3D Structure Research Articles

Optimized Second-Generation IL-4Rα Inhibition: Structural and Molecular Dynamics Properties of Rademikibart Fab-IL-4Rα Complex

Introduction: Global Burden of Disease studies showed atopic dermatitis (AD) and asthma are the top two immune-mediated inflammatory diseases at younger age [1]. Dupilumab was the initial first-generation interleukin-4 receptor alpha (IL-4Rα) inhibitor for treating both type I and type II IL-4Rα-dependent inflammatory disorders. Following recent clinical trials, rademikibart (previously, CBP-201) emerges as an optimized next-generation human monoclonal antibody with higher binding affinity to IL-4Rα compared to dupilumab [2]. It demonstrated better effect in inhibiting STAT6 intracellular signaling in vitro and provided similar potency inhibiting both IL-4 induced TARC release and IL-4 induced B cell activation [2]. Materials & Methods: X-ray crystallography was used to determine the atomic resolution 3D structure of rademikibart fragment antigen binding (Fab) bound to IL-4Rα. This structure was analyzed and compared computationally with the 2.82 Å resolution crystal structure of dupilumab Fab bound to IL-4Rα (Protein Data Bank Code 6WGL). Molecular dynamics studies on rademikibart and dupilumab bound to IL-4Rα examined the stability of the complexes and effects of amino acid mutations on complex formation. Results: The x-ray crystal structure of rademikibart Fab bound to IL-4Rα was determined at 2.71Å and compared to the complex of dupilumab Fab and IL-4Rα. The rotation angle between dupilumab and rademikibart bound to IL- 4Rα is 59.17°. This rotation enables the epitope of rademikibart, but not dupilumab, on IL-4Rα to overlap more closely with the conserved binding interface utilized by IL-4 and IL-13 cytokines. Molecular dynamics simulations of rademikibart Fab and dupilumab Fab complexed with IL-4Rα showed the third interface loop (residues 148 to 152 in domain 2) of IL-4Rα interacts directly with rademikibart, which is absent in dupilumab/IL- 4Rα complex. This finding is confirmed by analysis of the hydrogen bond interactions at the interface between the antibodies and IL-4Rα, demonstrating superior binding energy for rademikibart. Through single amino acid mutation analysis on rademikibart, we identified residue Y50 on rademikibart as the key residue interacting with IL- 4Rα’s third interface loop. Conclusion: Our data provide a molecular and structural rationale for the enhanced IL-4Rα inhibition by rademikibart over dupilumab, confirming rademikibart as an optimized second-generation IL-4Rα inhibitor.

NO classifier prediction of anti neuroinflammatory agents using text mining of 3D molecular fingerprints.

CNS Drug discovery has been challenging due to the lack of clarity on CNS diseases' basic biological and pathological mechanisms. Despite the difficulty, some CNS drugs have been developed based on phenotypic effects. Herein, we propose a phenotype-structure relationship model, which predicts an anti-neuroinflammatory potency based on 3D molecular structures of the phenotype-active or inactive compounds without specifying targets. For this chemo-centric study, a predictive model of the nitric oxide (NO) inhibitory potency in hyper-activated microglia is built from the 548 agents, which were collected from 95 research articles (28 substructures consisting of natural products and synthetic scaffolds) and doubly externally validated by the agents of 9 research articles as third set. 3D Structures (multi-conformer ensemble) of every agent were encoded into the E3FP molecular fingerprint of the Keiser group as a 3D molecular representation. The location information of the molecular fingerprints could be learned and validated to classify the inhibitory potency of compounds (IC50 cut-off between the active and inactive: 37.1 µM): (1) multi-layer perceptron (MLP) (AUC-CV: 0.997, AUC-Test: 0.992), (2) recurrent neural network (RNN) (AUC-CV: 0.999, AUC-Test: 0.995), and (3) convolutional neural network (CNN) (AUC-CV: 0.998, AUC-Test: 0.994). The high performance of these models was compared with that of four classical machine classification models (Logistic, Ridge, Lasso, and Naïve Bayes). We named the binary classification models NO-Classifier. Independent test set validation and decision region analysis of the independent test set doubly demonstrated NO-Classifier effectively discerned the anti-inflammatory potency of testing compounds in inflammatory cell phenotype with the webserver in https://no-classifier.onrender.com.

R3DMCS: a web server for visualizing structural variation in RNA motifs across experimental 3D structures from the same organism or across species.

