Progression to type 1 diabetes in the DPT-1 and TN07 clinical trials is critically associated with specific residues in HLA-DQA1-B1 heterodimers.

Aims/hypothesis: The aim of this work was to explore molecular amino acids (AAs) and related structures of HLA-DQA1-DQB1 that underlie its contribution to the progression from stages 1 or 2 to stage 3 type 1 diabetes.

Methods: Using high-resolution DQA1 and DQB1 genotypes from 1216 participants in the Diabetes Prevention Trial-Type 1 and the Diabetes Prevention Trial, we applied hierarchically organised haplotype association analysis (HOH) to decipher which AAs contributed to the associations of DQ with disease and their structural properties. HOH relied on the Cox regression to quantify the association of DQ with time-to-onset of type 1 diabetes.

HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07).

Objective: To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D).

Research Design And Methods: Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed.

Conformational Morphing by a DNA Analogue Featuring 7-Deazapurines and 5-Halogenpyrimidines and the Origins of Adenine-Tract Geometry.

Several efforts are currently directed at the creation and cellular implementation of alternative genetic systems composed of pairing components that are orthogonal to the natural dA/dT and dG/dC base pairs. In an alternative approach, Watson-Crick-type pairing is conserved, but one or all of the four letters of the A, C, G, and T alphabet are substituted by modified components. Thus, all four nucleobases were altered to create halogenated deazanucleic acid (DZA): dA was replaced by 7-deaza-2'-deoxyadenosine (dzA), dG by 7-deaza-2'-deoxyguanosine (dzG), dC by 5-fluoro-2'-deoxycytidine (FdC), and dT by 5-chloro-2'-deoxyuridine (CldU).

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

Importance: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies.

Objective: To develop a haplotype-based artificial intelligence (HAI) model for identifying novel variants, including mixture variants (MVs) of known variants and new variants with novel mutations.

Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy.

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.

Application of Statistical Learning to Identify Omicron Mutations in SARS-CoV-2 Viral Genome Sequence Data From Populations in Africa and the United States.

Importance: With timely collection of SARS-CoV-2 viral genome sequences, it is important to apply efficient data analytics to detect emerging variants at the earliest time.

Objective: To evaluate the application of a statistical learning strategy (SLS) to improve early detection of novel SARS-CoV-2 variants using viral sequence data from global surveillance.

Design, Setting, And Participants: This case series applied an SLS to viral genomic sequence data collected from 63 686 individuals in Africa and 531 827 individuals in the United States with SARS-CoV-2.

Cryo neutron crystallography demonstrates influence of RNA 2'-OH orientation on conformation, sugar pucker and water structure.

The ribose 2'-hydroxyl is the key chemical difference between RNA and DNA and primary source of their divergent structural and functional characteristics. Macromolecular X-ray diffraction experiments typically do not reveal the positions of hydrogen atoms. Thus, standard crystallography cannot determine 2'-OH orientation (H2'-C2'-O2'-HO2' torsion angle) and its potential roles in sculpting the RNA backbone and the expansive fold space.

Rapidly Identifying New Coronavirus Mutations of Potential Concern in the Omicron Variant Using an Unsupervised Learning Strategy.

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p-value=9.

Mutations in viral nucleocapsid protein and endoRNase are discovered to associate with COVID19 hospitalization risk.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients ("cases") and 295 outpatients ("controls") from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020-March 2021) Using a Statistical Learning Strategy.

The emergence and establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest (VOIs) and variants of concern (VOCs) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from coronavirus disease 2019 (COVID-19) cases in the United States (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from 19 January 2020 to 15 March 2021.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 - 2021/03) Using a Statistical Learning Strategy.

The emergence and establishment of SARS-CoV-2 variants of interest (VOI) and variants of concern (VOC) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from US COVID-19 cases (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from January 19, 2020 to March 15, 2021.

