Structural Features and Physiological Associations of Human 14-3-3ζ Pseudogenes

There are about 14,000 pseudogenes that are mutated or truncated sequences resembling functional parent genes. About two-thirds of pseudogenes are processed, while others are duplicated. Although initially thought dead, emerging studies indicate they have functional and regulatory roles. We study 14-3-3ζ, an adaptor protein that regulates cytokine signaling and inflammatory diseases, including rheumatoid arthritis, cancer, and neurological disorders. To understand how 14-3-3ζ (gene symbol YWHAZ) performs diverse functions, we examined the human genome and identified nine YWHAZ pseudogenes spread across many chromosomes. Unlike the 32 kb exon-to-exon sequence in YWHAZ, all pseudogenes are much shorter and lack introns. Out of six, four YWHAZ exons are highly conserved, but the untranslated region (UTR) shows significant diversity. The putative amino acid sequence of pseudogenes is 78-97% homologous, resulting in striking structural similarities with the parent protein. The OMIM and Decipher database searches revealed chromosomal loci containing pseudogenes are associated with human diseases that overlap with the parent gene. To the best of our knowledge, this is the first report on pseudogenes of the 14-3-3 family protein and their implications for human health. This bioinformatics-based study introduces a new insight into the complexity of 14-3-3ζ's functions in biology.

A multiscale approach reveals the molecular architecture of the autoinhibited kinesin KIF5A

Kinesin-1 is a microtubule motor that transports cellular cargo along microtubules. KIF5A is one of three kinesin-1 isoforms in humans, all of which are autoinhibited by an interaction between the motor and an IAK motif in the proximal region of the C-terminal tail. The C-terminal tail of KIF5A is ∼80 residues longer than the other two kinesin-1 isoforms (KIF5B and KIF5C) and it is unclear if it contributes to autoinhibition. Mutations in KIF5A cause neuronal diseases and could affect autoinhibition, as reported for a mutation that skips exon 27, altering its C-terminal sequence. Here, we combined negative-stain electron microscopy, crosslinking mass spectrometry (XL-MS) and AlphaFold2 structure prediction to determine the molecular architecture of the full-length autoinhibited KIF5A homodimer, in the absence of light chains. We show that KIF5A forms a compact, bent conformation, through a bend between coiled-coils 2 and 3, around P687. XL-MS of WT KIF5A revealed extensive interactions between residues in the motor, between coiled-coil 1 and the motor, between coiled-coils 1 and 2, with coiled-coils 3 and 4, and the proximal region of the C-terminal tail and the motor in the autoinhibited state, but not between the distal C-terminal region and the rest of the molecule. While negative-stain electron microscopy of exon-27 KIF5A splice mutant showed the presence of autoinhibited molecules, XL-MS analysis suggested that its autoinhibited state is more labile. Our model offers a conceptual framework for understanding how mutations within the motor and stalk domain may affect motor activity.

Foldseek reveals a CBGA prenylating enzyme GlyMa_02G168000 from Glycine max

The present research provides an application for an aromatic prenyltransferase from Glycine max for use in heterologous microorganism expression to generate cannabinoids. The known cannabinoid prenyltransferase CsPT04 was queried in FoldSeek. An enzyme derived from Glycine max known as GLYMA_02G168000, which is a predicted homogentisate solanyltransferase, was identified and found to have affinity for the prenylation of geranyldiphosphate (GPP) and olivetolic acid (OA) to produce cannabigerolic acid (CBGA) and cannabigerol (CBG). The in vitro production of CBGA was accomplished through the heterologous expression of this prenyltransferase in Saccharomyces cerevisiae. After growing the yeast cells, a purified microsomal fraction was harvested, which was rich in the membrane-bound prenyltransferase GlyMa_02G168000. Addition of purified microsomal fraction to a reaction matrix facilitated the successful prenylation of externally supplied OA with GPP, culminating in the production of CBGA. Structural comparisons revealed a notably closer similarity between GLYMA_02G168000 and CsPT04, compared to the similarity of other cannabinoid prenyltransferases with CsPT04. Herein, a novel application for a homogentisate solanyltransferase has been established towards the production of cannabinoids.

