Incorporating chemical information in matrix completion for efficient prediction of multidimensional tunneling corrections
Discovery of metal–organic frameworks for inverse CO2/C2H2 separation by synergizing molecular simulation and machine learning
Top-performing metal–organic frameworks are discovered for inverse CO2/C2H2 separation.
Paper
Fitting a square peg in a round hole: parameterisation of quasi-spherical molecules employing the Mie potential
Apart for the case of noble gases, no single set of molecular force field parameters can simultaneously describe the fluid phase equilibria, transport, and solid transition properties of quasi-spherical molecules.
Paper
DynaMate: leveraging AI-agents for customized research workflows
Developments related to large language models (LLMs) have deeply impacted everyday activities and offer the potential to automate complex research workflows involving repetitive and time-consuming tasks. The presented template enables the rapid incorporation of custom tools with LLM agents.
Bioinspired design rules for flipping across the lipid bilayer from systematic simulations of membrane protein segments
We employ atomistic molecular dynamics simulations to investigate the flipping of truncated segments of EmrE and find that a membrane-exposed charged glutamate residue at the center of the N-terminal helix lowers the energetic barrier for flipping.
Paper
Quantum chemical screening of eutectic solvent components for insights into CO2 complexation mechanisms
Different eutectic solvent components are simulated to understand the thermodynamics associated with the different, potential CO2 complexation pathways.
Towards stable biologics: understanding co-excipient effects on hydrophobic interactions and solvent network integrity
The formulation of biologics for increased shelf life stability is a complex task that depends on the chemical composition of both the active ingredient and any excipients in solution.
Paper
PepMNet: a hybrid deep learning model for predicting peptide properties using hierarchical graph representations
Peptides are a powerful class of molecules that can be applied to a range of problems including biomaterials development and drug design.
About this collection
We are delighted to showcase this special collection of MSDE showcasing some of the research related to FOMMS 2024. MSDE is working in partnership with the conference to highlight some of the most interesting research in the area of molecular modeling and simulation.
More articles will be added to the collection as they are published.