Publications by authors named "Dong-Qing Wei"

217 Publications

Insights Into Mutations Induced Conformational Changes and Rearrangement of Fe Ion in Gene of to Decipher the Mechanism of Resistance to Pyrazinamide.

Front Mol Biosci 2021 20;8:633365. Epub 2021 May 20.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

Pyrazinamide (PZA) is the first-line drug commonly used in treating infections and reduces treatment time by 33%. This prodrug is activated and converted to an active form, Pyrazinoic acid (POA), by Pyrazinamidase (PZase) enzyme. resistance to PZA is the outcome of mutations frequently reported in , , and genes. Among the mentioned genes, mutations contribute to 72-99% of the total resistance to PZA. Thus, considering the vital importance of this gene in PZA resistance, its frequent mutations (D49N, Y64S, W68G, and F94A) were investigated through in-depth computational techniques to put conclusions that might be useful for new scaffolds design or structure optimization to improve the efficacy of the available drugs. Mutants and wild type PZase were used in extensive and long-run molecular dynamics simulations in triplicate to disclose the resistance mechanism induced by the above-mentioned point mutations. Our analysis suggests that these mutations alter the internal dynamics of PZase and hinder the correct orientation of PZA to the enzyme. Consequently, the PZA has a low binding energy score with the mutants compared with the wild type PZase. These mutations were also reported to affect the binding of Fe ion and its coordinated residues. Conformational dynamics also revealed that β-strand two is flipped, which is significant in Fe binding. MM-GBSA analysis confirmed that these mutations significantly decreased the binding of PZA. In conclusion, these mutations cause conformation alterations and deformities that lead to PZA resistance.
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http://dx.doi.org/10.3389/fmolb.2021.633365DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174790PMC
May 2021

Identifying potential drug targets and candidate drugs for COVID-19: biological networks and structural modeling approaches.

F1000Res 2021;10:127. Epub 2021 Feb 18.

Centre of Interdisciplinary Science-Computational Life Sciences, College of Chemistry and Chemical Engineering,, Henan University of Technology, Zhengzhou, Henan, 450001, China.

Coronavirus (CoV) is an emerging human pathogen causing severe acute respiratory syndrome (SARS) around the world. Earlier identification of biomarkers for SARS can facilitate detection and reduce the mortality rate of the disease. Thus, by integrated network analysis and structural modeling approach, we aimed to explore the potential drug targets and the candidate drugs for coronavirus medicated SARS. Differentially expression (DE) analysis of CoV infected host genes (HGs) expression profiles was conducted by using the Limma. Highly integrated DE-CoV-HGs were selected to construct the protein-protein interaction (PPI) network.  Using the Walktrap algorithm highly interconnected modules include module 1 (202 nodes); module 2 (126 nodes) and module 3 (121 nodes) modules were retrieved from the PPI network. MYC, HDAC9, NCOA3, CEBPB, VEGFA, BCL3, SMAD3, SMURF1, KLHL12, CBL, ERBB4, and CRKL were identified as potential drug targets (PDTs), which are highly expressed in the human respiratory system after CoV infection. Functional terms growth factor receptor binding, c-type lectin receptor signaling, interleukin-1 mediated signaling, TAP dependent antigen processing and presentation of peptide antigen via MHC class I, stimulatory T cell receptor signaling, and innate immune response signaling pathways, signal transduction and cytokine immune signaling pathways were enriched in the modules. Protein-protein docking results demonstrated the strong binding affinity (-314.57 kcal/mol) of the ERBB4-3cLpro complex which was selected as a drug target. In addition, molecular dynamics simulations indicated the structural stability and flexibility of the ERBB4-3cLpro complex. Further, Wortmannin was proposed as a candidate drug to ERBB4 to control SARS-CoV-2 pathogenesis through inhibit receptor tyrosine kinase-dependent macropinocytosis, MAPK signaling, and NF-kb singling pathways that regulate host cell entry, replication, and modulation of the host immune system. We conclude that CoV drug target "ERBB4" and candidate drug "Wortmannin" provide insights on the possible personalized therapeutics for emerging COVID-19.
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http://dx.doi.org/10.12688/f1000research.50850.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080978.3PMC
May 2021

Are the Allergic Reactions of COVID-19 Vaccines Caused by mRNA Constructs or Nanocarriers? Immunological Insights.

Interdiscip Sci 2021 Jun 22;13(2):344-347. Epub 2021 May 22.

The State Key Laboratory of Microbial Metabolism, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang, Shanghai, 200240, China.

The Food and Drug Administration (FDA) has recently authorized the two messenger RNA (mRNA) vaccines BNT162b2 and mRNA-1273 for emergency use against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the COVID-19 coronavirus disease. BNT162b2 and mRNA-1273 vaccines were developed by Pfizer-BioNTech and Moderna, respectively, in 2020. The United Kingdom, Bahrain, Canada, Mexico, United States, Singapore, Oman, Saudi Arabia, Kuwait, and European Union began their vaccination programs with the BNT162b2 vaccine, while the United States and Canada also started the mRNA-1273 vaccination program in mid December 2020. On 28th December 2020, studies reported severe allergic reactions in people who received the BNT162b2, and few people who received the mRNA-1273 vaccine. Authors of the letter thus attempt to explore possible causes of anaphylaxis following COVID-19 vaccination.
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http://dx.doi.org/10.1007/s12539-021-00438-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140554PMC
June 2021

MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph.

Brief Bioinform 2021 May 3. Epub 2021 May 3.

State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, P.R. China.

