Structural basis for negative regulation of ABA signaling by ROP11 GTPase

Abscisic acid (ABA) is an essential plant hormone responsible for plant development and stress responses. Recent structural and biochemical studies have identified the key components involved in ABA signaling cascade, including PYR/PYL/RCAR receptors, protein phosphatases PP2C, and protein kinases SnRK2. The plant-specific, Roh-like (ROPs) small GTPases are negative regulators of ABA signal transduction by interacting with PP2C, which can shut off “leaky” ABA signal transduction caused by constitutive activity of monomeric PYR/PYL/RCAR receptors. However, the structural basis for negative regulation of ABA signaling by ROP GTPases remain elusive. In this study, we have utilized large-scale coarse-grained (10.05 milliseconds) and all-atom molecular dynamics simulations and standard protein-protein binding free energy calculations to predict the complex structure of AtROP11 and phosphatase AtABI1. In addition, we have elucidated the detailed complex association pathway and identified the ..., , # Structural basis for negative regulation of ABA signaling by ROP11 GTPase

Dataset DOI: [10.5061/dryad.h9w0vt4tx](10.5061/dryad.h9w0vt4tx)

## Description of the data and file structure

### Files and variables

#### File: clustering\_tica\_600\_mapped.pkl

**Description:** Pickle file containing time-lagged independent component analysis (tICA) representation of the normalized features. The clustering was performed with KMeans clustering with 600 clusters and 4 tICA dimensions.

#### File: msm800.pkl

**Description:** Pickle file containing the Markov state model (MSM) object, constructed from clustered tICA. The MSM was created with 600 clusters, 4 tICA dimensions and a lag-time of 800ns.

#### File: features\_normalized.npy

**Description:** Numpy file containing normalized features used to construct tICA.

#### File: features\_raw\.npy

**Description:** Numpy file containing raw features consisting of 1 centre-of-mass distance and 5 dihedral angles.
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