Jeffrey K. Weber

Markov State Models Provide Insights into Dynamic Modulation of Protein Function

Conspectus Protein function is inextricably linked to protein dynamics. As we move from a static structural picture to a dynamic ensemble view of protein structure and function, novel computational paradigms are required for observing and understanding conformational dynamics of proteins and its functional implications. In principle, molecular dynamics simulations can provide the time evolution of atomistic models of proteins, but the long time scales associated with functional dynamics make it difficult to observe rare dynamical transitions. The issue of extracting essential functional components of protein dynamics from noisy simulation data presents another set of challenges in obtaining an unbiased understanding of protein motions. Therefore, a methodology that provides a statistical framework for efficient sampling and a human-readable view of the key aspects of functional dynamics from data analysis is required. The Markov state model (MSM), which has recently become popular worldwide for studying protein dynamics, is an example of such a framework. In this Account, we review the use of Markov state models for efficient sampling of the hierarchy of time scales associated with protein dynamics, automatic identification of key conformational states, and the degrees of freedom associated with slow dynamical processes. Applications of MSMs for studying long time scale phenomena such as activation mechanisms of cellular signaling proteins has yielded novel insights into protein function. In particular, from MSMs built using large-scale simulations of GPCRs and kinases, we have shown that complex conformational changes in proteins can be described in terms of structural changes in key structural motifs or “molecular switches” within the protein, the transitions between functionally active and inactive states of proteins proceed via multiple pathways, and ligand or substrate binding modulates the flux through these pathways. Finally, MSMs also provide a theoretical toolbox for studying the effect of nonequilibrium perturbations on conformational dynamics. Considering that protein dynamics in vivo occur under nonequilibrium conditions, MSMs coupled with nonequilibrium statistical mechanics provide a way to connect cellular components to their functional environments. Nonequilibrium perturbations of protein folding MSMs reveal the presence of dynamically frozen glass-like states in their conformational landscape. These frozen states are also observed to be rich in β-sheets, which indicates their possible role in the nucleation of β-sheet rich aggregates such as those observed in amyloid-fibril formation. Finally, we describe how MSMs have been used to understand the dynamical behavior of intrinsically disordered proteins such as amyloid-β, human islet amyloid polypeptide, and p53. While certainly not a panacea for studying functional dynamics, MSMs provide a rigorous theoretical foundation for understanding complex entropically dominated processes and a convenient lens for viewing protein motions.

Reduced Cytotoxicity of Graphene Nanosheets Mediated by Blood-Protein Coating.

The advent and pending wide use of nanoscale materials urges a biosafety assessment and safe design of nanomaterials that demonstrate applicability to human medicine. In biological microenvironment, biomolecules will bind onto nanoparticles forming corona and endow nanoparticles new biological identity. Since blood-circulatory system will most likely be the first interaction organ exposed to these nanomaterials, a deep understanding of the basic interaction mechanisms between serum proteins and foreign nanoparticles may help to better clarify the potential risks of nanomaterials and provide guidance on safe design of nanomaterials. In this study, the adsorption of four high-abundance blood proteins onto the carbon-based nanomaterial graphene oxide (GO) and reduced GO (rGO) were investigated via experimental (AFM, florescence spectroscopy, SPR) and simulation-based (molecular dynamics) approaches. Among the proteins in question, we observe competitive binding to the GO surface that features a mélange of distinct packing modes. Our MD simulations reveal that the protein adsorption is mainly enthalpically driven through strong π-π stacking interactions between GO and aromatic protein residues, in addition to hydrophobic interactions. Overall, these results were in line with previous findings related to adsorption of serum proteins onto single-walled carbon nanotubes (SWCNTs), but GO exhibits a dramatic enhancement of adsorption capacity compared to this one-dimensional carbon form. Encouragingly, protein-coated GO resulted in a markedly less cytotoxicity than pristine and protein-coated SWCNTs, suggesting a useful role for this planar nanomaterial in biomedical applications.

A CI study of the classical and nonclassical structures of the vinyl cation and their optimum path for rearrangement

Ab initio calculations including configuration interaction (CI) are reported for the classical (linear) and the nonclassical (bridged) structures of the vinyl cation (C2H3+), and for the minimum energy path for the rearrangement from one to the other. A ’’double‐zeta plus polarization’’ one‐particle basis of contracted Gaussian functions was used to construct an n‐particle space for the CI calculation consisting of the ground state self‐ consistent field (SCF) configuration and all single and double excitations from it. Critical evaluation of the calculations leads to the chemical predictions that (i) the two structures have the same energy, to within ∼1–2 kcal/mole with probably the bridged structure more stable, (ii) that the minimum energy path for rearrangement keeps a planar configuration of the atomic nuclei, and (iii) that the barrier to rearrangement is low, less than ∼1–3 kcal/mole. The calculations include geometry optimization along the rearrangement path as well as the effects of electronic co...

Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy

HLA genotype affects response Immunotherapy works by activating the patients own immune system to fight cancer. For effective tumor killing, CD8+ T cells recognize tumor peptides presented by human leukocyte antigen class I (HLA-I) molecules. In humans, there are three major HLA-I genes (HLA-A, HLA-B, and HLA-C). Chowell et al. asked whether germline HLA-I genotype influences how T cells recognize tumor peptides and respond to checkpoint inhibitor immunotherapies (see the Perspective by Kvistborg and Yewdell). They examined more than 1500 patients and found that heterozygosity at HLA-I loci was associated with better survival than homozygosity for one or more HLA-I genes. Thus, specific HLA-I mutations could have implications for immune recognition and for the design of epitopes for cancer vaccines and immunotherapies. Science, this issue p. 582; see also p. 516 Human leukocyte antigen superfamilies predict immunotherapy response. CD8+ T cell–dependent killing of cancer cells requires efficient presentation of tumor antigens by human leukocyte antigen class I (HLA-I) molecules. However, the extent to which patient-specific HLA-I genotype influences response to anti–programmed cell death protein 1 or anti–cytotoxic T lymphocyte–associated protein 4 is currently unknown. We determined the HLA-I genotype of 1535 advanced cancer patients treated with immune checkpoint blockade (ICB). Maximal heterozygosity at HLA-I loci (“A,” “B,” and “C”) improved overall survival after ICB compared with patients who were homozygous for at least one HLA locus. In two independent melanoma cohorts, patients with the HLA-B44 supertype had extended survival, whereas the HLA-B62 supertype (including HLA-B*15:01) or somatic loss of heterozygosity at HLA-I was associated with poor outcome. Molecular dynamics simulations of HLA-B*15:01 revealed different elements that may impair CD8+ T cell recognition of neoantigens. Our results have important implications for predicting response to ICB and for the design of neoantigen-based therapeutic vaccines.

A Peptide-Coated Gold Nanocluster Exhibits Unique Behavior in Protein Activity Inhibition

Gold nanoclusters (AuNCs) can be primed for biomedical applications through functionalization with peptide coatings. Often anchored by thiol groups, such peptide coronae not only serve as passivators but can also endow AuNCs with additional bioactive properties. In this work, we use molecular dynamics simulations to study the structure of a tridecapeptide-coated Au25 cluster and its subsequent interactions with the enzyme thioredoxin reductase 1, TrxR1. We find that, in isolation, both the distribution and conformation of the coating peptides fluctuate considerably. When the coated AuNC is placed around TrxR1, however, the motion of the highly charged peptide coating (+5e/peptide) is quickly biased by electrostatic attraction to the protein; the asymmetric coating acts to guide the nanoclusters diffusion toward the enzymes negatively charged active site. After the AuNC comes into contact with TrxR1, its peptide corona spreads over the protein surface to facilitate stable binding with protein. Though individual salt bridge interactions between the tridecapeptides and TrxR1 are transient in nature, the cooperative binding of the peptide-coated AuNC is very stable, overall. Interestingly, the biased corona peptide motion, the spreading and the cooperation between peptide extensions observed in AuNC binding are reminiscent of bacterial stimulus-driven approaching and adhesion mechanisms mediated by cilia. The prevailing AuNC binding mode we characterize also satisfies a notable hydrophobic interaction seen in the association of thioredoxin to TrxR1, providing a possible explanation for the AuNC binding specificity observed in experiments. Our simulations thus suggest this peptide-coated AuNC serves as an adept thioredoxin mimic that extends an array of auxiliary structural components capable of enhancing interactions with the target protein in question.