Accurate identification of the miRNA-disease associations (MDAs) helps to understand the etiology and mechanisms of various diseases. However, the experimental methods are costly and time-consuming. Thus, it is urgent to develop computational methods towards the prediction of MDAs. Based on the graph theory, the MDA prediction is regarded as a node classification task in the present study. To solve this task, we propose a novel method MDA-GCNFTG, which predicts MDAs based on Graph Convolutional Networks (GCNs) via graph sampling through the Feature and Topology Graph to improve the training efficiency and accuracy. This method models both the potential connections of feature space and the structural relationships of MDA data. The nodes of the graphs are represented by the disease semantic similarity, miRNA functional similarity and Gaussian interaction profile kernel similarity. Moreover, we considered six tasks simultaneously on the MDA prediction problem at the first time, which ensure that under both balanced and unbalanced sample distribution, MDA-GCNFTG can predict not only new MDAs but also new diseases without known related miRNAs and new miRNAs without known related diseases. The results of 5-fold cross-validation show that the MDA-GCNFTG method has achieved satisfactory performance on all six tasks and is significantly superior to the classic machine learning methods and the state-of-the-art MDA prediction methods. Moreover, the effectiveness of GCNs via the graph sampling strategy and the feature and topology graph in MDA-GCNFTG has also been demonstrated. More importantly, case studies for two diseases and three miRNAs are conducted and achieved satisfactory performance.
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http://dx.doi.org/10.1093/bib/bbab165DOI Listing
May 2021

Computational Modeling of Immune Response Triggering Immunogenic Peptide Vaccine Against the Human Papillomaviruses to Induce Immunity Against Cervical Cancer.

Viral Immunol 2021 May 10. Epub 2021 May 10.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China.

Papillomaviruses are placed within the family Papillomaviride, and the members of this family have a double-stranded circular DNA genome. Every year, ∼30% of cancers are reported to be human papillomavirus (HPV) related, which represents 63,000 cancers of all infectious agent-induced cancers. HPV16 and HPV18 are reported to be associated with 70% of cervical cancers. The quest for an effective drug or vaccine candidate still continues. In this study, we aim to design B cell and T cell epitope-based vaccine using the two structural major capsid protein L1 and L2 as well as other three important proteins (E1, E2, and E6) against HPV strain 16 (HPV16). We used a computational pipeline to design a multiepitope subunit vaccine and tested its efficacy using computational modeling approaches. Our analysis revealed that the multiepitope subunit vaccine possesses antigenic properties, and using cloning method revealed proper expression and downstream processing of the vaccine construct. Besides this, we also performed immune simulation to check the immune response upon the injection. Our results strongly suggest that this vaccine candidate should be tested immediately for the immune response against the cervical cancer-causing agent. The safety, efficacy, expression, and immune response profiling makes it the first choice for experimental and setup.
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http://dx.doi.org/10.1089/vim.2020.0306DOI Listing
May 2021

Genome-wide screening of vaccine targets prioritization and reverse vaccinology aided design of peptides vaccine to enforce humoral immune response against Campylobacter jejuni.

Comput Biol Med 2021 Jun 18;133:104412. Epub 2021 Apr 18.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, PR China; State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, PR China. Electronic address:

Campylobacter jejuni, gram-negative bacteria, is an infectious agent of foodborne disease-causing bloody diarrhea, abdominal pain, fever, Guillain-Barré syndrome (GBS) and Miller Fisher syndrome in humans. Campylobacter spp. with multidrug resistance to fluoroquinolones, tetracycline, and erythromycin are reported. Hence, an effective vaccine candidate would provide long-term immunity against C. jejuni infections. Thus, we used a subtractive proteomics pipeline to prioritize essential proteins, which impart a critical role in virulence, replication and survival. Five proteins, i.e. Single-stranded DNA-binding protein, UPF0324 membrane protein Cj0999c, DNA translocase FtsK, 50S ribosomal protein L22, and 50S ribosomal protein L1 were identified as virulent proteins and selected for vaccine designing. We reported that the multi-epitopes subunit vaccine based on CTL, HTL and B-cell epitopes combination possess strong antigenic properties and associates no allergenic reaction. Further investigation revealed that the vaccine interacts with the immune receptor (TLR-4) and triggered the release of primary and secondary immune factors. Moreover, the CAI and GC contents obtained through codon optimization were reported to be 0.93 and 53% that confirmed a high expression in the selected vector. The vaccine designed in this study needs further scientific consensus and will aid in managing C. jejuni infections.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104412DOI Listing
June 2021

Immunogenomics guided design of immunomodulatory multi-epitope subunit vaccine against the SARS-CoV-2 new variants, and its validation through in silico cloning and immune simulation.

Comput Biol Med 2021 06 24;133:104420. Epub 2021 Apr 24.

Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, PR China; State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, PR China. Electronic address:

Reports of the novel and more contagious strains of SARS-CoV-2 originating in different countries have further aggravated the pandemic situation. The recent substitutions in spike protein may be critical for the virus to evade the host's immune system and therapeutics that have already been developed. Thus, this study has employed an immunoinformatics pipeline to target the spike protein of this novel strain to construct an immunogenic epitope (CTL, HTL, and B cell) vaccine against the new variant. Our investigation revealed that 12 different epitopes imparted a critical role in immune response induction. This was validated by an exploration of physiochemical properties and experimental feasibility. In silico and host immune simulation confirmed the expression and induction of both primary and secondary immune factors such as IL, cytokines, and antibodies. The current study warrants further lab experiments to demonstrate its efficacy and safety.
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http://dx.doi.org/10.1016/j.compbiomed.2021.104420DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064902PMC
June 2021

BC-TFdb: a database of transcription factor drivers in breast cancer.

Database (Oxford) 2021 Apr;2021

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, P.R. China.

Transcription factors (TFs) are DNA-binding proteins, which regulate many essential biological functions. In several cancer types, TF function is altered by various direct mechanisms, including gene amplification or deletion, point mutations, chromosomal translocations, expression alterations, as well as indirectly by non-coding DNA mutations influencing the binding of the TF. TFs are also actively involved in breast cancer (BC) initiation and progression. Herein, we have developed an open-access database, BC-TFdb (Breast Cancer Transcription Factors database), of curated, non-redundant TF involved in BC. The database provides BC driver TFs related information including genomic sequences, proteomic sequences, structural data, pathway information, mutations information, DNA binding residues, survival and therapeutic resources. The database will be a useful platform for researchers to obtain BC-related TF-specific information. High-quality datasets are downloadable for users to evaluate and develop computational methods for drug designing against BC. Database URL: https://www.dqweilab-sjtu.com/index.php.
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http://dx.doi.org/10.1093/database/baab018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060005PMC
April 2021

Insight into the drug resistance whole genome of Mycobacterium tuberculosis isolates from Khyber Pakhtunkhwa, Pakistan.

