Determination of Amino Acid Residues Responsible for Specific Interaction of Protein Kinases with Small Molecule Inhibitors

Karasev, Dmitry; Veselovsky, A. V.; Lagunin, Alexey; Филимонов, Д. А.; Sobolev, Boris N.

doi:10.1134/s002689331802005x

Cited by 4 publications

(9 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…So, the substitution of single residues can modulate the ability of ligand binding that coincides with our prediction of the ligand-specific positions in protein kinase sequences [34]. These observations suggest a there is a weak correlation between the inhibitor specificity spectrum and phylogeny.…”

Section: Protein Kinasessupporting

confidence: 86%

“…The studied ligands are known to interact with kinase at the ATP-binding cleft, which is structurally conserved in proteins of a given family [35]. [43] 0.753 0.765 So, the substitution of single residues can modulate the ability of ligand binding that coincides with our prediction of the ligand-specific positions in protein kinase sequences [34]. These observations suggest a there is a weak correlation between the inhibitor specificity spectrum and phylogeny.…”

Section: Protein Kinasessupporting

confidence: 74%

“…For achieving reliable classification results, each ligand specificity class should contain at least five proteins. Application of such a restriction provided the most reliable results according to our earlier studies [34]. All sequences were extracted from UniProt KnowledgeBase (https://www.uniprot.org/).…”

Section: Training Setsmentioning

confidence: 92%

“…However, the specificity of drug compounds may not coincide with phylogenic relations [26]. Several publications display the cases when relatively few residues determine the protein functional specificity within the family of homologs [27][28][29][30][31][32][33][34]. The protein kinase family demonstrates a vivid example of this situation [35].…”

Section: Introductionmentioning

confidence: 99%

“…These values are input data to the classifier, which estimates the protein specificity to the ligands. Earlier, we have demonstrated that this tool can be applied for functional annotation of proteins [37] and identification of functionally important residues in diverged paralog proteins [34].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences

Karasev

Sobolev

Lagunin

et al. 2019

IJMS

View full text Add to dashboard Cite

The affinity of different drug-like ligands to multiple protein targets reflects general chemical–biological interactions. Computational methods estimating such interactions analyze the available information about the structure of the targets, ligands, or both. Prediction of protein–ligand interactions based on pairwise sequence alignment provides reasonable accuracy if the ligands’ specificity well coincides with the phylogenic taxonomy of the proteins. Methods using multiple alignment require an accurate match of functionally significant residues. Such conditions may not be met in the case of diverged protein families. To overcome these limitations, we propose an approach based on the analysis of local sequence similarity within the set of analyzed proteins. The positional scores, calculated by sequence fragment comparisons, are used as input data for the Bayesian classifier. Our approach provides a prediction accuracy comparable or exceeding those of other methods. It was demonstrated on the popular Gold Standard test sets, presenting different sequence heterogeneity and varying from the group, including different protein families to the more specific groups. A reasonable prediction accuracy was also found for protein kinases, displaying weak relationships between sequence phylogeny and inhibitor specificity. Thus, our method can be applied to the broad area of protein–ligand interactions.

show abstract

Section: Protein Kinasessupporting

confidence: 86%

Section: Protein Kinasessupporting

confidence: 74%

Section: Training Setsmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences

Karasev

Sobolev

Lagunin

et al. 2019

IJMS

View full text Add to dashboard Cite

show abstract

High-Performance Hybrid Computing for Bioinformatic Analysis of Protein Superfamilies

Suplatov

Sharapova

Shegay

et al. 2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

Prediction of Protein–ligand Interaction Based on Sequence Similarity and Ligand Structural Features

Karasev

Sobolev

Lagunin

et al. 2020

IJMS

View full text Add to dashboard Cite

Computationally predicting the interaction of proteins and ligands presents three main directions: the search of new target proteins for ligands, the search of new ligands for targets, and predicting the interaction of new proteins and new ligands. We proposed an approach providing the fuzzy classification of protein sequences based on the ligand structural features to analyze the latter most complicated case. We tested our approach on five protein groups, which represented promised targets for drug-like ligands and differed in functional peculiarities. The training sets were built with the original procedure overcoming the data ambiguity. Our study showed the effective prediction of new targets for ligands with an average accuracy of 0.96. The prediction of new ligands for targets displayed the average accuracy 0.95; accuracy estimates were close to our previous results, comparable in accuracy to those of other methods or exceeded them. Using the fuzzy coefficients reflecting the target-to-ligand specificity, we provided predicting interactions for new proteins and new ligands; the obtained accuracy values from 0.89 to 0.99 were acceptable for such a sophisticated task. The protein kinase family case demonstrated the ability to account for subtle features of proteins and ligands required for the specificity of protein–ligand interaction.

show abstract

Determination of Amino Acid Residues Responsible for Specific Interaction of Protein Kinases with Small Molecule Inhibitors

Cited by 4 publications

References 37 publications

Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences

Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences

High-Performance Hybrid Computing for Bioinformatic Analysis of Protein Superfamilies

Prediction of Protein–ligand Interaction Based on Sequence Similarity and Ligand Structural Features

Contact Info

Product

Resources

About