The recent progress in RNA structure determination methods has resulted in a surge of newly solved RNA 3D structures. However, there is an absence of a user-friendly browser-based tool that can facilitate the comparison and visualization of RNA motifs across multiple 3D structures. We introduce R3DMCS, a web server that allows users to compare selected RNA nucleotides across all 3D structures of a given molecule from a given species, or across all 3D structures mapped to a single Rfam family. Starting from one instance of the motif, R3DMCS retrieves, aligns, annotates, organizes, and displays 3D coordinates of corresponding sets of nucleotides from other 3D structures. With R3DMCS, one can explore conformational changes of motifs due to 3D structures being solved in different functional states or different experimental conditions. One can also investigate conservation of 3D structure across species, or changes in 3D structure due to changes in sequence. R3DMCS is open-source software and freely available at https://rna.bgsu.edu/correspondence/ and https://github.com/BGSU-RNA/RNA-3D-correspondence . Supplementary data are available at Bioinformatics online.

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

AbstractLight‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

RNA sample optimization for cryo-EM analysis.

RNAs play critical roles in most biological processes. Although the three-dimensional (3D) structures of RNAs primarily determine their functions, it remains challenging to experimentally determine these 3D structures due to their conformational heterogeneity and intrinsic dynamics. Cryogenic electron microscopy (cryo-EM) has recently played an emerging role in resolving dynamic conformational changes and understanding structure-function relationships of RNAs including ribozymes, riboswitches and bacterial and viral noncoding RNAs. A variety of methods and pipelines have been developed to facilitate cryo-EM structure determination of challenging RNA targets with small molecular weights at subnanometer to near-atomic resolutions. While a wide range of conditions have been used to prepare RNAs for cryo-EM analysis, correlations between the variables in these conditions and cryo-EM visualizations and reconstructions remain underexplored, which continue to hinder optimizations of RNA samples for high-resolution cryo-EM structure determination. Here we present a protocol that describes rigorous screenings and iterative optimizations of RNA preparation conditions that facilitate cryo-EM structure determination, supplemented by cryo-EM data processing pipelines that resolve RNA dynamics and conformational changes and RNA modeling algorithms that generate atomic coordinates based on moderate- to high-resolution cryo-EM density maps. The current protocol is designed for users with basic skills and experience in RNA biochemistry, cryo-EM and RNA modeling. The expected time to carry out this protocol may range from 3 days to more than 3 weeks, depending on the many variables described in the protocol. For particularly challenging RNA targets, this protocol could also serve as a starting point for further optimizations.

Plasma-Driven Conversion of 2D Graphene into 3D Pouch for Improved Electromagnetic Absorption Performance.

Graphene-based materials are ideal for electromagnetic wave-absorbing materials (EAMs) due to their strong electrical and dielectric losses with reduced thickness and weight. To enhance the electromagnetic wave absorption performance of these materials, additional components are often incorporated. However, this approach not only increases the complexity of the synthesis process but also complicates and destabilizes the control of the material properties. In this study, we successfully employed a one-step method to reduce graphene oxide and transform 2D graphene into a 3D pocket-like structure through plasma treatment. This unique 3D structure is induced by the formation of uneven defects on the surface due to plasma treatment. The distinctive pouch-like structure of the reduced graphene oxide achieved remarkable electromagnetic wave absorption properties. Specifically, the material demonstrated a minimum reflection loss of -38.65 dB at 7.14 GHz, with an effective absorption bandwidth of 5.13 GHz and a thickness of just 1.9 mm. These results highlight the potential of plasma processing as a rapid, efficient, and environmentally friendly approach for the continuous production of advanced EAMs, paving the way for greener manufacturing practices in the industry.

New thiophene derivatives: chemoselective synthesis, antitumor effectiveness, structural characterization, DFT calculations, Hirshfeld surface, and Fukui function analysis.

In this study, the chemoselective synthesis of two new thiophene derivatives is presented. The structure of newly synthesized thiophenes derivatives; ethyl 4-acetyl-3-phenyl-5-(phenylamino)thiophene-2-carboxylate (5) and ethyl (E)-4-(3-(dimethylamino)acryloyl)-3-phenyl-5-(phenylamino)thiophene-2-carboxylate (8) were established using different FTIR and NMR spectral analyses. Compound 8 was isolated as single crystal and its 3D structure was determined using X-ray crystallographic analysis. Possible intermolecular interactions that control the molecular packing of 8 were elucidated using Hirshfeld topology analysis. The O…H (13.7%), H…H (55.3%) and C…C (2.3%) intermolecular interactions are the most significant. Fukui functions showed that C4 in thiophene 5 and C3 in thiophene 8 are the most reactive atoms for nucleophilic attack, while N9 in thiophene 5 and C1 in thiophene 8 are the most reactive atoms for electrophilic attack. Antitumor activity of thiophene 5 was assessed and the results showed higher activity against HepG-2 (7.46µg/mL) compared to the HCT 116 (12.60µg/mL) cell line.

