RAG genomic variation causes autoimmune diseases through specific structure-based mechanisms of enzyme dysregulation.

Interpreting genetic changes observed in individual patients is a critical challenge. The array of immune deficiency syndromes is typically caused by genetic variation unique to individuals. Therefore, new approaches are needed to interpret functional variation and accelerate genomics interpretation. We constructed the first full-length structural model of human RAG recombinase across four functional states of the recombination process. We functionally tested 182 clinically observed RAG missense mutations. These experiments revealed dysfunction due to recombinase dysfunction and altered chromatin interactions. Structural modeling identified mechanical and energetic roles for each mutation. We built regression models for RAG1 (R2 = 0.91) and RAG2 (R2 = 0.97) to predict RAG activity changes. We applied our model to 711 additional RAG variants observed in population studies and identified a subset that may impair RAG function. Thus, we demonstrated a fundamental advance in the mechanistic interpretation of human genetic variations spanning from rare and undiagnosed diseases to population health.

Beyond Structural Bioinformatics for Genomics with Dynamics Characterization of an Expanded KRAS Mutational Landscape.

Current capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation.

Beyond structural bioinformatics for genomics with dynamics characterization of an expanded KRAS mutational landscape.

Current capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions. Because KRAS-altered tumors frequently harbor one of three classic hotspot mutations, nearly all studies have focused on these mutations, leaving significant functional ambiguity across the broader KRAS genomic landscape observed in cancer and non-cancer diseases. Herein, we extend structural bioinformatics with molecular simulations to study an expanded landscape of 86 KRAS mutations. We identify multiple coordinated changes strongly associated with experimentally established KRAS biophysical and biochemical properties. The patterns we observe span hotspot and non-hotspot alterations, which can all dysregulate Switch regions, producing mutation-restricted conformations with different effector binding propensities. We experimentally measured mutation thermostability and identified shared and distinct patterns with simulations. Our results indicate mutation-specific conformations, which show potential for future research into how these alterations reverberate into different molecular and cellular functions. The data we present is not predictable using current genomic tools, demonstrating the added functional information derived from molecular simulations for interpreting human genetic variation.