Linear scaling explicitly correlated MP2-F12 and ONIOM methods for the long-range interactions of the nanoscale clusters in methanol aqueous solutions

Fault-tolerant quantum chemical calculations with improved machine-learning models

Easy and effective usage of computational resources is crucial for scientific calculations. Following our recent work of machine-learning (ML) assisted scheduling optimization [J. Comput. Chem. 2023, 44, 1174], we further propose (1) the improved ML models for the better predictions of computational loads, and as such, more elaborate load-balancing calculations can be expected; (2) the idea of coded computation, that is, the integration of gradient coding, in order to introduce fault tolerance during the distributed calculations; and (3) their applications together with re-normalized exciton model with time-dependent density functional theory (REM-TDDFT) for calculating the excited states. Illustrated benchmark calculations include P38 protein, and solvent model with one or several excitable centers. The results show that the improved ML-assisted coded calculations can further improve the load-balancing and cluster utilization, owing primarily profit in fault tolerance that aims at the automated quantum chemical calculations for both ground and excited states.

Machine-learning assisted scheduling optimization and its application in quantum chemical calculations

Easy and effective usage of computational resources is crucial for scientific calculations, both from the perspectives of timeliness and economic efficiency. This work proposes a bi-level optimization framework to optimize the computational sequences. Machine-learning (ML) assisted static load-balancing, and different dynamic load-balancing algorithms can be integrated. Consequently, the computational and scheduling engine of the ParaEngine is developed to invoke optimized quantum chemical (QC) calculations. Illustrated benchmark calculations include high-throughput drug suit, solvent model, P38 protein, and SARS-CoV-2 systems. The results show that the usage rate of given computational resources for high throughput and large-scale fragmentation QC calculations can primarily profit, and faster accomplishing computational tasks can be expected when employing high-performance computing (HPC) clusters.

Amphiphilic Nanointerface: Inducing the Interfacial Activation for Lipase

Graphene-based materials are widely used in the field of immobilized enzymes due to their easily tunable interfacial properties. We designed amphiphilic nanobiological interfaces between graphene oxide (GO) and lipase TL (Thermomyces lanuginosus) with tunable reduction degrees through molecular dynamics simulations and a facile chemical modulation, thus revealing the optimal interface for the interfacial activation of lipase TL and addressing the weakness of lipase TL, which exhibits weak catalytic activity due to an inconspicuous active site lid. It was demonstrated that the reduced graphene oxide (rGO) after 4 h of ascorbic acid reduction could boost the relative enzyme activity of lipase TL to reach 208%, which was 48% higher than the pristine GO and 120% higher than the rGO after 48 h of reduction. Moreover, TL-GO-4 h's tolerance against heat, organic solvent, and long-term storage environment was higher than that of free TL. The drawbacks of strong hydrophobic nanomaterials on lipase production were explored in depth with the help of molecular dynamics simulations, which explained the mechanism of enzyme activity enhancement. We demonstrated that nanomaterials with certain hydrophilicity could facilitate the lipase to undergo interfacial activation and improve its stability and protein loading rate, displaying the potential of the extensive application.

Generalized energy-based fragmentation approach for calculations of solvation energies of large systems

A generalized energy-based fragmentation (GEBF) approach has been combined with a universal solvation model based on solute electron density (SMD) to compute the solvation energies of general large systems (such as protein molecules) in solutions. In the GEBF-SMD method, the solvation energy of a target system could be combined by the corresponding solvation energies of various subsystems, each of which is embedded in the background point charges and surface charges on the surface of solute cavity at the positions of its atoms and neighbouring atoms outside of the subsystem. Our results show that the GEBF-SMD model could reproduce the conventional SMD solvation energies quite well for various proteins in solutions, and could significantly reduce the computational costs for the SMD calculations of large proteins. In addition, the GEBF-SMD approach is almost independent of the basis sets and the types of solvents (including protic, polar, and nonpolar ones). Also, the GEBF-SMD approach could reproduce the relative energies of various conformers of large systems in solutions. Therefore, the GEBF-SMD method is expected to be applicable for computing the solvation energies of a broad range of large systems.

Accurate prediction of the structure and vibrational spectra of ionic liquid clusters with the generalized energy-based fragmentation approach: critical role of ion-pair-based fragmentation

The GEBF method with the ion-pair-based fragmentation has been developed to facilitate ab initio calculations of general ionic liquid clusters.

Are fragment-based quantum chemistry methods applicable to medium-sized water clusters?

The GEBF method is demonstrated to be more accurate than the EE-MB method for medium-sized water clusters.

Atomistic simulation for coil-to-globule transition of poly(2-dimethylaminoethyl methacrylate)

The coil-to-globule transition of poly(2-dimethylaminoethyl methacrylate) (PDMAEMA) in aqueous solution was investigated by all-atomistic molecular dynamics simulations. The polymer consistent force field (PCFF) was applied to the PDMAEMA model with a proper protonation state. The structural analysis indicates a distinct difference in the hydration state of particular functional groups of PDMAEMA as well as in the conformational state of PDMAEMA below and above the lower critical solution temperature (LCST). In particular, by monitoring the motion of water molecules, we observe that water molecules in the vicinity of the carbonyl group are relatively restricted to the motion in the globule state due to the extended relaxation time of hydrogen bonds among water molecules. The degree of protonation was also adjusted to study the effect of protonation on the conformational state of PDMAEMA.

