A long noncoding RNA controls muscle differentiation by functioning as a competing endogenous RNA.

Recently, a new regulatory circuitry has been identified in which RNAs can crosstalk with each other by competing for shared microRNAs. Such competing endogenous RNAs (ceRNAs) regulate the distribution of miRNA molecules on their targets and thereby impose an additional level of post-transcriptional regulation. Here we identify a muscle-specific long noncoding RNA, linc-MD1, which governs the time of muscle differentiation by acting as a ceRNA in mouse and human myoblasts. Downregulation or overexpression of linc-MD1 correlate with retardation or anticipation of the muscle differentiation program, respectively. We show that linc-MD1 "sponges" miR-133 and miR-133 [corrected] to regulate the expression of MAML1 and MEF2C, transcription factors that activate muscle-specific gene expression. Finally, we demonstrate that linc-MD1 exerts the same control over differentiation timing in human myoblasts, and that its levels are strongly reduced in Duchenne muscle cells. We conclude that the ceRNA network plays an important role in muscle differentiation.

Paternal age and perinatal outcomes: an observational study.

OBJECTIVES: The study's primary aim was to examine the relationship between paternal age and perinatal outcomes. METHODS: This study used data from two hospital birth registries to examine the association between paternal age and adverse perinatal outcomes. The sample included all live singleton births between 2010 and 2022. The primary exposure was paternal age, and the following perinatal outcomes were considered: mode of conception, mode of delivery, pregnancy complications, and neonatal outcomes. RESULTS: A total of 15,232 pregnant women were considered. Maternal and paternal ages were 31.9 ± 5.3 and 36.5 ± 6.5 years, respectively. Independent of maternal, paternal age was associated with lower odds of spontaneous conceptions (OR 0.930, 95 % CI 0.968/0.993; p=0.003) and higher odds of intracytoplasmatic sperm injection (OR 1.054, 95 % CI 1.045/1.062; p=0.0001), respectively. In contrast to maternal age, paternal age decreased the odds of any (OR 0.922, 95 % CI 0.985/0.999; p=0.032) and urgent/emergent (OR 0.984, 95 % CI 0.975/0.993; p=0.0001) cesarean delivery. Paternal age did not affect the gestation length, placental or neonatal weight, blood loss during delivery, and neonatal 5th-minute Apgar score. CONCLUSIONS: Paternal age is associated with perinatal outcomes. These findings suggest that advanced paternal age may have implications for reproductive counseling and prenatal care.

Exposure to Prolonged Rupture of Membranes at Term Increases the Risk for Ventilatory Support in Uninfected Neonates.

OBJECTIVE: The effects of prolonged rupture of membranes (ROMs) on perinatal outcomes are still unclear, and it remains controversial for the management of those labors. This study aims to evaluate how the exposure of pregnant women to a prolonged ROM (≥ 24 hours) affects maternal and neonatal outcomes. STUDY DESIGN: This retrospective cohort study included singleton pregnant women at term delivering between January 2019 and March 2020 in a tertiary hospital. All relevant sociodemographic, pregnancy, and perinatal variables (maternal age, prepregnancy body mass index, labor, and delivery outcomes) were collected anonymously. Data were compared between the "ROM < 24 hours" and "ROM ≥ 24 hours" study groups. RESULTS: A total of 2,689 dyads were included in the study and divided according to their ROM-delivery time: ROM <24 hours (2,369 women, 88.1%), and ROM ≥ 24 hours (320 women, 11.9%). Maternal baseline characteristics were comparable except for the rate of nulliparous women, which was significantly higher among patients with ROM ≥ 24 hours. No significant differences were found regarding infectious neonatal outcomes. However, mechanical ventilation and continuous positive airway pressure were more common among neonates born after ROM ≥ 24 hours. The greater likelihood of neonatal respiratory distress was also confirmed among infants born to Group-B Streptococcus-negative women with ROM ≥ 24 hours (15 out of 267 neonates, 5.6% vs. 52 out of 1,529 with ROM < 24 hours, 3.4%, p = 0.04). CONCLUSION: According to the actual expectant policy, prolonged ROM is associated with an increased risk of respiratory support in noninfected neonates. Further investigations are required to explain such an association. KEY POINTS: · The management of women with prolonged rupture of membranes is controversial.. · The exposure of pregnant women to a prolonged rupture of membranes affects neonatal outcomes.. · Prolonged rupture of membranes is associated with an increased risk of respiratory support, in group-B Streptococcus-negative neonates..

PIGSPro: prediction of immunoGlobulin structures v2.

PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro.

Assessment of model accuracy estimations in CASP12.

