arXiv subjects

Art E. Cho

Publications and source records attributed to Art E. Cho.

4 recordsLinked to original sources

arXiv2025

Synergistic Computational Approaches for Accelerated Drug Discovery: Integrating Quantum Mechanics, Statistical Thermodynamics, and Quantum Computing

Accurately predicting protein-ligand binding free energies (BFEs) remains a central challenge in drug discovery, particularly because the most reliable methods, such as free energy perturbation (FEP), are computationally intensive and difficult to scale. Here, we introduce a hybrid quantum-classical framework that combines Mining Minima sampling with quantum mechanically refined ligand partial charges, QM/MM interaction evaluation, and variational quantum eigensolver (VQE)-based electronic energy correction. This design enables explicit treatment of polarization, charge redistribution, and electronic correlation effects that are often underestimated in purely classical scoring schemes, while retaining computational efficiency. Across 23 protein targets and 543 ligands, the method achieves a mean absolute error of about 1.10 kcal/mol with strong rank-order fidelity (Pearson R = 0.75, Spearman rho = 0.76, Kendall tau = 0.57), consistent with the performance of contemporary FEP protocols. Notably, the workflow requires only about 25 minutes per ligand on standard compute resources, resulting in an approximate 20-fold reduction in computational cost relative to alchemical free energy approaches. This level of accuracy and efficiency makes the method well-suited for high-throughput lead optimization and iterative design cycles in pharmaceutical discovery. The framework also provides a natural foundation for future integration with machine learning models to enable predictive, large-scale, and adaptive screening strategies.

physics.chem-ph↗

arXiv2018

Origin and Control of Polyacrylonitrile Alignments on Carbon Nanotube and Graphene Nanoribbon

While one of the most promising applications of carbon nanotubes (CNTs) is to enhance polymer orientation and crystallization to achieve advanced carbon fibers, the successful realization of this goal has been hindered by the insufficient atomistic understanding of polymer-CNT interfaces. We herein theoretically study polyacrylonitrile (PAN)-CNT hybrid structures as a representative example of polymer-CNT composites. Based on density-functional theory calculations, we first find that the relative orientation of polar PAN nitrile groups with respect to the CNT surface is the key factor that determines the PAN-CNT interface energetics and the lying-down PAN configurations are much more preferable than their standing-up counterparts. The CNT curvature is identified as another important factor, giving the largest binding energy in the zero-curvature graphene limit. Charge transfer analysis explains the unique tendency of linear PAN alignments on the CNT surface and the possibility of ordered PAN-PAN assembly. Next, performing large-scale molecular dynamics simulations, we show that the desirable linear PAN-CNT alignment can be achieved even for relatively large initial misorientations and further demonstrate that graphene nanoribbons are a promising carbon nano-reinforcement candidate. The microscopic understanding accumulated in this study will provide design guidelines for the development of next-generation carbon nanofibers.

cond-mat.mtrl-sci↗

arXiv2017

Nitrogen doping of carbon nanoelectrodes for enhanced control of DNA translocation dynamics

Controlling the dynamics of DNA translocation is a central issue in the emerging nanopore-based DNA sequencing. To address the potential of heteroatom doping of carbon nanostructures to achieve this goal, herein we carry out atomistic molecular dynamics simulations for single-stranded DNAs translocating between two pristine or doped carbon nanotube (CNT) electrodes. Specifically, we consider the substitutional nitrogen doping of capped CNT (capCNT) electrodes and perform two types of molecular dynamics simulations for the entrapped and translocating single-stranded DNAs. We find that the substitutional nitrogen doping of capCNTs stabilizes the edge-on nucleobase configurations rather than the original face-on ones and slows down the DNA translocation speed by establishing hydrogen bonds between the N dopant atoms and nucleobases. Due to the enhanced interactions between DNAs and N-doped capCNTs, the duration time of nucleobases within the nanogap was extended by up to ~ 290 % and the fluctuation of the nucleobases was reduced by up to ~ 70 %. Given the possibility to be combined with extrinsic light or gate voltage modulation methods, the current work demonstrates that the substitutional nitrogen doping is a promising direction for the control of DNA translocation dynamics through a nanopore or nanogap based of carbon nanomaterials.

cond-mat.mes-hall↗

arXiv2004

Broken-Symmetry Unrestricted Hybrid Density Functional Calculations on Nickel Dimer and Nickel Hydride

In the present work we investigate the adequacy of broken-symmetry unrestricted density functional theory (DFT) for constructing the potential energy curve of nickel dimer and nickel hydride, as a model for larger bare and hydrogenated nickel cluster calculations. We use three hybrid functionals: the popular B3LYP, Becke's newest optimized functional Becke98, and the simple FSLYP functional (50% Hartree-Fock and 50% Slater exchange and LYP gradient-corrected correlation functional) with two basis sets: all-electron (AE) Wachters+f basis set and Stuttgart RSC effective core potential (ECP) and basis set. We find that, overall, the best agreement with experiment, comparable to that of the high-level CASPT2, is obtained with B3LYP/AE, closely followed by Becke98/AE and Becke98/ECP. FSLYP/AE and B3LYP/ECP give slightly worse agreement with experiment, and FSLYP/ECP is the only method among the ones we studied that gives an unaceptably large error, underestimating the dissociation energy of nickel dimer by 28%, and being in the largest disagreement with the experiment and the other theoretical predictions.

physics.chem-ph↗