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Zhe Wang

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#natural language process... Jan 2026

How to efficiently characterize the interaction pathways of protein-ligand recognition? A comparative analysis on enhanced sampling approaches.

It is evidenced that many elaborately designed molecules that can interact well with the binding pocket of their target fail to exhibit activity in wet-lab experiments. This may associate with the interacting process of drug-target recognition. To efficiently characterize the drug-target interacting process, various enhanced sampling technologies have been proposed; yet, very few studies have systemically investigated whether the settings of these simulations are favorable to characterize the purposed tasks. Here, by comparing two popular enhanced sampling technologies, namely, the well-temped metadynamics and random acceleration molecular dynamics (RAMD), we systemically investigate the strategies to efficiently characterize the dissociating process of protein-ligand interactions. Two target families are employed for the analysis, including the kinase family (represented by TRK1) that represents the interaction-pathway obvious systems and the nuclear receptor family (represented by THRβ) that represents the interaction-pathway unobvious systems. Our results suggest that (1) in terms of maintaining stability of the protein structure, MetaD at various simulation conditions and RAMD with a large random force are good choice; (2) drug residence time derived from both MetaD and RAMD based on various parameters shows reasonable correlation to the experimental binding strength of the ligands, but RAMD usually runs with much less simulation time; and (3) both enhanced sampling methods result in reasonably consistent pathway preference for the two target families. Taken together, it will be much time-saving to utilize RAMD with high random force for interaction pathway exploration for both the pathway obvious and unobvious systems if the protein keeps stable in the simulation; otherwise, MetaD with a high bias factor is proposed to balance the computational accuracy and efficiency for the exploration.

Zhiliang Jiang, Mingyun Shen, Zhe Wang et al. · 1 citation
#computer vision Jan 2026

Understanding the Kinetic Mechanism of Ligands Stabilizing the RAS-CYPA Interaction

Molecular glues, including protein degraders and protein-protein interaction (PPI) stabilizers, have emerged as a new paradigm of drug design for regulating interactions between biomacromolecules; yet it is still a challenge for rational design of molecular glues. KRAS, as a prevalent oncogenic driver, is notoriously difficult to target by traditional small molecular drugs due to its challenging binding surface and frequent mutations. Although the small molecular drug RMC7977 has been designed as a PPI stabilizer for stabilizing the inherently weak RAS-CYPA interaction, the precise molecular mechanism underlying its stabilization effect and selectivity difference requires a deeper understanding. To this end, we leverage an integrated computational strategy combining molecular dynamics (MD) simulation, end-point binding free-energy calculation, and enhanced sampling technologies to elucidate the dynamic characteristics of RAS-ligand-CYPA interactions. Our result exhibits a high correlation between the predicted binding affinities and the experimental observations, demonstrating that RMC7977, acting as a strong PPI stabilizer, significantly enhances the stability of the KRAS-CYPA interaction, where, by delicately remodeling the protein-protein interface, the drug optimizes various interactions. Moreover, the results also uncover the dynamic process of stabilizer-mediated KRAS-CYPA stabilization and the mechanistic origin of the binding selectivity. This study provides essential molecular-level insights into RMC7977's function and offers a valuable computational framework for evaluating the stabilization effect of ligands targeting the KRAS-CYPA and other challenging PPI systems.

Kexin Xu, Mingyun Shen, Zhe Wang et al. · 0 citations