Protein 3D Structure Analysis Research Articles

An analysis of double-quantum coherence ESR in an N-spin system: Analytical expressions and predictions.

Electron spin resonance pulsed dipolar spectroscopy (PDS) has become popular in protein 3D structure analysis. PDS studies yield distance distributions between a pair or multiple pairs of spin probes attached to protein molecules, which can be used directly in structural studies or as constraints in theoretical predictions. Double-quantum coherence (DQC) is a highly sensitive and accurate PDS technique to study protein structures in the solid state and under physiologically relevant conditions. In this work, we have derived analytical expressions for the DQC signal for a system with N-dipolar coupled spin-1/2 particles in the solid state. The expressions are integrated over the relevant spatial parameters to obtain closed form DQC signal expressions. These expressions contain the concentration-dependent "instantaneous diffusion" and the background signal. For micromolar and lower concentrations, these effects are negligible. An approximate analysis is provided for cases of finite pulses. The expressions obtained in this work should improve the analysis of DQC experimental data significantly, and the analytical approach could be extended easily to a wide range of magnetic resonance phenomena.

SpatialPPI: Three-dimensional space protein-protein interaction prediction with AlphaFold Multimer

Rapid advancements in protein sequencing technology have resulted in gaps between proteins with identified sequences and those with mapped structures. Although sequence-based predictions offer insights, they can be incomplete due to the absence of structural details. Conversely, structure-based methods face challenges with respect to newly sequenced proteins. The AlphaFold Multimer has remarkable accuracy in predicting the structure of protein complexes. However, it cannot distinguish whether the input protein sequences can interact. Nonetheless, by analyzing the information in the models predicted by the AlphaFold Multimer, we propose a highly accurate method for predicting protein interactions. This study focuses on the use of deep neural networks, specifically to analyze protein complex structures predicted by the AlphaFold Multimer. By transforming atomic coordinates and utilizing sophisticated image-processing techniques, vital 3D structural details were extracted from protein complexes. Recognizing the significance of evaluating residue distances in protein interactions, this study leveraged image recognition approaches by integrating Densely Connected Convolutional Networks (DenseNet) and Deep Residual Network (ResNet) within 3D convolutional networks for protein 3D structure analysis. When benchmarked against leading protein-protein interaction prediction methods, such as SpeedPPI, D-script, DeepTrio, and PEPPI, our proposed method, named SpatialPPI, exhibited notable efficacy, emphasizing the promising role of 3D spatial processing in advancing the realm of structural biology. The SpatialPPI code is available at: https://github.com/ohuelab/SpatialPPI.

SLC35F2-SYVN1-TRIM59 axis critically regulates ferroptosis of pancreatic cancer cells by inhibiting endogenous p53.

Pancreatic cancer cells undergo intricate metabolic reprogramming to sustain their survival and proliferation. p53 exhibits a dual role in tumor cell ferroptosis. However, the precise role and mechanisms underlying wild-type p53 activation in promoting ferroptosis in pancreatic cancer cells remain obscure. In this study, we applied bioinformatics tools and performed an analysis of clinical tissue sample databases and observed a significantly upregulated expression of solute carrier family 35 member F2 (SLC35F2) in pancreatic cancer tissues. Our clinical investigations indicated that elevated SLC35F expression was related to adverse survival outcomes. Through multi-omics analyses, we discerned that SLC35F2 influences the transcriptome and inhibits ferroptosis in pancreatic cancer cells. Moreover, our findings reveal the pivotal involvement of p53 in mediating SLC35F2-mediated ferroptosis, both in vitro and in vivo. SLC35F2 inhibits ferroptosis by facilitating TRIM59-mediated p53 degradation. Further mechanistic investigations demonstrated that SLC35F2 competitively interacts with the E3 ubiquitin ligase SYVN1 of TRIM59, thereby stabilizing TRIM59 expression and consequentially promoting p53 degradation. Utilizing protein 3D structure analysis and drug screening, we identified irinotecan hydrochloride and lapatinib ditosylate as compounds targeting SLC35F2, augmenting the antitumor effect of imidazole ketone erastin (IKE) in a wild-type p53 patient-derived xenograft (PDX) model. However, in the p53 mutant PDX model, irinotecan hydrochloride and lapatinib ditosylate did not alter the sensitivity of the tumor xenograft model to IKE-triggered ferroptosis. In summary, our work establishes a novel mechanism wherein the SLC35F2-SYVN1-TRIM59 axis critically regulates ferroptosis of pancreatic cancer cells by inhibiting endogenous p53. Thus, SLC35F2 emerges as a promising therapeutic target for treating pancreatic cancer.

