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1.
Pac Symp Biocomput ; 27: 34-45, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34890134

RESUMO

The established approach to unsupervised protein contact prediction estimates coevolving positions using undirected graphical models. This approach trains a Potts model on a Multiple Sequence Alignment. Increasingly large Transformers are being pretrained on unlabeled, unaligned protein sequence databases and showing competitive performance on protein contact prediction. We argue that attention is a principled model of protein interactions, grounded in real properties of protein family data. We introduce an energy-based attention layer, factored attention, which, in a certain limit, recovers a Potts model, and use it to contrast Potts and Transformers. We show that the Transformer leverages hierarchical signal in protein family databases not captured by single-layer models. This raises the exciting possibility for the development of powerful structured models of protein family databases.


Assuntos
Biologia Computacional , Proteínas , Atenção , Humanos , Proteínas/genética , Alinhamento de Sequência
2.
Nature ; 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34853475

RESUMO

There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences1-3. Here we investigate whether the information captured by such networks is sufficiently rich to generate new folded proteins with sequences unrelated to those of the naturally occurring proteins used in training the models. We generate random amino acid sequences, and input them into the trRosetta structure prediction network to predict starting residue-residue distance maps, which, as expected, are quite featureless. We then carry out Monte Carlo sampling in amino acid sequence space, optimizing the contrast (Kullback-Leibler divergence) between the inter-residue distance distributions predicted by the network and background distributions averaged over all proteins. Optimization from different random starting points resulted in novel proteins spanning a wide range of sequences and predicted structures. We obtained synthetic genes encoding 129 of the network-'hallucinated' sequences, and expressed and purified the proteins in Escherichia coli; 27 of the proteins yielded monodisperse species with circular dichroism spectra consistent with the hallucinated structures. We determined the three-dimensional structures of three of the hallucinated proteins, two by X-ray crystallography and one by NMR, and these closely matched the hallucinated models. Thus, deep networks trained to predict native protein structures from their sequences can be inverted to design new proteins, and such networks and methods should contribute alongside traditional physics-based models to the de novo design of proteins with new functions.

4.
Phys Chem Chem Phys ; 23(46): 26376-26384, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34792064

RESUMO

The magnetic properties of M2AX (M = Mn, Fe; A = Al, Ga, Si, Ge; X = C, N) phases were studied within DFT-GGA. The magnetic electronic ground state is determined. The investigation of the phase stability of M2AX phases is performed by comparing the total energy of MAX phases to that of the set of competitive phases for calculation of the phase formation enthalpy. As the result of such an approach, we have found one stable compound (Mn2GaC), and seven metastable ones. It is shown that several metastable MAX phases (Mn2AlC, Fe2GaC, Mn2GeC, and Mn2GeN) become stable at a small applied pressure (1.5-7 GPa). The mechanical, electronic and elastic properties of metastable MAX phases are studied.

5.
Curr Opin Chem Biol ; 65: 136-144, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34547592

RESUMO

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information - but largely piece-by-piece - from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.

6.
Science ; 373(6557): 871-876, 2021 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-34282049

RESUMO

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.


Assuntos
Aprendizado Profundo , Conformação Proteica , Dobramento de Proteína , Proteínas/química , Proteínas ADAM/química , Sequência de Aminoácidos , Simulação por Computador , Microscopia Crioeletrônica , Cristalografia por Raios X , Bases de Dados de Proteínas , Proteínas de Membrana/química , Modelos Moleculares , Complexos Multiproteicos/química , Redes Neurais de Computação , Subunidades Proteicas/química , Proteínas/fisiologia , Receptores Acoplados a Proteínas G/química , Esfingosina N-Aciltransferase/química
7.
Dalton Trans ; 50(28): 9735-9745, 2021 Jul 21.
Artigo em Inglês | MEDLINE | ID: mdl-34165472

