Long-Range Signaling in MutS and MSH Homologs via Switching of Dynamic Communication Pathways.

Allostery is conformation regulation by propagating a signal from one site to another distal site. This study focuses on the long-range communication in DNA mismatch repair proteins MutS and its homologs where intramolecular signaling has to travel over 70 Å to couple lesion detection to ATPase activity and eventual downstream repair. Using dynamic network analysis based on extensive molecular dynamics simulations, multiple preserved communication pathways were identified that would allow such long-range signaling. The pathways appear to depend on the nucleotides bound to the ATPase domain as well as the type of DNA substrate consistent with previously proposed functional cycles of mismatch recognition and repair initiation by MutS and homologs. A mechanism is proposed where pathways are switched without major conformational rearrangements allowing for efficient long-range signaling and allostery.

Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs.

Predicting protein backbone chemical shifts from Cα coordinates: extracting high resolution experimental observables from low resolution models.

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, 13Cß, 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. More importantly, we demonstrate that LARMORCα predicted chemical shifts are able to resolve native structure from decoy pools that contain both native and non-native models, and so it is sensitive to protein structure. As an application, we use LARMORCα to characterize the transient state of the fast-folding protein gpW using recently published NMR relaxation dispersion derived backbone chemical shifts. The model we obtain is consistent with the previously proposed model based on independent analysis of the chemical shift dispersion pattern of the transient state. We anticipate that LARMORCα will find utility as a tool that enables important protein conformational substates to be identified by "parsing" trajectories and ensembles generated using coarse-grained modeling and simulations.

Multiscale modeling of a conditionally disordered pH-sensing chaperone.

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. Our approach combines pK(a) (logarithmic acid dissociation constant) calculations from all-atom constant pH molecular dynamics simulations with coarse-grained modeling and yields new, atomic-level, insights into HdeA chaperone function that can be directly tested by experiment. "pH triggers" that significantly destabilize the dimer are each located near the N-terminus of a helix, suggesting that their neutralization at low pH destabilizes the helix macrodipole as a mechanism of monomer disordering. Moreover, we observe a non-monotonic change in the pH-dependent stability of HdeA, with maximal stability of the dimer near pH5. This affect is attributed to the protonation Glu37, which exhibits an anomalously high pK(a) value and is located within the hydrophobic dimer interface. Finally, the pH-dependent binding pathway of HdeA comprises a partially unfolded, dimeric intermediate that becomes increasingly stable relative to the native dimer at lower pH values and displays key structural features for chaperone-substrate interaction. We anticipate that the insights from our model will help inform ongoing NMR and biochemical investigations.

Hamiltonian Mapping Revisited: Calibrating Minimalist Models to Capture Molecular Recognition by Intrinsically Disordered Proteins.

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 (Kd) of the system. Given sufficient conformational sampling in a single trajectory, Hamiltonian mapping accurately reproduces Kd values from direct simulation. This method may be generally applied to systems beyond IDPs in force field optimization and in describing changes in thermodynamic behavior as a function of external conditions for connection with experiment.

A simple and fast approach for predicting (1)H and (13)C chemical shifts: toward chemical shift-guided simulations of RNA.

We introduce a simple and fast approach for predicting RNA chemical shifts from interatomic distances that performs with an accuracy similar to existing predictors and enables the first chemical shift-restrained simulations of RNA to be carried out. Our analysis demonstrates that the applied restraints can effectively guide conformational sampling toward regions of space that are more consistent with chemical shifts than the initial coordinates used for the simulations. As such, our approach should be widely applicable in mapping the conformational landscape of RNAs via chemical shift-guided molecular dynamics simulations. The simplicity and demonstrated sensitivity to three-dimensional structure should also allow our method to be used in chemical shift-based RNA structure prediction, validation, and refinement.

PCASSO: a fast and efficient Cα-based method for accurately assigning protein secondary structure elements.

Proteins are often characterized in terms of their primary, secondary, tertiary, and quaternary structure. Algorithms such as define secondary structure of proteins (DSSP) can automatically assign protein secondary structure based on the backbone hydrogen-bonding pattern. However, the assignment of secondary structure elements (SSEs) becomes a challenge when only the Cα coordinates are available. In this work, we present protein C-alpha secondary structure output (PCASSO), a fast and accurate program for assigning protein SSEs using only the Cα positions. PCASSO achieves ∼95% accuracy with respect to DSSP and takes ∼0.1 s using a single processor to analyze a 1000 residue system with multiple chains. Our approach was compared with current state-of-the-art Cα-based methods and was found to outperform all of them in both speed and accuracy. A practical application is also presented and discussed.

Prepaying the entropic cost for allosteric regulation in KIX.

