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1.
Microbiol Spectr ; 9(2): e0101821, 2021 Oct 31.
Artigo em Inglês | MEDLINE | ID: mdl-34668739

RESUMO

Leishmania parasites are the causal agent of leishmaniasis, an endemic disease in more than 90 countries worldwide. Over the years, traditional approaches focused on the parasite when developing treatments against leishmaniasis. Despite numerous attempts, there is not yet a universal treatment, and those available have allowed for the appearance of resistance. Here, we propose and follow a host-directed approach that aims to overcome the current lack of treatment. Our approach identifies potential therapeutic targets in the host cell and proposes known drug interactions aiming to improve the immune response and to block the host machinery necessary for the survival of the parasite. We started analyzing transcription factor regulatory networks of macrophages infected with Leishmania major. Next, based on the regulatory dynamics of the infection and available gene expression profiles, we selected potential therapeutic target proteins. The function of these proteins was then analyzed following a multilayered network scheme in which we combined information on metabolic pathways with known drugs that have a direct connection with the activity carried out by these proteins. Using our approach, we were able to identify five host protein-coding gene products that are potential therapeutic targets for treating leishmaniasis. Moreover, from the 11 drugs known to interact with the function performed by these proteins, 3 have already been tested against this parasite, verifying in this way our novel methodology. More importantly, the remaining eight drugs previously employed to treat other diseases, remain as promising yet-untested antileishmanial therapies. IMPORTANCE This work opens a new path to fight parasites by targeting host molecular functions by repurposing available and approved drugs. We created a novel approach to identify key proteins involved in any biological process by combining gene regulatory networks and expression profiles. Once proteins have been selected, our approach employs a multilayered network methodology that relates proteins to functions to drugs that alter these functions. By applying our novel approach to macrophages during the Leishmania infection process, we both validated our work and found eight drugs already approved for use in humans that to the best of our knowledge were never employed to treat leishmaniasis, rendering our work as a new tool in the box available to the scientific community fighting parasites.

2.
Front Genet ; 12: 649764, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34394179

RESUMO

Gene Regulatory Networks (GRNs) allow the study of regulation of gene expression of whole genomes. Among the most relevant advantages of using networks to depict this key process, there is the visual representation of large amounts of information and the application of graph theory to generate new knowledge. Nonetheless, despite the many uses of GRNs, it is still difficult and expensive to assign Transcription Factors (TFs) to the regulation of specific genes. ChIP-Seq allows the determination of TF Binding Sites (TFBSs) over whole genomes, but it is still an expensive technique that can only be applied one TF at a time and requires replicates to reduce its noise. Once TFBSs are determined, the assignment of each TF and its binding sites to the regulation of specific genes is not trivial, and it is often performed by carrying out site-specific experiments that are unfeasible to perform in all possible binding sites. Here, we addressed these relevant issues with a two-step methodology using Drosophila melanogaster as a case study. First, our protocol starts by gathering all transcription factor binding sites (TFBSs) determined with ChIP-Seq experiments available at ENCODE and FlyBase. Then each TFBS is used to assign TFs to the regulation of likely target genes based on the TFBS proximity to the transcription start site of all genes. In the final step, to try to select the most likely regulatory TF from those previously assigned to each gene, we employ GENIE3, a random forest-based method, and more than 9,000 RNA-seq experiments from D. melanogaster. Following, we employed known TF protein-protein interactions to estimate the feasibility of regulatory events in our filtered networks. Finally, we show how known interactions between co-regulatory TFs of each gene increase after the second step of our approach, and thus, the consistency of the TF-gene assignment. Also, we employed our methodology to create a network centered on the Drosophila melanogaster gene Hr96 to demonstrate the role of this transcription factor on mitochondrial gene regulation.

3.
Interface Focus ; 11(4): 20200076, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34123358

RESUMO

The regulation of gene expression is a key factor in the development and maintenance of life in all organisms. Even so, little is known at whole genome scale for most genes and contexts. We propose a method, Tool for Weighted Epigenomic Networks in Drosophila melanogaster (Fly T-WEoN), to generate context-specific gene regulatory networks starting from a reference network that contains all known gene regulations in the fly. Unlikely regulations are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from the literature. Experimental data files can be generated with several standard procedures and used solely when and if available. Fly T-WEoN is available as a Cytoscape application that permits integration with other tools and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster. Fly T-WEoN together with its step-by-step guide is available at https://weon.readthedocs.io.

