Publications by authors named "Bifang He"

22 Publications

  • Page 1 of 1

TUPDB: Target-Unrelated Peptide Data Bank.

Interdiscip Sci 2021 May 16. Epub 2021 May 16.

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 611731, China.

The isolation of target-unrelated peptides (TUPs) through biopanning remains as a major problem of phage display selection experiments. These TUPs do not have any actual affinity toward targets of interest, which tend to be mistakenly identified as target-binding peptides. Therefore, an information portal for storing TUP data is urgently needed. Here, we present a TUP data bank (TUPDB), which is a comprehensive, manually curated database of approximately 73 experimentally verified TUPs and 1963 potential TUPs collected from TUPScan, the BDB database, and public research articles. The TUPScan tool has been integrated in TUPDB to facilitate TUP analysis. We believe that TUPDB can help identify and remove TUPs in future reports in the biopanning community. The database is of great importance to improving the quality of phage display-based epitope mapping and promoting the development of vaccines, diagnostics, and therapeutics. The TUPDB database is available at http://i.uestc.edu.cn/tupdb .
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http://dx.doi.org/10.1007/s12539-021-00436-5DOI Listing
May 2021

Parcellation of the thalamus by using a dual-segment method based on resting-state functional connectivity: An application on autism spectrum disorder.

Neurosci Lett 2021 01 24;742:135518. Epub 2020 Nov 24.

School of Medicine, Guizhou University, Guizhou, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China. Electronic address:

Background: Evidence suggests thalamus is a key "information relay" center and all cortical areas receive inputs from the thalamus and each of the main nuclei of thalamus connects a single one or a few cortical areas. The traditional "winner-takes-all" thalamus parcellation method was then proposed based on this assumption. However, this method is based on the structural segments of the cortex which is not suitable for the functional parcellation of the thalamus.

Method: Here we proposed a dual-segment method for thalamus functional parcellation based on the resting-state fMRI data. The traditional "winner-takes-all" and the proposed dual-segment methods were both applied to the dataset of 76 healthy controls (HCs) and 34 subjects with autism spectrum disorder.

Results: The results showed that the thalamus was subdivided into two sub-regions by using the dual-segment method: one is located in the dorsomedial part of thalamus which connects the high-level cognitive cortical regions; the other is located in the ventrolateral part of thalamus which connects the low-level sensory cortical areas. The functional connectivity strength between thalamus sub-regions and the corresponding cortical regions based on the dual-segment method was higher than that of results from the traditional "winner-takes-all" method. The thalamo-cortical functional connectivity based on our proposed method also showed higher classification ability to distinguish subjects with autism spectrum disorder from HCs.

Conclusion: Our study will provide a new method for functional thalamus parcellation which might help understand the sub-regions functions of thalamus in neuroscience studies.
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http://dx.doi.org/10.1016/j.neulet.2020.135518DOI Listing
January 2021

Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder.

Autism Res 2021 03 18;14(3):464-472. Epub 2020 Nov 18.

School of Medicine, Guizhou University, Guiyang, Guizhou, China.

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD.
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http://dx.doi.org/10.1002/aur.2435DOI Listing
March 2021

PVsiRNAPred: Prediction of plant exclusive virus-derived small interfering RNAs by deep convolutional neural network.

J Bioinform Comput Biol 2019 12;17(6):1950039

Medical College, Guizhou University, Jiaxiu Road, Huaxi Zone, Guiyang 550025, P. R. China.

Plant exclusive virus-derived small interfering RNAs (vsiRNAs) regulate various biological processes, especially important in antiviral immunity. The identification of plant vsiRNAs is important for understanding the biogenesis and function mechanisms of vsiRNAs and further developing anti-viral plants. In this study, we extracted plant vsiRNA sequences from the PVsiRNAdb database. We then utilized deep convolutional neural network (CNN) to develop a deep learning algorithm for predicting plant vsiRNAs based on vsiRNA sequence composition, known as PVsiRNAPred. The key part of PVsiRNAPred is the CNN module, which automatically learns hierarchical representations of vsiRNA sequences related to vsiRNA profiles in plants. When evaluated using an independent testing dataset, the accuracy of the model was 65.70%, which was higher than those of five conventional machine learning method-based classifiers. In addition, PVsiRNAPred obtained a sensitivity of 67.11%, specificity of 64.26% and Matthews correlation coefficient (MCC) of 0.31, and the area under the receiver operating characteristic (ROC) curve (AUC) of PVsiRNAPred was 0.71 in the independent test. The permutation test with 1000 shuffles resulted in a value . The above results reveal that PVsiRNAPred has favorable generalization capabilities. We hope PVsiRNAPred, the first bioinformatics algorithm for predicting plant vsiRNAs, will allow efficient discovery of new vsiRNAs.
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http://dx.doi.org/10.1142/S0219720019500392DOI Listing
December 2019

AGONOTES: A Robot Annotator for Argonaute Proteins.