The record high 42 model accuracy estimation methods were tested in CASP12. The paper presents results of the assessment of these methods in the whole-model and per-residue accuracy modes. Scores from four different model evaluation packages were used as the "ground truth" for assessing accuracy of methods' estimates. They include a rigid-body score-GDT_TS, and three local-structure based scores-LDDT, CAD and SphereGrinder. The ability of methods to identify best models from among several available, predict model's absolute accuracy score, distinguish between good and bad models, predict accuracy of the coordinate error self-estimates, and discriminate between reliable and unreliable regions in the models was assessed. Single-model methods advanced to the point where they are better than clustering methods in picking the best models from decoy sets. On the other hand, consensus methods, taking advantage of the availability of large number of models for the same target protein, are still better in distinguishing between good and bad models and predicting local accuracy of models. The best accuracy estimation methods were shown to perform better with respect to the frozen in time reference clustering method and the results of the best method in the corresponding class of methods from the previous CASP. Top performing single-model methods were shown to do better than all but three CASP12 tertiary structure predictors when evaluated as model selectors.

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

This article reports the outcome of the 12th round of Critical Assessment of Structure Prediction (CASP12), held in 2016. CASP is a community experiment to determine the state of the art in modeling protein structure from amino acid sequence. Participants are provided sequence information and in turn provide protein structure models and related information. Analysis of the submitted structures by independent assessors provides a comprehensive picture of the capabilities of current methods, and allows progress to be identified. This was again an exciting round of CASP, with significant advances in 4 areas: (i) The use of new methods for predicting three-dimensional contacts led to a two-fold improvement in contact accuracy. (ii) As a consequence, model accuracy for proteins where no template was available improved dramatically. (iii) Models based on a structural template showed overall improvement in accuracy. (iv) Methods for estimating the accuracy of a model continued to improve. CASP continued to develop new areas: (i) Assessing methods for building quaternary structure models, including an expansion of the collaboration between CASP and CAPRI. (ii) Modeling with the aid of experimental data was extended to include SAXS data, as well as again using chemical cross-linking information. (iii) A team of assessors evaluated the suitability of models for a range of applications, including mutation interpretation, analysis of ligand binding properties, and identification of interfaces. This article describes the experiment and summarizes the results. The rest of this special issue of PROTEINS contains papers describing CASP12 results and assessments in more detail.

Evaluation of the template-based modeling in CASP12.

The article describes results of numerical evaluation of CASP12 models submitted on targets for which structural templates could be identified and for which servers produced models of relatively high accuracy. The emphasis is on analysis of details of models, and how well the models compete with experimental structures. Performance of contributing research groups is measured in terms of backbone accuracy, all-atom local geometry, and the ability to estimate local errors in models. Separate analyses for all participating groups and automatic servers were carried out. Compared with the last CASP, two years ago, there have been significant improvements in a number of areas, particularly the accuracy of protein backbone atoms, accuracy of sequence alignment between models and available structures, increased accuracy over that which can be obtained from simple copying of a closest template, and accuracy of modeling of sub-structures not present in the closest template. These advancements are likely associated with more effective strategies to build non-template regions of the targets ab initio, better algorithms to combine information from multiple templates, enhanced refinement methods, and better methods for estimating model accuracy.

A structural view of microRNA-target recognition.

It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed by AGO, a miRNA and 22 nt of a target mRNA that putatively interacts with it. We show here that MiREN can be used to assess the likelihood that an RNA molecule is the target of a given miRNA and that this approach is more accurate than other existing methods, usually based on sequence or sequence-related features. Our results also suggest that AGO plays a relevant role in the selection of the miRNA targets. Our method can represent an additional step for refining predictions made by faster but less accurate classical methods for the identification of miRNA targets.

PepComposer: computational design of peptides binding to a given protein surface.

There is a wide interest in designing peptides able to bind to a specific region of a protein with the aim of interfering with a known interaction or as starting point for the design of inhibitors. Here we describe PepComposer, a new pipeline for the computational design of peptides binding to a given protein surface. PepComposer only requires the target protein structure and an approximate definition of the binding site as input. We first retrieve a set of peptide backbone scaffolds from monomeric proteins that harbor the same backbone arrangement as the binding site of the protein of interest. Next, we design optimal sequences for the identified peptide scaffolds. The method is fully automatic and available as a web server at http://biocomputing.it/pepcomposer/webserver.

Genome-wide identification of direct HBx genomic targets.

BACKGROUND: The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. RESULTS: ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR-33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. CONCLUSIONS: Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication.

Prediction of the permeability of neutral drugs inferred from their solvation properties.

MOTIVATION: Determination of drug absorption is an important component of the drug discovery and development process in that it plays a key role in the decision to promote drug candidates to clinical trials. We have developed a method that, on the basis of an analysis of the dynamic distribution of water molecules around a compound obtained by molecular dynamics simulations, can compute a parameter-free value that correlates very well with the compound permeability measured using the human colon adenocarcinoma (Caco-2) cell line assay. RESULTS: The method has been tested on twenty-three neutral drugs for which a consistent set of experimental data is available. We show here that our method reproduces the experimental data better than other existing tools. Furthermore it provides a detailed view of the relationship between the hydration and the permeability properties of molecules. CONTACT: anna.tramontano@uniroma1.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Critical assessment of methods of protein structure prediction: Progress and new directions in round XI.