4.
Mol Ther ; 29(5): 1862-1882, 2021 05 05.
Artigo em Inglês | MEDLINE | ID: mdl-33545358

RESUMO

Alteration to endoplasmic reticulum (ER) proteostasis is observed in a variety of neurodegenerative diseases associated with abnormal protein aggregation. Activation of the unfolded protein response (UPR) enables an adaptive reaction to recover ER proteostasis and cell function. The UPR is initiated by specialized stress sensors that engage gene expression programs through the concerted action of the transcription factors ATF4, ATF6f, and XBP1s. Although UPR signaling is generally studied as unique linear signaling branches, correlative evidence suggests that ATF6f and XBP1s may physically interact to regulate a subset of UPR target genes. In this study, we designed an ATF6f/XBP1s fusion protein termed UPRplus that behaves as a heterodimer in terms of its selective transcriptional activity. Cell-based studies demonstrated that UPRplus has a stronger effect in reducing the abnormal aggregation of mutant huntingtin and α-synuclein when compared to XBP1s or ATF6 alone. We developed a gene transfer approach to deliver UPRplus into the brain using adeno-associated viruses (AAVs) and demonstrated potent neuroprotection in vivo in preclinical models of Parkinson's disease and Huntington's disease. These results support the concept in which directing UPR-mediated gene expression toward specific adaptive programs may serve as a possible strategy to optimize the beneficial effects of the pathway in different disease conditions.

5.
Bioinformatics ; 2020 Dec 26.
Artigo em Inglês | MEDLINE | ID: mdl-33367504

RESUMO

MOTIVATION: Cells are complex systems composed of hundreds of genes whose products interact to produce elaborated behaviors. To control such behaviors, cells rely on transcription factors to regulate gene expression, and gene regulatory networks (GRNs) are employed to describe and understand such behavior. However, GRNs are static models, and dynamic models are difficult to obtain due to their size, complexity, stochastic dynamics, and interactions with other cell processes. RESULTS: We developed Atlas, a Python software that converts genome graphs and gene regulatory, interaction, and metabolic networks into dynamic models. The software employs these biological networks to write rule-based models for the PySB framework. The underlying method is a divide-and-conquer strategy to obtain sub-models and combine them later into an ensemble model. To exemplify the utility of Atlas, we used networks of varying size and complexity of Escherichia coli and evaluated in silico modifications such as gene knockouts and the insertion of promoters and terminators. Moreover, the methodology could be applied to the dynamic modeling of natural and synthetic networks of any bacteria. AVAILABILITY: Code, models, and tutorials are available online (https://github.com/networkbiolab/atlas). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

6.
Sci Rep ; 9(1): 15104, 2019 10 22.
Artigo em Inglês | MEDLINE | ID: mdl-31641245

RESUMO

Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures.

7.
PeerJ ; 6: e5998, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30568854

RESUMO

Protein structure is not static; residues undergo conformational rearrangements and, in doing so, create, stabilize or break non-covalent interactions. Molecular dynamics (MD) is a technique used to simulate these movements with atomic resolution. However, given the data-intensive nature of the technique, gathering relevant information from MD simulations is a complex and time consuming process requiring several computational tools to perform these analyses. Among different approaches, the study of residue interaction networks (RINs) has proven to facilitate the study of protein structures. In a RIN, nodes represent amino-acid residues and the connections between them depict non-covalent interactions. Here, we describe residue interaction networks in protein molecular dynamics (RIP-MD), a visual molecular dynamics (VMD) plugin to facilitate the study of RINs using trajectories obtained from MD simulations of proteins. Our software generates RINs from MD trajectory files. The non-covalent interactions defined by RIP-MD include H-bonds, salt bridges, VdWs, cation-π, π-π, Arginine-Arginine, and Coulomb interactions. In addition, RIP-MD also computes interactions based on distances between Cαs and disulfide bridges. The results of the analysis are shown in an user friendly interface. Moreover, the user can take advantage of the VMD visualization capacities, whereby through some effortless steps, it is possible to select and visualize interactions described for a single, several or all residues in a MD trajectory. Network and descriptive table files are also generated, allowing their further study in other specialized platforms. Our method was written in python in a parallelized fashion. This characteristic allows the analysis of large systems impossible to handle otherwise. RIP-MD is available at http://www.dlab.cl/ripmd.

