The latest release of NWChem delivers an open-source computational chemistry package with extensive capabilities for large scale simulations of chemical and biological systems. Utilizing a common computational framework, diverse theoretical descriptions can be used to provide the best solution for a given scientific problem. Scalable parallel implementations and modular software design enable efficient utilization of current computational architectures. This paper provides an overview of NWChem focusing primarily on the core theoretical modules provided by the code and their parallel performance.

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Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

We have investigated intrinsic point defects in ZnO and extended this study to Li, Cu and Al impurity centres. Atomic and electronic structures as well as defect energies have been obtained for the main oxidation states of all defects using our embedded cluster hybrid quantum mechanical/molecular mechanical approach to the treatment of localised states in ionic solids. With these calculations we were able to explain the nature of a number of experimentally observed phenomena. We show that in zinc excess materials the energetics of zinc interstitial are very similar to those for oxygen vacancy formation. Our results also suggest assignments for a number of bands observed in photoluminescence and other spectroscopic studies of the material.

We describe the procedure to start an SCF calculation of the general type from a sum of atomic electron densities, as implemented in GAMESS-UK. Although the procedure is well known for closed-shell calculations and was already suggested when the Direct SCF procedure was proposed, the general procedure is less obvious. For instance, there is no need to converge the corresponding closed-shell Hartree-Fock calculation when dealing with an open-shell species. We describe the various choices and illustrate them with test calculations, showing that the procedure is easier, and on average better, than starting from a converged minimal basis calculation and much better than using a bare nucleus Hamiltonian.

Parallel hardware has become readily available to the computational chemistry research community. This perspective will review the current state of parallel computational chemistry software utilizing high-performance parallel computing platforms. Hardware and software trends and their effect on quantum chemistry methodologies, algorithms, and software development will also be discussed.

We have investigated the description of excited state relaxation in naked and hydrated TiO2 nanoparticles using Time-Dependent Density Functional Theory (TD-DFT) with three common hybrid exchange-correlation (XC) potentials: B3LYP, CAM-B3LYP and BHLYP. Use of TD-CAM-B3LYP and TD-BHLYP yields qualitatively similar results for all structures, which are also consistent with predictions of coupled-cluster theory for small particles. TD-B3LYP, in contrast, is found to make rather different predictions; including apparent conical intersections for certain particles that are not observed with TD-CAM-B3LYP nor with TD-BHLYP. In line with our previous observations for vertical excitations, the issue with TD-B3LYP appears to be the inherent tendency of TD-B3LYP, and other XC potentials with no or a low percentage of Hartree-Fock like exchange, to spuriously stabilize the energy of charge-transfer (CT) states. Even in the case of hydrated particles, for which vertical excitations are generally well described with all XC potentials, the use of TD-B3LYP appears to result in CT problems during excited state relaxation for certain particles. We hypothesize that the spurious stabilization of CT states by TD-B3LYP even may drive the excited state optimizations to different excited state geometries from those obtained using TD-CAM-B3LYP or TD-BHLYP. Finally, focusing on the TD-CAM-B3LYP and TD-BHLYP results, excited state relaxation in small naked and hydrated TiO2 nanoparticles is predicted to be associated with a large Stokes' shift.

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel noncovalent smallmolecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (M pro ) by employing a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this M pro inhibitor with an inhibition constant (K i ) of 2.9 μM (95% CI 2.2, 4.0). Furthermore, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of M pro forming stable hydrogen bond and hydrophobic interactions. We then used multiple μs-time scale molecular dynamics (MD) simulations and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by M pro , involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits M pro and offers a springboard for further therapeutic design.