Publications by authors named "Logan S Ahlstrom"

Article Synopsis
  • Heterogeneous and dynamic biomolecular complexes are crucial for cellular functions but are hard to study due to experimental difficulties.
  • A new method called READ combines X-ray crystallography with NMR techniques to better analyze these complex structures.
  • The READ method allows researchers to visualize and select conformational ensembles from diverse binding poses, providing a clearer understanding of dynamic protein-protein interactions.
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HdeA is a periplasmic chaperone that is rapidly activated upon shifting the pH to acidic conditions. This activation is thought to involve monomerization of HdeA. There is evidence that monomerization and partial unfolding allow the chaperone to bind to proteins denatured by low pH, thereby protecting them from aggregation.

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Understanding the fundamental biophysics behind protein-nanoparticle (NP) interactions is essential for the design and engineering bio-NP systems. The authors describe the development of a coarse-grained protein-NP model that utilizes a structure centric protein model. A key feature of the protein-NP model is the quantitative inclusion of the hydrophobic character of residues in the protein and their interactions with the NP surface.

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Side chains in protein crystal structures are essential for understanding biochemical processes such as catalysis and molecular recognition. However, crystal packing could influence side-chain conformation and dynamics, thus complicating functional interpretations of available experimental structures. Here we investigate the effect of crystal packing on side-chain conformational dynamics with crystal and solution molecular dynamics simulations using Cyanovirin-N as a model system.

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We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms.

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Chaperones maintain a healthy proteome by preventing aggregation and by aiding in protein folding. Precisely how chaperones influence the conformational properties of their substrates, however, remains unclear. To achieve a detailed description of dynamic chaperone-substrate interactions, we fused site-specific NMR information with coarse-grained simulations.

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Challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone-substrate complexes would ultimately reveal how chaperones help proteins fold into their native state.

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Intrinsically disordered regions of proteins can gain structure by binding to a partner. This process, of coupled folding and binding (CFaB), is a fundamental part of many important biological processes. Structure-based models have proven themselves capable of revealing fundamental aspects of how CFaB occurs, however, typical methods to enhance the sampling of these transitions, such as replica exchange, do not adequately sample the transition state region of this extremely rare process.

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Given the demonstrated utility of coarse-grained modeling and simulations approaches in studying protein structure and dynamics, developing methods that allow experimental observables to be directly recovered from coarse-grained models is of great importance. In this work, we develop one such method that enables protein backbone chemical shifts (1HN, 1Hα, 13Cα, 13C, 13Cβ, and 15N) to be predicted from Cα coordinates. We show that our Cα-based method, LARMORCα, predicts backbone chemical shifts with comparable accuracy to some all-atom approaches.

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The pH-sensing chaperone HdeA promotes the survival of enteropathogenic bacteria during transit through the harshly acidic environment of the mammalian stomach. At low pH, HdeA transitions from an inactive, folded, dimer to chaperone-active, disordered, monomers to protect against the acid-induced aggregation of periplasmic proteins. Toward achieving a detailed mechanistic understanding of the pH response of HdeA, we develop a multiscale modeling approach to capture its pH-dependent thermodynamics.

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Molecular recognition by intrinsically disordered proteins (IDPs) plays a central role in many critical cellular processes. Toward achieving detailed mechanistic understanding of IDP-target interactions, here we employ the "Hamiltonian mapping" methodology, which is rooted in the weighted histogram analysis method (WHAM), for the fast and efficient calibration of structure-based models in studies of IDPs. By performing reference simulations on a given Hamiltonian, we illustrate for two model IDPs how this method can extrapolate thermodynamic behavior under a range of modified Hamiltonians, in this case representing changes in the binding affinity () of the system.

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Variation among crystal structures of the λ Cro dimer highlights conformational flexibility. The structures range from a wild type closed to a mutant fully open conformation, but it is unclear if each represents a stable solution state or if one may be the result of crystal packing. Here we use molecular dynamics (MD) simulation to investigate the energetics of crystal packing interfaces and the influence of site-directed mutagenesis on them in order to examine the effect of crystal packing on wild type and mutant Cro dimer conformation.

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Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone.

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The small pH stress-sensing chaperone HdeA helps pathogenic enteric E. coli survive passage through the severely acidic environment of the mammalian stomach. Under stress conditions, HdeA transitions from an inactive folded dimer to a chaperone-active unfolded monomer to prevent the acid-induced aggregation of periplasmic proteins.

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The significant variation among solved structures of the λ Cro dimer suggests its flexibility. However, contacts in the crystal lattice could have stabilized a conformation which is unrepresentative of its dominant solution form. Here we report on the conformational space of the Cro dimer in solution using replica exchange molecular dynamics in explicit solvent.

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Alpha-synuclein (αS) is a 140-amino-acid protein that is involved in a number of neurodegenerative diseases. In Parkinson's disease, the protein is typically encountered in intracellular, high-molecular-weight aggregates. Although αS is abundant in the presynaptic terminals of the central nervous system, its physiological function is still unknown.

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