investigating-protein-sequence-structure-dynamics-relationships-with

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

We demonstrate the usage of Bio3D-web for the interactive analysis of biomolecular structure data. The Bio3D-web application provides online functionality ...

University of Michigan Medical School

Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful information relevant to sequence-structure relationship. However, at present, the prediction accuracy of pure HMM-type methods is much lower than that of machine learning-based methods such as neural networks (NN) or support vector machines (SVM).

A dynamic Bayesian network approach to protein secondary structure prediction.

A "key-residue" hypothesis that a few residues' characteristics contain the essential dynamics of the whole protein is proposed for the study of side-chain relaxation near native states. Molecular dynamics simulation is performed on the folding of Trp-cage, and four key residues are discovered and shown to be highly sensitive to the change of state of the protein away from the native state. Order parameters that characterize the geometrical properties of key residues are shown to form valuable phase plane on which one distinguishes different reaction pathways. Furthermore, one of the key residues, Trp6, is observed to display two reconfiguration processes, in which one is induced by an unconstrained torsion of the side-chain of Trp6, with a rate faster by almost an order of magnitude than the other one described by Kussell's model. The faster process seems to occur more frequently in our simulation and thus represent a significant mechanism in folding dynamics.

Key residue-dominated protein folding dynamics.

Wild type and mutant alpha-lytic protease, differing by only one amino acid, have distinct specificities. Previous studies have shown that motion patterns of the binding pocket play an important role. However, it is still unclear how these differences are generated from a single amino acid mutation. Based on comparative molecular dynamics simulations using explicit and implicit solvent models, we studied the dynamic properties of both protein and water. The explicit solvent simulations showed specificity related differences in the energy landscapes and the power spectra between the two enzymes, whereas implicit solvent simulations did not. Moreover, the explicit solvent simulations demonstrated obvious distinctions in dynamic behaviors of water, such as their residence behaviors and hydrogen bonding. These results suggest that the interplay between water and enzyme is essential in determining the substrate specificity, and the detail knowledge of such interplay can greatly improve our understanding of bio-molecules.

Water-protein interplay reveals the specificity of alpha-lytic protease.

A computational method independent of experimental protein structure information is proposed to recognize key residues in protein folding, from the study of hydration water dynamics. Based on all-atom molecular dynamics simulation, two key residues are recognized with distinct water dynamical behavior in a folding process of the Trp-cage protein. The identified key residues are shown to play an essential role in both 3D structure and hydrophobic-induced collapse. With observations on hydration water dynamics around key residues, a dynamical pathway of folding can be interpreted.

Water dynamics clue to key residues in protein folding.

Multidrug resistance is a serious problem in current chemotherapy. The efflux system largely responsible for resistance in Escherichia coli contains the drug transporter, AcrB. The structures of AcrB were solved in 2002 as the symmetric homo-trimer, and then in 2006 as the asymmetric homo-trimer. The latter suggested a functionally rotating mechanism. Here, by molecular simulations of the AcrB porter domain, we uncovered allosteric coupling and the drug export mechanism in the AcrB trimer. Allosteric coupling stabilized the asymmetric structure with one drug molecule bound, which validated the modelling. Drug dissociation caused a conformational change and stabilized the symmetric structure, providing a unified view of the structures reported in 2002 and 2006. A dynamic study suggested that, among the three potential driving processes, only protonation of the drug-bound protomer can drive the functional rotation and simultaneously export the drug.

Drug export and allosteric coupling in a multidrug transporter revealed by molecular simulations.

Multidrug resistance has been a critical issue in current chemotherapy. In Escherichia coli , a major efflux pump responsible for the multidrug resistance contains a transporter AcrB. Crystallographic studies and mutational assays of AcrB provided much of structural and overall functional insights, which led to the functionally rotating mechanism. However, the drug uptake pathways are somewhat controversial because at least two possible pathways, the vestibule and the cleft paths, were suggested. Here, combining molecular simulations and site-directed mutagenesis experiments, we addressed the uptake mechanism finding that the drug uptake pathways can be significantly different depending on the properties of drugs. First, in the computational free energy analysis of drug movements along AcrB tunnels, we found a ligand-dependent drug uptake mechanism. With the same molecular sizes, drugs that are both strongly hydrophobic and lipophilic were preferentially taken in via the vestibule path, while other drugs favored the cleft path. Second, direct simulations realized totally about 3500 events of drug uptake by AcrB for a broad range of drug property. These simulations confirmed the ligand-dependent drug uptake and further suggested that a smaller drug favors the vestibule path, while a larger one is taken in via the cleft path. Moreover, the direct simulations identified an alternative uptake path which is not visible in the crystal structure. Third, site-directed mutagenesis of AcrB in E. coli verified that mutations of residues located along the newly identified path significantly reduced the efflux efficiency, supporting its relevance in in vivo function.

