RIBFIND2: Identifying rigid bodies in protein and nucleic acid structures.

Molecular structures are often fitted into cryo-EM maps by flexible fitting. When this requires large conformational changes, identifying rigid bodies can help optimize the model-map fit. Tools for identifying rigid bodies in protein structures exist, however an equivalent for nucleic acid structures is lacking. With the increase in cryo-EM maps containing RNA and progress in RNA structure prediction, there is a need for such tools. We previously developed RIBFIND, a program for clustering protein secondary structures into rigid bodies. In RIBFIND2, this approach is extended to nucleic acid structures. RIBFIND2 can identify biologically relevant rigid bodies in important groups of complex RNA structures, capturing a wide range of dynamics, including large rigid-body movements. The usefulness of RIBFIND2-assigned rigid bodies in cryo-EM model refinement was demonstrated on three examples, with two conformations each: Group II Intron complexed IEP, Internal Ribosome Entry Site and the Processome, using cryo-EM maps at 2.7-5 Å resolution. A hierarchical refinement approach, performed on progressively smaller sets of RIBFIND2 rigid bodies, was clearly shown to have an advantage over classical all-atom refinement. RIBFIND2 is available via a web server with structure visualization and as a standalone tool.

Clinical Phenotype in Individuals With Birk-Landau-Perez Syndrome Associated With Biallelic SLC30A9 Pathogenic Variants.

BACKGROUND AND OBJECTIVES: Birk-Landau-Perez syndrome is a genetic disorder caused by biallelic pathogenic variants in SLC30A9 presenting with a complex movement disorder, developmental regression, oculomotor abnormalities, and renal impairment. It has previously been reported in 2 families. We describe the clinical phenotype of 8 further individuals from 4 unrelated families with SLC30A9-related disease. METHOD: Following detailed clinical phenotyping, 1 family underwent research whole-genome sequencing (WGS), 1 research whole-exome sequencing, and 2 diagnostic WGS. Variants of interest were assessed for pathogenicity using in silico prediction tools, homology modeling, and, where relevant, sequencing of complementary DNA (cDNA) for splicing effect. RESULTS: In 2 unrelated families of Pakistani origin (1 consanguineous and 1 not), the same homozygous missense variant in SLC30A9 (c.1253G>T, p.Gly418Val) was identified. Family 1 included 2 affected brothers, and family 2 one affected boy. In family 3, also consanguineous, there were 4 affected siblings homozygous for the variant c.1049delCAG, pAla350del. The fourth family was nonconsanguineous: the 1 affected individual was compound heterozygous for c.1083dup, p.Val362Cysfs*5, and c.1413A>G, p.Ser471=. Despite phenotypic variability between the 4 families, all affected patients manifested with a progressive hyperkinetic movement disorder, associated with oculomotor apraxia and ptosis. None had evidence of severe renal impairment. For the novel missense variant, the conformation of the loop domain and packing of transmembrane helices are likely to be disrupted based on structure modeling. Its presence in 2 unrelated Pakistani families suggests a possible founder variant. For the synonymous variant p.Ser471=, an effect on splicing was confirmed through cDNA analysis. DISCUSSION: Pathogenic variants in SLC30A9 cause a progressive autosomal recessive neurologic syndrome associated with a complex hyperkinetic movement disorder. Our report highlights the expanding disease phenotype, which can present with a wider spectrum of severity than has previously been recognized.

PTPN11 Mosaicism Causes a Spectrum of Pigmentary and Vascular Neurocutaneous Disorders and Predisposes to Melanoma.

