DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability

Investigating druggable kinases for targeted therapy in retinoblastoma

Retinoblastoma (RB) is a childhood retinal neoplasm and commonly treated with cytotoxic chemotherapeutic agents. However, these therapeutic approaches often lead to diverse adverse effects. A precise molecular therapy will alleviate these side effects and offer better treatment outcomes. Over the years, kinases have become potential drug targets in cancer therapy. Hence, we aimed to investigate genetic alterations of putative kinase drug targets in RB. Targeted exome sequencing was performed on 35 RB tumors with paired blood samples using a gene panel consisting of 29 FDA-approved kinase genes. Single nucleotide variants were analyzed for pathogenicity using an in-house pipeline and copy number variations (CNVs) were detected by a depth of coverage and CNVPanelizer. The correlation between genetic changes and clinicopathological features was assessed using GraphPad Prism. Three somatic mutations, two in ERBB4 and one in EGFR were identified. Two of these mutations (ERBB4 c.C3836A & EGFR c.A1196T) were not reported earlier. CNV analysis revealed recurrent gains of ALK, MAP2K2, SRC, STK11, and FGFR3 as well as frequent losses of ATM, PI3KCA and ERBB4. Notably, nonresponsive tumors had a higher incidence of amplifications in clinically actionable genes such as ALK. Moreover, ALK gain and ATM loss were strongly correlated with optic nerve head invasion. In conclusion, our study revealed genetic alterations of druggable kinases in RB, providing preliminary insights for the exploration of kinase-targeted therapy in RB.

Impact of mutations in SARS-CoV-2 recombinant sub-variant XBB.1.16 on the binding affinity with human ACE2 receptor

Despite the waning threat of the COVID-19 pandemic, its detrimental impact on global health persists. Regardless of natural immunity or immunity obtained through vaccination, emerging variants of the virus continue to undergo mutations and propagate globally. The persistent mutations in SARS-CoV-2, along with the subsequent formation of recombinant sub-variants has become a challenge for researchers and health professionals, raising concerns about the efficacy of current vaccines. Gaining a better understanding of the biochemical interactions between the Spike Protein (RBD) of SARS-CoV-2 variants and the human ACE2 receptor can prove to be beneficial in designing and developing antiviral therapeutics that are equally effective against all strains and emerging variants. Our objective in this study was to investigate the interfacial binding pattern of the SARS-CoV-2 RBD-ACE2 complex of the Wild Type (WT), Omicron, and the Omicron recombinant sub-variant XBB.1.16. We aimed to examine the atomic level factors and observe how mutations influence the interaction between the virus and its host using Molecular Dynamics simulation, MM/GBSA energy calculations, and Principal Component Analysis. Our findings reveal a higher degree of structural deviation and flexibility in XBB.1.16 compared to WT and Omicron. PCA indicated a wider cluster and significant flexibility in the movements of XBB.1.16 which can also be observed in free energy landscapes, while the normal mode analysis revealed converging motions within the RBD-ACE2 complexes which can facilitate the interaction between them. A pattern of decreased binding affinity was observed in case of XBB.1.16 when compared to the WT and Omicron. These observed deviations in XBB.1.16 when compared to its parent lineage Omicron, and WT can be attributed to the mutations specific to it. Collectively, these results enhance our understanding of the impact of mutations on the interaction between this strain and the host, taking us one step closer to designing effective antiviral therapeutics against the continually mutating strains.

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors

BACKGROUND

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

RESULTS

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

CONCLUSIONS

VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method

BACKGROUND

Thermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure-function relationship, and is also of great interest in protein engineering and pharmaceutical design.

RESULTS

Here we present mutDDG-SSM, a deep learning-based framework that uses the geometric representations encoded in protein structure to predict the mutation-induced protein stability changes. mutDDG-SSM consists of two parts: a graph attention network-based protein structural feature extractor that is trained with a self-supervised learning scheme using large-scale high-resolution protein structures, and an eXtreme Gradient Boosting model-based stability change predictor with an advantage of alleviating overfitting problem. The performance of mutDDG-SSM was tested on several widely-used independent datasets. Then, myoglobin and p53 were used as case studies to illustrate the effectiveness of the model in predicting protein stability changes upon mutations. Our results show that mutDDG-SSM achieved high performance in estimating the effects of mutations on protein stability. In addition, mutDDG-SSM exhibited good unbiasedness, where the prediction accuracy on the inverse mutations is as well as that on the direct mutations.

CONCLUSION

Meaningful features can be extracted from our pre-trained model to build downstream tasks and our model may serve as a valuable tool for protein engineering and drug design.

Genetic and pathophysiological insights from autopsied patient with primary familial brain calcification: novel MYORG variants and astrocytic implications

Primary familial brain calcification (PFBC) is a genetic neurological disorder characterized by symmetric brain calcifications that manifest with variable neurological symptoms. This study aimed to explore the genetic basis of PFBC and elucidate the underlying pathophysiological mechanisms. Six patients from four pedigrees with brain calcification were enrolled. Whole-exome sequencing identified two novel homozygous variants, c.488G > T (p.W163L) and c.2135G > A (p.W712*), within the myogenesis regulating glycosidase (MYORG) gene. Cerebellar ataxia (n = 5) and pyramidal signs (n = 4) were predominant symptoms, with significant clinical heterogeneity noted even within the same family. An autopsy of one patient revealed extensive brainstem calcifications, sparing the cerebral cortex, and marked by calcifications predominantly in capillaries and arterioles. The pathological study suggested morphological alterations characterized by shortened foot processes within astrocytes in regions with pronounced calcification and decreased immunoreactivity of AQP4. The morphology of astrocytes in regions without calcification remains preserved. Neuronal loss and gliosis were observed in the basal ganglia, thalamus, brainstem, cerebellum, and dentate nucleus. Notably, olivary hypertrophy, a previously undescribed feature in MYORG-PFBC, was discovered. Neuroimaging showed reduced blood flow in the cerebellum, highlighting the extent of cerebellar involvement. Among perivascular cells constituting the blood-brain barrier (BBB) and neurovascular unit, MYORG is most highly expressed in astrocytes. Astrocytes are integral components of the BBB, and their dysfunction can precipitate BBB disruption, potentially leading to brain calcification and subsequent neuronal loss. This study presents two novel homozygous variants in the MYORG gene and highlights the pivotal role of astrocytes in the development of brain calcifications, providing insights into the pathophysiological mechanisms underlying PFBC associated with MYORG variants.

Enhanced molecular stability of ApxII antigen during secretion in Corynebacterium glutamicum by rational design

ApxII is a vaccine antigen used to protect against porcine contagious pleuropneumonia, which is a significant threat to the pig industry. Here, we aimed to improve the proteolytic degradation stability of ApxII during its secretion by establishing a complete screening process of stable variants through bioinformatics and site-directed mutagenesis. We employed a combination of semi-rational and rational design strategies to create 34 single-point variants of ApxII. Among them, R114E and T115D variants exhibited better stability without compromising antigen activity. Furthermore, we constructed a multi-site variant, R114E/T115D, which demonstrated the best stability, activity, and yield. Protein stability and molecular dynamic analysis indicated that the greater solubility and lower structural expansion coefficient might explain the increased stability of R114E/T115D. Additionally, site T115 was identified as a key point of truncated ApxII stability. The R114E/T115D variant, with its proven stability and intact antigenic activity, holds promising prospects for industrial-scale applications in the prevention of porcine contagious pleuropneumonia.

Preclinical alternative drug discovery programs for monogenic rare diseases. The case of hereditary spastic paraplegias

Patients diagnosed with rare diseases and their and families search desperately to organize drug discovery campaigns. Alternative models that differ from default paradigms offer real opportunities. There are, however, no clear guidelines for the development of such models, which reduces success rates and raises costs. We address the main challenges in making the discovery of new preclinical treatments more accessible, using rare hereditary paraplegia as a paradigmatic case. First, we discuss the necessary expertise, and the patients' clinical and genetic data. Then, we revisit gene therapy, de novo drug development, and drug repurposing, discussing their applicability. Moreover, we explore a pool of recommended in silico tools for pathogenic variant and protein structure prediction, virtual screening, and experimental validation methods, discussing their strengths and weaknesses. Finally, we focus on successful case applications.