Infect Genet Evol 2021 Aug 20;92:104861. Epub 2021 Apr 20.

State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, and Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nanshan District, Shenzhen, Guangdong 518055, China. Electronic address:

Whole genome sequencing (WGS) is one of the most reliable methods for detection of drug resistance, genetic diversity in other virulence factor and also evolutionary dynamics of Mycobacterium tuberculosis complex (MTBC). First-line anti-tuberculosis drugs are the major weapons against Mycobacterium tuberculosis (MTB). However, the emergence of drug resistance remained a major obstacle towards global tuberculosis (TB) control program 2030, especially in high burden countries including Pakistan. To overcome the resistance and design potent drugs, genomic variations in drugs targets as well as in the virulence and evolutionary factors might be useful for better understanding and designing potential inhibitors. Here we aimed to find genomic variations in the first-line drugs targets, along with other virulence and evolutionary factors among the circulating isolates in Khyber Pakhtunkhwa, Pakistan. Samples were collected and drug susceptibility testing (DST) was performed as per WHO standard. The resistance samples were subjected to WGS. Among the five whole genome sequences, three samples (NCBI BioProject Accession: PRJNA629298, PRJNA629388) harbored 1997, 1162, and 2053 mutations. Some novel mutations have been detected in drugs targets. Similarly, numerous novel variants have also been detected in virulency and evolutionary factors, PE, PPE, and secretory system of MTB isolates. Exploring the genomic variations among the circulating isolates in geographical specific locations might be useful for future drug designing. To the best of our knowledge, this is the first study that provides useful data regarding the insight genomic variations in virulency, evolutionary factors including ESX and PE/PPE as well as drug targets, for better understanding and management of TB in a WHO declared high burden country.
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http://dx.doi.org/10.1016/j.meegid.2021.104861DOI Listing
August 2021

Human Cathelicidin Inhibits SARS-CoV-2 Infection: Killing Two Birds with One Stone.

ACS Infect Dis 2021 06 14;7(6):1545-1554. Epub 2021 Apr 14.

State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Combined Injury of PLA, Chongqing Engineering Research Center for Nanomedicine, College of Preventive Medicine, Third Military Medical University, Chongqing 400038, China.

SARS-CoV-2 infection begins with the association of its spike 1 (S1) protein with host angiotensin-converting enzyme-2 (ACE2). Targeting the interaction between S1 and ACE2 is a practical strategy against SARS-CoV-2 infection. Herein, we show encouraging results indicating that human cathelicidin LL37 can simultaneously block viral S1 and cloak ACE2. LL37 binds to the receptor-binding domain (RBD) of S1 with high affinity (11.2 nM) and decreases subsequent recruitment of ACE2. Owing to the RBD blockade, LL37 inhibits SARS-CoV-2 S pseudovirion infection, with a half-maximal inhibitory concentration of 4.74 μg/mL. Interestingly, LL37 also binds to ACE2 with an affinity of 25.5 nM and cloaks the ligand-binding domain (LBD), thereby decreasing S1 adherence and protecting cells against pseudovirion infection . Intranasal administration of LL37 to C57 mice infected with adenovirus expressing human ACE2 either before or after pseudovirion invasion decreased lung infection. The study identified a versatile antimicrobial peptide in humans as an inhibitor of SARS-CoV-2 attachment using dual mechanisms, thus providing a potential candidate for coronavirus disease 2019 (COVID-19) prevention and treatment.
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http://dx.doi.org/10.1021/acsinfecdis.1c00096DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056948PMC
June 2021

Potential Cancer- and Alzheimer's Disease-Targeting Phosphodiesterase Inhibitors from : Insights from and Consensus Virtual Screening.

ACS Omega 2021 Mar 16;6(12):8403-8417. Epub 2021 Mar 16.

Laboratory of Organic Reactivity, Discovery & Synthesis (LORDS), Research Center for Natural & Applied Sciences, University of Santo Tomas, España Blvd., 1015 Manila, Philippines.

Inhibition of the major cyclic adenosine monophosphate-metabolizing enzyme PDE4 has shown potential for the discovery of drugs for cancer, inflammation, and neurodegenerative disorders such as Alzheimer's disease. As a springboard to explore new anti-cancer and anti-Alzheimer's chemical prototypes from rare Annonaceae species, the present study evaluated anti-PDE4B along with antiproliferative and anti-cholinesterase activities of the extracts of the Philippine endemic species using assays and framed the resulting biological significance through computational binding and reactivity-based experiments. Thus, the PDE4 B2B-inhibiting dichloromethane sub-extract (UaD) of elicited antiproliferative activity against chronic myelogenous leukemia (K-562) and cytostatic effects against human cervical cancer (HeLa). The extract also profoundly inhibited acetylcholinesterase (AChE), an enzyme involved in the progression of neurodegenerative diseases. Chemical profiling analysis of the bioactive extract identified 18 putative secondary metabolites. Molecular docking and molecular dynamics simulations showed strong free energy binding mechanisms and dynamic stability at 50-ns simulations in the catalytic domains of PDE4 B2B, ubiquitin-specific peptidase 14, and Kelch-like ECH-associated protein 1 (KEAP-1 Kelch domain) for the benzylated dihydroflavone dichamanetin (), and of an AChE and KEAP-1 BTB domain for 3-(3,4-dihydroxybenzyl)-3',4',6-trihydroxy-2,4-dimethoxychalcone () and grandifloracin (), respectively. Density functional theory calculations to demonstrate Michael addition reaction of the most electrophilic metabolite and kinetically stable grandifloracin () with Cys151 of the KEAP-1 BTB domain illustrated favorable formation of a β-addition adduct. The top-ranked compounds also conferred favorable pharmacokinetic properties.
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http://dx.doi.org/10.1021/acsomega.1c00137DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8015132PMC
March 2021

Antibacterial and COX-2 Inhibitory Tetrahydrobisbenzylisoquinoline Alkaloids from the Philippine Medicinal Plant .