8.
Methods Mol Biol ; 1819: 3-32, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30421397

RESUMO

Complex systems are governed by dynamic processes whose underlying causal rules are difficult to unravel. However, chemical reactions, molecular interactions, and many other complex systems can be usually represented as concentrations or quantities that vary over time, which provides a framework to study these dynamic relationships. An increasing number of tools use these quantifications to simulate dynamically complex systems to better understand their underlying processes. The application of such methods covers several research areas from biology and chemistry to ecology and even social sciences.In the following chapter, we introduce the concept of rule-based simulations based on the Stochastic Simulation Algorithm (SSA) as well as other mathematical methods such as Ordinary Differential Equations (ODE) models to describe agent-based systems. Besides, we describe the mathematical framework behind Kappa (κ), a rule-based language for the modeling of complex systems, and some extensions for spaßtial models implemented in PISKaS (Parallel Implementation of a Spatial Kappa Simulator). To facilitate the understanding of these methods, we include examples of how these models can be used to describe population dynamics in a simple predator-prey ecosystem or to simulate circadian rhythm changes.


Assuntos
Algoritmos , Simulação por Computador , Cadeia Alimentar , Modelos Biológicos , Processos Estocásticos
9.
BMC Genomics ; 19(1): 731, 2018 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-30290792

RESUMO

BACKGROUND: The high-density lipoprotein receptor SR-B1 mediates cellular uptake of several lipid species, including cholesterol and vitamin E. During early mouse development, SR-B1 is located in the maternal-fetal interface, where it facilitates vitamin E transport towards the embryo. Consequently, mouse embryos lacking SR-B1 are vitamin E-deficient, and around half of them fail to close the neural tube and show cephalic neural tube defects (NTD). Here, we used transcriptomic profiling to identify the molecular determinants of this phenotypic difference between SR-B1 deficient embryos with normal morphology or with NTD. RESULTS: We used RNA-Seq to compare the transcriptomic profile of three groups of embryos retrieved from SR-B1 heterozygous intercrosses: wild-type E9.5 embryos (WT), embryos lacking SR-B1 that are morphologically normal, without NTD (KO-N) and SR-B1 deficient embryos with this defect (KO-NTD). We identified over 1000 differentially expressed genes: down-regulated genes in KO-NTD embryos were enriched for functions associated to neural development, while up-regulated genes in KO-NTD embryos were enriched for functions related to lipid metabolism. Feeding pregnant dams a vitamin E-enriched diet, which prevents NTD in SR-B1 KO embryos, resulted in mRNA levels for those differentially expressed genes that were more similar to KO-N than to KO-NTD embryos. We used gene regulatory network analysis to identify putative transcriptional regulators driving the different embryonic expression profiles, and identified a regulatory circuit controlled by the androgen receptor that may contribute to this dichotomous expression profile in SR-B1 embryos. Supporting this possibility, the expression level of the androgen receptor correlated strongly with the expression of several genes involved in neural development and lipid metabolism. CONCLUSIONS: Our analysis shows that normal and defective embryos lacking SR-B1 have divergent expression profiles, explained by a defined set of transcription factors that may explain their divergent phenotype. We propose that distinct expression profiles may be relevant during early development to support embryonic nutrition and neural tube closure.


Assuntos
Antígenos CD36/deficiência , Antígenos CD36/genética , Perfilação da Expressão Gênica , Técnicas de Inativação de Genes , Redes Reguladoras de Genes , Tubo Neural/embriologia , Transcrição Genética , Animais , Humanos , Camundongos , Tubo Neural/metabolismo , Defeitos do Tubo Neural/genética , Defeitos do Tubo Neural/metabolismo , Fenótipo , Desmame
10.
Biochem Biophys Res Commun ; 498(2): 342-351, 2018 03 29.
Artigo em Inglês | MEDLINE | ID: mdl-29175206

RESUMO

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems.