The KAG motif of HLA-DRB1 (β71, β74, β86) predicts seroconversion and development of type 1 diabetes.

Background: HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated.

Methods: We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D.

Incorporating a Thiophosphate Modification into a Common RNA Tetraloop Motif Causes an Unanticipated Stability Boost.

GNRA (N = A, C, G, or U; R = A or G) tetraloops are common RNA secondary structural motifs and feature a phosphate stacked atop a nucleobase. The rRNA sarcin/ricin loop (SRL) is capped by ApGA, and the phosphate p stacks on . We recently found that regiospecific incorporation of a single dithiophosphate (PS2) but not a monothiophosphate (PSO) instead of phosphate in the backbone of RNA aptamers dramatically increases the binding affinity for their targets.

Enhanced Dispersion and Polarization Interactions Achieved through Dithiophosphate Group Incorporation Yield a Dramatic Binding Affinity Increase for an RNA Aptamer-Thrombin Complex.

Regiospecific replacement of a single phosphate (PO2) by a dithiophosphate (PS2) group in an RNA can dramatically increase its binding affinity for a target protein. Thus, complexes between antithrombin and anti-VEGF RNA aptamers with single dithiophosphate moieties and thrombin and VEGF, respectively, display equilibrium dissociation constants K of ca. 1 pM, 1000-fold tighter than the native RNA complexes (ca.

Molecular Dynamics Simulation of Cyclooxygenase-2 Complexes with Indomethacin closo-Carborane Analogs.

Molecular dynamics simulation of carborane-containing ligands in complex with target enzymes is a challenging task due to the unique structure and properties of the carborane substituents and relative lack of appropriate experimental data to help assess the quality of carborane force field parameters. Here, we report results from energy minimization calculations for a series of carborane-amino acid complexes using carborane force field parameters published previously in the literature and adapted for use with the AMBER ff99SB and ff14SB potential functions. These molecular mechanics results agree well with quantum mechanical geometry optimization calculations obtained using dispersion-corrected density functional theory methods, suggesting that the carborane force field parameters should be suitable for more detailed calculations.

Molecular Modeling of the Interactions between Carborane-Containing Analogs of Indomethacin and Cyclooxygenase-2.

Molecular modeling studies were performed in order to gain insight into the binding mode and interaction of carborane-containing derivatives of indomethacin methyl ester with the cyclooxygenase-2 (COX-2) isoform, and to assess the predictive capability of the computational tools available for studying carboranes, a unique class of pharmacophores. Docking simulations were able to identify the correct binding mode and reproduced the experimental binding affinity trends with encouraging quality. Nevertheless, the docking results needed to be verified through extensive and resource-intensive quantum chemical calculations, and the interpretation of the theoretical results would not have been straightforward without the supporting experimental data.

A Streptavidin Binding Site Mutation Yields an Unexpected Result: An Ionized Asp128 Residue Is Not Essential for Strong Biotin Binding.

We report a detailed study of a point mutation of the crucial binding site residue, D128, in the biotin-streptavidin complex. The conservative substitution, D128N, preserves the detailed structure observed for the wild-type complex but has an only minimal impact on biotin binding, even though previous experimental and computational studies suggested that a charged D128 residue was crucial for high-affinity binding. These results show clearly that the fundamental basis for streptavidin's extremely strong biotin binding affinity is more complex than assumed and illustrate some of the challenges that may arise when analyzing extremely strong ligand-protein binding interactions.

Evoking picomolar binding in RNA by a single phosphorodithioate linkage.

RNA aptamers are synthetic oligonucleotide-based affinity molecules that utilize unique three-dimensional structures for their affinity and specificity to a target such as a protein. They hold the promise of numerous advantages over biologically produced antibodies; however, the binding affinity and specificity of RNA aptamers are often insufficient for successful implementation in diagnostic assays or as therapeutic agents. Strong binding affinity is important to improve the downstream applications.

