Welcome to ProteinPred


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.

Fill the following input:










Amino acid composition

Chemical score of essential amino acids
Major properties
Theoretical UV-visible absorption spectrum


Save plot
Wavelength dependence of the refractive index increment (dn/dc)


Save plot
Charge as a function of pH


Save plot


Calculated sorption isotherm


Save plot


Atomic composition


Scattering related parameters
Upload a CSV File

Download the template CSV file for 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.





Major properties
Theoretical UV-visible absorption spectrum


Save plot
Wavelength dependence of the refractive index increment (dn/dc)


Save plot
Charge as a function of pH


Save plot


Data - charge

Data - capacitance
Calculated sorption isotherm


Save plot
Atomic composition table

Scattering related parameters
Upload a CSV File

Download the template CSV file for 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.





Major properties
Theoretical UV-visible absorption spectrum


Save plot
Wavelength dependence of the refractive index increment (dn/dc)


Save plot
Charge as a function of pH


Save plot


Data - charge

Data - capacitance
Calculated sorption isotherm


Save plot
Atomic composition table

Scattering related parameters

Welcome to Help Section


User input

(1) Single sequence module


You need to fill the following input fields:
  • Protein name: no specific requirements,
  • Amino acid sequence: unlimited number of letters comprised in the natural 20 amino acids code (fasta format accepted),
  • Number of polypeptide chains: numerical value, not exceeding the total number of amino acid
  • Number of disulfide bonds: numerical value, not exceeding twice the cystein content.
Click on the "Load Example" button for demonstration purposes. Click on the "Reset" button to remove all the fields.



(2) Multiple sequence module


The CSV file to updload need to fulfill the following requirements:
  • Contain at least 4 columns with the column names provided in the template,
  • Contain at least 1 row,
  • Protein name: unique value,
  • Amino acid sequence: unlimited number of letters comprised in the natural 20 amino acids code (fasta format not accepted),
  • 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.
Download and upload the example of CSV file for demonstration purposes.

(3) Amino acid composition module


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, the FoodProteinsDB database lists the amino acid composition and associated molecular weights for many food proteins.

Download and upload the example of CSV file for demonstration purposes.



Analysis & ouput

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

Paper in preparation.