N-methyl-d-aspartate (NMDA) receptor genetics: The power of paralog homology and protein dynamics in defining dominant genetic variants.

Predicting genotype-to-phenotype correlations from genomic variants has been challenging, particularly for genes that have a complex balance of dominant and recessive inheritance for phenotypes. Variants in NMDA receptor components GRIN1, GRIN2A, and GRIN2B cause a myriad of dominant disease phenotypes, with the most common being epilepsy and autism spectrum disorder. Starting from the analysis of a variant of uncertain significance (VUS, GRIN2A G760S), we realized the need for tools to map dominant variants for the components of the NMDA receptor. Some variants within GRIN1, GRIN2A, and GRIN2B exert dominant epilepsy and developmental delay, yet other amino acid variants are conserved and predicted to alter protein function but do not have dominant phenotypes. Common variant annotation tools are not powered to determine pathogenic dominant outcomes. To address this gap, we integrated sequence and structural analyses for GRIN1, GRIN2A, and GRIN2B. Using this approach, we determined that paralog homology mapping and topology can segregate dominant variants, with an elevation of intermolecular contacts between the subunits. Furthermore, demonstrating the general utility of our methodology, we show that 25 VUS within ClinVar also reach a dominant variant annotation, including the GRIN2A G760S variant. Our work suggests paralog homology and protein topology as a powerful strategy within the receptor complex to resolve dominant genetic variants relative to variants that would fit a recessive inheritance, requiring two damaging variants. These strategies should be tested in additional dominant genetic disorders to determine the broader utility.

SARS-CoV-2 (COVID-19) structural and evolutionary dynamicome: Insights into functional evolution and human genomics.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has challenged the speed at which laboratories can discover the viral composition and study health outcomes. The small ∼30-kb ssRNA genome of coronaviruses makes them adept at cross-species spread while enabling a robust understanding of all of the proteins the viral genome encodes. We have employed protein modeling, molecular dynamics simulations, evolutionary mapping, and 3D printing to gain a full proteome- and dynamicome-level understanding of SARS-CoV-2. We established the Viral Integrated Structural Evolution Dynamic Database (VIStEDD at RRID:SCR_018793) to facilitate future discoveries and educational use. Here, we highlight the use of VIStEDD for nsp6, nucleocapsid (N), and spike (S) surface glycoprotein. For both nsp6 and N, we found highly conserved surface amino acids that likely drive protein-protein interactions. In characterizing viral S protein, we developed a quantitative dynamics cross-correlation matrix to gain insights into its interactions with the angiotensin I-converting enzyme 2 (ACE2)-solute carrier family 6 member 19 (SLC6A19) dimer. Using this quantitative matrix, we elucidated 47 potential functional missense variants from genomic databases within ACE2/SLC6A19/transmembrane serine protease 2 (TMPRSS2), warranting genomic enrichment analyses in SARS-CoV-2 patients. These variants had ultralow frequency but existed in males hemizygous for ACE2. Two ACE2 noncoding variants (rs4646118 and rs143185769) present in ∼9% of individuals of African descent may regulate ACE2 expression and may be associated with increased susceptibility of African Americans to SARS-CoV-2. We propose that this SARS-CoV-2 database may aid research into the ongoing pandemic.

SLC6A1 G443D associated with developmental delay and epilepsy.

SLC6A1 is associated with an autosomal dominant early-onset seizure and epileptic encephalopathy associated with intellectual disability. We present a 2-yr-old girl with developmental delay and epilepsy, using a new computational filtering impact score to show the patient's variant ranks with other pathogenic variants. Genomic studies within the patient revealed a G443D variant of uncertain significance. Structural and evolutionary assessments establish this variant as a loss of function to the protein. Compiled metrics through our custom tools on sequence, structure, and protein dynamics combined with PolyPhen-2, PROVEAN, SIFT, and Align-GVGD reveal this variant to rank in the top functional outcome changes relative to gnomAD, TOPMed, and ClinVar variants known to date. The patient was resistant to multiple epileptic drugs, finally finding that valproic acid controls the seizures. This is consistent with additional groups studying SLC6A1 variants within patients.

SARS-CoV2 (COVID-19) Structural/Evolution Dynamicome: Insights into functional evolution and human genomics.

The SARS-CoV-2 pandemic, starting in 2019, has challenged the speed at which labs perform science, ranging from discoveries of the viral composition to handling health outcomes in humans. The small ~30kb single-stranded RNA genome of Coronaviruses makes them adept at cross species spread and drift, increasing their probability to cause pandemics. However, this small genome also allows for a robust understanding of all proteins coded by the virus. We employed protein modeling, molecular dynamic simulations, evolutionary mapping, and 3D printing to gain a full proteome and dynamicome understanding of SARS-CoV-2. The Viral Integrated Structural Evolution Dynamic Database (VIStEDD) has been established (prokoplab.com/vistedd), opening future discoveries and educational usage. In this paper, we highlight VIStEDD usage for nsp6, Nucleocapsid (N), and Spike (S) surface glycoprotein. For both nsp6 and N we reveal highly conserved surface amino acids that likely drive protein-protein interactions. In characterizing viral S protein, we have developed a quantitative dynamics cross correlation matrix insight into interaction with the ACE2/SLC6A19 dimer complex. From this quantitative matrix, we elucidated 47 potential functional missense variants from population genomic databases within ACE2/SLC6A19/TMPRSS2, warranting genomic enrichment analyses in SARS-CoV-2 patients. Moreover, these variants have ultralow frequency, but can exist as hemizygous in males for ACE2, which falls on the X-chromosome. Two noncoding variants (rs4646118 and rs143185769) found in ~9% of African descent individuals for ACE2 may regulate expression and be related to increased susceptibility of African Americans to SARS-CoV-2. This powerful database of SARS-CoV-2 can aid in research progress in the ongoing pandemic.