NLM DIR Seminar Schedule
UPCOMING SEMINARS
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July 15, 2025 Noam Rotenberg
Cell phenotypes in the biomedical literature: a systematic analysis and the NLM CellLink text mining corpus
RECENT SEMINARS
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July 3, 2025 Matthew Diller
Using Ontologies to Make Knowledge Computable -
July 1, 2025 Yoshitaka Inoue
Graph-Aware Interpretable Drug Response Prediction and LLM-Driven Multi-Agent Drug-Target Interaction Prediction -
June 10, 2025 Aleksandra Foerster
Interactions at pre-bonding distances and bond formation for open p-shell atoms: a step toward biomolecular interaction modeling using electrostatics -
June 3, 2025 MG Hirsch
Interactions among subclones and immunity controls melanoma progression -
May 29, 2025 Harutyun Sahakyan
In silico evolution of globular protein folds from random sequences
Scheduled Seminars on June 10, 2025
In-person: Building 38A/B2N14 NCBI Library or Meeting Link
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Open-shell systems, characterized by the presence of unpaired electrons, play a central role in many biological processes, including electron transfer, oxygen activation, and enzymatic catalysis. Their unique electronic structures give rise to distinct interaction patterns not observed in closed-shell systems, providing critical insights into fundamental molecular mechanisms in biology. Understanding the forces and energy landscapes associated with open-shell interactions enables prediction of reactivity and supports the rational design of new compounds.
Despite advances in methods for modeling molecular interactions—from molecular docking to molecular mechanics and quantum mechanical approaches—accurate treatment of open-shell and excited-state interactions remains challenging. We propose a combined ∆SCF and coupled-cluster (CC) approach as a practical and efficient method for computing state-specific interaction energies, particularly when specific electronic configurations must be defined.
Moreover, given the computational cost of quantum methods, predicting the attractive or repulsive nature of pre-bonding interactions using classical electrostatics remains an attractive alternative, especially for large biological systems. Accuracy can be improved by incorporating quantum-derived properties, such as atomic polarizabilities, as seen in modern force fields. In this work, we extend our group’s Small Dielectric Spheres Model to open-shell systems with lone p-electrons and demonstrate its superior accuracy over common DFT methods at pre-bonding distances. We further argue that treating molecular systems as classical dielectrics offers a promising direction for modeling pre-bonding interactions in ligands, proteins, and cellular membranes.