The unique biophysical and biochemical properties of intrinsically disordered proteins (IDPs) and their recombinant derivatives, intrinsically disordered protein polymers (IDPPs) offer opportunities for producing multistimuli‐responsive materials; their sequence‐encoded disorder and tendency for phase separation facilitate the development of multifunctional materials. This review highlights the strategies for enhancing the structural diversity of elastin‐like polypeptides (ELPs) and resilin‐like polypeptides (RLPs), and their self‐assembled structures via genetic fusion to ordered motifs such as helical or beta sheet domains. In particular, this review describes approaches that harness the synergistic interplay between order‐promoting and thermoresponsive building blocks to design hybrid biomaterials, resulting in well‐structured, stimuli‐responsive supramolecular materials ordered on the nanoscale.
- Award ID(s):
- 2003629
- NSF-PAR ID:
- 10341240
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 119
- Issue:
- 4
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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This data set for the manuscript entitled "Design of Peptides that Fold and Self-Assemble on Graphite" includes all files needed to run and analyze the simulations described in the this manuscript in the molecular dynamics software NAMD, as well as the output of the simulations. The files are organized into directories corresponding to the figures of the main text and supporting information. They include molecular model structure files (NAMD psf or Amber prmtop format), force field parameter files (in CHARMM format), initial atomic coordinates (pdb format), NAMD configuration files, Colvars configuration files, NAMD log files, and NAMD output including restart files (in binary NAMD format) and trajectories in dcd format (downsampled to 10 ns per frame). Analysis is controlled by shell scripts (Bash-compatible) that call VMD Tcl scripts or python scripts. These scripts and their output are also included.
Version: 2.0
Changes versus version 1.0 are the addition of the free energy of folding, adsorption, and pairing calculations (Sim_Figure-7) and shifting of the figure numbers to accommodate this addition.
Conventions Used in These Files
===============================Structure Files
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- graph_*.psf or sol_*.psf (original NAMD (XPLOR?) format psf file including atom details (type, charge, mass), as well as definitions of bonds, angles, dihedrals, and impropers for each dipeptide.)- graph_*.pdb or sol_*.pdb (initial coordinates before equilibration)
- repart_*.psf (same as the above psf files, but the masses of non-water hydrogen atoms have been repartitioned by VMD script repartitionMass.tcl)
- freeTop_*.pdb (same as the above pdb files, but the carbons of the lower graphene layer have been placed at a single z value and marked for restraints in NAMD)
- amber_*.prmtop (combined topology and parameter files for Amber force field simulations)
- repart_amber_*.prmtop (same as the above prmtop files, but the masses of non-water hydrogen atoms have been repartitioned by ParmEd)Force Field Parameters
----------------------
CHARMM format parameter files:
- par_all36m_prot.prm (CHARMM36m FF for proteins)
- par_all36_cgenff_no_nbfix.prm (CGenFF v4.4 for graphene) The NBFIX parameters are commented out since they are only needed for aromatic halogens and we use only the CG2R61 type for graphene.
- toppar_water_ions_prot_cgenff.str (CHARMM water and ions with NBFIX parameters needed for protein and CGenFF included and others commented out)Template NAMD Configuration Files
---------------------------------
These contain the most commonly used simulation parameters. They are called by the other NAMD configuration files (which are in the namd/ subdirectory):
- template_min.namd (minimization)
- template_eq.namd (NPT equilibration with lower graphene fixed)
- template_abf.namd (for adaptive biasing force)Minimization
-------------
- namd/min_*.0.namdEquilibration
-------------
- namd/eq_*.0.namdAdaptive biasing force calculations
-----------------------------------
- namd/eabfZRest7_graph_chp1404.0.namd
- namd/eabfZRest7_graph_chp1404.1.namd (continuation of eabfZRest7_graph_chp1404.0.namd)Log Files
---------
For each NAMD configuration file given in the last two sections, there is a log file with the same prefix, which gives the text output of NAMD. For instance, the output of namd/eabfZRest7_graph_chp1404.0.namd is eabfZRest7_graph_chp1404.0.log.Simulation Output
-----------------
The simulation output files (which match the names of the NAMD configuration files) are in the output/ directory. Files with the extensions .coor, .vel, and .xsc are coordinates in NAMD binary format, velocities in NAMD binary format, and extended system information (including cell size) in text format. Files with the extension .dcd give the trajectory of the atomic coorinates over time (and also include system cell information). Due to storage limitations, large DCD files have been omitted or replaced with new DCD files having the prefix stride50_ including only every 50 frames. The time between frames in these files is 50 * 50000 steps/frame * 4 fs/step = 10 ns. The system cell trajectory is also included for the NPT runs are output/eq_*.xst.Scripts
-------
Files with the .sh extension can be found throughout. These usually provide the highest level control for submission of simulations and analysis. Look to these as a guide to what is happening. If there are scripts with step1_*.sh and step2_*.sh, they are intended to be run in order, with step1_*.sh first.
