E2EDNA: Simulation Protocol for DNA Aptamers with Ligands.

We present E2EDNA, a simulation protocol and accompanying code for the molecular biophysics and materials science communities. This protocol is both easy to use and sufficiently efficient to simulate single-stranded (ss)DNA and small analyte systems that are important to cellular processes and nanotechnologies such as DNA aptamer-based sensors. Existing computational tools used for aptamer design focus on cost-effective secondary structure prediction and motif analysis in the large data sets produced by SELEX experiments. As a rule, they do not offer flexibility with respect to the choice of the theoretical engine or direct access to the simulation platform. Practical aptamer optimization often requires higher accuracy predictions for only a small subset of sequences suggested, e.g., by SELEX experiments, but in the absence of a streamlined procedure, this task is extremely time and expertise intensive. We address this gap by introducing E2EDNA, a computational framework that accepts a DNA sequence in the FASTA format and the structures of the desired ligands and performs approximate folding followed by a refining step, analyte complexation, and molecular dynamics sampling at the desired level of accuracy. As a case study, we simulate a DNA-UTP (uridine triphosphate) complex in water using the state-of-the-art AMOEBA polarizable force field. The code is available at https://github.com/InfluenceFunctional/E2EDNA.

Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field.

Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson-Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. Mean signed errors for the adaptive Poisson-Boltzmann solver (APBS), ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.58 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields opens the door to their use for folding and design applications.

Accurate description of molecular dipole surface with charge flux implemented for molecular mechanics.

The molecular dipole moment is strongly coupled to molecular geometry among different phases, conformational states, intermolecular interaction energy, and vibrational spectroscopy. Our previous inclusion of geometry dependent charge flux into the atomic multipole-based polarizable AMOEBA+ force field has shown significant improvement of water properties from gaseous to condensed phases [C. Liu et al., J. Phys. Chem. Lett. 11(2), 419-426 (2020)]. In this work, the parameterization of the CF model for a broad range of organic and biomolecular fragments is presented. Atom types are automatically assigned by matching the predefined SMARTS patterns. Comparing to the current AMOEBA+ model without the CF component, it is shown that the AMOEBA+ (CF) model improves the description of molecular dipole moments for the molecules we studied over both equilibrium and distorted geometries. For the equilibrium-geometry structures, AMOEBA+ (CF) reduces the mean square error (MSE) from 6.806 × 10-1 (without CF) to 4.249 × 10-4 D2. For non-equilibrium structures, the MSE is reduced from 5.766 × 10-1 (without CF) to 2.237 × 10-3 D2. Finally, the transferability of the CF model and parameters were validated on two sets of molecules: one includes molecules in the training set but with different geometries, and the other one involves new molecules outside of the training set. A similar improvement on dipole surfaces was obtained on the validation sets. The CF algorithms and parameters derived in this work are general and can be implemented into any existing molecular mechanical force fields.

Polarizable Force Fields for Biomolecular Simulations: Recent Advances and Applications.

Realistic modeling of biomolecular systems requires an accurate treatment of electrostatics, including electronic polarization. Due to recent advances in physical models, simulation algorithms, and computing hardware, biomolecular simulations with advanced force fields at biologically relevant timescales are becoming increasingly promising. These advancements have not only led to new biophysical insights but also afforded opportunities to advance our understanding of fundamental intermolecular forces. This article describes the recent advances and applications, as well as future directions, of polarizable force fields in biomolecular simulations.