a, CG-scale protein graph generation. The atomistic structure of a protein-protein complex is transformed into its coarse-grained (CG)-scale structure and force field parameters using the MARTINI engine (MARTINI22 and MARTINI3 are supported in this study), with these parameters encompassing bead t...
As an example, the powerful SAFT-γ EoS, a variation of the Statistical Associating Fluid Theory (SAFT), has been used to estimate the coarse-grained potentials of the Mie force field [50]. This force field has been recently used to calculate solvation free energies of aromatic compounds, ...
assume in the following that the mapping is given, focusing instead on the second point, which is the choice of an energy function for the CG model that can reproduce relevant properties of the fine-grained system. Recently, our groups and others have used machine learning methods to extend t...
MOFDiff is a deep neural network that models metal organic framework (MOF) 3D structures. What can MOFDiff do? MOFDiff allows you to train and sample from models that yield a coarse-grained representation of a MOF. It also includes functions for reassembly of an atomistic MOF structure from...
learning methods to extend the theoretical ideas of coarse-graining to systems of practical interest, which provides a systematic and general solution to reduce the degrees of freedom of a molecular system by building a potential of mean force over the coarse-grained system41,42,43,44,45,46,47...
The coarse-grained UNRES force field (UNited RESidue) [28,29] is very well suited to the task of structure prediction and the study of protein folding. It enables large-scale simulations with the aim of identifying functionally important conformational changes in large proteins. This model (Fig....
MOFDiff is a deep neural network that models metal organic framework (MOF) 3D structures. What can MOFDiff do? MOFDiff allows you to train and sample from models that yield a coarse-grained representation of a MOF. It also includes functions for reassembly of an atomistic MOF structure from...
The 3154 pockets from 160 NMR RNA-related structures are first divided into 297 groups by similarity using a coarse-grained lattice model. Then, we introduce the flexibility score to quantify the pockets’ topological flexibility. The flexibility scores show a strong correlation with RMSF calculations...
RNA 3D structure; coarse-grained model; full atomic structure reconstruction1. Introduction RNAs play diverse biological roles in living organisms, such as protein synthesis, RNA splicing, and transcription regulation, and the involvement in various human diseases underscores their significance in ...
One study utilized machine learning models to predict and optimize RCA concrete compressive strength, using a large experimental dataset. Gradient Boosting Regression Trees (GBRT) and Deep Learning had superior predictive performance. GBRT, coupled with Particle Swarm Optimization (PSO), proposed ...