RESUMO

The ludwigite Co2FeBO5 has been studied experimentally using 57Fe Mössbauer spectroscopy and theoretically using DFT + GGA calculations. The room-temperature Mössbauer spectra are composed of four quadrupole doublets corresponding to the high-spin Fe3+ ions in octahedral oxygen coordination. All components undergo splitting below 117 K due to the magnetic hyperfine fields. The DFT + GGA calculations performed for three models of Fe ion distributions have revealed that the ground state corresponds to the "Fe4(HS)" model with the high-spin Fe3+ ions located at the M4 site and the high-spin Co2+ ions located at the M1, M2, and M3 sites. A ferrimagnetic ground state, with the Co and Fe magnetic moments being nearly parallel to the b-axis and a total magnetic moment of circa 1.1µB f.u.-1, was found. The other Fe distributions cause an increase in the local octahedral distortions and transformation of the spin state. The calculated quadrupole splitting values are in good agreement with the experimental values obtained by Mössbauer spectroscopy.

8.
Nanomaterials (Basel) ; 11(6)2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34071773

RESUMO

The atomic and electronic structure of vanadium phosphide one- to four-atomic-layer thin films and their composites with zinc oxide substrate are modelled by means of quantum chemistry. Favorable vanadium phosphide to ZnO orientation is defined and found to remain the same for all the structures under consideration. The electronic structure of the composites is analyzed in detail. The features of the charge and spin density distribution are discussed.

9.
Proc Natl Acad Sci U S A ; 118(11)2021 03 16.
Artigo em Inglês | MEDLINE | ID: mdl-33712545

RESUMO

The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.


Assuntos
Redes Neurais de Computação , Proteínas/química , Modelos Moleculares , Conformação Proteica , Dobramento de Proteína , Termodinâmica
10.
Protein Sci ; 29(11): 2274-2280, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32949024

RESUMO

Biofilms are accumulations of microorganisms embedded in extracellular matrices that protect against external factors and stressful environments. Cyanobacterial biofilms are ubiquitous and have potential for treatment of wastewater and sustainable production of biofuels. But the underlying mechanisms regulating cyanobacterial biofilm formation are unclear. Here, we report the solution NMR structure of a protein, Se0862, conserved across diverse cyanobacterial species and involved in regulation of biofilm formation in the cyanobacterium Synechococcus elongatus PCC 7942. Se0862 is a class α+ß protein with ααßßßßαα topology and roll architecture, consisting of a four-stranded ß-sheet that is flanked by four α-helices on one side. Conserved surface residues constitute a hydrophobic pocket and charged regions that are likely also present in Se0862 orthologs.


Assuntos
Proteínas de Bactérias/química , Biofilmes , Synechococcus , Ressonância Magnética Nuclear Biomolecular , Conformação Proteica em alfa-Hélice , Conformação Proteica em Folha beta , Synechococcus/química , Synechococcus/fisiologia
11.
Mol Cell ; 79(6): 881-901, 2020 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-32768408

RESUMO

Nucleosomes package genomic DNA into chromatin. By regulating DNA access for transcription, replication, DNA repair, and epigenetic modification, chromatin forms the nexus of most nuclear processes. In addition, dynamic organization of chromatin underlies both regulation of gene expression and evolution of chromosomes into individualized sister objects, which can segregate cleanly to different daughter cells at anaphase. This collaborative review shines a spotlight on technologies that will be crucial to interrogate key questions in chromatin and chromosome biology including state-of-the-art microscopy techniques, tools to physically manipulate chromatin, single-cell methods to measure chromatin accessibility, computational imaging with neural networks and analytical tools to interpret chromatin structure and dynamics. In addition, this review provides perspectives on how these tools can be applied to specific research fields such as genome stability and developmental biology and to test concepts such as phase separation of chromatin.


