Showing papers by "Michael Feig published in 2017"

CHARMM36m: An improved force field for folded and intrinsically disordered proteins

Abstract: An all-atom protein force field, CHARMM36m, offers improved accuracy for simulating intrinsically disordered peptides and proteins. The all-atom additive CHARMM36 protein force field is widely used in molecular modeling and simulations. We present its refinement, CHARMM36m ( http://mackerell.umaryland.edu/charmm_ff.shtml ), with improved accuracy in generating polypeptide backbone conformational ensembles for intrinsically disordered peptides and proteins.

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations.

Abstract: The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments.

Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation.

Abstract: For a long time, the effect of a crowded cellular environment on protein dynamics has been largely ignored. Recent experiments indicate that proteins diffuse more slowly in a living cell than in a diluted solution, and further studies suggest that the diffusion depends on the local surroundings. Here, detailed insight into how diffusion depends on protein–protein contacts is presented based on extensive all-atom molecular dynamics simulations of concentrated villin headpiece solutions. After force field adjustments in the form of increased protein–water interactions to reproduce experimental data, translational and rotational diffusion was analyzed in detail. Although internal protein dynamics remained largely unaltered, rotational diffusion was found to slow down more significantly than translational diffusion as the protein concentration increased. The decrease in diffusion is interpreted in terms of a transient formation of protein clusters. These clusters persist on sub-microsecond time scales and fol...

Computational protein structure refinement: almost there, yet still so far to go

Abstract: Protein structures are essential in modern biology yet experimental methods are far from being able to catch up with the rapid increase in available genomic data. Computational protein structure prediction methods aim to fill the gap while the role of protein structure refinement is to take approximate initial template-based models and bring them closer to the true native structure. Current methods for computational structure refinement rely on molecular dynamics simulations, related sampling methods, or iterative structure optimization protocols. The best methods are able to achieve moderate degrees of refinement but consistent refinement that can reach near-experimental accuracy remains elusive. Key issues revolve around the accuracy of the energy function, the inability to reliably rank multiple models, and the use of restraints that keep sampling close to the native state but also limit the degree of possible refinement. A different aspect is the question of what exactly the target of high-resolution refinement should be as experimental structures are affected by experimental conditions and different biological questions require varying levels of accuracy. While improvement of the global protein structure is a difficult problem, high-resolution refinement methods that improves local structural quality such as favorable stereochemistry and the avoidance of atomic clashes are much more successful.

Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation

Abstract: For a long time, the effect of a crowded cellular environment on protein dynamics has been largely ignored. Recent experiments indicate that proteins diffuse more slowly in a living cell than in a diluted solution, and further studies suggest that the diffusion depends on the local surroundings. Here, detailed insight into how diffusion depends on protein–protein contacts is presented based on extensive all-atom molecular dynamics simulations of concentrated villin headpiece solutions. After force field adjustments in the form of increased protein–water interactions to reproduce experimental data, translational and rotational diffusion was analyzed in detail. Although internal protein dynamics remained largely unaltered, rotational diffusion was found to slow down more significantly than translational diffusion as the protein concentration increased. The decrease in diffusion is interpreted in terms of a transient formation of protein clusters. These clusters persist on sub-microsecond time scales and follow distributions that increasingly shift toward larger cluster size with increasing protein concentrations. Weighting diffusion coefficients estimated for different clusters extracted from the simulations with the distribution of clusters largely reproduces the overall observed diffusion rates, suggesting that transient cluster formation is a primary cause for a slow-down in diffusion upon crowding with other proteins.

Hybrid All-Atom/Coarse-Grained Simulations of Proteins by Direct Coupling of CHARMM and PRIMO Force Fields

Abstract: Hybrid all-atom/coarse-grained (AA/CG) simulations of proteins offer a computationally efficient compromise where atomistic details are only applied to biologically relevant regions while benefiting from the speedup of treating the remaining parts of a given system at the CG level. The recently developed CG model, PRIMO, allows a direct coupling with an atomistic force field with no additional modifications or coupling terms and the ability to carry out dynamic simulations without any restraints on secondary or tertiary structures. A hybrid AA/CG scheme based on combining all-atom CHARMM and coarse-grained PRIMO representations was validated via molecular dynamics and replica exchange simulations of soluble and membrane proteins. The AA/CG scheme was also tested in the calculation of the free energy profile for the transition from the closed to the open state of adenylate kinase via umbrella sampling molecular dynamics method. The overall finding is that the AA/CG scheme generates dynamics and energetics ...