Generalized energy-based fragmentation approach and its applications to macromolecules and molecular aggregates

Conspectus The generalized energy-based fragmentation (GEBF) approach provides a very simple way of approximately evaluating the ground-state energy or properties of a large system in terms of ground-state energies of various small "electrostatically embedded" subsystems, which can be calculated with any traditional ab initio quantum chemistry (X) method (X = Hartree-Fock, density functional theory, and so on). Due to its excellent parallel efficiency, the GEBF approach at the X theory level (GEBF-X) allows full quantum mechanical (QM) calculations to be accessible for systems with hundreds and even thousands of atoms on ordinary workstations. The implementation of the GEBF approach at various theoretical levels can be easily done with existing quantum chemistry programs. This Account reviews the methodology, implementation, and applications of the GEBF-X approach. This method has been successfully applied to optimize the structures of various large systems including molecular clusters, polypeptides, proteins, and foldamers. Such investigations could allow us to elucidate the origin and nature of the cooperative interaction in secondary structures of long peptides or the driving force of the self-assembly processes of aromatic oligoamides. These GEBF-based QM calculations reveal that the structures and stability of various complex systems result from a subtle balance of many types of noncovalent interactions such as hydrogen bonding and van der Waals interactions. The GEBF-based ab initio molecular dynamics (AIMD) method also allows the investigation of dynamic behaviors of large systems on the order of tens of picoseconds. It was demonstrated that the conformational dynamics of two model peptides predicted by GEBF-based AIMD are noticeably different from those predicted by the classical force field MD method. With the target of extending QM calculations to molecular aggregates in the condensed phase, we have implemented the GEBF-based multilayer hybrid models, which could provide satisfactory descriptions of the binding energies between a solute molecule and its surrounding waters and the chain-length dependence of the conformational changes of oligomers in aqueous solutions. A coarse-grained polarizable molecular mechanics model, furnished with GEBF-X dipole moments of subsystems, exhibits some advantages of treating the electrostatic polarization with reduced computational costs. We anticipate that the GEBF approach will continue to develop with the ultimate goal of studying complicated phenomena at mesoscopic scales and serve as a practical tool to elucidate the structure and dynamics of chemical and biological systems.

Improved cluster-in-molecule local correlation approach for electron correlation calculation of large systems

An improved cluster-in-molecule (CIM) local correlation approach is developed to allow electron correlation calculations of large systems more accurate and faster. We have proposed a refined strategy of constructing virtual LMOs of various clusters, which is suitable for basis sets of various types. To recover medium-range electron correlation, which is important for quantitative descriptions of large systems, we find that a larger distance threshold (ξ) is necessary for highly accurate results. Our illustrative calculations show that the present CIM-MP2 (second-order Møller-Plesser perturbation theory, MP2) or CIM-CCSD (coupled cluster singles and doubles, CCSD) scheme with a suitable ξ value is capable of recovering more than 99.8% correlation energies for a wide range of systems at different basis sets. Furthermore, the present CIM-MP2 scheme can provide reliable relative energy differences as the conventional MP2 method for secondary structures of polypeptides.

Parametrization of an Orbital-Based Linear-Scaling Quantum Force Field for Noncovalent Interactions

We parametrize a linear-scaling quantum mechanical force field called mDC for the accurate reproduction of nonbonded interactions. We provide a new benchmark database of accurate ab initio interactions between sulfur-containing molecules. A variety of nonbond databases are used to compare the new mDC method with other semiempirical, molecular mechanical, ab initio, and combined semiempirical quantum mechanical/molecular mechanical methods. It is shown that the molecular mechanical force field significantly and consistently reproduces the benchmark results with greater accuracy than the semiempirical models and our mDC model produces errors twice as small as the molecular mechanical force field. The comparisons between the methods are extended to the docking of drug candidates to the Cyclin-Dependent Kinase 2 protein receptor. We correlate the protein-ligand binding energies to their experimental inhibition constants and find that the mDC produces the best correlation. Condensed phase simulation of mDC water is performed and shown to produce O-O radial distribution functions similar to TIP4P-EW.

Analysis of the Errors in the Electrostatically Embedded Many-Body Expansion of the Energy and the Correlation Energy for Zn and Cd Coordination Complexes with Five and Six Ligands and Use of the Analysis to Develop a Generally Successful Fragmentation Strategy

In the present paper, we apply the electrostatically embedded many-body expansion of the correlation energy (EE-MB-CE) to the calculation of zinc-ligand and cadmium-ligand bond dissociation energies, and we analyze the errors due to various fragmentation schemes in a variety of neutral, positively charged, and negatively charged Zn²⁺ and Cd²⁺ coordination complexes. As a result of the analysis, we are able to present a new, simple, and unambiguous fragmentation strategy. Following this strategy, we show that both methods perform well for zinc-ligand and cadmium-ligand bond dissociation energies for all systems studied in the paper, including a model of the catalytic site of the zinc-bearing anthrax toxin lethal factor (LF), which has garnered substantial attention as a target for drug development. To draw general conclusions we consider ten pentacoordinate and hexacoordinate zinc and cadmium containing coordination complexes, each with 10 or 15 different fragmentation schemes. By analyzing errors, we developed a prescription for the optimal fragmentation strategy. With this scheme, and using MP2 correlation energies as a test, we find that the electrostatically embedded three-body expansion of the correlation energy (EE-3B-CE) method is able to reproduce all 53 conventionally calculated bond energies with an average absolute error of only 0.59 kcal/mol. The paper also presents EE-MB-CE calculations using the CCSD(T) level of theory on an LF model system. With CCSD(T), EE-3B-CE has an average error of 0.30 kcal/mol.