Genome-Wide Identification of the PYL Gene Family in Chenopodium quinoa: From Genes to Protein 3D Structure Analysis

The halophytic crop Chenopodium quinoa has a remarkable resistance to harsh growth conditions in suboptimal environments and marginal soils. Additionally, quinoa is a pseudocereal and produces seeds with outstanding nutritional value. Quinoa is an allotetraploid (2n = 4× = 36) with an estimated genome size of approximately 1.5 Gbp. In plants, the family of pyrabactin resistance 1 (PYR1)/PYR1-like (PYL)/regulatory components of ABA receptors (RCAR) play a vital role in the initial step of ABA signaling, leading to abiotic stress resistance. Here 20 CqPYL genes were identified using the genome-search method. Based on the phylogenetic analysis, these CqPYL genes were divided into three classes or subfamilies. These genes have different structures and intron numbers, even within the same subfamily. Analysis of conserved motifs showed the presence of the PYR_PYL_RCAR motif domain in each PYL protein sequence. Furthermore, the tissue-specific expression of CqPYLs was analyzed through public available RNA-seq data. CqPYL4a/b and CqPYL8c/d showed higher expression levels in seedlings. Finally, 3D structures of the CqPYL proteins were predicted by homology modeling and analyzed through topology inspection to speculate on putative new ABA receptor features. This study provides a theoretical basis for further functional study of PYL genes for stress-resistance breeding of quinoa and other crops.

Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants.

SummaryWhole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a “personalized structural biology” (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.

SWORD2: hierarchical analysis of protein 3D structures.

Understanding the functions and origins of proteins requires splitting these macromolecules into fragments that could be independent in terms of folding, activity, or evolution. For that purpose, structural domains are the typical level of analysis, but shorter segments, such as subdomains and supersecondary structures, are insightful as well. Here, we propose SWORD2, a web server for exploring how an input protein structure may be decomposed into ‘Protein Units’ that can be hierarchically assembled to delimit structural domains. For each partitioning solution, the relevance of the identified substructures is estimated through different measures. This multilevel analysis is achieved by integrating our previous work on domain delineation, ‘protein peeling’ and model quality assessment. We hope that SWORD2 will be useful to biologists searching for key regions in their proteins of interest and to bioinformaticians building datasets of protein structures. The web server is freely available online: https://www.dsimb.inserm.fr/SWORD2.

Prediction of the Impact of Deleterious Nonsynonymous Single Nucleotide Polymorphisms on the Human RRM2B Gene: A Molecular Modeling Study.

RRM2B gene encodes ribonucleoside-diphosphate reductase subunit M2 B, the p53-inducible small subunit (p53R2) of ribonucleotide reductase (RNR), an enzyme catalyzing dNTP synthesis for mitochondrial DNA. Defects in this gene may cause severe mitochondrial disease affecting mainly the nervous system. This study is aimed at examining the effect of deleterious nonsynonymous SNP (nsSNP) on the structure of the RRM2B protein, using a variety of prediction tools followed by a molecular modeling analysis. After using 13 algorithms, 19 nsSNPs were predicted deleterious. Among these variants, 18 decreased the protein stability and 16 were localized in very highly conserved regions. Protein 3D structure analysis showed that 18 variants changed amino acid interactions. These results concur with what has been found in experimental trials; 7 deleterious nsSNPs were previously reported in patients suffering from genetic disorders affecting the nervous system. Thus, our study will provide useful information to design more efficient and fast genetic tests to find RRM2B gene mutations.

