Intrinsically disordered protein-specific force field CHARMM36IDPSFF

Refined Bonded Terms in Coarse-Grained Models for Intrinsically Disordered Proteins Improve Backbone Conformations

Coarse-grained models designed for intrinsically disordered proteins and regions (IDP/Rs) usually omit some bonded potentials (e.g., angular and dihedral potentials) as a conventional strategy to enhance backbone flexibility. However, a notable drawback of this approach is the generation of inaccurate backbone conformations. Here, we addressed this problem by introducing residue-specific angular, refined dihedral, and correction map (CMAP) potentials, derived based on the statistics from a customized coil database. These bonded potentials were integrated into the existing Mpipi model, resulting in a new model, denoted as the "Mpipi+" model. Results show that the Mpipi+ model can improve backbone conformations. More importantly, it can markedly improve the secondary structure propensity (SSP) based on the experimental chemical shift and, consequently, succeed in capturing transient secondary structures. Moreover, the Mpipi+ model preserves the liquid-liquid phase separation (LLPS) propensities of IDPs.

On the Validation of Protein Force Fields Based on Structural Criteria

Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.

Elucidating the Membrane Binding Process of a Disordered Protein: Dynamic Interplay of Anionic Lipids and the Polybasic Region

Intrinsically disordered regions of proteins are responsible for many biological processes such as in the case of liver kinase B1 (LKB1)-a serine/threonine kinase relevant for cell proliferation and cell polarity. LKB1 becomes fully activated upon recruitment to the plasma membrane by binding of its disordered C-terminal polybasic motif consisting of eight lysines/arginines to phospholipids. Here, we present extensive molecular dynamics (MD) simulations of the polybasic motif interacting with a model membrane composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleyl phosphatidic acid (PA) and cell culture experiments. Protein-membrane binding effects are due to the electrostatic interactions between the polybasic amino acids and PAs. For significant binding, the first three lysines turn out to be dispensable, which was also recapitulated in cell culture using transfected GFP-LKB1 variants. LKB1-membrane binding results in nonmonotonous changes in the structure of the protein as well as the membrane, in particular, accumulation of PAs and reduced thickness at the protein-membrane contact area. The protein-lipid binding turns out to be highly dynamic due to an interplay of PA-PA repulsion and protein-PA attraction. The thermodynamics of this interplay is captured by a statistical fluctuation model, which allows the estimation of both energies. Quantification of the significance of each polar amino acid in the polybasic provides detailed insights into the molecular mechanism of protein-membrane binding of LKB1. These results can likely be transferred to other proteins, which interact by intrinsically disordered polybasic regions with anionic membranes.

Comprehensive Comparison and Critical Assessment of RNA-Specific Force Fields

Molecular dynamics simulations play a pivotal role in elucidating the dynamic behaviors of RNA structures, offering a valuable complement to traditional methods such as nuclear magnetic resonance or X-ray. Despite this, the current precision of RNA force fields lags behind that of protein force fields. In this work, we systematically compared the performance of four RNA force fields (ff99bsc0χOL3, AMBERDES, ff99OL3_CMAP1, AMBERMaxEnt) across diverse RNA structures. Our findings highlight significant challenges in maintaining stability, particularly with regard to cross-strand and cross-loop hydrogen bonds. Furthermore, we observed the limitations in accurately describing the conformations of nonhelical structural motif, terminal nucleotides, and also base pairing and base stacking interactions by the tested RNA force fields. The identified deficiencies in existing RNA force fields provide valuable insights for subsequent force field development. Concurrently, these findings offer recommendations for selecting appropriate force fields in RNA simulations.

Balanced Three-Point Water Model OPC3-B for Intrinsically Disordered and Ordered Proteins

Intrinsically disordered proteins (IDPs) play a critical role in many biological processes. Due to the inherent structural flexibility of IDPs, experimental methods present significant challenges for sampling their conformational information at the atomic level. Therefore, molecular dynamics (MD) simulations have emerged as the primary tools for modeling IDPs whose accuracy depend on force field and water model. To enhance the accuracy of physical modeling of IDPs, several force fields have been developed. However, current water models lack precision and underestimate the interaction between water molecules and proteins. Here, we used Monte-Carlo re-weighting method to re-parameterize a three-point water model based on OPC3 for IDPs (named OPC3-B). We benchmarked the performance of OPC3-B compared with nine different water models for 10 IDPs and three ordered proteins. The results indicate that the performance of OPC3-B is better than other water models for both IDPs and ordered proteins. At the same time, OPC3-B possess the power of transferability with other force field to simulate IDPs. This newly developed water model can be used to insight into the research of sequence-disordered-function paradigm for IDPs.

Toward a general neural network force field for protein simulations: Refining the intramolecular interaction in protein

Molecular dynamics (MD) is an extremely powerful, highly effective, and widely used approach to understanding the nature of chemical processes in atomic details for proteins. The accuracy of results from MD simulations is highly dependent on force fields. Currently, molecular mechanical (MM) force fields are mainly utilized in MD simulations because of their low computational cost. Quantum mechanical (QM) calculation has high accuracy, but it is exceedingly time consuming for protein simulations. Machine learning (ML) provides the capability for generating accurate potential at the QM level without increasing much computational effort for specific systems that can be studied at the QM level. However, the construction of general machine learned force fields, needed for broad applications and large and complex systems, is still challenging. Here, general and transferable neural network (NN) force fields based on CHARMM force fields, named CHARMM-NN, are constructed for proteins by training NN models on 27 fragments partitioned from the residue-based systematic molecular fragmentation (rSMF) method. The NN for each fragment is based on atom types and uses new input features that are similar to MM inputs, including bonds, angles, dihedrals, and non-bonded terms, which enhance the compatibility of CHARMM-NN to MM MD and enable the implementation of CHARMM-NN force fields in different MD programs. While the main part of the energy of the protein is based on rSMF and NN, the nonbonded interactions between the fragments and with water are taken from the CHARMM force field through mechanical embedding. The validations of the method for dipeptides on geometric data, relative potential energies, and structural reorganization energies demonstrate that the CHARMM-NN local minima on the potential energy surface are very accurate approximations to QM, showing the success of CHARMM-NN for bonded interactions. However, the MD simulations on peptides and proteins indicate that more accurate methods to represent protein-water interactions in fragments and non-bonded interactions between fragments should be considered in the future improvement of CHARMM-NN, which can increase the accuracy of approximation beyond the current mechanical embedding QM/MM level.

Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm

Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.

Phosphorylation Modification Force Field FB18CMAP Improving Conformation Sampling of Phosphoproteins

Phosphorylation of proteins plays an important regulatory role at almost all levels of cellular organization. Molecular dynamics (MD) simulation is a promising tool to reveal the mechanism of how phosphorylation regulates many key biological processes at the atomistic level. MD simulation accuracy depends on force field precision, while the current force fields for phospho-amino acids have resulted in notable inconsistency with experimental data. Here, a new force field parameter (named FB18CMAP) is generated by fitting against quantum mechanics (QM) energy in aqueous solution with φ/ψ dihedral potential-energy surfaces optimized using CMAP parameters. MD simulations of phosphorylated dipeptides, intrinsically disordered proteins (IDPs), and ordered (folded) proteins show that FB18CMAP can mimic NMR observables and structural characteristics of phosphorylated dipeptides and proteins more accurately than the FB18 force field. These findings suggest that FB18CMAP performs well in both the simulation of ordered and disordered states of phosphorylated proteins.

Influence of force field choice on the conformational landscape of rat and human islet amyloid polypeptide

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.

Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning

Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabetes, and other diseases. Experimental methods can hardly capture the ensemble of diverse conformations for IDPs. Molecular dynamics (MD) simulations can sample continuous conformations that might provide a valuable complement to experimental data. However, the accuracy of MD simulations depends on the quality of force field. In particular, the evolutionary conservation and coevolution of IDPs introduce that current force fields could not precisely reproduce the conformation of IDPs. In order to improve the performance of force field, deep learning and reweighting methods were used to automatically generate personal force field parameters for intrinsically disordered and ordered proteins. At first, the deep learning method predicted more accuracy φ/ψ dihedral of residue than the previous method. Then, reweighting optimized the personal force field parameters for each residue. Finally, typical representative systems such as IDPs, structure protein, and fast-folding protein were used to evaluate this force field. The results indicate that two personal force field parameters (named PPFF1 and PPFF1_af2) could better reproduce the experimental observables than ff03CMAP force field. In summary, this strategy will provide feasibility for the development of precise personal force fields.

Concerted enhanced-sampling simulations to elucidate the helix-fibril transition pathway of intrinsically disordered α-Synuclein

Fibril formation of α-synuclein is linked with Parkinson's disease. The intrinsically disordered nature of α-syn provides extensive conformational plasticity and becomes difficult to characterize its transition pathway from native monomeric to disease-associated fibril form. We implemented different simulation methods such as steered dynamics-umbrella sampling, and replica-exchange and conventional MD simulations to access various conformational states of α-syn. Nineteen distinct intermediate structures were identified by free energy landscape and cluster analysis. They were then sorted based on secondary structure and solvent exposure of fibril-core residues to illustrate the fibril dissociation pathway. The analysis showed that following the initial dissociation of the polypeptide chain from the fibril, α-syn might form either compact-conformations by long-range interactions or extended-conformations stabilized by local interactions. This leads α-syn to adapt two different pathways. The secondary structure, solvation, contact distance, interaction energies and backbone dihedrals of thirty-two selected residues were analyzed for all the 19 intermediates. The results suggested that formation of β-turns, reorganization of salt bridges, and dihedral changes in the hydrophobic regions are the major driving forces for helix-fibril transition. Structural features of the intermediates also correlated with the earlier experimental and computational studies. The study provides critical information on the fibrillation pathway of α-syn.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

Performance evaluation of the balanced force field ff03CMAP for intrinsically disordered and ordered proteins

Intrinsically disordered proteins (IDPs) have been found to be closely associated with various human diseases. Because IDPs have no fixed tertiary structure under physiological conditions, current experimental methods, such as X-ray spectroscopy, NMR, and CryoEM, cannot capture all the dynamic conformations. Molecular dynamics simulation is an useful tool that is widely used to study the conformer distributions of IDPs and has become an important complementary tool for experimental methods. However, the accuracy of MD simulations directly depends on utilizing a precise force field. Recently a CMAP optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of IDPs and folded proteins. In order to further evaluate the performance, more types of disordered and ordered proteins were used to test the ability for conformer sampling. The results showed that simulated chemical shifts, J-coupling, and R_g distribution with the ff03CMAP force field were in better agreement with NMR measurements and were more accurate than those with the ff03 force field. The sampling conformations by ff03CMAP were more diverse than those of ff03. At the same time, ff03CMAP could stabilize the conformers of the ordered proteins. These findings indicate that ff03CMAP can be widely used to sample diverse conformers for proteins, including the intrinsically disordered regions.

Molecular dynamics simulations of the adsorption of an intrinsically disordered protein: Force field and water model evaluation in comparison with experiments

This study investigates possible structural changes of an intrinsically disordered protein (IDP) when it adsorbs to a solid surface. Experiments on IDPs primarily result in ensemble averages due to their high dynamics. Therefore, molecular dynamics (MD) simulations are crucial for obtaining more detailed information on the atomistic and molecular levels. An evaluation of seven different force field and water model combinations have been applied: (A) CHARMM36IDPSFF + CHARMM-modified TIP3P, (B) CHARMM36IDPSFF + TIP4P-D, (C) CHARMM36m + CHARMM-modified TIP3P, (D) AMBER99SB-ILDN + TIP3P, (E) AMBER99SB-ILDN + TIP4P-D, (F) AMBERff03ws + TIP4P/2005, and (G) AMBER99SB-disp + disp-water. The results have been qualitatively compared with those of small-angle X-ray scattering, synchrotron radiation circular dichroism spectroscopy, and attenuated total reflectance Fourier transform infrared spectroscopy. The model IDP corresponds to the first 33 amino acids of the N-terminal of the magnesium transporter A (MgtA) and is denoted as KEIF. With a net charge of +3, KEIF is found to adsorb to the anionic synthetic clay mineral Laponite^® due to the increase in entropy from the concomitant release of counterions from the surface. The experimental results show that the peptide is largely disordered with a random coil conformation, whereas the helical content (α- and/or 3₁₀-helices) increased upon adsorption. MD simulations corroborate these findings and further reveal an increase in polyproline II helices and an extension of the peptide conformation in the adsorbed state. In addition, the simulations provided atomistic resolution of the adsorbed ensemble of structures, where the arginine residues had a high propensity to form hydrogen bonds with the surface. Simulations B, E, and G showed significantly better agreement with experiments than the other simulations. Particularly noteworthy is the discovery that B and E with TIP4P-D water had superior performance to their corresponding simulations A and D with TIP3P-type water. Thus, this study shows the importance of the water model when simulating IDPs and has also provided an insight into the structural changes of surface-active IDPs induced by adsorption, which may play an important role in their function.

Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization

Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.

Balanced Force Field ff03CMAP Improving the Dynamics Conformation Sampling of Phosphorylation Site

Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins.

Base-specific RNA force field improving the dynamics conformation of nucleotide

RNA plays a key role in numerous biological processes. Traditional experimental methods have difficulties capturing the structure and dynamic conformation of RNA. Thus, Molecular dynamic simulations (MDs) has become an essential complementary for RNA experiment. However, state-of-the-art RNA force fields have two major limitations of overestimation base stacking propensity and generation of a high ratio of intercalated conformations. Therefore, a two-step strategy was used to optimize the parameters of ff99bsc0χOL3 (named BSFF1) to improve these limitations, which as well adjusted the unbonded parameters of nucleobase heavy atoms and added ζ/α grid-based energy correction map energy term with reweighting. MD simulations of tetranucleotides indicate that BSFF1 can significantly decrease the ratio of intercalated conformations. Tests of single-strand RNA and kink-turn show that BSFF1 force field can reproduce more accurate conformers than ff99bsc0χOL3 force field. BSFF1 can also stabilize the conformers of duplex and riboswitch. The successful ab initio folding of tetraloop further supports the performance of BSFF1. These findings confirm that the newly developed force field BSFF1 can improve the conformer sampling of RNA.

Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15N spin relaxation, without the need for reweighting. Further inspection revealed that 10-20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.

Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields

The development of accurate protein force fields has been the cornerstone of molecular simulations for the past 50 years. During this period, many lessons have been learned regarding the use of experimental target data and parameter fitting procedures. Here, we review recent advances in protein force field development. We discuss the recent emergence of polarizable force fields and the role of electronic polarization and areas in which additive force fields fall short. The use of automated fitting methods and the inclusion of additional experimental solution data during parametrization is discussed as a means to highlight possible routes to improve the accuracy of force fields even further.

Multiscale Computational Study of the Conformation of the Full-Length Intrinsically Disordered Protein MeCP2

The malfunction of the methyl-CpG binding protein 2 (MeCP2) is associated with the Rett syndrome, one of the most common causes of cognitive impairment in females. MeCP2 is an intrinsically disordered protein (IDP), making its experimental characterization a challenge. There is currently no structure available for the full-length MeCP2 in any of the databases, and only the structure of its MBD domain has been solved. We used this structure to build a full-length model of MeCP2 by completing the rest of the protein via ab initio modeling. Using a combination of all-atom and coarse-grained simulations, we characterized its structure and dynamics as well as the conformational space sampled by the ID and transcriptional repression domain (TRD) domains in the absence of the rest of the protein. The present work is the first computational study of the full-length protein. Two main conformations were sampled in the coarse-grained simulations: a globular structure similar to the one observed in the all-atom force field and a two-globule conformation. Our all-atom model is in good agreement with the available experimental data, predicting amino acid W104 to be buried, amino acids R111 and R133 to be solvent-accessible, and having a 4.1% α-helix content, compared to the 4% found experimentally. Finally, we compared the model predicted by AlphaFold to our Modeller model. The model was not stable in water and underwent further folding. Together, these simulations provide a detailed (if perhaps incomplete) conformational ensemble of the full-length MeCP2, which is compatible with experimental data and can be the basis of further studies, e.g., on mutants of the protein or its interactions with its biological partners.

Early aggregation mechanism of Aβ16-22 revealed by Markov state models

Aβ_16-22 is believed to have critical role in early aggregation of full length amyloids that are associated with the Alzheimer's disease and can aggregate to form amyloid fibrils. However, the early aggregation mechanism is still unsolved. Here, multiple long-term molecular dynamics simulations combining with Markov state model were used to probe the early oligomerization mechanism of Aβ_16-22 peptides. The identified dimeric form adopted either globular random-coil or extended β-strand like conformations. The observed dimers of these variants shared many overall conformational characteristics but differed in several aspects at detailed level. In all cases, the most common type of secondary structure was intermolecular antiparallel β-sheets. The inter-state transitions were very frequent ranges from few to hundred nanoseconds. More strikingly, those states which contain fraction of β secondary structure and significant amount of extended coiled structures, therefore exposed to the solvent, were majorly participated in aggregation. The assembly of low-energy dimers, in which the peptides form antiparallel β sheets, occurred by multiple pathways with the formation of an obligatory intermediates. We proposed that these states might facilitate the Aβ_16-22 aggregation through a significant component of the conformational selection mechanism, because they might increase the aggregates population by promoting the inter-chain hydrophobic and the hydrogen bond contacts. The formation of early stage antiparallel β sheet structures is critical for oligomerization, and at the same time provided a flat geometry to seed the ordered β-strand packing of the fibrils. Our findings hint at reorganization of this part of the molecule as a potentially critical step in Aβ aggregation and will insight into early oligomerization for large β amyloids.

