Amino Acid Position Research Articles

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Structural basis for the distinct roles of non-conserved Pro116 and conserved Tyr124 of BCH domain of yeast p50RhoGAP

p50RhoGAP is a key protein that interacts with and downregulates the small GTPase RhoA. p50RhoGAP is a multifunctional protein containing the BNIP-2 and Cdc42GAP Homology (BCH) domain that facilitates protein–protein interactions and lipid binding and the GAP domain that regulates active RhoA population. We recently solved the structure of the BCH domain from yeast p50RhoGAP (YBCH) and showed that it maintains the adjacent GAP domain in an auto-inhibited state through the β5 strand. Our previous WT YBCH structure shows that a unique kink at position 116 thought to be made by a proline residue between alpha helices α6 and α7 is essential for the formation of intertwined dimer from asymmetric monomers. Here we sought to establish the role and impact of this Pro116. However, the kink persists in the structure of P116A mutant YBCH domain, suggesting that the scaffold is not dictated by the proline residue at this position. We further identified Tyr124 (or Tyr188 in HBCH) as a conserved residue in the crucial β5 strand. Extending to the human ortholog, when substituted to acidic residues, Tyr188D or Tyr188E, we observed an increase in RhoA binding and self-dimerization, indicative of a loss of inhibition of the GAP domain by the BCH domain. These results point to distinct roles and impact of the non-conserved and conserved amino acid positions in regulating the structural and functional complexity of the BCH domain.

Reactivity of amino acids and short peptide sequences: identifying bioactive compounds via DFT calculations.

Bioactive peptides are short amino acid sequences that play important roles in various physiological processes, including antioxidant and protective effects. These compounds can be obtained through protein hydrolysis and have a wide range of potential applications in a variety of areas. However, despite the potential of these compounds, more in-depth knowledge is still necessary to better understand details regarding their chemical reactivity and electronic properties. In this study, we used molecular modeling techniques to investigate the electronic structure of isolated amino acids (AA) and short peptide sequences. Details on the relative alignments between the frontier electronic levels, local chemical reactivity and donor-acceptor properties of the 20 primary amino acids and some di- and tripeptides were evaluated in the framework of the density functional theory (DFT). Our results suggest that the electronic properties of isolated amino acids can be used to interpret the reactivity of short sequences. We found that aromatic and charged amino acids, as well as Methionine, play a key role in determining the local reactivity of peptides, in agreement with experimental data. Our analyses also allowed us to identify the influence of the relative position of AA and terminations on the local reactivity of the sequences, which can guide experimental studies and help to propose/evaluate possible mechanisms of action. In summary, our data indicate that the position of active sites of polypeptides can be predicted from short sequences, providing a promising strategy for the synthesis and bioprospection of new optimized compounds.

Phenomic landscape and pharmacogenomic implications for HLA region in a Taiwan Han Chinese population

BackgroundThe human leukocyte antigen (HLA) genes, exhibiting significant genetic diversity, are associated with susceptibility to various clinical diseases and diverse in drug responses. High costs of HLA sequencing and the population-specific architecture of this genetic region necessitate the establishment of a population-specific HLA imputation reference panel. Moreover, there is a lack of understanding about the genetic and phenotypic landscape of HLA variations within the Taiwanese population.MethodsWe created models for a Taiwanese-specific HLA imputation reference panel. These models were trained with the array genotype data and HLA sequencing data from 845 Taiwanese subjects. HLA imputation was applied for 59,448 Taiwanese subjects to characterize the HLA allele and haplotype frequencies. Additionally, a phenome-wide association study (PheWAS) was conducted to identify the phenotypes associated with HLA variations. The association of the biallelic HLA variants with the binary and quantitative traits were evaluated with additive logistic and linear regression models, respectively. Furthermore, an omnibus test with likelihood-ratio test was applied for each HLA amino acid position in the multiallelic HLA amino acid polymorphisms to compare the difference between a fitted model and a null model following a χ2 distribution of n-1 degree of freedom at a position with n residues. Finally, we estimated the prevalence of adverse drug reactions (ADR)-related HLA alleles in the Taiwanese population.ResultsIn this study, the reference panel models displayed remarkable accuracy, with averages of 99.3%, 98.9%, and 99.1% for 2-, 4-, 6-digit alleles of the eight classical HLA genes, respectively. For PheWAS, a total of 18,136 significant associations with HLA variants across 26 phenotypes are identified (p < 5×10-8), highlighting the pleiotropy feature of the HLA region. Among the independent signals, 15 are novel, including the association of HLA-B pos 138 variation with ankylosing spondylitis (AS), and rs9266290 and rs9266292 with allergy. Through an analysis spanning the entire HLA region, we identified clusters of phenotype correlations. Finally, the carriers of pharmacogenomic related HLA alleles, including HLA-C*01:02 (35.86%), HLA-B*58:01 (20.9%), and HLA-B*15:02 (8.38%), were characterized in the Taiwanese general population.ConclusionsWe successfully delivered the HLA imputation for 59,448 Taiwanese subjects and characterized the genetic and phenotypic landscapes of the HLA variations. In addition, we quantified the estimated prevalence of the ADR-related HLA alleles in the Taiwanese population. The developed HLA imputation reference panel could be used for estimation of population HLA allele frequencies, which can facilitate further studies in the role of HLA variants in a wider range of phenotypes in the population.

