Comparison and Evaluation of Force Fields for Intrinsically Disordered Proteins.

Structural Ensembles of Intrinsically Disordered Proteins using Molecular Dynamics Simulation

Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field

Improved Accuracy and Convergence of Intrinsically Disordered Protein Molecular Dynamics Simulations Using the ff14IDPSFF Force Field

Intrinsically disordered regions (IDRs) or proteins (IDPs), which play crucial biological functions in essential biological processes of life, do not have well-defined secondary or tertiary structures when isolated in solution. The highly dynamic properties and conformational heterogeneity of IDPs make them challenging to study with traditional experimental techniques. As a powerful complementary tool for experiments, all-atom molecular dynamics simulation can obtain detailed conformational information on IDPs, but the limitation of force field accuracy is a challenge for reproducing IDP conformers. Here, we compared five empirical all-atom force fields AMBER03, AMBER99SB-ILDN, CHARMM27, OPLS-AA/L and CHARMM36m in modeling the conformational ensembles of wild-type peptide TAD2(41-62) from the human p53 tumor suppressor. Our results show that for the model peptide, the newest force field CHARMM36m produces more expanded coil ensemble followed by AMBER99SB-ILDN; CHARMM27 displays a predominant propensity for a helical structure; whereas OPLS-AA/L exhibits a apparent preference for a β-sheet structure and yields the most compact conformation. In the comparison of the simulated dimensions with theoretical prediction and the back-calculated chemical shifts with experimental measurements, AMBER99SB-ILDN gives a more consistent agreement than the other force fields. In addition, the region from residues 47 to 55, which commonly forms an amphipathic α-helix upon binding target proteins according to experimental observation, could form a helical structure with a different probability population in our simulations with different force fields. This implies that the binding process might be conducted by, or partly by "conformation selection" for this peptide. This work indicates that force field development for modeling general IDPs accurately has a long way to go, and more detailed experimental data of IDPs are also in demand.

Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein (IDP) whose abnormal aggregation into toxic soluble oligomers and insoluble amyloid fibrils is a pathological feature in type‐2 diabetes. Rat IAPP (rIAPP) differs from hIAPP by only six amino acids yet has a reduced tendency to aggregate or form fibrils. The structures of the monomeric forms of IAPP are difficult to characterize due to their intrinsically disordered nature. Molecular dynamics simulations can provide a detailed characterization of the monomeric forms of rIAPP and hIAPP in near‐physiological conditions. In this work, the conformational landscapes of rIAPP and hIAPP as a function of secondary structure content were predicted using well‐tempered bias exchange metadynamics simulations. Several combinations of commonly used biomolecular force fields and water models were tested. The predicted conformational preferences of both rIAPP and hIAPP are typical of IDPs, exhibiting dominant random coil structures but showing a low propensity for transient α‐helical conformations. Predicted nuclear magnetic resonance Cα chemical shifts reveal different preferences with each force field towards certain conformations, with AMBERff99SBnmr2/TIP4Pd showing the best agreement with the experiment. Comparisons of secondary structure content demonstrate residue‐specific differences between hIAPP and rIAPP that may reflect their different aggregation propensities.

Protein folding is a fascinating, not fully understood phenomenon in biology. Molecular dynamics (MD) simulations are an invaluable tool to study conformational changes in atomistic detail, including folding and unfolding processes of proteins. However, the accuracy of the conformational ensembles derived from MD simulations inevitably relies on the quality of the underlying force field in combination with the respective water model. Here, we investigate protein folding, unfolding, and misfolding of fast-folding proteins by examining different force fields with their recommended water models, i.e., ff14SB with the TIP3P model and ff19SB with the OPC model. To this end, we generated long conventional MD simulations highlighting the perks and pitfalls of these setups. Using Markov state models, we defined kinetically independent conformational substates and emphasized their distinct characteristics, as well as their corresponding state probabilities. Surprisingly, we found substantial differences in thermodynamics and kinetics of protein folding, depending on the combination of the protein force field and water model, originating primarily from the different water models. These results emphasize the importance of carefully choosing the force field and the respective water model as they determine the accuracy of the observed dynamics of folding events. Thus, the findings support the hypothesis that the water model is at least equally important as the force field and hence needs to be considered in future studies investigating protein dynamics and folding in all areas of biophysics.

Proteins with intrinsically disordered regions (IDRs) have large hydrodynamic radii, compared with globular proteins of equivalent weight. Recent experiments showed that IDRs with large radii can create steric pressure to drive membrane curvature during Clathrin-mediated endocytosis (CME). Epsin and Eps15 are two CME proteins with IDRs that contain multiple motifs for binding the adaptor protein AP2, but the impact of AP2-binding on these IDRs is unknown. Some IDRs acquire binding-induced function by forming a folded quaternary structure, but we hypothesize that the IDRs of Epsin and/or Eps15 acquire binding-induced function by increasing their steric volume. We explore this hypothesis in silico by generating conformational ensembles of the IDRs of Epsin (4 million structures) or Eps15 (3 million structures), then estimating the impact of AP2-binding on Radius of Gyration (RG). Results show that the ensemble of Epsin IDR conformations that accommodate AP2 binding has a right-shifted distribution of RG (larger radii) than the unbound Epsin ensemble. In contrast, the ensemble of Eps15 IDR conformations has comparable RG distribution between AP2-bound and unbound. We speculate that AP2 triggers the Epsin IDR to function through binding-induced-expansion, which could increase steric pressure and membrane bending during CME.