Assuntos
Algoritmos , Modelos Biológicos , Processos Estocásticos , Surtos de Doenças , Escherichia coli/genética , Teoria do Jogo , Regulação Bacteriana da Expressão Gênica , Redes Reguladoras de Genes , Doença pelo Vírus Ebola/epidemiologia , Doença pelo Vírus Ebola/transmissão , Humanos , Dilema do Prisioneiro , Confiança
11.
Front Physiol ; 8: 38, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28232803

RESUMO

Although connexins (Cxs) are broadly expressed by cells of mammalian organisms, Cx39 has a very restricted pattern of expression and the biophysical properties of Cx39-based channels [hemichannels (HCs) and gap junction channels (GJCs)] remain largely unknown. Here, we used HeLa cells transfected with Cx39 (HeLa-Cx39 cells) in which intercellular electrical coupling was not detected, indicating the absence of GJCs. However, functional HCs were found on the surface of cells exposed to conditions known to increase the open probability of other Cx HCs (e.g., extracellular divalent cationic-free solution (DCFS), extracellular alkaline pH, mechanical stimulus and depolarization to positive membrane potentials). Cx39 HCs were blocked by some traditional Cx HC blockers, but not by others or a pannexin1 channel blocker. HeLa-Cx39 cells showed similar resting membrane potentials (RMPs) to those of parental cells, and exposure to DCFS reduced RMPs in Cx39 transfectants, but not in parental cells. Under these conditions, unitary events of ~75 pS were frequent in HeLa-Cx39 cells and absent in parental cells. Real-time cellular uptake experiments of dyes with different physicochemical features, as well as the application of a machine-learning approach revealed that Cx39 HCs are preferentially permeable to molecules characterized by six categories of descriptors, namely: (1) electronegativity, (2) ionization potential, (3) polarizability, (4) size and geometry, (5) topological flexibility and (6) valence. However, Cx39 HCs opened by mechanical stimulation or alkaline pH were impermeable to Ca2+. Molecular modeling of Cx39-based channels suggest that a constriction present at the intracellular portion of the para helix region co-localizes with an electronegative patch, imposing an energetic and steric barrier, which in the case of GJCs may hinder channel function. Results reported here demonstrate that Cx39 form HCs and add to our understanding of the functional roles of Cx39 HCs under physiological and pathological conditions in cells that express them.

12.
PLoS One ; 11(10): e0163497, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27695050

RESUMO

Understanding the control of gene expression remains one of the main challenges in the post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene expression levels. These variations underlay almost all relevant biological phenomena, including disease and adaptation to environmental conditions. However, computational tools to identify how regulation changes are scarce. Regulation of gene expression is usually depicted in the form of a gene regulatory network (GRN). Structural changes in a GRN over time and conditions represent variations in the regulation of gene expression. Like other biological networks, GRNs are composed of basic building blocks called graphlets. As a consequence, two new metrics based on graphlets are proposed in this work: REConstruction Rate (REC) and REC Graphlet Degree (RGD). REC determines the rate of graphlet similarity between different states of a network and RGD identifies the subset of nodes with the highest topological variation. In other words, RGD discerns how th GRN was rewired. REC and RGD were used to compare the local structure of nodes in condition-specific GRNs obtained from gene expression data of Escherichia coli, forming biofilms and cultured in suspension. According to our results, most of the network local structure remains unaltered in the two compared conditions. Nevertheless, changes reported by RGD necessarily imply that a different cohort of regulators (i.e. transcription factors (TFs)) appear on the scene, shedding light on how the regulation of gene expression occurs when E. coli transits from suspension to biofilm. Consequently, we propose that both metrics REC and RGD should be adopted as a quantitative approach to conduct differential analyses of GRNs. A tool that implements both metrics is available as an on-line web server (http://dlab.cl/loto).


