Structure-based coarse graining of molecular systems offers a systematic route to reproduce the many-body potential of mean force. Unfortunately, common strategies are inherently limited by the molecular mechanics force field employed. Here, we extend the concept of multisurface dynamics, initially developed to describe electronic transitions in chemical reactions, to accurately sample the conformational ensemble of a classical system in equilibrium. In analogy to describing different electronic configurations, a surface-hopping scheme couples distinct conformational basins beyond the additivity of the Hamiltonian. The incorporation of more surfaces leads systematically toward improved cross-correlations. The resulting models naturally achieve consistent long-time dynamics for systems governed by barrier-crossing events.
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http://dx.doi.org/10.1103/PhysRevLett.121.256002 | DOI Listing |
Mol Pharm
January 2025
Schrödinger, Inc., 101 SW Main Street, Suite 1300, Portland Oregon 97204, United States!
Biochemistry
December 2024
Advanced Materials Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong 511400, China.
Engrailed homeodomain (EngHD), a highly charged transcription factor regulating over 200 genes, is a fast-folding protein. Recent studies have shown that the abundant charged residues in EngHD not only facilitate protein-DNA interactions but also influence the conformational disorder of its native structure. However, the mechanisms by which electrostatic interactions modulate the folding of EngHD remain unclear.
View Article and Find Full Text PDFNat Commun
November 2024
School of Computer Science, The University of Birmingham, Edgbaston, Birmingham, UK.
Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While most existing algorithms represent PPI complex graph structures at the atom-scale or residue-scale, these representations can be computationally expensive or may not sufficiently integrate finer chemical-plausible interaction details for improving predictions. Here, we introduce MCGLPPI, a geometric representation learning framework that combines graph neural networks (GNNs) with MARTINI molecular coarse-grained (CG) models to predict PPI overall properties accurately and efficiently.
View Article and Find Full Text PDFBiophys Chem
January 2025
Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, West Bengal 741246, India. Electronic address:
The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is a critical enzyme essential for the virus's replication and transcription, making it a key therapeutic target. The RdRp protein exhibits a characteristic cupped right-hand shaped structure with two vital subdomains: the fingers and the thumb. Despite being distinct, biophysical experiments suggest that these subdomains cooperate to facilitate RNA accommodation, ensuring RdRp functionality.
View Article and Find Full Text PDFJ Chem Theory Comput
July 2024
State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 360015, P. R. China.
Molecular docking remains an indispensable tool in computational biology and structure-based drug discovery. However, the correct prediction of binding poses remains a major challenge for molecular docking, especially for target proteins where a substrate binding induces significant reorganization of the active site. Here, we introduce an Induced Fit Docking (IFD) approach named AA/UA/CG-SA-IFD, which combines a hybrid All-Atom/United-Atom/Coarse-Grained model with Simulated Annealing.
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