questions with the use of benchwork, aiming to facilitate prediction, preven-tion, diagnosis, and treatment of diseases . The Director of US National Institutes of Health （NIH）, Dr.
文摘Estimating taxonomic content constitutes a key problem in metagenomic sequencing data analysis.However,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available software.Here,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data analysis.Results show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin nodes.In comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat node.CloudLCA can be run on one multiprocessor node or a cluster.It is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following analysis.Moreover,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.
基金supported by the National High Technology Research and Development Program of China(2015AA020108)the National Key Research and Development Program of China(2016YFC0902100)+2 种基金the China Human Proteome Project(2014DFB30010,2014DFB30030)the National Science Foundation of China(31671377,31401133,31771460,91629103)the Program of Introducing Talents of Discipline to Universities of China(B14019)
文摘RNA sequencing(RNA-seq) has greatly facilitated the exploring of transcriptome landscape for diverse organisms.However,transcriptome reconstruction is still challenging due to various limitations of current tools and sequencing technologies.Here,we introduce an efficient tool,QuaPra(Quadratic Programming combined with Apriori),for accurate transcriptome assembly and quantification.QuaPra could detect at least 26.5% more low abundance(0.1–1 FPKM) transcripts with over 2.7% increase of sensitivity and precision on simulated data compared to other currently popular tools.Moreover,around one-quarter more known transcripts were correctly assembled by QuaPra than other assemblers on real sequencing data.QuaPra is freely available at http://www.megabionet.org/QuaPra/.
基金supported in part by the National Natural Science Foundation of China (31000564,31071137,91229120)the Beijing Natural Science Foundation (5122029)the Knowledge Innovation Program of the Chinese Academy of Sciences (KSCX2-EW-R-01)
文摘Eukaryotic mRNAs consist of two forms of transcripts:poly(A)+ and poly(A),based on the presence or absence of poly(A) tails at the 3 end.Poly(A)+ mRNAs are mainly protein coding mRNAs,whereas the functions of poly(A) mRNA are largely unknown.Previous studies have shown that a significant proportion of gene transcripts are poly(A) or bimorphic(containing both poly(A)+ and poly(A) transcripts).We compared the expression levels of poly(A) and poly(A)+ RNA mRNAs in normal and cancer cell lines.We also investigated the potential functions of these RNA transcripts using an integrative workflow to explore poly(A)+ and poly(A) transcriptome sequences between a normal human mammary gland cell line(HMEC) and a breast cancer cell line(MCF-7),as well as between a normal human lung cell line(NHLF) and a lung cancer cell line(A549).The data showed that normal and cancer cell lines differentially express these two forms of mRNA.Gene ontology(GO) annotation analyses hinted at the functions of these two groups of transcripts and grouped the differentially expressed genes according to the form of their transcript.The data showed that cell cycle-,apoptosis-,and cell death-related functions corresponded to most of the differentially expressed genes in these two forms of transcripts,which were also associated with the cancers.Furthermore,translational elongation and translation functions were also found for the poly(A) protein-coding genes in cancer cell lines.We demonstrate that poly(A) transcripts play an important role in cancer development.
基金Hibah PUPT BOPTN Ditjen Dikti 2015 No.0528/UN2.R12/HKP.05.00/2015,for supporting this research
文摘Highly Pathogenic Avian Influenza（HPAI） H5N1 has attracted much attention as a potential pandemic virus in humans, which makes death inevitable in humans. Neuraminidase（NA） has an important role in viral replication. Thus, it is an attractive target when designing anti-influenza virus drug. However, evolving viruses cause some anti-viral drugs to be ineffective, as they show resistance to them. Selection of peptides as drug candidates is important for the peptide-receptor activity and good selectivity. Cyclic bonds in the peptide ligand design aim to improve the stability of the system and remove the obstacles in drug metabolism. The design is based on the polarity of the ligand and amino acid residues in the active site of NA. The results are 4200 cyclic pentapeptides as potential lead compounds. Docking simulations were conducted using MOE 2008.10 and were screened based on the value of the binding energy（？Gbinding）. ADME-Tox prediction assay was conducted on the selected ligands.Intra- and inter-molecular interactions, as well as changes in the form of bonds, were tested by molecular dynamics simulations at temperatures of 310 K and 312 K. The results of the docking simulations and toxicity prediction assay show that there are two ligands that have a residual interaction with the target protein： CLDRC and CIWRC. These two ligands have ？Gbindingvalues of –40.5854 and –39.9721 kcal/mol（1 kcal/mol = 4.18 k J/mol）. These ligands are prone to be mutagenic and carcinogenic, and they have a good oral bioavailability. The results show that the molecular dynamics of both ligand CLDRC and CIWRC are more feasible at the temperature of 312 K. At the end,both CIWRC and CLDRC ligands can be used as the drug candidates against H5N1 virus.
