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Kuila, S.

Publications and source records attributed to Kuila, S..

4 recordsLinked to original sources

Cross-family interactions of vascular endothelial growth factors and platelet-derived growth factors on the endothelial cell surface: A computational model

Angiogenesis, the formation of new vessels from existing vessels, is mediated by vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). Despite discoveries supporting the cross-family interactions between VEGF and PDGF families, sharing the binding partners between them makes it challenging to identify growth factors that predominantly affect angiogenesis. Systems biology offers promises to untangle this complexity. Thus, in this study, we developed a mass-action kinetics-based computational model for cross-family interactions between VEGFs (VEGF-A, VEGF-B, and PlGF) and PDGFs (PDGF-AA, PDGF-AB, and PDGF-BB) with their receptors (VEGFR1, VEGFR2, NRP1, PDGFR, and PDGFR{beta}). The model, parametrized with our literature mining and surface resonance plasmon assays, was validated by comparing the concentration of VEGFR1 complexes with a previously constructed angiogenesis model. The model predictions include five outcomes: 1) the percentage of free or bound ligands and 2) receptors, 3) the concentration of free ligands, 4) the percentage of ligands occupying each receptor, and 5) the concentration of ligands that is bound to each receptor. We found that at equimolar ligand concentrations (1 nM), PlGF and VEGF-A were the main binding partners of VEGFR1 and VEGFR2, respectively. Varying the density of receptors resulted in the following five outcomes: 1) Increasing VEGFR1 density depletes the free PlGF concentration, 2) increasing VEGFR2 density decreases PDGF:PDGFR complexes, 3) increased NRP1 density generates a biphasic concentration of the free PlGF, 4) increased PDGFR density increases PDGFs:PDGFR binding, and 5) increasing PDGFR{beta} density increases VEGF-A:PDGFR{beta}. Our model offers a reproducible, fundamental framework for exploring cross-family interactions that can be extended to the tissue level or intracellular molecular level. Also, our model may help develop therapeutic strategies in pathological angiogenesis by identifying the dominant complex in the cell signaling. Author summaryNew blood vessel formation from existing ones is essential for growth, healing, and reproduction. However, when this process is disrupted--either too much or too little--it can contribute to diseases such as cancer and peripheral arterial disease. Two key families of proteins, vascular endothelial growth factors (VEGFs) and platelet-derived growth factors (PDGFs), regulate this process. Traditionally, scientists believed that VEGFs only bind to VEGF receptors and PDGFs to PDGF receptors. However, recent findings show that these proteins can interact with each others receptors, making it more challenging to understand and control blood vessel formation. To clarify these complex interactions, we combined computer modeling with biological data to map out which proteins bind to which receptors and to what extent. Our findings show that when VEGFs and PDGFs are present in equal amounts, VEGFs are the primary binding partners for VEGF receptors. We also explored how changes in receptor levels affect these interactions in disease-like conditions. This work provides a foundational computational model for studying cross-family interactions, which can be expanded to investigate tissue-level effects and processes inside cells. Ultimately, our model may help develop better treatments for diseases linked to abnormal blood vessel growth by identifying key protein-receptor interactions.

systems biology↗

Integrative analysis of angiogenic signaling in obesity: capillary features and VEGF binding kinetics

Obesity is a global health crisis, with its prevalence particularly severe in the United States, where over 42% of adults are classified as obese. Obesity is driven by complex molecular and tissue-level mechanisms that remain poorly understood. Among these, angiogenesis--primarily mediated by vascular endothelial growth factor (VEGF-A)--is critical for adipose tissue expansion but presents unique challenges for therapeutic targeting due to its intricate regulation. Systems biology approaches have advanced our understanding of VEGF-A signaling in vascular diseases, but their application to obesity is limited by scattered and sometimes contradictory data. To address this gap, we performed a comprehensive analysis of the existing literature to synthesize key findings, standardize data, and provide a holistic perspective on the adipose vascular microenvironment. The data mining revealed five key findings: (1) obesity increases adipocyte size by 78%; (2) vessel density in adipose tissue decreases by 51% in obese mice, with vessels being 47-58% smaller and 4-9 times denser in comparison with tumor vessels; (3) capillary basement membrane thickness remains similar regardless of obesity; (4) VEGF-A shows the strongest binding affinity for VEGFR1, with four times stronger affinity for VEGFR2 than for NRP1; and (5) binding affinities measured by radioligand binding assay and surface plasmon resonance (SPR) are significantly different. These consolidated findings provide essential parameters for systems biology modeling, new insights into obesity-induced changes in adipose tissue, and a foundation for developing angiogenesis-targeting therapies for obesity.