Measuring Disorder and Dynamical Properties of FG-Nucleoporins

<p>The use of computational simulation to study the dynamics and interactions of macromolecules has become an important tool in the field of biochemistry. A common method to perform these simulations is to use all-atom explicit-solvent molecular dynamics (MD). However, due to the limitations in computational power currently available, this method is not practical for simulating large-scale biomolecular systems on long timescales. An alternative is to perform implicit-solvent Brownian dynamics (BD) simulations using a coarse grained (CG) model that allows for increased computational efficiency. However, if simulations using the CG model are not realistic, then the gain in computational efficiency from using a CG model is not worthwhile.</p> <p>This thesis describes the derivation of a set of bonded and nonbonded CG potential functions for use in implicit-solvent BD simulations of proteins derived from all-atom explicit-solvent MD simulations of amino acids. To determine which force field and water model to use in the MD simulations, Chapter II describes 1 Μs all-atom explicit-solvent MD simulations of glycine, asparagine, phenylalanine, and valine solutions at 50, 100, 200 and 300 mg/ml concentrations performed using eight different force field and water model combinations. To evaluate the accuracy of the force fields at high solute concentrations, the density, viscosity, and dielectric increments of the four amino acids were calculated from the simulations and compared to experimental results. Additionally, the change in the strength of hydrophobic and electrostatic interactions with increasing solute concentration was calculated for each force field and water model combination. As a result of this study, the Amber ff99SB-ILDN force field and TIP4P-Ew explicit-solvent water model were chosen for all subsequent MD simulations. Chapter III describes the derivation of CG bonded potential functions from 1 Μs all-atom explicit-solvent MD simulations of each of the twenty amino acids, including a separate simulation for protonated histidine. The angle and dihedral probability distributions sampled during the MD simulations were used to optimize the bonded potential functions using the iterative Boltzmann inversion (IBI) method. Chapter IV describes the derivation of CG nonbonded potential functions from 1 Μs all-atom explicit-solvent MD simulations of every possible pairing of the amino acids (231 different systems). The radial distribution functions calculated from these MD simulations were used to optimize a set of nonbonded CG potential functions using the IBI method. The optimized set of bonded and nonbonded potential functions, which is termed COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins), quantitatively reproduced all of the calculated MD distributions. To determine if COFFDROP would be useful for simulations of bimolecular systems, Chapter V describes the testing of the transferability of the force field. First, COFFDROP was used to simulate concentrated amino acid solutions. The clustering of the solutes in these simulations was directly compared with results from corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. Next, BD simulations of 9.2 mM solutions of the small protein villin headpiece were performed. The proteins aggregated during these simulations, which is in agreement with results from MD simulation but in disagreement with experiment. After scaling the strength of COFFDROP's nonbonded potential functions by a factor of 0.8 and rerunning the BD simulations, the amount of aggregation was comparable to experimental observations. Based on these results, COFFDROP is likely to be applicable in CG BD simulations of large, highly concentrated, biomolecular systems.</p>

Transcription factor cyclic Adenosine monophosphate response-element binding protein plays a critical role in the cyclic AMP response pathway via its intrinsically disordered kinase inducible transactivation domain (KID). KID is one of the most studied intrinsically disordered proteins (IDPs), although most previous studies focus on characterizing its disordered state structures. An interesting question that remains to be answered is how the order-disorder transition occurs at experimental conditions. Thanks to the newly developed IDP-specific force field ff14IDPSFF, the quality of conformer sampling for IDPs has been dramatically improved. In this study, molecular dynamics (MD) simulations were used to study the order-to-disorder transition kinetics of KID based on the good agreement with the experiment on its disordered-state properties. Specifically, we tested four force fields, ff99SBildn, ff99IDPs, ff14IDPSFF, and ff14IDPs in the simulations of KID and found that ff14IDPSFF can generate more diversified disordered conformers and also reproduce more accurate experimental secondary chemical shifts. Kinetics analysis of MD simulations demonstrates that the order-disorder transition of KID obeys the first-order kinetics, and the transition nucleus is I127/L128/L141. The possible transition pathways from the nucleus to the last folded residues were identified as I127-R125-L138-L141-S143-A145 and L128-R125-L138-L141-S143-A145 based on a residue-level dynamical network analysis. These computational studies not only provide testable prediction/hypothesis on the order-disorder transition of KID but also confirm that the ff14IDPSFF force field can be used to explore the correlation between the structure and function of IDPs.

Molecular dynamics simulations of intrinsically disordered protein regions enable biophysical interpretation of variant effect predictors.