Plants (Basel) 2021 Mar 1;10(3). Epub 2021 Mar 1.

Laboratory for Organic Reactivity, Discovery and Synthesis (LORDS), Research Center for the Natural and Applied Sciences, University of Santo Tomas, España Blvd., Manila 1015, Philippines.

(Roxb. ex G.Don) J.Sinclair (previously known as (Presl) Merr) is a Philippine medicinal plant occurring as evergreen shrub in the lowland forests of Luzon islands. It is used traditionally by Filipinos to treat bacterial conjunctivitis, ulcer and wound infections. Based on previous investigations where cyclooxygenase-2 (COX-2) functions as immune-linked factor in infectious sensitivities to bacterial pathogens by triggering pro-inflammatory immune-associated reactions, we investigated the antimicrobial and COX inhibitory activities of the extracts and tetrahydrobisbenzylisoquinoline alkaloids of in vitro and in silico to validate its ethnomedicinal uses. Thus, the dichloromethane-methanol (DCM-MeOH) crude extract and alkaloid extracts exhibiting antibacterial activities against drug-resistant bacterial strains such as methicillin-resistance (MRSA), vancomycin-resistant (VRE), + CRE and + MBL afforded (+)-tetrandrine () and (+)-limacusine () as the major biologically active tetrahydrobisbenzylisoquinoline alkaloidal constituents after purification. Both tetrahydrobisbenzylisoquinoline alkaloids and showed broad spectrum antibacterial activity with strongest inhibition against the Gram-negative bacteria MβL- + CRE. Interestingly, the alkaloid limacusine () showed selective inhibition against ovine COX-2 in vitro. These results were ascertained by molecular docking and molecular dynamics simulation experiments where alkaloid showed strong affinity in the catalytic sites of Gram-negative bacterial enzymes elastase and KPC-2 carbapenemase (enzymes involved in infectivity mechanisms), and of ovine COX-2. Overall, our study provides credence on the ethnomedicinal use of the Philippine medicinal plant as traditional plant-based adjuvant to treat bacterial conjunctivitis and other related infections. The antibacterial activities and selective COX-2 inhibition observed for limacusine () point to its role as the biologically active constituent of A limited number of drugs with COX-2 inhibitory properties like celecoxib also confer antibacterial activity. Thus, tetrahydrobisbenzyl alkaloids, especially , are promising pharmaceutical inspirations for developing treatments of bacterial/inflammation-related infections.
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http://dx.doi.org/10.3390/plants10030462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999448PMC
March 2021

Higher infectivity of the SARS-CoV-2 new variants is associated with K417N/T, E484K, and N501Y mutants: An insight from structural data.

J Cell Physiol 2021 Mar 23. Epub 2021 Mar 23.

Department of Bioinformatics and Biological Statistics, Shanghai Jiao Tong University, Shanghai, P.R. China.

The evolution of the SARS-CoV-2 new variants reported to be 70% more contagious than the earlier one is now spreading fast worldwide. There is an instant need to discover how the new variants interact with the host receptor (ACE2). Among the reported mutations in the Spike glycoprotein of the new variants, three are specific to the receptor-binding domain (RBD) and required insightful scrutiny for new therapeutic options. These structural evolutions in the RBD domain may impart a critical role to the unique pathogenicity of the SARS-CoV-2 new variants. Herein, using structural and biophysical approaches, we explored that the specific mutations in the UK (N501Y), South African (K417N-E484K-N501Y), Brazilian (K417T-E484K-N501Y), and hypothetical (N501Y-E484K) variants alter the binding affinity, create new inter-protein contacts and changes the internal structural dynamics thereby increases the binding and eventually the infectivity. Our investigation highlighted that the South African (K417N-E484K-N501Y), Brazilian (K417T-E484K-N501Y) variants are more lethal than the UK variant (N501Y). The behavior of the wild type and N501Y is comparable. Free energy calculations further confirmed that increased binding of the spike RBD to the ACE2 is mainly due to the electrostatic contribution. Further, we find that the unusual virulence of this virus is potentially the consequence of Darwinian selection-driven epistasis in protein evolution. The triple mutants (South African and Brazilian) may pose a serious threat to the efficacy of the already developed vaccine. Our analysis would help to understand the binding and structural dynamics of the new mutations in the RBD domain of the Spike protein and demand further investigation in in vitro and in vivo models to design potential therapeutics against the new variants.
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http://dx.doi.org/10.1002/jcp.30367DOI Listing
March 2021

SARS-CoV-2 Genome from the Khyber Pakhtunkhwa Province of Pakistan.

ACS Omega 2021 Mar 3;6(10):6588-6599. Epub 2021 Mar 3.

State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, P. R. China.

Among viral outbreaks, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the deadliest ones, and it has triggered the global COVID-19 pandemic. In Pakistan, until 5th September 2020, a total of 6342 deaths have been reported, of which 1255 were from the Khyber Pakhtunkhwa (KPK) province. To understand the disease progression and control and also to produce vaccines and therapeutic efforts, whole genome sequence analysis is important. In the current investigation, we sequenced a single sample of SARS-CoV-2 genomes (accession no. MT879619) from a male suspect from Peshawar, the KPK capital city, during the first wave of infection. The local SARS-CoV-2 strain shows some unique characteristics compared to neighboring Iranian and Chinese isolates in phylogenetic tree and mutations. The circulating strains of SARS-CoV-2 represent an intermediate evolution from China and Iran. Furthermore, eight complete whole genome sequences, including the current Pakistani isolates which have been submitted to Global Initiative on Sharing All Influenza Data (GSAID), were also investigated for specific mutations and characters. Some novel mutations [NSP2 (D268del), NSP5 (N228K), and NS3 (F105S)] and specific characters have been detected in the coding regions, which may affect viral transmission, epidemiology, and disease severity. The computational modeling revealed that a majority of these mutations may have a stabilizing effect on the viral protein structure. In conclusion, the genome sequencing of local strains is important for better understanding the pathogenicity, immunogenicity, and epidemiology of causative agents.
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http://dx.doi.org/10.1021/acsomega.0c05163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944396PMC
March 2021

An approach to identify the potential hot spots in SARS-CoV-2 spike RBD to block the interaction with ACE2 receptor.