Ureibacillus aquaedulcis sp. nov., isolated from freshwater well and reclassification of Lysinibacillus yapensis and Lysinibacillus antri as Ureibacillus yapensis comb. nov. and Ureibacillus antri comb. Nov.

A Gram-stain-positive aerobic, rod-shaped, spore-producing bacterium forming colonies with convex elevation and a smooth, intact margin was isolated from a freshwater sample collected from a well situated in an agricultural field. The 16S rRNA gene sequence of the isolated strain BA0131T showed the highest sequence similarity to Lysinibacillus yapensis ylb-03T (99.25%) followed by Ureibacillus chungkukjangi 2RL3-2T (98.91%) and U. sinduriensis BLB-1T (98.65%). The strain BA0131T was oxidase and catalase positive and urease negative. It also tested positive for esculin hydrolysis and reduction of potassium nitrate, unlike its phylogenetically closest relatives. The predominant fatty acids in strain BA0131T included were anteiso-C15:0, iso-C16:0, iso-C15:0, iso-C14:0 and the major polar lipids comprised were phosphatidylglycerol, diphosphatidylglycerol and phosphatidylethanolamine. The respiratory quinones identified in strain BA0131T were MK8 (H2) (major) and MK8 (minor). The strain BA0131T shared the lowest dDDH values with L. yapensis ylb-03T (21%) followed by U. chungkukjangi 2RL3-2T (24.2%) and U. sinduriensis BLB-1T (26.4%) suggesting a closer genetic relationship U. sinduriensis BLB-1T. The ANI percentage supported the close relatedness with U. sinduriensis BLB-1T (83.61%) followed by U. chungkukjangi 2RL3-2T (82.03%) and U. yapensis ylb-03T (79.57%). The core genome-based phylogeny constructed using over 13,704 amino acid positions and 92 core genes revealed the distinct phylogenetic position of strain BA0131T among the genus Ureibacillus. The distinct physiological, biochemical characteristics and genotypic relatedness data indicate the strain BA0131T represents a novel species of the genus Ureibacillus for which the name Ureibacillus aquaedulcis sp. nov. (Type strain, BA0131T = MCC 5284 = JCM 36475) is proposed. Additionally, based on extensive genomic and phylogenetic analyses, we propose reclassification of two species, L. yapensis and L. antri, as U. yapensis comb. nov. (Type strain, ylb-03T = JCM 32871T = MCCC 1A12698T) and U. antri (Type strain, SYSU K30002T = CGMCC 1.13504T = KCTC 33955T).

Interpretable Prediction of SARS-CoV-2 Epitope-Specific TCR Recognition Using a Pre-Trained Protein Language Model.

