AlphaFold2 modeling and molecular dynamics simulations of an intrinsically disordered protein.

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations.

Accurate prediction by AlphaFold2 for ligand binding in a reductive dehalogenase and implications for PFAS (per- and polyfluoroalkyl substance) biodegradation.

Despite the success of AlphaFold2 (AF2), it is unclear how AF2 models accommodate for ligand binding. Here, we start with a protein sequence from Acidimicrobiaceae TMED77 (T7RdhA) with potential for catalyzing the degradation of per- and polyfluoroalkyl substances (PFASs). AF2 models and experiments identified T7RdhA as a corrinoid iron-sulfur protein (CoFeSP) which uses a norpseudo-cobalamin (BVQ) cofactor and two Fe4S4 iron-sulfur clusters for catalysis. Docking and molecular dynamics simulations suggest that T7RdhA uses perfluorooctanoic acetate (PFOA) as a substrate, supporting the reported defluorination activity of its homolog, A6RdhA. We showed that AF2 provides processual (dynamic) predictions for the binding pockets of ligands (cofactors and/or substrates). Because the pLDDT scores provided by AF2 reflect the protein native states in complex with ligands as the evolutionary constraints, the Evoformer network of AF2 predicts protein structures and residue flexibility in complex with the ligands, i.e., in their native states. Therefore, an apo-protein predicted by AF2 is actually a holo-protein awaiting ligands.

Agave REVEILLE1 regulates the onset and release of seasonal dormancy in Populus.

Deciduous woody plants like poplar (Populus spp.) have seasonal bud dormancy. It has been challenging to simultaneously delay the onset of bud dormancy in the fall and advance bud break in the spring, as bud dormancy, and bud break were thought to be controlled by different genetic factors. Here, we demonstrate that heterologous expression of the REVEILLE1 gene (named AaRVE1) from Agave (Agave americana) not only delays the onset of bud dormancy but also accelerates bud break in poplar in field trials. AaRVE1 heterologous expression increases poplar biomass yield by 166% in the greenhouse. Furthermore, we reveal that heterologous expression of AaRVE1 increases cytokinin contents, represses multiple dormancy-related genes, and up-regulates bud break-related genes, and that AaRVE1 functions as a transcriptional repressor and regulates the activity of the DORMANCY-ASSOCIATED PROTEIN 1 (DRM1) promoter. Our findings demonstrate that AaRVE1 appears to function as a regulator of bud dormancy and bud break, which has important implications for extending the growing season of deciduous trees in frost-free temperate and subtropical regions to increase crop yield.

Molecular Dynamics Investigation into pH Dependent Metal Binding of the Intrinsically Disordered Worm Jaw Protein, Nvjp-1.

Sclerotization of the Nereis virens jaw is mediated by metal binding to the histidine-rich jaw protein, Nvjp-1. Previous studies showed that the mechanical properties of Nvjp-1 hydrogels could be modulated with zinc binding as well as the associated anion. Here, we show that the mechanical properties of Nvjp-1 hydrogels can be modulated by pH and that zinc binding to Nvjp-1 is stable at both acidic and alkaline pH conditions. To probe the mechanism of Zn2+ binding to Nvjp-1 at different pH conditions, we utilized all atom molecular dynamics simulations employing a polarizable force field. At low pH conditions, polar residues predominantly interacted with Zn2+, with at most two residues interacting with a given zinc ion. Surprisingly, little to no Zn2+ binding was observed with the abundant Nvjp-1 acidic residues, which form salt-bridges with the protonated histidines to effectively block their binding to Zn2+ ions. As the pH was shifted to alkaline conditions, Zn2+ binding residues reconfigured to form additional coordination bonds with histidine, resulting in a reduction in the radius of gyration that correlated with hydrogel sclerotization. Furthermore, acetate ions were shown to facilitate the capture of zinc ions through association with protonated histidines at low pH, freeing acidic residues to interact with Zn2+ ions and increasing the number of Zn2+ ions that diffuse into the Nvjp-1 interior. Thus, these studies provide valuable molecular insights into how amino acid residues in Nvjp-1 manage metal salt binding and coordination in hydrogels as a function of the pH and ionic environments.