Computational and AI-driven 3D structural analysis of human papillomavirus (HPV) oncoproteins E5, E6, and E7 reveal significant divergence of HPV E5 between low-risk and high-risk genotypes

There are over 220 identified genotypes of Human papillomavirus (HPV), and the HPV genome encodes 3 major oncogenes, E5, E6, and E7. Conservation and divergence in protein sequence and function between low-risk versus high-risk oncogenic HPV genotypes has not been fully characterized. Here, we used modern computational and structural folding algorithms to perform a comparative analysis of HPV E5, E6, and E7 between multiple low risk and high risk genotypes. We first identified significantly greater sequence divergence in E5 between low- and high-risk genotypes compared to E6 and E7. Next, we used AlphaFold to model the structure of papillomavirus proteins and complexes with high confidence, including some with no established consensus structure. We observed that HPV E5, but not E6 or E7, had a dramatically different 3D structure between low-risk and high-risk genotypes. To our knowledge, this is the first comparative analysis of HPV proteins using Alphafold artificial intelligence (AI) system. The marked differences in E5 sequence and structure in high-risk HPVs may contribute in important and underappreciated ways to the development of HPV-associated cancers.

The mystery of transient pregnancy-induced cushing's syndrome: a case report and literature review highlighting GNAS somatic mutations and LHCGR overexpression

PURPOSE

Transient pregnancy-induced Cushing's syndrome is a rare condition characterized by the manifestation of symptoms solely during pregnancy, which typically resolve spontaneously following delivery or miscarriage. While it has been established that GNAS is associated with adrenal tumors, its specific role in the pathogenesis of pregnancy-induced Cushing's syndrome remains uncertain.This work aims to examine the association between GNAS mutation and pregnancy-induced Cushing's syndrome.

METHODS

DNA was extracted from patients' peripheral blood and tumor tissues for whole-exome sequencing (WES) and Sanger sequencing. We used AlphaFold to predict the protein structure of wild-type and mutant GNAS and to make functional predictions, and immunohistochemistry was used to detect disease-associated protein expression. A review and summary of reported cases of transient pregnancy-induced Cushing's syndrome induced by pregnancy was conducted.

RESULTS

Using WES, we identified a somatic mutation in GNAS (NM_000516, c.C601T, p.R201C) that was predicted to have a deleterious effect using computational methods, such as AlphaFold. Human chorionic gonadotropin (hCG) stimulation tests had weakly positive results, and immunohistochemical staining of adrenal adenoma tissue also revealed positivity for luteinizing hormone/chorionic gonadotropin receptor (LHCGR) and cytochrome P450 family 11 subfamily B member 1 (CYP11B1). We reviewed 15 published cases of transient Cushing's syndrome induced by pregnancy. Among these cases, immunohistochemical staining of the adrenal gland showed positive LHCGR expression in 3 case reports, similar to our findings.

CONCLUSION

Transient pregnancy-induced Cushing's syndrome may be associated with somatic GNAS mutations and altered adrenal pathology due to abnormal activation of LHCGR.

An attacin antimicrobial peptide, Hill_BB_C10074, from Hermetia illucens with anti-Pseudomonas aeruginosa activity

BACKGROUND

There is a global need to develop new therapies to treat infectious diseases and tackle the rise in antimicrobial resistance. To date, the larvae of the Black Solider Fly, Hermetia illucens, have the largest repertoire of antimicrobial peptides derived from insects. Antimicrobial peptides are of particular interest in the exploration of alternative antimicrobials due to their potent action and reduced propensity to induce resistance compared with more traditional antibiotics.