The emergence of the novel coronavirus, designated as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has posed a significant threat to public health worldwide. There has been progress in reducing hospitalizations and deaths due to SARS-CoV-2. However, challenges stem from the emergence of SARS-CoV-2 variants, which exhibit high transmission rates, increased disease severity, and the ability to evade humoral immunity. Epitope-specific T-cell receptor (TCR) recognition is key in determining the T-cell immunogenicity for SARS-CoV-2 epitopes. Although several data-driven methods for predicting epitope-specific TCR recognition have been proposed, they remain challenging due to the enormous diversity of TCRs and the lack of available training data. Self-supervised transfer learning has recently been proven useful for extracting information from unlabeled protein sequences, increasing the predictive performance of fine-tuned models, and using a relatively small amount of training data. This study presents a deep-learning model generated by fine-tuning pre-trained protein embeddings from a large corpus of protein sequences. The fine-tuned model showed markedly high predictive performance and outperformed the recent Gaussian process-based prediction model. The output attentions captured by the deep-learning model suggested critical amino acid positions in the SARS-CoV-2 epitope-specific TCRβ sequences that are highly associated with the viral escape of T-cell immune response.

Therapeutic Intervention of Serine Protease Inhibitors against Hepatitis C Virus.

Hepatitis C virus (HCV) is a globally prevalent and hazardous disorder that is responsible for inducing several persistent and potentially fatal liver diseases. Current treatment strategies offer limited efficacy, often accompanied by severe and debilitating adverse effects. Consequently, there is an urgent and compelling need to develop novel therapeutic interventions that can provide maximum efficacy in combating HCV while minimizing the burden of adverse effects on patients. One promising target against HCV is the NS3-4A serine protease, a complex composed of two HCV-encoded proteins. This non-covalent heterodimer is crucial in the viral life cycle and has become a primary focus for therapeutic interventions. Although peginterferon, combined with ribavirin, is commonly employed for HCV treatment, its efficacy is hampered by significant adverse effects that can profoundly impact patients' quality of life. In recent years, the development of direct-acting antiviral agents (DAAs) has emerged as a breakthrough in HCV therapy. These agents exhibit remarkable potency against the virus and have demonstrated fewer adverse effects when combined with other DAAs. However, it is important to note that there is a potential for developing resistance to DAAs due to alterations in the amino acid position of the NS3-4A protease. This emphasizes the need for ongoing research to identify strategies that can minimize the emergence of resistance and ensure long-term effectiveness. While the combination of DAAs holds promise for HCV treatment, it is crucial to consider the possibility of drug-drug interactions. These interactions may occur when different DAAs are used concurrently, potentially compromising their therapeutic efficacy. Therefore, carefully evaluating and monitoring potential drug interactions are vital to optimize treatment outcomes. In the pursuit of novel therapeutic interventions for HCV, the field of computational biology and bioinformatics has emerged as a valuable tool. These advanced technologies and methodologies enable the development and design of new drugs and therapeutic agents that exhibit maximum efficacy, reduced risk of resistance, and minimal adverse effects. By leveraging computational approaches, researchers can efficiently screen and optimize potential candidates, accelerating the discovery and development of highly effective treatments for HCV, treatments.

Precision Vaccine Development: Unraveling the Immunoinformatics Code Against Epstein-Barr Virus's T41 Glycoprotein 350/220

Epstein-Barr Virus (EBV) poses a substantial global health threat, with a 90% morbidity rate in adults worldwide. Linked to infectious mononucleosis, autoimmune diseases, and cancers, there is an imperative for effective preventive measures, given the absence of current vaccines or medications. This study employs a bioinformatics strategy to design an epitope vaccine targeting EBV. The primary target for immunity is the EBV glycoprotein 350/220 (gp350), which mediates attachment to B cells through complement receptor 2 (CR2/CD21). The selected protein, EBV glycoprotein 350/220 was chosen based on its role in pathogenicity. In the post-therapeutic approach, three-dimensional structure prediction, validation, and verification processes were conducted, followed by molecular docking studies to identify potential drug-binding sites and suitable therapeutic inhibitors for the target protein. The protein's ability to stimulate humoral and cell-mediated immunity was assessed, leading to the identification of a peptide segment ATNLFLLEL from positions 342 to 356 as the predominant T cell epitope. This epitope demonstrated compatibility with various HLA profiles, enhanced by its interaction with eight HLA-A and HLA-B alleles. Population coverage analysis revealed broad responsiveness across geographies, suggesting its potential as a widely applicable vaccine component. Its non-allergic classification further supports its potential efficacy for diverse individuals. Docking studies with HLA-B*3501 confirmed its significant affinity for MHC-I molecules, establishing it as a promising vaccination candidate. Additionally, a region from amino acid positions 253 to 310 was identified as containing potential B-cell epitopes, with the sequence "LGAGELALTMRSKKLP" showing promise due to its antigenic potential. This computational approach to epitope-based peptide vaccine design and target site prediction against EBV represents a pioneering advancement in EBV virus research, emphasizing the need for validation through &lt;i&gt;in vitro&lt;/i&gt; and &lt;i&gt;in vivo&lt;/i&gt; trials.