J Biomol Struct Dyn 2021 Mar 9:1-16. Epub 2021 Mar 9.

State Key Laboratory of Subtropical Silviculture, Department of Traditional Chinese Medicine, Zhejiang A&F University, Hangzhou, China.

A novel acute viral pneumonia induced by SARS-CoV-2 exploded at the end of 2019, causing a severe medical and economic crisis. For developing specific pharmacotherapy against SARS-CoV-2, an virtual screening was developed for the available in-house molecules. The conserved domain analysis was performed to identify the highly conserved and exposed amino acid regions in the SARS-CoV-2-S RBD sites. The Protein-Protein interaction analyses demonstrated the higher affinity between the SARS-CoV-2-S and ACE2 due to varieties of significant interactions between them. The computational alanine scanning mutation study has recognized the highly stabilized amino acids in the SARS-CoV-2-S RBD/ACE2 complex. The cumulative sequence investigations have inferred that Lys417, Phe486, Asn487, Tyr489, and Gln493 are perhaps the iconic target amino acids to develop a drug molecule or vaccine against SARS-CoV-2 infection. Most of the selected compounds include luteolin, zhebeirine, 3-dehydroverticine, embelin, andrographolide, ophiopogonin D, crocin-1, sprengerinin A, B, C, peimine, etc. were exhibited distinguish drug actions through the strong hydrogen bonding with the hot spots of the RBD. Besides, the 100 ns molecular dynamics simulation and free energy binding analysis showed the significant efficacy of luteolin to inhibit the infection of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1897682DOI Listing
March 2021

Pan-Cancer Analysis and Drug Formulation for GPR139 and GPR142.

Front Pharmacol 2020 19;11:521245. Epub 2021 Feb 19.

School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

GPR (G protein receptor) 139 and 142 are novel foundling GPCRs (G protein-coupled receptors) in the class "A" of the GPCRs family and are suitable targets for various biological conditions. To engage these targets, validated pharmacophores and 3D QSAR (Quantitative structure-activity relationship) models are widely used because of their direct fingerprinting capability of the target and an overall accuracy. The current work initially analyzes GPR139 and GPR142 for its genomic alteration via tumor samples. Next to that, the pharmacophore is developed to scan the 3D database for such compounds that can lead to potential agonists. As a result, several compounds have been considered, showing satisfactory performance and a strong association with the target. Additionally, it is gripping to know that the obtained compounds were observed to be responsible for triggering pan-cancer. This suggests the possible role of novel GPR139 and GPR142 as the substances for initiating a physiological response to handle the condition incurred as a result of cancer.
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http://dx.doi.org/10.3389/fphar.2020.521245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933564PMC
February 2021

Characterization of Piezoelectric Properties of Ag-NPs Doped PVDF Nanocomposite Fibres Membrane Prepared by Near Field Electrospinning.

Comb Chem High Throughput Screen 2021 03 1. Epub 2021 Mar 1.

Institute of Precision Medicine, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan

Background: In this study, Near-field electrospinning (NFES) technique used with a cylindrical collector to fabricate a large area permanent piezoelectric micro and nanofibers by a prepared solution. NFES requires a small electric field to fabricate fibers.

Objective: The objective of this paper to investigate silver nanoparticle (Ag-NP)/ Polyvinylidene fluoride (PVDF) composite as the best piezoelectric material with improved properties to produced tremendously flexible and sensitive piezoelectric material with pertinent conductance.

Method: In this paper we used controllable electrospinning technique based on Near-field electrospinning (NFES)The process parameter for Ag-NP/PVDF composite electrospun fiber based on pure PVDF fiber. A PVDF solution concentration of 18 wt.% and 6 wt.% silver nitrate which is relative to the weight of PVDF wt.% with 1058 µS conductivity fibers have been directly written on a rotating cylindrical collector for aligned fiber PVDF/Ag-NP fibers are patterned on fabricated copper (Cu) interdigitated electrodes were implemented on a thin flexible polyethylene terephthalate (PET) substrate and Polydimethylsiloxane (PDMS) used as a package to enhance the durability of the PVDF/ Ag-NP device.

Results: A notable effect on the piezoelectric response has been observed after Ag-NP addition confirmed by XRD characterization and tapping test of Ag-NP/PVDF composite fiber. The morphology of the PVDF/Ag-NP fibers and measure diameter by scanning electron microscopy (SEM) and Optical micrograph (OM), of fiber. Finally, The result shows that diameter of PVDF/Ag-NP fibers up to ~7 μm. The. High diffraction peak at 2θ = 20.5˚ was investigated by X-ray diffraction (XRD) in the piezoelectric crystal β-phase structure. While the electromechanical conversion is found enhance from ~0.1 V to ~1 V by the addition of silver nanoparticles (Ag-NPs) in the PVDF solution.

Conclusion: In conclusion, we can say that confirmed and validated the addition of Ag-NP in PVDF could enhance the piezoelectric property by using NFES technique with improved crystalline phase content can be useful for a wide range of power and sensing applications like biomedical devices and energy harvesting, among others.
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http://dx.doi.org/10.2174/1386207324666210302100728DOI Listing
March 2021

Computational Method for Classification of Avian Influenza A Virus Using DNA Sequence Information and Physicochemical Properties.

Front Genet 2021 28;12:599321. Epub 2021 Jan 28.

