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.

Structures of the Omicron spike trimer with ACE2 and an anti-Omicron antibody.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has become the dominant infective strain. We report the structures of the Omicron spike trimer on its own and in complex with angiotensin-converting enzyme 2 (ACE2) or an anti-Omicron antibody. Most Omicron mutations are located on the surface of the spike protein and change binding epitopes to many current antibodies. In the ACE2-binding site, compensating mutations strengthen receptor binding domain (RBD) binding to ACE2. Both the RBD and the apo form of the Omicron spike trimer are thermodynamically unstable. An unusual RBD-RBD interaction in the ACE2-spike complex supports the open conformation and further reinforces ACE2 binding to the spike trimer. A broad-spectrum therapeutic antibody, JMB2002, which has completed a phase 1 clinical trial, maintains neutralizing activity against Omicron. JMB2002 binds to RBD differently from other characterized antibodies and inhibits ACE2 binding.

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.