Interdiscip Sci 2020 Mar 18;12(1):109-116. Epub 2019 Nov 18.

Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 637111, China.

The argonaute protein (Ago) exists in almost all organisms. In eukaryotes, it functions as a regulatory system for gene expression. In prokaryotes, it is a type of defense system against foreign invasive genomes. The Ago system has been engineered for gene silencing and genome editing and plays an important role in biological studies. With an increasing number of genomes and proteomes of various microbes becoming available, computational tools for identifying and annotating argonaute proteins are urgently needed. We introduce AGONOTES (Argonaute Notes). It is a web service especially designed for identifying and annotating Ago. AGONOTES uses the BLASTP similarity search algorithm to categorize all submitted proteins into three groups: prokaryotic argonaute protein (pAgo), eukaryotic argonaute protein (eAgo), and non-argonaute protein (non-Ago). Argonaute proteins can then be aligned to the corresponding standard set of Ago sequences using the multiple sequence alignment program MUSCLE. All functional domains of Ago can further be curated from the alignment results and visualized easily through Bio::Graphic modules in the BioPerl bundle. Compared with existing tools such as CD-Search and available databases such as UniProt and AGONOTES showed a much better performance on domain annotations, which is fundamental in studying the new Ago. AGONOTES can be freely accessed at http://i.uestc.edu.cn/agonotes/. AGONOTES is a friendly tool for annotating Ago domains from a proteome or a series of protein sequences.
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http://dx.doi.org/10.1007/s12539-019-00349-4DOI Listing
March 2020

NeuroCS: A Tool to Predict Cleavage Sites of Neuropeptide Precursors.

Protein Pept Lett 2020 ;27(4):337-345

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.

Background: Neuropeptides are a class of bioactive peptides produced from neuropeptide precursors through a series of extremely complex processes, mediating neuronal regulations in many aspects. Accurate identification of cleavage sites of neuropeptide precursors is of great significance for the development of neuroscience and brain science.

Objective: With the explosive growth of neuropeptide precursor data, it is pretty much needed to develop bioinformatics methods for predicting neuropeptide precursors' cleavage sites quickly and efficiently.

Methods: We started with processing the neuropeptide precursor data from SwissProt and NueoPedia into two sets of data, training dataset and testing dataset. Subsequently, six feature extraction schemes were applied to generate different feature sets and then feature selection methods were used to find the optimal feature subset of each. Thereafter the support vector machine was utilized to build models for different feature types. Finally, the performance of models were evaluated with the independent testing dataset.

Results: Six models are built through support vector machine. Among them the enhanced amino acid composition-based model reaches the highest accuracy of 91.60% in the 5-fold cross validation. When evaluated with independent testing dataset, it also showed an excellent performance with a high accuracy of 90.37% and Area under Receiver Operating Characteristic curve up to 0.9576.

Conclusion: The performance of the developed model was decent. Moreover, for users' convenience, an online web server called NeuroCS is built, which is freely available at http://i.uestc.edu.cn/NeuroCS/dist/index.html#/. NeuroCS can be used to predict neuropeptide precursors' cleavage sites effectively.
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http://dx.doi.org/10.2174/0929866526666191112150636DOI Listing
September 2020

CasPDB: an integrated and annotated database for Cas proteins from bacteria and archaea.

Database (Oxford) 2019 01;2019

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China.

Clustered regularly interspaced short palindromic repeats (CRISPR) and associated proteins (Cas) constitute CRISPR-Cas systems, which are antiphage immune systems present in numerous bacterial and most archaeal species. In recent years, CRISPR-Cas systems have been developed into reliable and powerful genome editing tools. Nevertheless, finding similar or better tools from bacteria or archaea remains crucial. This requires the exploration of different CRISPR systems, identification and characterization new Cas proteins. Archives tailored for Cas proteins are urgently needed and necessitate the prediction and grouping of Cas proteins into an information center with all available experimental evidence. Here, we constructed Cas Protein Data Bank (CasPDB), an integrated and annotated online database for Cas proteins from bacteria and archaea. The CasPDB database contains 287 reviewed Cas proteins, 257 745 putative Cas proteins and 3593 Cas operons from 32 023 bacteria species and 1802 archaea species. The database can be freely browsed and searched. The CasPDB web interface also represents all the 3593 putative Cas operons and its components. Among these operons, 328 are members of the type II CRISPR-Cas system.
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http://dx.doi.org/10.1093/database/baz093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693189PMC
January 2019

SAROTUP: a suite of tools for finding potential target-unrelated peptides from phage display data.