State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

Accurate and fast characterization of the subtype sequences of Avian influenza A virus (AIAV) hemagglutinin (HA) and neuraminidase (NA) depends on expanding diagnostic services and is embedded in molecular epidemiological studies. A new approach for classifying the AIAV sequences of the HA and NA genes into subtypes using DNA sequence data and physicochemical properties is proposed. This method simply requires unaligned, full-length, or partial sequences of HA or NA DNA as input. It allows for quick and highly accurate assignments of HA sequences to subtypes H1-H16 and NA sequences to subtypes N1-N9. For feature extraction, k-gram, discrete wavelet transformation, and multivariate mutual information were used, and different classifiers were trained for prediction. Four different classifiers, Naïve Bayes, Support Vector Machine (SVM), K nearest neighbor (KNN), and Decision Tree, were compared using our feature selection method. This comparison is based on the 30% dataset separated from the original dataset for testing purposes. Among the four classifiers, Decision Tree was the best, and Precision, Recall, F1 score, and Accuracy were 0.9514, 0.9535, 0.9524, and 0.9571, respectively. Decision Tree had considerable improvements over the other three classifiers using our method. Results show that the proposed feature selection method, when trained with a Decision Tree classifier, gives the best results for accurate prediction of the AIAV subtype.
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http://dx.doi.org/10.3389/fgene.2021.599321DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877484PMC
January 2021

Targeting the N-terminal domain of the RNA-binding protein of the SARS-CoV-2 with high affinity natural compounds to abrogate the protein-RNA interaction: a molecular dynamics study.

J Biomol Struct Dyn 2021 Feb 8:1-9. Epub 2021 Feb 8.

State Key Lab of Microbial Metabolism, Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

The emergence of COVID-19 took the world by shock in December 2019, starting from Wuhan, China and swiftly spreading across the globe. The number of COVID-19 cases continues to rise which is a global burden on the health care system worldwide. Efforts are continuing to come up with a solution either to develop a small molecular inhibitor or vaccine, but still no success. In the fight against SARS-CoV-2, targeting a different protein of the SARS-CoV-2 is the need of the hour to impede and relinquish the current pandemic. Therefore, in this study, computational modelling and simulation approaches are used to target the N-terminal domain of the phosphor-nucleoprotein (RNA binding protein), which is primarily responsible for binding and packing the viral genome to get ribonucleoprotein complex (RNP). Our multi-step drug screening approach shortlisted potential drugs. These top hits were confirmed by re-docking which revealed that the interacting molecules block the key residues i.e. Thr57, His59, Ser105, Arg107, and Arg177 and thus ultimately block the NTD from RNA recognition. Furthermore, the activity of the top four hits was also confirmed by using molecular dynamics simulation and free energy calculation. Our analysis suggests that these top hits possess strong inhibitory properties and should be tested experimentally. In conclusion, we hope these top hits would abrogate the binding of RNA and the NTD of the SARS-CoV-2, which might be helpful to combat COVID-19.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1882337DOI Listing
February 2021

Globally ncRNAs Expression Profiling of TNBC and Screening of Functional lncRNA.

Front Bioeng Biotechnol 2020 21;8:523127. Epub 2021 Jan 21.

Wuxi School of Medicine, Jiangnan University, Wuxi, China.

One of the most well-known cancer subtypes worldwide is triple-negative breast cancer (TNBC) which has reduced prediction due to its antagonistic biotic actions and target's deficiency for the treatment. The current work aims to discover the countenance outlines and possible roles of lncRNAs in the TNBC via computational approaches. Long non-coding RNAs (lncRNAs) exert profound biological functions and are widely applied as prognostic features in cancer. We aim to identify a prognostic lncRNA signature for the TNBC. First, samples were filtered out with inadequate tumor purity and retrieved the lncRNA expression data stored in the TANRIC catalog. TNBC sufferers were divided into two prognostic classes which were dependent on their survival time (shorter or longer than 3 years). Random forest was utilized to select lncRNA features based on the lncRNAs differential expression between shorter and longer groups. The Stochastic gradient boosting method was used to construct the predictive model. As a whole, 353 lncRNAs were differentially transcribed amongst the shorter and longer groups. Using the recursive feature elimination, two lncRNAs were further selected. Trained by stochastic gradient boosting, we reached the highest accuracy of 69.69% and area under the curve of 0.6475. Our findings showed that the two-lncRNA signs can be proved as potential biomarkers for the prognostic grouping of TNBC's sufferers. Many lncRNAs remained dysregulated in TNBC, while most of them are likely play a role in cancer biology. Some of these lncRNAs were linked to TNBC's prediction, which makes them likely to be promising biomarkers.
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http://dx.doi.org/10.3389/fbioe.2020.523127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7860147PMC
January 2021

Proteome wide vaccine targets prioritization and designing of antigenic vaccine candidate to trigger the host immune response against the Mycoplasma genitalium infection.

Microb Pathog 2021 Mar 29;152:104771. Epub 2021 Jan 29.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, PR China; State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Centre on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200030, PR China; Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nashan District, Shenzhen, Guangdong, 518055, PR China. Electronic address:

Mycoplasma genitalium is a small size, sexually transmitted bacterial pathogen that causes urethritis in males and cervicitis in females. Being resistant to antibiotics, difficulty in diagnosis, treatment, and control of this cosmopolitan infection, vaccination is the alternating method for its effective management. Herein, this study was conducted to computationally design a multi-epitope vaccine to boost host immune responses against M. genitalium. To achieve the study aim, immunoinformatics approaches were applied to the said pathogen's proteomics sequence data. B and T cell epitopes were projected from the three shortlisted vaccine proteins; MG014, MG015, Hmw3MG317. The final vaccine ensemble comprises cytotoxic and helper T cell epitopes fused through appropriate linkers. The epitopes peptide is then liked to an adjuvant for efficient recognition and processing by the host immune system. The various physicochemical parameters such as allergenicity, antigenicity, theoretical pI, GRAVY, and molecular weight of the vaccine were checked and found safe and effective to be used in post-experimental studies. The stability and binding affinity of the vaccine with the TLR1/2 heterodimer were ensured by performing molecular docking. The best-docked complex was considered, ranked top having the lowest binding energy and strong intermolecular binding and stability. Finally, the vaccine constructs better expression was obtained by in silico cloning into the pET28a (+) vector in Escherichia coli K-12 strain, and immune simulation validated the immune response. In a nutshell, all these approaches lead to developing a multi-epitope vaccine that possessed the ability to induce cellular and antibody-mediated immune responses against the pathogen used.
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http://dx.doi.org/10.1016/j.micpath.2021.104771DOI Listing
March 2021

Bringing Structural Implications and Deep Learning-Based Drug Identification for Mutants.