Assuntos
Cromatina/genética , Cromossomos/genética , DNA/genética , Nucleossomos/genética , Reparo do DNA/genética , Replicação do DNA/genética , Epigênese Genética/genética , Humanos
12.
Commun Biol ; 3(1): 320, 2020 06 19.
Artigo em Inglês | MEDLINE | ID: mdl-32561885

RESUMO

Bacteria and archaea possessing the hgcAB gene pair methylate inorganic mercury (Hg) to form highly toxic methylmercury. HgcA consists of a corrinoid binding domain and a transmembrane domain, and HgcB is a dicluster ferredoxin. However, their detailed structure and function have not been thoroughly characterized. We modeled the HgcAB complex by combining metagenome sequence data mining, coevolution analysis, and Rosetta structure calculations. In addition, we overexpressed HgcA and HgcB in Escherichia coli, confirmed spectroscopically that they bind cobalamin and [4Fe-4S] clusters, respectively, and incorporated these cofactors into the structural model. Surprisingly, the two domains of HgcA do not interact with each other, but HgcB forms extensive contacts with both domains. The model suggests that conserved cysteines in HgcB are involved in shuttling HgII, methylmercury, or both. These findings refine our understanding of the mechanism of Hg methylation and expand the known repertoire of corrinoid methyltransferases in nature.


Assuntos
Proteínas de Bactérias/química , Proteínas de Bactérias/metabolismo , Mercúrio/metabolismo , Complexos Multiproteicos/química , Complexos Multiproteicos/metabolismo , Proteínas de Bactérias/genética , Corrinoides/metabolismo , Desulfovibrio desulfuricans/genética , Metagenoma , Metilação , Modelos Moleculares , Complexos Multiproteicos/genética , Filogenia , Conformação Proteica , Domínios Proteicos , Espectrofotometria Ultravioleta
13.
Science ; 368(6489)2020 04 24.
Artigo em Inglês | MEDLINE | ID: mdl-32327568

RESUMO

Misfolded luminal endoplasmic reticulum (ER) proteins undergo ER-associated degradation (ERAD-L): They are retrotranslocated into the cytosol, polyubiquitinated, and degraded by the proteasome. ERAD-L is mediated by the Hrd1 complex (composed of Hrd1, Hrd3, Der1, Usa1, and Yos9), but the mechanism of retrotranslocation remains mysterious. Here, we report a structure of the active Hrd1 complex, as determined by cryo-electron microscopy analysis of two subcomplexes. Hrd3 and Yos9 jointly create a luminal binding site that recognizes glycosylated substrates. Hrd1 and the rhomboid-like Der1 protein form two "half-channels" with cytosolic and luminal cavities, respectively, and lateral gates facing one another in a thinned membrane region. These structures, along with crosslinking and molecular dynamics simulation results, suggest how a polypeptide loop of an ERAD-L substrate moves through the ER membrane.


Assuntos
Proteínas de Transporte/química , Degradação Associada com o Retículo Endoplasmático , Glicoproteínas de Membrana/química , Proteínas de Membrana/química , Complexos Multiproteicos/química , Proteólise , Proteínas de Saccharomyces cerevisiae/química , Ubiquitina-Proteína Ligases/química , Proteínas de Transporte/metabolismo , Microscopia Crioeletrônica , Retículo Endoplasmático/metabolismo , Glicoproteínas de Membrana/metabolismo , Proteínas de Membrana/metabolismo , Simulação de Dinâmica Molecular , Complexos Multiproteicos/metabolismo , Domínios Proteicos , Dobramento de Proteína , Proteínas de Saccharomyces cerevisiae/metabolismo
14.
Molecules ; 25(6)2020 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-32178469

RESUMO

The structural, magnetic, electrical, and dilatation properties of the rare-earth NdCoO3 and SmCoO3 cobaltites were investigated. Their comparative analysis was carried out and the effect of multiplicity fluctuations on physical properties of the studied cobaltites was considered. Correlations between the spin state change of cobalt ions and the temperature dependence anomalies of the lattice parameters, magnetic susceptibility, volume thermal expansion coefficient, and electrical resistance have been revealed. A comparison of the results with well-studied GdCoO3 allows one to single out both the general tendencies inherent in all rare-earth cobaltites taking into account the lanthanide contraction and peculiar properties of the samples containing Nd and Sm.


