Protein features identification for machine learning-based prediction of protein-protein interactions

Raza, Khalid

doi:10.1101/137257

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…Protein-protein interactions (PPIs) have a crucial role in cells and control essential cellular and biological processes. Any disease-causing mutations affecting PPIs may lead to disruption of protein-DNA interactions, protein misfolding and new undesirable interactions ( 65 ). A better understanding of possible PPIs allows for the prediction of pathways, protein functions and potential novel therapeutic targets.…”

Section: Resultsmentioning

confidence: 99%

Discovering pathways in benign prostate hyperplasia: A functional genomics pilot study

Chen¹,

2021

Exp Ther Med

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Benign prostate hyperplasia (BPH) is one of the well-known urological neoplasms common in males with an increasing number of associated deaths in aging males. It causes uncomfortable urinary symptoms, including urine flow blockage, and may cause bladder, urinary tract or kidney problems. The histopathological and clinical knowledge regarding BPH is limited. In the present study, an in silico approach was applied that uses genome-scale microarray expression data to discover a wide range of protein-protein interactions in addition to focusing on specific genes responsible for BPH to develop prognostic biomarkers. Various genes that were differentially expressed in BPH were identified. Gene and functional annotation clusters were determined and an interaction analysis with disease phenotypes of BPH was performed, as well as an RNA tissue specificity analysis. Furthermore, a molecular docking study of certain short-listed gene biomarkers, namely anterior gradient 2 (AGR2; PDB ID: 2LNT), steroid 5α-reductase 2 (PDB ID: 6OQX), zinc finger protein 3 (PDB ID: 5T00) and collagen type XII α1 chain (PDB ID: 1U5M), was performed in order to identify alternative Chinese herbal agents for the treatment of BPH. Data from the present study revealed that AGR2 receptor (PDB ID: 2LNT) and berberine (Huang Bo) form the most stable complex and therefore may be assessed in further pharmacological studies for the treatment of BPH.

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Section: Resultsmentioning

confidence: 99%

Discovering pathways in benign prostate hyperplasia: A functional genomics pilot study

Chen¹,

2021

Exp Ther Med

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“…Protein-protein interactions (PPIs) play a pivotal role in both predicting the functions of the target protein and therapeutic potential of the targeted molecules. Most of the genes and proteins function as a result of a set of interactions [28], and understanding the physical, as well as the functional interactions, are important for the biologists. Some of the experimental methods for PPI detection are affinity purification, yeast 2 hybrid (Y2H) and tandem affinity purification (TAP).…”

Section: Protein-protein Interaction Studiesmentioning

confidence: 99%

New insight in understanding and exploring optimal biomarkers in stroke: Key diagnostic markers for clinical treatment

Zhang

Wang

Fan

et al. 2019

Preprint

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Background A stroke is a complex neurological phenomenon where patients may suddenly experience paralysis, loss of vision or impaired speech because of interruption of blood flow. Stroke is the second leading cause of death and a significant reason for long-term disability worldwide. Optimal biomarkers latent in stroke remain relatively unknown, and efforts are ongoing to effectively define the molecular fingerprints of a stroke. In this study, we utilized microarray gene expression data for the in silico discovery of novel key diagnostic markers which can be utilized for clinical treatment of ischemic stroke.Methods and results We performed differential expression analysis and obtained 20 genes which have at least a two-fold change in the expression level. We also performed gene-disease association studies, functional categories enrichment and GO term enrichment analysis, tissue expression analysis, protein-protein interaction (PPI) analysis, interaction study of miRNAs that target identified biomarkers. The identified diagnostic markers were validated with the PubMed literature using publication enrichment analysis.Conclusions It was observed that most of the identified genes, including AKAP7, ARG1, S100A2, MMP9, TIMP, and CCR7 are markers for early or post-ischemic stroke.

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“…Ovchinnikov predicted residue–residue interactions across protein interfaces using evolutionary information [ 6 ]. There are many other methods that are not described here [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers

Lyu

Gong

2020

Molecules

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Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. Different descriptors and different combinations may give different prediction results. We propose feature combination engineering based on correlation coefficients and F-values. The accuracy of our method is 65.38% in independent test set, indicating biological significance. Our predictions are consistent with the experimental results. It shows the effectiveness and reliability of our method to predict interface residue pairs of protein trimers.

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Protein features identification for machine learning-based prediction of protein-protein interactions

Cited by 4 publications

References 38 publications

Discovering pathways in benign prostate hyperplasia: A functional genomics pilot study

Discovering pathways in benign prostate hyperplasia: A functional genomics pilot study

New insight in understanding and exploring optimal biomarkers in stroke: Key diagnostic markers for clinical treatment

A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers

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