Do Molecular Dynamics Force Fields Accurately Model Ramachandran Distributions of Amino Acid Residues in Water?

Author(s):  
Brian Andrews ◽  
Jose Guerra ◽  
Reinhard Schweitzer-Stenner ◽  
Brigita Urbanc

Molecular dynamics (MD) is a powerful tool for studying intrinsically disordered proteins, however, its reliability depends on the accuracy of the force field. We here assess Amber ff14SB, Amber ff14SB,...

2020 ◽  
Author(s):  
Suman Samantray ◽  
Feng Yin ◽  
Batuhan Kav ◽  
Birgit Strodel

AbstractThe progress towards understanding the molecular basis of Alzheimers’s disease is strongly connected to elucidating the early aggregation events of the amyloid-β (Aβ) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of Aβ into oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as Aβ were developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the Aβ16−22 peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-disp overestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results are obtained with CHARMM36m and especially its version with increased protein–water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it.


2019 ◽  
Vol 20 (3) ◽  
pp. 596 ◽  
Author(s):  
Ankur Mishra ◽  
Wouter Sipma ◽  
Liesbeth Veenhoff ◽  
Erik Van der Giessen ◽  
Patrick Onck

Nuclear pore complexes (NPCs) are large protein complexes embedded in the nuclear envelope separating the cytoplasm from the nucleoplasm in eukaryotic cells. They function as selective gates for the transport of molecules in and out of the nucleus. The inner wall of the NPC is coated with intrinsically disordered proteins rich in phenylalanine-glycine repeats (FG-repeats), which are responsible for the intriguing selectivity of NPCs. The phosphorylation state of the FG-Nups is controlled by kinases and phosphatases. In the current study, we extended our one-bead-per-amino-acid (1BPA) model for intrinsically disordered proteins to account for phosphorylation. With this, we performed molecular dynamics simulations to probe the effect of phosphorylation on the Stokes radius of isolated FG-Nups, and on the structure and transport properties of the NPC. Our results indicate that phosphorylation causes a reduced attraction between the residues, leading to an extension of the FG-Nups and the formation of a significantly less dense FG-network inside the NPC. Furthermore, our simulations show that upon phosphorylation, the transport rate of inert molecules increases, while that of nuclear transport receptors decreases, which can be rationalized in terms of modified hydrophobic, electrostatic, and steric interactions. Altogether, our models provide a molecular framework to explain how extensive phosphorylation of FG-Nups decreases the selectivity of the NPC.


2021 ◽  
Vol 22 (7) ◽  
pp. 3420
Author(s):  
Meili Liu ◽  
Akshaya K. Das ◽  
James Lincoff ◽  
Sukanya Sasmal ◽  
Sara Y. Cheng ◽  
...  

Many pairwise additive force fields are in active use for intrinsically disordered proteins (IDPs) and regions (IDRs), some of which modify energetic terms to improve the description of IDPs/IDRs but are largely in disagreement with solution experiments for the disordered states. This work considers a new direction—the connection to configurational entropy—and how it might change the nature of our understanding of protein force field development to equally well encompass globular proteins, IDRs/IDPs, and disorder-to-order transitions. We have evaluated representative pairwise and many-body protein and water force fields against experimental data on representative IDPs and IDRs, a peptide that undergoes a disorder-to-order transition, for seven globular proteins ranging in size from 130 to 266 amino acids. We find that force fields with the largest statistical fluctuations consistent with the radius of gyration and universal Lindemann values for folded states simultaneously better describe IDPs and IDRs and disorder-to-order transitions. Hence, the crux of what a force field should exhibit to well describe IDRs/IDPs is not just the balance between protein and water energetics but the balance between energetic effects and configurational entropy of folded states of globular proteins.


2020 ◽  
Author(s):  
Utsab R. Shrestha ◽  
Jeremy C. Smith ◽  
Loukas Petridis

ABSTRACTMolecular dynamics (MD) simulation is widely used to complement ensemble-averaged experiments of intrinsically disordered proteins (IDPs). However, MD often suffers from limitations of inaccuracy in the force fields and inadequate sampling. Here, we show that enhancing the sampling using Hamiltonian replica-exchange MD led to unbiased ensembles of unprecedented accuracy, reproducing small-angle scattering and NMR chemical shift experiments, for three IDPs of variable sequence properties using two recently optimized force fields. Surprisingly, we reveal that despite differences in their sequence, the inter-chain statistics of all three IDPs are similar for short contour lengths (< 10 residues).


2021 ◽  
Author(s):  
Mustapha Carab Ahmed ◽  
Line K. Skaanning ◽  
Alexander Jussupow ◽  
Estella A. Newcombe ◽  
Birthe B. Kragelund ◽  
...  

AbstractThe inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulations times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rakesh Trivedi ◽  
Hampapathalu Adimurthy Nagarajaram

Abstract An amino acid substitution scoring matrix encapsulates the rates at which various amino acid residues in proteins are substituted by other amino acid residues, over time. Database search methods make use of substitution scoring matrices to identify sequences with homologous relationships. However, widely used substitution scoring matrices, such as BLOSUM series, have been developed using aligned blocks that are mostly devoid of disordered regions in proteins. Hence, these substitution-scoring matrices are mostly inappropriate for homology searches involving proteins enriched with disordered regions as the disordered regions have distinct amino acid compositional bias, and therefore expected to have undergone amino acid substitutions that are distinct from those in the ordered regions. We, therefore, developed a novel series of substitution scoring matrices referred to as EDSSMat by exclusively considering the substitution frequencies of amino acids in the disordered regions of the eukaryotic proteins. The newly developed matrices were tested for their ability to detect homologs of proteins enriched with disordered regions by means of SSEARCH tool. The results unequivocally demonstrate that EDSSMat matrices detect more number of homologs than the widely used BLOSUM, PAM and other standard matrices, indicating their utility value for homology searches of intrinsically disordered proteins.


2021 ◽  
Vol 8 ◽  
Author(s):  
Mustapha Carab Ahmed ◽  
Line K. Skaanning ◽  
Alexander Jussupow ◽  
Estella A. Newcombe ◽  
Birthe B. Kragelund ◽  
...  

The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.


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