Components and anisotropy of 3D QFP waves during the early solar eruption

Abstract The propagation of disturbances in the solar atmosphere is inherently three-dimensional (3D), yet comprehensive studies on the spatial structure and dynamics of 3D wavefronts are scarce. Here we conduct high-resolution 3D numerical simulations to investigate filament eruptions, focusing particularly on the 3D structure and genesis of EUV waves. Our results demonstrate that the EUV wavefront forms a dome-like configuration subdivided into three distinct zones. The foremost zone, preceding the flux rope, consists of fast-mode shock waves that heat the adjacent plasma. Adjacent to either side of the flux rope, the second zone contains expansion waves that cool the nearby plasma. The third zone, at the juncture of the first two, exhibits minimal disturbances. This anisotropic structure of the wavefront stems from the configuration and dynamics of the flux rope, which acts as a 3D piston during eruptions—compressing the plasma ahead to generate fast-mode shocks and evacuating the plasma behind to induce expansion waves. This dynamic results in the observed anisotropic wavefront. Additionally, with synthetic EUV images from simulation data, the EUV waves are observable in Atmospheric Imaging Assembly 193 and 211 $\AA$, which are identified as the fast-mode shocks. The detection of EUV waves varies with the observational perspective: the face-on view reveals EUV waves from the lower to the higher corona, whereas an edge-on view uncovers these waves only in the higher corona.

In Silico Efficacy of Oleic Acid, n-Hexanoic acid, and Epiglobulol Obtained from Conocarpus Lancifolius against Class D β-lactamases

Introduction: Antimicrobial resistance poses an escalating global challenge, compounded by the sluggish pace of new antibiotic discovery. Objectives: This study undertook an in silico analysis of phytochemicals derived from Conocarpus lancifolius, a local plant in the Jazan region of Saudi Arabia, to investigate potential antibacterial agents. Methods: The 3D crystallographic structure of OXA-48 was sourced from the RCSB protein databank (PDBID: 3HBR) and pre-processed. The Lib Dock algorithm facilitated the analysis of optimal binding orientations and potential interactions between compounds and the 3HBR. Results: The docking analysis outcome revealed Oleic acid as the most active compound and the binding mode exhibited that the -OH group of the terminal carboxylic acid moiety formed hydrogen bonds with Thr197 and Ala207, and the oxygen atom showed bonding with Lys116. Moreover, N-hexanoic acid also demonstrated promising binding interactions with the 3HBR, displaying hydrogen bond interactions with Lys208, Tyr211, and Ser70, along with hydrophobic alkyl interactions with Lys208 and Met115 at the protein's active sites. Unfavourable donor-donor and acceptor-acceptor bindings were also observed with Ser70 and Arg250 residues. Conclusions: The OXA-48 and NDM-1 predominate in countries of the Arabian Peninsula. Our findings suggest oleic acid as a promising candidate for combating OXA-48 β-lactamase, pending further assessment of its atomic structure via X-ray crystallography.

Flattening behaviour of weft-knitted spacer fabrics

AbstractWeft-knitted spacer fabrics are thick 3D knitted structures prized for their cushioning properties which have gathered increasing attention in the last decade. The thickness of a spacer fabric is one of its most influential parameters and strongly impacts its cushioning properties, wearability, thermal insulation or permeability. However, the fabric's natural undulation and high deformability make its thickness measurement uneasy. The current standard measurement methods require to measure the fabric thickness after compressing it until a fixed threshold stress value is reached to flatten it. The diversity of these threshold values is confusing, and each of them is unsuitable to variety of fabric rigidity. In this article, a standard for thickness evaluation was proposed and used to measure the thickness of 20 samples knitted with 5 independent parameters. The measured thickness was compared to the thickness measured at a threshold value of 1 kPa and to a theoretical thickness. The proposed measurement standard was proved reproducible and efficient for all fabrics when the threshold measures showed large errors on the softer and stiffer samples. The flattening stress of the fabrics ranged from 86 to 5262 Pa and could not be approximated by a single standard value. The theoretical thickness was more accurate, predicting the thickness with an average error of 3.8%.

