Assessing the Quality of the OPEP Coarse-Grained Force Field

A refined pH-dependent coarse-grained model for peptide structure prediction in aqueous solution

Introduction: Peptides carry out diverse biological functions and the knowledge of the conformational ensemble of polypeptides in various experimental conditions is important for biological applications. All fast dedicated softwares perform well in aqueous solution at neutral pH. Methods: In this study, we go one step beyond by combining the Debye-Hückel formalism for charged-charged amino acid interactions and a coarse-grained potential of the amino acids to treat pH and salt variations. Results: Using the PEP-FOLD framework, we show that our approach performs as well as the machine-leaning AlphaFold2 and TrRosetta methods for 15 well-structured sequences, but shows significant improvement in structure prediction of six poly-charged amino acids and two sequences that have no homologous in the Protein Data Bank, expanding the range of possibilities for the understanding of peptide biological roles and the design of candidate therapeutic peptides.

Molecular Mechanism of Protein Unfolding under Shear: A Lattice Boltzmann Molecular Dynamics Study

Proteins are marginally stable soft-matter entities that can be disrupted using a variety of perturbative stresses, including thermal, chemical, or mechanical ones. Fluid under extreme flow conditions is a possible route to probe the weakness of biomolecules and collect information on the molecular cohesive interactions that secure their stability. Moreover, in many cases, physiological flow triggers the functional response of specialized proteins as occurring in blood coagulation or cell adhesion. We deploy the Lattice Boltzmann molecular dynamics technique based on the coarse-grained model for protein OPEP to study the mechanism of protein unfolding under Couette flow. Our simulations provide a clear view of how structural elements of the proteins are affected by shear, and for the simple study case, the β-hairpin, we exploited the analogy to pulling experiments to quantify the mechanical forces acting on the protein under shear.

Multi-scale simulations of biological systems using the OPEP coarse-grained model

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.

Free-Energy Landscape of the Amino-Terminal Fragment of Huntingtin in Aqueous Solution

The first exon of Huntingtin-a protein with multiple biological functions whose misfolding is related to Huntington's disease-modulates its localization, aggregation, and function within the cell. It is composed of a 17-amino-acid amphipathic segment (Htt17), an amyloidogenic segment of consecutive glutamines (QN), and a proline-rich segment. Htt17 is of fundamental importance: it serves as a membrane anchor to control the localization of huntingtin, it modulates huntingtin's function through posttranslational modifications, and it controls the self-assembly of the amyloidogenic QN segment into oligomers and fibrils. Experimentally, the conformational ensemble of the Htt17 monomer, as well as the impact of the polyglutamine and proline-rich segments, remains, however, mostly uncharacterized at the atomic level due to its intrinsic flexibility. Here, we unveil the free-energy landscape of Htt17, Htt17Q17, and Htt17Q17P11 using Hamiltonian replica exchange combined with well-tempered metadynamics. We characterize the free-energy landscape of these three fragments in terms of a few selected collective variables. Extensive simulations reveal that the free energy of Htt17 is dominated by a broad ensemble of configurations that agree with solution NMR chemical shifts. Addition of Q17 at its carboxy-terminus reduces the extent of the main basin to more extended configurations of Htt17 with lower helix propensity. Also, the aliphatic carbons of Q17 partially sequester the nonpolar amino acids of Htt17. For its part, addition of Q17P11 shifts the overall landscape to a more extended and helical Htt17 stabilized by interactions with Q17 and P11, which almost exclusively form a PPII-helix, as well as by intramolecular H-bonds and salt bridges. Our characterization of Huntingtin's amino-terminus provides insights into the structural origin of its ability to oligomerize and interact with phospholipid bilayers, processes closely linked to the biological functions of this protein.

