TopSuite Web Server: A Meta-Suite for Deep-Learning-Based Protein Structure and Quality Prediction

Structure and dimerization properties of the plant-specific copper chaperone CCH

Copper chaperones of the ATX1 family are found in a wide range of organisms where these essential soluble carriers strictly control the transport of monovalent copper across the cytoplasm to various targets in diverse cellular compartments thereby preventing detrimental radical formation catalyzed by the free metal ion. Notably, the ATX1 family in plants contains two distinct forms of the cellular copper carrier. In addition to ATX1 having orthologs in other species, they also contain the copper chaperone CCH. The latter features an extra C-terminal extension whose function is still unknown. The secondary structure of this extension was predicted to be disordered in previous studies, although this has not been experimentally confirmed. Solution NMR studies on purified CCH presented in this study disclose that this region is intrinsically disordered regardless of the chaperone's copper loading state. Further biophysical analyses of the purified metallochaperone provide evidence that the C-terminal extension stabilizes chaperone dimerization in the copper-free and copper-bound states. A variant of CCH lacking the C-terminal extension, termed CCHΔ, shows weaker dimerization but similar copper binding. Computational studies further corroborate the stabilizing role of the C-terminal extension in chaperone dimerization and identify key residues that are vital to maintaining dimer stability.

Identification of potent schistosomicidal compounds predicted as type II-kinase inhibitors against Schistosoma mansoni c-Jun N-terminal kinase SMJNK

Introduction

Schistosomiasis has for many years relied on a single drug, praziquantel (PZQ) for treatment of the disease. Immense efforts have been invested in the discovery of protein kinase (PK) inhibitors; however, given that the majority of PKs are still not targeted by an inhibitor with a useful level of selectivity, there is a compelling need to expand the chemical space available for synthesizing new, potent, and selective PK inhibitors. Small-molecule inhibitors targeting the ATP pocket of the catalytic domain of PKs have the potential to become drugs devoid of (major) side effects, particularly if they bind selectively. This is the case for type II PK inhibitors, which cause PKs to adopt the so-called DFG-out conformation, corresponding to the inactive state of the enzyme.

Methods

The goal was to perform a virtual screen against the ATP pocket of the inactive JNK protein kinase. After virtually screening millions of compounds, Atomwise provided 85 compounds predicted to target c-Jun N-terminal kinase (JNK) as type II inhibitors. Selected compounds were screened in vitro against larval stage (schistosomula) of S. mansoni using the XTT assay. Adult worms were assessed for motility, attachment, and pairing stability. Active compounds were further analyzed by molecular docking against SmJNK.

Results

In total, 33 compounds were considered active in at least one of the assays, and two compounds were active in every in vitro screening assay. The two most potent compounds presented strong effects against both life stages of the parasite, and microscopy analysis showed phenotypic alterations on the tegument, in the gonads, and impairment of cell proliferation.

Conclusion

The approach to screen type II kinase inhibitors resulted in the identification of active compounds that will be further developed against schistosomiasis.

Structure-guided identification of a selective sulfonamide-based inhibitor targeting the human carbonic anhydrase VA isoform

In recent years, multistep hybrid computational protocols have attracted attention for their application in the drug discovery of enzyme inhibitors. So far, there are large collections of human carbonic anhydrase (hCA) inhibitors, but only a few of them selectively inhibit the mitochondrial isoforms hCA VA and VB as potential therapeutics in obesity treatment. Most sulfonamide-based inhibitors show poor selectivity for inhibiting isoforms of therapeutic interest over ubiquitous hCA I and hCA II. Herein, we propose a combination of ligand- and structure-based approaches to generate pharmacophore models for hCA VA inhibitors. Then, we performed a virtual screening (VS) campaign on a database of commercially available sulfonamides. Finally, the in silico screening followed by docking studies suggested several "hit compounds" that demonstrated to inhibit hCA VA at a low nanomolar concentration in a stopped-flow CO₂ hydrase assay. Notably, the best candidate, 2-(3,4-dihydro-2H-quinolin-1-yl)-N-(4-sulfamoylphenyl)acetamide (code name VAME-28) proved to be a potent hCA VA inhibitor (K_i value of 54.8 nM) and a more selective agent over hCA II when compared to the reference compound topiramate.

