Native structure-based modeling and simulation of biomolecular systems per mouse click

Background Molecular dynamics (MD) simulations provide valuable insight into biomolecular systems at the atomic level. Notwithstanding the ever-increasing power of high performance computers current MD simulations face several challenges: the fastest atomic movements require time steps of a few femtoseconds which are small compared to biomolecular relevant timescales of milliseconds or even seconds for large conformational motions. At the same time, scalability to a large number of cores is limited mostly due to long-range interactions. An appealing alternative to atomic-level simulations is coarse-graining the resolution of the system or reducing the complexity of the Hamiltonian to improve sampling while decreasing computational costs. Native structure-based models, also called Gō-type models, are based on energy landscape theory and the principle of minimal frustration. They have been tremendously successful in explaining fundamental questions of, e.g., protein folding, RNA folding or protein function. At the same time, they are computationally sufficiently inexpensive to run complex simulations on smaller computing systems or even commodity hardware. Still, their setup and evaluation is quite complex even though sophisticated software packages support their realization. Results Here, we establish an efficient infrastructure for native structure-based models to support the community and enable high-throughput simulations on remote computing resources via GridBeans and UNICORE middleware. This infrastructure organizes the setup of such simulations resulting in increased comparability of simulation results. At the same time, complete workflows for advanced simulation protocols can be established and managed on remote resources by a graphical interface which increases reusability of protocols and additionally lowers the entry barrier into such simulations for, e.g., experimental scientists who want to compare their results against simulations. We demonstrate the power of this approach by illustrating it for protein folding simulations for a range of proteins. Conclusions We present software enhancing the entire workflow for native structure-based simulations including exception-handling and evaluations. Extending the capability and improving the accessibility of existing simulation packages the software goes beyond the state of the art in the domain of biomolecular simulations. Thus we expect that it will stimulate more individuals from the community to employ more confidently modeling in their research

The Trimeric Major Capsid Protein of Mavirus is stabilized by its Interlocked N-termini Enabling Core Flexibility for Capsid Assembly

Icosahedral viral capsids assemble with high fidelity from a large number of identical buildings blocks. The mechanisms that enable individual capsid proteins to form stable oligomeric units (capsomers) while affording structural adaptability required for further assembly into capsids are mostly unknown. Understanding these mechanisms requires knowledge of the capsomers’ dynamics, especially for viruses where no additional helper proteins are needed during capsid assembly like for the Mavirus virophage that despite its complexity (triangulation number T = 27) can assemble from its major capsid protein (MCP) alone. This protein forms the basic building block of the capsid namely a trimer (MCP$_{3}$) of double-jelly roll protomers with highly intertwined N-terminal arms of each protomer wrapping around the other two at the base of the capsomer, secured by a clasp that is formed by part of the C-terminus. Probing the dynamics of the capsomer with HDX mass spectrometry we observed differences in conformational flexibility between functional elements of the MCP trimer. While the N-terminal arm and clasp regions show above average deuterium incorporation, the two jelly-roll units in each protomer also differ in their structural plasticity, which might be needed for efficient assembly. Assessing the role of the N-terminal arm in maintaining capsomer stability showed that its detachment is required for capsomer dissociation, constituting a barrier towards capsomer monomerisation. Surprisingly, capsomer dissociation was irreversible since it was followed by a global structural rearrangement of the protomers as indicated by computational studies showing a rearrangement of the N-terminus blocking part of the capsomer forming interface

