Replica-Based Protein Structure Sampling Methods II: Advanced Hybrid Solvent TIGER2hs

Abstract

In many cases, native states of proteins may be predicted with sufficient accuracy by molecular dynamics simulations (MDSs) with modern force fields. Enhanced sampling methods based on MDS are applied for exploring the phase space of a protein sequence and to overcome barriers on rough conformational energy landscapes. The minimum free energy state is obtained with sampling algorithms providing sufficient convergence and accuracy. A reliable but computationally very expensive method is replica exchange molecular dynamics, with many modifications to this approach presented in the past. Recently, we demonstrated how our temperature intervals with global exchange of replicas hybrid (TIGER2h) solvent sampling algorithm made a good compromise between efficiency and accuracy. There, all states are sampled under full explicit solvent conditions with a freely chosen number of replicas, whereas an implicit solvent is used during the swap decisions. This hybrid method yielded a much better approximation to the agreement with calculations in an explicit solvent than fully implicit solvent simulations. Here, we present an extension of TIGER2h and add a few layers of explicit water molecules around the peptide for the energy calculations, whereas the dynamics in fully explicit water is maintained. We claim that these water layers better reproduce steric effects, the polarization of the solvent, and the resulting reaction field energy than typical implicit solvent models. By investigating the protein−solvent interactions across comprehensive thermodynamic state ensembles, we found a strong conformational dependence of this reaction field energy. All simulations were performed with nanoscale molecular dynamics on two peptides, the α-helical peptide (AAQAA) 3 and the β-hairpin peptide HP7. A production-ready TIGER2hs implementation is supplied, approaching the accuracy of full explicit solvent sampling at a fraction of computational resources.

Phosphorylation of Fibronectin Influences the Structural Stability of the Predicted Interchain Domain

“…Here, we present the first structural model of the C-terminal cross-linked domain in the ECM protein fibronectin (Figure 2A), which we obtained by replica exchange simulations. 20 We introduce the structural details of this domain and discuss its relevance for the structure−function correlation of the fibronectin molecule (Figure 2). We evaluated our novel structural model on the basis of folding-free-energy landscapes, which are presented in Figure 3.…”

“…Here, an enhanced version of classical replica exchange MDs (REMD) simulations is used, namely, TIGER2hs. 20 Each monomeric CTXL strand of fibronectin has a length of 50 amino acids (sequence number 2337−2386, UniProt ID P02751 12 ). Because the CTXL region consists of a disulfidelinked double strand, the dimeric structure contains a total of 100 amino acids.…”

“…Because such REMD simulations are intensively demanding in computational resource consumption, our novel TIGER2hs method can be used to reduce these resources significantly. 20 This reduction is achieved by introducing an additional quenching (cooling) phase at the end of each cycle and a change in the Metropolis criterion. The exchange decisions now take place at the same rather than at different temperatures.…”

“…To provide further insight into these open questions, we applied sophisticated enhanced sampling on the basis of molecular dynamics (MD) simulations using our recently introduced protein structure sampling method TIGER2hs. 20 From sufficiently converged Boltzmann ensembles, we obtained a new structural model of the CTXL region. For the first time, this new structural model enabled us to study the involvement of phosphorylation in the biological functions of fibronectin in silico.…”

“…The structure of the fibronectin modules Fn I, Fn II, and Fn III was already established in previous studies. , Determining the missing structure of the important interchain domain near the C-terminal will enable us to understand the biological role of phosphorylation in binding of fibronectin to other proteins and the involvement of phosphoryl groups in the process of fibronectin fibrillogenesis. To provide further insight into these open questions, we applied sophisticated enhanced sampling on the basis of molecular dynamics (MD) simulations using our recently introduced protein structure sampling method TIGER2hs . From sufficiently converged Boltzmann ensembles, we obtained a new structural model of the CTXL region.…”