More Like this

1. Congenital heart disease missense mutations in the TBX5 DNA-binding domain alter thermal stability and DNA-binding affinity

   https://doi.org/10.1093/g3journal/jkaf174  

   Rivera-Madera, Alejandro; Peña-Martínez, Edwin G; Messon-Bird, Jean L; Pomales-Matos, Diego A; Echevarría-Bonilla, Oswaldo L; Sanabria-Alberto, Leandro; Peterson-Peguero, Esther A; Rodríguez-Martínez, José A (August 2025, G3: Genes, Genomes, Genetics)

   Sampath, K (Ed.)

   Missense mutations can alter the biochemical properties of proteins, including stability, structure, and function, potentially contributing to the development of multiple human diseases. Mutations in TBX5, a transcription factor necessary for heart development, are among the causes of congenital heart diseases. However, further research on biophysical and biochemical mechanisms is needed to understand how missense mutations in transcription factors alter their function in regulating gene expression. In this work, we applied in vitro and in silico approaches to understand how 5 missense mutations in the TBX5 T-box DNA-binding domain (I54T, M74V, I101F, R113K, and R237W) impact protein structure, thermal stability, and DNA-binding affinity to known TBX5 cognate binding sites. Differential scanning fluorimetry showed that mutants I54T and M74V had decreased thermal stability, mutants I101F and R113K had increased stability, and R237W had no significant effect on stability. Additionally, DNA-binding affinity decreased for all 5 missense mutants when evaluated in vitro for known TBX5 genomic binding sites within regulatory elements of Nppa and Camta1 genes. Structural modeling of the TBX5 predicted altered protein conformations and stability due to the loss or gain of amino acid residue interactions. Together, our findings provide biophysical and biochemical mechanisms that can be further explored to establish causality between TBX5 missense mutations and the development of congenital heart diseases. 

   more » « less
2. Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs

   https://doi.org/10.1093/bib/bbac187  

   Sen, Neeladri; Anishchenko, Ivan; Bordin, Nicola; Sillitoe, Ian; Velankar, Sameer; Baker, David; Orengo, Christine (July 2022, Briefings in Bioinformatics)

   Abstract Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein–protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models. 

   more » « less
3. Computational Mutagenesis of GPx7 and GPx8: Structural and Stability Insights into Rare Genetic and Somatic Missense Mutations and Their Implications for Cancer Development

   https://doi.org/10.3390/cancers17010105  

   Sobitan, Adebiyi; Buhari, Nosimot; Youssri, Zainab; Wen, Fayuan; Kidane, Dawit; Teng, Shaolei (December 2024, Cancers)

   Background/Objectives: Somatic and genetic mutations in glutathione peroxidases (GPxs), including GPx7 and GPx8, have been linked to intellectual disability, microcephaly, and various tumors. GPx7 and GPx8 evolved the latest among the GPx enzymes and are present in the endoplasmic reticulum. Although lacking a glutathione binding domain, GPx7 and GPx8 possess peroxidase activity that helps the body respond to cellular stress. However, the protein mutations in these peroxidases remain relatively understudied. Methods: By elucidating the structural and stability consequences of missense mutations, this study aims to provide insights into the pathogenic mechanisms involved in different cancers, thereby aiding clinical diagnosis, treatment strategies, and the development of targeted therapies. We performed saturated computational mutagenesis to analyze 2926 and 3971 missense mutations of GPx7 and GPx8, respectively. Results: The results indicate that G153H and G153F in GPx7 are highly destabilizing, while E93M and W142F are stabilizing. In GPx8, N74W and G173W caused the most instability while S70I and S119P increased stability. Our analysis shows that highly destabilizing somatic and genetic mutations are more likely pathogenic compared to stabilizing mutations. Conclusions: This comprehensive analysis of missense mutations in GPx7 and GPx8 provides critical insights into their impact on protein structure and stability, contributing to a deeper understanding of the roles of somatic mutations in cancer development and progression. These findings can inform more precise clinical diagnostics and targeted treatment approaches for cancers. 

   more » « less
4. Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants

   https://doi.org/10.1371/journal.pcbi.1010006  

   Ose, Nicholas J.; Butler, Brandon M.; Kumar, Avishek; Kazan, I. Can; Sanderford, Maxwell; Kumar, Sudhir; Ozkan, S. Banu (April 2022, PLOS Computational Biology)

   Wallqvist, Anders (Ed.)

   Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor fall in any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for pathogenesis. In this study, we present an analysis of 591 pathogenic missense variants in 144 human enzymes that suggests that allosteric dynamic coupling of mutated positions with known active sites is a plausible biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of β-Glucocerebrosidase (GCase) in which a vast majority of 94 sites harboring Gaucher disease-associated missense variants are located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling caused by missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease. 

   more » « less
5. Systemic effects of missense mutations on SARS-CoV-2 spike glycoprotein stability and receptor-binding affinity

   https://doi.org/10.1093/bib/bbaa233  

   Teng, Shaolei; Sobitan, Adebiyi; Rhoades, Raina; Liu, Dongxiao; Tang, Qiyi (March 2021, Briefings in Bioinformatics)

   null (Ed.)

   Abstract The spike (S) glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the binding to the permissive cells. The receptor-binding domain (RBD) of SARS-CoV-2 S protein directly interacts with the human angiotensin-converting enzyme 2 (ACE2) on the host cell membrane. In this study, we used computational saturation mutagenesis approaches, including structure-based energy calculations and sequence-based pathogenicity predictions, to quantify the systemic effects of missense mutations on SARS-CoV-2 S protein structure and function. A total of 18 354 mutations in S protein were analyzed, and we discovered that most of these mutations could destabilize the entire S protein and its RBD. Specifically, residues G431 and S514 in SARS-CoV-2 RBD are important for S protein stability. We analyzed 384 experimentally verified S missense variations and revealed that the dominant pandemic form, D614G, can stabilize the entire S protein. Moreover, many mutations in N-linked glycosylation sites can increase the stability of the S protein. In addition, we investigated 3705 mutations in SARS-CoV-2 RBD and 11 324 mutations in human ACE2 and found that SARS-CoV-2 neighbor residues G496 and F497 and ACE2 residues D355 and Y41 are critical for the RBD–ACE2 interaction. The findings comprehensively provide potential target sites in the development of drugs and vaccines against COVID-19. 

   more » « less