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1.
Proteins ; 90(1): 45-57, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34293212

RESUMO

Deep mutational scanning provides unprecedented wealth of quantitative data regarding the functional outcome of mutations in proteins. A single experiment may measure properties (eg, structural stability) of numerous protein variants. Leveraging the experimental data to gain insights about unexplored regions of the mutational landscape is a major computational challenge. Such insights may facilitate further experimental work and accelerate the development of novel protein variants with beneficial therapeutic or industrially relevant properties. Here we present a novel, machine learning approach for the prediction of functional mutation outcome in the context of deep mutational screens. Using sequence (one-hot) features of variants with known properties, as well as structural features derived from models thereof, we train predictive statistical models to estimate the unknown properties of other variants. The utility of the new computational scheme is demonstrated using five sets of mutational scanning data, denoted "targets": (a) protease specificity of APPI (amyloid precursor protein inhibitor) variants; (b-d) three stability related properties of IGBPG (immunoglobulin G-binding ß1 domain of streptococcal protein G) variants; and (e) fluorescence of GFP (green fluorescent protein) variants. Performance is measured by the overall correlation of the predicted and observed properties, and enrichment-the ability to predict the most potent variants and presumably guide further experiments. Despite the diversity of the targets the statistical models can generalize variant examples thereof and predict the properties of test variants with both single and multiple mutations.


Assuntos
Análise Mutacional de DNA/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Aprendizado de Máquina , Mutação/genética , Proteínas , Algoritmos , Biologia Computacional/métodos , Modelos Estatísticos , Mapas de Interação de Proteínas , Proteínas/química , Proteínas/genética , Proteínas/metabolismo
2.
Proc Natl Acad Sci U S A ; 118(40)2021 10 05.
Artigo em Inglês | MEDLINE | ID: mdl-34593629

RESUMO

Approximately 40% of human messenger RNAs (mRNAs) contain upstream open reading frames (uORFs) in their 5' untranslated regions. Some of these uORF sequences, thought to attenuate scanning ribosomes or lead to mRNA degradation, were recently shown to be translated, although the function of the encoded peptides remains unknown. Here, we show a uORF-encoded peptide that exhibits kinase inhibitory functions. This uORF, upstream of the protein kinase C-eta (PKC-η) main ORF, encodes a peptide (uPEP2) containing the typical PKC pseudosubstrate motif present in all PKCs that autoinhibits their kinase activity. We show that uPEP2 directly binds to and selectively inhibits the catalytic activity of novel PKCs but not of classical or atypical PKCs. The endogenous deletion of uORF2 or its overexpression in MCF-7 cells revealed that the endogenously translated uPEP2 reduces the protein levels of PKC-η and other novel PKCs and restricts cell proliferation. Functionally, treatment of breast cancer cells with uPEP2 diminished cell survival and their migration and synergized with chemotherapy by interfering with the response to DNA damage. Furthermore, in a xenograft of MDA-MB-231 breast cancer tumor in mice models, uPEP2 suppressed tumor progression, invasion, and metastasis. Tumor histology showed reduced proliferation, enhanced cell death, and lower protein expression levels of novel PKCs along with diminished phosphorylation of PKC substrates. Hence, our study demonstrates that uORFs may encode biologically active peptides beyond their role as translation regulators of their downstream ORFs. Together, we point to a unique function of a uORF-encoded peptide as a kinase inhibitor, pertinent to cancer therapy.