Int J Biol Sci 2019 2;15(7):1452-1459. Epub 2019 Jun 2.

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China.

SAROTUP (Scanner And Reporter Of Target-Unrelated Peptides) 3.1 is a significant upgrade to the widely used SAROTUP web server for the rapid identification of target-unrelated peptides (TUPs) in phage display data. At present, SAROTUP has gathered a suite of tools for finding potential TUPs and other purposes. Besides the TUPScan, the motif-based tool, and three tools based on the BDB database, i.e., MimoScan, MimoSearch, and MimoBlast, three predictors based on support vector machine, i.e., PhD7Faster, SABinder and PSBinder, are integrated into SAROTUP. The current version of SAROTUP contains 27 TUP motifs and 823 TUP sequences. We also developed the standalone SAROTUP application with graphical user interface (GUI) and command line versions for processing deep sequencing phage display data and distributed it as an open source package, which can perform perfectly locally on almost all systems that support C++ with little or no modification. The web interfaces of SAROTUP have also been redesigned to be more self-evident and user-friendly. The latest version of SAROTUP is freely available at http://i.uestc.edu.cn/sarotup3.
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http://dx.doi.org/10.7150/ijbs.31957DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6643146PMC
April 2020

PhD7Faster 2.0: predicting clones propagating faster from the Ph.D.-7 phage display library by coupling PseAAC and tripeptide composition.

PeerJ 2019 17;7:e7131. Epub 2019 Jun 17.

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.

Selection from phage display libraries empowers isolation of high-affinity ligands for various targets. However, this method also identifies propagation-related target-unrelated peptides (PrTUPs). These false positive hits appear because of their amplification advantages. In this report, we present PhD7Faster 2.0 for predicting fast-propagating clones from the Ph.D.-7 phage display library, which was developed based on the support vector machine. Feature selection was performed against PseAAC and tripeptide composition using the incremental feature selection method. Ten-fold cross-validation results show that PhD7Faster 2.0 succeeds a decent performance with the accuracy of 81.84%, the Matthews correlation coefficient of 0.64 and the area under the ROC curve of 0.90. The permutation test with 1,000 shuffles resulted in < 0.001. We implemented PhD7Faster 2.0 into a publicly accessible web tool (http://i.uestc.edu.cn/sarotup3/cgi-bin/PhD7Faster.pl) and constructed standalone graphical user interface and command-line versions for different systems. The standalone PhD7Faster 2.0 is able to detect PrTUPs within small datasets as well as large-scale datasets. This makes PhD7Faster 2.0 an enhanced and powerful tool for scanning and reporting faster-growing clones from the Ph.D.-7 phage display library.
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http://dx.doi.org/10.7717/peerj.7131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6585900PMC
June 2019

CISI: A Tool for Predicting Cross-interaction or Self-interaction of Monoclonal Antibodies Using Sequences.

Interdiscip Sci 2019 Dec 22;11(4):691-697. Epub 2019 May 22.

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Monoclonal antibodies (mAbs) are one of the robust classes of therapeutic proteins. Their stability, specificity, and high solubility allow the successful development and commercialization of antibody-based drugs. Though with these characteristics, mAbs projects are often suspended due to self- or cross-interaction of monoclonal antibodies. This is one of the main reasons which causes the development of mAbs into drugs taking forever and expensive. CISI is short for cross-interaction or self-interaction of mAbs. It can be quantified by several assays. The assays such as poly-specificity reagent and cross-interaction chromatography can measure cross-interaction of mAbs. Self-interaction can be assayed through clone self-interaction by biolayer interferometry and affinity-capture self-interaction nanoparticle spectroscopy. To save time and money, we developed a model called CISI which can predict cross-interaction or self-interaction based on tripeptide composition. It showed 88.20% accuracy, 90.22% sensitivity, 86.05% specificity, 0.78 Mathew correlation coefficient, and 0.96 area under the receiver operating characteristic (ROC) curve (AUC) in the leave-one-out cross-validation. CISI is freely available at http://i.uestc.edu.cn/eli/cgi-bin/cisi.pl.
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http://dx.doi.org/10.1007/s12539-019-00330-1DOI Listing
December 2019

Molecular Design of Peptide-Fc Fusion Drugs.