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Modelos Biológicos , Algoritmos , Biofilmes/crescimento & desenvolvimento , Escherichia coli/genética , Escherichia coli/crescimento & desenvolvimento , Perfilação da Expressão Gênica/estatística & dados numéricos , Regulação Bacteriana da Expressão Gênica/genética , Fatores de Transcrição/genética
13.
J Biomol Struct Dyn ; 34(1): 135-51, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-25671669

RESUMO

The PR20 HIV-1 protease, a variant with 20 mutations, exhibits high levels of multi-drug resistance; however, to date, there has been no report detailing the impact of these 20 mutations on the conformational and drug binding landscape at a molecular level. In this report, we demonstrate the first account of a comprehensive study designed to elaborate on the impact of these mutations on the dynamic features as well as drug binding and resistance profile, using extensive molecular dynamics analyses. Comparative MD simulations for the wild-type and PR20 HIV proteases, starting from bound and unbound conformations in each case, were performed. Results showed that the apo conformation of the PR20 variant of the HIV protease displayed a tendency to remain in the open conformation for a longer period of time when compared to the wild type. This led to a phenomena in which the inhibitor seated at the active site of PR20 tends to diffuse away from the binding site leading to a significant change in inhibitor-protein association. Calculating the per-residue fluctuation (RMSF) and radius of gyration, further validated these findings. MM/GBSA showed that the occurrence of 20 mutations led to a drop in the calculated binding free energies (ΔGbind) by ~25.17 kcal/mol and ~5 kcal/mol for p2-NC, a natural peptide substrate, and darunavir, respectively, when compared to wild type. Furthermore, the residue interaction network showed a diminished inter-residue hydrogen bond network and changes in inter-residue connections as a result of these mutations. The increased conformational flexibility in PR20 as a result of loss of intra- and inter-molecular hydrogen bond interactions and other prominent binding forces led to a loss of protease grip on ligand. It is interesting to note that the difference in conformational flexibility between PR20 and WT conformations was much higher in the case of substrate-bound conformation as compared to DRV. Thus, developing analogues of DRV by retaining its key pharmacophore features will be the way forward in the search for novel protease inhibitors against multi-drug resistant strains.


Assuntos
Inibidores da Protease de HIV/química , Protease de HIV/química , HIV-1/química , Sulfonamidas/química , Sítios de Ligação , Resistência a Múltiplos Medicamentos/genética , Protease de HIV/genética , Protease de HIV/metabolismo , HIV-1/enzimologia , Humanos , Ligação de Hidrogênio , Simulação de Dinâmica Molecular , Mutação , Conformação Proteica/efeitos dos fármacos , Termodinâmica
14.
BMC Genomics ; 15 Suppl 4: S7, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25057121

RESUMO

BACKGROUND: The rapid growth of un-annotated missense variants poses challenges requiring novel strategies for their interpretation. From the thermodynamic point of view, amino acid changes can lead to a change in the internal energy of a protein and induce structural rearrangements. This is of great relevance for the study of diseases and protein design, justifying the development of prediction methods for variant-induced stability changes. RESULTS: Here we propose NeEMO, a tool for the evaluation of stability changes using an effective representation of proteins based on residue interaction networks (RINs). RINs are used to extract useful features describing interactions of the mutant amino acid with its structural environment. Benchmarking shows NeEMO to be very effective, allowing reliable predictions in different parts of the protein such as ß-strands and buried residues. Validation on a previously published independent dataset shows that NeEMO has a Pearson correlation coefficient of 0.77 and a standard error of 1 Kcal/mol, outperforming nine recent methods. The NeEMO web server can be freely accessed from URL: http://protein.bio.unipd.it/neemo/. CONCLUSIONS: NeEMO offers an innovative and reliable tool for the annotation of amino acid changes. A key contribution are RINs, which can be used for modeling proteins and their interactions effectively. Interestingly, the approach is very general, and can motivate the development of a new family of RIN-based protein structure analyzers. NeEMO may suggest innovative strategies for bioinformatics tools beyond protein stability prediction.


