We have ported and optimized the graphics processing unit (GPU)-accelerated QUICK and AMBER-based ab initio quantum mechanics/molecular mechanics (QM/MM) implementation on AMD GPUs. This encompasses ...the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra operations. General performance improvements to the QUICK GPU code are also presented. Benchmarks carried out on NVIDIA V100 and AMD MI100 cards display similar performance on both hardware for standalone HF/DFT calculations with QUICK and QM/MM molecular dynamics simulations with QUICK/AMBER. Furthermore, with respect to the QUICK/AMBER release version 21, significant speedups are observed for QM/MM molecular dynamics simulations. This significantly increases the range of scientific problems that can be addressed with open-source QM/MM software on state-of-the-art computer hardware.
We implemented an ab initio CCS prediction workflow which incrementally refines generated structures using molecular mechanics, a deep learning potential, conformational clustering, and quantum ...mechanics (QM). Automating intermediate steps for a high performance computing (HPC) environment allows users to input the SMILES structure of small organic molecules and obtain a Boltzmann averaged collisional cross section (CCS) value as output. The CCS of a molecular species is a metric measured by ion mobility spectrometry (IMS) which can improve annotation of untargeted metabolomics experiments. We report only a minor drop in accuracy when we expedite the CCS calculation by replacing the QM geometry refinement step with a single-point energy calculation. Even though the workflow involves stochastic steps (i.e., conformation generation and clustering), the final CCS value was highly reproducible for multiple iterations on L-carnosine. Finally, we illustrate that the gas phase ensembles modeled for the workflow are intermediate files which can be used for the prediction of other properties such as aqueous phase nuclear magnetic resonance chemical shift prediction. The software is available at the following link: https://github.com/DasSusanta/snakemake_ccs.
Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search ...engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility–mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.
Computational chemists have long demonstrated great interest in finding ways to reliably and accurately predict the molecular properties for transition-metal-containing complexes. This study is a ...continuation of our validation efforts of density functional theory (DFT) methods when applied to transition-metal-containing systems (Riley, K.E.; Merz, K. M., Jr. J. Phys. Chem. 2007, 111, 6044−6053). In our previous work we examined DFT using all-electron basis sets, but approaches incorporating effective core potentials (ECPs) are effective in reducing computational expense. With this in mind, our efforts were expanded to include evaluation of the performance of the basis set derived to approximate such an approach as well on the same set of density functionals. Indeed, employing an ECP basis such as LANL2DZ (Los Alamos National Laboratory 2 double ζ) for transition metals, while using all-electron basis sets for all other non-transition-metal atoms, has become more and more popular in computations on transition-metal-containing systems. In this study, we assess the performance of 12 different DFT functionals, from the GGA (generalized gradient approximation), hybrid-GGA, meta-GGA, and hybrid-meta-GGA classes, respectively, along with the 6-31+G** + LANL2DZ (on the transition metal) mixed basis set in predicting two important molecular properties, heats of formation and ionization potentials, for 94 and 58 systems containing first-row transition metals from Ti to Zn, which are all in the third row of the periodic table. An interesting note is that the inclusion of the exact exchange term in density functional methods generally increases the accuracy of ionization potential prediction for the hybrid-GGA methods but decreases the reliability of determining the heats of formation for transition-metal-containing complexes for all hybrid density functional methods. The hybrid-GGA functional B3LYP gives the best performance in predicting the ionization potentials, while the meta-GGA functional TPSSTPSS provides the most reliable and accurate results for heat of formation calculations. TPSSTPSS, a meta-GGA functional, which was constructed from first principles and subject to known exact constraints just like in an “ab initio” way, is successful in predicting both the ionization potentials and the heats of formation for transition-metal-containing systems.
