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1.
Front Mol Biosci ; 8: 676268, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34476238

RESUMO

Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining sparse paramagnetic NMR with physical modelling to infer approximate protein structural ensembles. We use calmodulin in complex with the smooth muscle myosin light chain kinase peptide as a model system. Despite acquiring data from samples labeled only at the backbone amide positions, we are able to produce an ensemble with an average RMSD of ∼2.8 Å from a reference X-ray crystal structure. Our approach requires only backbone chemical shifts and measurements of the paramagnetic relaxation enhancement and residual dipolar couplings that can be obtained from sparsely labeled samples.

2.
Nat Commun ; 12(1): 1986, 2021 03 31.
Artigo em Inglês | MEDLINE | ID: mdl-33790266

RESUMO

Many bacteria use the second messenger cyclic diguanylate (c-di-GMP) to control motility, biofilm production and virulence. Here, we identify a thermosensory diguanylate cyclase (TdcA) that modulates temperature-dependent motility, biofilm development and virulence in the opportunistic pathogen Pseudomonas aeruginosa. TdcA synthesizes c-di-GMP with catalytic rates that increase more than a hundred-fold over a ten-degree Celsius change. Analyses using protein chimeras indicate that heat-sensing is mediated by a thermosensitive Per-Arnt-SIM (PAS) domain. TdcA homologs are widespread in sequence databases, and a distantly related, heterologously expressed homolog from the Betaproteobacteria order Gallionellales also displayed thermosensitive diguanylate cyclase activity. We propose, therefore, that thermotransduction is a conserved function of c-di-GMP signaling networks, and that thermosensitive catalysis of a second messenger constitutes a mechanism for thermal sensing in bacteria.


Assuntos
Proteínas de Bactérias/metabolismo , GMP Cíclico/análogos & derivados , Proteínas de Escherichia coli/metabolismo , Fósforo-Oxigênio Liases/metabolismo , Pseudomonas aeruginosa/metabolismo , Sistemas do Segundo Mensageiro/fisiologia , Transdução de Sinais/fisiologia , Algoritmos , Proteínas de Bactérias/genética , Biofilmes/crescimento & desenvolvimento , Cromatografia Líquida , GMP Cíclico/metabolismo , Proteínas de Escherichia coli/genética , Regulação Bacteriana da Expressão Gênica , Espectrometria de Massas , Fósforo-Oxigênio Liases/genética , Pseudomonas aeruginosa/genética , Pseudomonas aeruginosa/fisiologia , Temperatura
3.
J Am Soc Mass Spectrom ; 31(2): 207-216, 2020 Feb 05.
Artigo em Inglês | MEDLINE | ID: mdl-32031402

RESUMO

The functional properties of a protein are strongly influenced by its topography, or the solvent-facing contour map of its surface. Together with crosslinking, covalent labeling mass spectrometry (CL-MS) has the potential to contribute topographical data through the measurement of surface accessibility. However, recent efforts to correlate measures of surface accessibility with labeling yield have been met with mixed success. Most applications of CL-MS involve differential analysis of protein interactions (i.e., footprinting experiments) where such inconsistencies have limited effect. Extending CL-MS into structural analysis requires an improved evaluation of the relationship between labeling and surface exposure. In this study, we applied recently developed diazirine reagents to obtain deep coverage of the large motor domain of Eg5 (a mitotic kinesin), and together with computational methods we correlated labeling yields with accessibility data in a number of ways. We observe that correlations can indeed be seen at a local structural level, but these correlations do not extend across the structure. The lack of correlation arises from the influence of protein dynamics and chemical composition on reagent partitioning and, thus, also on labeling yield. We conclude that our use of CL-MS data should be considered in light of "chemical accessibility" rather than "solvent accessibility" and suggest that CL-MS data would be a useful tool in the fundamental study of protein-solute interactions.