Assuntos
Biologia Computacional , Proteínas/metabolismo , Aminoácidos/química , Aminoácidos/metabolismo , Internet , Mutação , Mapas de Interação de Proteínas , Estabilidade Proteica , Estrutura Terciária de Proteína , Proteínas/química , Proteínas/genética , Termodinâmica , Interface Usuário-Computador
15.
Mol Biosyst ; 10(8): 2215-28, 2014 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-24931725

RESUMO

The emergence of different drug resistant strains of HIV-1 reverse transcriptase (HIV RT) remains of prime interest in relation to viral pathogenesis as well as drug development. Amongst those mutations, M184V was found to cause a complete loss of ligand fitness. In this study, we report the first account of the molecular impact of M184V mutation on HIV RT resistance to 3TC (lamivudine) using an integrated computational approach. This involved molecular dynamics simulation, binding free energy analysis, principle component analysis (PCA) and residue interaction networks (RINs). Results clearly confirmed that M184V mutation leads to steric conflict between 3TC and the beta branched side chain of valine, decreases the ligand (3TC) binding affinity by ∼7 kcal mol(-1) when compared to the wild type, changes the overall conformational landscape of the protein and distorts the native enzyme residue-residue interaction network. The comprehensive molecular insight gained from this study should be of great importance in understanding drug resistance against HIV RT as well as assisting in the design of novel reverse transcriptase inhibitors with high ligand efficacy on resistant strains.


Assuntos
Biologia Computacional/métodos , Transcriptase Reversa do HIV/química , Transcriptase Reversa do HIV/genética , Mutação , Substituição de Aminoácidos , Fármacos Anti-HIV/química , Farmacorresistência Viral , Lamivudina/química , Metionina/metabolismo , Simulação de Dinâmica Molecular , Análise de Componente Principal , Estrutura Secundária de Proteína , Relação Quantitativa Estrutura-Atividade , Valina/metabolismo
16.
PLoS One ; 8(11): e78383, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-24265686

RESUMO

Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/.


Assuntos
Internet , Anotação de Sequência Molecular/métodos , Mapeamento de Interação de Proteínas/métodos , Software , Gráficos por Computador , Alinhamento de Sequência
17.
Proc Natl Acad Sci U S A ; 110(15): 6163-8, 2013 Apr 09.
Artigo em Inglês | MEDLINE | ID: mdl-23536301

RESUMO

Cryptochromes are flavoproteins, structurally and evolutionarily related to photolyases, that are involved in the development, magnetoreception, and temporal organization of a variety of organisms. Drosophila CRYPTOCHROME (dCRY) is involved in light synchronization of the master circadian clock, and its C terminus plays an important role in modulating light sensitivity and activity of the protein. The activation of dCRY by light requires a conformational change, but it has been suggested that activation could be mediated also by specific "regulators" that bind the C terminus of the protein. This C-terminal region harbors several protein-protein interaction motifs, likely relevant for signal transduction regulation. Here, we show that some functional linear motifs are evolutionarily conserved in the C terminus of cryptochromes and that class III PDZ-binding sites are selectively maintained in animals. A coimmunoprecipitation assay followed by mass spectrometry analysis revealed that dCRY interacts with Retinal Degeneration A (RDGA) and with Neither Inactivation Nor Afterpotential C (NINAC) proteins. Both proteins belong to a multiprotein complex (the Signalplex) that includes visual-signaling molecules. Using bioinformatic and molecular approaches, dCRY was found to interact with Neither Inactivation Nor Afterpotential C through Inactivation No Afterpotential D (INAD) in a light-dependent manner and that the CRY-Inactivation No Afterpotential D interaction is mediated by specific domains of the two proteins and involves the CRY C terminus. Moreover, an impairment of the visual behavior was observed in fly mutants for dCRY, indicative of a role, direct or indirect, for this photoreceptor in fly vision.


Assuntos
Criptocromos/fisiologia , Proteínas de Drosophila/fisiologia , Drosophila melanogaster/fisiologia , Proteínas do Olho/fisiologia , Visão Ocular/fisiologia , Motivos de Aminoácidos , Animais , Sítios de Ligação , Biologia Computacional , Drosophila melanogaster/metabolismo , Eletrorretinografia , Flavoproteínas/metabolismo , Luz , Espectrometria de Massas , Mapeamento de Interação de Proteínas , Transdução de Sinais , Técnicas do Sistema de Duplo-Híbrido
18.
Bioinformatics ; 28(15): 2080-1, 2012 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-22661649