Fabrication, characterization, and 3D printing of high-internal phase Pickering emulsion stabilized by heat-treated copra protein and calcium composite.

HCP-Ca nanoparticles were prepared by incorporating varying concentrations of CaCl2 into heated copra protein (HCP). The results showed a positive correlation between Ca2+ concentration and turbidity, indicating greater HCP aggregation with increasing Ca2+ levels. Microscopy analysis revealed that HCP-Ca nanoparticles had a rough surface morphology. Intermolecular forces such as disulfide bonds, hydrophobic interactions, and hydrogen bonds were key in the conformation of HCP aggregates, with calcium ions enhancing stability by forming salt bridges. HCP-Ca nanoparticle-based high internal phase Pickering emulsions (HIPPEs) were also fabricated using homogenization-centrifugation treatment. The nanoparticles showed contact angles of 87.8° to 98.3°, particle sizes between 80.42 and 80.95 nm, and the HIPPEs had zeta potentials ranging from -23 to -39 mV. The addition of Ca2+ enhanced stability by forming salt bridges, reducing particle size, and altering size distributions. Rheological and texture analysis showed that Ca2+ addition significantly improved the viscoelasticity of HCP-Ca nanoparticle-based HIPPEs, as well as increasing hardness and adhesiveness. Optical microscopy and magnetic imaging techniques revealed details about emulsion formation and oil-water distribution in HCP-Ca nanoparticle-based HIPPEs. The excellent printing stability and structural versatility of HCP-Ca nanoparticle-based HIPPEs allowed the formation of complex 3D structures, offering a valuable approach for fabricating processable and editable HIPPEs from waste materials. This paper aims to develop a food-grade copra protein-based Pickering HIPPE and explore differences in fabrication methods, providing new insights into the design of innovative Pickering stabilizers.

Highly Tunable, Nanomaterial-Functionalized Structural Templating of Intracellular Protein Structures Within Biological Species.

Inside living organisms, proteins are self-assembled into diverse 3D structures optimized for specific functions. This structure-function relationship can be exploited to synthesize functional materials through biotemplating and depositing functional materials onto protein structures. However, conventional biotemplating faces limitations due to the predominantly intracellular existence of proteins and associated challenges in achieving tunability while preserving functionality. In this study, Conversion to Advanced Materials via labeled Biostructures (CamBio), an integrated biotemplating platform that involves labeling target protein structures with antibodies followed by the growth of functional materials, ensuring outstanding nanostructure tunability is proposed. Protein-derived plasmonic nanostructures created by CamBio can serve as precise quantitative tools for assessing target species is demonstrated. The assessment is achieved through highly tunable and efficient surface-enhanced Raman spectroscopy (SERS). CamBio enables the formation of dense nanogap hot spots among metal nanoparticles, templated by diverse fibrous proteins comprising densely repeated monomers. Furthermore, iterative antibody labeling strategies to adjust the antibody density surrounding targets, amplifying the number of nanogaps and consequently improving SERS performance are employed. Finally, cell-patterned substrates and whole meat sections as SERS substrates, confirming their easily accessible, cost-effective, scalable preparation capabilities and dimensional tunability are incorporated.

ASpdb: an integrative knowledgebase of human protein isoforms from experimental and AI-predicted structures.

Alternative splicing is a crucial cellular process in eukaryotes, enabling the generation of multiple protein isoforms with diverse functions from a single gene. To better understand the impact of alternative splicing on protein structures, protein-protein interaction and human diseases, we developed ASpdb (https://biodataai.uth.edu/ASpdb/), a comprehensive database integrating experimentally determined structures and AlphaFold 2-predicted models for human protein isoforms. ASpdb includes over 3400 canonical isoforms, each represented by both experimentally resolved and predicted structures, and >7200 alternative isoforms with AlphaFold 2 predictions. In addition to detailed splicing events, 3D structures, sequence variationsand functional annotations, ASpdb uniquely offers comparative analyses and visualization of structural alterations among isoforms. This resource is invaluable for advancing research in alternative splicing, structural biologyand disease mechanisms.

Recent Development of Fibrous Hydrogels: Properties, Applications and Perspectives.

