Combined Force-Torque Spectroscopy of Proteins by Means of Multiscale Molecular Simulation

Abstract

Assessing the structural properties of large proteins is important to gain an understanding of their function in, e.g., biological systems or biomedical applications. We propose a method to examine the mechanical properties of proteins subject to applied forces by means of multiscale simulation. Both stretching and torsional forces are considered, and these may be applied independently of each other. As a proof of principle, we apply torsional forces to a coarse-grained continuum model of the antibody protein immunoglobulin G (IgG) using Fluctuating Finite Element Analysis and use it to identify the area of strongest deformation. This region is essential to the torsional properties of the molecule as a whole, as it represents the softest, most deformable domain. Zooming in, this part of the molecule is subjected to torques and stretching forces using molecular dynamics simulations on an atomistically resolved level, in order to investigate its torsional properties. We calculate the torsional resistance as a function of the rotation of the domain, while subjecting it to various stretching forces. From this, we assess how the measured twist-torque profiles develop with increasing stretching force, and show that they exhibit torsion stiffening, in qualitative agreement with experimental findings. We argue that combining the twist-torque profiles for various stretching forces effectively results in a combined force-torque spectroscopy analysis, which may serve as a mechanical signature for a biological macromolecule.SIGNIFICANCE In this work, we propose a multiscale numerical approach to assess the mechanical properties of macromolecules such as proteins. We perform a combined force-torque spectroscopy analysis on the mechanically most relevant domain to compute the response signature of the spatial structure of the macromolecule. This information may lead to a better understanding of molecular structure and function in biological context and may be used towards diagnostic and sensing applications in the biomedical field.

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“…Despite this limitation, which can nonetheless be alleviated by the application of enhanced sampling techniques (Yang et al, 2019), the QM/MM method is having an increasing impact on the study of biomolecules (Lonsdale et al, 2013;Lonsdale et al, 2014;Tyzack et al, 2016), mostly enzyme-ligand complexes. For instance, QM/MM simulations proved useful to compute binding free-energy profiles and barriers for enzyme-catalyzed reactions (Barnes et al, 2013), and to characterize binding kinetics (Haldar et al, 2018).…”

“…The absence of an atomistic level of detail clearly sets a dramatically large lower bound to the length scales achievable by FFEA; on the other hand, this method represents a promising opportunity for pushing the analysis of biological systems to truly meso-to macroscopic scales. Originally applied to the prediction of the dynamics of globular proteins close to their native states ( Oliver et al, 2013 ), FFEA was later employed to analyze the behavior of complex macromolecular systems such as molecular chaperones ( Solernou et al, 2018 ), conformational transition of molecular motors ( Richardson et al, 2014 ; Hanson et al, 2015 ; Richardson et al, 2020 ; Hanson et al, 2021 ), and the effect of the application of stretching and torsional forces on the structural stability of antibodies ( van der Heijden et al, 2020 ).…”

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“…conformational states, for example between the pre-and post-powerstroke states of molecular motors . Fluctuating finite element analysis has been used to successfully model diverse biological systems, including the rotary ATPase motor (Richardson et al, 2014), axonemal and cytoplasmic (Hanson et al, 2021) dynein motors, and protein antibodies subjected to external forces (van der Heijden et al, 2020). Multiscale biological simulations.…”

“…Fluctuating finite element analysis also includes functionality to exert external forces on proteins, to connect proteins together with harmonic springs and to represent conformational changes between distinct protein conformational states, for example between the pre- and post-powerstroke states of molecular motors (Richardson et al, 2020). Fluctuating finite element analysis has been used to successfully model diverse biological systems, including the rotary ATPase motor (Richardson et al, 2014), axonemal (Richardson et al, 2020) and cytoplasmic (Hanson et al, 2021) dynein motors, and protein antibodies subjected to external forces (van der Heijden et al, 2020).…”

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“…FFEA also includes functionality to exert external forces on proteins, to connect proteins together with harmonic springs and to represent conformational changes between distinct protein conformational states, for example between the pre- and post-powerstroke states of molecular motors (Richardson et al, 2020). FFEA has been used to successfully model diverse biological systems, including the rotary ATPase motor (Richardson et al, 2014), axonemal (Richardson et al, 2020) and cytoplasmic (Hanson et al, 2021) dynein motors, and protein antibodies subjected to external forces (van der Heijden et al, 2020).…”