Interaction of intramembrane metalloprotease SpoIVFB with substrate Pro-σK

Abstract: Intramembrane proteases (IPs) cleave membrane-associated substrates in nearly all organisms and regulate diverse processes. A better understanding of how these enzymes interact with their substrates is necessary for rational design of IP modulators. We show that interaction of Bacillus subtilis IP SpoIVFB with its substrate Pro-σK depends on particular residues in the interdomain linker of SpoIVFB. The linker plus either the N-terminal membrane domain or the C-terminal cystathione-β-synthase (CBS) domain of SpoIVFB was sufficient for the interaction but not for cleavage of Pro-σK. Chemical cross-linking and mass spectrometry of purified, inactive SpoIVFB–Pro-σK complex indicated residues of the two proteins in proximity. A structural model of the complex was built via partial homology and by using constraints based on cross-linking data. In the model, the Proregion of Pro-σK loops into the membrane domain of SpoIVFB, and the rest of Pro-σK interacts extensively with the linker and the CBS domain of SpoIVFB. The extensive interaction is proposed to allow coordination between ATP binding by the CBS domain and Pro-σK cleavage by the membrane domain.

Heterogeneous dielectric generalized Born model with a van der Waals term provides improved association energetics of membrane-embedded transmembrane helices.

Abstract: The heterogeneous dielectric generalized Born (HDGB) implicit membrane formalism is extended by the addition of a van der Waals dispersion term to better describe the nonpolar components of the free energy of solvation. The new model, termed HDGBvdW, improves the energy estimates in the hydrophobic interior of the membrane, where polar and charged species are rarely found and nonpolar interactions become significant. The implicit van der Waals term for the membrane environment extends the model from Gallicchio et al. (J. Comput. Chem. 2004, 25, 479) by combining separate contributions from each of the membrane components. The HDGBvdW model is validated with a series of test cases ranging from membrane insertion and pair association profiles of amino acid side chain analogs and transmembrane helices. Overall, the HDGBvdW model leads to increased agreement with explicit membrane simulation results and experimental data. © 2016 Wiley Periodicals, Inc.

Determination of Hydrophobic Lengths of Membrane Proteins with the HDGB Implicit Membrane Model

Abstract: A protocol for predicting the hydrophobic length of membrane proteins using the heterogeneous dielectric generalized Born (HDGB) implicit membrane model is presented. The method involves optimal positioning in the membrane and identification of lipid-facing and inward-facing residues, followed by energy optimization of the implicit membrane model to obtain the hydrophobic length from the optimal membrane width. The latest HDGB version 3 (HDGBv3) and HDGB van der Waals (HDGBvdW) models were applied to a test set containing 15 proteins (seven β-barrel and eight α-helical proteins), for which matching membrane widths are available from experiment, and an additional set contains ten α-helical and ten β-barrel proteins without any experimental data. The results with the HDGB model compare favorably with predictions from methods used in the Orientations of Proteins in Membranes (OPM) and Protein Data Bank of Transmembrane Proteins (PDB-TM) databases.

Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions

Abstract: A scoring protocol based on implicit membrane-based scoring functions and a new protocol for optimizing the positioning of proteins inside the membrane was evaluated for its capacity to discriminate native-like states from misfolded decoys. A decoy set previously established by the Baker lab (Proteins: Struct., Funct., Genet. 2006, 62, 1010–1025) was used along with a second set that was generated to cover higher resolution models. The Implicit Membrane Model 1 (IMM1), IMM1 model with CHARMM 36 parameters (IMM1-p36), generalized Born with simple switching (GBSW), and heterogeneous dielectric generalized Born versions 2 (HDGBv2) and 3 (HDGBv3) were tested along with the new HDGB van der Waals (HDGBvdW) model that adds implicit van der Waals contributions to the solvation free energy. For comparison, scores were also calculated with the distance-scaled finite ideal-gas reference (DFIRE) scoring function. Z-scores for native state discrimination, energy vs root-mean-square deviation (RMSD) correlations, and ...

Molecular Dynamics Simulations of Biomolecules in Cellular Environments

Abstract: Atomic structures of proteins, nucleic acids, and their complexes are determined using X-ray crystallography, NMR, or cryo-Electron Microscopy. These structures are essential to understand their structure-function relationships. However, the experimental conditions are totally different from the actual cellular environments and it is hard to understand how biomolecules behave in such cellular environments, just using the atomic structures. We have recently built protein crowding systems in computers and carried out all-atom molecular dynamics (MD) simulations of the systems to understand biomolecular dynamics in the crowded environments. The largest simulations we have ever performed were the all-atom MD simulations of a bacterial cytoplasm using K computer. By analyzing the simulation trajectories, we observed that non-specific protein-protein and protein-metabolite interactions play important roles in biomolecular dynamics and stability in a cell. The new insight from the simulations is useful not only for basic life science in molecular and cellular biology but also drug discovery in future for introducing the effect of non-specific protein-drug interactions.