RESULTS

The predicted attacin from H. illucens, Hill_BB_C10074, was first identified in the transcriptome of H. illucens populations that had been fed a plant-oil based diet. In this study, recombinant Hill_BB_C10074 (500 µg/mL), was found to possess potent antimicrobial activity against the serious Gram-negative pathogen, Pseudomonas aeruginosa. Sequence and structural homology modelling predicted that Hill_BB_C10074 formed a homotrimeric complex that may form pores in the Gram-negative bacterial outer membrane. In vitro experiments defined the antimicrobial action of Hill_BB_C10074 against P. aeruginosa and transmission electron microscopy and electrochemical impedance spectroscopy confirmed the outer membrane disruptive power of Hill_BB_C10074 which was greater than the clinically relevant antibiotic, polymyxin B.

CONCLUSIONS

Combining predictive tools with in vitro approaches, we have characterised Hill_BB_C10074 as an important insect antimicrobial peptide and promising candidate for the future development of clinical antimicrobials.

Channel Formation in Cry Toxins: An Alphafold-2 Perspective

Bacillus thuringiensis (Bt) strains produce pore-forming toxins (PFTs) that attack insect pests. Information for pre-pore and pore structures of some of these Bt toxins is available. However, for the three-domain (I-III) crystal (Cry) toxins, the most used Bt toxins in pest control, this crucial information is still missing. In these Cry toxins, biochemical data have shown that 7-helix domain I is involved in insertion in membranes, oligomerization and formation of a channel lined mainly by helix α4, whereas helices α1 to α3 seem to have a dynamic role during insertion. In the case of Cry1Aa, toxic against Manduca sexta larvae, a tetrameric oligomer seems to precede membrane insertion. Given the experimental difficulty in the elucidation of the membrane insertion steps, we used Alphafold-2 (AF2) to shed light on possible oligomeric structural intermediates in the membrane insertion of this toxin. AF2 very accurately (<1 Å RMSD) predicted the crystal monomeric and trimeric structures of Cry1Aa and Cry4Ba. The prediction of a tetramer of Cry1Aa, but not Cry4Ba, produced an 'extended model' where domain I helices α3 and α2b form a continuous helix and where hydrophobic helices α1 and α2 cluster at the tip of the bundle. We hypothesize that this represents an intermediate that binds the membrane and precedes α4/α5 hairpin insertion, together with helices α6 and α7. Another Cry1Aa tetrameric model was predicted after deleting helices α1 to α3, where domain I produced a central cavity consistent with an ion channel, lined by polar and charged residues in helix α4. We propose that this second model corresponds to the 'membrane-inserted' structure. AF2 also predicted larger α4/α5 hairpin n-mers (14 ≤n ≤ 17) with high confidence, which formed even larger (~5 nm) pores. The plausibility of these models is discussed in the context of available experimental data and current paradigms.

Improving AlphaFold predicted contacts in alpha-helical transmembrane proteins structures using structural features

Background

Residue contacts maps offer a 2-d reduced representation of 3-d protein structures and constitute a structural constraint and scaffold in structural modeling. In addition, contact maps are also an effective tool in identifying interhelical binding sites and drawing insights about protein function. While most works predict contact maps using features derived from sequences, we believe information from known structures can be leveraged for a prediction improvement in unknown structures where decent approximate structures such as ones predicted by AlphaFold2 are available.

Results

Alphafold2's predicted structures are found to be quite accurate at inter-helical residue contact prediction task, achieving 83% average precision. We adopt an unconventional approach, using features extracted from atomic structures in the neighborhood of a residue pair and use them to predicting residue contact. We trained on features derived from experimentally determined structures and predicted on features derived from AlphaFold2's predicted structures. Our results demonstrate a remarkable improvement over AlphaFold2 achieving over 91.9% average precision for held-out and over 89.5% average precision in cross validation experiments.

Conclusion

Training on features generated from experimentally determined structures, we were able to leverage knowledge from known structures to significantly improve the contacts predicted using AlphaFold2 structures. We demonstrated that using coordinates directly (instead of the proposed features) does not lead to an improvement in contact prediction performance.