Overcoming Resistance in Cancer Therapy: Computational Exploration of PIK3CA Mutations, Unveiling Novel Non-Toxic Inhibitors, and Molecular Insights Into Targeting PI3Kα

Phosphoinositide-3-kinases (PI3 K) are pivotal regulators of cell signaling implicated in various cancers. Particularly, mutations in the PIK3CA gene encoding the p110α catalytic subunit drive oncogenic signaling, making it an attractive therapeutic target. Our study conducted in silico exploration of 31 PIK3CA mutations across breast, endometrial, colon, and ovarian cancers, assessing their impacts on response to PI3Kα inhibitors and identifying potential non-toxic inhibitors and also elucidating their effects on protein stability and flexibility. Specifically, we observed significant alterations in the stability and flexibility of the PI3 K protein induced by these mutations. Through molecular docking analysis, we evaluated the binding interactions between the selected inhibitors and the PI3 K protein. The filtration of ligands involved calculating chemical descriptors, incorporating Veber and Lipinski rules, as well as IC50 values and toxicity predictions. This process reduced the initial dataset of 1394 ligands to 12 potential non-toxic inhibitors, and four reference inhibitors with significant biological activity in clinical trials were then chosen based on their physico-chemical properties. This analysis revealed Lig5's exceptional performance, exhibiting superior affinity and specificity compared to established reference inhibitors such as pictilisib. Lig5 formed robust binding interactions with the PI3 K protein, suggesting its potential as a highly effective therapeutic agent against PI3 K-driven cancers. Furthermore, molecular dynamics simulations provided valuable insights into Lig5's stability and its interactions with PI3 K over 100 ns. These simulations supported Lig5's potential as a versatile inhibitor capable of effectively targeting various mutational profiles of PI3 K, thereby mitigating issues related to resistance and toxicity commonly associated with current inhibitors.

In Silico Deciphering of the Potential Impact of Variants of Uncertain Significance in Hereditary Colorectal Cancer Syndromes

Colorectal cancer (CRC) ranks third in terms of cancer incidence worldwide and is responsible for 8% of all deaths globally. Approximately 10% of CRC cases are caused by inherited pathogenic mutations in driver genes involved in pathways that are crucial for CRC tumorigenesis and progression. These hereditary mutations significantly increase the risk of initial benign polyps or adenomas developing into cancer. In recent years, the rapid and accurate sequencing of CRC-specific multigene panels by next-generation sequencing (NGS) technologies has enabled the identification of several recurrent pathogenic variants with established functional consequences. In parallel, rare genetic variants that are not characterized and are, therefore, called variants of uncertain significance (VUSs) have also been detected. The classification of VUSs is a challenging task because each amino acid has specific biochemical properties and uniquely contributes to the structural stability and functional activity of proteins. In this scenario, the ability to computationally predict the effect of a VUS is crucial. In particular, in silico prediction methods can provide useful insights to assess the potential impact of a VUS and support additional clinical evaluation. This approach can further benefit from recent advances in artificial intelligence-based technologies. In this review, we describe the main in silico prediction tools that can be used to evaluate the structural and functional impact of VUSs and provide examples of their application in the analysis of gene variants involved in hereditary CRC syndromes.

Evolution, diversity, and function of the disease susceptibility gene Snn1 in wheat

Septoria nodorum blotch (SNB), caused by Parastagonospora nodorum, is a disease of durum and common wheat initiated by the recognition of pathogen-produced necrotrophic effectors (NEs) by specific wheat genes. The wheat gene Snn1 was previously cloned, and it encodes a wall-associated kinase that directly interacts with the NE SnTox1 leading to programmed cell death and ultimately the development of SNB. Here, sequence analysis of Snn1 from 114 accessions including diploid, tetraploid, and hexaploid wheat species revealed that some wheat lines possess two copies of Snn1 (designated Snn1-B1 and Snn1-B2) approximately 120 kb apart. Snn1-B2 evolved relatively recently as a paralog of Snn1-B1, and both genes have undergone diversifying selection. Three point mutations associated with the formation of the first SnTox1-sensitive Snn1-B1 allele from a primitive wild wheat were identified. Four subsequent and independent SNPs, three in Snn1-B1 and one in Snn1-B2, converted the sensitive alleles to insensitive forms. Protein modeling indicated these four mutations could abolish Snn1-SnTox1 compatibility either through destabilization of the Snn1 protein or direct disruption of the protein-protein interaction. A high-throughput marker was developed for the absent allele of Snn1, and it was 100% accurate at predicting SnTox1-insensitive lines in both durum and spring wheat. Results of this study increase our understanding of the evolution, diversity, and function of Snn1-B1 and Snn1-B2 genes and will be useful for marker-assisted elimination of these genes for better host resistance.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

Identification of a novel RHCE*Ce (829G > A) allele associated with absence of C and e antigens expression

BACKGROUND

The Rh blood group antigens are encoded by the RHD and RHCE genes, which possess a remarkable degree of polymorphism owing to their high homologous structures. These variants of the RH genes can lead to absence or weak expression of antigens.

METHODS

Analysis of RHCE genotyping by Polymerase Chain Reaction (PCR-SSP) method specific to detect c.48G, c.48C, 109 bp insertion of IVS2, c.201A and c.307C and RhCE phenotyping, were conducted in 316 Chinese patients in previous study. One patient with discrepancy typing result was collected for further RhCE serologic typing using microcolumn gel method and tube method in saline using monoclonal antibodies. PacBio sequencing was performed for RHCE, RHD and RHAG complete sequence analysis. 3D molecular models of the protein with the wild-type and mutant residue were generated using the DynaMut web server. The effect of the mutation on the protein function was predicted by PolyPhen-2 software.

RESULTS

One male patient of Chinese Han was detected with RHCE*C allele showed by PCR-SSP method but ccEE phenotype. Further PacBio sequencing identified one normal RHCE*cE allele and one RHCE*Ce allele carried a novel c.829G > A (p.Gly277Arg) variant, which the encoded amino acid located in the ninth transmembrane segment of RhCE protein. Crystallisation analysis of 3D molecular models revealed that the substitution at Arg277 leads to the formation of additional hydrogen bonds, including weak hydrogen bonds between multiple atoms. It also results in hydrophobic ion interactions between Arg277 and Ala244. This mutation is predicted to have a damaging effect on protein function.

CONCLUSION

One novel RHCE*Ce allele with c.829G > A (p.Gly277Arg) variant was identified to resulting in the absence or weak expression of C and e antigens.

Undetected Neuromuscular Disease in Patients after Heart Transplantation

(1) Heart transplantation (HTX) improves the overall survival and functional status of end-stage heart failure patients with cardiomyopathies (CMPs). The majority of CMPs have genetic causes, and the overlap between CMPs and inherited myopathies is well documented. However, the long-term outcome in skeletal muscle function and possibility of an undiagnosed underlying genetic cause of both a cardiac and skeletal pathology remain unknown. (2) Thirty-nine patients were assessed using open and standardized interviews on muscle function, a quality-of-life (EuroQol EQ-5D-3L) questionnaire, and a physical examination (Medical Research Council Muscle scale). Whole-exome sequencing was completed in three stages for those with skeletal muscle weakness. (3) Seven patients (17.9%) reported new-onset muscle weakness and motor limitations. Objective muscle weakness in the upper and lower extremities was seen in four patients. In three of them, exome sequencing revealed pathogenic/likely pathogenic variants in the genes encoding nexilin, myosin heavy chain, titin, and SPG7. (4) Our findings support a positive long-term outcome of skeletal muscle function in HTX patients. However, 10% of patients showed clinical signs of myopathy due to a possible genetic cause. The integration of genetic testing and standardized neurological assessment of motor function during the peri-HTX period should be considered.