Assuntos
Diazometano/química , Espectrometria de Massas/métodos , Humanos , Indicadores e Reagentes , Modelos Moleculares , Conformação Proteica
4.
J Med Chem ; 62(11): 5522-5540, 2019 06 13.
Artigo em Inglês | MEDLINE | ID: mdl-31117518

RESUMO

Protein-protein interactions (PPIs) have emerged as significant targets for therapeutic development, owing to their critical nature in diverse biological processes. An ideal PPI-based target is the protein myeloid cell leukemia 1 (MCL1), a critical prosurvival factor in cancers such as multiple myeloma where MCL1 levels directly correlate to disease progression. Current strategies for halting the antiapoptotic properties of MCL1 revolve around inhibiting its sequestration of proapoptotic factors. Existing inhibitors disrupt endogenous regulatory proteins; however, this strategy actually leads to an increase of MCL1 protein levels. Here, we show the development of hetero-bifunctional small molecules capable of selectively targeting MCL1 using a proteolysis targeting chimera (PROTAC) methodology leading to successful degradation. We have confirmed the involvement of the E3 ligase CUL4A-DDB1 cereblon ubiquitination pathway, making these PROTACs a first step toward a new class of antiapoptotic B-cell lymphoma 2 family protein degraders.


Assuntos
Proteína de Sequência 1 de Leucemia de Células Mieloides/metabolismo , Proteólise/efeitos dos fármacos , Linhagem Celular , Humanos , Indóis/farmacologia , Modelos Moleculares , Proteína de Sequência 1 de Leucemia de Células Mieloides/química , Complexo de Endopeptidases do Proteassoma/metabolismo , Conformação Proteica , Sulfonamidas/farmacologia , Ubiquitinação/efeitos dos fármacos
5.
Angew Chem Int Ed Engl ; 58(20): 6564-6568, 2019 05 13.
Artigo em Inglês | MEDLINE | ID: mdl-30913341

RESUMO

There is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid-state NMR restraints with physics-based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi-quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid-state NMR data for the model protein GB1 labeled with Cu2+ -EDTA at six different sites. We are able to determine the structure to 0.9 Šaccuracy within a single day of computation on a GPU cluster. We further show that in some cases, the data from only a single paramagnetic tag are sufficient for accurate folding.


Assuntos
Espectroscopia de Ressonância Magnética/métodos , Proteínas/química , Humanos , Estrutura Molecular , Conformação Proteica
6.
Curr Opin Struct Biol ; 49: 145-153, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-29554555

RESUMO

Biomolecular structure determination has long relied on heuristics based on physical insight; however, recent efforts to model conformational ensembles and to make sense of sparse, ambiguous, and noisy data have revealed the value of detailed, quantitative physical models in structure determination. We review these two key challenges, describe different approaches to physical modeling in structure determination, and illustrate several successes and emerging technologies enabled by physical modeling.


Assuntos
Modelos Moleculares , Modelos Teóricos , Algoritmos , Conformação Molecular , Relação Estrutura-Atividade
7.
J Phys Chem B ; 122(21): 5448-5457, 2018 05 31.
Artigo em Inglês | MEDLINE | ID: mdl-29584433

RESUMO

Replica exchange is a widely used sampling strategy in molecular simulation. While a variety of methods exist to optimize parameters for temperature replica exchange, less is known about how to optimize parameters for more general Hamiltonian replica exchange simulations. We present an algorithm for the online optimization of total acceptance for both temperature and Hamiltonian replica exchange simulations using stochastic gradient descent. We optimize the total acceptance, a heuristic objective function capturing the efficiency of replica exchange. Our approach is general and has several desirable properties, including: (1) it makes few assumptions about the system of interest, (2) optimization occurs online without the requirement of presimulation, and (3) most importantly, it readily generalizes to systems where there are multiple control parameters (e.g., temperatures, force constants, etc.) that determine the Hamiltonian of each replica. We explore some general properties of the algorithm on a simple harmonic oscillator system, and demonstrate its effectiveness on a more complex data-guided protein folding simulation.

8.
Biochim Biophys Acta Proteins Proteom ; 1865(11 Pt B): 1654-1663, 2017 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-28648524

RESUMO

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.


