1,721,024 research outputs found
Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations
No full textPredicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors
Optimizing the performance of bias-exchange metadynamics: Folding a 48-residue LysM domain using a coarse-grained model
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
PARCE: Protocol for Amino acid Refinement through Computational Evolution
No full textThe in silico design of peptides and proteins as binders is useful for diagnosis and therapeutics due to their low adverse effects and major specificity. To select the most promising candidates, a key matter is to understand their interactions with protein targets. In this work, we present PARCE, an open source Protocol for Amino acid Refinement through Computational Evolution that implements an advanced and promising method for the design of peptides and proteins. The protocol performs a random mutation in the binder sequence, then samples the bound conformations using molecular dynamics simulations, and evaluates the protein–protein interactions using multiple scoring functions. Finally, it accepts or rejects the mutation by applying a consensus criterion based on the binding scores. The procedure is iterated with the aim to explore efficiently novel sequences with potential better affinities towards their targets. We also provide a tutorial for running and reproducing the methodology. Program summary: Program Title: PARCE CPC Library link to program files: http://dx.doi.org/10.17632/jcpj3j83rt.1 Developer's repository link: https://github.com/PARCE-project/PARCE-1 Licensing provisions: MIT License Programming language: Python 3 Nature of problem: Computational design of peptides and proteins as binders for diagnosis and therapeutics. Solution method: A protocol that performs random mutations in the binder sequence, samples the bound conformations using molecular dynamics simulations, and evaluates the protein–protein interactions from multiple scoring predictions in order to accept or reject the mutations. Additional comments including restrictions and unusual features: Subprograms used: Gromacs 5.1.4, Scwrl4, FASPR, PDB2PQR, Scoring functions source code. This article describes version 1.0. PARCE is available at: https://github.com/PARCE-project/PARCE-1, and a Docker container can be downloaded from: https://hub.docker.com/r/rochoa85/parce-1
PARCE: Protocol for Amino acid Refinement through Computational Evolution
No full textThe in silico design of peptides and proteins as binders is useful for diagnosis and therapeutics due to their low adverse effects and major specificity. To select the most promising candidates, a key matter is to understand their interactions with protein targets. In this work, we present PARCE, an open source Protocol for Amino acid Refinement through Computational Evolution that implements an advanced and promising method for the design of peptides and proteins. The protocol performs a random mutation in the binder sequence, then samples the bound conformations using molecular dynamics simulations, and evaluates the protein–protein interactions using multiple scoring functions. Finally, it accepts or rejects the mutation by applying a consensus criterion based on the binding scores. The procedure is iterated with the aim to explore efficiently novel sequences with potential better affinities towards their targets. We also provide a tutorial for running and reproducing the methodology. Program summary: Program Title: PARCE CPC Library link to program files: http://dx.doi.org/10.17632/jcpj3j83rt.1 Developer's repository link: https://github.com/PARCE-project/PARCE-1 Licensing provisions: MIT License Programming language: Python 3 Nature of problem: Computational design of peptides and proteins as binders for diagnosis and therapeutics. Solution method: A protocol that performs random mutations in the binder sequence, samples the bound conformations using molecular dynamics simulations, and evaluates the protein–protein interactions from multiple scoring predictions in order to accept or reject the mutations. Additional comments including restrictions and unusual features: Subprograms used: Gromacs 5.1.4, Scwrl4, FASPR, PDB2PQR, Scoring functions source code. This article describes version 1.0. PARCE is available at: https://github.com/PARCE-project/PARCE-1, and a Docker container can be downloaded from: https://hub.docker.com/r/rochoa85/parce-1
Assessing the capability of in silico mutation protocols for predicting the finite temperature conformation of amino acids
Full text linkMutation protocols are a key tool in computational biophysics for modelling unknown side chain conformations. In particular, these protocols are used to generate the starting structures for molecular dynamics simulations. The accuracy of the initial side chain and backbone placement is crucial to obtain a stable and quickly converging simulation. In this work, we assessed the performance of several mutation protocols in predicting the most probable conformer observed in finite temperature molecular dynamics simulations for a set of protein-peptide crystals differing only by single-point mutations in the peptide sequence. Our results show that several programs which predict well the crystal conformations fail to predict the most probable finite temperature configuration. Methods relying on backbone-dependent rotamer libraries have, in general, a better performance, but even the best protocol fails in predicting approximately 30% of the mutations
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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