The Significance of the 98th Amino Acid in GP2a for Porcine Reproductive and Respiratory Syndrome Virus Adaptation in Marc-145 Cells.

Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important pathogens in the pig industry. Marc-145 cells are widely used for PRRSV isolation, vaccine production, and investigations into virus biological characteristics. Despite their significance in PRRSV research, Marc-145 cells struggle to isolate specific strains of the North American virus genotype (PRRSV-2). The involvement of viral GP2a, GP2b, and GP3 in this phenomenon has been noted. However, the vital amino acids have not yet been identified. In this study, we increased the number of blind passages and successfully isolated two strains that were previously difficult to isolate with Marc-145 cells. Both strains carried an amino acid substitution in GP2a, specifically phenylalanine to leucine at the 98th amino acid position. Through a phylogenetic and epidemiologic analysis of 32 strains, those that were not amenable to isolation widely exhibited this mutation. Then, by using the PRRSV reverse genetics system, IFA, and Western blotting, we identified the mutation that could affect the tropism of PRRSV-2 for Marc-145 cells. Furthermore, an animal experiment was conducted. Through comparisons of clinical signs, mortality rates, and viral load in the organs and sera, we found that mutation did not affect the pathogenicity of PRRSV-2. In conclusion, our study firmly establishes the 98th amino acid in GP2a as a key determinant of PRRSV-2 tropism for Marc-145 cells.

Immune-Escape Mutations Are Prevalent among Patients with a Coexistence of HBsAg and Anti-HBs in a Tertiary Liver Center in the United States.

The concurrent seropositivity of HBsAg and anti-HBs has been described among patients with chronic hepatitis B (CHB), but its prevalence is variable. HBV S-gene mutations can affect the antigenicity of HBsAg. Patients with mutations in the 'α' determinant region of the S gene can develop severe HBV reactivation under immunosuppression. In this study at a tertiary liver center in the United States, we evaluated the frequency and virological characteristics of the HBsAg mutations among CHB patients with the presence of both HBsAg and anti-HBs. In this cohort, 45 (2.1%) of 2178 patients were identified to have a coexistence of HBsAg and anti-HBs, and 24 had available sera for the genome analysis of the Pre-S1, Pre-S2, and S regions. The frequency of mutations in the S gene was significantly higher among those older than 50 years (mean 8.5 vs. 5.4 mutations per subject, p = 0.03). Twelve patients (50%) had mutations in the 'α' determinant region of the S gene. Mutations at amino acid position 126 were most common in eight subjects. Three had a mutation at position 133. Only one patient had a mutation at position 145-the classic vaccine-escape mutation. Despite the universal HBV vaccination program, the vaccine-escape mutant is rare in our cohort of predominantly Asian patients.

Molecular characterization of the nonstructural 5A (NS5A) region of hepatitis C virus in Thai blood donors.

Direct acting antivirals (DAAs) have been developed for hepatitis C virus (HCV) therapy, and they are usually effective, however resistance to DAA regimens has also been reported to have a significant impact. Resistance associated substitutions (RASs) in the NS5A region are known to be correlated with failure of DAA therapy. HCV genotypes 3a and 1 are the most prevalent genotypes in Thailand. This study analyzed the type and frequency of RASs associated with DAA failure, focusing on the NS5A region. Serum samples of HCV genotype 3a, 1a, and 1b infection from Thai blood donors were selected. The NS5A region was amplified using reverse transcription-polymerase chain reaction (RT-PCR). A phylogenetic tree was constructed to identify the genotypes of HCV. Nucleotide sequencing and amino acid sequencing were conducted to determine the prevalence of RASs. Construction of the phylogenetic tree indicated that 29 samples were genotype 3a, 11 samples were genotype 1a, and 9 were genotype 1b. Both HCV genotypes 1a and 3a can be categorized into two subclades. Results showed that the NS5A substitutions A30V/K, A62T/V/I/M/P/S/L, and S98G were present in HCV genotype 3a. In HCV genotype 1a, only NS5A RASs H54Y was detected. NS5A amino acid substitutions Q54H and P58L were found in HCV genotype 1b. In conclusion, NS5A RASs at amino acid positions 30, 62, 54, 58, and 98 are present within HCV genotypes 3a and 1. While keeping in mind that additional information was not available on the anonymous blood donors tested in this study, these findings can contribute to understand the NS5A mutation. Further study with known patients under drug treatment is recommended.