Assuntos
Algoritmos , Simulação por Computador , Modelos Moleculares , Ressonância Magnética Nuclear Biomolecular/métodos , Conformação Molecular
9.
Sci Adv ; 2(11): e1601274, 2016 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-27847872

RESUMO

We report a key proof of principle of a new acceleration method [Modeling Employing Limited Data (MELD)] for predicting protein structures by molecular dynamics simulation. It shows that such Boltzmann-satisfying techniques are now sufficiently fast and accurate to predict native protein structures in a limited test within the Critical Assessment of Structure Prediction (CASP) community-wide blind competition.


Assuntos
Simulação de Dinâmica Molecular , Dobramento de Proteína , Proteínas/química , Software
10.
J Chem Theory Comput ; 11(10): 4770-9, 2015 Oct 13.
Artigo em Inglês | MEDLINE | ID: mdl-26574266

RESUMO

Force fields, such as Amber's ff12SB, can be fairly accurate models of the physical forces in proteins and other biomolecules. When coupled with accurate solvation models, force fields are able to bring insight into the conformational preferences, transitions, pathways, and free energies for these biomolecules. When computational speed/cost matters, implicit solvent is often used but at the cost of accuracy. We present an empirical grid-like correction term, in the spirit of cMAPs, to the combination of the ff12SB protein force field and the GBneck2 implicit-solvent model. Ff12SB-cMAP is parametrized on experimental helicity data. We provide validation on a set of peptides and proteins. Ff12SB-cMAP successfully improves the secondary structure biases observed in ff12SB + Gbneck2. Ff12SB-cMAP can be downloaded ( https://github.com/laufercenter/Amap.git ) and used within the Amber package. It can improve the agreement of force fields + implicit solvent with experiments.


Assuntos
Simulação de Dinâmica Molecular , Proteínas/química , Dobramento de Proteína , Solventes/química
11.
Proc Natl Acad Sci U S A ; 112(38): 11846-51, 2015 Sep 22.
Artigo em Inglês | MEDLINE | ID: mdl-26351667

RESUMO

Atomistic molecular dynamics (MD) simulations of protein molecules are too computationally expensive to predict most native structures from amino acid sequences. Here, we integrate "weak" external knowledge into folding simulations to predict protein structures, given their sequence. For example, we instruct the computer "to form a hydrophobic core," "to form good secondary structures," or "to seek a compact state." This kind of information has been too combinatoric, nonspecific, and vague to help guide MD simulations before. Within atomistic replica-exchange molecular dynamics (REMD), we develop a statistical mechanical framework, modeling using limited data with coarse physical insight(s) (MELD + CPI), for harnessing weak information. As a test, we apply MELD + CPI to predict the native structures of 20 small proteins. MELD + CPI samples to within less than 3.2 Å from native for all 20 and correctly chooses the native structures (<4 Å) for 15 of them, including ubiquitin, a millisecond folder. MELD + CPI is up to five orders of magnitude faster than brute-force MD, satisfies detailed balance, and should scale well to larger proteins. MELD + CPI may be useful where physics-based simulations are needed to study protein mechanisms and populations and where we have some heuristic or coarse physical knowledge about states of interest.


Assuntos
Simulação de Dinâmica Molecular , Proteínas/química , Algoritmos , Teorema de Bayes , Estrutura Secundária de Proteína , Termodinâmica
12.
Proc Natl Acad Sci U S A ; 112(22): 6985-90, 2015 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-26038552

RESUMO

More than 100,000 protein structures are now known at atomic detail. However, far more are not yet known, particularly among large or complex proteins. Often, experimental information is only semireliable because it is uncertain, limited, or confusing in important ways. Some experiments give sparse information, some give ambiguous or nonspecific information, and others give uncertain information-where some is right, some is wrong, but we don't know which. We describe a method called Modeling Employing Limited Data (MELD) that can harness such problematic information in a physics-based, Bayesian framework for improved structure determination. We apply MELD to eight proteins of known structure for which such problematic structural data are available, including a sparse NMR dataset, two ambiguous EPR datasets, and four uncertain datasets taken from sequence evolution data. MELD gives excellent structures, indicating its promise for experimental biomolecule structure determination where only semireliable data are available.


Assuntos
Modelos Moleculares , Biologia Molecular/métodos , Proteínas/química , Teorema de Bayes , Conformação Proteica
13.
J Chem Phys ; 143(24): 243143, 2015 Dec 28.
Artigo em Inglês | MEDLINE | ID: mdl-26723628

RESUMO

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.