Multiscale simulation of molecular processes in cellular environments

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Metadynamic metainference: Enhanced sampling of the metainference ensemble using metadynamics

Accurate and precise structural ensembles of proteins and macromolecular complexes can be obtained with metainference, a recently proposed Bayesian inference method that integrates experimental information with prior knowledge and deals with all sources of errors in the data as well as with sample heterogeneity. The study of complex macromolecular systems, however, requires an extensive conformational sampling, which represents a separate challenge. To address such challenge and to exhaustively and efficiently generate structural ensembles we combine metainference with metadynamics and illustrate its application to the calculation of the free energy landscape of the alanine dipeptide.

Protein Simulations in Fluids: Coupling the OPEP Coarse-Grained Force Field with Hydrodynamics

A novel simulation framework that integrates the OPEP coarse-grained (CG) model for proteins with the Lattice Boltzmann (LB) methodology to account for the fluid solvent at mesoscale level is presented. OPEP is a very efficient, water-free and electrostatic-free force field that reproduces at quasi-atomistic detail processes like peptide folding, structural rearrangements, and aggregation dynamics. The LB method is based on the kinetic description of the solvent in order to solve the fluid mechanics under a wide range of conditions, with the further advantage of being highly scalable on parallel architectures. The capabilities of the approach are presented, and it is shown that the strategy is effective in exploring the role of hydrodynamics on protein relaxation and peptide aggregation. The end result is a strategy for modeling systems of thousands of proteins, such as in the case of dense protein suspensions. The future perspectives of the multiscale approach are also discussed.

Testing the transferability of a coarse-grained model to intrinsically disordered proteins

The coarse-grained PLUM model is shown to capture structural and dimerization behaviour of the intrinsically disordered biomineralisation peptide n16N.

Are coarse-grained models apt to detect protein thermal stability? The case of OPEP force field

We present the first investigation of the kinetic and thermodynamic stability of two homologous thermophilic and mesophilic proteins based on the coarse-grained model OPEP. The object of our investigation is a pair of G-domains of relatively large size, 200 amino acids each, with an experimental stability gap of about 40 K. The OPEP force field is able to maintain stable the fold of these relatively large proteins within the hundrend-nanosecond time scale without including external constraints. This makes possible to characterize the conformational landscape of the folded protein as well as to explore the unfolding. In agreement with all-atom simulations used as a reference, we show that the conformational landscape of the thermophilic protein is characterized by a larger number of substates with slower dynamics on the network of states and more resilient to temperature increase. Moreover, we verify the stability gap between the two proteins using replica-exchange simulations and estimate a difference between the melting temperatures of about 23 K, in fair agreement with experiment. The detailed investigation of the unfolding thermodynamics, allows to gain insight into the mechanism underlying the enhanced stability of the thermophile relating it to a smaller heat capacity of unfolding.

Recent advances in transferable coarse-grained modeling of proteins

Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.

The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems

The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.

The power of coarse graining in biomolecular simulations

Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.

Balancing bond, nonbond, and gō-like terms in coarse grain simulations of conformational dynamics

Characterization of the protein conformational landscape remains a challenging problem, whether it concerns elucidating folding mechanisms, predicting native structures or modeling functional transitions. Coarse-grained molecular dynamics simulation methods enable exhaustive sampling of the energetic landscape at resolutions of biological interest. The general utility of structure-based models is reviewed along with their differing levels of approximation. Simple Gō models incorporate attractive native interactions and repulsive nonnative contacts, resulting in an ideal smooth landscape. Non-Gō coarse-grained models reduce the parameter set as needed but do not include bias to any desired native structure. While non-Gō models have achieved limited success in protein coarse-graining, they can be combined with native structured-based potentials to create a balanced and powerful force field. Recent applications of such Gō-like models have yielded insight into complex folding mechanisms and conformational transitions in large macromolecules. The accuracy and usefulness of reduced representations are also revealed to be a function of the mathematical treatment of the intrinsic bonded topology.

Importance of the ion-pair interactions in the OPEP coarse-grained force field: parametrization and validation

We have derived new effective interactions that improve the description of ion-pairs in the OPEP coarse-grained force field without introducing explicit electrostatic terms. The iterative Boltzmann inversion method was used to extract these potentials from all atom simulations by targeting the radial distribution function of the distance between the center of mass of the side-chains. The new potentials have been tested on several systems that differ in structural properties, thermodynamic stabilities and number of ion-pairs. Our modeling, by refining the packing of the charged amino-acids, impacts the stability of secondary structure motifs and the population of intermediate states during temperature folding/unfolding; it also improves the aggregation propensity of peptides. The new version of the OPEP force field has the potentiality to describe more realistically a large spectrum of situations where salt-bridges are key interactions.

