The journal of physical chemistry letters
May 9, 2025
We present an efficient and reliable large-scale non-adiabatic dynamics simulation method based on machine learning Hamiltonian and force field. The quasi-diabatic Hamiltonian network (DHNet) is trained in the Wannier basis based on well-designed tra...
The journal of physical chemistry letters
May 9, 2025
Excited state proton transfer is a fundamental process in photochemistry, playing a crucial role in fluorescence sensing, bioimaging, and optoelectronic applications. However, fully resolving its dynamics remains challenging due to the prohibitive co...
The journal of physical chemistry letters
Apr 3, 2025
Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how pro...
The journal of physical chemistry letters
Feb 18, 2025
Infrared (IR) spectroscopy and Raman spectroscopy are powerful tools for probing protein and peptide structures due to their capability to provide molecular fingerprints. As a popular spectral simulation method, the quantum chemistry (QC) calculation...
The journal of physical chemistry letters
Jan 23, 2025
Surface-enhanced Raman spectroscopy (SERS) has become an indispensable tool for biomolecular analysis, yet the detection of DNA signals remains hindered by spectral interference from citrate ions, which overlap with key DNA features. This study intro...
The journal of physical chemistry letters
Dec 11, 2024
Antimicrobial peptides (AMPs) hold significant potential as broad-spectrum therapeutics due to their ability to target a variety of different pathogens, including bacteria, fungi, and viruses. However, the rational design of these peptides requires t...
The journal of physical chemistry letters
Aug 2, 2024
Intrinsically disordered proteins and regions (IDP/IDRs) are ubiquitous across all domains of life. Characterized by a lack of a stable tertiary structure, IDP/IDRs populate a diverse set of transiently formed structural states that can promiscuously...
The journal of physical chemistry letters
Jul 22, 2024
Accurate prediction of Drug-Target Interactions (DTI) is crucial for drug development. Current state-of-the-art deep learning methods have significantly advanced the field; however, these methods exhibit limitations in predictive performance and the ...
The journal of physical chemistry letters
May 23, 2024
Nanozymes are unique materials with many valuable properties for applications in biomedicine, biosensing, environmental monitoring, and beyond. In this work, we developed a machine learning (ML) approach to search for new nanozymes and deployed a web...
The journal of physical chemistry letters
Nov 30, 2023
Accurate prediction of binding free energy changes upon mutations is vital for optimizing drugs, designing proteins, understanding genetic diseases, and cost-effective virtual screening. While machine learning methods show promise in this domain, ach...