A comment on the reweighting method for accelerated molecular dynamics simulations

Molecular Modeling of Chemosensory Protein 3 from Spodoptera litura and Its Binding Property with Plant Defensive Metabolites

Chemosensory perception in insects involves a broad set of chemosensory proteins (CSPs) that identify the bouquet of chemical compounds present in the external environment and regulate specific behaviors. The current study is focused on the Spodoptera litura (Fabricius) chemosensory-related protein, SlitCSP3, a midgut-expressed CSP, which demonstrates differential gene expression upon different diet intake. There is an intriguing possibility that SlitCSP3 can perceive food-derived chemical signals and modulate insect feeding behavior. We predicted the three-dimensional structure of SlitCSP3 and subsequently performed an accelerated molecular dynamics (aMD) simulation of the best-modeled structure. SlitCSP3 structure has six α-helices arranged as a prism and a hydrophobic binding pocket predominated by leucine and isoleucine. We analyzed the interaction of selected host plant metabolites with the modeled structure of SlitCSP3. Out of two predicted binding pockets in SlitCSP3, the plant-derived defensive metabolites 2-b-D-glucopyranosyloxy-4-hydroxy-7-methoxy-1, 4-benzoxazin-3-one (DIMBOA), 6-Methoxy-2–benzoxazolinone (MBOA), and nicotine were found to interact preferably to the hydrophobic site 1, compared to site 2. The current study provides the potential role of CSPs in recognizing food-derived chemical signals, host-plant specialization, and adaptation to the varied ecosystem. Our work opens new perspectives in designing novel pest-management strategies. It can be further used in the development of CSP-based advanced biosensors.

Accelerated Molecular Dynamics Applied to the Peptaibol Folding Problem

The use of enhanced sampling molecular dynamics simulations to facilitate the folding of proteins is a relatively new approach which has quickly gained momentum in recent years. Accelerated molecular dynamics (aMD) can elucidate the dynamic path from the unfolded state to the near-native state, “flattened” by introducing a non-negative boost to the potential. Alamethicin F30/3 (Alm F30/3), chosen in this study, belongs to the class of peptaibols that are 7–20 residue long, non-ribosomally synthesized, amphipathic molecules that show interesting membrane perturbing activity. The recent studies undertaken on the Alm molecules and their transmembrane channels have been reviewed. Three consecutive simulations of ~900 ns each were carried out where N-terminal folding could be observed within the first 100 ns, while C-terminal folding could only be achieved almost after 800 ns. It took ~1 μs to attain the near-native conformation with stronger potential boost which may take several μs worth of classical MD to produce the same results. The Alm F30/3 hexamer channel was also simulated in an E. coli mimicking membrane under an external electric field that correlates with previous experiments. It can be concluded that aMD simulation techniques are suited to elucidate peptaibol structures and to understand their folding dynamics.

Tripleurin XIIc: Peptide Folding Dynamics in Aqueous and Hydrophobic Environment Mimic Using Accelerated Molecular Dynamics

Peptaibols are a special class of fungal peptides with an acetylated N-terminus and a C-terminal 1,2-amino alcohol along with non-standard amino acid residues. New peptaibols named tripleurins were recently identified from a strain of the filamentous fungal species Trichoderma pleuroti, which is known to cause green mould disease on cultivated oyster mushrooms. To understand the mode of action of these peptaibols, the three-dimensional structure of tripleurin (TPN) XIIc, an 18-mer peptide, was elucidated using an enhanced sampling method, accelerated MD, in water and chloroform solvents. Non-standard residues were parameterized by the Restrained Electrostatic Potential (RESP) charge fitting method. The dihedral distribution indicated towards a right-handed helical formation for TPN XIIc in both solvents. Dihedral angle based principal component analysis revealed a propensity for a slightly bent, helical folded conformation in water solvent, while two distinct conformations were revealed in chloroform: One that folds into highly bent helical structure that resembles a beta-hairpin and another with an almost straight peptide backbone appearing as a rare energy barrier crossing event. The hinge-like movement of the terminals was also observed and is speculated to be functionally relevant. The convergence and efficient sampling is addressed using Cartesian PCA and Kullback-Leibler divergence methods.

From glucose to enantiopure morpholino β-amino acid: a new tool for stabilizing γ-turns in peptides

“Environmentally sustainable” synthesis of a new enantiopure morpholino β-amino acid from glucose: a new tool for exotic peptide architectures.

