*5.8. Semi-Quantitative Proteomics Analysis*

Semi-quantitative protein analysis was performed using the Label Free Quantification MaxLFQ algorithm from MaxQuant software with an FDR rate of ≤1% to compare relative abundance of proteins in each of the cell lines [152]. Data generated by MaxQuant were entered into the Perseus program to further perform statistical and bioinformatics analyzes [153]. Proteins identified in the contaminant database and the decoy database were removed. As a protein identification criterion, it was considered that only peptides identified with the posterior error probability (PEP) ≤ 0.01 in at least one biological replicate, the minimum identification of eight ions belonging to the b and y ion series in the MS/MS spectra, and the occurrence of at least one unique peptide. We considered the intensity values of the LFQ that are normalized by the Maxquant software based on the sum of the intensity of all peptides of all identified proteins. LFQ data was considered for calculation, when the intensity data were present in at least two out of three replicates. Protein abundance or fold change (FC) analysis was performed using Microsoft Excel software. In addition, proteins that had a zero value in two of the three conditions were analyzed separately. The breast cancer cell lines treated with the whole *B. jararaca* venom for two different doses were compared according to the differentially expressed proteins with FC ≥ 1.5 by hierarchical clustering using as variables the average log2 fold change for the three replicates for each treatment, normalized with mean-centering. The Clustering analysis was performed using R statistical software version 3.6.3 (http://www.R-project.org accessed on 1 October 2019). The set of protein dissimilarities were computed using the "Euclidean" distance with the function "dist" to the hierarchical clustering based on the package and function "hclust". There was employed the agglomerative method with "ward.D2". The fold change and the protein–protein interactions provided by information from the String database [154] was used to explore the biological interactions of proteins identified as differentially abundant between control and cells treated with *B. jararaca* venom using the *Homo sapiens* reference genome.