Enhancing predictions of protein stability changes induced by single mutations using MSA-based Language Models

MOTIVATION

Protein Language Models offer a new perspective for addressing challenges in structural biology, while relying solely on sequence information. Recent studies have investigated their effectiveness in forecasting shifts in thermodynamic stability caused by single amino acid mutations, a task known for its complexity due to the sparse availability of data, constrained by experimental limitations. To tackle this problem, we introduce two key novelties: leveraging a Protein Language Model that incorporates Multiple Sequence Alignments to capture evolutionary information, and using a recently released mega-scale dataset with rigorous data pre-processing to mitigate overfitting.

RESULTS

We ensure comprehensive comparisons by fine-tuning various pre-trained models, taking advantage of analyses such as ablation studies and baselines evaluation. Our methodology introduces a stringent policy to reduce the widespread issue of data leakage, rigorously removing sequences from the training set when they exhibit significant similarity with the test set. The MSA Transformer emerges as the most accurate among the models under investigation, given its capability to leverage co-evolution signals encoded in aligned homologous sequences. Moreover, the optimized MSA Transformer outperforms existing methods and exhibits enhanced generalization power, leading to a notable improvement in predicting changes in protein stability resulting from point mutations.

AVAILABILITY AND IMPLEMENTATION

Code and data at https://github.com/RitAreaSciencePark/PLM4Muts.

SUPPLEMENTARY INFORMATION

Supplementary Information is available at Bioinformatics online.

Genetic landscape and clinical outcomes of autosomal recessive polycystic kidney disease in Kuwait

Background

Autosomal recessive polycystic kidney disease (ARPKD), a rare genetic disorder characterized by kidney cysts, shows complex clinical and genetic heterogeneity. This study aimed to explore the genetic landscape of ARPKD in Kuwait and examine the intricate relationship between its genes and clinical presentation to enhance our understanding and contribute towards more efficient management strategies for ARPKD.

Methods

This study recruited 60 individuals with suspected ARPKD from 44 different families in Kuwait. The participants were of different ethnicities and aged 0-70 years. Additionally, 33 were male, 15 were female, and 12 had indeterminant sex due to congenital anomalies. Comprehensive clinical data were collected. Mutations were identified by next-generation whole exome sequencing and confirmed using Sanger sequencing.

Results

Of the 60 suspected ARPKD cases, 20 (33.3 %) died within hours of birth or by the end of the first month of life and one (1.7 %) within 12 months of birth. The remaining 39 (65.0 %) cases were alive, at the time of the study, and exhibited diverse clinical features related to ARPKD, including systematic hypertension (5.0 %), pulmonary hypoplasia (11.7 %), dysmorphic features (40.0 %), cardiac problems (8.3 %), cystic liver (5.0 %), Potter syndrome (13.3 %), developmental delay (8.3 %), and enlarged cystic kidneys (100 %). Twelve mutations, including novel truncating mutations, were identified in 31/60 cases (51.7 %) from 17/44 families (38.6 %). Additionally, 8/12 (66.7 %) mutations were in the PKHD1 gene, with the remaining four in different genes: NPHP3, VPS13P, CC2D2A, and ZNF423.

Conclusions

This study highlights the spectrum of clinical features and genetic mutations of patients with ARPKD in Kuwait. It highlights the necessity for personalized approaches to improve ARPKD diagnosis and treatment, offering crucial insights into managing ARPKD.

MutationExplorer: a webserver for mutation of proteins and 3D visualization of energetic impacts

The possible effects of mutations on stability and function of a protein can only be understood in the context of protein 3D structure. The MutationExplorer webserver maps sequence changes onto protein structures and allows users to study variation by inputting sequence changes. As the user enters variants, the 3D model evolves, and estimated changes in energy are highlighted. In addition to a basic per-residue input format, MutationExplorer can also upload an entire replacement sequence. Previously the purview of desktop applications, such an upload can back-mutate PDB structures to wildtype sequence in a single step. Another supported variation source is human single nucelotide polymorphisms (SNPs), genomic coordinates input in VCF format. Structures are flexibly colorable, not only by energetic differences, but also by hydrophobicity, sequence conservation, or other biochemical profiling. Coloring by interface score reveals mutation impacts on binding surfaces. MutationExplorer strives for efficiency in user experience. For example, we have prepared 45 000 PDB depositions for instant retrieval and initial display. All modeling steps are performed by Rosetta. Visualizations leverage MDsrv/Mol*. MutationExplorer is available at: http://proteinformatics.org/mutation_explorer/.

Cefiderocol susceptibility endows hope in treating carbapenem-resistant Pseudomonas aeruginosa: insights from in vitro and in silico evidence

'High-risk' hypermutable clones of Pseudomonas aeruginosa disseminating extensive drug-resistance (XDR) have raised global health concerns with escalating mortality rates in immunocompromised patients. Mutations in conventional drug-targets under antibiotic stress necessitate structural understanding to formulate sustainable therapeutics. In the present study, the major β-lactam antibiotic target, penicillin-binding protein-3 (PBP3) with mutations F533L and T91A, were identified in carbapenemase-positive P. aeruginosa isolates (n = 6) using whole genome sequencing. Antibiotic susceptibility tests showed susceptibility to cefiderocol (MIC ≤ 4 μg ml-1) despite pan-β-lactam resistance in the isolates. Both the mutations reduced local intra-chain interactions in PBP3 that marginally increased the local flexibility (∼1%) in the structures to affect antibiotic-interactions. Molecular dynamics simulations confirmed the overall stability of the PBP3 mutants through root-mean square deviations, radius of gyration, solvent-accessibility and density curves, which favored their selection. Docking studies unveiled that the mutations in PBP3 elicited unfavorable stereochemical clashes with the conventional antibiotics thereby increasing their inhibition constants (IC) up to ∼50 fold. It was deciphered that cefiderocol retained its susceptibility despite mutations in PBP3, due to its higher average binding affinity (ΔG: -8.2 ± 0.4 kcal mol-1) towards multiple PBP-targets and lower average binding affinity (ΔG: -6.7 ± 0.7 kcal mol-1) to β-lactamases than the other β-lactam antibiotics. The molecular dynamics simulations and molecular mechanics Poisson Boltzmann surface area calculations further indicated energetically favorable binding for cefiderocol with PBP3 proteins. The study gave structural insight into emerging non-polar amino acid substitutions in PBP3 causing XDR and recommends prioritizing available antibiotics based on multi-target affinities to overcome challenges imposed by target-protein mutations.

Identification of a novel LFNG variant in a Chinese fetus with spondylocostal dysostosis and a systematic review

Spondylocostal dysostosis (SCDO) encompasses a group of skeletal disorders characterized by multiple segmentation defects in the vertebrae and ribs. SCDO has a complex genetic etiology. This study aimed to analyze and identify pathogenic variants in a fetus with SCDO. Copy number variant sequencing and whole exome sequencing were performed on a Chinese fetus with SCDO, followed by bioinformatics analyses, in vitro functional assays and a systematic review on the reported SCDO cases with LFNG pathogenic variants. Ultrasound examinations in utero exhibited that the fetus had vertebral malformation, scoliosis and tethered cord, but rib malformation was not evident. We found a novel homozygous variant (c.1078 C > T, p.R360C) within the last exon of LFNG. The variant was predicted to cause loss of function of LFNG by in silico prediction tools, which was confirmed by an in vitro assay of LFNG enzyme activity. The systematic review listed a total of 20 variants of LFNG in SCDO. The mutational spectrum spans across all exons of LFNG except the last one. This study reported the first Chinese case of LFNG-related SCDO, revealing the prenatal phenotypes and expanding the mutational spectrum of the disorder.