AlphaFold2 models indicate that protein sequence determines both structure and dynamics.

AlphaFold 2 (AF2) has placed Molecular Biology in a new era where we can visualize, analyze and interpret the structures and functions of all proteins solely from their primary sequences. We performed AF2 structure predictions for various protein systems, including globular proteins, a multi-domain protein, an intrinsically disordered protein (IDP), a randomized protein, two larger proteins (> 1000 AA), a heterodimer and a homodimer protein complex. Our results show that along with the three dimensional (3D) structures, AF2 also decodes protein sequences into residue flexibilities via both the predicted local distance difference test (pLDDT) scores of the models, and the predicted aligned error (PAE) maps. We show that PAE maps from AF2 are correlated with the distance variation (DV) matrices from molecular dynamics (MD) simulations, which reveals that the PAE maps can predict the dynamical nature of protein residues. Here, we introduce the AF2-scores, which are simply derived from pLDDT scores and are in the range of [0, 1]. We found that for most protein models, including large proteins and protein complexes, the AF2-scores are highly correlated with the root mean square fluctuations (RMSF) calculated from MD simulations. However, for an IDP and a randomized protein, the AF2-scores do not correlate with the RMSF from MD, especially for the IDP. Our results indicate that the protein structures predicted by AF2 also convey information of the residue flexibility, i.e., protein dynamics.

Ab initio molecular dynamics modeling of single polyethylene chains: Scission kinetics and influence of radical under mechanical strain.

Ab initio molecular dynamics was used to estimate the response to constant imposed strain on a short polyethylene (PE) chain and a radical chain with a removed hydrogen atom. Two independent types of simulations were run. In the first case, the chains were strained by expanding a periodic cell, restraining the length but allowing the internal degrees of freedom to reach equilibrium. From these simulations, the average force on the chain was computed, and the resulting force was integrated to determine the Helmholtz free energy for chain stretching. In the second set of simulations, chains were constrained to various lengths, while a bond was restrained at various bond lengths using umbrella sampling. This provided free energy of bond scission for various chain strains. The sum of the two free energy functions results in an approximation of the free energy of chain scission under various strains and gives a realistic and new picture of the effect of chain strain on bond breaking. Unimolecular scission rates for each chain type were examined as a function of chain strain. The scission rate for the radical chain is several orders of magnitude larger than that of the pristine chain at smaller strains and at equilibrium. This highlights the importance of radical formation in PE rupture and is consistent with experiments. Constant strain results were used to derive a constant-force model for the radical chain that demonstrates a roll over in rate similar to the "catch-bond" behavior observed in protein membrane detachment experiments.

On the Nature of Epoxy Resin Post-Curing.

Post-curing is intended to improve strength, elevate glass transition, and reduce residual stress and outgassing in thermosets. Also, experiments indicate post-curing temperatures lead to ether crosslinks and backbone dehydration. These results informed molecular dynamics methods to represent them and compare the resulting thermomechanical effects. Diglycidyl ether of bisphenol A (DGEBA)-diamino diphenyl sulfone (DDS) systems were examined. Independent variables were resin length, stoichiometry, and reaction type (i.e., amine addition, etherification, and dehydration). Etherification affected excess epoxide systems most. These were strengthened and became strain hardening. Systems which were both etherified and dehydrated were most consistent with results of post-curing experiments. Dehydration stiffened and strengthened systems with the longer resin molecules due to their intermediate hydroxyl groups for crosslinking. Changes in the concavity of functions fit to the specific volume versus temperature were used to detect thermal transitions. Etherification generally increased transition temperatures. Dehydration resulted in more transitions.

Prediction of the Wetting Behavior of Active and Hole-Transport Layers for Printed Flexible Electronic Devices Using Molecular Dynamics Simulations.