Surface Curvature Relation to Protein Adsorption for Carbon-based Nanomaterials

The adsorption of proteins onto carbon-based nanomaterials (CBNs) is dictated by hydrophobic and π-π interactions between aliphatic and aromatic residues and the conjugated CBN surface. Accordingly, protein adsorption is highly sensitive to topological constraints imposed by CBN surface structure; in particular, adsorption capacity is thought to increase as the incident surface curvature decreases. In this work, we couple Molecular Dynamics (MD) simulations with fluorescence spectroscopy experiments to characterize this curvature dependence in detail for the model protein bovine serum albumin (BSA). By studying BSA adsorption onto carbon nanotubes of increasing radius (featuring descending local curvatures) and a flat graphene sheet, we confirm that adsorption capacity is indeed enhanced on flatter surfaces. Naïve fluorescence experiments featuring multi-walled carbon nanotubes (MWCNTs), however, conform to an opposing trend. To reconcile these observations, we conduct additional MD simulations with MWCNTs that match those prepared in experiments; such simulations indicate that increased mass to surface area ratios in multi-walled systems explain the observed discrepancies. In reduction, our work substantiates the inverse relationship between protein adsorption capacity and surface curvature and further demonstrates the need for subtle consideration in experimental and simulation design.

Emergence of glass-like behavior in Markov state models of protein folding dynamics.

The extent to which glass-like kinetics govern dynamics in protein folding has been heavily debated. Here, we address the subject with an application of space-time perturbation theory to the dynamics of protein folding Markov state models. Borrowing techniques from the s-ensemble method, we argue that distinct active and inactive phases exist for protein folding dynamics, and that kinetics for specific systems can fall into either dynamical regime. We do not, however, observe a true glass transition in any system studied. We go on to discuss how these inactive and active phases might relate to general protein folding properties.

PEGylated graphene oxide elicits strong immunological responses despite surface passivation

Engineered nanomaterials promise to transform medicine at the bio–nano interface. However, it is important to elucidate how synthetic nanomaterials interact with critical biological systems before such products can be safely utilized in humans. Past evidence suggests that polyethylene glycol-functionalized (PEGylated) nanomaterials are largely biocompatible and elicit less dramatic immune responses than their pristine counterparts. We here report results that contradict these findings. We find that PEGylated graphene oxide nanosheets (nGO-PEGs) stimulate potent cytokine responses in peritoneal macrophages, despite not being internalized. Atomistic molecular dynamics simulations support a mechanism by which nGO-PEGs preferentially adsorb onto and/or partially insert into cell membranes, thereby amplifying interactions with stimulatory surface receptors. Further experiments demonstrate that nGO-PEG indeed provokes cytokine secretion by enhancing integrin β8-related signalling pathways. The present results inform that surface passivation does not always prevent immunological reactions to 2D nanomaterials but also suggest applications for PEGylated nanomaterials wherein immune stimulation is desired.

Single-Walled Carbon Nanotubes Inhibit the Cytochrome P450 Enzyme, CYP3A4

We report a detailed computational and experimental study of the interaction of single-walled carbon nanotubes (SWCNTs) with the drug-metabolizing cytochrome P450 enzyme, CYP3A4. Dose-dependent inhibition of CYP3A4-mediated conversion of the model compound, testosterone, to its major metabolite, 6β-hydroxy testosterone was noted. Evidence for a direct interaction between SWCNTs and CYP3A4 was also provided. The inhibition of enzyme activity was alleviated when SWCNTs were pre-coated with bovine serum albumin. Furthermore, covalent functionalization of SWCNTs with polyethylene glycol (PEG) chains mitigated the inhibition of CYP3A4 enzymatic activity. Molecular dynamics simulations suggested that inhibition of the catalytic activity of CYP3A4 is mainly due to blocking of the exit channel for substrates/products through a complex binding mechanism. This work suggests that SWCNTs could interfere with metabolism of drugs and other xenobiotics and provides a molecular mechanism for this toxicity. Our study also suggests means to reduce this toxicity, eg., by surface modification.

Dynamical Phase Transitions Reveal Amyloid-like States on Protein Folding Landscapes

Developing an understanding of protein misfolding processes presents a crucial challenge for unlocking the mysteries of human disease. In this article, we present our observations of β-sheet-rich misfolded states on a number of protein dynamical landscapes investigated through molecular dynamics simulation and Markov state models. We employ a nonequilibrium statistical mechanical theory to identify the glassy states in a proteins dynamics, and we discuss the nonnative, β-sheet-rich states that play a distinct role in the slowest dynamics within seven protein folding systems. We highlight the fundamental similarity between these states and the amyloid structures responsible for many neurodegenerative diseases, and we discuss potential consequences for mechanisms of protein aggregation and intermolecular amyloid formation.