B38-CAP is a bacteria-derived ACE2-like enzyme that suppresses hypertension and cardiac dysfunction

Angiotensin-converting enzyme 2 (ACE2) is critically involved in cardiovascular physiology and pathology, and is currently clinically evaluated to treat acute lung failure. Here we show that the B38-CAP, a carboxypeptidase derived from Paenibacillus sp. B38, is an ACE2-like enzyme to decrease angiotensin II levels in mice. In protein 3D structure analysis, B38-CAP homolog shares structural similarity to mammalian ACE2 with low sequence identity. In vitro, recombinant B38-CAP protein catalyzed the conversion of angiotensin II to angiotensin 1–7, as well as other known ACE2 target peptides. Treatment with B38-CAP suppressed angiotensin II-induced hypertension, cardiac hypertrophy, and fibrosis in mice. Moreover, B38-CAP inhibited pressure overload-induced pathological hypertrophy, myocardial fibrosis, and cardiac dysfunction in mice. Our data identify the bacterial B38-CAP as an ACE2-like carboxypeptidase, indicating that evolution has shaped a bacterial carboxypeptidase to a human ACE2-like enzyme. Bacterial engineering could be utilized to design improved protein drugs for hypertension and heart failure.

Identification of exon skipping events associated with Alzheimer\u2019s disease in the human hippocampus

BackgroundAt least 90% of human genes are alternatively spliced. Alternative splicing has an important function regulating gene expression and miss-splicing can contribute to risk for human diseases, including Alzheimer’s disease (AD).MethodsWe developed a splicing decision model as a molecular mechanism to identify functional exon skipping events and genetic variation affecting alternative splicing on a genome-wide scale by integrating genomics, transcriptomics, and neuroimaging data in a systems biology approach. In this study, we analyzed RNA-Seq data of hippocampus brain tissue from Alzheimer’s disease (AD; n = 24) and cognitively normal elderly controls (CN; n = 50) and identified three exon skipping events in two genes (RELN and NOS1) as significantly associated with AD (corrected p-value < 0.05 and fold change > 1.5). Next, we identified single-nucleotide polymorphisms (SNPs) affecting exon skipping events using the splicing decision model and then performed an association analysis of SNPs potentially affecting three exon skipping events with a global cortical measure of amyloid-β deposition measured by [18F] Florbetapir position emission tomography (PET) scan as an AD-related quantitative phenotype. A whole-brain voxel-based analysis was also performed.ResultsTwo exons in RELN and one exon in NOS1 showed significantly lower expression levels in the AD participants compared to CN participants, suggesting that the exons tend to be skipped more in AD. We also showed the loss of the core protein structure due to the skipped exons using the protein 3D structure analysis. The targeted SNP-based association analysis identified one intronic SNP (rs362771) adjacent to the skipped exon 24 in RELN as significantly associated with cortical amyloid-β levels (corrected p-value < 0.05). This SNP is within the splicing regulatory element, i.e., intronic splicing enhancer. The minor allele of rs362771 conferred decreases in cortical amyloid-β levels in the right temporal and bilateral parietal lobes.ConclusionsOur results suggest that exon skipping events and splicing-affecting SNPs in the human hippocampus may contribute to AD pathogenesis. Integration of multiple omics and neuroimaging data provides insights into possible mechanisms underlying AD pathophysiology through exon skipping and may help identify novel therapeutic targets.

Increasing thermal stability of glutamate decarboxylase from Escherichia. coli by site-directed saturation mutagenesis and its application in GABA production

Gamma-amino butyric acid (GABA) is an important bio-product used in pharmaceuticals, functional foods, and a precursor of the biodegradable plastic polyamide 4 (Nylon 4). Glutamate decarboxylase B (GadB) from Escherichia. coli is a highly active biocatalyst that can convert l-glutamate to GABA. However, its practical application is limited by the poor thermostability and only active under acidic conditions of GadB. In this study, we performed site-directed saturation mutagenesis of the N-terminal residues of GadB from Escherichia coli to improve its thermostability. A triple mutant (M6, Gln5Ile/Val6Asp/Thr7Gln) showed higher thermostability, with a 5.6 times (560%) increase in half-life value at 45 °C, 8.7 °C rise in melting temperature (Tm) and a 14.3 °C rise in the temperature at which 50% of the initial activity remained after 15 min incubation (T1550), compared to wild-type enzyme. Protein 3D structure analysis showed that the induced new hydrogen bonds in the same polypeptide chain or between polypeptide chains in E. coli GadB homo-hexamer may be responsible for the improved thermostability. Increased thermostability contributed to increased GABA conversion ability. After 12 h conversion of 3 mol/L l-glutamate, GABA produced and mole conversion rate catalyzed by M6 whole cells was 297 g/L and 95%, respectively, while those by wild-type GAD was 273.5 g/L and 86.2%, respectively.