Emergence of ceftazidime-avibactam resistance in blaKPC-33-harbouring ST11 Klebsiella pneumoniae in a paediatric patient

Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses immense threats to the health of infected patients worldwide, especially children. This study reports the infection caused by CRKP in a paediatric intensive care unit (PICU) child and its drug-resistant mutation during the treatment. Twelve Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae strains were isolated from the child. Broth microdilution method, plasmid transformation assay, and whole genome sequencing (WGS) were performed to investigate the antimicrobial susceptibility, resistance mechanisms, and genetic structural features of CRKPs. The results showed that 12 strains were highly resistant to most available antimicrobial agents. Among them, K. pneumoniae FD11 and K. pneumoniae FD12 were resistant to ceftazidime-avibactam (CZA, MIC >64 mg/L) and restored the carbapenem susceptibility (Imipenem, MIC =0.25 mg/L; Meropenem, MIC =2 mg/L). The patient improved after treatment with CZA in combination with aztreonam. Plasmid transformation assay demonstrated that the blaKPC-33-positive transformant increased MICs of CZA by at least 33-fold and 8-fold compared with the recipient Escherichia coli DH5α and blaKPC-2-positive transformants. WGS analysis revealed that all strains belonged to the ST11-KL64 type and showed highly homologous (3–26 single nucleotide polymorphisms [SNPs]). A single base mutation (G532T) of blaKPC-2 resulted in a tyrosine to aspartic acid substitution at Ambler amino acid position 179 (D179Y), which conferred CZA resistance in K. pneumoniae. This is the first report of a drug-resistant mutation evolving into blaKPC-33 during the treatment of blaKPC-2-positive CRKP in paediatric-infected patients. It advises clinicians that routine sequential antimicrobial susceptibility testing and KPC genotyping are critical during CZA therapy in children infected with CRKP.

Effect of limited hydrolysis with endopeptidase on bitterness properties of wheat gluten hydrolysates

The application of limited hydrolysis on wheat gluten (WG) has been found to be a highly effective method for improving a wide range of functional properties associated with plant protein. However, the bitter peptides formed during this process have an unpleasant bitterness. To provide a theoretical framework for de-bittering techniques, this study examined the modulation of bitterness intensity in wheat gluten hydrolysates (WGHs) by manipulating enzyme cleavage sites and degree of hydrolysis (DH). It was found that the bitter peptide's release content increased significantly, and the bitterness threshold decreased markedly with increasing DH. Furthermore, the structure-bitterness threshold association of bitter peptides was investigated. The results indicated that peptide segments in molecular weights (MW) from 500 to 1000 exhibited the greatest influence on bitterness threshold compared to peptides with other MWs. The percentage of total hydrophobic amino acid content and position of some hydrophobic amino acids in the amino acid sequence had a significant effect on the bitterness threshold. Finally, 47 peptides were identified by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. These peptides were mainly small peptides with less than 13 amino acid residues and MW below 1500 Da, and most of them had Q values higher than 5855 J/mol.

Combinatorial Approach with Mass Spectrometry and Lectin Microarray Dissected Site-Specific Glycostem and Glycoleaf Features of the Virion-Derived Spike Protein of Ancestral and γ Variant SARS-CoV-2 Strains.

