Stochastic Lag Time Parameterization for Markov State Models of Protein Dynamics.

Markov state models (MSMs) play a key role in studying protein conformational dynamics. A sliding count window with a fixed lag time is widely used to sample sub-trajectories for transition counting and MSM construction. However, sub-trajectories sampled with a fixed lag time may not perform well under different selections of lag time, which requires strong prior practice and leads to less robust estimation. To alleviate it, we propose a novel stochastic method from a Poisson process to generate perturbative lag time for sub-trajectory sampling and utilize it to construct a Markov chain. Comprehensive evaluations on the double-well system, WW domain, BPTI, and RBD-ACE2 complex of SARS-CoV-2 reveal that our algorithm significantly increases the robustness and power of a constructed MSM without disturbing the Markovian properties. Furthermore, the superiority of our algorithm is amplified for slow dynamic modes in complex biological processes.

Improved drug-target interaction prediction with intermolecular graph transformer.

The identification of active binding drugs for target proteins (referred to as drug-target interaction prediction) is the key challenge in virtual screening, which plays an essential role in drug discovery. Although recent deep learning-based approaches achieve better performance than molecular docking, existing models often neglect topological or spatial of intermolecular information, hindering prediction performance. We recognize this problem and propose a novel approach called the Intermolecular Graph Transformer (IGT) that employs a dedicated attention mechanism to model intermolecular information with a three-way Transformer-based architecture. IGT outperforms state-of-the-art (SoTA) approaches by 9.1% and 20.5% over the second best option for binding activity and binding pose prediction, respectively, and exhibits superior generalization ability to unseen receptor proteins than SoTA approaches. Furthermore, IGT exhibits promising drug screening ability against severe acute respiratory syndrome coronavirus 2 by identifying 83.1% active drugs that have been validated by wet-lab experiments with near-native predicted binding poses. Source code and datasets are available at https://github.com/microsoft/IGT-Intermolecular-Graph-Transformer.

Exploring the Regulatory Function of the N‐terminal Domain of SARS‐CoV‐2 Spike Protein through Molecular Dynamics Simulation

SARS‐CoV‐2 is what has caused the COVID‐19 pandemic. Early viral infection is mediated by the SARS‐CoV‐2 homo‐trimeric Spike (S) protein with its receptor binding domains (RBDs) in the receptor‐accessible state. Molecular dynamics simulation on the S protein with a focus on the function of its N‐terminal domains (NTDs) is performed. The study reveals that the NTD acts as a “wedge” and plays a crucial regulatory role in the conformational changes of the S protein. The complete RBD structural transition is allowed only when the neighboring NTD that typically prohibits the RBD's movements as a wedge detaches and swings away. Based on this NTD “wedge” model, it is proposed that the NTD–RBD interface should be a potential drug target. The Spike protein of SARS‐CoV‐2 plays a key role in the infection process. The N‐terminal domain (NTD) of the Spike protein plays a regulatory function by the “wedge” model: it typically wedges in to prohibit receptor binding domain's (RBD's) movements and occasionally moves out to allow RBD to tilt downward. Potential drugs are virtually screened for the NTD‐RBD interface.

Exploring the Regulatory Function of the N-terminal Domain of SARS-CoV-2 Spike Protein through Molecular Dynamics Simulation (Adv. Theory Simul. 10/2021)

N-terminal Domain of SARS-CoV-2 Spike Protein In article number 2100152, Yao Li, Tong Wang, Haipeng Gong, and co-workers propose the ?wedge? model to demonstrate the regulatory function of the N-terminal domain (NTD) of SARS-CoV-2 Spike protein. The NTD typically wedges in to prohibit receptor binding domain's (RBD's) movements and it occasionally moves out to allow RBD to tilt downward.