J Chem Inf Model 2021 Feb 29;61(2):571-586. Epub 2021 Jan 29.

Department of Bioinformatics and Biostatistics, State Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanghai 200240, China.

Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten Rat Sarcoma () harboring codons 13 and 61 mutations. The objective for this study is to search for clinically important codon 61 mutations and analyze how they affect the protein structural dynamics. Additionally, a deep-learning approach is used to carry out a similarity search for potential compounds that might have a comparatively better affinity. Public databases like The Cancer Genome Atlas and Genomic Data Commons were accessed for obtaining the data regarding mutations that are associated with colon cancer. Multiple analysis such as genomic alteration landscape, survival analysis, and systems biology-based kinetic simulations were carried out to predict dynamic changes for the selected mutations. Additionally, a molecular dynamics simulation of 100 ns for all the seven shortlisted codon 61 mutations have been conducted, which revealed noticeable deviations. Finally, the deep learning-based predicted compounds were docked with the 3D conformer, showing better affinity and good docking scores as compared to the already existing drugs. Taking together the outcomes of systems biology and molecular dynamics, it is observed that the reported mutations in the SII region are highly detrimental as they have an immense impact on the protein sensitive sites' native conformation and overall stability. The drugs reported in this study show increased performance and are encouraged to be used for further evaluation regarding the situation that ascends as a result of mutations.
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http://dx.doi.org/10.1021/acs.jcim.0c00488DOI Listing
February 2021

Hantavirus: The Next Pandemic We Are Waiting For?

Interdiscip Sci 2021 Mar 24;13(1):147-152. Epub 2021 Jan 24.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China.

Hantaviruses, albeit reported more than 40 years ago, are now considered emerging viruses' because of their growing importance as human pathogens. Hantavirus created focal news when the paradoxical spread was reported during the world's pandemic battle of the COVID-19, killing a man in Yunnan province of China, further jeopardizing the existing of the human race on the planet earth. In recent years an increasing number of infections and human-to-human transmission is creating a distressing situation. In this short communication, we have focused on the biology, pathogenesis, immunology, epidemiology and future perspective of the Hantaviruses. Our understandings of hantavirus related pandemics and syndrome are limited, the contributing environmental factors, the cellular and viral dynamics in transmission from natural reservoirs to humans and finally, the virology in humans is quite intricate. Priorities for future research suggest that setting up scientific collaboration, the funding, and encouragement of health ministries and the research institutes should take admirable steps to build an understanding of this virus. Discovering new drugs or other therapeutic molecules such as vaccines takes a longer time. Thus with the recent artificial intelligence (AI) technology, the rifle for impending new medicines should be hastened. Last but not least, a data-sharing platform should be provided where all the researchers should share and make available all the necessary information such as genomics, proteomics, host-factors, and other epigenetics information, which will encourage the research collaboration in the preparation against the Hantaviruses.
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http://dx.doi.org/10.1007/s12539-020-00413-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826498PMC
March 2021

Structures of SARS-CoV-2 RNA-Binding Proteins and Therapeutic Targets.

Intervirology 2021 15;64(2):55-68. Epub 2021 Jan 15.

State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, and Joint Laboratory of International Cooperation in Metabolic and Developmental Sciences, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China,

Background: The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) epidemic has resulted in thousands of infections and deaths worldwide. Several therapies are currently undergoing clinical trials for the treatment of SARS-CoV-2 infection. However, the development of new drugs and the repositioning of existing drugs can only be achieved after the identification of potential therapeutic targets within structures, as this strategy provides the most precise solution for developing treatments for sudden epidemic infectious diseases.

Summary: In the current investigation, crystal and cryo-electron microscopy structures encoded by the SARS-CoV-2 genome were systematically examined for the identification of potential drug targets. These structures include nonstructural proteins (Nsp-9; Nsp-12; and Nsp-15), nucleocapsid (N) proteins, and the main protease (Mpro). Key Message: The structural information reveals the presence of many potential alternative therapeutic targets, primarily involved in interaction between N protein and Nsp3, forming replication-transcription complexes (RTCs) which might be a potential drug target for effective control of current SARS-CoV-2 pandemic. RTCs consist of 16 nonstructural proteins (Nsp1-16) that play the most essential role in the synthesis of viral RNA. Targeting the physical linkage between the envelope and single-stranded positive RNA, a process facilitated by matrix proteins may provide a good alternative strategy. Our current study provides useful information for the development of new lead compounds against SARS-CoV-2 infections.
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http://dx.doi.org/10.1159/000513686DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900486PMC
April 2021

In silico and in vitro evaluation of kaempferol as a potential inhibitor of the SARS-CoV-2 main protease (3CLpro).

Phytother Res 2021 Jan 15. Epub 2021 Jan 15.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

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http://dx.doi.org/10.1002/ptr.6998DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8013176PMC
January 2021

Evolutionary and structural analysis of SARS-CoV-2 specific evasion of host immunity.

Genes Immun 2020 12 3;21(6-8):409-419. Epub 2020 Dec 3.

National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan.

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading fast worldwide. There is a pressing need to understand how the virus counteracts host innate immune responses. Deleterious clinical manifestations of coronaviruses have been associated with virus-induced direct dysregulation of innate immune responses occurring via viral macrodomains located within nonstructural protein-3 (Nsp3). However, no substantial information is available concerning the relationship of macrodomains to the unusually high pathogenicity of SARS-CoV-2. Here, we show that structural evolution of macrodomains may impart a critical role to the unique pathogenicity of SARS-CoV-2. Using sequence, structural, and phylogenetic analysis, we identify a specific set of historical substitutions that recapitulate the evolution of the macrodomains that counteract host immune response. These evolutionary substitutions may alter and reposition the secondary structural elements to create new intra-protein contacts and, thereby, may enhance the ability of SARS-CoV-2 to inhibit host immunity. Further, we find that the unusual virulence of this virus is potentially the consequence of Darwinian selection-driven epistasis in protein evolution. Our findings warrant further characterization of macrodomain-specific evolutionary substitutions in in vitro and in vivo models to determine their inhibitory effects on the host immune system.
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http://dx.doi.org/10.1038/s41435-020-00120-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711619PMC
December 2020

Core amino acid substitutions in HCV-3a isolates from Pakistan and opportunities for multi-epitopic vaccines.

