The Bio3D packages for structural bioinformatics.

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D-eddm package supports both experimental and theoretical simulation-generated structures, is integrated with other methods for dissecting sequence-structure-function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/.

Author Correction: A structural model for microtubule minus-end recognition and protection by CAMSAP proteins.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comparative Protein Structure Analysis with Bio3D-Web.

Bio3D-web is an online application for the interactive analysis of sequence-structure-dynamics relationships in user-defined protein structure sets. Major functionality includes structure database searching, sequence and structure conservation assessment, inter-conformer relationship mapping and clustering with principal component analysis (PCA), and flexibility prediction and comparison with ensemble normal mode analysis (eNMA). Collectively these methods allow users to start with a single sequence or structure and characterize the structural, conformational, and internal dynamic properties of homologous proteins for which there are high-resolution structures available. Functionality is also provided for the generation of custom PDF, Word, and HTML analysis reports detailing all user-specified analysis settings and corresponding results. Bio3D-web is available at http://thegrantlab.org/bio3d/webapps , as a Docker image https://hub.docker.com/r/bio3d/bio3d-web/ , or downloadable source code https://bitbucket.org/Grantlab/bio3d-web .

Neck linker docking is critical for Kinesin-1 force generation in cells but at a cost to motor speed and processivity.

Kinesin force generation involves ATP-induced docking of the neck linker (NL) along the motor core. However, the roles of the proposed steps of NL docking, cover-neck bundle (CNB) and asparagine latch (N-latch) formation, during force generation are unclear. Furthermore, the necessity of NL docking for transport of membrane-bound cargo in cells has not been tested. We generated kinesin-1 motors impaired in CNB and/or N-latch formation based on molecular dynamics simulations. The mutant motors displayed reduced force output and inability to stall in optical trap assays but exhibited increased speeds, run lengths, and landing rates under unloaded conditions. NL docking thus enhances force production but at a cost to speed and processivity. In cells, teams of mutant motors were hindered in their ability to drive transport of Golgi elements (high-load cargo) but not peroxisomes (low-load cargo). These results demonstrate that the NL serves as a mechanical element for kinesin-1 transport under physiological conditions.

Comparative structural dynamic analysis of GTPases.

GTPases regulate a multitude of essential cellular processes ranging from movement and division to differentiation and neuronal activity. These ubiquitous enzymes operate by hydrolyzing GTP to GDP with associated conformational changes that modulate affinity for family-specific binding partners. There are three major GTPase superfamilies: Ras-like GTPases, heterotrimeric G proteins and protein-synthesizing GTPases. Although they contain similar nucleotide-binding sites, the detailed mechanisms by which these structurally and functionally diverse superfamilies operate remain unclear. Here we compare and contrast the structural dynamic mechanisms of each superfamily using extensive molecular dynamics (MD) simulations and subsequent network analysis approaches. In particular, dissection of the cross-correlations of atomic displacements in both the GTP and GDP-bound states of Ras, transducin and elongation factor EF-Tu reveals analogous dynamic features. This includes similar dynamic communities and subdomain structures (termed lobes). For all three proteins the GTP-bound state has stronger couplings between equivalent lobes. Network analysis further identifies common and family-specific residues mediating the state-specific coupling of distal functional sites. Mutational simulations demonstrate how disrupting these couplings leads to distal dynamic effects at the nucleotide-binding site of each family. Collectively our studies extend current understanding of GTPase allosteric mechanisms and highlight previously unappreciated similarities across functionally diverse families.

A posttranslational modification of the mitotic kinesin Eg5 that enhances its mechanochemical coupling and alters its mitotic function.

Numerous posttranslational modifications have been described in kinesins, but their consequences on motor mechanics are largely unknown. We investigated one of these-acetylation of lysine 146 in Eg5-by creating an acetylation mimetic lysine to glutamine substitution (K146Q). Lysine 146 is located in the α2 helix of the motor domain, where it makes an ionic bond with aspartate 91 on the neighboring α1 helix. Molecular dynamics simulations predict that disrupting this bond enhances catalytic site-neck linker coupling. We tested this using structural kinetics and single-molecule mechanics and found that the K146Q mutation increases motor performance under load and coupling of the neck linker to catalytic site. These changes convert Eg5 from a motor that dissociates from the microtubule at low load into one that is more tightly coupled and dissociation resistant-features shared by kinesin 1. These features combined with the increased propensity to stall predict that the K146Q Eg5 acetylation mimetic should act in the cell as a "brake" that slows spindle pole separation, and we have confirmed this by expressing this modified motor in mitotically active cells. Thus, our results illustrate how a posttranslational modification of a kinesin can be used to fine tune motor behavior to meet specific physiological needs.

Altered chemomechanical coupling causes impaired motility of the kinesin-4 motors KIF27 and KIF7.

