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

Abstract

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.

Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling

“…We comprehensively evaluate the performance of our model in reconstructing and generating protein conformations, including metrics like RMSD, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\mathrm{\varphi} -\mathrm{\psi}$\end{document} distribution, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\mathrm{\omega}$\end{document} angle distribution, contact map, Rg distribution, PCA and clustering results. The trajectories involved in this study were proved to converge in the previous research [ 27 ].…”

“…In this regard, we believe that in the next step, we should involve pre-training the model on the PDB database, enabling it to capture the diversity present in experimental structures, followed by fine-tuning with MD simulation trajectories specific to different systems [ 25 ]. Additionally, more accurate force fields and solvent models should be employed for simulations [ 26 , 27 ].…”

Precise Generation of Conformational Ensembles for Intrinsically Disordered Proteins via Fine-tuned Diffusion Models

“…To assess the fidelity of the dynamics conformational ensembles predicted by IDPFold, we collected experimental physical quantities from 27 IDP systems of varying lengths (Table S1) and performed 1 μs all-atom molecular dynamics simulation for each system. All simulations were utilized with the ESFF1 force field along with the OPC3-B solvent model 18,29 , which are specifically targeted for disordered proteins. Convergence of the simulation trajectories was confirmed.…”

Graphormer supervised de novo protein design method and function validation

“…This force field was developed by our group and was proved to balance the ordered–disordered region co-existing systems (Recent force field strategies for intrinsically disordered proteins). The solvent model used was TIP4P-Ew [ 36 ], a model proved to be suitable for ordered protein [ 37 , 38 ]. The antechamber was used to parameterize the ligand molecule [ 39 ].…”