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Novel germline JAK2R715T mutation causing PV-like erythrocytosis in 3 generations. Amelioration by Ropeg-Interferon

Polycythemia vera (PV) is a clonal disorder arising from the acquired somatic mutations of the JAK2 gene, including JAK2V617F or several others in exon 12. A 38-year-old female had a stroke at age 32 and found to have elevated hemoglobin, normal leukocytes, normal platelets, and tested negative for JAK2V617F and exon 12 mutations. Next generation sequencing revealed a novel mutation: JAK2R715T in the pseudokinase domain (JH2) at 47.5%. Its presence in her nail DNA confirmed a germline origin. Her mother and her son similarly had erythrocytosis and a JAK2R715T mutation. Computer modeling indicated gain-of-function JAK2 activity. The propositus and her mother had polyclonal myelopoiesis, ruling out another somatic mutation-derived clonal hematopoiesis. Some erythroid progenitors of all three generations grew without erythropoietin, a hallmark of PV. The in vitro reporter assay confirmed increased activity of the JAK2R715T kinase. Similar to PV, the JAK2R715T native cells have increased STAT5 phosphorylation, augmented transcripts of prothrombotic and inflammatory genes, and decreased KLF2 transcripts. The propositus was not controlled by hydroxyurea, and JAK2 inhibitors were not tolerated; however, Ropeginterferon-alfa-2b (Ropeg-IFN-α) induced a remission. Ropeg-IFN-α treatment also reduced JAK2 activity in the propositus, her mother and JAK2V617F PV subjects. We report dominantly inherited erythrocytosis secondary to a novel germline JAK2R715T gain-of-function mutation with many but not all comparable molecular features to JAK2V617F PV. We also document a previously unreported inhibitory mechanism of JAK2 signaling by Ropeg-IFN-α.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors

Background

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

Results

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past 25 years, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 186 VIPs, resulting in a total of 403 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

Conclusions

VIPdb version 2 summarizes 403 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications.

Availability

VIPdb version 2 is available at https://genomeinterpretation.org/vipdb.

Catalyzing precision: unraveling the diagnostic conundrum of tunisian familial hypophosphatasia case through integrative clinical and molecular approaches

Familial Hypophosphatasia presents a complex diagnostic challenge due to its wide-ranging clinical manifestations and genetic heterogeneity. This study aims to elucidate the molecular underpinnings of familial Hypophosphatasia within a Tunisian family harboring a rare c.896 T > C mutation in the ALPL gene, offering insights into genotype-phenotype correlations and potential therapeutic avenues. The study employs a comprehensive approach, integrating biochemical examination, genetic analysis, structural modeling, and functional insights to unravel the impact of this rare mutation. Genetic investigation revealed the presence of the p.Leu299Pro mutation within the ALPL gene in affected family members. This mutation is strategically positioned in proximity to both the catalytic site and the metal-binding domain, suggesting potential functional consequences. Homology modeling techniques were employed to predict the 3D structure of TNSALP, providing insights into the structural context of the mutation. Our findings suggest that the mutation may induce conformational changes in the vicinity of the catalytic site and metal-binding domain, potentially affecting substrate recognition and catalytic efficiency. Molecular dynamics simulations were instrumental in elucidating the dynamic behavior of the tissue-nonspecific alkaline phosphatase isozyme (TNSALP) in the presence of the p.Leu299Pro mutation. The simulations indicated alterations in structural flexibility near the mutation site, with potential ramifications for the enzyme's overall stability and function. These dynamic changes may influence the catalytic efficiency of TNSALP, shedding light on the molecular underpinnings of the observed clinical manifestations within the Tunisian family. The clinical presentation of affected individuals highlighted significant phenotypic heterogeneity, underscoring the complex genotype-phenotype correlations in familial Hypophosphatasia. Variability in age of onset, severity of symptoms, and radiographic features was observed, emphasizing the need for a nuanced understanding of the clinical spectrum associated with the p.Leu299Pro mutation. This study advances our understanding of familial Hypophosphatasia by delineating the molecular consequences of the p.Leu299Pro mutation in the ALPL gene. By integrating genetic, structural, and clinical analyses, we provide insights into disease pathogenesis and lay the groundwork for personalized therapeutic strategies tailored to specific genetic profiles. Our findings underscore the importance of comprehensive genetic and clinical evaluation in guiding precision medicine approaches for familial Hypophosphatasia.

Investigation of a Large Kindred Reveals Cardiac Calsequestrin (CASQ2) as a Cause of Brugada Syndrome

BACKGROUND

Brugada syndrome (BrS) is an inherited primary channelopathy syndrome associated with the risk of ventricular fibrillation (VF) and sudden cardiac death in a structurally normal heart.

AIM OF THE STUDY

The aim of this study was to clinically and genetically evaluate a large family with severe autosomal dominant Brugada syndrome.

METHODS

Clinical and genetic studies were performed. Genetic analysis was conducted with NGS technologies (WES) using the Illumina instrument. According to the standard procedure, variants found by WES were confirmed in all available families by Sanger sequencing. The effect of the variants was studied by using in silico prediction of pathogenicity.

RESULTS

The proband was a 52-year-old man who was admitted to the emergency department for syncope at rest. WES of the index case identified a heterozygous VUS CASQ2, c.532T>C, p.(Tyr178His). We studied the segregation of the variation in all pedigree members. All the patients were heterozygous for the variation CASQ2 p.(Tyr178His), whereas the remaining healthy individuals in the family were homozygous for the normal allele. Structural analysis of CASQ2 p.(Tyr178His) was performed and revealed an important effect of the missense variation on monomer stability. The CASQ2 Tyr180 residue is located inside the sarcoplasmic reticulum (SR) junctional face membrane interaction domain and is predicted to disrupt filamentation.

CONCLUSIONS

Our data suggest that the p.Tyr178His substitution is associated with BrS in the family investigated, affecting the stability of the protein, disrupting filamentation at the interdimer interface, and affecting the subsequent formation of tetramers and polymers that contain calcium-binding sites.

Roles of the Arabidopsis KEULE Gene in Postembryonic Development

Cytokinesis in plant cells begins with the fusion of vesicles that transport cell wall materials to the center of the cell division plane, where the cell plate forms and expands radially until it fuses with the parental cell wall. Vesicle fusion is facilitated by trans-SNARE complexes, with assistance from Sec1/Munc18 (SM) proteins. The SNARE protein KNOLLE and the SM protein KEULE are required for membrane fusion at the cell plate. Due to the crucial function of KEULE, all Arabidopsis (Arabidopsis thaliana) keule mutants identified to date are seedling lethal. Here, we identified the Arabidopsis serrata4-1 (sea4-1) and sea4-2 mutants, which carry recessive, hypomorphic alleles of KEULE. Homozygous sea4-1 and sea4-2 plants are viable and fertile but have smaller rosettes and fewer leaves at bolting than the wild type. Their leaves are serrated, small, and wavy, with a complex venation pattern. The mutant leaves also develop necrotic patches and undergo premature senescence. RNA-seq revealed transcriptome changes likely leading to reduced cell wall integrity and an increase in the unfolded protein response. These findings shed light on the roles of KEULE in postembryonic development, particularly in the patterning of rosette leaves and leaf margins.

FDXR variants cause adrenal insufficiency and atypical sexual development

Genetic defects affecting steroid biosynthesis cause cortisol deficiency and differences of sex development; among these defects are recessive mutations in the steroidogenic enzymes CYP11A1 and CYP11B, whose function is supported by reducing equivalents donated by ferredoxin reductase (FDXR) and ferredoxin. So far, mutations in the mitochondrial flavoprotein FDXR have been associated with a progressive neuropathic mitochondriopathy named FDXR-related mitochondriopathy (FRM), but cortisol insufficiency has not been documented. However, patients with FRM often experience worsening or demise following stress associated with infections. We investigated 2 female patients with FRM carrying the potentially novel homozygous FDXR mutation p.G437R with ambiguous genitalia at birth and sudden death in the first year of life; they presented with cortisol deficiency and androgen excess compatible with 11-hydroxylase deficiency. In addition, steroidogenic FDXR-variant cell lines reprogrammed from 3 patients with FRM fibroblasts displayed deficient mineralocorticoid and glucocorticoid production. Finally, Fdxr-mutant mice allelic to the severe p.R386W human variant showed reduced progesterone and corticosterone production. Therefore, our comprehensive studies show that human FDXR variants may cause compensated but possibly life-threatening adrenocortical insufficiency in stress by affecting adrenal glucocorticoid and mineralocorticoid synthesis through direct enzyme inhibition, most likely in combination with disturbed mitochondrial redox balance.