Kinesin-4 motors play important roles in cell division, microtubule organization, and signaling. Understanding how motors perform their functions requires an understanding of their mechanochemical and motility properties. We demonstrate that KIF27 can influence microtubule dynamics, suggesting a conserved function in microtubule organization across the kinesin-4 family. However, kinesin-4 motors display dramatically different motility characteristics: KIF4 and KIF21 motors are fast and processive, KIF7 and its Drosophila melanogaster homologue Costal2 (Cos2) are immotile, and KIF27 is slow and processive. Neither KIF7 nor KIF27 can cooperate for fast processive transport when working in teams. The mechanistic basis of immotile KIF7 behavior arises from an inability to release adenosine diphosphate in response to microtubule binding, whereas slow processive KIF27 behavior arises from a slow adenosine triphosphatase rate and a high affinity for both adenosine triphosphate and microtubules. We suggest that evolutionarily selected sequence differences enable immotile KIF7 and Cos2 motors to function not as transporters but as microtubule-based tethers of signaling complexes.

A structural model for microtubule minus-end recognition and protection by CAMSAP proteins.

CAMSAP and Patronin family members regulate microtubule minus-end stability and localization and thus organize noncentrosomal microtubule networks, which are essential for cell division, polarization and differentiation. Here, we found that the CAMSAP C-terminal CKK domain is widely present among eukaryotes and autonomously recognizes microtubule minus ends. Through a combination of structural approaches, we uncovered how mammalian CKK binds between two tubulin dimers at the interprotofilament interface on the outer microtubule surface. In vitro reconstitution assays combined with high-resolution fluorescence microscopy and cryo-electron tomography suggested that CKK preferentially associates with the transition zone between curved protofilaments and the regular microtubule lattice. We propose that minus-end-specific features of the interprotofilament interface at this site serve as the basis for CKK's minus-end preference. The steric clash between microtubule-bound CKK and kinesin motors explains how CKK protects microtubule minus ends against kinesin-13-induced depolymerization and thus controls the stability of free microtubule minus ends.

Navigating the conformational landscape of G protein-coupled receptor kinases during allosteric activation.

G protein-coupled receptors (GPCRs) are essential for transferring extracellular signals into carefully choreographed intracellular responses controlling diverse aspects of cell physiology. The duration of GPCR-mediated signaling is primarily regulated via GPCR kinase (GRK)-mediated phosphorylation of activated receptors. Although many GRK structures have been reported, the mechanisms underlying GRK activation are not well-understood, in part because it is unknown how these structures map to the conformational landscape available to this enzyme family. Unlike most other AGC kinases, GRKs rely on their interaction with GPCRs for activation and not phosphorylation. Here, we used principal component analysis of available GRK and protein kinase A crystal structures to identify their dominant domain motions and to provide a framework that helps evaluate how close each GRK structure is to being a catalytically competent state. Our results indicated that disruption of an interface formed between the large lobe of the kinase domain and the regulator of G protein signaling homology domain (RHD) is highly correlated with establishment of the active conformation. By introducing point mutations in the GRK5 RHD-kinase domain interface, we show with both in silico and in vitro experiments that perturbation of this interface leads to higher phosphorylation activity. Navigation of the conformational landscape defined by this bioinformatics-based study is likely common to all GPCR-activated GRKs.

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 for: (1) The identification of related protein structure sets to user specified thresholds of similarity; (2) Their multiple alignment and structure superposition; (3) Sequence and structure conservation analysis; (4) Inter-conformer relationship mapping with principal component analysis, and (5) comparison of predicted internal dynamics via ensemble normal mode analysis. This integrated functionality provides a complete online workflow for investigating sequence-structure-dynamic relationships within protein families and superfamilies.

Structural and Molecular Mechanisms of Cytokine-Mediated Endocrine Resistance in Human Breast Cancer Cells.

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 IKKß 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 IKKß signaling, suggesting a mechanism through which the tumor microenvironment controls tumor progression and endocrine resistance.

Systems Structural Biology Analysis of Ligand Effects on ERα Predicts Cellular Response to Environmental Estrogens and Anti-hormone Therapies.

Environmental estrogens and anti-hormone therapies for breast cancer have diverse tissue- and signaling-pathway-selective outcomes, but how estrogen receptor alpha (ERα) mediates this phenotypic diversity is poorly understood. We implemented a statistical approach to allow unbiased, parallel analyses of multiple crystal structures, and identified subtle perturbations of ERα structure by different synthetic and environmental estrogens. Many of these perturbations were in the sub-Å range, within the noise of the individual structures, but contributed significantly to the activities of synthetic and environmental estrogens. Combining structural perturbation data from many structures with quantitative cellular activity profiles of the ligands enabled identification of structural rules for ligand-specific allosteric signaling-predicting activity from structure. This approach provides a framework for understanding the diverse effects of environmental estrogens and for guiding iterative medicinal chemistry efforts to generate improved breast cancer therapies, an approach that can be applied to understanding other ligand-regulated allosteric signaling pathways.