Protein family structure signature for multidomain proteins

The rapid increase in available protein structure datasets requires new techniques for fast, yet, effective analysis of protein 3D structures. In this work, we propose a structure-based signature for protein families, suitable for rapid analysis of multidomain protein structures. Our method is alignment-free, using protein strings as the basic representation. A key novelty is the two-stage approach, whereby an initial list of candidate protein superfamilies are rapidly identified using the protein family signature, and then information retrieval methods are applied only to the members of the candidate superfamilies. This approach is the key to both improved speed, and improved structure retrieval accuracy. Experimental results, including comparative results with state-of-the-art methods, demonstrate the performance of the proposed protein family signature on queries with multidomain protein structures.

CX, DPX, and PCW: Web Servers for the Visualization of Interior and Protruding Regions of Protein Structures in 3D and 1D.

The CX and DPX web-based servers at http://pongor.itk.ppke.hu/bioinfoservices are dedicated to the analysis of protein 3D structures submitted by the users as Protein Data Bank (PDB) files. CX computes an atomic protrusion index, cx that makes it possible to highlight the protruding atoms within a protein 3D structure. DPX calculates a depth index, dpx for buried atoms, and allows one to visualize the distribution of buried residues. CX and DPX visualize 3D structures colored according to the calculated indices and return PDB files that can be visualized using standard programs. A combined server site, the Protein Core Workbench allows visualization of dpx, cx, solvent-accessible area as well as the number of atomic contacts as 3D plots and 1D sequence plots. Online visualization of the 3D structures and 1D sequence plots are available in all three servers. Mirror sites are available at http://hydra.icgeb.trieste.it/protein/ .

The Subcellular Localization and Functional Analysis of Fibrillarin2, a Nucleolar Protein in Nicotiana benthamiana.

Nucleolar proteins play important roles in plant cytology, growth, and development. Fibrillarin2 is a nucleolar protein of Nicotiana benthamiana (N. benthamiana). Its cDNA was amplified by RT-PCR and inserted into expression vector pEarley101 labeled with yellow fluorescent protein (YFP). The fusion protein was localized in the nucleolus and Cajal body of leaf epidermal cells of N. benthamiana. The N. benthamiana fibrillarin2 (NbFib2) protein has three functional domains (i.e., glycine and arginine rich domain, RNA-binding domain, and α-helical domain) and a nuclear localization signal (NLS) in C-terminal. The protein 3D structure analysis predicted that NbFib2 is an α/β protein. In addition, the virus induced gene silencing (VIGS) approach was used to determine the function of NbFib2. Our results showed that symptoms including growth retardation, organ deformation, chlorosis, and necrosis appeared in NbFib2-silenced N. benthamiana.

Automated assignment of MS/MS cleavable cross-links in protein 3D-structure analysis.

CID-MS/MS cleavable cross-linkers hold an enormous potential for an automated analysis of cross-linked products, which is essential for conducting structural proteomics studies. The created characteristic fragment ion patterns can easily be used for an automated assignment and discrimination of cross-linked products. To date, there are only a few software solutions available that make use of these properties, but none allows for an automated analysis of cleavable cross-linked products. The MeroX software fills this gap and presents a powerful tool for protein 3D-structure analysis in combination with MS/MS cleavable cross-linkers. We show that MeroX allows an automatic screening of characteristic fragment ions, considering static and variable peptide modifications, and effectively scores different types of cross-links. No manual input is required for a correct assignment of cross-links and false discovery rates are calculated. The self-explanatory graphical user interface of MeroX provides easy access for an automated cross-link search platform that is compatible with commonly used data file formats, enabling analysis of data originating from different instruments. The combination of an MS/MS cleavable cross-linker with a dedicated software tool for data analysis provides an automated workflow for 3D-structure analysis of proteins. MeroX is available at www.StavroX.com .