CONTENTS
========The directory contents are as follows. The directories Sim_Figure-1 and Sim_Figure-8 include README.txt files that describe the files and naming conventions used throughout this data set.
Sim_Figure-1: Simulations of N-acetylated C-amidated amino acids (Ac-X-NHMe) at the graphite–water interface.
Sim_Figure-2: Simulations of different peptide designs (including acyclic, disulfide cyclized, and N-to-C cyclized) at the graphite–water interface.
Sim_Figure-3: MM-GBSA calculations of different peptide sequences for a folded conformation and 5 misfolded/unfolded conformations.
Sim_Figure-4: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.
Sim_Figure-5: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 295 K.
Sim_Figure-5_replica: Temperature replica exchange molecular dynamics simulations for the peptide cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) with 20 replicas for temperatures from 295 to 454 K.
Sim_Figure-6: Simulation of the peptide molecule cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) in free solution (no graphite).
Sim_Figure-7: Free energy calculations for folding, adsorption, and pairing for the peptide CHP1404 (sequence: cyc(GTGSGTG-GPGG-GCGTGTG-SGPG)). For folding, we calculate the PMF as function of RMSD by replica-exchange umbrella sampling (in the subdirectory Folding_CHP1404_Graphene/). We make the same calculation in solution, which required 3 seperate replica-exchange umbrella sampling calculations (in the subdirectory Folding_CHP1404_Solution/). Both PMF of RMSD calculations for the scrambled peptide are in Folding_scram1404/. For adsorption, calculation of the PMF for the orientational restraints and the calculation of the PMF along z (the distance between the graphene sheet and the center of mass of the peptide) are in Adsorption_CHP1404/ and Adsorption_scram1404/. The actual calculation of the free energy is done by a shell script ("doRestraintEnergyError.sh") in the 1_free_energy/ subsubdirectory. Processing of the PMFs must be done first in the 0_pmf/ subsubdirectory. Finally, files for free energy calculations of pair formation for CHP1404 are found in the Pair/ subdirectory.
Sim_Figure-8: Simulation of four peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) where the peptides are far above the graphene–water interface in the initial configuration.
Sim_Figure-9: Two replicates of a simulation of nine peptide molecules with the sequence cyc(GTGSGTG-GPGG-GCGTGTG-SGPG) at the graphite–water interface at 370 K.
Sim_Figure-9_scrambled: Two replicates of a simulation of nine peptide molecules with the control sequence cyc(GGTPTTGGGGGGSGGPSGTGGC) at the graphite–water interface at 370 K.
Sim_Figure-10: Adaptive biasing for calculation of the free energy of the folded peptide as a function of the angle between its long axis and the zigzag directions of the underlying graphene sheet.