Assuntos
Peptídeos/farmacologia , Proteína Quinase C/antagonistas & inibidores , Inibidores de Proteínas Quinases/farmacologia , Sequência de Aminoácidos , Linhagem Celular Tumoral , Humanos , Fases de Leitura Aberta , Peptídeos/química , Proteína Quinase C/metabolismo , Inibidores de Proteínas Quinases/química , Especificidade por Substrato
3.
Bioinformatics ; 36(12): 3733-3738, 2020 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-32186698

RESUMO

MOTIVATION: The Protein Data Bank (PDB), the ultimate source for data in structural biology, is inherently imbalanced. To alleviate biases, virtually all structural biology studies use nonredundant (NR) subsets of the PDB, which include only a fraction of the available data. An alternative approach, dubbed redundancy-weighting (RW), down-weights redundant entries rather than discarding them. This approach may be particularly helpful for machine-learning (ML) methods that use the PDB as their source for data. Methods for secondary structure prediction (SSP) have greatly improved over the years with recent studies achieving above 70% accuracy for eight-class (DSSP) prediction. As these methods typically incorporate ML techniques, training on RW datasets might improve accuracy, as well as pave the way toward larger and more informative secondary structure classes. RESULTS: This study compares the SSP performances of deep-learning models trained on either RW or NR datasets. We show that training on RW sets consistently results in better prediction of 3- (HCE), 8- (DSSP) and 13-class (STR2) secondary structures. AVAILABILITY AND IMPLEMENTATION: The ML models, the datasets used for their derivation and testing, and a stand-alone SSP program for DSSP and STR2 predictions, are freely available under LGPL license in http://meshi1.cs.bgu.ac.il/rw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Aprendizado Profundo , Biologia Computacional , Bases de Dados de Proteínas , Aprendizado de Máquina , Estrutura Secundária de Proteína
4.
IEEE/ACM Trans Comput Biol Bioinform ; 16(5): 1515-1523, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-28113636

RESUMO

The function of a protein is determined by its structure, which creates a need for efficient methods of protein structure determination to advance scientific and medical research. Because current experimental structure determination methods carry a high price tag, computational predictions are highly desirable. Given a protein sequence, computational methods produce numerous 3D structures known as decoys. Selection of the best quality decoys is both challenging and essential as the end users can handle only a few ones. Therefore, scoring functions are central to decoy selection. They combine measurable features into a single number indicator of decoy quality. Unfortunately, current scoring functions do not consistently select the best decoys. Machine learning techniques offer great potential to improve decoy scoring. This paper presents two machine-learning based scoring functions to predict the quality of proteins structures, i.e., the similarity between the predicted structure and the experimental one without knowing the latter. We use different metrics to compare these scoring functions against three state-of-the-art scores. This is a first attempt at comparing different scoring functions using the same non-redundant dataset for training and testing and the same features. The results show that adding informative features may be more significant than the method used.


Assuntos
Biologia Computacional/métodos , Proteínas , Máquina de Vetores de Suporte , Algoritmos , Bases de Dados de Proteínas , Aprendizado de Máquina , Proteínas/química , Proteínas/classificação , Proteínas/metabolismo
5.
Sci Rep ; 8(1): 9939, 2018 07 02.
Artigo em Inglês | MEDLINE | ID: mdl-29967418

RESUMO

Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.


Assuntos
Caspase 12/metabolismo , Caspases/metabolismo , Biologia Computacional/métodos , Modelos Moleculares , Software , Caspase 12/química , Caspases/química , Humanos , Conformação Proteica
6.
Proteins ; 86 Suppl 1: 361-373, 2018 03.
Artigo em Inglês | MEDLINE | ID: mdl-28975666

RESUMO

Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact-based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.


Assuntos
Biologia Computacional/métodos , Modelos Moleculares , Conformação Proteica , Proteínas/química , Bases de Dados de Proteínas , Humanos , Alinhamento de Sequência , Análise de Sequência de Proteína
7.
Bioinformatics ; 30(16): 2295-301, 2014 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-24771517