Directed Evolution of Stabilized Peptides with Bacterial Display

Interactions between proteins govern cellular and the body’s states, including aberrant interactions found in diseases such as in cancers and infections. Small molecule drugs are not ideal in targeting these interactions as their size generally prevents efficient blocking of contacts over large surface areas. Antibodies and related biologics have seen clinical success in the past few decades and can block large surfaces but are typically limited to extracellular targets. Intermediate-size peptides have the potential to bridge this gap, with the ability to target large surface areas inside the cell. Peptide stapling, by chemically linking two or more amino acid residues, can confer affinity improvements, resistance to degradation, and better biological transport properties. As such, stapled peptides show promise as next-generation therapeutics. Unfortunately, existing methods to screen sequence and stapling locations suffer from numerous disadvantages including limited search space, lack of real-time monitoring of selections, and difficulty in incorporating the non-canonical amino acids used for amino acid stapling. In this dissertation, I describe my research on stapled peptide discovery with bacterial incorporation of non-canonical amino acids. To screen stapled peptides of the type desired, we incorporated azidohomoalanine (AHA) into surface displayed peptides, enabling an in situ ‘click’ chemistry reaction to bridge two turns of an alpha helical (i, i+7) amino acid library for directed evolution. Using the p53-MDM2 interaction as a model target, we developed peptides that block MDM2 degradation of the tumor suppressor protein p53, an interaction that is dysregulated in a sizeable fraction of cancers. We generated and displayed a stapled peptide library on the bacterial cell surface with fixed residues for stabilization and binding requirements, while randomizing the remaining amino acids. After multiple rounds of selection, clones were sequenced and characterized. The dissociation constants of the peptide-MDM2 interaction were measured on both the bacterial cell surface by flow cytometry and in solution by bio-layer interferometry. The highest affinity variant, named SPD-M6-V1 with sequence VCDFXCYWNDLXGY (dissociation constant = 1.8 nM; X = azidohomoalanine) was selected for structural characterization by NMR spectroscopy, revealing a bicyclic disulfide and double click-constrained peptide. Sequencing showed that peptides with two cysteines were highly enriched, further suggesting that the MDM2-binding conformation was enforced with a disulfide bond. In addition, SPD-M6-V1 was the most protease-resistant peptide from the library that we tested. Next, we stapled the displayed peptide library with chemically distinct linkers and screened each library separately. We performed deep sequencing to better understand the relationship between amino acid sequence and linker identity in contributing to high affinity MDM2 binding. We found that both linker-specific and linker-agnostic (i.e. MDM2-specific) mutations were enhanced. Finally, we developed a dual-channel, sequential labeling selection strategy to discriminate between high-display, low-affinity peptides and low-display, high-affinity peptides, two categories that would ordinarily overlap in a typical one-color screen in the absence of an independent display marker. In summary, this thesis develops the chemical tools to screen libraries of stabilized peptides on the bacterial cell surface and applies these techniques to select stabilized alpha helices that disrupt the p53-MDM2 interaction.PHDChemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163094/1/tejasn_1.pd

Stability and aggregation-prone conformations of an antibody fragment antigen-binding (Fab)

Antibody-based products have become the main drug class of approved biopharmaceuticals, with over 60 drugs on the market and many more in clinical development. However, many never reach the market because protein aggregates form during manufacturing and storage, which lower the efficacy of the product and may cause immune responses in patients. To date, very little is known about the structural conformers that initiate aggregation. Stability of the humanized fragment antigen-binding (Fab) A33 was first studied using molecular dynamic (MD) simulations under two stresses, low pH and high temperature. Results revealed different unfolding pathways, with CL domain partially unfolding at low pH, and CL and VH at high temperature. These conformational changes exposed different predicted aggregation-prone regions (APR), to suggest different aggregation mechanisms. Further salt bridge analysis provided insights into the ionizable residues likely to get protonated first. Mutational study with FoldX and Rosetta predicted that the constant domain interface can be stabilized further, backed by packing density calculations. To experimentally characterize the aggregation-prone conformers, solution structures of Fab A33 under different conditions of pH and salt concentration, were solved using small angle X-ray scattering (SAXS). SAXS revealed an expanded conformation at pH 5.5 and below, with an Rg increase of 2.2% to 4.1%, that correlated with accelerated aggregation. Scattering data were fitted using 45,000 structures obtained from the atomistic MD simulations under the same conditions, to locate the conformational change at low pH to the CL domain. The approach was then validated using intra-molecular single-molecule FRET with a dual-labelled Fab as an orthogonal detection method. The conformational changes were found to expose a predicted APR, which forms a mechanistic basis for subsequent aggregation. Overall, these findings provide a means by which aggregation-prone conformers can be determined experimentally, and thus potentially used to guide protein engineering, or ligand binding strategies, with the aim of stabilizing the protein against aggregation

KinImmerse: Macromolecular VR for NMR ensembles

<p>Abstract</p> <p>Background</p> <p>In molecular applications, virtual reality (VR) and immersive virtual environments have generally been used and valued for the visual and interactive experience – to enhance intuition and communicate excitement – rather than as part of the actual research process. In contrast, this work develops a software infrastructure for research use and illustrates such use on a specific case.</p> <p>Methods</p> <p>The Syzygy open-source toolkit for VR software was used to write the KinImmerse program, which translates the molecular capabilities of the kinemage graphics format into software for display and manipulation in the DiVE (Duke immersive Virtual Environment) or other VR system. KinImmerse is supported by the flexible display construction and editing features in the KiNG kinemage viewer and it implements new forms of user interaction in the DiVE.</p> <p>Results</p> <p>In addition to molecular visualizations and navigation, KinImmerse provides a set of research tools for manipulation, identification, co-centering of multiple models, free-form 3D annotation, and output of results. The molecular research test case analyzes the local neighborhood around an individual atom within an ensemble of nuclear magnetic resonance (NMR) models, enabling immersive visual comparison of the local conformation with the local NMR experimental data, including target curves for residual dipolar couplings (RDCs).</p> <p>Conclusion</p> <p>The promise of KinImmerse for production-level molecular research in the DiVE is shown by the locally co-centered RDC visualization developed there, which gave new insights now being pursued in wider data analysis.</p

