Cefuroxime-induced anaphylaxis with prominent central nervous system manifestations: A case report

ChAlPred: A web server for prediction of allergenicity of chemical compounds

BACKGROUND

Allergy is the abrupt reaction of the immune system that may occur after the exposure to allergens such as proteins, peptides, or chemicals. In the past, various methods have been generated for predicting allergenicity of proteins and peptides. In contrast, there is no method that can predict allergenic potential of chemicals. In this paper, we described a method ChAlPred developed for predicting chemical allergens as well as for designing chemical analogs with desired allergenicity.

METHOD

In this study, we have used 403 allergenic and 1074 non-allergenic chemical compounds obtained from IEDB database. The PaDEL software was used to compute the molecular descriptors of the chemical compounds to develop different prediction models. All the models were trained and tested on the 80% training data and evaluated on the 20% validation data using the 2D, 3D and FP descriptors.

RESULTS

In this study, we have developed different prediction models using several machine learning approaches. It was observed that the Random Forest based model developed using hybrid descriptors performed the best, and achieved the maximum accuracy of 83.39% and AUC of 0.93 on validation dataset. The fingerprint analysis of the dataset indicates that certain chemical fingerprints are more abundant in allergens that include PubChemFP129 and GraphFP1014. We have also predicted allergenicity potential of FDA-approved drugs using our best model and identified the drugs causing allergic symptoms (e.g., Cefuroxime, Spironolactone, Tioconazole). Our results agreed with allergenicity of these drugs reported in literature.

CONCLUSIONS

To aid the research community, we developed a smart-device compatible web server ChAlPred (https://webs.iiitd.edu.in/raghava/chalpred/) that allows to predict and design the chemicals with allergenic properties.

Changes in stroke presentation in neo-Covid patients: A case study

A 35 year old male had a generalized seizure a week after symptoms of daily fever, rigors, and throat discomfort. He was hospitalized. Magnetic resonance imaging brain showed multiple bilateral scattered infarcts. COVID-19 swab test came positive. An elaborate panel of tests for young strokes, cardiac work-up was normal. At home, he complained of some visual blurring, slowing in thought processing, occasional loss of words. His face became significantly pigmented. A young male, COVID-19 positive, showed multiple scattered infarcts. Exaggerated pro-thrombotic activity of the nature of a cytokine storm, is the probable cause.