SPIKES

SPIKES: Knowledge of the host-specific properties of the spike protein is of crucial importance to understand the adaptability of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) to infect multiple species and alter transmissibility, particularly in humans. Here, we propose a spike protein predictor SPIKES incorporating with an inheritable bi-objective combinatorial genetic algorithm to identify the biochemical properties of spike proteins and determine their specificity to human hosts. We suggest that alterations of these amino acids between human and animal coronaviruses may provide insights into the development and transmission of SARS-CoV-2 in human and other species and support the discovery of targeted antiviral therapies.

Input Data

FASTA format (e.g., example.fa)

Getting start

git clone https://github.com/mingjutsai/SPIKES
cd SPIKES

build AAIndex

cd src/aaindex
make

build LIBSVM

cd src/libsvm_320
make

Example of running SPIKES

create a new folder for the new analysis

mkdir example_output

perl SPIKES_main.pl example.fa example_output

Result of SPIKES

results of example.fa -> example_output/SPIKES_prediction_results.csv SPIKES_prediction_results.csv

The format of prediction results

1st: accession number of proteins
2nd: protein sequence
3rd: prediction score (normalized probabilities less than 0.5 are predicted to be human’s Spike protein, those greater than 0.5 are predicted to be non-human’s Spike protein.)

Precalculating Dataset

Citing SPIKES

SPIKES:Identification of physicochemical properties of spike proteins across diverse host species of SARS-CoV-2, STAR PROTOCOLS, 2022 [DOI:https://doi.org/10.1016/j.xpro.2022.101460]
Tracking the amino acid changes of spike proteins across diverse host species of severe acute respiratory syndrome coronavirus 2. iScience, 2022 [PMID:34877480]

Contact

Srinivasulu Yerukala Sathipati: sathipathi.srinivasulu@marshfieldclinic.org
Ming-Ju Tsai: mingjutsai@hsl.harvard.edu