Fibrous hydrogels (FGs), characterized by a 3D network structure made from prefabricated fibers, fibrils and polymeric materials, have emerged as significant materials in numerous fields. However, the challenge of balancing mechanical properties and functions hinders their further development. This article reviews the main advantages of FGs, including enhanced mechanical properties, high conductivity, high antimicrobial and anti-inflammatory properties, stimulus responsiveness, and an extracellular matrix (ECM)-like structure. It also discusses the influence of assembly methods, such as fiber cross-linking, interfacial treatments of fibers with hydrogel matrices, and supramolecular assembly, on the diverse functionalities of FGs. Furthermore, the mechanisms for improving the performance of the above five aspects are discussed, such as creating ion carrier channels for conductivity, in situ gelation of drugs to enhance antibacterial and anti-inflammatory properties, and entanglement and hydrophobic interactions between fibers, resulting in ECM-like structured FGs. In addition, this review addresses the application of FGs in sensors, dressings, and tissue scaffolds based on the synergistic effects of optimizing the performance. Finally, challenges and future applications of FGs are discussed, providing a theoretical foundation and new insights for the design and application of cutting-edge FGs.

Mullite Synthesis Using Porous 3D Structures Consisting of Nanofibrils of Aluminum Oxyhydroxide Chemically Modified with Ethoxysilanes

Nanocrystalline mullite was synthetized by annealing a highly porous 3D structure consisting of nanofibrous aluminum oxyhydroxides treated with ethoxysilanes. The chemical, structural, and phase transformations in the aluminosilicate nanosystem were studied in the temperature range between 100 and 1600 °C. The features of the solid-phase synthesis of mullite at the interface of crystalline alumina with a liquid silica layer are discussed. It was established that chemical modification of the alumina surface with ethoxysilanes significantly limits the interphase mass transport and delays the phase transformation of the amorphous oxide into γ-Al2O3, which begins at temperatures above 1000 °C, while the basic structural nanofibrils are already crystallized at ~850 °C. The formation of mullite was completed at temperatures ≥ 1200 °C, where the fraction of γ-Al2O3 sharply decreased.

High detail resolution cellulose structures through electroprinting.

Electrospinning is a technique used to fabricate polymer fibers in micro- and nanoscales. Due to the large distance between the nozzle and collector, there is a limited positioning accuracy of electrospun fibers. To enhance the possibility of fabricating structures with micrometer placement, an electroprinting technique has been developed. By reducing the distance between the nozzle and the collector it is demonstrated that it is possible to get an improved control over fiber positioning which gives a possibility to fabricate designed 3D structures at the micron scale. In this study, cellulose acetate (CA) has been selected as a biomaterial to advance the 3D printing of membranes with possible use in separation applications. Various parameters, such as CA concentration and molecular weight, printing speed, printing pattern, applied voltage, etc. are evaluated with respect to printing control. Results indicate that by optimizing the printing parameters it is possible to print structures with inter- fiber distances down to 3µm and fiber diameters at a sub-µm scale. This electroprinting development is promising for the fabrication of customized separation membranes. However, printing speed still remains a challenge.

3D Point Cloud Fusion Method Based on EMD Auto-Evolution and Local Parametric Network

Although the development of high-resolution remote sensing satellite technology has made it possible to reconstruct the 3D structure of object-level features using satellite imagery, the results from a single reconstruction are often insufficient to comprehensively describe the 3D structure of the target. Therefore, developing an effective 3D point cloud fusion method can fully utilize information from multiple observations to improve the accuracy of 3D reconstruction. To this end, this paper addresses the problems of shape distortion and sparse point cloud density in existing 3D point cloud fusion methods by proposing a 3D point cloud fusion method based on Earth mover’s distance (EMD) auto-evolution and local parameterization network. Our method is divided into two stages. In the first stage, EMD is introduced as a key metric for evaluating the fusion results, and a point cloud fusion method based on EMD auto-evolution is constructed. The method uses an alternating iterative technique to sequentially update the variables and produce an initial fusion result. The second stage focuses on point cloud optimization by constructing a local parameterization network for the point cloud, mapping the upsampled point cloud in the 2D parameter domain back to the 3D space to complete the optimization. Through these two steps, the method achieves the fusion of two sets of non-uniform point cloud data obtained from satellite stereo images into a single, denser 3D point cloud that more closely resembles the true target shape. Experimental results demonstrate that our fusion method outperforms other classical comparison algorithms for targets such as buildings, planes, and ships, and achieves a fused RMSE of approximately 2 m and an EMD accuracy better than 0.5.