Molecular dynamics (MD) simulations were used to predict the wetting behavior of materials typical of active and hole-transport layers in organic electronics by evaluating their contact angles and adhesion energies. The active layer (AL) here consists of a blend of poly(3-hexylthiophene) and phenyl-C61-butyric acid methyl ester (P3HT:PCBM), whereas the hole-transport layer (HTL) consists of a blend of poly(3,4-ethylenedioxythiophene) and poly(styrenesulfonate) (PEDOT:PSS). Simulations of the wetting of these surfaces by multiple solvents show that formamide, glycerol, and water droplet contact angle trends correlate with experimental values. However, droplet simulations on surfaces are computationally expensive and would be impractical for routine use in printed electronics and other applications. As an alternative, contact angle measurements can be related to adhesion energy, which can be calculated more quickly and easily from simulations and has been shown to correlate with contact angles. Calculations of adhesion energy for 16 different solvents were used to rapidly predict the wetting behavior of solvents on the AL and HTL surfaces. Among the tested solvents, pentane and hexane exhibit low and similar adhesion energy on both of the surfaces considered. This result suggests that among the tested solvents, pentane and hexane exhibit strong potential as orthogonal solvent in printing electronic materials onto HTL and AL materials. The simulation results further show that MD can accelerate the evaluation of processing parameters for printed electronics.

Bond breaking in epoxy systems: A combined QM/MM approach.

A novel method to combine quantum mechanics (QM) and molecular mechanics has been developed to accurately and efficiently account for covalent bond breaking in polymer systems under high strain without the use of predetermined break locations. Use of this method will provide a better fundamental understanding of the mechano-chemical origins of fracture in thermosets. Since classical force fields cannot accurately account for bond breaking, and QM is too demanding to simulate large systems, a hybrid approach is required. In the method presented here, strain is applied to the system using a classical force field, and all bond lengths are monitored. When a bond is stretched past a threshold value, a zone surrounding the bond is used in a QM energy minimization to determine which, if any, bonds break. The QM results are then used to reconstitute the system to continue the classical simulation at progressively larger strain until another QM calculation is triggered. In this way, a QM calculation is only computed when and where needed, allowing for efficient simulations. A robust QM method for energy minimization has been determined, as well as appropriate values for the QM zone size and the threshold bond length. Compute times do not differ dramatically from classical molecular mechanical simulations.

Computation of the binding free energy of peptides to graphene in explicit water.

The characteristic properties of graphene make it useful in an assortment of applications. One particular application--the use of graphene in biosensors--requires a thorough understanding of graphene-peptide interactions. In this study, the binding of glycine (G) capped amino acid residues (termed GXG tripeptides) to trilayer graphene surfaces in aqueous solution was examined and compared to results previously obtained for peptide binding to single-layer free-standing graphene [A. N. Camden, S. A. Barr, and R. J. Berry, J. Phys. Chem. B 117, 10691-10697 (2013)]. In order to understand the interactions between the peptides and the surface, binding enthalpy and free energy values were calculated for each GXG system, where X cycled through the typical 20 amino acids. When the GXG tripeptides were bound to the surface, distinct conformations were observed, each with a different binding enthalpy. Analysis of the binding energy showed the binding of peptides to trilayer graphene was dominated by van der Waals interactions, unlike the free-standing graphene systems, where the binding was predominantly electrostatic in nature. These results demonstrate the utility of computational materials science in the mechanistic explanation of surface-biomolecule interactions which could be applied to a wide range of systems.

Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach.

Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.

Simulations of peptide-graphene interactions in explicit water.