Assuntos
Simulação de Dinâmica Molecular , Proteínas/química , Termodinâmica , Ressonância Magnética Nuclear Biomolecular , Conformação Proteica
14.
Proteins ; 82(10): 2671-80, 2014 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-24975328

RESUMO

A large number of methods generate conformational ensembles of biomolecules. Often one structure is selected to be representative of the whole ensemble, usually by clustering and selecting the structure closest to the center of the most populated cluster. We find that this structure is not necessarily the best representation of the cluster and present here two computationally inexpensive averaging protocols that can systematically provide better representations of the system, which can be more directly compared with structures from X-ray crystallography. In practice, systematic errors in the generated conformational ensembles appear to limit the maximum improvement of averaging methods.


Assuntos
Modelos Moleculares , Complexos Multiproteicos/química , Proteínas/química , Animais , Análise por Conglomerados , Cristalografia por Raios X , Bases de Dados de Proteínas , Transferência de Energia , Entropia , Humanos , Internet , Simulação de Dinâmica Molecular , Complexos Multiproteicos/metabolismo , Dinâmica não Linear , Distribuição Normal , Conformação Proteica , Domínios e Motivos de Interação entre Proteínas , Multimerização Proteica , Proteínas/metabolismo , Reprodutibilidade dos Testes , Software , Estatística como Assunto
15.
J Phys Chem B ; 118(24): 6597-603, 2014 Jun 19.
Artigo em Inglês | MEDLINE | ID: mdl-24898871

RESUMO

Extracting kinetic models from single molecule data is an important route to mechanistic insight in biophysics, chemistry, and biology. Data collected from force spectroscopy can probe discrete hops of a single molecule between different conformational states. Model extraction from such data is a challenging inverse problem because single molecule data are noisy and rich in structure. Standard modeling methods normally assume (i) a prespecified number of discrete states and (ii) that transitions between states are Markovian. The data set is then fit to this predetermined model to find a handful of rates describing the transitions between states. We show that it is unnecessary to assume either (i) or (ii) and focus our analysis on the zipping/unzipping transitions of an RNA hairpin. The key is in starting with a very broad class of non-Markov models in order to let the data guide us toward the best model from this very broad class. Our method suggests that there exists a folding intermediate for the P5ab RNA hairpin whose zipping/unzipping is monitored by force spectroscopy experiments. This intermediate would not have been resolved if a Markov model had been assumed from the onset. We compare the merits of our method with those of others.


Assuntos
RNA/química , Algoritmos , Modelos Teóricos , Conformação de Ácido Nucleico , Desnaturação de Ácido Nucleico
16.
Structure ; 22(1): 168-75, 2014 Jan 07.
Artigo em Inglês | MEDLINE | ID: mdl-24316402

RESUMO

Protein molecules often undergo conformational changes. In order to gain insights into the forces that drive such changes, it would be useful to have a method that computes the per-residue contributions to the conversion free energy. Here, we describe the "confine-convert-release" (CCR) method, which is applicable to large conformational changes. We show that CCR correctly predicts the stable states of several "chameleon" sequences that have previously been challenging for molecular simulations. CCR can often discriminate better from worse predictions of native protein models in critical assessment of protein structure prediction (CASP). We show how the total conversion free energies can be parsed into per-residue free-energy components. Such parsing gives insights into which amino acids are most responsible for given transformations. For example, here we are able to "reverse-engineer" the known design principles of the chameleon proteins. This opens up the possibility for systematic improvements in structure-prediction scoring functions, in the design of protein conformational switches, and in interpreting protein mechanisms at the amino-acid level.