The kinase-inducible domain interacting (KIX) domain of the CREB binding protein (CBP) is capable of simultaneously binding two intrinsically disordered transcription factors, such as the mixed-lineage leukemia (MLL) and c-Myb peptides, at isolated interaction sites. In vitro, the affinity for binding c-Myb is approximately doubled when KIX is in complex with MLL, which suggests a positive cooperative binding mechanism, and the affinity for MLL is also slightly increased when KIX is first bound by c-Myb. Expanding the scope of recent NMR and computational studies, we explore the allosteric mechanism at a detailed molecular level that directly connects the microscopic structural dynamics to the macroscopic shift in binding affinities. To this end, we have performed molecular dynamics simulations of free KIX, KIX-c-Myb, MLL-KIX, and MLL-KIX-c-Myb using a topology-based Go-like model. Our results capture an increase in affinity for the peptide in the allosteric site when KIX is prebound by a complementary effector and both peptides follow an effector-independent folding-and-binding mechanism. More importantly, we discover that MLL binding lowers the entropic cost for c-Myb binding, and vice versa, by stabilizing the L12-G2 loop and the C-terminal region of the α3 helix on KIX. This work demonstrates the importance of entropy in allosteric signaling between promiscuous molecular recognition sites and can inform the rational design of small molecule stabilizers to target important regions of conformationally dynamic proteins.

pH-sensitive residues in the p19 RNA silencing suppressor protein from carnation Italian ringspot virus affect siRNA binding stability.

Tombusviruses, such as Carnation Italian ringspot virus (CIRV), encode a protein homodimer called p19 that is capable of suppressing RNA silencing in their infected hosts by binding to and sequestering short-interfering RNA (siRNA) away from the RNA silencing pathway. P19 binding stability has been shown to be sensitive to changes in pH but the specific amino acid residues involved have remained unclear. Using constant pH molecular dynamics simulations, we have identified key pH-dependent residues that affect CIRV p19-siRNA binding stability at various pH ranges based on calculated changes in the free energy contribution from each titratable residue. At high pH, the deprotonation of Lys60, Lys67, Lys71, and Cys134 has the largest effect on the binding stability. Similarly, deprotonation of several acidic residues (Asp9, Glu12, Asp20, Glu35, and/or Glu41) at low pH results in a decrease in binding stability. At neutral pH, residues Glu17 and His132 provide a small increase in the binding stability and we find that the optimal pH range for siRNA binding is between 7.0 and 10.0. Overall, our findings further inform recent experiments and are in excellent agreement with data on the pH-dependent binding profile.

Molecular dynamics trajectory compression with a coarse-grained model.

Molecular dynamics trajectories are very data-intensive thereby limiting sharing and archival of such data. One possible solution is compression of trajectory data. Here, trajectory compression based on conversion to the coarse-grained model PRIMO is proposed. The compressed data is about one third of the original data and fast decompression is possible with an analytical reconstruction procedure from PRIMO to all-atom representations. This protocol largely preserves structural features and to a more limited extent also energetic features of the original trajectory.

Base-flipping mechanism in postmismatch recognition by MutS.

DNA mismatch recognition and repair is vital for preserving the fidelity of the genome. Conserved across prokaryotes and eukaryotes, MutS is the primary protein that is responsible for recognizing a variety of DNA mismatches. From molecular dynamics simulations of the Escherichia coli MutS-DNA complex, we describe significant conformational dynamics in the DNA surrounding a G·T mismatch that involves weakening of the basepair hydrogen bonding in the basepair adjacent to the mismatch and, in one simulation, complete base opening via the major groove. The energetics of base flipping was further examined with Hamiltonian replica exchange free energy calculations revealing a stable flipped-out state with an initial barrier of ~2 kcal/mol. Furthermore, we observe changes in the local DNA structure as well as in the MutS structure that appear to be correlated with base flipping. Our results suggest a role of base flipping as part of the repair initiation mechanism most likely leading to sliding-clamp formation.

Deciphering the mismatch recognition cycle in MutS and MSH2-MSH6 using normal-mode analysis.

Postreplication DNA mismatch repair is essential for maintaining the integrity of genomic information in prokaryotes and eukaryotes. The first step in mismatch repair is the recognition of base-base mismatches and insertions/deletions by bacterial MutS or eukaryotic MSH2-MSH6. Crystal structures of both proteins bound to mismatch DNA reveal a similar molecular architecture but provide limited insight into the detailed molecular mechanism of long-range allostery involved in mismatch recognition and repair initiation. This study describes normal-mode calculations of MutS and MSH2-MSH6 with and without DNA. The results reveal similar protein flexibilities and suggest common dynamic and functional characteristics. A strongly correlated motion is present between the lever domain and ATPase domains, which suggests a pathway for long-range allostery from the N-terminal DNA binding domain to the C-terminal ATPase domains, as indicated by experimental studies. A detailed analysis of individual low-frequency modes of both MutS and MSH2-MSH6 shows changes in the DNA-binding domains coupled to the ATPase sites, which are interpreted in the context of experimental data to arrive at a complete molecular-level mismatch recognition cycle. Distinct conformational states are proposed for DNA scanning, mismatch recognition, repair initiation, and sliding along DNA after mismatch recognition. Hypotheses based on the results presented here form the basis for further experimental and computational studies.