Modeling of protein structure from amino acid sequence now plays a major role in structural biology. Here we report new developments and progress from the CASP11 community experiment, assessing the state of the art in structure modeling. Notable points include the following: (1) New methods for predicting three dimensional contacts resulted in a few spectacular template free models in this CASP, whereas models based on sequence homology to proteins with experimental structure continue to be the most accurate. (2) Refinement of initial protein models, primarily using molecular dynamics related approaches, has now advanced to the point where the best methods can consistently (though slightly) improve nearly all models. (3) The use of relatively sparse NMR constraints dramatically improves the accuracy of models, and another type of sparse data, chemical crosslinking, introduced in this CASP, also shows promise for producing better models. (4) A new emphasis on modeling protein complexes, in collaboration with CAPRI, has produced interesting results, but also shows the need for more focus on this area. (5) Methods for estimating the accuracy of models have advanced to the point where they are of considerable practical use. (6) A first assessment demonstrates that models can sometimes successfully address biological questions that motivate experimental structure determination. (7) There is continuing progress in accuracy of modeling regions of structure not directly available by comparative modeling, while there is marginal or no progress in some other areas. Proteins 2016; 84(Suppl 1):4-14. © 2016 Wiley Periodicals, Inc.

Methods of model accuracy estimation can help selecting the best models from decoy sets: Assessment of model accuracy estimations in CASP11.

The article presents assessment of the model accuracy estimation methods participating in CASP11. The results of the assessment are expected to be useful to both-developers of the methods and users who way too often are presented with structural models without annotations of accuracy. The main emphasis is placed on the ability of techniques to identify the best models from among several available. Bivariate descriptive statistics and ROC analysis are used to additionally assess the overall correctness of the predicted model accuracy scores, the correlation between the predicted and observed accuracy of models, the effectiveness in distinguishing between good and bad models, the ability to discriminate between reliable and unreliable regions in models, and the accuracy of the coordinate error self-estimates. A rigid-body measure (GDT_TS) and three local-structure-based scores (LDDT, CADaa, and SphereGrinder) are used as reference measures for evaluating methods' performance. Consensus methods, taking advantage of the availability of several models for the same target protein, perform well on the majority of tasks. Methods that predict accuracy on the basis of a single model perform comparably to consensus methods in picking the best models and in the estimation of how accurate is the local structure. More groups than in previous experiments submitted reasonable error estimates of their own models, most likely in response to a recommendation from CASP and the increasing demand from users. Proteins 2016; 84(Suppl 1):349-369. © 2015 Wiley Periodicals, Inc.

New encouraging developments in contact prediction: Assessment of the CASP11 results.

This article provides a report on the state-of-the-art in the prediction of intra-molecular residue-residue contacts in proteins based on the assessment of the predictions submitted to the CASP11 experiment. The assessment emphasis is placed on the accuracy in predicting long-range contacts. Twenty-nine groups participated in contact prediction in CASP11. At least eight of them used the recently developed evolutionary coupling techniques, with the top group (CONSIP2) reaching precision of 27% on target proteins that could not be modeled by homology. This result indicates a breakthrough in the development of methods based on the correlated mutation approach. Successful prediction of contacts was shown to be practically helpful in modeling three-dimensional structures; in particular target T0806 was modeled exceedingly well with accuracy not yet seen for ab initio targets of this size (>250 residues). Proteins 2016; 84(Suppl 1):131-144. © 2015 Wiley Periodicals, Inc.

Tabhu: tools for antibody humanization.

SUMMARY: Antibodies are rapidly becoming essential tools in the clinical practice, given their ability to recognize their cognate antigens with high specificity and affinity, and a high yield at reasonable costs in model animals. Unfortunately, when administered to human patients, xenogeneic antibodies can elicit unwanted and dangerous immunogenic responses. Antibody humanization methods are designed to produce molecules with a better safety profile still maintaining their ability to bind the antigen. This can be accomplished by grafting the non-human regions determining the antigen specificity into a suitable human template. Unfortunately, this procedure may results in a partial or complete loss of affinity of the grafted molecule that can be restored by back-mutating some of the residues of human origin to the corresponding murine ones. This trial-and-error procedure is hard and involves expensive and time-consuming experiments. Here we present tools for antibody humanization (Tabhu) a web server for antibody humanization. Tabhu includes tools for human template selection, grafting, back-mutation evaluation, antibody modelling and structural analysis, helping the user in all the critical steps of the humanization experiment protocol. AVAILABILITY: http://www.biocomputing.it/tabhu CONTACT: anna.tramontano@uniroma1.it, pierpaolo.olimpieri@uniroma1.it SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

LoopIng: a template-based tool for predicting the structure of protein loops.