Assuntos
Algoritmos , Aminoácidos/química , Modelos Moleculares , Oligopeptídeos/química , Proteínas/química , Simulação por Computador , Genes Sintéticos , Estabilidade Proteica , Estrutura Secundária de Proteína , Estrutura Terciária de Proteína , Termodinâmica
17.
Science ; 338(6110): 1042-6, 2012 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-23180855

RESUMO

The protein-folding problem was first posed about one half-century ago. The term refers to three broad questions: (i) What is the physical code by which an amino acid sequence dictates a protein's native structure? (ii) How can proteins fold so fast? (iii) Can we devise a computer algorithm to predict protein structures from their sequences? We review progress on these problems. In a few cases, computer simulations of the physical forces in chemically detailed models have now achieved the accurate folding of small proteins. We have learned that proteins fold rapidly because random thermal motions cause conformational changes leading energetically downhill toward the native structure, a principle that is captured in funnel-shaped energy landscapes. And thanks in part to the large Protein Data Bank of known structures, predicting protein structures is now far more successful than was thought possible in the early days. What began as three questions of basic science one half-century ago has now grown into the full-fledged research field of protein physical science.


Assuntos
Conformação Proteica , Dobramento de Proteína , Proteínas/química , Sequência de Aminoácidos , Caspase 9/química , Simulação por Computador , Modelos Químicos , Preparações Farmacêuticas/química
18.
J Chem Theory Comput ; 8(10): 3985-3991, 2012 Oct 09.
Artigo em Inglês | MEDLINE | ID: mdl-25530735

RESUMO

It is often valuable to compare protein structures to determine how similar they are. Structure comparison methods such as RMSD and GDT-TS are based solely on fixed geometry and do not take into account the intrinsic flexibility or energy landscape of the protein. We propose a method, which we call FlexE, that is based on a simple elastic network model and uses the deformation energy as measure of the similarity between two structures. FlexE can distinguish biologically relevant conformational changes from random changes, while existing geometry-based methods cannot. Additionally, FlexE incorporates the concept of thermal energy, which provides a rational way to determine when two models are "the same". FlexE provides a unique measure of the similarity between protein structures that is complementary to existing methods.

19.
Proteins ; 79 Suppl 10: 74-90, 2011.
Artigo em Inglês | MEDLINE | ID: mdl-22069034

RESUMO

We assess performance in the structure refinement category in CASP9. Two years after CASP8, the performance of the best groups has not improved. There are few groups that improve any of our assessment scores with statistical significance. Some predictors, however, are able to consistently improve the physicality of the models. Although we cannot identify any clear bottleneck in improving refinement, several points arise: (1) The refinement portion of CASP has too few targets to make many statistically meaningful conclusions. (2) Predictors are usually very conservative, limiting the possibility of large improvements in models. (3) No group is actually able to correctly rank their five submissions-indicating that potentially better models may be discarded. (4) Different sampling strategies work better for different refinement problems; there is no single strategy that works on all targets. In general, conservative strategies do better, while the greatest improvements come from more adventurous sampling-at the cost of consistency. Comparison with experimental data reveals aspects not captured by comparison to a single structure. In particular, we show that improvement in backbone geometry does not always mean better agreement with experimental data. Finally, we demonstrate that even given the current challenges facing refinement, the refined models are useful for solving the crystallographic phase problem through molecular replacement. Proteins 2011;. © 2011 Wiley-Liss, Inc.


Assuntos
Biologia Computacional/métodos , Modelos Moleculares , Proteínas/química , Cristalografia por Raios X , Ressonância Magnética Nuclear Biomolecular , Conformação Proteica , Software
20.
Trends Biochem Sci ; 36(12): 653-62, 2011 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-21930386

RESUMO

The partitioning of amino acid sidechains into the membrane is a key aspect of membrane protein folding. However, lipid bilayers exhibit rapidly changing physicochemical properties over their nanometer-scale thickness, which complicates understanding the thermodynamics and microscopic details of membrane partitioning. Recent data from diverse approaches, including protein insertion by the Sec translocon, folding of a small beta-barrel membrane protein and computer simulations of the exact distribution of a variety of small molecules and peptides, have joined older hydrophobicity scales for membrane protein prediction. We examine the correlations among the scales and find that they are remarkably correlated even though there are large differences in magnitude. We discuss the implications of these scales for understanding membrane protein structure and function.


Assuntos
Interações Hidrofóbicas e Hidrofílicas , Lipídeos/química , Proteínas de Membrana/química , Humanos , Termodinâmica
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