Three-dimensional modeling and diversity analysis reveals distinct AVR recognition sites and evolutionary pathways in wild and domesticated wheat Pm3 R genes.

The Pm3 gene confers resistance against wheat powdery mildew. Studies of Pm3 diversity have shown that Pm3 alleles isolated from southern populations of wild emmer wheat located in Lebanon, Jordan, Israel, and Syria are more diverse and more distant from bread wheat alleles than alleles from the northern wild wheat populations located in Turkey, Iran, and Iraq. Therefore, southern populations from Israel were studied extensively to reveal novel Pm3 alleles that are absent from the cultivated gene pool. Candidate Pm3 genes were isolated via a polymerase chain reaction cloning approach. Known and newly identified Pm3 genes were subjected to variation analysis and polymorphic amino acid residues were superimposed on a three-dimensional (3D) model of PM3. The region of highest interspecies diversity between Triticum aestivum and T. dicoccoides lies in leucine-rich repeats (LRR) 19 to 24, whereas most intraspecies diversity in T. aestivum is located in LRR 25 to 28. Interestingly, these two regions are separated by one large LRR whose propensity for flexibility facilitates the conformation of the PM3 LRR domain into two differently structured models. The combination of evolutionary and protein 3D structure analysis revealed that Pm3 genes in wild and domesticated wheat show different evolutionary histories which might have been triggered through different interactions with the powdery mildew pathogen.

Reliable identification of cross-linked products in protein interaction studies by 13C-labeled p-benzoylphenylalanine.

We describe the use of the (13)C-labeled artificial amino acid p-benzoyl-L-phenylalanine (Bpa) to improve the reliability of cross-linked product identification. Our strategy is exemplified for two protein-peptide complexes. These studies indicate that in many cases the identification of a cross-link without additional stable isotope labeling would result in an ambiguous assignment of cross-linked products. The use of a (13)C-labeled photoreactive amino acid is considered to be preferred over the use of deuterated cross-linkers as retention time shifts in reversed phase chromatography can be ruled out. The observation of characteristic fragment ions additionally increases the reliability of cross-linked product assignment. Bpa possesses a broad reactivity towards different amino acids and the derived distance information allows mapping of spatially close amino acids and thus provides more solid structural information of proteins and protein complexes compared to the longer deuterated amine-reactive cross-linkers, which are commonly used for protein 3D-structure analysis and protein-protein interaction studies.

Incorporating Secondary Features into the General form of Chou's PseAAC for Predicting Protein Structural Class

Protein structure information is very useful for the confirmation of protein function. The protein structural class can provide information for protein 3D structure analysis, causing the conformation of the protein overall folding type plays a significant part in molecular biology. In this paper, we focus on the prediction of protein structural class which was based on new feature representation. We extract features from the Chou-Fasman parameter, amino acid compositions, amino acids hydrophobicity features, polarity information and pair-coupled amino acid composition. The prediction result by the Support vector machine (SVM) classifier shows that our method is better than some others.

A Hidden Markov Model applied to the protein 3D structure analysis

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. A Hidden Markov Model has been set up to optimally compress 3D conformation of proteins into a structural alphabet (SA), corresponding to a library of limited and representative SA-letters. Each SA-letter corresponds to a set of short local fragments of four C α similar both in terms of geometry and in the way in which these fragments are concatenated in order to make a protein. The discretization of protein backbone local conformation as series of SA-letters results on a simplification of protein 3D coordinates into a unique 1D representation. Some evidence is presented that such approach can constitute a very relevant way to analyze protein architecture in particular for protein structure comparison or prediction.

CX, DPX and PRIDE: WWW servers for the analysis and comparison of protein 3D structures

The WWW servers at are dedicated to the analysis of protein 3D structures submitted by the users as the Protein Data Bank (PDB) files. CX computes an atomic protrusion index that makes it possible to highlight the protruding atoms within a protein 3D structure. DPX calculates a depth index for the buried atoms and makes it possible to analyze the distribution of buried residues. CX and DPX return PDB files containing the calculated indices that can then be visualized using standard programs, such as Swiss-PDBviewer and Rasmol. PRIDE compares 3D structures using a fast algorithm based on the distribution of inter-atomic distances. The options include pairwise as well as multiple comparisons, and fold recognition based on searching the CATH fold database.