Precision medicine review: rare driver mutations and their biophysical classification

Abstract

How can biophysical principles help precision medicine identify rare driver mutations? A major tenet of pragmatic approaches to precision oncology and pharmacology is that driver mutations are very frequent. However, frequency is a statistical attribute, not a mechanistic one. Rare mutations can also act through the same mechanism, and as we discuss below, Blatent driver^mutations may also follow the same route, with Bhelper^mutations. Here, we review how biophysics provides mechanistic guidelines that extend precision medicine. We outline principles and strategies, especially focusing on mutations that drive cancer. Biophysics has contributed profoundly to deciphering biological processes. However, driven by data science, precision medicine has skirted some of its major tenets. Data science embodies genomics, tissue-and cell-specific expression levels, making it capable of defining genome-and systems-wide molecular disease signatures. It classifies cancer driver genes/mutations and affected pathways, and its associated protein structural data guide drug discovery. Biophysics complements data science. It considers structures and their heterogeneous ensembles, explains how mutational variants can signal through distinct pathways, and how allo-network drugs can be harnessed. Biophysics clarifies how one mutation-frequent or rare-can affect multiple phenotypic traits by populating conformations that favor interactions with other network modules. It also suggests how to identify such mutations and their signaling consequences. Biophysics offers principles and strategies that can help precision medicine push the boundaries to transform our insight into biological processes and the practice of personalized medicine. By contrast, Bphenotypic drug discovery,^which capitalizes on physiological cellular conditions and first-in-class drug discovery, may not capture the proper molecular variant. This is because variants of the same protein can express more than one phenotype, and a phenotype can be encoded by several variants.

A Pan-Cancer assessment of alterations of the kinase domain of ULK1, an upstream regulator of autophagy

“…Despite the large number of X-ray structures of the ULK1 kinase domain, no extensive molecular dynamics (MD) simulation studies of the protein have been undertaken. The availability of a conformational ensemble of a protein is of paramount importance to better understand its function and the effects of its alterations due to mutations [41][42][43][44]. We thus used all-atom and coarse-grain models to obtain an ensemble of conformations and account for ULK1 flexibility and dynamics.…”

2019—A year in Biophysical Reviews

“…Edited by Assoc. Prof. Joshua Ho and Dr. Eleni Giannoulatou (Ho and Giannoulatou 2019) the Big Data Issue contained 16 contributions dealing with subjects as diverse as Bayesian statistical analysis (Yau and Campbell 2019), the dangers of using statistical tests rooted in the assumption of a normal distribution (Mar 2019), Hi-C analysis of interactions between genomic loci (Pal et al 2019), bioinformatics-based discovery of cancer causing mutations (Nussinov et al 2019), and machine learning in predicting cancer patient treatment outcomes (Mehreen and Aittokallio 2019).…”

Significant epitranscriptomes in heterogeneous cancer

“…In addition, in the process of cancer metastasis, the biological mechanism of epithelial‐mesenchymal transition (EMT) is controlled by epigenetic regulations rather than genetic events, suggesting a role of the transcriptional and epigenetic landscapes, and the gene regulatory network in controlling EMT states . In addition, it has been shown that focus on phenotypic drug development might not target the appropriate molecular variant in rare driver mutations, as variants of the same protein can express more than one phenotype . This indicates that a multifaceted understanding beyond genetics is required in order to ensure further precision in cancer research and medicine.…”