A novel missense mutation of CCDC34 causes male infertility with oligoasthenoteratozoospermia in a consanguineous Pakistani family

ABSTRACT

Male infertility is a worldwide health issue, affecting 8%-12% of the global population. Oligoasthenoteratozoospermia (OAT) represents a severe type of male infertility, characterized by reduced sperm count and motility and an increased frequency of sperm with aberrant morphology. Using whole-exome sequencing, this study identified a novel missense mutation (c.848C>A, p.A283E) in the coiled-coil domain-containing 34 gene (CCDC34) in a consanguineous Pakistani family. This rare mutation was predicted to be deleterious and to affect the protein stability. Hematoxylin and eosin staining of spermatozoa from the patient with OAT revealed multiple morphological abnormalities of the flagella and transmission electron microscopy indicated axonemal ultrastructural defects with a lack of outer dynein arms. These findings indicated that CCDC34 plays a role in maintaining the axonemal ultrastructure and the assembly or stability of the outer dynein arms, thus expanding the phenotypic spectrum of CCDC34 missense mutations.

Haploinsufficiency underlies the neurodevelopmental consequences of SLC6A1 variants

Heterozygous variants in SLC6A1, encoding the GAT-1 GABA transporter, are associated with seizures, developmental delay, and autism. The majority of affected individuals carry missense variants, many of which are recurrent germline de novo mutations, raising the possibility of gain-of-function or dominant-negative effects. To understand the functional consequences, we performed an in vitro GABA uptake assay for 213 unique variants, including 24 control variants. De novo variants consistently resulted in a decrease in GABA uptake, in keeping with haploinsufficiency underlying all neurodevelopmental phenotypes. Where present, ClinVar pathogenicity reports correlated well with GABA uptake data; the functional data can inform future reports for the remaining 72% of unscored variants. Surface localization was assessed for 86 variants; two-thirds of loss-of-function missense variants prevented GAT-1 from being present on the membrane while GAT-1 was on the surface but with reduced activity for the remaining third. Surprisingly, recurrent de novo missense variants showed moderate loss-of-function effects that reduced GABA uptake with no evidence for dominant-negative or gain-of-function effects. Using linear regression across multiple missense severity scores to extrapolate the functional data to all potential SLC6A1 missense variants, we observe an abundance of GAT-1 residues that are sensitive to substitution. The extent of this missense vulnerability accounts for the clinically observed missense enrichment; overlap with hypermutable CpG sites accounts for the recurrent missense variants. Strategies to increase the expression of the wild-type SLC6A1 allele are likely to be beneficial across neurodevelopmental disorders, though the developmental stage and extent of required rescue remain unknown.

From driver genes to gene families: A computational analysis of oncogenic mutations and ubiquitination anomalies in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive computational analysis to explore the involvement of genes within the same families as known driver genes in HCC. Specifically, we expanded the concept beyond single-gene mutations to encompass gene families sharing homologous structures, integrating various omics data to comprehensively understand gene abnormalities in cancer. Our analysis identified 74 domains with an enriched mutation burden, 404 domain mutation hotspots, and 233 dysregulated driver genes. We observed that specific low-frequency somatic mutations may contribute to HCC occurrence, potentially overlooked by single-gene algorithms. Furthermore, we systematically analyzed how abnormalities in the ubiquitinated proteasome system (UPS) impact HCC, finding that abnormal genes in E3, E2, DUB families, and Degron genes often result in HCC by affecting the stability of oncogenic or tumor suppressor proteins. In conclusion, expanding the exploration of driver genes to include gene families with homologous structures emerges as a promising strategy for uncovering additional oncogenic alterations in HCC.

Engineering G protein-coupled receptors for stabilization

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations

Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, as it directly correlated with the protein function. Thus, this study delves into the intricacies of protein stability, highlighting its dependence on various factors, including thermodynamics, thermal conditions, and structural properties. Moreover, a notable focus is placed on the free energy change of unfolding (ΔGunfolding), change in heat capacity (ΔCp) with protein structural transition, melting temperature (Tm) and number of disulfide bonds, which are critical parameters in understanding protein stability. In this study, a machine learning (ML) predictive model was developed to estimate these four parameters using the primary sequence of the protein. The shortfall of available tools for protein stability prediction based on multiple parameters propelled the completion of this study. Convolutional Neural Network (CNN) with multiple layers was adopted to develop a more reliable ML model. Individual predictive models were prepared for each property, and all the prepared models showed results with high accuracy. The R2 (coefficient of determination) of these models were 0.79, 0.78, 0.92 and 0.92, respectively, for ΔG, ΔCp, Tm and disulfide bonds. A case study on stability analysis of two homologous proteins was presented to validate the results predicted through the developed model. The case study included in silico analysis of protein stability using molecular docking and molecular dynamic simulations. This validation study assured the accuracy of each model in predicting the stability associated properties. The alignment of physics-based principles with ML models has provided an opportunity to develop a fast machine learning solution to replace the computationally demanding physics-based calculations used to determine protein stability. Furthermore, this work provided valuable insights into the impact of mutation on protein stability, which has implications for the field of protein engineering. The source codes are available at https://github.com/Growdeatechnology.

Genetic/epigenetic effects in NF1 microdeletion syndrome: beyond the haploinsufficiency, looking at the contribution of not deleted genes

NF1 microdeletion syndrome, accounting for 5-11% of NF1 patients, is caused by a deletion in the NF1 region and it is generally characterized by a severe phenotype. Although 70% of NF1 microdeletion patients presents the same 1.4 Mb type-I deletion, some patients may show additional clinical features. Therefore, the contribution of several pathogenic mechanisms, besides haploinsufficiency of some genes within the deletion interval, is expected and needs to be defined. We investigated an altered expression of deletion flanking genes by qPCR in patients with type-1 NF1 deletion, compared to healthy donors, possibly contributing to the clinical traits of NF1 microdeletion syndrome. In addition, the 1.4-Mb deletion leads to changes in the 3D chromatin structure in the 17q11.2 region. Specifically, this deletion alters DNA-DNA interactions in the regions flanking the breakpoints, as demonstrated by our 4C-seq analysis. This alteration likely causes position effect on the expression of deletion flanking genes.Interestingly, 4C-seq analysis revealed that in microdeletion patients, an interaction was established between the RHOT1 promoter and the SLC6A4 gene, which showed increased expression. We performed NGS on putative modifier genes, and identified two "likely pathogenic" rare variants in RAS pathway, possibly contributing to incidental phenotypic features.This study provides new insights into understanding the pathogenesis of NF1 microdeletion syndrome and suggests a novel pathomechanism that contributes to the expression phenotype in addition to haploinsufficiency of genes located within the deletion.This is a pivotal approach that can be applied to unravel microdeletion syndromes, improving precision medicine, prognosis and patients' follow-up.

De novo structure prediction of meteorin and meteorin-like protein for identification of domains, functional receptor binding regions, and their high-risk missense variants

Meteorin (Metrn) and Meteorin-like (Metrnl) are homologous secreted proteins involved in neural development and metabolic regulation. In this study, we have performed de novo structure prediction and analysis of both Metrn and Metrnl using Alphafold2 (AF2) and RoseTTAfold (RF). Based on the domain and structural homology analysis of the predicted structures, we have identified that these proteins are composed of two functional domains, a CUB domain and an NTR domain, connected by a hinge/loop region. We have identified the receptor binding regions of Metrn and Metrnl using the machine-learning tools ScanNet and Masif. These were further validated by docking Metrnl with its reported KIT receptor, thus establishing the role of each domain in the receptor interaction. Also, we have studied the effect of non-synonymous SNPs on the structure and function of these proteins using an array of bioinformatics tools and selected 16 missense variants in Metrn and 10 in Metrnl that can affect the protein stability. This is the first study to comprehensively characterize the functional domains of Metrn and Metrnl at their structural level and identify the functional domains, and protein binding regions. This study also highlights the interaction mechanism of the KIT receptor and Metrnl. The predicted deleterious SNPs will allow further understanding of the role of these variants in modulating the plasma levels of these proteins in disease conditions such as diabetes.Communicated by Ramaswamy H. Sarma.

