# multiSMD – A Python Toolset for Multidirectional Steered Molecular Dynamics

## TL;DR

multiSMD is a Python tool that automates multidirectional force simulations to study how biomolecules respond to forces from different directions.

## Contribution

multiSMD introduces a new framework for multidirectional SMD simulations, revealing direction-dependent mechanical behaviors in biomolecules.

## Key findings

- multiSMD reveals anisotropic unbinding in protein–protein complexes.
- The tool identifies ligand dissociation pathways dependent on pulling direction.
- It captures force-induced remodeling in intrinsically disordered protein regions.

## Abstract

Molecular forces
govern all biological processes from cellular
mechanics to molecular recognition events. Understanding the direction-dependence
of these forces is particularly critical for elucidating fundamental
interactions, such as protein–protein binding, ligand dissociation,
and signal mechanotransduction. While steered molecular dynamics (SMD)
simulations enable the study of force-induced transitions, conventional
single-direction approaches may overlook anisotropic mechanical responses
inherent to biomolecular systems. Therefore, probing the mechanical
stability of molecular systems with respect to a director of an external
force may provide critical information. Here, we present multiSMD,
a Python-based tool that automates the setup and analysis of multidirectional
SMD simulations in NAMD and GROMACS. By systematically probing forces
along multiple spatial vectors, multiSMD captures direction-dependent
phenomena, such as changing energy barriers or structural resilience,
that remain hidden in standard SMD. We demonstrate the utility of
our approach through three distinct applications: (i) anisotropic
unbinding in a protein–protein complex, (ii) search for ligand
dissociation pathways dependent on the pulling direction, and (iii)
force-induced remodeling of intrinsically disordered regions in proteins.
multiSMD streamlines the exploration of nanomechanical anisotropy
in biomolecules, offering a computational framework to guide experiments
(e.g., atomic force microscopy – AFM or optical tweezers) and
uncover mechanistic properties inaccessible to single-axis methods.