Prediction of Accurate Binding Modes Using Combination of Classical and Accelerated Molecular Dynamics and Free-Energy Perturbation Calculations: An Application to Toxicity Studies

Estimating the correct binding modes of ligands in protein-ligand complexes is crucial not only in the drug discovery process but also for elucidating potential toxicity mechanisms. In the current paper, we propose a computational modeling workflow using the combination of docking, classical molecular dynamics (cMD), accelerated molecular dynamics (aMD) and free-energy perturbation (FEP+ protocol) for identification of possible ligand binding modes. It was applied for investigation of selected perfluorocarboxyl acids (PFCAs) in the PPARγ nuclear receptor. Although both regular and induced fit docking failed to reproduce the experimentally determined binding mode of the ligands when docked into a non-native X-ray structure, cMD and aMD simulations successfully identified the most probable binding conformations. Moreover, multiple binding modes were identified for all of these compounds and the shorter-chain PFCAs continuously moved between a few energetically favorable binding conformations. On the basis of MD predictions of binding conformations, we applied the default and also redesigned FEP+ sampling protocols, which accurately reproduced experimental differences in the binding energies. Thus, the preliminary MD simulations can also provide helpful information about correct setup of the FEP+ calculations. These results show that the PFCA binding modes were accurately predicted and that the FEP+ protocol can be used to estimate free energies of binding of flexible ligands that are not typical druglike compounds. Our in silico workflow revealed the specific ligand-residue interactions within the ligand binding domain and the main characteristics of the PFCAs, and it was concluded that these compounds are week PPARγ partial agonists. This work also suggests a common pipeline for identification of ligand binding modes, ligand-protein dynamics description, and relative free-energy calculations.

Peptidic Macrocycles - Conformational Sampling and Thermodynamic Characterization

Macrocycles are of considerable interest as highly specific drug candidates, yet they challenge standard conformer generators with their large number of rotatable bonds and conformational restrictions. Here, we present a molecular dynamics-based routine that bypasses current limitations in conformational sampling and extensively profiles the free energy landscape of peptidic macrocycles in solution. We perform accelerated molecular dynamics simulations to capture a diverse conformational ensemble. By applying an energetic cutoff, followed by geometric clustering, we demonstrate the striking robustness and efficiency of the approach in identifying highly populated conformational states of cyclic peptides. The resulting structural and thermodynamic information is benchmarked against interproton distances from NMR experiments and conformational states identified by X-ray crystallography. Using three different model systems of varying size and flexibility, we show that the method reliably reproduces experimentally determined structural ensembles and is capable of identifying key conformational states that include the bioactive conformation. Thus, the described approach is a robust method to generate conformations of peptidic macrocycles and holds promise for structure-based drug design.

Molecular Dynamics Simulation of Tau Peptides for the Investigation of Conformational Changes Induced by Specific Phosphorylation Patterns

The Tau protein plays an important role due to its biomolecular interactions in neurodegenerative diseases. The lack of stable structure and various posttranslational modifications such as phosphorylation at various sites in the Tau protein pose a challenge for many experimental methods that are traditionally used to study protein folding and aggregation. Atomistic molecular dynamics (MD) simulations can help around deciphering relationship between phosphorylation and various intermediate and stable conformations of the Tau protein which occur on longer timescales. This chapter outlines protocols for the preparation, execution, and analysis of all-atom MD simulations of a 21-amino acid-long phosphorylated Tau peptide with the aim of generating biologically relevant structural and dynamic information. The simulations are done in explicit solvent and starting from nearly extended configurations of the peptide. The scaled MD method implemented in AMBER14 was chosen to achieve enhanced conformational sampling in addition to a conventional MD approach, thereby allowing the characterization of folding for such an intrinsically disordered peptide at 293 K. Emphasis is placed on the analysis of the simulation trajectories to establish correlations with NMR data (i.e., chemical shifts and NOEs). Finally, in-depth discussions are provided for commonly encountered problems.

Localization of Millisecond Dynamics: Dihedral Entropy from Accelerated MD

Here, we demonstrate a method to capture local dynamics on a time scale 3 orders of magnitude beyond state-of-the-art simulation approaches. We apply accelerated molecular dynamics simulations for conformational sampling and extract reweighted backbone dihedral distributions. Local dynamics are characterized by torsional probabilities, resulting in residue-wise dihedral entropies. Our approach is successfully validated for three different protein systems of increasing size: alanine dipeptide, bovine pancreatic trypsin inhibitor (BPTI), and the major birch pollen allergen Bet v 1a. We demonstrate excellent agreement of flexibility profiles with both large-scale computer simulations and NMR experiments. Thus, our method provides efficient access to local protein dynamics on extended time scales of high biological relevance.

PPARγ helix 12 exhibits an antagonist conformation

PPARγ activation helix 12 can exist in an antagonist form: evidence from high-throughput accelerated molecular dynamics and metadynamics.