ProteinPred is a computing tool designed to predict biochemical, physical-chemical, and nutritional properties
of individual proteins or protein groups. This analysis is based on their amino acid sequences or experimental amino acid compositions.
ProteinPred provides three types of user inputs:
 
Calculated parameters includes :
- Amino Acid Compositions & Chemical Scores - Biophysical Chemical Parameters : molecular weight, isoelectric point, hydrophobicity, fraction of charged residues, net of charge per residue,
partial specific volume, protein volume, extinction coefficients, nitrogen-to-protein conversion factor, partial specific volume, refractive index increment (dn/dc), protein volume
- Theoretical UV-Visible Spectra,
- Wavelength Dependence of dn/dc,
- Protein Charge & capacitance as a function of pH,
- Theoretical Sorption Isotherm and related parameters,
- Scattering-Related Parameters: atomic composition, scattering length density (SLD), D2O/H2O matching point & electron density.
Explore your results on the web interface, receive them via email, or download as an Excel file.
Visit the Documentation tab for detailed explanations of calculations, corresponding references for citation,
and contact information for any questions or comments.
 
 
 
 
 
This application was developed and maintained by INRAE Transform Plastic.
Download the template CSV filefor analysing a group of protein sequences. Fill it with your data and upload it below.
You will find the guidelines to fill the CSV file in the documentation tab. You can also test the app by downloading the following example of CSV file.
Atomic composition table Scattering related parameters
Upload a CSV File
Download the template CSV filefor analysing a group of experimental amino acid compositions. Fill it with your data and upload it below.
You will find the guidelines to fill the CSV file in the documentation tab. You can also test the app by downloading the following example of CSV file.
The CSV file to updload need to fulfill a following requirements:
Contain at least 24 columns with the column names provided in the template,
Contain at least 1 row,
Protein name: unique value,
Number of polypeptide chains: numerical values, not exceeding the total number of amino acid
Number of disulfide bonds: numerical values, not exceeding twice the cystein content.
Amino acid composition: expressed in g/kg of powder for 18 amino acids ,
Molecular weight: expressed in g/mol,
The module 'Amino acid Composition' requires information beyond amino acid composition.
Specifically, experimentally, asparagines and glutamines are analyzed in their acidic forms.
Therefore, an estimation of the ratios of asparagine (N) to aspartic acid (D) and glutamine (Q) to glutamic acid (E) is needed.
These ratios are expressed as follows:
Ratio_N_N+D = weight of N / (weight of N + weight of D),
Ratio_Q_Q+E = weight of Q / (weight of Q + weight of E),
Weights are expressed in mg/g of protein. If these ratios are unknown to the user, they can be determined using modules 1 and 2 from the sequences.
Additionally, theFoodProteinsDBdatabase lists the amino acid composition and associated molecular weights for many food proteins.
You can proceed by clicking on the "Launch analysis" button. The analysis is computed.
You can visualize your data on the bottom part of the app.
You can get the indivual data either in each tabset using the "Copy", "Download", and/or "Save plot" buttons
All the data may be downloaded or sent by email on the top right panel.
About ProteinPred
Applicability of ProteinPred
ProteinPred is a computing tool designed to meet the needs of researchers, engineers, and students in Food Science & Technology .
It may also be of interest to broader communities in biophysics, biotechnology, or biomedical fields.
People behind ProteinPred
The calculation, iconography, and design behind ProteinPred were built by Adeline Boire, research scientist at INRAE,
BIA Nantes. The ShinyApp and the informatic infrastructure behind to host the website were developed by Michard Rakotoson,
computer engineer at INRAE, Plastic (TRANSFORM platform).
For bug reports and feature requests, please contact Adeline Boire at adeline.boire@inrae.fr .
The following people have contributed to the development of ProteinPred: Maude Ducrocq, Aurélie Nicolas, Stéphane Pezennec, Antoine Bouchoux, Denis Renard and Hamza Mameri.
Fundings
The application was developped in the framework of the project FoodProteinsDB, founded by
INRAE TRANSFORM department department during the period of 2022-2023.
Reference