RESUMO

MOTIVATION: Structural knowledge, extracted from the Protein Data Bank (PDB), underlies numerous potential functions and prediction methods. The PDB, however, is highly biased: many proteins have more than one entry, while entire protein families are represented by a single structure, or even not at all. The standard solution to this problem is to limit the studies to non-redundant subsets of the PDB. While alleviating biases, this solution hides the many-to-many relations between sequences and structures. That is, non-redundant datasets conceal the diversity of sequences that share the same fold and the existence of multiple conformations for the same protein. A particularly disturbing aspect of non-redundant subsets is that they hardly benefit from the rapid pace of protein structure determination, as most newly solved structures fall within existing families. RESULTS: In this study we explore the concept of redundancy-weighted datasets, originally suggested by Miyazawa and Jernigan. Redundancy-weighted datasets include all available structures and associate them (or features thereof) with weights that are inversely proportional to the number of their homologs. Here, we provide the first systematic comparison of redundancy-weighted datasets with non-redundant ones. We test three weighting schemes and show that the distributions of structural features that they produce are smoother (having higher entropy) compared with the distributions inferred from non-redundant datasets. We further show that these smoothed distributions are both more robust and more correct than their non-redundant counterparts. We suggest that the better distributions, inferred using redundancy-weighting, may improve the accuracy of knowledge-based potentials and increase the power of protein structure prediction methods. Consequently, they may enhance model-driven molecular biology.


Assuntos
Conformação Proteica , Aminoácidos/química , Mineração de Dados , Bases de Dados de Proteínas , Proteínas/química
8.
Proteins ; 82(9): 1850-68, 2014 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-24677212

RESUMO

The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.


Assuntos
Biologia Computacional/métodos , Simulação por Computador , Comportamento Cooperativo , Estrutura Terciária de Proteína , Proteínas/ultraestrutura , Humanos , Modelos Moleculares , Projetos de Pesquisa , Jogos de Vídeo
9.
Science ; 341(6144): 384-7, 2013 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-23888037

RESUMO

Histocompatibility is the basis by which multicellular organisms of the same species distinguish self from nonself. Relatively little is known about the mechanisms underlying histocompatibility reactions in lower organisms. Botryllus schlosseri is a colonial urochordate, a sister group of vertebrates, that exhibits a genetically determined natural transplantation reaction, whereby self-recognition between colonies leads to formation of parabionts with a common vasculature, whereas rejection occurs between incompatible colonies. Using genetically defined lines, whole-transcriptome sequencing, and genomics, we identified a single gene that encodes self-nonself and determines "graft" outcomes in this organism. This gene is significantly up-regulated in colonies poised to undergo fusion and/or rejection, is highly expressed in the vasculature, and is functionally linked to histocompatibility outcomes. These findings establish a platform for advancing the science of allorecognition.


Assuntos
Genes , Histocompatibilidade/genética , Urocordados/genética , Urocordados/imunologia , Alelos , Animais , Genoma , Genótipo , Tolerância Imunológica , Dados de Sequência Molecular , Análise de Sequência de DNA , Transcriptoma , Regulação para Cima , Urocordados/fisiologia
10.
Structure ; 20(5): 924-35, 2012 May 09.
Artigo em Inglês | MEDLINE | ID: mdl-22579257

RESUMO

The complex hydrophobic and hydrophilic milieus of membrane-associated proteins pose experimental and theoretical challenges to their understanding. Here, we produce a nonredundant database to compute knowledge-based asymmetric cross-membrane potentials from the per-residue distributions of C(ß), C(γ) and functional group atoms. We predict transmembrane and peripherally associated regions from genomic sequence and position peptides and protein structures relative to the bilayer (available at http://www.degradolab.org/ez). The pseudo-energy topological landscapes underscore positional stability and functional mechanisms demonstrated here for antimicrobial peptides, transmembrane proteins, and viral fusion proteins. Moreover, experimental effects of point mutations on the relative ratio changes of dual-topology proteins are quantitatively reproduced. The functional group potential and the membrane-exposed residues display the largest energetic changes enabling to detect native-like structures from decoys. Hence, focusing on the uniqueness of membrane-associated proteins and peptides, we quantitatively parameterize their cross-membrane propensity, thus facilitating structural refinement, characterization, prediction, and design.