Curr Drug Metab 2019 ;20(3):203-208

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, China.

Background: Peptide-Fc fusion drugs, also known as peptibodies, are a category of biological therapeutics in which the Fc region of an antibody is genetically fused to a peptide of interest. However, to develop such kind of drugs is laborious and expensive. Rational design is urgently needed.

Methods: We summarized the key steps in peptide-Fc fusion technology and stressed the main computational resources, tools, and methods that had been used in the rational design of peptide-Fc fusion drugs. We also raised open questions about the computer-aided molecular design of peptide-Fc.

Results: The design of peptibody consists of four steps. First, identify peptide leads from native ligands, biopanning, and computational design or prediction. Second, select the proper Fc region from different classes or subclasses of immunoglobulin. Third, fuse the peptide leads and Fc together properly. At last, evaluate the immunogenicity of the constructs. At each step, there are quite a few useful resources and computational tools.

Conclusion: Reviewing the molecular design of peptibody will certainly help make the transition from peptide leads to drugs on the market quicker and cheaper.
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http://dx.doi.org/10.2174/1389200219666180821095355DOI Listing
November 2019

Computational Design of Antiangiogenic Peptibody by Fusing Human IgG1 Fc Fragment and HRH Peptide: Structural Modeling, Energetic Analysis, and Dynamics Simulation of Its Binding Potency to VEGF Receptor.

Int J Biol Sci 2018 22;14(8):930-937. Epub 2018 May 22.

Center for Informational Biology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.

Peptibodies represent a new class of biological therapeutics with combination of peptide activity and antibody-like properties. Previously, we discovered a novel peptide HRH that exhibited a dose-dependent angiogenesis-suppressing effect by targeting vascular endothelial growth factor receptors (VEGFRs). Here, we computationally designed an antiangiogenic peptibody, termed as PbHRH, by fusing the HRH peptide to human IgG1 Fc fragment using the first approved peptibody drug Romiplostim as template. The biologically active peptide of Romiplostim is similar with HRH peptide; both of them have close sequence lengths and can fold into a α-helical conformation in free state. Molecular dynamics simulations revealed that the HRH functional domain is highly flexible, which is functionally independent of Fc fragment in the designed PbHRH peptibody. Subsequently, the intermolecular interactions between VEGFR-1 domain 2 (D2) and PbHRH were predicted, clustered and refined into three representatives. Conformational analysis and energetic evaluation unraveled that the PbHRH can adopt multiple binding modes to block the native VEGF-A binding site of VEGFR-1 D2 with its HRH functional domain, although the binding effectiveness of HRH segments in peptibody context seems to be moderately decreased relative to that of free HRH peptide. Overall, it is suggested that integrating HRH peptide into PbHRH peptibody does not promote the direct intermolecular interaction between VEGFR-1 D2 and HRH. Instead, the peptibody may indirectly help to improve the pharmacokinetic profile and bioavailability of HRH.
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http://dx.doi.org/10.7150/ijbs.24582DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6036755PMC
July 2019

Development and Application of Computational Methods in Phage Display Technology.

Curr Med Chem 2019 ;26(42):7672-7693

Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China.

Background: Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.

Methods: We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.

Results: We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.

Conclusion: The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed.
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http://dx.doi.org/10.2174/0929867325666180629123117DOI Listing
January 2020

Biopanning data bank 2018: hugging next generation phage display.

Database (Oxford) 2018 01;2018

Center for Informational Biology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China.

Database Url: The BDB database is available at http://immunet.cn/bdb.
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http://dx.doi.org/10.1093/database/bay032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206649PMC
January 2018

PSBinder: A Web Service for Predicting Polystyrene Surface-Binding Peptides.

Biomed Res Int 2017 27;2017:5761517. Epub 2017 Dec 27.

Center for Informational Biology, University of Electronic Science and Technology of China, Sichuan, China.

