42 research outputs found
Supporting information for CCSD(F12*) vs. CCSD-F12b vs. CCSD paper
No full textSupporting information for manuscript, "Do CCSD and approximate CCSD-F12 variants converge to the same basis set limits? The case of atomization energies" by Manoj K. Kesharwani, Nitai Sylvetsky, Andreas Köhn, David P. Tew, and Jan M.L. Martin, J. Chem. Phys., accepted with revision
2019-nCoV vs. SARS-CoV: Which Truly Has a Higher ACE2 Affinity? A Quantum Chemical Perspective on Virus-Receptor Noncovalent Interactions
No full textNoncovalent interaction energetics associated with ACE2 affinity differences are investigated using electronic structure methods; Our results were found to challenge previous predictions – claiming a higher affinity for 2019-nCoV compared to SARS-CoV based merely on "chemical intuition". In addition, we demonstrate that a broadly-used classical molecular dynamics force field – MMFF94 – is clearly incapable of reproducing DFT-based noncovalent interaction energetics for the systems at hand (despite being specifically parameterized for van der Waals interactions)
Toward Simple, Predictive Understanding of Protein-Ligand Interactions: Electronic Structure Calculations Join Forces with the Chemist’s Intuition
No full textContemporary efforts for modeling protein-ligand interactions entail a painful tradeoff – as reliable information on both noncovalent binding factors and the dynamic behavior of a protein-ligand complex is often beyond practical limits. In the following paper, we demonstrate that information drawn exclusively from static molecular structures can be used for the semi-quantitative prediction of experimentally-measured binding affinities for protein-ligand complexes. In the particular case considered here, inhibition constants (Ki) were calculated for eight different ligands of torpedo californica acetylcholinesterase using a simple, multiple-linearregression-based model. The latter, incorporating five informative and independent variables – drawn from QM cluster, DLPNO-CCSD(T) calculations and LED analyses on the eight complexes – is shown to recover no-lessthan 96% of the sum of squares for measured Ki values, and used to predict the inhibition potential for yet another ligand (E20, for which no Ki values are available in the literature). This thus challenges the widespread assumption that “static pictures” are inadequate for predicting reactivity properties of flexible and dynamic protein-ligand systems
Toward Simple, Predictive Understanding of Protein-Ligand Interactions: Electronic Structure Calculations Join Forces with the Chemist’s Intuition
No full text2019-nCoV vs. SARS-CoV: Which Truly Has a Higher ACE2 Affinity? A Quantum Chemical Perspective on Virus-Receptor Noncovalent Interactions
No full textMP2-F12 basis set convergence for the S66 noncovalent interactions benchmark: Transferability of the complementary auxiliary basis set (CABS)
No full textProbing the Basis Set Limit for Thermochemical Contributions of Inner-Shell Correlation: Balance of Core-Core and Core-Valence Contributions
No full textThe inner-shell correlation contributions to the total atomization energies of the W4-17 computational thermochemistry benchmark have been determined at the CCSD(T) level near the basis set limit using several families of core correlation basis sets, such as aug-cc-pCVnZ (n=3-6), aug-cc-pwCVnZ (n=3-5), and nZaPa-CV (n=3-5). The three families of basis sets agree very well with each other (0.01 kcal/mol RMS) when extrapolating from the two largest available basis sets: however, there are considerable differences in convergence behavior for the smaller basis sets. nZaPa-CV is superior for the core-core term and awCVnZ for the core-valence term. While the aug-cc-pwCV(T+d)Z basis set of Yockel and Wilson is superior to aug-cc-pwCVTZ, further extension of this family proved unproductive. The best compromise between accuracy and computational cost, in the context of high-accuracy computational thermochemistry methods such as W4 theory, is CCSD(T)/awCV{T,Q}Z, where the {T,Q} notation stands for extrapolation from the awCVTZ and awCVQZ basis set pair. For lower-cost calculations, a previously proposed combination of CCSD-F12b/cc-pCVTZ-F12 and CCSD(T)/pwCVTZ(no f) appears to ‘give the best bang for the buck’. While core-valence correlation accounts for the lion’s share of the inner shell contribution in first-row molecules, for second-row molecules core-core contributions may become important, particularly in systems like P4and S4with multiple adjacent second-row atoms.[In memory of Dieter Cremer, 1944-2017]</div
Surprising performance for vibrational frequencies of the distinguishable clusters with singles and doubles (DCSD) and MP2.5 approximations
No full textProbing the Basis Set Limit for Thermochemical Contributions of Inner-Shell Correlation: Balance of Core-Core and Core-Valence Contributions
No full textThe inner-shell correlation contributions to the total atomization energies of the W4-17 computational thermochemistry benchmark have been determined at the CCSD(T) level near the basis set limit using several families of core correlation basis sets, such as aug-cc-pCVnZ (n=3-6), aug-cc-pwCVnZ (n=3-5), and nZaPa-CV (n=3-5). The three families of basis sets agree very well with each other (0.01 kcal/mol RMS) when extrapolating from the two largest available basis sets: however, there are considerable differences in convergence behavior for the smaller basis sets. nZaPa-CV is superior for the core-core term and awCVnZ for the core-valence term. While the aug-cc-pwCV(T+d)Z basis set of Yockel and Wilson is superior to aug-cc-pwCVTZ, further extension of this family proved unproductive. The best compromise between accuracy and computational cost, in the context of high-accuracy computational thermochemistry methods such as W4 theory, is CCSD(T)/awCV{T,Q}Z, where the {T,Q} notation stands for extrapolation from the awCVTZ and awCVQZ basis set pair. For lower-cost calculations, a previously proposed combination of CCSD-F12b/cc-pCVTZ-F12 and CCSD(T)/pwCVTZ(no f) appears to ‘give the best bang for the buck’. While core-valence correlation accounts for the lion’s share of the inner shell contribution in first-row molecules, for second-row molecules core-core contributions may become important, particularly in systems like P<sub>4</sub>and S<sub>4</sub>with multiple adjacent second-row atoms.<div>[In memory of Dieter Cremer, 1944-2017]</div></jats:p
Minimally Empirical Double Hybrid Functionals Trained Against the GMTKN55 Database: revDSD-PBEP86-D4, revDOD-PBE-D4, and DOD-SCAN-D4
No full textWe present a family of minimally empirical double-hybrid DFT functionals parametrized against the very large and diverse GMTKN55 benchmark. The very recently proposed wB97M(2) empirical double hybrid (with 16 empirical parameters) has the lowest WTMAD2 (weighted mean absolute deviation over GMTKN55) ever reported at 2.19 kcal/mol. However, our xrevDSD-PBEP86-D4 functional reaches a statistically equivalent WTMAD2=2.22 kcal/mol, using just a handful of empirical parameters, and the xrevDOD-PBEP86-D4 functional reaches 2.25 kcal/mol with just opposite-spin MP2 correlation, making it amenable to reduced-scaling algorithms. In general, the D4 empirical dispersion correction is clearly superior to D3BJ. If one eschews dispersion corrections of any kind, noDispSD-SCAN offers a viable alternative. Parametrization over the entire GMTKN55 dataset yields substantial improvement over the small training set previously employed in the DSD papers