The coronavirus disease (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has impacted public health globally. As the glycosylation of viral envelope glycoproteins is strongly associated with their immunogenicity, intensive studies have been conducted on the glycans of the glycoprotein of SARS-CoV-2, the spike (S) protein. Here, we conducted intensive glycoproteomic analyses of the SARS-CoV-2 S protein of ancestral and γ-variant strains using a combinatorial approach with two different technologies: mass spectrometry (MS) and lectin microarrays (LMA). Our unique MS1-based glycoproteomic technique, Glyco-RIDGE, in addition to MS2-based Byonic search, identified 1448 (ancestral strain) and 1785 (γ-variant strain) site-specific glycan compositions, respectively. Asparagine at amino acid position 20 (N20) is mainly glycosylated within two successive potential glycosylation sites, N17 and N20, of the γ-variant S protein; however, we found low-frequency glycosylation at N17. Our novel approaches, glycostem mapping and glycoleaf scoring, also illustrate the moderately branched/extended, highly fucosylated, and less sialylated natures of the glycoforms of S proteins. Subsequent LMA analysis emphasized the intensive end-capping of glycans by Lewis fucoses, which complemented the glycoproteomic features. These results illustrate the high-resolution glycoproteomic features of the SARS-CoV-2 S protein, contributing to vaccine design and understanding of viral protein synthesis.

PyCoM: a python library for large-scale analysis of residue-residue coevolution data.

Computational methods to detect correlated amino acid positions in proteins have become a valuable tool to predict intra- and inter-residue protein contacts, protein structures, and effects of mutation on protein stability and function. While there are many tools and webservers to compute coevolution scoring matrices, there is no central repository of alignments and coevolution matrices for large-scale studies and pattern detection leveraging on biological and structural annotations already available in UniProt. We present a Python library, PyCoM, which enables users to query and analyze coevolution matrices and sequence alignments of 457622 proteins, selected from UniProtKB/Swiss-Prot database (length ≤ 500 residues), from a precompiled coevolution matrix database (PyCoMdb). PyCoM facilitates the development of statistical analyses of residue coevolution patterns using filters on biological and structural annotations from UniProtKB/Swiss-Prot, with simple access to PyCoMdb for both novice and advanced users, supporting Jupyter Notebooks, Python scripts, and a web API access. The resource is open source and will help in generating data-driven computational models and methods to study and understand protein structures, stability, function, and design. PyCoM code is freely available from https://github.com/scdantu/pycom and PyCoMdb and the Jupyter Notebook tutorials are freely available from https://pycom.brunel.ac.uk.

De novo missense variants in exon 9 of SEPHS1 cause a neurodevelopmental condition with developmental delay, poor growth, hypotonia, and dysmorphic features

Selenophosphate synthetase (SEPHS) plays an essential role in selenium metabolism. Two mammalian SEPHS paralogues, SEPHS1 and SEPHS2, share high sequence identity and structural homology with SEPHS. Here, we report nine individuals from eight families with developmental delay, growth and feeding problems, hypotonia, and dysmorphic features, all with heterozygous missense variants in SEPHS1. Eight of these individuals had a recurrent variant at amino acid position 371 of SEPHS1 (p.Arg371Trp, p.Arg371Gln, and p.Arg371Gly); seven of these variants were known to be de novo. Structural modeling and biochemical assays were used to understand the effect of these variants on SEPHS1 function. We found that a variant at residue Trp352 results in local structural changes of the C-terminal region of SEPHS1 that decrease the overall thermal stability of the enzyme. In contrast, variants of a solvent-exposed residue Arg371 do not impact enzyme stability and folding but could modulate direct protein-protein interactions of SEPSH1 with cellular factors in promoting cell proliferation and development. In neuronal SH-SY5Y cells, we assessed the impact of SEPHS1 variants on cell proliferation and ROS production and investigated the mRNA expression levels of genes encoding stress-related selenoproteins. Our findings provided evidence that the identified SEPHS1 variants enhance cell proliferation by modulating ROS homeostasis. Our study supports the hypothesis that SEPHS1 plays a critical role during human development and provides a basis for further investigation into the molecular mechanisms employed by SEPHS1. Furthermore, our data suggest that variants in SEPHS1 are associated with a neurodevelopmental disorder.

Abstract 5814: EPriL macrocycles as a platform for the rapid generation of effective kinase degrader antibody conjugates (DACs)