Conservative Secondary Shell Substitution In Cyclooxygenase-2 Reduces Inhibition by Indomethacin Amides and Esters via Altered Enzyme Dynamics.

The cyclooxygenase enzymes (COX-1 and COX-2) are the therapeutic targets of nonsteroidal anti-inflammatory drugs (NSAIDs). Neutralization of the carboxylic acid moiety of the NSAID indomethacin to an ester or amide functionality confers COX-2 selectivity, but the molecular basis for this selectivity has not been completely revealed through mutagenesis studies and/or X-ray crystallographic attempts. We expressed and assayed a number of divergent secondary shell COX-2 active site mutants and found that a COX-2 to COX-1 change at position 472 (Leu in COX-2, Met in COX-1) reduced the potency of enzyme inhibition by a series of COX-2-selective indomethacin amides and esters.

Characterization of the Lipid-Binding Site of Equinatoxin II by NMR and Molecular Dynamics Simulation.

Equinatoxin II (EqtII) is a soluble, 20 kDa pore-forming protein toxin isolated from the sea anemone Actinia equina. Although pore formation has long been known to occur in distinct stages, including monomeric attachment to phospholipid membranes followed by detachment of the N-terminal helical domain and oligomerization into the final pore assembly, atomistic-level detail of the protein-lipid interactions underlying these events remains elusive. Using high-resolution solution state NMR of uniformly-(15)N-labeled EqtII at the critical micelle concentration of dodecylphosphocholine, we have mapped the lipid-binding site through chemical shift perturbations.

Distance geometry protocol to generate conformations of natural products to structurally interpret ion mobility-mass spectrometry collision cross sections.

Ion mobility-mass spectrometry (IM-MS) allows the separation of ionized molecules based on their charge-to-surface area (IM) and mass-to-charge ratio (MS), respectively. The IM drift time data that is obtained is used to calculate the ion-neutral collision cross section (CCS) of the ionized molecule with the neutral drift gas, which is directly related to the ion conformation and hence molecular size and shape. Studying the conformational landscape of these ionized molecules computationally provides interpretation to delineate the potential structures that these CCS values could represent, or conversely, structural motifs not consistent with the IM data.

Automated structure refinement for a protein heterodimer complex using limited EPR spectroscopic data and a rigid-body docking algorithm: a three-dimensional model for an ankyrin-CDB3 complex.

We report here specialized functions incorporated recently in the rigid-body docking software toolkit TagDock to utilize electron paramagnetic resonance derived (EPR-derived) interresidue distance measurements and spin-label accessibility data. The TagDock package extensions include a custom methanethiosulfonate spin label rotamer library to enable explicit, all-atom spin-label side-chain modeling and scripts to evaluate spin-label surface accessibility. These software enhancements enable us to better utilize the biophysical data routinely available from various spin-labeling experiments.

TagDock: an efficient rigid body docking algorithm for oligomeric protein complex model construction and experiment planning.

We report here new computational tools and strategies to efficiently generate three-dimensional models for oligomeric biomolecular complexes in cases where there is limited experimental restraint data to guide the docking calculations. Our computational tools are designed to rapidly and exhaustively enumerate all geometrically possible docking poses for an oligomeric complex, rather than generate detailed, atomic-resolution models. Experimental data, such as interatomic distance measurements, are then used to select and refine docking poses that are consistent with the experimental restraints.

Structural consequences of cutting a binding loop: two circularly permuted variants of streptavidin.

Circular permutation of streptavidin was carried out in order to investigate the role of a main-chain amide in stabilizing the high-affinity complex of the protein and biotin. Mutant proteins CP49/48 and CP50/49 were constructed to place new N-termini at residues 49 and 50 in a flexible loop involved in stabilizing the biotin complex. Crystal structures of the two mutants show that half of each loop closes over the binding site, as observed in wild-type streptavidin, while the other half adopts the open conformation found in the unliganded state.