# Explicit ions in implicit solvent: fast and accurate. > **NIH NIH R21** · VIRGINIA POLYTECHNIC INST AND ST UNIV · 2020 · $207,086 ## Abstract Project Summary. This proposal responds to PAR-17-046 “Exploratory Research for Technology Development (R21)”. The goal of the proposal is to design and test in a pilot implementation of a novel “GB- ION” model that will allow fast and accurate atomistic simulations of dynamics of biologically relevant structures such as proteins and DNA in implicit water with explicit ions. Progress in modern bio-molecular sciences, from structural biology to structure-based drug design, is greatly accelerated by methods of atomic-level modeling and simulations that bridge the gap between theory and experiment. The so-called implicit solvation model provides critical advantages of speed and versatility through representing the effects of water – often the most computationally expensive part of such simulations – in an approximate manner. The resulting speed-up of modeling efforts is critical in many areas, from fundamental research in human biology to design of novel medicines; fast implicit solvent methodology can make possible simulations that are otherwise prohibitively expensive within the traditional explicit solvent approach. However, the version of the methodology best suited for atomistic simulations – the so-called generalized Born (GB) model – has a critical flaw in its foundation that precludes its use on systems and problems where explicit treatment of biologically relevant ions is needed. In fact, the majority of bio-medically relevant applications is out of reach to current GB for this reason – these are most of systems where multi- valent ions such as Mg2+ or Ca2+ play a critical role, or where binding of mono-valent ions to specific sites is important. Ion transport or compaction of nucleic acids and chromatin are just two examples out of a long list. This serious limitation of the GB model will be addressed in a novel, systematic way; advantages of the new implicit solvation model will be demonstrated through a pilot implementation and testing on biologically relevant structures. We will develop a novel model, GB-ION, similar in spirit to the generalized Born, that treats ions explicitly, at the same level of accuracy and efficiency as the current fast analytical GB models. Specifically, the GB will be extended to work for multiple, disconnected dielectric boundaries, beyond the singly-connected spherical topology that the current model assumes. The new prototype model will be parametrized for representative examples of mono-, di-, and tri-valent ions. We will test the model on several biologically relevant structures and processes, and implement its prototype in an open source package, widely used (AmberTools or/and OpenMM.) Results will benefit the entire biomolecular modeling community by establishing validity of an approach to carry out fast implicit solvent atomistic simulations in situations where explicit treatment of ions is necessary, which is the majority of bio-medically relevant simulations. ## Key facts - **NIH application ID:** 9986834 - **Project number:** 5R21GM134404-02 - **Recipient organization:** VIRGINIA POLYTECHNIC INST AND ST UNIV - **Principal Investigator:** ALEXEY VLAD ONUFRIEV - **Activity code:** R21 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $207,086 - **Award type:** 5 - **Project period:** 2019-08-01 → 2021-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9986834 ## Citation > US National Institutes of Health, RePORTER application 9986834, Explicit ions in implicit solvent: fast and accurate. (5R21GM134404-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9986834. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*