scholarly journals Helical structure motifs made searchable for functional peptide design

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Cheng-Yu Tsai ◽  
Emmanuel Oluwatobi Salawu ◽  
Hongchun Li ◽  
Guan-Yu Lin ◽  
Ting-Yu Kuo ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Point Mutations ◽  
Protein Secondary Structure ◽  
Helical Structure ◽  
Peptide Design ◽  
Sequence Motifs ◽  
Helical Structures ◽  
Protein Protein Interaction ◽  
Functional Peptides ◽  
Functional Peptide

AbstractThe systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/.

scholarly journals In situFTIR Assessment of Desiccation-Tolerant Tissues

2003 ◽  
Vol 17 (2-3) ◽  
pp. 297-313 ◽  
Author(s):  
Willem F. Wolkers ◽  
Folkert A. Hoekstra
Keyword(s):  
Secondary Structure ◽  
Desiccation Tolerance ◽  
Higher Plants ◽  
Protein Secondary Structure ◽  
Biological Tissues ◽  
Glassy Matrix ◽  
Vibration Band ◽  
Helical Structures ◽  
Ftir Studies ◽  
Stretching Vibration

This essay shows how Fourier transform infrared (FTIR) microspectroscopy can be applied to study thermodynamic parameters and conformation of endogenous biomolecules in desiccation-tolerant biological tissues. Desiccation tolerance is the remarkable ability of some organisms to survive complete dehydration. Seed and pollen of higher plants are well known examples of desiccation-tolerant tissues. FTIR studies on the overall protein secondary structure indicate that during the acquisition of desiccation tolerance, plant embryos exhibit proportional increases inα-helical structures and thatµ-sheet structures dominate upon drying of desiccation sensitive-embryos. During ageing of pollen and seeds, the overall protein secondary structure remains stable, whereas drastic changes in the thermotropic response of membranes occur, which coincide with a complete loss of viability. Properties of the cytoplasmic glassy matrix in desiccation-tolerant plant organs can be studied by monitoring the position of the OH-stretching vibration band of endogenous carbohydrates and proteins as a function of temperature. By applying these FTIR techniques to maturation-defective mutant seeds ofArabidopsis thalianawe were able to establish a correlation between macromolecular stability and desiccation tolerance. Taken together,in situFTIR studies can give unique information on conformation and stability of endogenous biomolecules in desiccation-tolerant tissues.

Secondary Structure Estimation of Proteins Using the Amide III Region of Fourier Transform Infrared Spectroscopy: Application to Analyze Calcium-Binding-Induced Structural Changes in Calsequestrin

1994 ◽  
Vol 48 (11) ◽  
pp. 1432-1441 ◽  
Author(s):  
Fen-Ni Fu ◽  
Daniel B. Deoliveira ◽  
William R. Trumble ◽  
Hemanta K. Sarkar ◽  
Bal Ram Singh
Keyword(s):  
Fourier Transform ◽  
Secondary Structure ◽  
Calcium Binding ◽  
Structural Changes ◽  
Spectroscopic Method ◽  
Spectral Feature ◽  
Protein Secondary Structure ◽  
Fourier Transform Infrared ◽  
Helical Structure ◽  
Α Helix

A Fourier transform infrared spectroscopic method has been developed to analyze protein secondary structure by employing the amide III spectral region (1350–1200 cm−1)· Benefits of using the amide III region have been shown to be substantial. The interference from the water vibration (∼1640 cm−1) in the amide I region can be avoided when one is using the amide III band; furthermore, the amide III region also presents a more characterized spectral feature which provides easily resolved and better defined bands for quantitative analysis. Estimates of secondary structure are accomplished with the use of Fourier self-deconvolution, second derivatization, and curve-fitting on original protein spectra. The secondary structure frequency windows (α-helix, 1328–1289 cm−1; unordered, 1288–1256 cm−1; and β-sheets, 1255–1224 cm−1) have been obtained, and estimates of secondary structural contents are consistent with X-ray crystallography data for model proteins and parallel results obtained with the use of the amide I region. We have further applied the analysis to the structural change of calsequestrin upon Ca2+ binding. Treatment of calsequestrin with 1 mM Ca2+ results in the formation of crystalline aggregates accompanied by a 10% increase in α-helical structure, which is consistent with previous results obtained by Raman spectroscopy. Thus the amide III region of protein IR spectra appears to be a valuable tool in estimating individual protein secondary structural contents.

scholarly journals Genomic mutations and changes in protein secondary structure and solvent accessibility of SARS-CoV-2 (COVID-19 virus)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thanh Thi Nguyen ◽  
Pubudu N. Pathirana ◽  
Thin Nguyen ◽  
Quoc Viet Hung Nguyen ◽  
Asim Bhatti ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Solvent Accessibility ◽  
Point Mutations ◽  
Protein Secondary Structure ◽  
Intervention Strategies ◽  
Relative Solvent Accessibility ◽  
Highly Pathogenic ◽  
Coding Regions ◽  
Pathogenic Virus ◽  
And Control

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic virus that has caused the global COVID-19 pandemic. Tracing the evolution and transmission of the virus is crucial to respond to and control the pandemic through appropriate intervention strategies. This paper reports and analyses genomic mutations in the coding regions of SARS-CoV-2 and their probable protein secondary structure and solvent accessibility changes, which are predicted using deep learning models. Prediction results suggest that mutation D614G in the virus spike protein, which has attracted much attention from researchers, is unlikely to make changes in protein secondary structure and relative solvent accessibility. Based on 6324 viral genome sequences, we create a spreadsheet dataset of point mutations that can facilitate the investigation of SARS-CoV-2 in many perspectives, especially in tracing the evolution and worldwide spread of the virus. Our analysis results also show that coding genes E, M, ORF6, ORF7a, ORF7b and ORF10 are most stable, potentially suitable to be targeted for vaccine and drug development.

scholarly journals Genomic Mutations and Changes in Protein Secondary Structure and Solvent Accessibility of SARS-CoV-2 (COVID-19 Virus)

2020 ◽  
Author(s):  
Thanh Thi Nguyen ◽  
Pubudu N. Pathirana ◽  
Thin Nguyen ◽  
Henry Nguyen ◽  
Asim Bhatti ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Solvent Accessibility ◽  
Point Mutations ◽  
Protein Secondary Structure ◽  
Intervention Strategies ◽  
Relative Solvent Accessibility ◽  
Highly Pathogenic ◽  
Coding Regions ◽  
Pathogenic Virus ◽  
And Control

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic virus that has caused the global COVID-19 pandemic. Tracing the evolution and transmission of the virus is crucial to respond to and control the pandemic through appropriate intervention strategies. This paper reports and analyses genomic mutations in the coding regions of SARS-CoV-2 and their probable protein secondary structure and solvent accessibility changes, which are predicted using deep learning models. Prediction results suggest that mutation D614G in the virus spike protein, which has attracted much attention from researchers, is unlikely to make changes in protein secondary structure and relative solvent accessibility. Based on 6,324 viral genome sequences, we create a spreadsheet dataset of point mutations that can facilitate the investigation of SARS-CoV-2 in many perspectives, especially in tracing the evolution and worldwide spread of the virus. Our analysis results also show that coding genes E, M, ORF6, ORF7a, ORF7b and ORF10 are most stable, potentially suitable to be targeted for vaccine and drug development.

A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: Prediction of proteins’ secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

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