Assuntos
Proteínas de Membrana/química , Proteínas/química , Algoritmos , Bases de Dados Factuais , Interações Hidrofóbicas e Hidrofílicas , Bases de Conhecimento , Modelos Moleculares , Termodinâmica
11.
Phys Biol ; 9(2): 026005, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22476003

RESUMO

The structural reorganization of the actin cytoskeleton is facilitated through the action of motor proteins that crosslink the actin filaments and transport them relative to each other. Here, we present a combined experimental-computational study that probes the dynamic evolution of mixtures of actin filaments and clusters of myosin motors. While on small spatial and temporal scales the system behaves in a very noisy manner, on larger scales it evolves into several well distinct patterns such as bundles, asters and networks. These patterns are characterized by junctions with high connectivity, whose formation is possible due to the organization of the motors in 'oligoclusters' (intermediate-size aggregates). The simulations reveal that the self-organization process proceeds through a series of hierarchical steps, starting from local microscopic moves and ranging up to the macroscopic large scales where the steady-state structures are formed. Our results shed light on the mechanisms involved in processes such as cytokinesis and cellular contractility, where myosin motors organized in clusters operate cooperatively to induce the structural organization of cytoskeletal networks.


Assuntos
Citoesqueleto de Actina/metabolismo , Actinas/metabolismo , Modelos Biológicos , Miosina Tipo II/metabolismo , Actinas/química , Actinas/isolamento & purificação , Animais , Proteínas de Transporte/química , Proteínas de Transporte/genética , Proteínas de Transporte/metabolismo , Simulação por Computador , Proteínas dos Microfilamentos/química , Proteínas dos Microfilamentos/genética , Proteínas dos Microfilamentos/metabolismo , Músculo Esquelético/química , Miosina Tipo II/química , Miosina Tipo II/isolamento & purificação , Coelhos , Proteínas Recombinantes/química , Proteínas Recombinantes/genética , Proteínas Recombinantes/metabolismo
12.
BMC Struct Biol ; 11(1): 20, 2011 May 04.
Artigo em Inglês | MEDLINE | ID: mdl-21542935

RESUMO

BACKGROUND: Protein surfaces serve as an interface with the molecular environment and are thus tightly bound to protein function. On the surface, geometric and chemical complementarity to other molecules provides interaction specificity for ligand binding, docking of bio-macromolecules, and enzymatic catalysis.As of today, there is no accepted general scheme to represent protein surfaces. Furthermore, most of the research on protein surface focuses on regions of specific interest such as interaction, ligand binding, and docking sites. We present a first step toward a general purpose representation of protein surfaces: a novel surface patch library that represents most surface patches (~98%) in a data set regardless of their functional roles. RESULTS: Surface patches, in this work, are small fractions of the protein surface. Using a measure of inter-patch distance, we clustered patches extracted from a data set of high quality, non-redundant, proteins. The surface patch library is the collection of all the cluster centroids; thus, each of the data set patches is close to one of the elements in the library.We demonstrate the biological significance of our method through the ability of the library to capture surface characteristics of native protein structures as opposed to those of decoy sets generated by state-of-the-art protein structure prediction methods. The patches of the decoys are significantly less compatible with the library than their corresponding native structures, allowing us to reliably distinguish native models from models generated by servers. This trend, however, does not extend to the decoys themselves, as their similarity to the native structures does not correlate with compatibility with the library. CONCLUSIONS: We expect that this high-quality, generic surface patch library will add a new perspective to the description of protein structures and improve our ability to predict them. In particular, we expect that it will help improve the prediction of surface features that are apparently neglected by current techniques.The surface patch libraries are publicly available at http://www.cs.bgu.ac.il/~keasar/patchLibrary.