Simulating the Chelate Effect Sengupta, Arkajyoti; Seitz, Anthony; Merz, Kenneth M
Journal of the American Chemical Society,
11/2018, Letnik:
140, Številka:
45
Journal Article
Recenzirano
Despite the rich history of experimental studies focusing on the thermochemistry and kinetics associated with the chelate effect, molecular-level computational studies on the chelate ring ...opening/ring closure are scarce. The challenge lies in an accurate description of both the metal ion and its aqueous environment. Herein, we demonstrate that an optimized 12-6-4 Lennard-Jones (LJ) model can capture the thermodynamics and provide detailed structural and mechanistic insights into the formation of ethylenediamine (en) complexes with metal ions. The water molecules in the first solvation shell of the metal ion are found to facilitate the chelate ring formation. The optimized parameters further simulate the formation of bis and tris(en) complexes representing the wide applicability of the model to simulate coordination chemistry and self-assembly processes.
Commonly seen in rare-earth chemistry and materials science, highly charged metal ions play key roles in many chemical processes. Computer simulations have become an important tool for scientific ...research nowadays. Meaningful simulations require reliable parameters. In the present work, we parametrized 18 M(III) and 6 M(IV) metal ions for four new water models (OPC3, OPC, TIP3P-FB, TIP4P-FB) in conjunction with each of the 12-6 and 12-6-4 nonbonded models. Similar to what was observed previously, issues with the 12-6 model can be fixed by using the 12-6-4 model. Moreover, the four new water models showed comparable performance or considerable improvement over the previous water models (TIP3P, SPC/E, and TIP4PEW) in the same category (3-point or 4-point water models, respectively). Finally, we reported a study of a metalloprotein system demonstrating the capability of the 12-6-4 model to model metalloproteins. The reported parameters will facilitate accurate simulations of highly charged metal ions in aqueous solution.
While accurately modeling the conformational ensemble is required for predicting properties of flexible molecules, the optimal method of obtaining the conformational ensemble appears as varied as ...their applications. Ensemble structures have been modeled by generation, refinement, and clustering of conformations with a sufficient number of samples. We present a conformational clustering algorithm intended to automate the conformational clustering step through the Louvain algorithm, which requires minimal hyperparameters and importantly no predefined number of clusters or threshold values. The conformational graphs produced by this method for O-succinyl-l-homoserine, oxidized nicotinamide adenine dinucleotide, and 200 representative metabolites each preserved the geometric/energetic correlation expected for points on the potential energy surface. Clustering based on these graphs provides partitions informed by the potential energy surface. Automating conformational clustering in a workflow with AutoGraph may mitigate human biases introduced by guess and check over hyperparameter selection while allowing flexibility to the result by not imposing predefined criteria other than optimizing the model’s loss function. Associated codes are available at https://github.com/TanemuraKiyoto/AutoGraph.
Currently the Protein Data Bank (PDB) contains over 25 000 structures that contain a metal ion including Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Pd, Ag, Cd, Ir, Pt, Au, and Hg. In general, ...carrying out classical molecular dynamics (MD) simulations of metalloproteins is a convoluted and time-consuming process. Herein, we describe MCPB (Metal Center Parameter Builder), which allows one to conveniently and rapidly incorporate metal ions using the bonded plus electrostatics model (Hoops et al. J. Am. Chem. Soc. 1991, 113, 8262−8270) into the AMBER force field (FF). MCPB was used to develop a zinc FF, ZAFF, which is compatible with the existing AMBER FFs. The PDB was mined for all Zn-containing structures with most being tetrahedrally bound. The most abundant primary shell ligand combinations were extracted, and FFs were created. These include Zn bound to CCCC, CCCH, CCHH, CHHH, HHHH, HHHO, HHOO, HOOO, HHHD, and HHDD (O = water and the remaining are 1-letter amino acid codes). Bond and angle force constants and RESP charges were obtained from B3LYP/6-31G* calculations of model structures from the various primary shell combinations. MCPB and ZAFF can be used to create FFs for MD simulations of metalloproteins to study enzyme catalysis, drug design, and metalloprotein crystal refinement.
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