This material is based upon work supported by the US National Science Foundation under grant no. DMR-1945589. A majority of the computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CHE-1726332, CNS-1006860, EPS-1006860, and EPS-0919443. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562, through allocation BIO200030. -
null (Ed.)Background: Hypertrophic cardiomyopathy (HCM) is caused by pathogenic variants in sarcomere protein genes that evoke hypercontractility, poor relaxation, and increased energy consumption by the heart and increased patient risks for arrhythmias and heart failure. Recent studies show that pathogenic missense variants in myosin, the molecular motor of the sarcomere, are clustered in residues that participate in dynamic conformational states of sarcomere proteins. We hypothesized that these conformations are essential to adapt contractile output for energy conservation and that pathophysiology of HCM results from destabilization of these conformations. Methods: We assayed myosin ATP binding to define the proportion of myosins in the super relaxed state (SRX) conformation or the disordered relaxed state (DRX) conformation in healthy rodent and human hearts, at baseline and in response to reduced hemodynamic demands of hibernation or pathogenic HCM variants. To determine the relationships between myosin conformations, sarcomere function, and cell biology, we assessed contractility, relaxation, and cardiomyocyte morphology and metabolism, with and without an allosteric modulator of myosin ATPase activity. We then tested whether the positions of myosin variants of unknown clinical significance that were identified in patients with HCM, predicted functional consequences and associations with heart failure and arrhythmias. Results: Myosins undergo physiological shifts between the SRX conformation that maximizes energy conservation and the DRX conformation that enables cross-bridge formation with greater ATP consumption. Systemic hemodynamic requirements, pharmacological modulators of myosin, and pathogenic myosin missense mutations influenced the proportions of these conformations. Hibernation increased the proportion of myosins in the SRX conformation, whereas pathogenic variants destabilized these and increased the proportion of myosins in the DRX conformation, which enhanced cardiomyocyte contractility, but impaired relaxation and evoked hypertrophic remodeling with increased energetic stress. Using structural locations to stratify variants of unknown clinical significance, we showed that the variants that destabilized myosin conformations were associated with higher rates of heart failure and arrhythmias in patients with HCM. Conclusions: Myosin conformations establish work-energy equipoise that is essential for life-long cellular homeostasis and heart function. Destabilization of myosin energy-conserving states promotes contractile abnormalities, morphological and metabolic remodeling, and adverse clinical outcomes in patients with HCM. Therapeutic restabilization corrects cellular contractile and metabolic phenotypes and may limit these adverse clinical outcomes in patients with HCM.more » « less
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Abstract Modulation of inter‐ and intramolecular interactions between bioinspired designer molecules can be harnessed for developing functional structures that mimic the complex hierarchical organization of multicomponent assemblies observed in nature. Furthermore, such multistimuli‐responsive molecules offer orthogonal tunability for generating versatile multifunctional platforms via independent biochemical and biophysical cues. In this review, the remarkable physicochemical and mechanical properties of genetically engineered protein polymers derived from intrinsically disordered proteins, specifically elastin and resilin, are discussed. This review highlights emerging technologies which use them as building blocks in the fabrication of highly programmable structured biomaterials for applications in delivery of biotherapeutic cargo and regenerative medicine.
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ABSTRACT Tsr, the serine chemoreceptor in Escherichia coli , transduces signals from a periplasmic ligand-binding site to its cytoplasmic tip, where it controls the activity of the CheA kinase. To function, Tsr forms trimers of homodimers (TODs), which associate in vivo with the CheA kinase and CheW coupling protein. Together, these proteins assemble into extended hexagonal arrays. Here, we use cryo-electron tomography and molecular dynamics simulation to study Tsr in the context of a near-native array, characterizing its signaling-related conformational changes at both the individual dimer and the trimer level. In particular, we show that individual Tsr dimers within a trimer exhibit asymmetric flexibilities that are a function of the signaling state, highlighting the effect of their different protein interactions at the receptor tips. We further reveal that the dimer compactness of the Tsr trimer changes between signaling states, transitioning at the glycine hinge from a compact conformation in the kinase-OFF state to an expanded conformation in the kinase-ON state. Hence, our results support a crucial role for the glycine hinge: to allow the receptor flexibility necessary to achieve different signaling states while also maintaining structural constraints imposed by the membrane and extended array architecture. IMPORTANCE In Escherichia coli , membrane-bound chemoreceptors, the histidine kinase CheA, and coupling protein CheW form highly ordered chemosensory arrays. In core signaling complexes, chemoreceptor trimers of dimers undergo conformational changes, induced by ligand binding and sensory adaptation, which regulate kinase activation. Here, we characterize by cryo-electron tomography the kinase-ON and kinase-OFF conformations of the E. coli serine receptor in its native array context. We found distinctive structural differences between the members of a receptor trimer, which contact different partners in the signaling unit, and structural differences between the ON and OFF signaling complexes. Our results provide new insights into the signaling mechanism of chemoreceptor arrays and suggest an important functional role for a previously postulated flexible region and glycine hinge in the receptor molecule.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2115523119