Polystyrene surface-binding peptides (PSBPs) are useful as affinity tags to build a highly effective ELISA system. However, they are also a quite common type of target-unrelated peptides (TUPs) in the panning of phage-displayed random peptide library. As TUP, PSBP will mislead the analysis of panning results if not identified. Therefore, it is necessary to find a way to quickly and easily foretell if a peptide is likely to be a PSBP or not. In this paper, we describe PSBinder, a predictor based on SVM. To our knowledge, it is the first web server for predicting PSBP. The SVM model was built with the feature of optimized dipeptide composition and 87.02% (MCC = 0.74; AUC = 0.91) of peptides were correctly classified by fivefold cross-validation. PSBinder can be used to exclude highly possible PSBP from biopanning results or to find novel candidates for polystyrene affinity tags. Either way, it is valuable for biotechnology community.
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http://dx.doi.org/10.1155/2017/5761517DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763211PMC
August 2018

Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing.

Sci Rep 2018 01 19;8(1):1214. Epub 2018 Jan 19.

Department of Chemistry and Alberta Glycomics Centre, University of Alberta, Edmonton, AB T6G 2G2, Canada.

Understanding the composition of a genetically-encoded (GE) library is instrumental to the success of ligand discovery. In this manuscript, we investigate the bias in GE-libraries of linear, macrocyclic and chemically post-translationally modified (cPTM) tetrapeptides displayed on the M13KE platform, which are produced via trinucleotide cassette synthesis (19 codons) and NNK-randomized codon. Differential enrichment of synthetic DNA {S}, ligated vector {L} (extension and ligation of synthetic DNA into the vector), naïve libraries {N} (transformation of the ligated vector into the bacteria followed by expression of the library for 4.5 hours to yield a "naïve" library), and libraries chemically modified by aldehyde ligation and cysteine macrocyclization {M} characterized by paired-end deep sequencing, detected a significant drop in diversity in {L} → {N}, but only a minor compositional difference in {S} → {L} and {N} → {M}. Libraries expressed at the N-terminus of phage protein pIII censored positively charged amino acids Arg and Lys; libraries expressed between pIII domains N1 and N2 overcame Arg/Lys-censorship but introduced new bias towards Gly and Ser. Interrogation of biases arising from cPTM by aldehyde ligation and cysteine macrocyclization unveiled censorship of sequences with Ser/Phe. Analogous analysis can be used to explore library diversity in new display platforms and optimize cPTM of these libraries.
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http://dx.doi.org/10.1038/s41598-018-19439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5775325PMC
January 2018

A novel peptide specifically binding to VEGF receptor suppresses angiogenesis and .

Signal Transduct Target Ther 2017;2:17010. Epub 2017 May 12.

Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Vascular endothelial growth factor (VEGF), one of the most important angiogenic factors, plays an essential role in both physiological and pathological angiogenesis through binding to VEGF receptors (VEGFRs). Here we report a novel peptide designated HRHTKQRHTALH (peptide HRH), which was isolated from the Ph.D. -12 phage display library using VEGFR-Fc fusion protein as the bait. This peptide was found to dose-dependently inhibit the proliferation of human umbilical vein endothelial cells stimulated by VEGF. The anti-angiogenesis effect of the HRH peptide was further confirmed using the chick chorioallantoic membrane assay, which was also dose-dependent. Besides, peptide HRH was proved to inhibit corneal neovascularization in an alkali-burnt rat corneal model and a suture-induced rat corneal model. Taken together, these findings suggest that the HRH peptide can inhibit angiogenesis both and . Consequently, the HRHTKQRHTALH peptide might be a promising lead peptide for the development of potential angiogenic inhibitors.
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http://dx.doi.org/10.1038/sigtrans.2017.10DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5661615PMC
February 2021

SABinder: A Web Service for Predicting Streptavidin-Binding Peptides.

Biomed Res Int 2016 17;2016:9175143. Epub 2016 Aug 17.

Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China.

Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community.
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http://dx.doi.org/10.1155/2016/9175143DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005764PMC
February 2017

BDB: biopanning data bank.

Nucleic Acids Res 2016 Jan 25;44(D1):D1127-32. Epub 2015 Oct 25.