RNA-Specific Force Field Optimization with CMAP and Reweighting

RNA plays a key role in a variety of cell activities. However, it is difficult to capture its structure dynamics by the traditional experimental methods because of the inherent limitations. Molecular dynamics simulation has become a valuable complement to the experimental methods. Previous studies have indicated that the current force fields cannot accurately reproduce the conformations and structural dynamics of RNA. Therefore, an RNA-specific force field was developed to improve the conformation sampling of RNA. The distribution of ζ/α dihedrals of tetranucleotides was optimized by a reweighting method, and the grid-based energy correction map (CMAP) term was first introduced into the Amber RNA force field of ff99bsc0χOL3, named ff99OL3_CMAP1. Extensive validations of tetranucleotides and tetraloops show that ff99OL3_CMAP1 can significantly decrease the population of an incorrect structure, increase the consistency between the simulation results and experimental values for tetranucleotides, and improve the stability of tetraloops. ff99OL3_CMAP1 can also precisely reproduce the conformation of a duplex and riboswitches. These findings confirm that the newly developed force field ff99OL3_CMAP1 can improve the conformer sampling of RNA.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Physics of biomolecular recognition and conformational dynamics

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Balanced Solvent Model for Intrinsically Disordered and Ordered Proteins

Intrinsically disordered proteins (IDPs) have no fixed three-dimensional (3D) structures under physiological conditions, with the content being about 51% in human proteomics. IDPs are associated with many human diseases, such as cancer, diabetes, and neurodegenerative diseases. Because IDPs do not crystallize and have diverse conformers, traditional experimental methods such as crystallization and NMR can hardly capture their conformation ensemble and just provide average structural characters of IDPs. Therefore, molecular dynamics (MD) simulations become a valuable complement to the experimental data. However, the accuracy of molecular dynamics simulation for IDPs depends on the combination of force fields and solvent models. Recently, we released an environment-specific force field (ESFF1) for IDPs, which can well reproduce the local structural properties (such as J-coupling and secondary chemical shifts). However, there is still a large deviation for the radius of gyration (R_g). Therefore, a solvent model combined with ESFF1 is necessary to capture the local and global characters for IDPs and ordered proteins. Here, we investigated the underestimation or overestimation of the solvent interaction for four solvent models (TIP3P, TIP4P-Ew, TIP4P-D, OPC) under ESFF1 and found the important ε parameter of the solvent model to play a key role in scaling R_g. A near-linear relationship between the simulation R_g and the ε parameter was used to develop the new solvent model, named TIP4P-B. The results indicate that the simulated R_g with TIP4P-B is in better agreement with the experimental observations than the other four solvent models. Simultaneously, TIP4P-B can also maintain the advantages of the ESFF1 force field for the local structural properties. Additionally, TIP4P-B can successfully sample the conformation of ordered proteins. These findings confirm that TIP4P-B is a balanced solvent model and can improve sampling R_g performance for folded proteins and IDPs.

Force Field Effects in Simulations of Flexible Peptides with Varying Polyproline II Propensity

Five peptides previously suggested to possess polyproline II (PPII) structure have here been investigated by using atomistic molecular dynamics simulations to compare how well four different force fields known for simulating intrinsically disordered proteins relatively well (Amber ff99SB-disp, Amber ff99SB-ILDN, CHARM36IDPSFF, and CHARMM36m) can capture this secondary structure element. The results revealed that all force fields sample PPII structures but to different extents and with different propensities toward other secondary structure elements, in particular, the β-sheet and "random coils". A cluster analysis of the simulations of histatin 5 also revealed that the conformational ensembles of the force fields are quite different. We compared the simulations to circular dichroism and nuclear magnetic resonance spectroscopy experiments and conclude that further experiments and methods for interpreting them are needed to assess the accuracy of force fields in determining PPII structure.

Catalytic mechanism of butane anaerobic oxidation for alkyl-coenzyme M reductase

Methane is among the most potent of the greenhouse gases, which plays a key role in global climate change. As an excellent carbon and energy source, methane can be utilized by anaerobic methane oxidizing archaea and aerobic methane oxidizing bacteria. The previous work shows that an anaerobic thermophilic enrichment culture composed of dense consortia of archaea and bacteria apparently uses partly similar pathways to oxidize the C4 hydrocarbon butane. However, the catalytic mechanism of butane anaerobic oxidation for alkyl-coenzyme M reductase is still unknown. Therefore, molecular dynamics (MD) simulation was used to investigate the dynamics differences of catalytic mechanism between methane coenzyme M reductase (MCR) and alkyl-coenzyme M reductase (ACR). At first, the binding pocket of ACR is larger than that of MCR. Then, the complex of butane and ACR is more stable than that of methane and ACR. Protein conformation cloud suggests that the position of methane is dynamics and methane escapes from the binding pocket of ACR during most of the simulation time, while butane tightly binds in the pocket of ACR. The hydrophobic interactions between butane and ACR are more and stronger than those between methane and ACR. At the same time, the binding free energy between butane and ACR is significantly lower than that between methane and ACR. The dynamics correlation network indicates that the transformation of information flow for ACR-butane is smoother than that for ACR-methane. The shortest pathway for ACR-butane is from Gln144, Ala141, Hie135, Ile133, Ala160, Arg206, Asp97, Met94, Tyr347 to Phe345 with synergistic effect for two butane molecules. This study can insight into the catalytic mechanism for butane/ACR complex.

Extensive evaluation of environment-specific force field for ordered and disordered proteins

Intrinsically disordered proteins (IDPs) have no fixed tertiary structure under physiological conditions and are associated with many human diseases. Because IDPs have the characteristic of possessing diverse conformations, current experimental methods cannot capture all the conformations of IDPs. However, molecular dynamics simulation can sample these atomistically diverse conformations as a valuable complement to experimental data. To accurately describe the properties of IDPs, the environment-specific precise force field (ESFF1) was successfully released to reproduce the conformer character of ordered and disordered proteins. Here, three typical IDPs and thirteen folded proteins were used to further evaluate the performance of this force field. The results indicate that the NMR observables of ESFF1 better approach experimental data than do those of ff14SB for IDPs. The sampling conformations by ESFF1 are more diverse than those of ff14SB. For folded proteins, these force fields have comparable performances for reproducing conformers. Therefore, ESFF1 can be used to reveal the model of sequence-disorder-function for IDPs.

Fisetin inhibits tau aggregation by interacting with the protein and preventing the formation of β-strands

Alzheimer's disease is a neurodegenerative disease which severely impacts the health of the elderly. Current treatments are only able to alleviate symptoms, but not prevent or cure the disease. The neurofibrillary tangles formed by tau protein aggregation are one of the defining characteristics of Alzheimer's disease, so tau protein has become a key target for the drug design. In this study, we show that fisetin, a plant-derived polyphenol compound, can inhibit aggregation of the tau fragment, K18, and can disaggregate tau K18 filaments in vitro. Meanwhile it is able to prevent the formation of tau aggregates in cells. Both experimental and computational studies indicate that fisetin could directly interact with tau K18 protein. The binding is mainly created by hydrogen bond and van der Waal force, prevents the formation of β-strands at the two hexapeptide motifs, and does not perturb the secondary structure or the tubulin binding ability of tau protein. In summary, fisetin might be a candidate for further development as a potential preventive or therapeutic drug for Alzheimer's disease.

