ACS Fall 2025
Date & Time - August 17th-21st, 2025
Location - Washington, D.C
Schrödinger is excited to be participating in the ACS Fall 2025 conference taking place on August 17th – 21st in Washington, D.C. Join us for presentations by Schrödinger scientists.
AUG 20 | 11:20AM 
Hall E – Room 25 Dissipative particle dynamics simulations of mRNA containing lipid nanoparticles
Speaker:
John Shelley, Fellow, Schrödinger
Abstract:
We describe and apply an automated structure-based bottom-up workflow to produce a new dissipative particle dynamics (DPD) force field for simulating lipid nanoparticles (LNPs). This new force field is then applied to study the self-assembly of mRNA-containing LNPs and the critical process of endosomal escape.
AUG 21 | 9:50AM
Room 103A Coarse-grained modeling of membrane permeation for drug discovery
Speaker:
Martin Vögele, Senior Scientist II, Schrödinger
Abstract:
Drug molecules must cross biological membranes to reach their intended targets, thus predicting their permeability is a critical aspect of drug discovery. While computational models that rely on implicit membrane representations are fast and offer reasonable predictive power, they fail to capture the structural dynamics of lipid bilayers and its impact on permeant molecules. Explicit modeling of lipid bilayers via atomic simulations, on the other hand, can in principle provide detailed physical insights and more accurate predictions, but they require too much compute resources. Here, we evaluate the Martini coarse-grained (CG) model as an alternative approach for simulating membrane permeation of small molecules. Using umbrella sampling simulations, we calculated profiles of the potential of mean force of rigid and flexible drug-like compounds across membranes with and without cholesterol. Our results demonstrate that the Martini CG model can provide permeability predictions that correlate well with experiments while offering computational efficiency gains of up to two orders of magnitude compared to atomistic simulations. Additionally, this approach can reveal mechanistic insights inaccessible to implicit models, such as the influence of membrane composition on molecular orientation and conformation during permeation. We observed that cholesterol content significantly alters permeation barriers and transition pathways. For large and flexible molecules with a large number of accessible conformations, sampling all the translational, rotational, and conformational states across the membrane is a major challenge for accurate and efficient permeability predictions, and the preferred conformational states may be coupled with the membrane composition and the compound’s position within the membrane. Despite these challenges, we find that coarse-grained modeling is a promising approach for high-throughput permeability prediction in drug discovery workflows.