Free AI-platform for biochemical experimental data prognosis
Integration into existing workflows is another common obstacle to effective AI implementation
Machine learning for RNA 2D structure prediction
Bioinformatics Analysis Platform: Get 3D dimer physical properties: Input files-Download Data
Protein Thermostability Calculations
Strategies for Improving Peptide Stability . The possible solutions to enhance the stability of peptides.
Protein Phosphorylation: Mechanisms, Types/There are so many places in the lab where AI can streamline and improve processes and boost performance. Data mining is a perfect example – it involves using AI to analyze and process huge datasets of information, distilling it down into digestible, actionable insights.
A deep learning method for predicting antibody-antigen interactions based on sequence information
Predicting the Effects of Single Mutations on Protein Stability
Bioinformatics Analysis Platform: machine learning
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Fabs+Epitope
Input mutations in Fabs/Epitope
The goal of the AI platform is to replace and reduce the number of intermediate in vitro experiments
Accuracy of calculations:
a single Pdb file of interacting proteins
a single Pdb file of interacting proteins
depends on the accuracy of the PDB files. Try to use accurate structures of molecular entities that interact and form a single structure in a single PDB file.
Unnecessary fields just remain empty
Unnecessary fields just remain empty
Input your e-mail,
research name,
pdb files for wtPeptides (proteins)
research name,
pdb files for wtPeptides (proteins)
Input information about mutations
Click SUBMIT
now the calculated data will be sent to your email in the order of the queue.
Fab1/36/Ala
If you need to introduce mutations into the protein or peptide being studied, then go to the next window to enter information about mutations in the protein.
Specify the protein number (if there is more than one), as well as the sequence number of the substitution and specify the amino acid residue
Specify the protein number (if there is more than one), as well as the sequence number of the substitution and specify the amino acid residue
Wild Type
Peptide
Input mutations in Peptide
Correlation between calculated lg(cond(W)) and experimental data [urea]50% at the required increased denaturant concentration
Peptide+Protein
Input mutations in Peptide or protein
Examples of correlation graphs obtained from the interaction of mutant forms of a peptide and a protein.
The results of the experimental IC50 (a) and calculated values of lg(cond(W)) (c) ;
the top graphs present the experimental results for
MCL-1–Bax-BH3 (a)
complexes,
while the bottom graph show the results of numerical
calculations for the same biological complexes namely MCL-1–Bax-BH3 (c)
the top graphs present the experimental results for
MCL-1–Bax-BH3 (a)
complexes,
while the bottom graph show the results of numerical
calculations for the same biological complexes namely MCL-1–Bax-BH3 (c)
[A Paradigm Shift in Experimental Biochemistry: A Priori Estimation of Physical Parameters of Biomolecules]
Proteins interaction
Input mutations in proteins
Examples of calculations in the form of a graph of biochemical reactions:
Proteins+Inhibitor
Input mutations in Protein
Scheme and numerical calculations of allosteric small chemical molecule interactions of the
EGFR–EGFR dimer, JBJ-04-125-02,
and AMP–PNP
EGFR–EGFR dimer, JBJ-04-125-02,
and AMP–PNP
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