Assuntos
Biologia Computacional/métodos , Bases de Dados de Proteínas , Proteínas/química , Algoritmos , Análise por Conglomerados , Modelos Moleculares , Fragmentos de Peptídeos/química , Conformação Proteica , Propriedades de Superfície
13.
Proteins ; 79(6): 1952-63, 2011 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-21491495

RESUMO

The identification of catalytic residues is an essential step in functional characterization of enzymes. We present a purely structural approach to this problem, which is motivated by the difficulty of evolution-based methods to annotate structural genomics targets that have few or no homologs in the databases. Our approach combines a state-of-the-art support vector machine (SVM) classifier with novel structural features that augment structural clues by spatial averaging and Z scoring. Special attention is paid to the class imbalance problem that stems from the overwhelming number of non-catalytic residues in enzymes compared to catalytic residues. This problem is tackled by: (1) optimizing the classifier to maximize a performance criterion that considers both Type I and Type II errors in the classification of catalytic and non-catalytic residues; (2) under-sampling non-catalytic residues before SVM training; and (3) during SVM training, penalizing errors in learning catalytic residues more than errors in learning non-catalytic residues. Tested on four enzyme datasets, one specifically designed by us to mimic the structural genomics scenario and three previously evaluated datasets, our structure-based classifier is never inferior to similar structure-based classifiers and comparable to classifiers that use both structural and evolutionary features. In addition to the evaluation of the performance of catalytic residue identification, we also present detailed case studies on three proteins. This analysis suggests that many false positive predictions may correspond to binding sites and other functional residues. A web server that implements the method, our own-designed database, and the source code of the programs are publicly available at http://www.cs.bgu.ac.il/∼meshi/functionPrediction.


Assuntos
Inteligência Artificial , Enzimas/química , Genômica/métodos , Domínio Catalítico , Bases de Dados de Proteínas , Conformação Proteica
14.
Bioinformatics ; 25(20): 2639-45, 2009 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-19628506

RESUMO

MOTIVATION: The roughness of energy landscapes is a major obstacle to protein structure prediction, since it forces conformational searches to spend much time struggling to escape numerous traps. Specifically, beta-sheet formation is prone to stray, since many possible combinations of hydrogen bonds are dead ends in terms of beta-sheet assembly. It has been shown that cooperative terms for backbone hydrogen bonds ease this problem by augmenting hydrogen bond patterns that are consistent with beta sheets. Here, we present a novel cooperative hydrogen-bond term that is both effective in promoting beta sheets and computationally efficient. In addition, the new term is differentiable and operates on all-atom protein models. RESULTS: Energy optimization of poly-alanine chains under the new term led to significantly more beta-sheet content than optimization under a non-cooperative term. Furthermore, the optimized structure included very few non-native patterns. AVAILABILITY: The new term is implemented within the MESHI package and is freely available at http://cs.bgu.ac.il/ approximately meshi.


Assuntos
Estrutura Secundária de Proteína , Proteínas/química , Simulação por Computador , Bases de Dados de Proteínas , Ligação de Hidrogênio , Modelos Moleculares , Dobramento de Proteína , Termodinâmica
15.
J Biol Chem ; 284(26): 17677-86, 2009 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-19366695

RESUMO

Vesicular zinc transporters (ZnTs) play a critical role in regulating Zn2+ homeostasis in various cellular compartments and are linked to major diseases ranging from Alzheimer disease to diabetes. Despite their importance, the intracellular localization of ZnTs poses a major challenge for establishing the mechanisms by which they function and the identity of their ion binding sites. Here, we combine fluorescence-based functional analysis and structural modeling aimed at elucidating these functional aspects. Expression of ZnT5 was followed by both accelerated removal of Zn2+ from the cytoplasm and its increased vesicular sequestration. Further, activity of this zinc transport was coupled to alkalinization of the trans-Golgi network. Finally, structural modeling of ZnT5, based on the x-ray structure of the bacterial metal transporter YiiP, identified four residues that can potentially form the zinc binding site on ZnT5. Consistent with this model, replacement of these residues, Asp599 and His451, with alanine was sufficient to block Zn2+ transport. These findings indicate, for the first time, that Zn2+ transport mediated by a mammalian ZnT is catalyzed by H+/Zn2+ exchange and identify the zinc binding site of ZnT proteins essential for zinc transport.