Review of predicting protein stability changes upon variations

Forecasting alterations in protein stability caused by variations holds immense importance. Improving the thermal stability of proteins is important for biomedical and industrial applications. This review discusses the latest methods for predicting the effects of mutations on protein stability, databases containing protein mutations and thermodynamic parameters, and experimental techniques for efficiently assessing protein stability in high-throughput settings. Various publicly available databases for protein stability prediction are introduced. Furthermore, state-of-the-art computational approaches for anticipating protein stability changes due to variants are reviewed. Each method's types of features, base algorithm, and prediction results are also detailed. Additionally, some experimental approaches for verifying the prediction results of computational methods are introduced. Finally, the review summarizes the progress and challenges of protein stability prediction and discusses potential models for future research directions.

Emerging variants, unique phenotypes, and transcriptomic signatures: an integrated study of COASY-associated diseases

OBJECTIVE

COASY, the gene encoding the bifunctional enzyme CoA synthase, which catalyzes the last two reactions of cellular de novo coenzyme A (CoA) biosynthesis, has been linked to two exceedingly rare autosomal recessive disorders, such as COASY protein-associated neurodegeneration (CoPAN), a form of neurodegeneration with brain iron accumulation (NBIA), and pontocerebellar hypoplasia type 12 (PCH12). We aimed to expand the phenotypic spectrum and gain insights into the pathogenesis of COASY-related disorders.

METHODS

Patients were identified through targeted or exome sequencing. To unravel the molecular mechanisms of disease, RNA sequencing, bioenergetic analysis, and quantification of critical proteins were performed on fibroblasts.

RESULTS

We identified five new individuals harboring novel COASY variants. While one case exhibited classical CoPAN features, the others displayed atypical symptoms such as deafness, language and autism spectrum disorders, brain atrophy, and microcephaly. All patients experienced epilepsy, highlighting its potential frequency in COASY-related disorders. Fibroblast transcriptomic profiling unveiled dysregulated expression in genes associated with mitochondrial respiration, responses to oxidative stress, transmembrane transport, various cellular signaling pathways, and protein translation, modification, and trafficking. Bioenergetic analysis revealed impaired mitochondrial oxygen consumption in COASY fibroblasts. Despite comparable total CoA levels to control cells, the amounts of mitochondrial 4'-phosphopantetheinylated proteins were significantly reduced in COASY patients.

INTERPRETATION

These results not only extend the clinical phenotype associated with COASY variants but also suggest a continuum between CoPAN and PCH12. The intricate interplay of altered cellular processes and signaling pathways provides valuable insights for further research into the pathogenesis of COASY-associated diseases.

DAB2IP associates with hereditary angioedema: Insights into the role of VEGF signaling in HAE pathophysiology

BACKGROUND

In the recent years, there was an important improvement in the understanding of the pathogenesis of hereditary angioedema (HAE). Notwithstanding, in a large portion of patients with unknown mutation (HAE-UNK) the genetic cause remains to be identified.

OBJECTIVES

To identify new genetic targets associated with HAE, a large Argentine family with HAE-UNK spanning 3 generations was studied.

METHODS

Whole exome sequencing was performed on affected family members to identify potential genetic variants associated with HAE-UNK. In silico analyses and experimental studies were applied to assess the role of the identified gene variant.

RESULTS

A missense variant (p.D239N) in DAB2IP was identified. The variant occurred in the C2-domain, the region interacting with vascular endothelial growth factor receptor 2 (VEGFR2). It was found to be rare, and predicted to have a detrimental effect on the functionality of DAB2IP. Protein structure modeling predicted changes in the mutant p.D239N protein structure, impacting protein stability. The p.D239N variant affected the subcellular localization of VEGFR2. Cells transfected with the DAB2IP-239N transcript exhibited an intracellular distribution, and VEGFR2 remained associated with the cell membrane. The altered localization pattern indicated reduced colocalization of the mutant protein with VEGFR2, suggesting a diminished ability of VEGFR2 binding.

CONCLUSIONS

The study identified a novel missense variant (p.D239N) in DAB2IP in a family with HAE-UNK and highlighted the role of dysregulated VEGF-mediated signaling in altered endothelial permeability. DAB2IP loss-of-function pathogenic variants lead to the impairment of the endothelial VEGF/VEGFR2 ligand system and represent a new pathophysiologic cause of HAE-UNK.

Targeting decaprenylphosphoryl-β-D-ribose 2'-epimerase for Innovative Drug Development Against Mycobacterium Tuberculosis Drug-Resistant Strains

Tuberculosis (TB) remains a global health challenge with the emergence of drug-resistant Mycobacterium tuberculosis variants, necessitating innovative drug molecules. One potential target is the cell wall synthesis enzyme decaprenylphosphoryl-β-D-ribose 2'-epimerase (DprE1), crucial for virulence and survival. This study employed virtual screening of 111 Protein Data Bank (PDB) database molecules known for their inhibitory biological activity against DprE1 with known IC50 values. Six compounds, PubChem ID: 390820, 86287492, 155294899, 155522922, 162651615, and 162665075, exhibited promising attributes as drug candidates and validated against clinical trial inhibitors BTZ043, TBA-7371, PBTZ169, and OPC-167832. Concurrently, this research focused on DprE1 mutation effects using molecular dynamic simulations. Among the 10 mutations tested, C387N significantly influenced protein behavior, leading to structural alterations observed through root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent-accessible surface area (SASA) analysis. Ligand 2 (ID: 390820) emerged as a promising candidate through ligand-based pharmacophore analysis, displaying enhanced binding compared with reference inhibitors. Molecular dynamic simulations highlighted ligand 2's interaction with the C387N mutation, reducing fluctuations, augmenting hydrogen bonding, and influencing solvent accessibility. These collective findings emphasize ligand 2's efficacy, particularly against severe mutations, in enhancing protein-ligand complex stability. Integrated computational and pharmacophore methodologies offer valuable insights into drug candidates and their interactions within intricate protein environments. This research lays a strategic foundation for targeted interventions against drug-resistant TB, highlighting ligand 2's potential for advanced drug development strategies.

Alpha Carbonic Anhydrase from Nitratiruptor tergarcus Engineered for Increased Activity and Thermostability

The development of carbon capture and storage technologies has resulted in a rising interest in the use of carbonic anhydrases (CAs) for CO2 fixation at elevated temperatures. In this study, we chose to rationally engineer the α-CA (NtCA) from the thermophilic bacterium Nitratiruptor tergarcus, which has been previously suggested to be thermostable by in silico studies. Using a combination of analyses with the DEEPDDG software and available structural knowledge, we selected residues in three regions, namely, the catalytic pocket, the dimeric interface and the surface, in order to increase thermostability and CO2 hydration activity. A total of 13 specific mutations, affecting seven amino acids, were assessed. Single, double and quadruple mutants were produced in Escherichia coli and analyzed. The best-performing mutations that led to improvements in both activity and stability were D168K, a surface mutation, and R210L, a mutation in the dimeric interface. Apart from these, most mutants showed improved thermostability, with mutants R210K and N88K_R210L showing substantial improvements in activity, up to 11-fold. Molecular dynamics simulations, focusing particularly on residue fluctuations, conformational changes and hydrogen bond analysis, elucidated the structural changes imposed by the mutations. Successful engineering of NtCA provided valuable lessons for further engineering of α-CAs.

In silico evidence that substitution of glycine for valine (p.G8V) in a common variant of TMPRSS2 isoform 1 increases accessibility to an endocytic signal: Implication for SARS-cov-2 entry into host cells and susceptibility to COVID-19

The TMPRSS2 protease plays a key role in the entry of the SARS-CoV-2 into cells. The TMPRSS2 gene is highly polymorphic in humans, and some polymorphisms may affect the susceptibility to COVID-19 or disease severity. rs75603675 (c.23G > T) is a missense variant that causes the replacement of glycine with valine at position 8 (p.G8V) in the TMPRSS2 isoform 1. According to GnomAD v4.0.0 database, the allele frequency of the rs75603675 on a global scale is 38.10 %, and range from 0.92 % in East Asian to 40.77 % in non-Finnish European (NFE) population. We analyzed the occurrence of the rs75603675 in two cohorts of patients, the first with severe/critical COVID-19 enrolled in a French hospital (42 patients), and the second with predominantly asymptomatic/pauci-symptomatic/mild COVID-19 enrolled in an Italian hospital (69 patients). We found that the TMPRSS2-c.23T minor allele frequency was similar in the two cohorts, 46.43 % and 46.38 %, respectively, and higher than the frequency in the NFE population (40.77 %). Chi-square test provided significant results (p < 0.05) when the genotype data (TMPRSS2-c.23T/c.23T homozygotes + TMPRSS2-c.23G/c.23T heterozygotes vs. TMPRSS2-c.23G/c.23G homozygotes) of the two patient groups were pooled and compared to the expected data for the NFE population, suggesting a possible pathogenetic mechanism of the p.G8V substitution. We explored the possible effects of the p.G8V substitution and found that the N-terminal region of the TMPRSS2 isoform 1 contains a signal for clathrin/AP-2-dependent endocytosis. In silico analysis predicted that the p.G8V substitution may increase the accessibility to the endocytic signal, which could help SARS-CoV-2 enter cells.