Abstract The therapeutic success of antibody drug conjugates (ADCs) drives a continuous search for novel payloads that can increase therapeutic window and thereby widen the applications for ADCs. Recently, heterobifunctional degraders have gained great interest as payloads, and degrader antibody conjugates (DACs) are seen as a novel therapeutic modality. Heterobifunctional degraders consist of a small molecule ligand that binds a target (protein of interest or POI), a spacer and an E3 ligase ligand, which can catalyze target degradation. Owing to their catalytic activity, degraders can have better potency than the equivalent inhibitors, making them suitable as ADC payload [1]. Degrader payloads can target a wider variety of mechanisms than classic payloads, which use the same antitumor strategies as chemotherapy, such as tubulin binding or topoisomerase inhibition. Since many FDA-approved targeted therapies are based on the inhibition of protein kinases, we investigated degraders of these kinases as DAC payloads. Kinase DACs could bring enhanced targeting and therefore better therapeutic window to a field where classic ADC payloads have often shown substantial toxicities. As many heterobifunctional degraders show poor cell membrane penetration, their inhibitory potential could be increased as part of a DAC, where endocytic uptake is followed by intracellular release of the degrader payload. To identify kinase degrader payloads, we present a workflow based on a platform called Energetically Privileged Ligands (EPriLs). EPriLs are macrocycle scaffolds that bind non-covalently in the kinase ATP pocket. Their unique binding mode avoids contacts with amino acid positions where resistance to kinase inhibitors frequently occurs. EPriL macrocycles can be decorated appropriately to rationally design specific inhibitors for many therapeutically relevant kinases, and provide synthetic handles to couple them to VHL or CRBN ligands to generate effective kinase degraders. Here we describe how EPriL kinase degraders can be developed into effective DACs, using consecutive libraries of EPriL ligands, spacers, E3 ligase ligands and linkers. First, suitable degraders are identified, based on rapid and deep target degradation and potent antiproliferative activity on target cell lines. Degraders are then transformed into maleimide-linked degraders using convenient attachment of enzymatically cleavable linkers. In a medium throughput fashion, these maleimides are coupled to antibodies to generate DACs, which are tested for stability and biological potency. Applying this workflow to various well-validated kinase targets in oncology resulted in a promising kinase targeting DAC with favorable ADME properties, clear potentiation compared to the parent degrader, and increased selectivity for tumor cell lines. 1] Dragovich et al., Chem. Soc. Rev. (2022) 51, 3886-3897. Citation Format: Joost C. Uitdehaag, Jos e Man, Michelle Muller, Freek an Cauter, Sander an Gemert, Milan Hoffmann, Yvonne G. an Mil, Winfried R. Mulder, Martine B. Prinsen, Jan Gerard Sterrenburg, Diep Vu, Joeri e Wit, Erik Ensing, Rogier C. Buijsman. EPriL macrocycles as a platform for the rapid generation of effective kinase degrader antibody conjugates (DACs) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5814.

Abstract 5591: ARID domain containing BAF subunits exhibit neomorphism: Have we identified the new Achilles heel in cancer

Abstract The SWI/SNF chromatin remodeler utilizes energy of ATP hydrolysis to slide or evict nucleosomes or histones, respectively, thus enabling nuclear processes by driving an ‘open’ chromatin architecture. The mammalian SWI/SNF, also termed the BrG1/Brm associated factor (BAF) complex, is the major chromatin remodeler in ontogeny and adult life. Three major BAF complexes namely canonical (cBAF), polybromo (pBAF), and non-canonical (ncBAF) have been studied. BAF components, classified as a tumor suppressors, exhibit frequent mutations in cancers. Though, studies have evaluated functional roles of BAF subunits, very few attempted to study BAF mutations identified across cancer types. In our previous studies, we identified tumor specific mutations in the gene encoding ‘A-T rich interaction domain containing 1B’ (ARID1B), within its nuclear localization signal (NLS). NLS-inactivated ARID1B exhibited cytoplasmic localization and promoted tumorigenesis by activating the ERK and Wnt/β-catenin pathways. More recently, we detected inactivating mutations in the gene encoding ARID2, a component of the pBAF complex and an ARID1B paralogue. We now present detailed characterization of tumor-specific ARID2 truncations that were presumed to be inactivating in nature. One such truncation mutation viz. p.Ser989fsArg21*, identified in our previous study, is expected to yield an ARID2 protein truncating at amino acid position 1010 (as against the full length of 1835 amino acids). Scrutiny of The Cancer Genome Atlas cBioPortal and Cancer Cell Line Encyclopedia mutation data bases revealed several ARID2 mutations expected to truncate the protein around the 1010 position. Surprisingly, ectopic expression of truncated ARID2 forms promoted oncogenic function in both ARID2 proficient and deficient backgrounds, thus validating a neomorphic gain of function for the truncated protein. Fluorescence based intracellular localization assays revealed a surprising cytoplasmic localization of truncated ARID2. Further, we mapped the ARID2 NLS by in silico analysis followed by evaluation of several deletion constructs, to be located at 1488-1518 position; thus, explaining the cytoplasmic localization of ARID2 forms truncating around 1010 position. Further, truncated ARID2 was unable to bind other pBAF components and did not sequester other pBAF components to the cytoplasm, in both ARID2 proficient and deficient cells. Tandem Affinity Purification Mass-spectrometry revealed putative interaction partners for truncated ARID2; analysis is currently underway to reveal the mechanism of tumorigenic induction exhibited by truncated ARID2. Immunohistochemistry on colorectal and breast cancer tissue microarrays revealed ARID2 cytoplasmic localization in a significant fraction of samples. We have discovered a novel YIN-YANG function of BAF components expected to yield efficient therapeutic options in cancer. Citation Format: Sanjana Sarkar, Murali Dharan Bashyam. ARID domain containing BAF subunits exhibit neomorphism: Have we identified the new Achilles heel in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5591.