Recent Force Field Strategies for Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.

Disaggregation mechanism of prion amyloid for tweezer inhibitor

The aggregation of amyloid has been an important event in the pathology of amyloidogenicity. A number of small molecules have been designed for Amyloidosis treatment. Molecular tweezer CLR01, a potential drug for misfolded β-amyloids inhibition, was reportedly bind directly to Lysine residues and interrupt oligomerization. However, the disaggregation mechanism of amyloid for this inhibitor is unclear. Here we used long timescale of molecular dynamic simulation to reveal the mechanism of disaggregation for pentamer prion amyloid. Molecular docking and molecular dynamics simulation demonstrate that CLR01 is attached with Lysine₂₂₂ nitrogen by π-cation interaction of its nine aromatic rings and formation of salt bridge/hydrogen bond of one of the two rotatable peripheral anionic phosphate groups. Upon CLR01 binding, we found a major shifting occurs in initial conformation of the oligomer and stretch out the N-terminal chain A from the rest of the amyloid which seems to be the first stage of disaggregated the fibrils slowly yet efficiently. Moreover, the CLR01 remodelled the pentamer Prion_220-272 into a compact structure which might be the resistant conformation for further oligomerization. Our work will contribute to better understand the interaction and deterioration mechanism of molecular tweezer for prions and similar amyloids, and offer significant insights into therapeutic development for Amyloidosis treatment.

Systematic Differences between Current Molecular Dynamics Force Fields To Represent Local Properties of Intrinsically Disordered Proteins

The prevalence of intrinsically disordered proteins (IDPs) and protein regions in structural biology has prompted the recent development of molecular dynamics (MD) force fields for the more realistic representations of such systems. Using experimental nuclear magnetic resonance backbone scalar ³J-coupling constants of the intrinsically disordered proteins α-synuclein and amyloid-β in their native aqueous environment as a metric, we compare the performance of four recent MD force fields, namely, AMBER ff14SB, CHARMM C36m, AMBER ff99SB-disp, and AMBER ff99SBnmr2, by partitioning the polypeptides into an overlapping series of heptapeptides for which a cumulative total of 276 μs MD simulations were performed. The results show substantial differences between the different force fields at the individual residue level. Except for ff99SBnmr2, the force fields systematically underestimate the scalar ³J(H^N,Hα)-couplings due to an underrepresentation of β-conformations and an overrepresentation of either α- or PP_II conformations. The study demonstrates that the incorporation of coil library information in modern MD force fields, as shown here for ff99SBnmr2, provides substantially improved performance and more realistic sampling of the local backbone dihedral angles of IDPs as reflected by the good accuracy of the computed scalar ³J(H^N,Hα)-couplings with less than 0.5 Hz error. Such force fields will enable a better understanding of how structural dynamics and thermodynamics influence the IDP function. Although the methodology based on heptapeptides used here does not allow the assessment of potential intramolecular long-range interactions, its computational affordability permits well-converged simulations that can be easily parallelized. This should make the quantitative validation of intrinsic disorder observed in MD simulations of polypeptides with experimental scalar J-couplings widely applicable.

Functional characterization of an unknown soybean intrinsically disordered protein in vitro and in Escherichia coli

Intrinsically disordered proteins (IDPs) possess a wide range of biological function in all organisms, however the specific functions of most IDPs are still unknown. Soybean LOC protein, LOC for short, is a heat-stable protein, which is more abundant in the stress-resistant radicles. Sequence alignment and phylogenetic analysis showed that LOC is a functionally unknown protein and conserved in Fabaceae. LOC, being enriched in most disorder-promoting residues and depleted in most order-promoting residues, was predicted to contain high levels of intrinsic disorder by several commonly used computational tools. However, it was also predicted to contain two disorder-based protein-protein binding sites and two short α-helical segments. The circular dichroism spectroscopic analysis showed that this protein is mostly disordered in water, but can form more α-helical structure in the presence of SDS and TFE. Functional in vitro studies showed that the LOC protein is able to prevent lactate dehydrogenase inactivation by freeze-thaw at a molar ratio of 10:1. Furthermore, in vivo analyses revealed the survival rate of Escherichia coli over-expressing LOC protein under the conditions of osmotic stress was noticeably increased in comparison with the control. These observations suggest that the intrinsically disordered protein LOC might serve as a chaperone and/or cell protector.

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

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

Computational strategy for intrinsically disordered protein ligand design leads to the discovery of p53 transactivation domain I binding compounds that activate the p53 pathway

Intrinsically disordered proteins or intrinsically disordered regions (IDPs) have gained much attention in recent years due to their vital roles in biology and prevalence in various human diseases. Although IDPs are perceived as attractive therapeutic targets, rational drug design targeting IDPs remains challenging because of their conformational heterogeneity. Here, we propose a hierarchical computational strategy for IDP drug virtual screening (IDPDVS) and applied it in the discovery of p53 transactivation domain I (TAD1) binding compounds. IDPDVS starts from conformation sampling of the IDP target, then it combines stepwise conformational clustering with druggability evaluation to identify potential ligand binding pockets, followed by multiple docking screening runs and selection of compounds that can bind multi-conformations. p53 is an important tumor suppressor and restoration of its function provides an opportunity to inhibit cancer cell growth. TAD1 locates at the N-terminus of p53 and plays key roles in regulating p53 function. No compounds that directly bind to TAD1 have been reported due to its highly disordered structure. We successfully used IDPDVS to identify two compounds that bind p53 TAD1 and restore wild-type p53 function in cancer cells. Our study demonstrates that IDPDVS is an efficient strategy for IDP drug discovery and p53 TAD1 can be directly targeted by small molecules.

A hierarchical computational strategy for IDP drug virtual screening (IDPDVS) was proposed and successfully applied to identify compounds that bind p53 TAD1 and restore wild-type p53 function in cancer cells.

