Protein language model rescue mutations highlight variant effects and structure in clinically relevant genes. (arXiv:2211.10000v1 [cs.LG])

Despite being self-supervised, protein language models have shown remarkable
performance in fundamental biological tasks such as predicting impact of
genetic variation on protein structure and function. The effectiveness of these
models on diverse set of tasks suggests that they learn meaningful
representations of fitness landscape that can be useful for downstream clinical
applications. Here, we interrogate the use of these language models in
characterizing known pathogenic mutations in curated, medically actionable
genes through an exhaustive search of putative compensatory mutations …

arxiv effects genes highlight language language model protein