RESUMO

MOTIVATION: Disordered protein regions are key to the function of numerous processes within an organism and to the determination of a protein's biological role. The most common source for protein disorder annotations, DisProt, covers only a fraction of the available sequences. Alternatively, the Protein Data Bank (PDB) has been mined for missing residues in X-ray crystallographic structures. Herein, we provide a centralized source for data on different flavours of disorder in protein structures, MobiDB, building on and expanding the content provided by already existing sources. In addition to the DisProt and PDB X-ray structures, we have added experimental information from NMR structures and five different flavours of two disorder predictors (ESpritz and IUpred). These are combined into a weighted consensus disorder used to classify disordered regions into flexible and constrained disorder. Users are encouraged to submit manual annotations through a submission form. MobiDB features experimental annotations for 17 285 proteins, covering the entire PDB and predictions for the SwissProt database, with 565 200 annotated sequences. Depending on the disorder flavour, 6-20% of the residues are predicted as disordered. AVAILABILITY: The database is freely available at http://mobidb.bio.unipd.it/. CONTACT: silvio.tosatto@unipd.it.


Assuntos
Bases de Dados de Proteínas , Anotação de Sequência Molecular , Proteínas/química , Cristalografia por Raios X , Espectroscopia de Ressonância Magnética , Estrutura Terciária de Proteína , Análise de Sequência de Proteína/métodos , Interface Usuário-Computador
19.
Bioinformatics ; 28(4): 503-9, 2012 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-22190692

RESUMO

MOTIVATION: Intrinsically disordered regions are key for the function of numerous proteins, and the scant available experimental annotations suggest the existence of different disorder flavors. While efficient predictions are required to annotate entire genomes, most existing methods require sequence profiles for disorder prediction, making them cumbersome for high-throughput applications. RESULTS: In this work, we present an ensemble of protein disorder predictors called ESpritz. These are based on bidirectional recursive neural networks and trained on three different flavors of disorder, including a novel NMR flexibility predictor. ESpritz can produce fast and accurate sequence-only predictions, annotating entire genomes in the order of hours on a single processor core. Alternatively, a slower but slightly more accurate ESpritz variant using sequence profiles can be used for applications requiring maximum performance. Two levels of prediction confidence allow either to maximize reasonable disorder detection or to limit expected false positives to 5%. ESpritz performs consistently well on the recent CASP9 data, reaching a S(w) measure of 54.82 and area under the receiver operator curve of 0.856. The fast predictor is four orders of magnitude faster and remains better than most publicly available CASP9 methods, making it ideal for genomic scale predictions. CONCLUSIONS: ESpritz predicts three flavors of disorder at two distinct false positive rates, either with a fast or slower and slightly more accurate approach. Given its state-of-the-art performance, it can be especially useful for high-throughput applications. AVAILABILITY: Both a web server for high-throughput analysis and a Linux executable version of ESpritz are available from: http://protein.bio.unipd.it/espritz/.


Assuntos
Redes Neurais de Computação , Proteínas/química , Proteínas/metabolismo , Algoritmos , Animais , Humanos , Conformação Proteica , Dobramento de Proteína
20.
Curr Protein Pept Sci ; 12(6): 549-62, 2011 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-21787307

RESUMO

In order to use a predicted protein structure one needs to know how good it is, as the utility of a model depends on its quality. To this aim, many Model Quality Assessment Programs (MQAP) have been developed over the last decade, with MQAP also being assessed at the CASP competition. We present a new knowledge-based MQAP which evaluates single protein structure models. We use a tree representation of the Cα trace to train a novel Neural Network Pairwise Interaction Field (NN-PIF) to predict the global quality of a model. NN-PIF allows fast evaluation of multiple structure models for a single sequence. In our tests on a large set of structures, our networks outperform most other methods based on different and more complex protein structure representations in global model quality prediction. Moreover, given NN-PIF can evaluate protein conformations very fast, we train a separate version of the model to gauge its ability to fold protein structures ab initio. We show that the resulting system, which relies only on basic information about the sequence and the Cα trace of a conformation, generally improves the quality of the structures it is presented with and may yield promising predictions in the absence of structural templates, although more research is required to harness the full potential of the model.


Assuntos
Biologia Computacional/métodos , Modelos Moleculares , Redes Neurais de Computação , Dobramento de Proteína , Proteínas/química , Algoritmos , Conformação Proteica , Reprodutibilidade dos Testes
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