Assuntos
Proteínas de Transporte de Cátions/metabolismo , Proteínas de Neoplasias/metabolismo , Zinco/metabolismo , Rede trans-Golgi/metabolismo , Ácido Aspártico/química , Ácido Aspártico/genética , Ácido Aspártico/metabolismo , Sítios de Ligação , Proteínas de Transporte de Cátions/química , Proteínas de Transporte de Cátions/genética , Células Cultivadas , Citoplasma/metabolismo , Histidina/química , Histidina/genética , Histidina/metabolismo , Humanos , Rim/citologia , Rim/metabolismo , Modelos Moleculares , Mutagênese Sítio-Dirigida , Proteínas de Neoplasias/química , Proteínas de Neoplasias/genética , Conformação Proteica , Prótons , ATPases Vacuolares Próton-Translocadoras/metabolismo
16.
BMC Struct Biol ; 8: 27, 2008 May 29.
Artigo em Inglês | MEDLINE | ID: mdl-18510728

RESUMO

BACKGROUND: The structural stability of peptides in solution strongly affects their binding affinities and specificities. Thus, in peptide biotechnology, an increase in the structural stability is often desirable. The present work combines two orthogonal computational techniques, Molecular Dynamics and a knowledge-based potential, for the prediction of structural stability of short peptides (< 20 residues) in solution. RESULTS: We tested the new approach on four families of short beta-hairpin peptides: TrpZip, MBH, bhpW and EPO, whose structural stabilities have been experimentally measured in previous studies. For all four families, both computational techniques show considerable correlation (r > 0.65) with the experimentally measured stabilities. The consensus of the two techniques shows higher correlation (r > 0.82). CONCLUSION: Our results suggest a prediction scheme that can be used to estimate the relative structural stability within a peptide family. We discuss the applicability of this predictive approach for in-silico screening of combinatorial peptide libraries.


Assuntos
Biotecnologia/métodos , Biologia Computacional/métodos , Peptídeos/química , Conformação Proteica , Dobramento de Proteína , Simulação por Computador
17.
Proteins ; 72(1): 62-73, 2008 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-18186478

RESUMO

Rotatable torsion angles are the major degrees of freedom in proteins. Adjacent angles are highly correlated and energy terms that rely on these correlations are intensively used in molecular modeling. However, the utility of torsion based terms is not yet fully exploited. Many of these terms do not capture the full scale of the correlations. Other terms, which rely on lookup tables, cannot be used in the context of force-driven algorithms because they are not fully differentiable. This study aims to extend the usability of torsion terms by presenting a set of high-dimensional and fully-differentiable energy terms that are derived from high-resolution structures. The set includes terms that describe backbone conformational probabilities and propensities, side-chain rotamer probabilities, and an elaborate term that couples all the torsion angles within the same residue. The terms are constructed by cubic spline interpolation with periodic boundary conditions that enable full differentiability and high computational efficiency. We show that the spline implementation does not compromise the accuracy of the original database statistics. We further show that the side-chain relevant terms are compatible with established rotamer probabilities. Despite their very local characteristics, the new terms are often able to identify native and native-like structures within decoy sets. Finally, force-based minimization of NMR structures with the new terms improves their torsion angle statistics with minor structural distortion (0.5 A RMSD on average). The new terms are freely available in the MESHI molecular modeling package. The spline coefficients are also available as a documented MATLAB file.


Assuntos
Proteínas/química , Torção Mecânica , Conformação Proteica , Termodinâmica
18.
J Comput Biol ; 13(5): 1041-8, 2006 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-16796550

RESUMO

Simulations of molecular systems typically handle interactions within non-bonded pairs. Generating and updating a list of these pairs can be the most time-consuming part of energy calculations for large systems. Thus, efficient non-bonded list processing can speed up the energy calculations significantly. While the asymptotic complexity of current algorithms (namely O(N), where N is the number of particles) is probably the lowest possible, a wide space for optimization is still left. This article offers a heuristic extension to the previously suggested grid based algorithms. We show that, when the average particle movements are slow, simulation time can be reduced considerably. The proposed algorithm has been implemented in the DistanceMatrix class of the molecular modeling package MESHI. MESHI is freely available at .