PRIMO: A Transferable Coarse-grained Force Field for Proteins

We describe here the PRIMO (PRotein Intermediate Model) force field, a physics-based fully transferable additive coarse-grained potential energy function that is compatible with an all-atom force field for multi-scale simulations. The energy function consists of standard molecular dynamics energy terms plus a hydrogen-bonding potential term and is mainly parameterized based on the CHARMM22/CMAP force field in a bottom-up fashion. The solvent is treated implicitly via the generalized Born model. The bonded interactions are either harmonic or distance-based spline interpolated potentials. These potentials are defined on the basis of all-atom molecular dynamics (MD) simulations of dipeptides with the CHARMM22/CMAP force field. The non-bonded parameters are tuned by matching conformational free energies of diverse set of conformations with that of CHARMM all-atom results. PRIMO is designed to provide a correct description of conformational distribution of the backbone (ϕ/ψ) and side chains (χ1) for all amino acids with a CMAP correction term. The CMAP potential in PRIMO is optimized based on the new CHARMM C36 CMAP. The resulting optimized force field has been applied in MD simulations of several proteins of 36-155 amino acids and shown that the root-mean-squared-deviation of the average structure from the corresponding crystallographic structure varies between 1.80 and 4.03 Å. PRIMO is shown to fold several small peptides to their native-like structures from extended conformations. These results suggest the applicability of the PRIMO force field in the study of protein structures in aqueous solution, structure predictions as well as ab initio folding of small peptides.

Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins

We present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of soluble proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with respective reference structures and all-atom molecular dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their molecular interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resolution. An efficient and robust heuristic algorithm based on particle swarm optimization is used for the derivation of CG parameters via a force-matching procedure. The ability of this protocol to deal with high dimensional search spaces suggests that the extension of this optimization procedure to larger data sets may lead to the generation of a fully transferable CG force field. At the present stage, these electrostatic-consistent CG potentials are easily and efficiently parametrized, show a good degree of transferability, and can be used to simulate soluble proteins or, more interestingly, large macromolecular assemblies for which long all-atom simulations may not be easily affordable.

Large loop conformation sampling using the activation relaxation technique, ART-nouveau method

We present an adaptation of the ART-nouveau energy surface sampling method to the problem of loop structure prediction. This method, previously used to study protein folding pathways and peptide aggregation, is well suited to the problem of sampling the conformation space of large loops by targeting probable folding pathways instead of sampling exhaustively that space. The number of sampled conformations needed by ART nouveau to find the global energy minimum for a loop was found to scale linearly with the sequence length of the loop for loops between 8 and about 20 amino acids. Considering the linear scaling dependence of the computation cost on the loop sequence length for sampling new conformations, we estimate the total computational cost of sampling larger loops to scale quadratically compared to the exponential scaling of exhaustive search methods.

Implementation of a protein reduced point charge model toward molecular dynamics applications

A reduced point charge model was developed in a previous work from the study of extrema in smoothed charge density distribution functions generated from the Amber99 molecular electrostatic potential. In the present work, such a point charge distribution is coupled with the Amber99 force field and implemented in the program TINKER to allow molecular dynamics (MD) simulations of proteins. First applications to two polypeptides that involve α-helix and β-sheet motifs are analyzed and compared to all-atom MD simulations. Two types of coarse-grained (CG)-based trajectories are generated using, on one hand, harmonic bond stretching terms and, on the other hand, distance restraints. Results show that the use of the unrestrained CG conditions are sufficient to preserve most of the secondary structure characteristics but restraints lead to a better agreement between CG and all-atom simulation results such as rmsd, dipole moment, and time-dependent mean square deviation functions.