Association of HLA-DRB1 locus with treatment response to abatacept or TNF inhibitors in patients with seropositive rheumatoid arthritis

The strongest genetic risk factor for rheumatoid arthritis (RA) has been known as HLA-DRB1 based on amino acid positions 11, 71, and 74. This study analyzed the association between specific HLA-DRB1 locus and treatment response to abatacept or TNF inhibitors (TNFi) in patients with seropositive RA. A total of 374 Korean RA patients were treated with abatacept (n = 110) or TNFi (n = 264). Associations between HLA-DRB1 and treatment response after 6 months were analyzed using multivariable logistic regression. Seropositive RA patients with HLA-DRB1 shared epitope (SE) had a favorable response to abatacept (OR = 3.67, P = 0.067) and an inversely associated response to TNFi (OR 0.57, P = 0.058) based on EULAR response criteria, but the difference was not statistically significant in comparison to those without SE. In analyses using amino acid positions of HLA-DRB1, a significant association was found between valine at amino acid position 11 of SE and good response to abatacept (OR = 6.46, P = 5.4 × 10–3). The VRA haplotype also showed a good response to abatacept (OR = 4.56, P = 0.013), but not to TNFi. Our results suggest that treatment response to abatacept or TNFi may differ depending on HLA-DRB1 locus in seropositive RA, providing valuable insights for selecting optimal therapy.

Autoantibodes to GP210 are a metric for UDCA responses in primary biliary cholangitis

ObjectivesAntibodies to gp210 and sp100 are specific and unique anti-nuclear autoantibodies (ANAs) associated with primary biliary cholangitis (PBC). Importantly the presence of anti-gp210 and anti-sp100 responses is indicative of poor clinical outcomes. However, the utility of measuring titers of these antibodies remains unclear. Materials and methodsUsing the in-house purified gp210 (HSA108-C18) and sp100 (amino acid position 296–386), we quantitatively measured serum autoantibodies to gp210 and sp100 using chemiluminescence immunoassay (CLIA) in a very large cohort of 390 patients with PBC, including 259 cases with no prior ursodesoxycholic acid (UDCA) treatment and 131 cases with UDCA treatment. We also analyzed serial changes in anti-gp210 and anti-sp100 levels in 245 sequential samples from 88 patients. ResultsIn our cross-sectional analysis, we detected anti-gp210 immunoglobulin G (IgG) and anti-sp100 IgG autoantibodies in 129 out of 390 (33.1%) and 80 out of 390 (20.5%) PBC patients, respectively. Multivariate analysis revealed that serum IgG (st.β = 0.35, P = 0.003) and gamma-glutamyltransferase (GGT) (st.β = 0.23, P = 0.042) levels at baseline were independently associated with anti-gp210 concentrations. In serial testing, we observed significant fluctuations in anti-gp210 antibody levels. These fluctuations reflected responsiveness to UDCA therapy, particularly in anti-gp210-positive patients with initially lower concentrations in the stages of disease. ConclusionsOur study reflects that quantitative changes of anti-gp210 antibody are indicative of UDCA responses. There is a great need for newer metrics in PBC and we suggest that a more detailed and longer study of these unique ANAs is warranted.