Identification of two novel SALL1 mutations in chinese families with townes-brocks syndrome and literature review

BACKGROUND

Townes-Brocks syndrome is a rare autosomal dominant genetic syndrome caused by mutations in SALL1. The clinical features of Townes-Brocks syndrome are highly heterogonous. Identification of new SALL1 mutations and study of the relation between SALL1 mutations and clinical features can facilitate diagnosis of Townes-Brocks syndrome.

METHODS

We collected clinical data and blood samples of the two patients and their family members for whole-exome sequencing and Sanger sequencing. Prediction analysis of the SALL1variation protein structure was achieved using Alphafold. The clinical materials and gene sequencing results were analyzed. The clinical materials and gene sequencing results were analyzed. The related literature of Townes-Brocks syndrome were searched and the genotype-renal phenotype analysis was performed combined with this two cases.

RESULTS

Based on the clinical features and gene sequencing results, the two patients were diagnosed as Townes-Brocks syndrome. Two novel SALL1 mutations (c.878-887del and c.1240G > T) were identified, both of which were pathogenic mutations. The correlation between genotypes and renal phenotypes in Townes-Brocks syndrome patients caused by SALL1 mutation were summarized.

CONCLUSION

This study identified two novel mutations and provided new insights into the correlation of genotypes and renal phenotypes of Townes-Brocks syndrome.

SecretoMyc, a web-based database on mycobacteria secreted proteins and structure-based homology identification using bio-informatics tools

To better understand the interaction between the host and the Mycobacterium tuberculosis pathogen, it is critical to identify its potential secreted proteins. While various experimental methods have been successful in identifying proteins under specific culture conditions, they have not provided a comprehensive characterisation of the secreted proteome. We utilized a combination of bioinformatics servers and in-house software to identify all potentially secreted proteins from six mycobacterial genomes through the three secretion systems: SEC, TAT, and T7SS. The results are presented in a database that can be crossed referenced to selected proteomics and transcriptomics studies (https://secretomyc.cbs.cnrs.fr). In addition, thanks to the recent availability of Alphafold models, we developed a tool in order to identify the structural homologues among the mycobacterial genomes.

Structural Study of the Cobetia marina Bacteriophage 1 (Carin-1) by Cryo-EM

Most of studied bacteriophages (phages) are terrestrial viruses. However, marine phages are shown to be highly involved in all levels of oceanic regulation. They are, however, still largely overlooked by the scientific community. By inducing cell lysis on half of the bacterial population daily, their role and influence on the bacterial biomass and evolution, as well as their impact in the global biogeochemical cycles, is undeniable. Cobetia marina virus 1 (Carin-1) is a member of the Podoviridae family infecting the γ-protoabacteria C. marina. Here, we present the almost complete, nearly-atomic resolution structure of Carin-1 comprising capsid, portal, and tail machineries at 3.5 Å, 3.8 Å and 3.9 Å, respectively, determined by cryo-electron microscopy (cryo-EM). Our experimental results, combined with AlphaFold2 (AF), allowed us to obtain the nearly-atomic structure of Carin-1 by fitting and refining the AF atomic models in the high resolution cryo-EM map, skipping the bottleneck of de-novo manual building and speeding up the structure determination process. Our structural results highlighted the T7-like nature of Carin1, as well as several novel structural features like the presence of short spikes on the capsid, reminiscent those described for Rhodobacter capsulatus gene transfer agent (RcGTA). This is, to our knowledge, the first time such assembly is described for a bacteriophage, shedding light into the common evolution and shared mechanisms between gene transfer agents and phages. This first full structure determined for a marine podophage allowed to propose an infection mechanism different than the one proposed for the archetypal podophage T7. IMPORTANCE Oceans play a central role in the carbon cycle on Earth and on the climate regulation (half of the planet's CO2 is absorbed by phytoplankton photosynthesis in the oceans and just as much O2 is liberated). The understanding of the biochemical equilibriums of marine biology represents a major goal for our future. By lysing half of the bacterial population every day, marine bacteriophages are key actors of these equilibriums. Despite their importance, these marine phages have, so far, only been studied a little and, in particular, structural insights are currently lacking, even though they are fundamental for the understanding of the molecular mechanisms of their mode of infection. The structures described in our manuscript allow us to propose an infection mechanism that differs from the one proposed for the terrestrial T7 virus, and might also allow us to, in the future, better understand the way bacteriophages shape the global ecosystem.