Assuntos
Algoritmos , Simulação por Computador , Modelos Químicos , Termodinâmica
19.
Bioinformatics ; 21(20): 3931-2, 2005 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-16105898

RESUMO

UNLABELLED: Adapting a modular and object-oriented approach in the design of molecular modeling packages may reduce the software development barrier between ideas and their programed applications. Towards this goal we developed MESHI, a new, strictly object-oriented, molecular modeling suite written in Java. MESHI provides a comprehensive library of extendable classes for all the essential components of molecular modeling: molecular and geometry elements, energy functions and optimization methods. AVAILABILITY: MESHI and its related documentation are freely available at http://www.cs.bgu.ac.il/~meshi; the MESHI API is available at http://www.cs.bgu.ac.il/~meshi/API CONTACT: keasar@cs.bgu.ac.il SUPPLEMENTARY INFORMATION: The Supplementary information includes (1) a detailed description of several key packages and classes, and (2) a brief presentation of results achieved by using the MESHI application--Beautify--in the CASP6 experiment.


Assuntos
Modelos Químicos , Modelos Moleculares , Linguagens de Programação , Proteínas/análise , Proteínas/química , Análise de Sequência de Proteína/métodos , Software , Simulação por Computador , Conformação Proteica
20.
RNA ; 10(11): 1764-75, 2004 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-15388875

RESUMO

All eukaryotic mRNAs possess a 5'-cap (m(7)GpppN) that is recognized by a family of cap-binding proteins. These participate in various processes, such as RNA transport and stabilization, as well as in assembly of the translation initiation complex. The 5'-cap of trypanosomatids is complex; in addition to 7-methyl guanosine, it includes unique modifications on the first four transcribed nucleotides, and is thus denoted cap-4. Here we analyze a cap-binding protein of Leishmania, in an attempt to understand the structural features that promote its binding to this unusual cap. LeishIF4E-1, a homolog of eIF4E, contains the conserved cap-binding pocket, similar to its mouse counterpart. The mouse eIF4E has a higher K(as) for all cap analogs tested, as compared with LeishIF4E-1. However, whereas the mouse eIF4E shows a fivefold higher affinity for m(7)GTP than for a chemically synthesized cap-4 structure, LeishIF4E-1 shows similar affinities for both ligands. A sequence alignment shows that LeishIF4E-1 lacks the region that parallels the C terminus in the murine eIF4E. Truncation of this region in the mouse protein reduces the difference that is observed between its binding to m(7)GTP and cap-4, prior to this deletion. We hypothesize that variations in the structure of LeishIF4E-1, possibly also the absence of a region that is homologous to the C terminus of the mouse protein, promote its ability to interact with the cap-4 structure. LeishIF4E-1 is distributed in the cytoplasm, but its function is not clear yet, because it cannot substitute the mammalian eIF4E in a rabbit reticulocyte in vitro translation system.


Assuntos
Fator de Iniciação 4E em Eucariotos/metabolismo , Guanosina Difosfato/análogos & derivados , Guanosina Difosfato/metabolismo , Leishmania/metabolismo , Proteínas de Ligação ao Cap de RNA/metabolismo , Sequência de Aminoácidos , Animais , Células Cultivadas , Simulação por Computador , Sequência Conservada , Citoplasma/química , Fator de Iniciação 4E em Eucariotos/química , Técnica Indireta de Fluorescência para Anticorpo , Guanosina Difosfato/química , Cinética , Leishmania major/metabolismo , Microscopia de Fluorescência , Modelos Moleculares , Dados de Sequência Molecular , Estrutura Secundária de Proteína , Proteínas de Ligação ao Cap de RNA/isolamento & purificação , RNA de Protozoário/isolamento & purificação , RNA de Protozoário/metabolismo , Proteínas Recombinantes/metabolismo , Homologia de Sequência de Aminoácidos
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