Abstract
Ras proteins play a pivotal role as oncogenes by participating in diverse signaling events, including those linked to cell growth, differentiation, and proliferation. Using experimental fitness data and implementing artificial intelligence and a computational mutagenesis technique, we developed models that reliably predict fitness for all single residue mutants of H-ras proto-oncogene protein p21. The computational mutagenesis generated a feature vector of protein structural changes for each variant, and these data correlated well with fitness. Random forest classification and tree regression machine learning algorithms were implemented for training predictive models. Cross-validations were used to evaluate model performance, and control experiments were performed to assess statistical significance. Classification models revealed a balanced accuracy rate as high as 82%, with a Matthew's correlation of 0.63, and an area under ROC curve of 0.90. Similarly, regression models displayed Pearson's correlation reaching 0.79. On the other hand, control data sets led to performance values consistent with random guessing. Comparisons with several related state-of-the-art methods reflected favorably on our trained models. This H-Ras proof-of-principle study suggests a complementary approach for understanding mechanisms with which other proteins are involved in oncogenesis, including related Ras isoforms, and for providing useful insights into designing future diagnostic and treatment modalities.
Highlights
Among the class of small GTPase molecules driving cell signaling pathways in the cellular architecture of all organisms, the p21 Ras proteins provide an essential role with respect to cellular proliferation, differentiation, and apoptosis (Pai et al, 1990; Rosnizeck et al, 2010)
The structurally related human Ras isoforms (N– K- and H-Ras) obtained through alternative splicing events are the products of proto-oncogenes found in up to 30% of human tumors, with rates reaching as high as 90% for pancreatic cancer (Coppe et al, 2018; Mattingly, 2013; Mo et al, 2018; Rosnizeck et al, 2010; Simanshu et al, 2017)
For any mutant defined by amino acid residue substitution(s) at one or more positions in the wild type protein, the methodology computes the overall change to protein sequence-structure compatibility and quantifies environmental perturbation (EP) scores for all residue positions in the protein, with the latter forming a vector of EP scores
Summary
Among the class of small GTPase molecules driving cell signaling pathways in the cellular architecture of all organisms, the p21 Ras proteins provide an essential role with respect to cellular proliferation, differentiation, and apoptosis (Pai et al, 1990; Rosnizeck et al, 2010). Wild type Ras acts as a molecular switch, cycling between the active (ON) and inactive (OFF) conformational states when complexed to guanosine triphosphate (GTP) and guanosine diphosphate (GDP), respectively (Pai et al, 1990; Simanshu et al, 2017). Mutant Ras proteins isolated from human tumors are found to remain trapped in the active conformation bound to GTP due to the inability of GAP to recycle them quickly enough to the inactive GDP bound form (Pai et al, 1990; Rosnizeck et al, 2010)
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