Phakomatosis pigmentovascularis is a diagnosis that denotes the coexistence of pigmentary and vascular birthmarks of specific types, accompanied by variable multisystem involvement, including CNS disease, asymmetrical growth, and a predisposition to malignancy. Using a tight phenotypic group and high-depth next-generation sequencing of affected tissues, we discover here clonal mosaic variants in gene PTPN11 encoding SHP2 phosphatase as a cause of phakomatosis pigmentovascularis type III or spilorosea. Within an individual, the same variant is found in distinct pigmentary and vascular birthmarks and is undetectable in blood. We go on to show that the same variants can cause either the pigmentary or vascular phenotypes alone, and drive melanoma development within pigmentary lesions. Protein structure modeling highlights that although variants lead to loss of function at the level of the phosphatase domain, resultant conformational changes promote longer ligand binding. In vitro modeling of the missense variants confirms downstream MAPK pathway overactivation and widespread disruption of human endothelial cell angiogenesis. Importantly, patients with PTPN11 mosaicism theoretically risk passing on the variant to their children as the germline RASopathy Noonan syndrome with lentigines. These findings improve our understanding of the pathogenesis and biology of nevus spilus and capillary malformation syndromes, paving the way for better clinical management.

Mycobacterium abscessus pathogenesis identified by phenogenomic analyses.

The medical and scientific response to emerging and established pathogens is often severely hampered by ignorance of the genetic determinants of virulence, drug resistance and clinical outcomes that could be used to identify therapeutic drug targets and forecast patient trajectories. Taking the newly emergent multidrug-resistant bacteria Mycobacterium abscessus as an example, we show that combining high-dimensional phenotyping with whole-genome sequencing in a phenogenomic analysis can rapidly reveal actionable systems-level insights into bacterial pathobiology. Through phenotyping of 331 clinical isolates, we discovered three distinct clusters of isolates, each with different virulence traits and associated with a different clinical outcome. We combined genome-wide association studies with proteome-wide computational structural modelling to define likely causal variants, and employed direct coupling analysis to identify co-evolving, and therefore potentially epistatic, gene networks. We then used in vivo CRISPR-based silencing to validate our findings and discover clinically relevant M. abscessus virulence factors including a secretion system, thus illustrating how phenogenomics can reveal critical pathways within emerging pathogenic bacteria.

Overview and applications of map and model validation tools in the CCP-EM software suite.

Cryogenic electron microscopy (cryo-EM) has recently been established as a powerful technique for solving macromolecular structures. Although the best resolutions achievable are improving, a significant majority of data are still resolved at resolutions worse than 3 Å, where it is non-trivial to build or fit atomic models. The map reconstructions and atomic models derived from the maps are also prone to errors accumulated through the different stages of data processing. Here, we highlight the need to evaluate both model geometry and fit to data at different resolutions. Assessment of cryo-EM structures from SARS-CoV-2 highlights a bias towards optimising the model geometry to agree with the most common conformations, compared to the agreement with data. We present the CoVal web service which provides multiple validation metrics to reflect the quality of atomic models derived from cryo-EM data of structures from SARS-CoV-2. We demonstrate that further refinement can lead to improvement of the agreement with data without the loss of geometric quality. We also discuss the recent CCP-EM developments aimed at addressing some of the current shortcomings.

The pore conformation of lymphocyte perforin.

Perforin is a pore-forming protein that facilitates rapid killing of pathogen-infected or cancerous cells by the immune system. Perforin is released from cytotoxic lymphocytes, together with proapoptotic granzymes, to bind to a target cell membrane where it oligomerizes and forms pores. The pores allow granzyme entry, which rapidly triggers the apoptotic death of the target cell. Here, we present a 4-Å resolution cryo-electron microscopy structure of the perforin pore, revealing previously unidentified inter- and intramolecular interactions stabilizing the assembly. During pore formation, the helix-turn-helix motif moves away from the bend in the central ß sheet to form an intermolecular contact. Cryo-electron tomography shows that prepores form on the membrane surface with minimal conformational changes. Our findings suggest the sequence of conformational changes underlying oligomerization and membrane insertion, and explain how several pathogenic mutations affect function.

Atomic model validation using the CCP-EM software suite.

Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process.

Assessment of protein-protein interfaces in cryo-EM derived assemblies.

Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we comprehensively assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed Protein Interface-score (PI-score), a density-independent machine learning-based metric, trained using the features of protein-protein interfaces in crystal structures. We evaluated 5873 interfaces in 1053 PDB-deposited cryo-EM models (including SARS-CoV-2 complexes), as well as the models submitted to CASP13 cryo-EM targets and the EM model challenge. We further inspected the interfaces associated with low-scores and found that some of those, especially in intermediate-to-low resolution (worse than 4 Å) structures, were not captured by density-based assessment scores. A combined score incorporating PI-score and fit-to-density score showed discriminatory power, allowing our method to provide a powerful complementary assessment tool for the ever-increasing number of complexes solved by cryo-EM.

Structure-Guided Computational Approaches to Unravel Druggable Proteomic Landscape of Mycobacterium leprae.

Leprosy, caused by Mycobacterium leprae (M. leprae), is treated with a multidrug regimen comprising Dapsone, Rifampicin, and Clofazimine. These drugs exhibit bacteriostatic, bactericidal and anti-inflammatory properties, respectively, and control the dissemination of infection in the host. However, the current treatment is not cost-effective, does not favor patient compliance due to its long duration (12 months) and does not protect against the incumbent nerve damage, which is a severe leprosy complication. The chronic infectious peripheral neuropathy associated with the disease is primarily due to the bacterial components infiltrating the Schwann cells that protect neuronal axons, thereby inducing a demyelinating phenotype. There is a need to discover novel/repurposed drugs that can act as short duration and effective alternatives to the existing treatment regimens, preventing nerve damage and consequent disability associated with the disease. Mycobacterium leprae is an obligate pathogen resulting in experimental intractability to cultivate the bacillus in vitro and limiting drug discovery efforts to repositioning screens in mouse footpad models. The dearth of knowledge related to structural proteomics of M. leprae, coupled with emerging antimicrobial resistance to all the three drugs in the multidrug therapy, poses a need for concerted novel drug discovery efforts. A comprehensive understanding of the proteomic landscape of M. leprae is indispensable to unravel druggable targets that are essential for bacterial survival and predilection of human neuronal Schwann cells. Of the 1,614 protein-coding genes in the genome of M. leprae, only 17 protein structures are available in the Protein Data Bank. In this review, we discussed efforts made to model the proteome of M. leprae using a suite of software for protein modeling that has been developed in the Blundell laboratory. Precise template selection by employing sequence-structure homology recognition software, multi-template modeling of the monomeric models and accurate quality assessment are the hallmarks of the modeling process. Tools that map interfaces and enable building of homo-oligomers are discussed in the context of interface stability. Other software is described to determine the druggable proteome by using information related to the chokepoint analysis of the metabolic pathways, gene essentiality, homology to human proteins, functional sites, druggable pockets and fragment hotspot maps.

Stepwise pathogenic evolution of Mycobacterium abscessus.

Although almost all mycobacterial species are saprophytic environmental organisms, a few, such as Mycobacterium tuberculosis, have evolved to cause transmissible human infection. By analyzing the recent emergence and spread of the environmental organism M. abscessus through the global cystic fibrosis population, we have defined key, generalizable steps involved in the pathogenic evolution of mycobacteria. We show that epigenetic modifiers, acquired through horizontal gene transfer, cause saltational increases in the pathogenic potential of specific environmental clones. Allopatric parallel evolution during chronic lung infection then promotes rapid increases in virulence through mutations in a discrete gene network; these mutations enhance growth within macrophages but impair fomite survival. As a consequence, we observe constrained pathogenic evolution while person-to-person transmission remains indirect, but postulate accelerated pathogenic adaptation once direct transmission is possible, as observed for M. tuberculosis Our findings indicate how key interventions, such as early treatment and cross-infection control, might restrict the spread of existing mycobacterial pathogens and prevent new, emergent ones.

TEMPy2: a Python library with improved 3D electron microscopy density-fitting and validation workflows.