Targeting Intrinsically Disordered Proteins through Dynamic Interactions

Intrinsically disordered proteins (IDPs) are over-represented in major disease pathways and have attracted significant interest in understanding if and how they may be targeted using small molecules for therapeutic purposes. While most existing studies have focused on extending the traditional structure-centric drug design strategies and emphasized exploring pre-existing structure features of IDPs for specific binding, several examples have also emerged to suggest that small molecules could achieve specificity in binding IDPs and affect their function through dynamic and transient interactions. These dynamic interactions can modulate the disordered conformational ensemble and often lead to modest compaction to shield functionally important interaction sites. Much work remains to be done on further elucidation of the molecular basis of the dynamic small molecule–IDP interaction and determining how it can be exploited for targeting IDPs in practice. These efforts will rely critically on an integrated experimental and computational framework for disordered protein ensemble characterization. In particular, exciting advances have been made in recent years in enhanced sampling techniques, Graphic Processing Unit (GPU)-computing, and protein force field optimization, which have now allowed rigorous physics-based atomistic simulations to generate reliable structure ensembles for nontrivial IDPs of modest sizes. Such de novo atomistic simulations will play crucial roles in exploring the exciting opportunity of targeting IDPs through dynamic interactions

Ceramides bind VDAC2 to trigger mitochondrial apoptosis

Ceramides draw wide attention as tumor suppressor lipids that act directly on mitochondria to trigger apoptotic cell death. However, molecular details of the underlying mechanism are largely unknown. Using a photoactivatable ceramide probe, we here identify the voltage-dependent anion channels VDAC1 and VDAC2 as mitochondrial ceramide binding proteins. Coarse-grain molecular dynamics simulations reveal that both channels harbor a ceramide binding site on one side of the barrel wall. This site includes a membrane-buried glutamate that mediates direct contact with the ceramide head group. Substitution or chemical modification of this residue abolishes photolabeling of both channels with the ceramide probe. Unlike VDAC1 removal, loss of VDAC2 or replacing its membrane-facing glutamate with glutamine renders human colon cancer cells largely resistant to ceramide-induced apoptosis. Collectively, our data support a role of VDAC2 as direct effector of ceramide-mediated cell death, providing a molecular framework for how ceramides exert their anti-neoplastic activity

Multiscale Simulations of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) lack stable secondary and/or tertiary structures under physiological conditions. The have now been recognized to play important roles in numerous biological processes, particularly cellular signaling and regulation. Mutation of IDPs are frequently associated with human diseases, such as cancers and neuron degenerative diseases. Therefore, it is important to understand the structure, dynamics, and interactions of IDPs, so as to establish the mechanistic basis of how intrinsic disorder mediates versatile functions and how such mechanisms may fail in human diseases. However, the heterogeneous structural ensembles of IDPs are not amenable to high resolution characterization solely through experimental measurements, and molecular modelling and simulation are required to study IDP structures, dynamics, and interactions at the atomistic levels. Here, we first applied the state-of-the-art explicit solvent atomistic simulations to an anti-apoptotic protein Bcl-xL and demonstrated how inherent structural disorder may provide a physical basis of protein regulated unfolding in signaling transduction. We have also constructed a series of efficient coarse-grained models to directly simulate the interactions between IDPs and unveiled how the preexisting structural elements accelerate binding of ACTR to NCBD by promoting efficient folding upon encounter. These studies shed important light on how IDPs perform functions in the cellular regulatory network, but also reveal the necessity of new sampling techniques for more efficient simulations of IDPs. We have thus developed a novel sampling technique, called multiscale enhanced sampling (MSES). MSES couples the atomistic model with coarse-grained ones, to accelerate the sampling of atomistic conformational space. Bias from coupling to a coarse-grained model can be removed using Hamiltonian replica exchange. To achieve the best possible efficiency of MSES simulations, we have developed a new hybrid resolution protein model that could capture the essential features of IDP structures, so as to generate local and long-range fluctuations that are largely consistent with those at the atomistic level. We have also developed an advanced replica exchange protocol, to allow the fast conformational transitions observed in the coupled conditions to be rapidly exchanged to the unbiased limit. Application of these strategies to characterize the structural ensembles of a few non-trivial IDPs shows that faster convergence rate can be achieved, demonstrating the great potential of MSES for atomistic simulations of larger and more complex IDPs