Drug uptake pathways of multidrug transporter AcrB studied by molecular simulations and site-directed mutagenesis experiments.

Heterotrimeric G proteins are conformational switches that turn on intracellular signaling cascades in response to the activation of G-protein-coupled receptors. Receptor activation by extracellular stimuli promotes a cycle of GTP binding and hydrolysis on the G protein α-subunit (Gα). Important conformational transitions occurring during this cycle have been characterized from extensive crystallographic studies of Gα. However, the link between the observed conformations and the mechanisms involved in G-protein activation and effector interaction remain unclear. Here we describe a comprehensive principal component analysis of available Gα crystallographic structures supplemented with extensive unbiased conventional and accelerated molecular dynamics simulations that together characterize the response of Gα to GTP binding and hydrolysis. Our studies reveal details of activating conformational changes as well as the intrinsic flexibility of the α-helical domain that includes a large-scale 60° domain opening under nucleotide-free conditions. This result is consistent with the recently reported open crystal structure of Gs, the stimulatory G protein for adenylyl cyclase, in complex with the α2 adrenergic receptor. Sets of unique interactions potentially important for the conformational transition are also identified. Moreover simulations reveal nucleotide-dependent dynamical couplings of distal regions and residues potentially important for the allosteric link between functional sites.

Domain-opening and dynamic coupling in the α-subunit of heterotrimeric G proteins.

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.

Integrating protein structural dynamics and evolutionary analysis with Bio3D.

Kinesin superfamily members play important roles in many diverse cellular processes, including cell motility, cell division, intracellular transport, and regulation of the microtubule cytoskeleton. How the properties of the family-defining motor domain of distinct kinesins are tailored to their different cellular roles remains largely unknown. Here, we employed molecular-dynamics simulations coupled with energetic calculations to infer the family-specific interactions of kinesin-1 and kinesin-3 motor domains with microtubules in different nucleotide states. We then used experimental mutagenesis and single-molecule motility assays to further assess the predicted residue-wise determinants of distinct kinesin-microtubule binding properties. Collectively, our results identify residues in the L8, L11, and α6 regions that contribute to family-specific microtubule interactions and whose mutation affects motor-microtubule complex stability and processive motility (the ability of an individual motor to take multiple steps along its microtubule filament). In particular, substitutions of prominent kinesin-3 residues with those found in kinesin-1, namely, R167S/H171D, K266D, and R346M, were found to decrease kinesin-3 processivity 10-fold and thus approach kinesin-1 levels.

Mapping the Processivity Determinants of the Kinesin-3 Motor Domain.

For simulating proteins at work in millisecond time scale or longer, we develop a coarse-grained (CG) molecular dynamics (MD) method and software, CafeMol. At the resolution of one-particle-per-residue, CafeMol equips four structure-based protein models: (1) the off-lattice Go model, (2) the atomic interaction based CG model for native state and folding dynamics, (3) the multiple-basin model for conformational change dynamics, and (4) the elastic network model for quasiharmonic fluctuations around the native structure. Ligands can be treated either explicitly or implicitly. For mimicking functional motions of proteins driven by some external force, CafeMol has various and flexible means to "switch" the energy functions that induce active motions of the proteins. CafeMol can do parallel computation with modest sized PC clusters. We describe CafeMol methods and illustrate it with several examples, such as rotary motions of F1-ATPase and drug exports from a transporter. The CafeMol source code is available at www.cafemol.org .

CafeMol: A Coarse-Grained Biomolecular Simulator for Simulating Proteins at Work.

G protein α subunits cycle between active and inactive conformations to regulate a multitude of intracellular signaling cascades. Important structural transitions occurring during this cycle have been characterized from extensive crystallographic studies. However, the link between observed conformations and the allosteric regulation of binding events at distal sites critical for signaling through G proteins remain unclear. Here we describe molecular dynamics simulations, bioinformatics analysis, and experimental mutagenesis that identifies residues involved in mediating the allosteric coupling of receptor, nucleotide, and helical domain interfaces of Gαi. Most notably, we predict and characterize novel allosteric decoupling mutants, which display enhanced helical domain opening, increased rates of nucleotide exchange, and constitutive activity in the absence of receptor activation. Collectively, our results provide a framework for explaining how binding events and mutations can alter internal dynamic couplings critical for G protein function.