Pathogen Resistance Depending on Jacalin-Dirigent Chimeric Proteins Is Common among Poaceae but Absent in the Dicot Arabidopsis as Evidenced by Analysis of Homologous Single-Domain Proteins

MonocotJRLs are Poaceae-specific two-domain proteins that consist of a jacalin-related lectin (JRL) and a dirigent (DIR) domain which participate in multiple developmental processes, including disease resistance. For OsJAC1, a monocotJRL from rice, it has been confirmed that constitutive expression in transgenic rice or barley plants facilitates broad-spectrum disease resistance. In this process, both domains of OsJAC1 act cooperatively, as evidenced from experiments with artificially separated JRL- or DIR-domain-containing proteins. Interestingly, these chimeric proteins did not evolve in dicotyledonous plants. Instead, proteins with a single JRL domain, multiple JRL domains or JRL domains fused to domains other than DIR domains are present. In this study, we wanted to test if the cooperative function of JRL and DIR proteins leading to pathogen resistance was conserved in the dicotyledonous plant Arabidopsis thaliana. In Arabidopsis, we identified 50 JRL and 24 DIR proteins, respectively, from which seven single-domain JRL and two single-domain DIR candidates were selected. A single-cell transient gene expression assay in barley revealed that specific combinations of the Arabidopsis JRL and DIR candidates reduced the penetration success of barley powdery mildew. Strikingly, one of these pairs, AtJAX1 and AtDIR19, is encoded by genes located next to each other on chromosome one. However, when using natural variation and analyzing Arabidopsis ecotypes that express full-length or truncated versions of AtJAX1, the presence/absence of the full-length AtJAX1 protein could not be correlated with resistance to the powdery mildew fungus Golovinomyces orontii. Furthermore, an analysis of the additional JRL and DIR candidates in a bi-fluorescence complementation assay in Nicotiana benthamiana revealed no direct interaction of these JRL/DIR pairs. Since transgenic Arabidopsis plants expressing OsJAC1-GFP also did not show increased resistance to G. orontii, it was concluded that the resistance mediated by the synergistic activities of DIR and JRL proteins is specific for members of the Poaceae, at least regarding the resistance against powdery mildew. Arabidopsis lacks the essential components of the DIR-JRL-dependent resistance pathway.

Protein engineering for feedback resistance in 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase

Abstract

The shikimate pathway delivers aromatic amino acids (AAAs) in prokaryotes, fungi, and plants and is highly utilized in the industrial synthesis of bioactive compounds. Carbon flow into this pathway is controlled by the initial enzyme 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase (DAHPS). AAAs produced further downstream, phenylalanine (Phe), tyrosine (Tyr), and tryptophan (Trp), regulate DAHPS by feedback inhibition. Corynebacterium glutamicum, the industrial workhorse for amino acid production, has two isoenzymes of DAHPS, AroF (Tyr sensitive) and AroG (Phe and Tyr sensitive). Here, we introduce feedback resistance against Tyr in the class I DAHPS AroF (AroF_cg). We pursued a consensus approach by drawing on structural modeling, sequence and structural comparisons, knowledge of feedback-resistant variants in E. coli homologs, and computed folding free energy changes. Two types of variants were predicted: Those where substitutions putatively either destabilize the inhibitor binding site or directly interfere with inhibitor binding. The recombinant variants were purified and assessed in enzyme activity assays in the presence or absence of Tyr. Of eight AroF_cg variants, two yielded > 80% (E154N) and > 50% (P155L) residual activity at 5 mM Tyr and showed > 50% specific activity of the wt AroF_cg in the absence of Tyr. Evaluation of two and four further variants at positions 154 and 155 yielded E154S, completely resistant to 5 mM Tyr, and P155I, which behaves similarly to P155L. Hence, feedback-resistant variants were found that are unlikely to evolve by point mutations from the parental gene and, thus, would be missed by classical strain engineering.