NRDE2 deficiency impairs homologous recombination repair and sensitizes hepatocellular carcinoma to PARP inhibitors

To identify novel susceptibility genes for hepatocellular carcinoma (HCC), we performed a rare-variant association study in Chinese populations consisting of 2,750 cases and 4,153 controls. We identified four HCC-associated genes, including NRDE2, RANBP17, RTEL1, and STEAP3. Using NRDE2 (index rs199890497 [p.N377I], p = 1.19 × 10-9) as an exemplary candidate, we demonstrated that it promotes homologous recombination (HR) repair and suppresses HCC. Mechanistically, NRDE2 binds to the subunits of casein kinase 2 (CK2) and facilitates the assembly and activity of the CK2 holoenzyme. This NRDE2-mediated enhancement of CK2 activity increases the phosphorylation of MDC1 and then facilitates the HR repair. These functions are eliminated almost completely by the NRDE2-p.N377I variant, which sensitizes the HCC cells to poly(ADP-ribose) polymerase (PARP) inhibitors, especially when combined with chemotherapy. Collectively, our findings highlight the relevance of the rare variants to genetic susceptibility to HCC, which would be helpful for the precise treatment of this malignancy.

Functional characterization of HNF4A gene variants identify promoter and cell line specific transactivation effects

Hepatocyte nuclear factor-4 alpha (HNF-4A) regulates genes with roles in glucose metabolism and β-cell development. Although pathogenic HNF4A variants are commonly associated with maturity-onset diabetes of the young (MODY1; HNF4A-MODY), rare phenotypes also include hyperinsulinemic hypoglycemia, renal Fanconi syndrome and liver disease. While the association of rare functionally damaging HNF1A variants with HNF1A-MODY and type 2 diabetes is well established owing to robust functional assays, the impact of HNF4A variants on HNF-4A transactivation in tissues including the liver and kidney is less known, due to lack of similar assays. Our aim was to investigate the functional effects of seven HNF4A variants, located in the HNF-4A DNA binding domain and associated with different clinical phenotypes, by various functional assays and cell lines (transactivation, DNA binding, protein expression, nuclear localization) and in silico protein structure analyses. Variants R85W, S87N and R89W demonstrated reduced DNA binding to the consensus HNF-4A binding elements in the HNF1A promoter (35, 13 and 9%, respectively) and the G6PC promoter (R85W ~10%). While reduced transactivation on the G6PC promoter in HepG2 cells was shown for S87N (33%), R89W (65%) and R136W (35%), increased transactivation by R85W and R85Q was confirmed using several combinations of target promoters and cell lines. R89W showed reduced nuclear levels. In silico analyses supported variant induced structural impact. Our study indicates that cell line specific functional investigations are important to better understand HNF4A-MODY genotype-phenotype correlations, as our data supports ACMG/AMP interpretations of loss-of-function variants and propose assay-specific HNF4A control variants for future functional investigations.

Computational analysis of non-synonymous single nucleotide polymorphism in the bovine PKLR geneComputational analysis of bovine PKLR gene

Pyruvate kinase (PKLR) is a potential candidate gene for milk production traits in cows. The main aim of this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the PKLR gene by using several computational tools. In silico tools including SIFT, Polyphen-2, SNAP2 and Panther indicated only 18 nsSNPs out of 170 were considered deleterious. The analysis of proteins' stability change due to amino acid substitution performed by the use of the I-mutant, MUpro, CUPSTAT, SDM and Dynamut confirmed that 9 nsSNPs decreased protein stability. ConSurf analysis predicted that all 18 nsSNPs were evolutionary moderately or highly conserved. Two different domains of PKLR protein were revealed by the InterPro tool with 12 nsSNPs positioned in the Pyruvate Kinase barrel domain and 6 nsSNP present in the Pyruvate Kinase C Terminal. The PKLR 3D model was predicted by MODELLER software and validated via Ramachandran plot and Prosa which indicated a good quality model. The analysis of energy minimizations for the native and mutated structures was performed by SWISS PDB viewer with GROMOS 96 program and showed that 3 structural and 4 functional residues had total energy higher than the native model. These findings indicate that these mutant structures (rs441424814, rs449326723, rs476805413, rs472263384, rs474320860, rs475521477, rs441633284) were less stable than the native model. Molecular Dynamics simulations were performed to confirm the impact of nsSNPs on the protein structure and function. The present study provides useful information about functional SNPs that have an impact on PKLR protein in cattle.Communicated by Ramaswamy H. Sarma.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

Comprehensive in silico analysis of prolactin receptor (PRLR) gene nonsynonymous single nucleotide polymorphisms (nsSNPs) reveals multifaceted impact on protein structure, function, and interactions

This study delves into the functional and structural implications of non-synonymous single nucleotide polymorphisms (nsSNPs) within the Prolactin Receptor (PRLR) gene. Thirteen deleterious nsSNPs were identified through bioinformatics tools, with SIFT predicting 168 out of 395 nsSNPs as detrimental, exhibiting tolerance index (TI) scores ranging from 0 to 0.05. Polyphen2 assigned likelihood scores >0.99 to all 13 nsSNPs, indicating high probability of harm, while Panther scores classified most nsSNPs as 'probably damaging', with specific mutations like W218R scoring 0.74, suggesting a higher impact. Stability analysis using DDG I-Mutant and DDG Mupro consistently predicted decreased stability for all mutations, with CUPSAT indicating mutations like V125G and W218R significantly decreasing stability. Structural analysis through DynaMut predicted destabilization for all mutations except L196I and L292H. MutPred2 highlighted structural alterations for all nsSNPs except L196I, L293V, R315W, and S353N. Domain analysis revealed key mutations within essential functional domains, with five nsSNPs located within Fibronectin type-III domains. Bayesian analysis through ConSurf identified 9 critical residues, with 11 nsSNPs exhibiting notably high conservation. STRING analysis unveiled a complex interaction network, indicating involvement in vital biological processes like lactation. Molecular dynamics (MD) simulations, spanning 100 nanoseconds, elucidated structural dynamics induced by detrimental missense SNPs. Post-translational modification (PTM) analysis identified specific mutations, such as R351, involved in methylation, while S353 was implicated in phosphorylation and glycosylation. These findings offer comprehensive insights into the molecular and phenotypic effects of deleterious nsSNPs in the PRLR gene, crucial for selective breeding.Communicated by Ramaswamy H. Sarma.

Wide Real-Life Data Support Reduced Sensitivity of Antigen Tests for Omicron SARS-CoV-2 Infections

With the continuous spread of new SARS-CoV-2 variants of concern (VOCs), the monitoring of diagnostic test performances is mandatory. We evaluated the changes in antigen diagnostic tests' (ADTs) accuracy along the Delta to Omicron VOCs transition, exploring the N protein mutations possibly affecting ADT sensitivity and assessing the best sampling site for the diagnosis of Omicron infections. In total, 5175 subjects were enrolled from 1 October 2021 to 15 July 2022. The inclusion criteria were SARS-CoV-2 ADT combined with a same-day RT-PCR swab test. For the sampling site analysis, 61 patients were prospectively recruited during the Omicron period for nasal and oral swab analyses by RT-PCR. Next-Generation Sequencing data were obtained to evaluate the different sublineages. Using RT-PCR as a reference, 387 subjects resulted in becoming infected and the overall sensitivity of the ADT decreased from 63% in the Delta period to 33% in the Omicron period. This decrease was highly statistically significant (p < 0.001), and no decrease in viral load was detected at the RNA level. The nasal site presented a significantly higher viral load than the oral site during the Omicron wave. The reduced detection rate of Omicron infections by ADT should be considered in the global testing strategy to preserve accurate diagnoses across the changing SARS-CoV-2 variants.