Assuntos
Cobalto/química , Estrutura Molecular , Neodímio/química , Óxidos/química , Samário/química , Cristalografia por Raios X , Fenômenos Eletromagnéticos , Íons/química , Magnetismo
15.
Proc Natl Acad Sci U S A ; 117(3): 1496-1503, 2020 01 21.
Artigo em Inglês | MEDLINE | ID: mdl-31896580

RESUMO

The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo-designed proteins, identifying the key fold-determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.


Assuntos
Conformação Proteica , Análise de Sequência de Proteína/métodos , Software , Animais , Aprendizado Profundo , Humanos
16.
Anal Bioanal Chem ; 411(25): 6723-6732, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31396648

RESUMO

Nucleic acid (NA) aptamers bind to their targets with high affinity and selectivity. The three-dimensional (3D) structures of aptamers play a major role in these non-covalent interactions. Here, we use a four-step approach to determine a true 3D structure of aptamers in solution using small-angle X-ray scattering (SAXS) and molecular structure restoration (MSR). The approach consists of (i) acquiring SAXS experimental data of an aptamer in solution, (ii) building a spatial distribution of the molecule's electron density using SAXS results, (iii) constructing a 3D model of the aptamer from its nucleotide primary sequence and secondary structure, and (iv) comparing and refining the modeled 3D structures with the experimental SAXS model. In the proof-of-principle we analyzed the 3D structure of RE31 aptamer to thrombin in a native free state at different temperatures and validated it by circular dichroism (CD). The resulting 3D structure of RE31 has the most energetically favorable conformation and the same elements such as a B-form duplex, non-complementary region, and two G-quartets which were previously reported by X-ray diffraction (XRD) from a single crystal. More broadly, this study demonstrates the complementary approach for constructing and adjusting the 3D structures of aptamers, DNAzymes, and ribozymes in solution, and could supply new opportunities for developing functional nucleic acids. Graphical abstract.


Assuntos
Aptâmeros de Nucleotídeos/química , Algoritmos , Simulação por Computador , Quadruplex G , Modelos Moleculares , Conformação de Ácido Nucleico , Espalhamento a Baixo Ângulo , Difração de Raios X/métodos
17.
Proteins ; 87(12): 1241-1248, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31444975

RESUMO

As a participant in the joint CASP13-CAPRI46 assessment, the ClusPro server debuted its new template-based modeling functionality. The addition of this feature, called ClusPro TBM, was motivated by the previous CASP-CAPRI assessments and by the proven ability of template-based methods to produce higher-quality models, provided templates are available. In prior assessments, ClusPro submissions consisted of models that were produced via free docking of pre-generated homology models. This method was successful in terms of the number of acceptable predictions across targets; however, analysis of results showed that purely template-based methods produced a substantially higher number of medium-quality models for targets for which there were good templates available. The addition of template-based modeling has expanded ClusPro's ability to produce higher accuracy predictions, primarily for homomeric but also for some heteromeric targets. Here we review the newest additions to the ClusPro web server and discuss examples of CASP-CAPRI targets that continue to drive further development. We also describe ongoing work not yet implemented in the server. This includes the development of methods to improve template-based models and the use of co-evolutionary information for data-assisted free docking.


Assuntos
Biologia Computacional , Conformação Proteica , Proteínas/ultraestrutura , Software , Algoritmos , Sítios de Ligação/genética , Bases de Dados de Proteínas , Humanos , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Mapeamento de Interação de Proteínas , Proteínas/química , Proteínas/genética , Homologia Estrutural de Proteína
18.
Mol Phylogenet Evol ; 139: 106562, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31323334