Key points

• We introduce feedback resistance against Tyr in the class I DAHPS AroF

• Variants at position 154 (155) yield > 80% (> 50%) residual activity at 5 mM Tyr

• The variants found are unlikely to evolve by point mutations from the parental gene

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12166-9.

A MademoiseLLE domain binding platform links the key RNA transporter to endosomes

Spatiotemporal expression can be achieved by transport and translation of mRNAs at defined subcellular sites. An emerging mechanism mediating mRNA trafficking is microtubule-dependent co-transport on shuttling endosomes. Although progress has been made in identifying various components of the endosomal mRNA transport machinery, a mechanistic understanding of how these RNA-binding proteins are connected to endosomes is still lacking. Here, we demonstrate that a flexible MademoiseLLE (MLLE) domain platform within RNA-binding protein Rrm4 of Ustilago maydis is crucial for endosomal attachment. Our structure/function analysis uncovered three MLLE domains at the C-terminus of Rrm4 with a functionally defined hierarchy. MLLE3 recognises two PAM2-like sequences of the adaptor protein Upa1 and is essential for endosomal shuttling of Rrm4. MLLE1 and MLLE2 are most likely accessory domains exhibiting a variable binding mode for interaction with currently unknown partners. Thus, endosomal attachment of the mRNA transporter is orchestrated by a sophisticated MLLE domain binding platform.

MUfoldQA_G: High-accuracy protein model QA via retraining and transformation

Protein tertiary structure prediction is an active research area and has attracted significant attention recently due to the success of AlphaFold from DeepMind. Methods capable of accurately evaluating the quality of predicted models are of great importance. In the past, although many model quality assessment (QA) methods have been developed, their accuracies are not consistently high across different QA performance metrics for diverse target proteins. In this paper, we propose MUfoldQA_G, a new multi-model QA method that aims at simultaneously optimizing Pearson correlation and average GDT-TS difference, two commonly used QA performance metrics. This method is based on two new algorithms MUfoldQA_Gp and MUfoldQA_Gr. MUfoldQA_Gp uses a new technique to combine information from protein templates and reference protein models to maximize the Pearson correlation QA metric. MUfoldQA_Gr employs a new machine learning technique that resamples training data and retrains adaptively to learn a consensus model that is better than naïve consensus while minimizing average GDT-TS difference. MUfoldQA_G uses a new method to combine the results of MUfoldQA_Gr and MUfoldQA_Gp so that the final QA prediction results achieve low average GDT-TS difference that is close to the results from MUfoldQA_Gr, while maintaining high Pearson correlation that is the same as the results from MUfoldQA_Gp. In CASP14 QA categories, MUfoldQA_G ranked No. 1 in Pearson correlation and No. 2 in average GDT-TS difference.

In silico approach to understand epigenetics of POTEE in ovarian cancer

Ovarian cancer is the third leading cause of cancer-related deaths in India. Epigenetics mechanisms seemingly plays an important role in ovarian cancer. This paper highlights the crucial epigenetic changes that occur in POTEE that get hypomethylated in ovarian cancer. We utilized the POTEE paralog mRNA sequence to identify major motifs and also performed its enrichment analysis. We identified 6 motifs of varying lengths, out of which only three motifs, including CTTCCAGCAGATGTGGATCA, GGAACTGCC, and CGCCACATGCAGGC were most likely to be present in the nucleotide sequence of POTEE. By enrichment and occurrences identification analyses, we rectified the best match motif as CTTCCAGCAGATGT. Since there is no experimentally verified structure of POTEE paralog, thus, we predicted the POTEE structure using an automated workflow for template-based modeling using the power of a deep neural network. Additionally, to validate our predicted model we used AlphaFold predicted POTEE structure and observed that the residual stretch starting from 237-958 had a very high confidence per residue. Furthermore, POTEE predicted model stability was evaluated using replica exchange molecular dynamic simulation for 50 ns. Our network-based epigenetic analysis discerns only 10 highly significant, direct, and physical associators of POTEE. Our finding aims to provide new insights about the POTEE paralog.