Time-Resolved Ultraviolet Photodissociation Mass Spectrometry Probes the Mutation-Induced Alterations in Protein Stability and Unfolding Dynamics

How mutations impact protein stability and structure dynamics is crucial for understanding the pathological process and rational drug design. Herein, we establish a time-resolved native mass spectrometry (TR-nMS) platform via a rapid-mixing capillary apparatus for monitoring the acid-initiated protein unfolding process. The molecular details in protein structure unfolding are further profiled by a 193 nm ultraviolet photodissociation (UVPD) analysis of the structure-informative photofragments. Compared with the wild-type dihydrofolate reductase (WT-DHFR), the M42T/H114R mutant (MT-DHFR) exhibits a significant stability decrease in TR-nMS characterization. UVPD comparisons of the unfolding intermediates and original DHFR forms indicate the special stabilization effect of cofactor NADPH on DHFR structure, and the M42T/H114R mutations lead to a significant decrease in NADPH-DHFR interactions, thus promoting the structure unfolding. Our study paves the way for probing the mutation-induced subtle changes in the stability and structure dynamics of drug targets.

Emerging insight of whole genome sequencing coupled with protein structure prediction into the pyrazinamide-resistance signature of Mycobacterium tuberculosis

Pyrazinamide (PZA) is considered to be a pivotal drug to shorten the treatment of both drug-susceptible and drug-resistant tuberculosis, but its use is challenged by the reliability of drug-susceptibility testing (DST). PZA resistance in Mycobacterium tuberculosis (MTB) is relevant to the amino acid substitution of pyrazinamidase that is responsible for the conversion of PZA to active pyrazinoic acid (POA). The single nucleotide variants (SNVs) within ribosomal protein S1 (rpsA) or aspartate decarboxylase (panD), the binding targets of POA, has been reported to drive the PZA-resistance signature of MTB. In this study, whole genome sequencing (WGS) was used to identify SNVs within the pncA, rpsA and panD genes in 100 clinical MTB isolates associated with DST results for PZA. The potential influence of high-confidence, interim-confidence or emerging variants on the interplay between target genes and PZA or POA was simulated computationally, and predicted with a protein structure modelling approach. The DST results showed weak agreement with the identification of high-confidence variants within the pncA gene (Cohen's kappa coefficient=0.58), the analytic results of WGS coupled with protein structure modelling on pncA mutants (Cohen's kappa coefficient=0.524) or related genes (Cohen's kappa coefficient=0.504). Taken together, these results suggest the practicable application of a genotypic-coupled bioinformatic approach to manage PZA-containing regimens for patients with MTB.

A personalized medicine approach identifies enasidenib as an efficient treatment for IDH2 mutant chondrosarcoma

BACKGROUND

Sarcomas represent an extensive group of malignant diseases affecting mesodermal tissues. Among sarcomas, the clinical management of chondrosarcomas remains a complex challenge, as high-grade tumours do not respond to current therapies. Mutations in the isocitrate dehydrogenase (IDH) 1 and 2 genes are among the most common mutations detected in chondrosarcomas and may represent a therapeutic opportunity. The presence of mutated IDH (mIDH) enzymes results in the accumulation of the oncometabolite 2-HG leading to molecular alterations that contribute to drive tumour growth.

METHODS

We developed a personalized medicine strategy based on the targeted NGS/Sanger sequencing of sarcoma samples (n = 6) and the use of matched patient-derived cell lines as a drug-testing platform. The anti-tumour potential of IDH mutations found in two chondrosarcoma cases was analysed in vitro, in vivo and molecularly (transcriptomic and DNA methylation analyses).

FINDINGS

We treated several chondrosarcoma models with specific mIDH1/2 inhibitors. Among these treatments, only the mIDH2 inhibitor enasidenib was able to decrease 2-HG levels and efficiently reduce the viability of mIDH2 chondrosarcoma cells. Importantly, oral administration of enasidenib in xenografted mice resulted in a complete abrogation of tumour growth. Enasidenib induced a profound remodelling of the transcriptomic landscape not associated to changes in the 5 mC methylation levels and its anti-tumour effects were associated with the repression of proliferative pathways such as those controlled by E2F factors.

INTERPRETATION

Overall, this work provides preclinical evidence for the use of enasidenib to treat mIDH2 chondrosarcomas.

FUNDING

Supported by the Spanish Research Agency/FEDER (grants PID2022-142020OB-I00; PID2019-106666RB-I00), the ISC III/FEDER (PI20CIII/00020; DTS18CIII/00005; CB16/12/00390; CB06/07/1009; CB19/07/00057); the GEIS group (GEIS-62); and the PCTI (Asturias)/FEDER (IDI/2021/000027).

Novel missense mutation c.797T>C (p.Met266Thr) gives rise to the rare B(A) phenotype in a Chinese family

BACKGROUND AND OBJECTIVES

B(A) phenotype is usually formed by nucleotide mutations in the ABO*B.01 allele, with their products exhibiting glycosyltransferases (GTs) A and B overlapping functionality. We herein report a B(A) allele found in a Chinese family.

MATERIALS AND METHODS

The entire ABO genes of the probands, including flanking regulatory regions, were sequenced through PacBio third-generation long-read single-molecule real-time sequencing. 3D molecular models of the wild-type and mutant GTB were generated using the DynaMut web server. The effect of the mutation on the enzyme function was predicted by PROVEAN and PolyPhen2. The predictions of stability changes were performed using DynaMut and SNPeffect.

RESULTS

Based on serological and sequencing features, we concluded the two probands as possible cases of the B(A) phenotype. Crystallization analysis showed that Thr266 substitution does not disrupt the hydrogen bonds. However, some changes in interatomic contacts, such as loss of ionic interactions and hydrophobic contacts, and addition of weak hydrogen bonds, may have affected protein stability to some extent. This mutation was predicted to have a benign effect on enzyme function and slightly reduce protein stability.

CONCLUSION

The probands had the same novel B(A) allele with a c.797T>C (p.Met266Thr) mutation on the ABO*B.01 backbone.

Characteristics of SARS-CoV-2 Omicron BA.5 variants in Shanghai after ending the zero-COVID policy in December 2022: a clinical and genomic analysis

Introduction

An unprecedented surge of Omicron infections appeared nationwide in China in December 2022 after the adjustment of the COVID-19 response policy. Here, we report the clinical and genomic characteristics of SARS-CoV-2 infections among children in Shanghai during this outbreak.

Methods

A total of 64 children with symptomatic COVID-19 were enrolled. SARS-CoV-2 whole genome sequences were obtained using next-generation sequencing (NGS) technology. Patient demographics and clinical characteristics were compared between variants. Phylogenetic tree, mutation spectrum, and the impact of unique mutations on SARS-CoV-2 proteins were analysed in silico.

Results

The genomic monitoring revealed that the emerging BA.5.2.48 and BF.7.14 were the dominant variants. The BA.5.2.48 infections were more frequently observed to experience vomiting/diarrhea and less frequently present cough compared to the BF.7.14 infections among patients without comorbidities in the study. The high-frequency unique non-synonymous mutations were present in BA.5.2.48 (N:Q241K) and BF.7.14 (nsp2:V94L, nsp12:L247F, S:C1243F, ORF7a:H47Y) with respect to their parental lineages. Of these mutations, S:C1243F, nsp12:L247F, and ORF7a:H47Y protein were predicted to have a deleterious effect on the protein function. Besides, nsp2:V94L and nsp12:L247F were predicted to destabilize the proteins.

Discussion

Further in vitro to in vivo studies are needed to verify the role of these specific mutations in viral fitness. In addition, continuous genomic monitoring and clinical manifestation assessments of the emerging variants will still be crucial for the effective responses to the ongoing COVID-19 pandemic.