Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure–activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein–nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.
In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron-microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modelling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril the side-chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-\beta structure of amyloid fibrils.
In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.
Purpose Genetic factors play an important role in the development of type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). However, few genetic association studies related to these disorders have been performed with Vietnamese subjects. In this study, the potential associations of ADIPOQ single nucleotide polymorphisms (SNPs) with T2DM and MetS in a Kinh Vietnamese population were investigated. Patients and Methods A study with 768 subjects was conducted to examine the associations of four ADIPOQ SNPs (rs266729, rs1501299, rs3774261, and rs822393) primarily with T2DM and secondarily with MetS. The TaqMan SNP genotyping assay was used to determine genotypes from subjects’ DNA samples. Results After statistical adjustment for age, sex, and body mass index, the ADIPOQ SNP rs266729 was found to be associated with increased risk of T2DM under multiple inheritance models: codominant (OR = 2.30, 95% CI = 1.16–4.58), recessive (OR = 2.17, 95% CI = 1.11–4.26), and log-additive (OR = 1.32, 95% CI = 1.02–1.70). However, rs1501299, rs3774261, and rs822393 were not associated with risk for T2DM. Additionally, rs266729, rs3774261, and rs822393 were statistically associated with MetS, while rs1501299 was not. Haplotype analysis showed a strong linkage disequilibrium between the SNP pairs rs266729/rs822393 and rs1501299/rs3774261, and the haplotype rs266729(G)/rs822393(T) was not statistically associated with MetS. Conclusion The results show that rs266729 is a lead candidate SNP associated with increased risk of developing T2DM and MetS in a Kinh Vietnamese population, while rs3774261 is associated with MetS only. Further functional characterization is needed to uncover the mechanism underlying the potential genotype–phenotype associations.
Type 2 diabetes mellitus (T2DM) is a genetically influenced disease, but few studies have been performed to investigate the genetic basis of T2DM in Vietnamese subjects. Thus, the potential associations of KCNJ11 and ABCC8 single nucleotide polymorphisms (SNPs) with T2DM were investigated in a Kinh Vietnamese population. A cross-sectional study consisting of 404 subjects including 202 T2DM cases and 202 non-T2DM controls was designed to examine the potential associations of 4 KCNJ11 and ABCC8 SNPs (rs5219, rs2285676, rs1799859, and rs757110) with T2DM. Genotypes were identified based on restriction fragment length polymorphism and tetra-primer amplification refractory mutation system polymerase chain reaction. After statistically adjusting for age, sex, and BMI, rs5219 was found to be associated with an increased risk of T2DM under 2 inheritance models: codominant (OR = 2.15, 95% confidence intervals [CI] = 1.09–4.22) and recessive (OR = 2.08, 95%CI = 1.09–3.94). On the other hand, rs2285676, rs1799859, and rs757110 were not associated with an increased risk of T2DM. Haplotype analysis elucidated a strong linkage disequilibrium between the 3 SNPs, rs5219, rs2285676, and rs757110. The haplotype rs5219(A)/rs2285676(T)/rs757110(G) was associated with an increased risk of T2DM (OR = 1.42, 95%CI = 1.01–1.99). The results show that rs5219 is a lead candidate SNP associated with an increased risk of developing T2DM in the Kinh Vietnamese population. Further functional characterization is needed to uncover the mechanism underlying the potential genotype-phenotype associations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.