Abstract 4138380: Cardiac protection of hiPSC-CMs loaded chitosan cardiac patch in myocardial infarcted swine

Background: The low grafting rate of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) following direct injection into the myocardium limits the efficacy of cardiac repair after myocardial infarction (MI). Chitosan-based scaffolds have emerged as functional biomaterials for designing delivery systems in cardiac therapies. This study aimed to enhance the potency of cardiac repair using a hiPSC-CMs loaded chitosan cardiac muscle patch (hCCMP). Methods: The patches were fabricated using chitosan. Characterization of the chitosan patches involved assessing their swelling rate and porosity. The biocompatibility of the hCCMP was analyzed through scanning electron microscopy (SEM) and the CCK8 assay. 16 Yorkshire swine (15-20 kg, 45-50 days of age) were randomly divided into 4 groups (n=4 per group): Sham, MI without further intervention, MI with an empty patch (without hiPSC-CMs), and MI with hCCMP implantation. One and four weeks post-MI, heart function, Infarction size, myocardial perfusion and metabolism were evaluated via cardiac PET-MRI. Engraftment was assessed through human cardiac troponin T staining. Histological analysis including left ventricular anterior wall thickness, cardiac remodeling, angiogenesis, arterialization, and apoptosis in the infarct border area were analyzed using immunofluorescence. Results: SEM showed that the chitosan patch had regular pore size and good 3D structure; porosity was about (96.7±0.37)%. On day3, the patch swelling rate was about (715±64.55)%. SEM, CCK8 assay showed a normal cells growth in the chitosan patch. The hiPSC-CMs grafted well with chitosan patch delivery systems and was associated with significantly improvement in LV function, infarction size, angiogenesis and cardiomyocyte apoptosis in pigs 4 weeks after MI. Conclusions: The 3D chitosan cardiac patch with hiPSC-CMs loaded can enhance the potency of cardiac repair in pigs after MI and present a novel and promising therapic strategy.

M630L MUTATION DISRUPTS THE STRUCTURE CONFORMATION OF BRUTON TYROSINE KINASE (BTK) DOMAIN IN PATIENT WITH X-LINKED AGAMMAGLOBULINEMIA: INSIGHTS FROM IN SILICO

X-Linked Agammaglobulinemia (XLA) is a rare inherited disease, attributed to mutations found in the Bruton Tyrosine Kinase (BTK) gene. This research outlines the application of Molecular Modelling and Simulation to predict the effects of a novel non-synonymous Single Nucleotide Polymorphism (nsSNP) reported in the BTK kinase domain protein of a male XLA patient. The mutation at position c.1888A>T causes a substitution of p.M630L within the kinase domain of the BTK protein. Functional assessment using in silico prediction tools (SIFT, Polyphen-2, PROVEAN, MutationAssessor, PANTHER, FATHMM, MutPred and MutationTaster) predicted the mutation to be deleterious, potentially disrupting both the structure and function of the protein. Nevertheless, the mutation is not located at the active site of the kinase domain. Consequently, the molecular dynamics (MD) simulations were performed to investigate the impact of amino acid substitution to the three-dimensional (3D) conformational structure of the BTK protein, contributing to the disease phenotype observed in the reported patient. MD analysis, clustering analysis and Principle Component Analysis (PCA) revealed that the 3D conformational structure of the kinase domain of mutant protein to be more compact and rigid compared to the wildtype. Given that the alterations in protein structure can influence their functional characteristics, the p.M630L mutation within the BTK protein kinase domain might disrupt the protein function, potentially impeding the maturation of B cells and contributing to the onset of XLA disease.

LociPARSE: A Locality-aware Invariant Point Attention Model for Scoring RNA 3D Structures.

A scoring function that can reliably assess the accuracy of a 3D RNA structural model in the absence of experimental structure is not only important for model evaluation and selection but also useful for scoring-guided conformational sampling. However, high-fidelity RNA scoring has proven to be difficult using conventional knowledge-based statistical potentials and currently available machine learning-based approaches. Here, we present lociPARSE, a locality-aware invariant point attention architecture for scoring RNA 3D structures. Unlike existing machine learning methods that estimate superposition-based root-mean-square deviation (RMSD), lociPARSE estimates Local Distance Difference Test (lDDT) scores capturing the accuracy of each nucleotide and its surrounding local atomic environment in a superposition-free manner, before aggregating information to predict global structural accuracy. Tested on multiple datasets including CASP15, lociPARSE significantly outperforms existing statistical potentials (rsRNASP, cgRNASP, DFIRE-RNA, and RASP) and machine learning methods (ARES and RNA3DCNN) across complementary assessment metrics. lociPARSE is freely available at https://github.com/Bhattacharya-Lab/lociPARSE.