MOTIVATION: Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are not very effective in modeling their structure. However, loops are often involved in protein function, hence inferring their structure is important for predicting protein structure as well as function. RESULTS: We describe a method, LoopIng, based on the Random Forest automated learning technique, which, given a target loop, selects a structural template for it from a database of loop candidates. Compared to the most recently available methods, LoopIng is able to achieve similar accuracy for short loops (4-10 residues) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has the advantage of being very fast (on average: 1 min/loop). AVAILABILITY AND IMPLEMENTATION: www.biocomputing.it/looping. CONTACT: anna.tramontano@uniroma1.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

3USS: a web server for detecting alternative 3'UTRs from RNA-seq experiments.

UNLABELLED: Protein-coding genes with multiple alternative polyadenylation sites can generate mRNA 3'UTR sequences of different lengths, thereby causing the loss or gain of regulatory elements, which can affect stability, localization and translation efficiency. 3USS is a web-server developed with the aim of giving experimentalists the possibility to automatically identify alternative 3 ': UTRs (shorter or longer with respect to a reference transcriptome), an option that is not available in standard RNA-seq data analysis procedures. The tool reports as putative novel the 3 ': UTRs not annotated in available databases. Furthermore, if data from two related samples are uploaded, common and specific alternative 3 ': UTRs are identified and reported by the server. AVAILABILITY AND IMPLEMENTATION: 3USS is freely available at http://www.biocomputing.it/3uss_server.

Characterization of the differences in the cyclopiazonic acid binding mode to mammalian and P. Falciparum Ca2+ pumps: a computational study.

Despite the investments in malaria research, an effective vaccine has not yet been developed and the causative parasites are becoming increasingly resistant to most of the available drugs. PfATP6, the sarco/endoplasmic reticulum Ca2+ pump (SERCA) of P. falciparum, has been recently genetically validated as a potential antimalarial target and cyclopiazonic acid (CPA) has been found to be a potent inhibitor of SERCAs in several organisms, including P. falciparum. In position 263, PfATP6 displays a leucine residue, whilst the corresponding position in the mammalian SERCA is occupied by a glutamic acid. The PfATP6 L263E mutation has been studied in relation to the artemisinin inhibitory effect on P. falciparum and recent studies have provided evidence that the parasite with this mutation is more susceptible to CPA. Here, we characterized, for the first time, the interaction of CPA with PfATP6 and its mammalian counterpart to understand similarities and differences in the mode of binding of the inhibitor to the two Ca2+ pumps. We found that, even though CPA does not directly interact with the residue in position 263, the presence of a hydrophobic residue in this position in PfATP6 rather than a negatively charged one, as in the mammalian SERCA, entails a conformational arrangement of the binding pocket which, in turn, determines a relaxation of CPA leading to a different binding mode of the compound. Our findings highlight differences between the plasmodial and human SERCA CPA-binding pockets that may be exploited to design CPA derivatives more selective toward PfATP6.

Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies.

MOTIVATION: Antibodies are able to recognize a wide range of antigens through their complementary determining regions formed by six hypervariable loops. Predicting the 3D structure of these loops is essential for the analysis and reengineering of novel antibodies with enhanced affinity and specificity. The canonical structure model allows high accuracy prediction for five of the loops. The third loop of the heavy chain, H3, is the hardest to predict because of its diversity in structure, length and sequence composition. RESULTS: We describe a method, based on the Random Forest automatic learning technique, to select structural templates for H3 loops among a dataset of candidates. These can be used to predict the structure of the loop with a higher accuracy than that achieved by any of the presently available methods. The method also has the advantage of being extremely fast and returning a reliable estimate of the model quality. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at http://www.biocomputing.it/H3Loopred/ .

Igs expressed by chronic lymphocytic leukemia B cells show limited binding-site structure variability.

Ag selection has been suggested to play a role in chronic lymphocytic leukemia (CLL) pathogenesis, but no large-scale analysis has been performed so far on the structure of the Ag-binding sites (ABSs) of leukemic cell Igs. We sequenced both H and L chain V(D)J rearrangements from 366 CLL patients and modeled their three-dimensional structures. The resulting ABS structures were clustered into a small number of discrete sets, each containing ABSs with similar shapes and physicochemical properties. This structural classification correlates well with other known prognostic factors such as Ig mutation status and recurrent (stereotyped) receptors, but it shows a better prognostic value, at least in the case of one structural cluster for which clinical data were available. These findings suggest, for the first time, to our knowledge, on the basis of a structural analysis of the Ab-binding sites, that selection by a finite quota of antigenic structures operates on most CLL cases, whether mutated or unmutated.