Sobitan, A. | Search bioRxiv

bioRxiv2025

Integrative Computational and Experimental Analysis of Curly Su Mutations in Drosophila melanogaster

The Curly Su (dMPO) protein, a homolog of the human myeloperoxidase (hMPO), is critical for wing development in Drosophila melanogaster. Like human peroxidases, dMPO is involved in various cellular and physiological processes, producing significant quantities of reactive oxygen species that contribute to both development and immunity in the fruit fly. Given the significant sequence and structural similarities between dMPO and hMPO, dMPO serves an ideal model for studying peroxidase functions and related pathologies. We performed saturated computational mutagenesis on dMPO, analyzing the effects of 11,191 missense mutations on its stability. Notably, the G378W mutation exhibited the greatest destabilizing effect, while the W621R, potentially pathogenic, also reduced dMPO stability. To investigate these effects in vivo, we used genome editing to generate the transgenic Drosophila with G378W, W621R, and deletion of residues 305-687. Remarkably, G378W mutants displayed significant alterations in wing morphology and reduced lifespan. RNA-seq analysis of transgenic and wild-type flies revealed differentially expressed genes (DEGs), as interpreted through gene ontology analysis. Our integrated computational and genetic approach identified dMPO mutations that disrupt protein stability and alter gene expression. These findings offer new insight into how single-point mutations can lead to systemic biological changes. Author SummaryProteins are the molecular machines that drive almost every process in living organisms, and even small genetic changes can disrupt their structure and function. In this study, we focused on Curly Su, a protein in fruit flies that is similar to human myeloperoxidase. We used a computational approach called saturation mutagenesis to model over 11,000 possible single mutations in the Curly Su protein and predict how they would affect its stability. We then used genome editing to introduce several destabilizing and potential disease-causing mutations into flies. These mutant flies developed abnormal wings, had shorter lifespans, and showed widespread changes in gene activity, particularly in metabolism and immune pathways. By combining computational predictions with experimental validation, our work demonstrates a powerful and generalizable strategy for linking specific genetic mutations to whole-organism outcomes. This approach not only sheds light on the biological role of Curly Su but also provides a framework that can be applied to other genes and organisms, offering insights relevant to human health and disease.

bioinformatics↗

bioRxiv2021

Computational saturation mutagenesis of SARS-CoV-1 spike glycoprotein: stability, binding affinity, and comparison with SARS-CoV-2

Severe Acute respiratory syndrome coronavirus (SARS-CoV-1) attaches to the host cell surface to initiate the interaction between the receptor-binding domain (RBD) of its spike glycoprotein (S) and the human Angiotensin-converting enzyme (hACE2) receptor. SARS-CoV-1 mutates frequently because of its RNA genome, which challenges the antiviral development. Here, we performed computational saturation mutagenesis of the S protein of SARS-CoV-1 to identify the residues crucial for its functions. We used the structure-based energy calculations to analyze the effects of the missense mutations on the SARS-CoV-1 S stability and the binding affinity with hACE2. The sequence and structure alignment showed similarities between the S proteins of SARS-CoV-1 and SARS-CoV-2. Interestingly, we found that target mutations of S protein amino acids generate similar effects on their stabilities between SARS-CoV-1 and SARS-CoV-2. For example, G839W of SARS-CoV-1 corresponds to G857W of SARS-CoV-2, which decrease the stability of their S glycoproteins. The viral mutation analysis of the two different SARS-CoV-1 isolates showed that mutations, T487S and L472P, weakened the S-hACE2 binding of the 2003-2004 SARS-CoV-1 isolate. In addition, the mutations of L472P and F360S destabilized the 2003-2004 viral isolate. We further predicted that many mutations on N-linked glycosylation sites would increase the stability of the S glycoprotein. Our results can be of therapeutic importance in the design of antivirals or vaccines against SARS-CoV-1 and SARS-CoV-2. Author SummarySevere acute respiratory syndrome coronavirus (SARS-CoV-1) is an RNA virus that undergoes frequent mutations, which may result in more virulent SARS-CoV-1 variants. To prevent another pandemic in the future, scientists must understand the mechanisms of viral mutations and predict if any variants could become a dominant. The infection of SARS-CoV-1 in cells is largely depending on the interactions of the viral Spike (S) and human angiotensin-converting enzyme 2 (hACE2). We applied a computational method to predict S missense mutations that will make SARS-CoV-1 more virulent. We are interested in the variants that can change SARS-CoV-1 spike protein stability and/or change the virus-receptor interactions. We mutated each residue of SARS-CoV-1 spike to all possible amino acids; we calculated the differences between the folding energy and binding energy of each variant and the wildtype and identified the target S mutations with significant effects on protein stability and protein-protein interaction. We found some viral mutations could destabilize S and weaken S-hACE2 binding of SARS-CoV-1 isolate. Our results show that the computational saturation mutagenesis is a reliable approach in the analysis and prediction of missense mutations.

bioinformatics↗