An α-helix mimetic oligopyridylamide, ADH-31, modulates Aβ42 monomer aggregation and destabilizes protofibril structures: insights from molecular dynamics simulations

Alzheimer's disease (AD), an epidemic growing worldwide due to no effective medical aid available in the market, is a neurological disorder. AD is known to be directly associated with the toxicity of amyloid-β (Aβ) aggregates. In search of potent inhibitors of Aβ aggregation, Hamilton and co-workers reported an α-helix mimetic, ADH-31, which acts as a powerful antagonist of Aβ42 aggregation. To identify the key interactions between protein-ligand complexes and to gain insights into the inhibitory mechanism of ADH-31 against Aβ42 aggregation, molecular dynamics (MD) simulations were performed in the present study. The MD simulations highlighted that ADH-31 showed distinct binding capabilities with residues spanning from the N-terminal to the central hydrophobic core (CHC) region of Aβ42 and restricted the conformational transition of the helix-rich structure of Aβ42 into another form of secondary structures (coil/turn/β-sheet). Hydrophobic contacts, hydrogen bonding and π-π interaction contribute to the strong binding between ADH-31 and Aβ42 monomer. The Dictionary of Secondary Structure of Proteins (DSSP) analysis highlighted that the probability of helical content increases from 38.5% to 50.2% and the turn content reduces from 14.7% to 6.2% with almost complete loss of the β-sheet structure (4.5% to 0%) in the Aβ42 monomer + ADH-31 complex. The per-residue binding free energy analysis demonstrated that Arg5, Tyr10, His14, Gln15, Lys16, Val18, Phe19 and Lys28 residues of Aβ42 are responsible for the favourable binding free energy in Aβ42 monomer + ADH-31 complex, which is consistent with the 2D HSQC NMR of the Aβ42 monomer that depicted a change in the chemical shift of residues spanning from Glu11 to Phe20 in the presence of ADH-31. The MD simulations highlighted the prevention of sampling of amyloidogenic β-strand conformations in Aβ42 trimer in the presence of ADH-31 as well as the ability of ADH-31 to destabilize Aβ42 trimer and protofibril structures. The lower binding affinity between Aβ42 trimer chains in the presence of ADH-31 highlights the destabilization of the Aβ42 trimer structure. Overall, MD results highlighted that ADH-31 inhibited Aβ42 aggregation by constraining Aβ peptides into helical conformation and destabilized Aβ42 trimer as well as protofibril structures. The present study provides a theoretical insight into the atomic level details of the inhibitory mechanism of ADH-31 against Aβ42 aggregation as well as protofibril destabilization and could be implemented in the structure-based drug design of potent therapeutic agents for AD.

Comparison and Evaluation of Force Fields for Intrinsically Disordered Proteins

Molecular dynamics (MD) simulations of six upgraded empirical force fields were compared and evaluated with short peptides, intrinsically disordered proteins, and folded proteins using trajectories of 1, 1.5, 5, or 10 μs (five replicates of 200 ns, 300 ns, 1 μs, or 2 μs) for each system. Previous studies have shown that different force fields, water models, simulation methods, and parameters can affect simulation outcomes. Here, the MD simulations were done in an explicit solvent with RS-peptide, HEWL19, HIV-rev, β amyloid (Aβ)-40, Aβ-42, phosphodiesterase-γ, CspTm, and ubiquitin using ff99IDPs, ff14IDPs, ff14IDPSFF, ff03w, CHARMM36m, and CHARMM22* force fields. The IDP ensembles generated by six all-atom empirical force fields were compared against NMR data. Despite using identical starting structures and simulation parameters, ensembles obtained with different force fields exhibit significant differences in NMR RMDs, secondary structure contents, and global properties such as the radius of gyration. The intrinsically disordered protein (IDP)-specific force fields could substantially reproduce the experimental observables in force field comparison: they have the lowest error in chemical shifts and J-couplings for short peptides/proteins, reasonably well for large IDPs and reasonably well with the radius of gyration. A high population of disorderness was observed in the IDP-specific force field for the IDP ensemble with a fraction of β sheets for β-amyloids. CHARMM22* performs better for many observables; however, it still has a preference toward the helicity for short peptides. The results of β-amyloid 42 starting from two different initial structures (Aβ42^1Z0Q and Aβ42^model) were also compared with DSSP and NMR data. The results obtained with IDP-specific force fields within 2 μs simulation time are similar, even though starting from different structures. The current force fields perform equally well for folded proteins. The results of currently developed or modified force fields for IDPs are capable of enlightening the overall performance of the force field for disordered as well as folded proteins, thereby contributing to force field development.

Development of Charge-Augmented Three-Point Water Model (CAIPi3P) for Accurate Simulations of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) are molecules without a fixed tertiary structure, exerting crucial roles in cellular signalling, growth and molecular recognition events. Due to their high plasticity, IDPs are very challenging in experimental and computational structural studies. To provide detailed atomic insight in IDPs' dynamics governing their functional mechanisms, all-atom molecular dynamics (MD) simulations are widely employed. However, the current generalist force fields and solvent models are unable to generate satisfactory ensembles for IDPs when compared to existing experimental data. In this work, we present a new solvation model, denoted as the Charge-Augmented Three-Point Water Model for Intrinsically Disordered Proteins (CAIPi3P). CAIPi3P has been generated by performing a systematic scan of atomic partial charges assigned to the widely popular molecular scaffold of the three-point TIP3P water model. We found that explicit solvent MD simulations employing CAIPi3P solvation considerably improved the small-angle X-ray scattering (SAXS) scattering profiles for three different IDPs. Not surprisingly, this improvement was further enhanced by using CAIPi3P water in combination with the protein force field parametrized for IDPs. We also demonstrated the applicability of CAIPi3P to molecular systems containing structured as well as intrinsically disordered regions/domains. Our results highlight the crucial importance of solvent effects for generating molecular ensembles of IDPs which reproduce the experimental data available. Hence, we conclude that our newly developed CAIPi3P solvation model is a valuable tool for molecular simulations of intrinsically disordered proteins and assessing their molecular dynamics.