Structural Analysis of Bacillus subtilis Sigma Factors

Bacteria use an array of sigma factors to regulate gene expression during different stages of their life cycles. Full-length, atomic-level structures of sigma factors have been challenging to obtain experimentally as a result of their many regions of intrinsic disorder. AlphaFold has now supplied plausible full-length models for most sigma factors. Here we discuss the current understanding of the structures and functions of sigma factors in the model organism, Bacillus subtilis, and present an X-ray crystal structure of a region of B. subtilis SigE, a sigma factor that plays a critical role in the developmental process of spore formation.

Ranking Peptide Binders by Affinity with AlphaFold

AlphaFold has revolutionized structural biology by predicting highly accurate structures of proteins and their complexes with peptides and other proteins. However, for protein-peptide systems, we are also interested in identifying the highest affinity binder among a set of candidate peptides. We present a novel competitive binding assay using AlphaFold to predict structures of the receptor in the presence of two peptides. For systems in which the individual structures of the peptides are well predicted, the assay captures the higher affinity binder in the bound state, and the other peptide in the unbound form with statistical significance. We test the application on six protein receptors for which we have experimental binding affinities to several peptides. We find that the assay is best suited for identifying medium to strong peptide binders that adopt stable secondary structures upon binding.

Critical assessment of methods of protein structure prediction (CASP)-Round XIV

Critical assessment of structure prediction (CASP) is a community experiment to advance methods of computing three-dimensional protein structure from amino acid sequence. Core components are rigorous blind testing of methods and evaluation of the results by independent assessors. In the most recent experiment (CASP14), deep-learning methods from one research group consistently delivered computed structures rivaling the corresponding experimental ones in accuracy. In this sense, the results represent a solution to the classical protein-folding problem, at least for single proteins. The models have already been shown to be capable of providing solutions for problematic crystal structures, and there are broad implications for the rest of structural biology. Other research groups also substantially improved performance. Here, we describe these results and outline some of the many implications. Other related areas of CASP, including modeling of protein complexes, structure refinement, estimation of model accuracy, and prediction of inter-residue contacts and distances, are also described.

Next generation protein structure predictions and genetic variant interpretation

The need to make sense of the thousands of genetic variants uncovered every day in terms of pathology or biological mechanism is acute. Many insights into how genetic changes impact protein function can be gleaned if three-dimensional structures of the associated proteins are available. The availability of a highly accurate method of predicting structures from amino acid sequences is thus potentially a great boost to those wanting to understand genetic changes. In this paper we discuss the current state of protein structures known for the human and other proteomes and how better structure predictions might impact on variant interpretation efforts. For the human proteome in particular, the state of the available structural data suggests that the impact on variant interpretation might be less than anticipated. We also discuss additional efforts in structure prediction that could further aid the understanding of genetic variants.

Machine learning in protein structure prediction

Prediction of protein structure from sequence has been intensely studied for many decades, owing to the problem's importance and its uniquely well-defined physical and computational bases. While progress has historically ebbed and flowed, the past two years saw dramatic advances driven by the increasing "neuralization" of structure prediction pipelines, whereby computations previously based on energy models and sampling procedures are replaced by neural networks. The extraction of physical contacts from the evolutionary record; the distillation of sequence-structure patterns from known structures; the incorporation of templates from homologs in the Protein Databank; and the refinement of coarsely predicted structures into finely resolved ones have all been reformulated using neural networks. Cumulatively, this transformation has resulted in algorithms that can now predict single protein domains with a median accuracy of 2.1 Å, setting the stage for a foundational reconfiguration of the role of biomolecular modeling within the life sciences.