The structural flexibility of DNA plays a key role in many biological processes of DNA, such as protein-DNA interactions, DNA packaging in viruses and nucleosome positioning on genomic DNA. Some experimental techniques have been employed to investigate the structural flexibility of DNA with the combination of elastic models, but these experiments could only provide the macroscopic properties of DNA, and thus, it is still difficult to understand the corresponding microscopic mechanisms. Recently, all-atom molecular dynamics (MD) simulation has emerged as a useful tool to investigate not only the macroscopic properties of DNA, but also the microscopic description of the flexibility of DNA at an atomic level. The most important issue in all-atom MD simulations of DNA is to choose an appropriate force field for simulating DNA. Very recently, a new force field for DNA has been developed based on the last generation force field of Amber bsc0, which was named Amber bsc1. In this work, all-atom MD simulations are employed to study the flexibility of a 30-bp DNA with the force fields of Amber bsc1 and Amber bsc0 in a comparative way. Our aim of the research is to examine the improvement of the new development of force field (Amber bsc1) in the macroscopic and microscopic properties of DNA, in comparison with the corresponding experimental measurements. All the MD simulations are performed with Gromacs 4.6 and lasted with a simulation time of 600 ns. The MD trajectories are analyzed with Curves+ for the last 500 ns, since the system reaches equilibrium approximately after ~100 ns. Our results show that the new force field (Amber bsc1) can lead to the improvements in the macroscopic parameters of DNA flexibility, i.e., stretch modulus S and twist-stretch coupling D become closer to experimental measurements, while bending persistence lengths lp and torsional persistence lengths C from the two force fields (bsc1 and bsc0) are both in good agreement with experimental data. Our microscopic analyses show that the microscopic structure parameters of DNA from the MD simulation with the Amber bsc1 force field are closer to the experimental values than those with the Amber bsc0 force field, except for slide, and the obvious improvements are observed in some microscopic parameters such as twist and inclination. Our further analyses show that the improvements in macroscopic flexibility from the Amber bsc1 force field are tightly related to the microscopic parameters and their fluctuations. This study would be helpful in understanding the performances of Amber bsc1 and bsc0 force fields in the description of DNA flexibility at both macroscopic and microscopic level.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions.

Phosphorylation is a major post-translational modification that is involved in the regulation of the dynamics and function of intrinsically disordered proteins (IDPs). We recently characterized a phenomenon, which we termed n-phosphate collaborations (nP-collabs), where bulk cations form stable bridges between several phosphoresidues in all-atom molecular dynamic simulations. nP-collabs were found to be sensitive to the combination of force fields and cation types. Here, we attempt to assess the physical relevance of these nP-collabs by evaluating the strength of the cation/phosphate interaction through osmotic coefficient (ϕ) calculations on the model 2Na+HPO42- and 2K+HPO42- salts, using different classical force fields for phosphorylations. All force fields were found to overestimate the strength of the interaction to various degrees. We thus designed new parameters for CHARMM36m and AmberFF99SB-ILDN using the Electronic Continuum Correction (ECC) approach, which provide remarkable agreement for ϕ values for both cation types and over a range of concentrations. We provide a preliminary test of these ECC parameters for phosphorylations by simulating the 7-fold-phosphorylated rhodopsin peptide 7PP and comparing secondary chemical shifts to experimental data. Conformational ensembles resulting from the ECC-derived phosphorylated force fields display both qualitative and quantitative improvements with regard to full-charge force fields. We thus conclude that long-lasting nP-collabs are artifacts for classical force fields born from the lack of explicit polarization, and propose a possible computational strategy for the extensive parametrization of phosphorylations. The presence of long-lived nP-collabs in simulations produced using classical force fields is therefore a serious concern for the accurate modeling of multiphosphorylated peptides and IDPs, which are at the center of research questions regarding neurodegenerative diseases such as Alzheimer's or Parkinson's.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a global leading cause of death from a single infectious agent. The unique cell envelope of Mtb, rich in complex lipids, is critical for its pathogenicity, host interaction, and antibiotic tolerance. Understanding the biophysical properties of these complex lipids is crucial but experimentally challenging. Molecular Dynamics (MD) simulations offer atomic-level insights, but the accuracy is hindered by the lack of dedicated force fields. Here, we developed BLipidFF (Bacteria Lipid Force Fields), a specialized all-atom force field for many key bacteria lipids derived from rigorous quantum mechanics-based parameterization. BLipidFF was validated on four representative Mtb outer membrane lipids: phthiocerol dimycocerosate (PDIM), α-mycolic acid (α-MA), trehalose dimycolate (TDM), and sulfoglycolipid-1 (SL-1). MD simulations results revealed that BLipidFF captured many important membrane properties which are poorly described by general force fields, including the rigidity and diffusion rate of α-MA bilayers. The MD simulation predictions based on BLipidFF are well consistent with the biophysical experiment observations. This study not only provides a validated force field for Mtb membrane lipids but also establishes a standardized framework for parameterizing bacterial membrane components, which will greatly improve the studies of bacterial pathogenicity and host-pathogen interactions.