Structural determination of molecular complexes by cryo-EM requires large, often complex processing of the image data that are initially obtained. Here, TEMPy2, an update of the TEMPy package to process, optimize and assess cryo-EM maps and the structures fitted to them, is described. New optimization routines, comprehensive automated checks and workflows to perform these tasks are described.

HARP: a database of structural impacts of systematic missense mutations in drug targets of Mycobacterium leprae.

Computational Saturation Mutagenesis is an in-silico approach that employs systematic mutagenesis of each amino acid residue in the protein to all other amino acid types, and predicts changes in thermodynamic stability and affinity to the other subunits/protein counterparts, ligands and nucleic acid molecules. The data thus generated are useful in understanding the functional consequences of mutations in antimicrobial resistance phenotypes. In this study, we applied computational saturation mutagenesis to three important drug-targets in Mycobacterium leprae (M. leprae) for the drugs dapsone, rifampin and ofloxacin namely Dihydropteroate Synthase (DHPS), RNA Polymerase (RNAP) and DNA Gyrase (GYR), respectively. M. leprae causes leprosy and is an obligate intracellular bacillus with limited protein structural information associating mutations with phenotypic resistance outcomes in leprosy. Experimentally solved structures of DHPS, RNAP and GYR of M. leprae are not available in the Protein Data Bank, therefore, we modelled the structures of these proteins using template-based comparative modelling and introduced systematic mutations in each model generating 80,902 mutations and mutant structures for all the three proteins. Impacts of mutations on stability and protein-subunit, protein-ligand and protein-nucleic acid affinities were computed using various in-house developed and other published protein stability and affinity prediction software. A consensus impact was estimated for each mutation using qualitative scoring metrics for physicochemical properties and by a categorical grouping of stability and affinity predictions. We developed a web database named HARP (a database of Hansen's Disease Antimicrobial Resistance Profiles), which is accessible at the URL - https://harp-leprosy.org and provides the details to each of these predictions.

KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation.

Heterozygous mutations in KMT2B are associated with an early-onset, progressive and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor features at disease presentation, evolving through a caudocranial pattern into generalized dystonia, with prominent oromandibular, laryngeal and cervical involvement. Although KMT2B-related disease is emerging as one of the most common causes of early-onset genetic dystonia, much remains to be understood about the full spectrum of the disease. We describe a cohort of 53 patients with KMT2B mutations, with detailed delineation of their clinical phenotype and molecular genetic features. We report new disease presentations, including atypical patterns of dystonia evolution and a subgroup of patients with a non-dystonic neurodevelopmental phenotype. In addition to the previously reported systemic features, our study has identified co-morbidities, including the risk of status dystonicus, intrauterine growth retardation, and endocrinopathies. Analysis of this study cohort (n = 53) in tandem with published cases (n = 80) revealed that patients with chromosomal deletions and protein truncating variants had a significantly higher burden of systemic disease (with earlier onset of dystonia) than those with missense variants. Eighteen individuals had detailed longitudinal data available after insertion of deep brain stimulation for medically refractory dystonia. Median age at deep brain stimulation was 11.5 years (range: 4.5-37.0 years). Follow-up after deep brain stimulation ranged from 0.25 to 22 years. Significant improvement of motor function and disability (as assessed by the Burke Fahn Marsden's Dystonia Rating Scales, BFMDRS-M and BFMDRS-D) was evident at 6 months, 1 year and last follow-up (motor, P = 0.001, P = 0.004, and P = 0.012; disability, P = 0.009, P = 0.002 and P = 0.012). At 1 year post-deep brain stimulation, >50% of subjects showed BFMDRS-M and BFMDRS-D improvements of >30%. In the long-term deep brain stimulation cohort (deep brain stimulation inserted for >5 years, n = 8), improvement of >30% was maintained in 5/8 and 3/8 subjects for the BFMDRS-M and BFMDRS-D, respectively. The greatest BFMDRS-M improvements were observed for trunk (53.2%) and cervical (50.5%) dystonia, with less clinical impact on laryngeal dystonia. Improvements in gait dystonia decreased from 20.9% at 1 year to 16.2% at last assessment; no patient maintained a fully independent gait. Reduction of BFMDRS-D was maintained for swallowing (52.9%). Five patients developed mild parkinsonism following deep brain stimulation. KMT2B-related disease comprises an expanding continuum from infancy to adulthood, with early evidence of genotype-phenotype correlations. Except for laryngeal dysphonia, deep brain stimulation provides a significant improvement in quality of life and function with sustained clinical benefit depending on symptoms distribution.

Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification.

Translational frameshift errors are often deleterious to the synthesis of functional proteins and could therefore be promoted therapeutically to kill bacteria. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and represents an attractive potential target for the development of new antibiotics. Here, we describe the application of a structure-guided fragment-based drug discovery approach to the design of a new class of inhibitors against TrmD in Mycobacterium abscessus. Fragment library screening, followed by structure-guided chemical elaboration of hits, led to the rapid development of drug-like molecules with potent in vitro TrmD inhibitory activity. Several of these compounds exhibit activity against planktonic M. abscessus and M. tuberculosis as well as against intracellular M. abscessus and M. leprae, indicating their potential as the basis for a novel class of broad-spectrum mycobacterial drugs.

Combining Information from Crosslinks and Monolinks in the Modeling of Protein Structures.

Monolinks are produced in a chemical crosslinking mass spectrometry experiment and are more abundant than crosslinks. They convey residue exposure information, but so far have not been used in the modeling of protein structures. Here, we present the Monolink Depth Score (MoDS), for assessing structural models based on the depth of monolinked residues, corresponding to their distance to the nearest bulk water. Using simulated and reprocessed experimental data from the Proteomic Identification Database, we compare the performance of MoDS to MNXL, our previously developed score for assessing models based on crosslinking data. Our results show that MoDS can be used to effectively score models based on monolinks, and that a crosslink/monolink combined score (XLMO) leads to overall higher performance. The work strongly supports the use of monolink data in the context of integrative structure determination. We also present XLM-Tools, a program to assist in this effort, available at: https://github.com/Topf-Lab/XLM-Tools.

Computational saturation mutagenesis to predict structural consequences of systematic mutations in the beta subunit of RNA polymerase in Mycobacterium leprae.

Rifampin resistance in leprosy may remain undetected due to the lack of rapid and effective diagnostic tools. A quick and reliable method is essential to determine the impacts of emerging detrimental mutations in the drug targets. The functional consequences of missense mutations in the ß-subunit of RNA polymerase (RNAP) in Mycobacterium leprae (M. leprae) contribute to phenotypic resistance to rifampin in leprosy. Here, we report in-silico saturation mutagenesis of all residues in the ß-subunit of RNAP to all other 19 amino acid types (generating 21,394 mutations for 1126 residues) and predict their impacts on overall thermodynamic stability, on interactions at subunit interfaces, and on ß-subunit-RNA and rifampin affinities (only for the rifampin binding site) using state-of-the-art structure, sequence and normal mode analysis-based methods. Mutations in the conserved residues that line the active-site cleft show largely destabilizing effects, resulting in increased relative solvent accessibility and a concomitant decrease in residue-depth (the extent to which a residue is buried in the protein structure space) of the mutant residues. The mutations at residue positions S437, G459, H451, P489, K884 and H1035 are identified as extremely detrimental as they induce highly destabilizing effects on the overall protein stability, and nucleic acid and rifampin affinities. Destabilizing effects were predicted for all the clinically/experimentally identified rifampin-resistant mutations in M. leprae indicating that this model can be used as a surveillance tool to monitor emerging detrimental mutations that destabilise RNAP-rifampin interactions and confer rifampin resistance in leprosy. AUTHOR SUMMARY: The emergence of primary and secondary drug resistance to rifampin in leprosy is a growing concern and poses a threat to the leprosy control and elimination measures globally. In the absence of an effective in-vitro system to detect and monitor phenotypic resistance to rifampin in leprosy, diagnosis mainly relies on the presence of mutations in drug resistance determining regions of the rpoB gene that encodes the ß-subunit of RNAP in M. leprae. Few labs in the world perform mouse food pad propagation of M. leprae in the presence of drugs (rifampin) to determine growth patterns and confirm resistance, however the duration of these methods lasts from 8 to 12 months making them impractical for diagnosis. Understanding molecular mechanisms of drug resistance is vital to associating mutations to clinically detected drug resistance in leprosy. Here we propose an in-silico saturation mutagenesis approach to comprehensively elucidate the structural implications of any mutations that exist or that can arise in the ß-subunit of RNAP in M. leprae. Most of the predicted mutations may not occur in M. leprae due to fitness costs but the information thus generated by this approach help decipher the impacts of mutations across the structure and conversely enable identification of stable regions in the protein that are least impacted by mutations (mutation coolspots) which can be a potential choice for small molecule binding and structure guided drug discovery.