RESUMO

One major challenge to delimiting species with genetic data is successfully differentiating population structure from species-level divergence, an issue exacerbated in taxa inhabiting naturally fragmented habitats. Many fields of science are now using machine learning, and in evolutionary biology supervised machine learning has recently been used to infer species boundaries. These supervised methods require training data with associated labels. Conversely, unsupervised machine learning (UML) uses inherent data structure and does not require user-specified training labels, potentially providing more objectivity in species delimitation. In the context of integrative taxonomy, we demonstrate the utility of three UML approaches (random forests, variational autoencoders, t-distributed stochastic neighbor embedding) for species delimitation in an arachnid taxon with high population genetic structure (Opiliones, Laniatores, Metanonychus). We find that UML approaches successfully cluster samples according to species-level divergences and not high levels of population structure, while model-based validation methods severely over-split putative species. UML offers intuitive data visualization in two-dimensional space, the ability to accommodate various data types, and has potential in many areas of systematic and evolutionary biology. We argue that machine learning methods are ideally suited for species delimitation and may perform well in many natural systems and across taxa with diverse biological characteristics.


Assuntos
Aprendizado de Máquina não Supervisionado , Animais , Aracnídeos/classificação , Aracnídeos/genética , Análise por Conglomerados , Filogenia , Polimorfismo de Nucleotídeo Único , Análise de Componente Principal
19.
Science ; 365(6449): 185-189, 2019 07 12.
Artigo em Inglês | MEDLINE | ID: mdl-31296772

RESUMO

Residue-residue coevolution has been observed across a number of protein-protein interfaces, but the extent of residue coevolution between protein families on the whole-proteome scale has not been systematically studied. We investigate coevolution between 5.4 million pairs of proteins in Escherichia coli and between 3.9 millions pairs in Mycobacterium tuberculosis We find strong coevolution for binary complexes involved in metabolism and weaker coevolution for larger complexes playing roles in genetic information processing. We take advantage of this coevolution, in combination with structure modeling, to predict protein-protein interactions (PPIs) with an accuracy that benchmark studies suggest is considerably higher than that of proteome-wide two-hybrid and mass spectrometry screens. We identify hundreds of previously uncharacterized PPIs in E. coli and M. tuberculosis that both add components to known protein complexes and networks and establish the existence of new ones.


Assuntos
Proteínas de Bactérias/metabolismo , Coevolução Biológica , Escherichia coli/metabolismo , Mycobacterium tuberculosis/metabolismo , Mapas de Interação de Proteínas , Proteínas de Bactérias/química , Proteínas de Escherichia coli/química , Proteínas de Escherichia coli/metabolismo , Conformação Proteica , Proteoma
20.
Sci China Life Sci ; 62(7): 873-882, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31119558

RESUMO

Functional manipulation of biosynthetic enzymes such as cytochrome P450s (or P450s) has attracted great interest in metabolic engineering of plant natural products. Cucurbitacins and mogrosides are plant triterpenoids that share the same backbone but display contrasting bioactivities. This structural and functional diversity of the two metabolites can be manipulated by engineering P450s. However, the functional redesign of P450s through directed evolution (DE) or structure-guided protein engineering is time consuming and challenging, often because of a lack of high-throughput screening methods and crystal structures of P450s. In this study, we used an integrated approach combining computational protein design, evolutionary information, and experimental data-driven optimization to alter the substrate specificity of a multifunctional P450 (CYP87D20) from cucumber. After three rounds of iterative design and evaluation of 96 protein variants, CYP87D20, which is involved in the cucurbitacin C biosynthetic pathway, was successfully transformed into a P450 mono-oxygenase that performs a single specific hydroxylation at C11 of cucurbitadienol. This integrated P450-engineering approach can be further applied to create a de novo pathway to produce mogrol, the precursor of the natural sweetener mogroside, or to alter the structural diversity of plant triterpenoids by functionally manipulating other P450s.


Assuntos
Sistema Enzimático do Citocromo P-450/química , Sistema Enzimático do Citocromo P-450/genética , Proteínas de Plantas/química , Proteínas de Plantas/genética , Aminoácidos/química , Aminoácidos/metabolismo , Vias Biossintéticas , Cucumis sativus/genética , Engenharia Metabólica , Simulação de Acoplamento Molecular , Mutação , Conformação Proteica , Especificidade por Substrato , Triterpenos/química , Triterpenos/metabolismo , Leveduras/genética , Leveduras/metabolismo
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