The interaction of graphene with biomolecules has a variety of useful applications. In particular, graphitic surfaces decorated with peptides are being considered for high performance biochemical sensors. The interaction of peptides with graphene can also provide insight into the binding behavior of larger biomolecules. In this investigation, we have computed the binding enthalpies of a series of GXG tripeptides with graphene using classical molecular dynamics. Explicit water molecules were included to capture the effect of solvent. Of the twenty amino acid residues examined (X in GXG), arginine, glutamine, and asparagine exhibit the strongest interactions with graphene. Analysis of the trajectories shows that the presence of graphene affects the peptide conformation relative to its conformation in solution. We also find that the peptides favor the graphene interface predominantly due to the influence of the solvent, with hydrophilic residues binding more strongly than hydrophobic residues. These results demonstrate the need to include explicit solvent atoms when modeling peptide-graphene systems to mimic experimental conditions. Furthermore, the scheme outlined herein may be widely applicable for the determination and validation of surface interaction parameters for a host of molecular fragments using a variety of techniques, ranging from coarse-grained models to quantum mechanical methods.

Chemistry of aqueous silica nanoparticle surfaces and the mechanism of selective peptide adsorption.

Control over selective recognition of biomolecules on inorganic nanoparticles is a major challenge for the synthesis of new catalysts, functional carriers for therapeutics, and assembly of renewable biobased materials. We found low sequence similarity among sequences of peptides strongly attracted to amorphous silica nanoparticles of various size (15-450 nm) using combinatorial phage display methods. Characterization of the surface by acid base titrations and zeta potential measurements revealed that the acidity of the silica particles increased with larger particle size, corresponding to between 5% and 20% ionization of silanol groups at pH 7. The wide range of surface ionization results in the attraction of increasingly basic peptides to increasingly acidic nanoparticles, along with major changes in the aqueous interfacial layer as seen in molecular dynamics simulation. We identified the mechanism of peptide adsorption using binding assays, zeta potential measurements, IR spectra, and molecular simulations of the purified peptides (without phage) in contact with uniformly sized silica particles. Positively charged peptides are strongly attracted to anionic silica surfaces by ion pairing of protonated N-termini, Lys side chains, and Arg side chains with negatively charged siloxide groups. Further, attraction of the peptides to the surface involves hydrogen bonds between polar groups in the peptide with silanol and siloxide groups on the silica surface, as well as ion-dipole, dipole-dipole, and van-der-Waals interactions. Electrostatic attraction between peptides and particle surfaces is supported by neutralization of zeta potentials, an inverse correlation between the required peptide concentration for measurable adsorption and the peptide pI, and proximity of cationic groups to the surface in the computation. The importance of hydrogen bonds and polar interactions is supported by adsorption of noncationic peptides containing Ser, His, and Asp residues, including the formation of multilayers. We also demonstrate tuning of interfacial interactions using mutant peptides with an excellent correlation between adsorption measurements, zeta potentials, computed adsorption energies, and the proposed binding mechanism. Follow-on questions about the relation between peptide adsorption on silica nanoparticles and mineralization of silica from peptide-stabilized precursors are raised.

Derivation of class II force fields. VIII. Derivation of a general quantum mechanical force field for organic compounds.

A class II valence force field covering a broad range of organic molecules has been derived employing ab initio quantum mechanical "observables." The procedure includes selecting representative molecules and molecular structures, and systematically sampling their energy surfaces as described by energies and energy first and second derivatives with respect to molecular deformations. In this article the procedure for fitting the force field parameters to these energies and energy derivatives is briefly reviewed. The application of the methodology to the derivation of a class II quantum mechanical force field (QMFF) for 32 organic functional groups is then described. A training set of 400 molecules spanning the 32 functional groups was used to parameterize the force field. The molecular families comprising the functional groups and, within each family, the torsional angles used to sample different conformers, are described. The number of stationary points (equilibria and transition states) for these molecules is given for each functional group. This set contains 1324 stationary structures, with 718 minimum energy structures and 606 transition states. The quality of the fit to the quantum data is gauged based on the deviations between the ab initio and force field energies and energy derivatives. The accuracy with which the QMFF reproduces the ab initio molecular bond lengths, bond angles, torsional angles, vibrational frequencies, and conformational energies is then given for each functional group. Consistently good accuracy is found for these computed properties for the various types of molecules. This demonstrates that the methodology is broadly applicable for the derivation of force field parameters across widely differing types of molecular structures. Copyright 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1782-1800, 2001