Center of Bioinformatics (COBI), Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu 610054, China

The BDB database (http://immunet.cn/bdb) is an update of the MimoDB database, which was previously described in the 2012 Nucleic Acids Research Database issue. The rebranded name BDB is short for Biopanning Data Bank, which aims to be a portal for biopanning results of the combinatorial peptide library. Last updated in July 2015, BDB contains 2904 sets of biopanning data collected from 1322 peer-reviewed papers. It contains 25,786 peptide sequences, 1704 targets, 492 known templates, 447 peptide libraries and 310 crystal structures of target-template or target-peptide complexes. All data stored in BDB were revisited, and information on peptide affinity, measurement method and procedures was added for 2298 peptides from 411 sets of biopanning data from 246 published papers. In addition, a more professional and user-friendly web interface was implemented, a more detailed help system was designed, and a new on-the-fly data visualization tool and a series of tools for data analysis were integrated. With these new data and tools made available, we expect that the BDB database would become a major resource for scholars using phage display, with improved utility for biopanning and related scientific communities.
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http://dx.doi.org/10.1093/nar/gkv1100DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702802PMC
January 2016

Mimotope-based prediction of B-cell epitopes.

Methods Mol Biol 2014 ;1184:237-43

Center of Bioinformatics (COBI), Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Room 341, Yifu Building, Shahe Campus, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, China,

Mimotopes are peptides mimicking epitopes on the corresponding antigen. They can be obtained via panning the phage-displayed random peptide library against the corresponding monoclonal antibody or specific sera. Besides mimotopes however, the experimental results also include all kinds of unwanted sequences called "target-unrelated peptides," which often interfere with the subsequent experimental and computational analyses. Nevertheless, the prediction of B-cell epitopes based on the experimental result of phage display has shown to be a promising and reliable strategy with acceptable precision. In this chapter, we summarize mimotope-based prediction of B-cell epitopes under three conditions and focus on protocols and tips for retrieving, cleaning, and decoding the data from phage display technology.
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http://dx.doi.org/10.1007/978-1-4939-1115-8_13DOI Listing
March 2015

Epitope mapping of metuximab on CD147 using phage display and molecular docking.

Comput Math Methods Med 2013 3;2013:983829. Epub 2013 Jun 3.

Center of Bioinformatics (COBI), Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.

Metuximab is the generic name of Licartin, a new drug for radioimmunotherapy of hepatocellular carcinoma. Although it is known to be a mouse monoclonal antibody against CD147, the complete epitope mediating the binding of metuximab to CD147 remains unknown. We panned the Ph.D.-12 phage display peptide library against metuximab and got six mimotopes. The following bioinformatics analysis based on mimotopes suggested that metuximab recognizes a conformational epitope composed of more than 20 residues. The residues of its epitope may include T28, V30, K36, L38, K57, F74, D77, S78, D79, D80, Q81, G83, S86, N98, Q100, L101, H102, G103, P104, V131, P132, and K191. The homology modeling of metuximab and the docking of CD147 to metuximab were also performed. Based on the top one docking model, the epitope was predicted to contain 28 residues: AGTVFTTV (23-30), I37, D45, E84, V88, EPMGTANIQLH (92-102), VPP (131-133), Q164, and K191. Almost half of the residues predicted on the basis of mimotope analysis also appear in the docking result, indicating that both results are reliable. As the predicted epitopes of metuximab largely overlap with interfaces of CD147-CD147 interactions, a structural mechanism of metuximab is proposed as blocking the formation of CD147 dimer.
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http://dx.doi.org/10.1155/2013/983829DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686076PMC
January 2014

[Differential diagnosis of malignant and benign peripheral pulmonary lesions based on two characteristic echo features of endobronchial ultrasonography].

Nan Fang Yi Ke Da Xue Xue Bao 2012 Jun;32(7):1016-9

Department of Respiratory Diseases, Guangdong General Hospital, China. gzhy79

Objective: To assess the feasibility of endobronchial ultrasonography (EBUS) in the differential diagnosis of malignant and benign lesions based on the two characteristic echo features of malignancy.

Methods: EBUS images from 102 patients undergoing bronchoscopy for peripheral lung lesions were analyzed. The sensitivity and specificity were determined for each echo feature, namely the halo sign and low-level echoes that indicated malignancy, or their combination in diagnosing malignant and benign lesions.

Results: Low-level echoes showed a sensitivity of 89.46% and a specificity of 83% in the diagnosis of malignancy, both higher than those of the halo sign (69.51% and 65%, respectively). The presence of either of the two echo features had a diagnostic sensitivity of 94.6% for malignant lesions, and the coexistence of the two features had a specificity of 93% for a diagnosis of malignant lesions.

Conclusion: EBUS is a useful adjunctive modality for lung cancer diagnosis, especially in cases where peripheral lung lesions are invisible in conventional bronchoscopy.
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June 2012