bioengineering↗

Understanding the effects of oxytocin receptor variants on OXT-OXT receptor binding: A mathematical model

Approximately half of U.S. women giving birth annually receive Pitocin, the synthetic form of oxytocin (OXT), yet its effective dose can vary significantly. This variability presents safety concerns due to unpredictable responses, which may lead to adverse outcomes for both mother and baby. To address the need for improved dosing, we developed a data-driven mathematical model to predict OXT receptor (OXTR) binding. Our study focuses on five prevalent OXTR variants (V45L, P108A, L206V, V281M, and E339K) and their impact on OXT-OXTR binding dynamics in two distinct cell types: human embryonic kidney cells (HEK293T), commonly used in experimental systems, and human myometrial smooth muscle cells, containing endogenous OXTR. We parameterized the model with cell-specific OXTR surface localization measurements. To strengthen the robustness of our study, we conducted a comprehensive meta-analysis of OXT- OXTR binding, enabling parameterization of our model with cell-specific OXT-OXTR binding kinetics (myometrial OXT-OXTR Kd = 1.6 nM, kon = 6.8 x 105 M-1 min-1, and koff = 0.0011 min-1). Our meta-analysis revealed significant homogeneity in OXT-OXTR affinity across experiments and species with a Kd = 0.52 - 9.32 nM and mean Kd = 1.48 {+/-} 0.36 nM. Our model achieves several valuable insights into designing dosage strategies. First, we predicted that the OXTR complex reaches maximum occupancy at 10 nM OXT in myometrial cells and at 1 {micro}M in HEK293T cells. This information is pivotal for guiding experimental design and data interpretation when working with these distinct cell types, emphasizing the need to consider effects for specific cell types when choosing OXTR-transfected cell lines. Second, our model recapitulated the significant effects of genetic variants for both experimental and physiologically relevant systems, with V281M and E339K substantially compromising OXT-OXTR binding capacity. These findings suggest the need for personalized oxytocin dosing based on individual genetic profiles to enhance therapeutic efficacy and reduce risks, especially in the context of labor and delivery. Third, we demonstrated the potential for rescuing the attenuated cell response observed in V281M and E339K variants by increasing the OXT dosage at specific, early time points. Cellular responses to OXT, including Ca2+ release, manifest within minutes. Our model indicates that providing V281M- and E339K-expressing cells with doubled OXT dose during the initial minute of binding can elevate OXT-OXTR complex formation to levels comparable to wild-type OXTR. In summary, our study provides a computational framework for precision oxytocin dosing strategies, paving the way for personalized medicine.

systems biology↗

Zinc2+ ion inhibits SARS-CoV-2 main protease and viral replication in vitro.

Zinc deficiency is linked to poor prognosis in COVID-19 patients while clinical trials with Zinc demonstrate better clinical outcome. The molecular target and mechanistic details of anti-coronaviral activity of Zinc remain obscure. We show that ionic Zinc not only inhibits SARS-CoV-2 main protease (Mpro) with nanomolar affinity, but also viral replication. We present the first crystal structure of Mpro-Zn2+ complex at 1.9 [A] and provide the structural basis of viral replication inhibition. We show that Zn2+ coordinates with the catalytic dyad at the enzyme active site along with two previously unknown water molecules in a tetrahedral geometry to form a stable inhibited Mpro-Zn2+ complex. Further, natural ionophore quercetin increases the anti-viral potency of Zn2+. As the catalytic dyad is highly conserved across SARS-CoV, MERS-CoV and all variants of SARS-CoV-2, Zn2+ mediated inhibition of Mpro may have wider implications.

biochemistry↗