Environment-Specific Force Field for Intrinsically Disordered and Ordered Proteins

The need for accurate and efficient force fields for modeling 3D structures of macrobiomolecules and in particular intrinsically disordered proteins (IDPs) has increased with recent findings to associate IDPs and human diseases. However, most conventional protein force fields and recent IDP-specific force fields are limited in reproducing accurate structural features of IDPs. Here, we present an environmental specific precise force field (ESFF1) based on CMAP corrections of 71 different sequence environments to improve the accuracy and efficiency of MD simulation for both IDPs and folded proteins. MD simulations of 84 different short peptides, IDPs, and structured proteins show that ESFF1 can accurately reproduce spectroscopic properties for different peptides and proteins whether they are disordered or ordered. The successful ab initio folding of five fast-folding proteins further supports the reliability of ESFF1. The extensive analysis documented here shows that ESFF1 is able to achieve a reasonable balance between ordered and disordered states in protein simulations.

Disorder-Order Transitions in Conformational Selection of a Peptide by Ebola Virus Nucleoprotein

This study presents parallel-tempering lattice Monte Carlo simulations based on the side-chain-only (SICHO) model for calculating the conformational landscape of a 28-residue intrinsically disordered peptide extracted from the Ebola virus protein VP35. The central issue is the applicability of the SICHO potential energy function and in general coarse-grained (CG) representations of intermediate resolution for modeling large-scale conformational heterogeneity that includes both folded and unstructured peptide states. Crystallographic data shows that the peptide folds in a 4₁₀-helix-turn-3₁₀-helix topology upon complex formation with the Ebola virus nucleoprotein, whereas in isolation, the peptide transitions to a disordered conformational ensemble as observed in circular dichroism experiments. The simulation reveals a potential of mean force that displays conformational diversity along the helix-forming reaction coordinate consistent with disorder-order transitions, yet unexpectedly the bound topology is poorly sampled, and a population shift to an unstructured state incurs a significant free-energy penalty. Applying an elastic network interpolation model suggests a hybrid binding mechanism through conformational selection of the 4₁₀-helix followed by an induced fit of the 3₁₀-helix. A comparison of the CG model with previously reported all-atom CHARMM-based simulations highlights a lattice-based approach that is computationally fast and with the correct parameterization yields good resolution to modeling conformational plasticity.

Identifying the key residues instrumental in imparting stability to amyloid beta protofibrils - a comparative study using MD simulations of 17-42 residues

Extracellular plaques, the hallmark of Alzheimer's disease brains, consist of insoluble amyloid fibrils that result from the aggregation of amyloid beta peptides. None of the few therapeutic options currently adopted, address the cause of the disease. Instead, they reduce symptom of the disease. Inhibition of aggregation or destabilization of aggregates therefore, emerges as a preferable therapeutic approach. Designing inhibitors or destabilizers demands comprehensive knowledge of the residues of amyloid beta responsible for the phenomenal structural stability of the aggregate. For the purpose, we have compared the effect on structural destabilization of 13 in silico mutations (single and double) with the wild type counterpart of beta-strand-turn-beta-strand motif of the amyloid beta protofibrils by molecular dynamics simulation. Besides the already known salt bridge interaction between K28 and D23, our analyses expose more significant role of K28 as the only positive charge present in the vicinity. Amongst the two consecutive aromatic residues, F19 is involved in stacking interaction; although effect of F20 mutation is more pronounced. Face to face arrangement of A21 and V36 acts as a pillar maintaining the necessary optimum distance between consecutive chains to promote stabilizing interactions. In addition to providing stability to the first beta-strand, large sized negatively charged E22 facilitates salt bridge formation by ensuring fixed relative position of D23 and in turn K28. Likewise, the hydrophobic residues I32 and L34 pack the protofibril core, once again fostering salt bridge interaction. Prospectively, these findings may be compiled for efficient identification or design of scaffolds accountable for protofibril destabilization.Communicated by Ramaswamy H. Sarma.

Enhanced Molecular Dynamics Simulations of Intrinsically Disordered Proteins

Molecular dynamics simulations represent a powerful tool to gain insights into structural and dynamical features of biomolecular systems. Nevertheless, their recognized limitation in terms of achievable timescales becomes particularly severe when dealing with slow processes. In such cases, the employment of enhanced sampling methods, which allow accelerating the characterization of rare events in a timeframe consistent with conventional computational resources, results as crucial. In particular, such advanced techniques have proven highly valuable in the context of protein folding and, specifically, to explore the conformational ensemble spanned by intrinsically disordered proteins (IDPs). Here, we describe how to set up molecular dynamics simulations with one of these enhanced sampling approaches (namely, Parallel Tempering Metadynamics in the Well-Tempered Ensemble) using the N_TAIL peptide as a test case.

Extensive tests and evaluation of the CHARMM36IDPSFF force field for intrinsically disordered proteins and folded proteins

Intrinsically disordered proteins (IDPs) have received increasing attention in recent studies due to their structural heterogeneity and critical biological functions. To fully understand the structural properties and determine accurate ensembles of IDPs, molecular dynamics (MD) simulation was widely used to sample diverse conformations and reveal the structural dynamics. However, the classical state-of-the-art force fields perform well for folded proteins while being unsatisfactory for the simulations of disordered proteins reported in many previous studies. Thus, improved force fields were developed to precisely describe both folded proteins and disordered proteins. Preliminary tests show that our newly developed CHARMM36IDPSFF (C36IDPSFF) force field can well reproduce the experimental observables of several disordered proteins, but more tests on different types of proteins are needed to further evaluate the performance of C36IDPSFF. Here, we extensively simulate short peptides, disordered proteins, and fast-folding proteins as well as folded proteins, and compare the simulated results with the experimental observables. The simulation results show that C36IDPSFF could substantially reproduce the experimental observables for most of the tested proteins but some limitations are also found in the radius of gyration of large disordered proteins and the stability of fast-folding proteins. This force field will facilitate large scale studies of protein structural dynamics and functions using MD simulations.

Well-Balanced Force Field ff03CMAP for Folded and Disordered Proteins

Molecular dynamics simulation as an important complement of experiment is widely used to study protein structures and functions. However, previous studies indicate that the current force fields cannot, simultaneously, provide accurate descriptions of folded proteins and intrinsically disordered proteins (IDPs). Therefore, a correction maps (CMAP)-optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of folded proteins and IDPs. Extensive validations of short peptides, folded proteins, disordered proteins, and fast-folding proteins show that simulated chemical shifts, J-coupling constants, order parameters, and residual dipolar couplings (RDCs) with the ff03CMAP force field are in very good agreement with nuclear magnetic resonance measurements and are more accurate than other ff03-series force fields. The influence of solvent models was also investigated. It was found that the combination of ff03CMAP/TIP4P-Ew is suitable for folded proteins, and that of ff03CMAP/TIP4PD is better for disordered proteins. These findings confirm that the newly developed force field ff03CMAP can improve the balance of conformer sampling between folded proteins and IDPs.

Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach

The optimization approaches classically used during the determination of protein structure encounter various difficulties, especially when the size of the conformational space is large. Indeed, in such a case, algorithmic convergence criteria are more difficult to set up. Moreover, the size of the search space makes it difficult to achieve a complete exploration. The interval branch-and-prune (iBP) approach, based on the reformulation of the distance geometry problem (DGP) provides a theoretical frame for the generation of protein conformations, by systematically sampling the conformational space. When an appropriate subset of interatomic distances is known exactly, this worst-case exponential-time algorithm is provably complete and fixed-parameter tractable. These guarantees, however, immediately disappear as distance measurement errors are introduced. Here we propose an improvement of this approach: threading-augmented interval branch-and-prune (TAiBP), where the combinatorial explosion of the original iBP approach arising from its exponential complexity is alleviated by partitioning the input instances into consecutive peptide fragments and by using self-organizing maps (SOMs) to obtain clusters of similar solutions. A validation of the TAiBP approach is presented here on a set of proteins of various sizes and structures. The calculation inputs are a uniform covalent geometry extracted from force field covalent terms, the backbone dihedral angles with error intervals, and a few long-range distances. For most of the proteins smaller than 50 residues and interval widths of 20°, the TAiBP approach yielded solutions with RMSD values smaller than 3 Å with respect to the initial protein conformation. The efficiency of the TAiBP approach for proteins larger than 50 residues will require the use of nonuniform covalent geometry and may have benefits from the recent development of residue-specific force-fields.

Molecular Dynamics Simulations Combined with Nuclear Magnetic Resonance and/or Small-Angle X-ray Scattering Data for Characterizing Intrinsically Disordered Protein Conformational Ensembles

The concept of intrinsically disordered proteins (IDPs) has emerged relatively slowly, but over the past 20 years, it has become an intense research area in structural biology. Indeed, because of their considerable flexibility and structural heterogeneity, the determination of IDP conformational ensemble is particularly challenging and often requires a combination of experimental measurements and computational approaches. With the improved accuracy of all-atom force fields and the increasing computing performances, molecular dynamics (MD) simulations have become more and more reliable to generate realistic conformational ensembles. And the combination of MD simulations with experimental approaches, such as nuclear magnetic resonance (NMR) and/or small-angle X-ray scattering (SAXS) allows one to converge toward a more accurate and exhaustive description of IDP structures. In this Review, we discuss the state of the art of MD simulations of IDP conformational ensembles, with a special focus on studies that back-calculated and directly compared theoretical and experimental NMR or SAXS observables, such as chemical shifts (CS), ³J-couplings (³Jc), residual dipolar couplings (RDC), or SAXS intensities. We organize the review in three parts. In the first section, we discuss the studies which used NMR and/or SAXS data to test and validate the development of force fields or enhanced sampling techniques. In the second part, we explore different methods for the refinement of MD-derived structural ensembles, such as NMR or SAXS data-restrained MD simulations or ensemble reweighting to better fit experiments. Finally, we survey some recent studies combining MD simulations with NMR and/or SAXS measurements to investigate the relationship between IDP conformational ensemble and biological activity, as well as their implication in human diseases. From this review, we noticed that quite a few studies compared MD-generated conformational ensembles with both NMR and SAXS measurements to validate IDP structures at both local and global levels. Yet, beside the IDP propensity to form local secondary structures, their dynamic extension or compactness also appears important for their activity. Thus, we believe that a close synergy between MD simulations, NMR, and SAXS experiments would be greatly appropriate to address the challenges of characterizing the disordered structures of proteins and their complexes, relative to their biological functions.

Allosteric Modulation of Intrinsically Disordered Proteins

The allosteric property of globular proteins is applauded as their intrinsic ability to regulate distant sites, and this property further plays a critical role in a wide variety of cellular regulatory mechanisms. Recent advancements and studies have revealed the manifestation of allostery in intrinsically disordered proteins or regions as allosteric sites present within or mediated by IDP/IDRs facilitates the signaling interactions for various biological mechanisms which would otherwise be impossible for globular proteins to regulate. This thematic review has highlighted the biological outcomes that can be achieved by the mechanism of allosteric regulation of intrinsically disordered proteins or regions. The similar mechanism has been implemented on Adenovirus 5 early region 1A and tumor apoptosis protein p53 in correspondence with other partners in binary and ternary complexes, which are the subject of the current review. Both these proteins regulate once they bind to their partners, consequently, forming either a binary or a ternary complex. Allosteric regulation by IDPs is currently a subject undergoing intense study, and the ongoing research work will ensure a better understanding of precision and efficiency of cellular regulation by them. Allosteric regulation mechanism can also be researched by intrinsically disordered protein-specific force field.

Computational Studies of Intrinsically Disordered Proteins

Frequently elusive to experimental characterizations, intrinsically disordered proteins (IDPs) can be probed using molecular dynamics to provide detailed insight into their complex structure, dynamics, and function. However, previous computational studies were often found to disagree with experiment due to either force field biases or insufficient sampling. In this study, nine unstructured short peptides and the HIV-1 Rev protein were simulated and extended to microseconds to assess these limitations in IDP simulations. In short peptide simulations, a tested IDP-specific force field ff14IDPSFF outperforms its generic counterpart ff14SB as agreement of simulated NMR observables with experiment improves, though its advantages are not clear-cut in apo Rev simulations. It is worth noting that sampling is probably still not sufficient in the ff14SB simulations of apo Rev even if 10 ms have been collected. This indicates that enhanced sampling techniques would greatly benefit IDP simulations. Finally, detailed structural analyses of apo Rev conformations demonstrate different secondary structural preferences between ff14SB (helical) and ff14IDPSFF (random coil). A natural next step is to ask a more quantitative question: whether ff14SB is too ordered or ff14IDPSFF is too disordered in simulations of more complex IDPs such as Rev. This requires further quantitative analyses both experimentally and computationally.