Dynamic Coupling and Allosteric Networks in the α Subunit of Heterotrimeric G Proteins.

Allosteric regulation is a primary means of controlling protein function. By definition, allostery involves the propagation of structural dynamic changes between distal protein sites that yields a functional change. Gaining improved knowledge of these fundamental mechanisms is important for understanding many biomolecular processes and for guiding protein engineering and drug design efforts. In this work we compare and contrast a range of normal mode analysis (NMA) approaches together with network analysis for the prediction of structural dynamics and allosteric sites. Application to heterotrimeric G proteins, hemoglobin, and caspase 7 indicates that atomistic elastic network models provide improved predictions of experimental allosteric mutation sites. Results for G proteins also display an improved consistency with those derived from more computationally demanding MD simulations. Application of this approach across available experimental structures for a given protein family in a unified manner, that we refer to as ensemble NMA, yields the best overall predictive performance. We propose that this atomistic ensemble NMA approach represents an efficient and powerful tool for guiding the exploration of coupled motions and allosteric mechanisms in cases where multiple structures are available and where MD may prove prohibitively expensive.

Rapid Characterization of Allosteric Networks with Ensemble Normal Mode Analysis.

Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics.

Online interactive analysis of protein structure ensembles with Bio3D-web.

Human breast cancers that exhibit high proportions of immune cells and elevated levels of pro-inflammatory cytokines predict poor prognosis. Here, we demonstrate that treatment of human MCF-7 breast cancer cells with pro-inflammatory cytokines results in ERα-dependent activation of gene expression and proliferation, in the absence of ligand or presence of 4OH-tamoxifen (TOT). Cytokine activation of ERα and endocrine resistance is dependent on phosphorylation of ERα at S305 in the hinge domain. Phosphorylation of S305 by IKKβ establishes an ERα cistrome that substantially overlaps with the estradiol (E2)-dependent ERα cistrome. Structural analyses suggest that S305-P forms a charge-linked bridge with the C-terminal F domain of ERα that enables inter-domain communication and constitutive activity from the N-terminal coactivator-binding site, revealing the structural basis of endocrine resistance. ERα therefore functions as a transcriptional effector of cytokine-induced IKKβ signaling, suggesting a mechanism through which the tumor microenvironment controls tumor progression and endocrine resistance.

Article	Year
A dynamic Bayesian network approach to protein secondary structure prediction. BMC bioinformatics\| PubMed ID: 18218144	2008
Key residue-dominated protein folding dynamics. Biochemical and biophysical research communications\| PubMed ID: 18549806	2008
Water-protein interplay reveals the specificity of alpha-lytic protease. Biochemical and biophysical research communications\| PubMed ID: 19450547	2009
Water dynamics clue to key residues in protein folding. Biochemical and biophysical research communications\| PubMed ID: 20059982	2010
Drug export and allosteric coupling in a multidrug transporter revealed by molecular simulations. Nature communications\| PubMed ID: 21081915	2010
Drug uptake pathways of multidrug transporter AcrB studied by molecular simulations and site-directed mutagenesis experiments. Journal of the American Chemical Society\| PubMed ID: 23627437	2013
Domain-opening and dynamic coupling in the α-subunit of heterotrimeric G proteins. Biophysical journal\| PubMed ID: 23870276	2013
Integrating protein structural dynamics and evolutionary analysis with Bio3D. BMC bioinformatics\| PubMed ID: 25491031	2014
Mapping the Processivity Determinants of the Kinesin-3 Motor Domain. Biophysical journal\| PubMed ID: 26488644	2015
CafeMol: A Coarse-Grained Biomolecular Simulator for Simulating Proteins at Work. Journal of chemical theory and computation\| PubMed ID: 26596457	2011
Dynamic Coupling and Allosteric Networks in the α Subunit of Heterotrimeric G Proteins. The Journal of biological chemistry\| PubMed ID: 26703464	2016
Rapid Characterization of Allosteric Networks with Ensemble Normal Mode Analysis. The journal of physical chemistry. B\| PubMed ID: 27056373	2016
Online interactive analysis of protein structure ensembles with Bio3D-web. Bioinformatics (Oxford, England)\| PubMed ID: 27423893	2016
Structural and Molecular Mechanisms of Cytokine-Mediated Endocrine Resistance in Human Breast Cancer Cells. Molecular cell\| PubMed ID: 28306507	2017

Xin-Qiu Yao

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