Computational and biochemical characterization of two partially overlapping interfaces and multiple weak-affinity K-Ras dimers.

Recent studies found that membrane-bound K-Ras dimers are important for biological function. However, the structure and thermodynamic stability of these complexes remained unknown because they are hard to probe by conventional approaches. Combining data from a wide range of computational and experimental approaches, here we describe the structure, dynamics, energetics and mechanism of assembly of multiple K-Ras dimers. Utilizing a range of techniques for the detection of reactive surfaces, protein-protein docking and molecular simulations, we found that two largely polar and partially overlapping surfaces underlie the formation of multiple K-Ras dimers. For validation we used mutagenesis, electron microscopy and biochemical assays under non-denaturing conditions. We show that partial disruption of a predicted interface through charge reversal mutation of apposed residues reduces oligomerization while introduction of cysteines at these positions enhanced dimerization likely through the formation of an intermolecular disulfide bond. Free energy calculations indicated that K-Ras dimerization involves direct but weak protein-protein interactions in solution, consistent with the notion that dimerization is facilitated by membrane binding. Taken together, our atomically detailed analyses provide unique mechanistic insights into K-Ras dimer formation and membrane organization as well as the conformational fluctuations and equilibrium thermodynamics underlying these processes.

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

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. AVAILABILITY: Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no.

Rapid Characterization of Allosteric Networks with Ensemble Normal Mode Analysis.

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.

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

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.

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

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.

Enrichment of druggable conformations from apo protein structures using cosolvent-accelerated molecular dynamics.

Here we describe the development of an improved workflow for utilizing experimental and simulated protein conformations in the structure-based design of inhibitors for anti-apoptotic Bcl-2 family proteins. Traditional structure-based approaches on similar targets are often constrained by the sparsity of available structures and difficulties in finding lead compounds that dock against flat, flexible protein-protein interaction surfaces. By employing computational docking of known small molecule inhibitors, we have demonstrated that structural ensembles derived from either accelerated MD (aMD) or MD in the presence of an organic cosolvent generally give better scores than those assessed from analogous conventional MD. Furthermore, conformations obtained from combined cosolvent aMD simulations started with the apo-Bcl-xL structure yielded better average and minimum docking scores for known binders than an ensemble of 72 experimental apo- and ligand-bound Bcl-xL structures. A detailed analysis of the simulated conformations indicates that the aMD effectively enhanced conformational sampling of the flexible helices flanking the main Bcl-xL binding groove, permitting the cosolvent acting as small ligands to penetrate more deeply into the binding pocket and shape ligand-bound conformations not evident in conventional simulations. We believe this approach could be useful for identifying inhibitors against other protein-protein interaction systems involving highly flexible binding sites, particularly for targets with less accumulated structural data.

Integrating protein structural dynamics and evolutionary analysis with Bio3D.

BACKGROUND: 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. RESULTS: Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. CONCLUSIONS: The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

Kinesin-5 allosteric inhibitors uncouple the dynamics of nucleotide, microtubule, and neck-linker binding sites.

Kinesin motor domains couple cycles of ATP hydrolysis to cycles of microtubule binding and conformational changes that result in directional force and movement on microtubules. The general principles of this mechanochemical coupling have been established; however, fundamental atomistic details of the underlying allosteric mechanisms remain unknown. This lack of knowledge hampers the development of new inhibitors and limits our understanding of how disease-associated mutations in distal sites can interfere with the fidelity of motor domain function. Here, we combine unbiased molecular-dynamics simulations, bioinformatics analysis, and mutational studies to elucidate the structural dynamic effects of nucleotide turnover and allosteric inhibition of the kinesin-5 motor. Multiple replica simulations of ATP-, ADP-, and inhibitor-bound states together with network analysis of correlated motions were used to create a dynamic protein structure network depicting the internal dynamic coordination of functional regions in each state. This analysis revealed the intervening residues involved in the dynamic coupling of nucleotide, microtubule, neck-linker, and inhibitor binding sites. The regions identified include the nucleotide binding switch regions, loop 5, loop 7, ?4-?5-loop 13, ?1, and ?4-?6-?7. Also evident were nucleotide- and inhibitor-dependent shifts in the dynamic coupling paths linking functional sites. In particular, inhibitor binding to the loop 5 region affected ?-sheet residues and ?1, leading to a dynamic decoupling of nucleotide, microtubule, and neck-linker binding sites. Additional analyses of point mutations, including P131 (loop 5), Q78/I79 (?1), E166 (loop 7), and K272/I273 (?7) G325/G326 (loop 13), support their predicted role in mediating the dynamic coupling of distal functional surfaces. Collectively, our results and approach, which we make freely available to the community, provide a framework for explaining how binding events and point mutations can alter dynamic couplings that are critical for kinesin motor domain function.