J Biomol Struct Dyn 2020 Nov 27:1-16. Epub 2020 Nov 27.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiaotong University, Shanghai, China.

Hepatitis C virus (HCV), which infected 71 million worldwide and about 5%-6% are from Pakistan, is an ssRNA virus, responsible for end-stage liver disease. To date, no effective therapy is available to cure this disease. Hence, it is important to study the most prevalent genotypes infecting human population and design novel vaccine or small molecule inhibitors to control the infections associated with HCV. Therefore, in this study clinical samples ( = 35; HCV-3a) from HCV patients were subjected to Sanger sequencing method. The sequencing of the core gene, which is generally considered as conserved, involved in the detection, quantitation and genotyping of HCV was performed. Multiple mutations, that is, R46C, R70Q, L91C, G60E, N/S105A, P108A, N110I, S116V, G90S, A77G and G145R that could be linked with response to antiviral therapies were detected. Phylogenetic analysis suggests emerging viral isolates are circulating in Pakistan. Using modelling technique, we predicted the 3D structure of core protein and subjected to molecular dynamics simulation to extract the most stable conformation of the structure for further analysis. Immunoinformatic approaches were used to propose a multi-epitopes vaccine against HCV by using core protein. The vaccine constructs consist of nine CTL and three HTL epitopes joined by different linkers were docked against the two reported Toll-like receptors (TLR-3 and TLR-8). Docking of vaccine construct with TLR-3 and TLR-8 shows proper binding and expression of the vaccine resulted in a CAI value of 0.93. These analyses suggest that specific immune responses may be produced by the proposed vaccine.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1850353DOI Listing
November 2020

Curative effect of Omeprazole under different treatment courses in treatment of children with PU and HP infection and its influence on inflammatory factors.

Pak J Med Sci 2020 Nov-Dec;36(7):1623-1627

Fang Gu, Department of Pediatric Medicine, Baoding Children's Hospital, Baoding 071000, Baoding, China.

Objective: To compare curative effect and safety of omeprazole under different treatment courses in treatment of children with peptic ulcer (PU, diameter≤1.0cm) and helicobacter pylori (HP) infection and its influence on inflammatory cytokines.

Methods: The study was a randomized controlled study and conducted at Baoding children's hospital from June 2015 to June 2018. In this study 100 PU children with positive HP were chosen and classified into two groups at random. The 58 cases in the observation group were given omeprazole + amoxicillin + clarithromycin, and the antibiotics were not used two weeks later. Then, omeprazole was used to treat for two weeks. 42 cases in the control group were given omeprazole + amoxicillin + clarithromycin for two weeks. Curative effect, HP eradication rate, clinical symptoms, incidence of adverse reactions, level of serum inflammatory cytokine interleukin-6 (IL-6) and level of tumor necrosis factor-a (TNF-a) in two groups were compared.

Results: Total effective rate, HP eradication rate and clinical symptom relief of observation group were better than those of control group, and the differences showed statistical significance (P>0.05). The differences of two groups in the incidence of adverse reactions had no statistical significance (P>0.05). Serum IL-6 level and TNF-a level of observation group were significantly lower than those of control group and before the treatment, and the differences had statistical significance (P>0.05).

Conclusion: The application of omeprazole in treatment of PU patients with positive HP for four weeks can significantly improve PU cure rate and HP eradication rate, relieve clinical symptoms and reduce inflammatory response, so it deserves to be promoted clinically.
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http://dx.doi.org/10.12669/pjms.36.7.3048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674910PMC
November 2020

Development of multi-epitope subunit vaccine for protection against the norovirus' infections based on computational vaccinology.

J Biomol Struct Dyn 2020 Nov 10:1-12. Epub 2020 Nov 10.

Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China.

Human Norovirus belongs to a family , and was identified in the outbreak of gastroenteritis in Norwalk, due to its seasonal prevalence known as "winter vomiting disease." Treatment of Norovirus infection is still mysterious because there is no effective antiviral drugs or vaccine developed to protect against the infection, to eradicate the infection an effective vaccine should be developed. In this study, capsid protein (A7YK10), small protein (A7YK11), and polyprotein (A7YK09) were utilized. These proteins were subjected to B and T cell epitopes prediction by using reliable immunoinformatics tools. The antigenic and non-allergenic epitopes were selected for the subunit vaccine, which can activate cellular and humoral immune responses. Linkers joined these epitopes together. The vaccine structure was modelled and validated by using Errat, ProSA, and rampage servers. The modelled vaccine was docked with TLR-7. The stability of the docked complex was evaluated by MD simulation. To apply the concept in a wet lab, the reverse translated vaccine sequence was cloned in pET28a (+). The vaccine developed in this study requires experimental validation to ensure its effectiveness against the disease.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1845799DOI Listing
November 2020

LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions.

Comput Biol Chem 2020 Dec 20;89:107406. Epub 2020 Oct 20.

State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China; Peng Cheng Laboratory, Shenzhen, Guangdong, China. Electronic address:

The interactions between miRNAs and long non-coding RNAs (lncRNAs) are subject to intensive recent studies due to its critical role in gene regulations. Computational prediction of lncRNA-miRNA interactions has become a popular alternative strategy to the experimental methods for identification of underlying interactions. It is desirable to develop the machine learning-based models for prediction of lncRNA-miRNA based on the experimentally validated interactions between lncRNAs and miRNAs. The accuracy and robustness of existing models based on machine learning techniques are subject to further improvement. Considering that the attributes of lncRNA and miRNA contribute key importance in the interaction between these two RNAs, a deep learning model, named LMI-DForest, is proposed here by combining the deep forest and autoencoder strategies. Systematic comparison on the experiment validated datasets for lncRNA-miRNA interaction datasets demonstrates that the proposed method consistently shows superior performance over the other machine learning models in the lncRNA-miRNA interaction prediction.
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http://dx.doi.org/10.1016/j.compbiolchem.2020.107406DOI Listing
December 2020