The current structural glycome landscape and emerging technologies.

Carbohydrates represent one of the building blocks of life, along with nucleic acids, proteins and lipids. Although glycans are involved in a wide range of processes from embryogenesis to protein trafficking and pathogen infection, we are still a long way from deciphering the glycocode. In this review, we aim to present a few of the challenges that researchers working in the area of glycobiology can encounter and what strategies can be utilised to overcome them. Our goal is to paint a comprehensive picture of the current saccharide landscape available in the Protein Data Bank (PDB). We also review recently updated repositories relevant to the topic proposed, the impact of software development on strategies to structurally solve carbohydrate moieties, and state-of-the-art molecular and cellular biology methods that can shed some light on the function and structure of glycans.

ProCarbDB: a database of carbohydrate-binding proteins.

Carbohydrate-binding proteins play crucial roles across all organisms and viruses. The complexity of carbohydrate structures, together with inconsistencies in how their 3D structures are reported, has led to difficulties in characterizing the protein-carbohydrate interfaces. In order to better understand protein-carbohydrate interactions, we have developed an open-access database, ProCarbDB, which, unlike the Protein Data Bank (PDB), clearly distinguishes between the complete carbohydrate ligands and their monomeric units. ProCarbDB is a comprehensive database containing over 5200 3D X-ray crystal structures of protein-carbohydrate complexes. In ProCarbDB, the complete carbohydrate ligands are annotated and all their interactions are displayed. Users can also select any protein residue in the proximity of the ligand to inspect its interactions with the carbohydrate ligand and with other neighbouring protein residues. Where available, additional curated information on the binding affinity of the complex and the effects of mutations on the binding have also been provided in the database. We believe that ProCarbDB will be an invaluable resource for understanding protein-carbohydrate interfaces. The ProCarbDB web server is freely available at http://www.procarbdb.science/procarb.

Cryo-electron microscopy targets in CASP13: Overview and evaluation of results.

Structures of seven CASP13 targets were determined using cryo-electron microscopy (cryo-EM) technique with resolution between 3.0 and 4.0 Å. We provide an overview of the experimentally derived structures and describe results of the numerical evaluation of the submitted models. The evaluation is carried out by comparing coordinates of models to those of reference structures (CASP-style evaluation), as well as checking goodness-of-fit of modeled structures to the cryo-EM density maps. The performance of contributing research groups in the CASP-style evaluation is measured in terms of backbone accuracy, all-atom local geometry and similarity of inter-subunit interfaces. The results on the cryo-EM targets are compared with those on the whole set of eighty CASP13 targets. A posteriori refinement of the best models in their corresponding cryo-EM density maps resulted in structures that are very close to the reference structure, including some regions with better fit to the density.