TopProperty: Robust Metaprediction of Transmembrane and Globular Protein Features Using Deep Neural Networks

Transmembrane proteins (TMPs) are critical components of cellular life. However, due to experimental challenges, the number of experimentally resolved TMP structures is severely underrepresented in databases compared to their cellular abundance. Prediction of (per-residue) features such as transmembrane topology, membrane exposure, secondary structure, and solvent accessibility can be a useful starting point for experimental design or protein structure prediction but often requires different computational tools for different features or types of proteins. We present TopProperty, a metapredictor that predicts all of these features for TMPs or globular proteins. TopProperty is trained on datasets without bias toward a high number of sequence homologs, and the predictions are significantly better than the evaluated state-of-the-art primary predictors on all quality metrics. TopProperty eliminates the need for protein type- or feature-tailored tools, specifically for TMPs. TopProperty is freely available as a web server and standalone at https://cpclab.uni-duesseldorf.de/topsuite/.

PDBeCIF: an open-source mmCIF/CIF parsing and processing package

Background

Biomacromolecular structural data outgrew the legacy Protein Data Bank (PDB) format which the scientific community relied on for decades, yet the use of its successor PDBx/Macromolecular Crystallographic Information File format (PDBx/mmCIF) is still not widespread. Perhaps one of the reasons is the availability of easy to use tools that only support the legacy format, but also the inherent difficulties of processing mmCIF files correctly, given the number of edge cases that make efficient parsing problematic. Nevertheless, to fully exploit macromolecular structure data and their associated annotations such as multiscale structures from integrative/hybrid methods or large macromolecular complexes determined using traditional methods, it is necessary to fully adopt the new format as soon as possible.

Results

To this end, we developed PDBeCIF, an open-source Python project for manipulating mmCIF and CIF files. It is part of the official list of mmCIF parsers recorded by the wwPDB and is heavily employed in the processes of the Protein Data Bank in Europe. The package is freely available both from the PyPI repository (http://pypi.org/project/pdbecif) and from GitHub (https://github.com/pdbeurope/pdbecif) along with rich documentation and many ready-to-use examples.

Conclusions

PDBeCIF is an efficient and lightweight Python 2.6+/3+ package with no external dependencies. It can be readily integrated with 3rd party libraries as well as adopted for broad scientific analyses.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04271-9.

Foamy Viruses, Bet, and APOBEC3 Restriction

Non-human primates (NHP) are an important source of viruses that can spillover to humans and, after adaptation, spread through the host population. Whereas HIV-1 and HTLV-1 emerged as retroviral pathogens in humans, a unique class of retroviruses called foamy viruses (FV) with zoonotic potential are occasionally detected in bushmeat hunters or zookeepers. Various FVs are endemic in numerous mammalian natural hosts, such as primates, felines, bovines, and equines, and other animals, but not in humans. They are apathogenic, and significant differences exist between the viral life cycles of FV and other retroviruses. Importantly, FVs replicate in the presence of many well-defined retroviral restriction factors such as TRIM5α, BST2 (Tetherin), MX2, and APOBEC3 (A3). While the interaction of A3s with HIV-1 is well studied, the escape mechanisms of FVs from restriction by A3 is much less explored. Here we review the current knowledge of FV biology, host restriction factors, and FV-host interactions with an emphasis on the consequences of FV regulatory protein Bet binding to A3s and outline crucial open questions for future studies.