scholarly journals A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+

2014 ◽  
Author(s):  
Jimmy Charnley Kromann ◽  
Anders Christensen ◽  
Casper Steinmann ◽  
Martin Korth ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Interaction Energy ◽  
Vibrational Analysis ◽  
Attractive Alternative ◽  
Third Generation ◽  
Dispersion Correction ◽  
Free Energies ◽  
Small Proteins

We present new dispersion and hydrogen bond corrections to the PM6 method, PM6-D3H+, and its implementation in the GAMESS program. The method combines the DFT-D3 dispersion correction by Grimme et al with a modified version of the H+ hydrogen bond correction by Korth. Overall, the interaction energy of PM6-D3H+ is very similar to PM6-DH2 and PM6-DH+, with RMSD and MAD values within 0.02 kcal/mol of one another. The main difference is that the geometry optimizations of 88 complexes result in 82, 6, 0, and 0 geometries with 0, 1, 2, and $\ge$ 3 imaginary frequencies using PM6-D3H+ implemented in GAMESS, while the corresponding numbers for PM6-DH+ implemented in MOPAC are 54, 17, 15, and 2. The PM6-D3H+ method as implemented in GAMESS offers an attractive alternative to PM6-DH+ in MOPAC in cases where the LBFGS optimizer must be used and a vibrational analysis is needed, e.g. when computing vibrational free energies. While the GAMESS implementation is up to 10 times slower for geometry optimizations of proteins in bulk solvent, compared to MOPAC, it is sufficiently fast to make geometry optimizations of small proteins practically feasible.

scholarly journals A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+

2014 ◽  
Author(s):  
Jimmy Charnley Kromann ◽  
Anders Christensen ◽  
Casper Steinmann ◽  
Martin Korth ◽  
Jan H. Jensen
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Interaction Energy ◽  
Vibrational Analysis ◽  
Attractive Alternative ◽  
Third Generation ◽  
Dispersion Correction ◽  
Free Energies ◽  
Small Proteins

We present new dispersion and hydrogen bond corrections to the PM6 method, PM6-D3H+, and its implementation in the GAMESS program. The method combines the DFT-D3 dispersion correction by Grimme et al with a modified version of the H+ hydrogen bond correction by Korth. Overall, the interaction energy of PM6-D3H+ is very similar to PM6-DH2 and PM6-DH+, with RMSD and MAD values within 0.02 kcal/mol of one another. The main difference is that the geometry optimizations of 88 complexes result in 82, 6, 0, and 0 geometries with 0, 1, 2, and $\ge$ 3 imaginary frequencies using PM6-D3H+ implemented in GAMESS, while the corresponding numbers for PM6-DH+ implemented in MOPAC are 54, 17, 15, and 2. The PM6-D3H+ method as implemented in GAMESS offers an attractive alternative to PM6-DH+ in MOPAC in cases where the LBFGS optimizer must be used and a vibrational analysis is needed, e.g. when computing vibrational free energies. While the GAMESS implementation is up to 10 times slower for geometry optimizations of proteins in bulk solvent, compared to MOPAC, it is sufficiently fast to make geometry optimizations of small proteins practically feasible.

scholarly journals New methods for computational drug design

2015 ◽  
Author(s):  
Jimmy Charnley Kromann
Keyword(s):  
Hydrogen Bond ◽  
Vibrational Analysis ◽  
Attractive Alternative ◽  
Interaction Energies ◽  
Free Energies ◽  
Order Of Accuracy ◽  
Computational Drug Design ◽  
New Methods ◽  
Small Proteins ◽  
The University

This thesis describes the work that has been carried out in connection with my Masters at the University of Copenhagen. This work has led to new dispersion and hydrogen bond corrections to the PM6 method, PM6-D3H+, and its implementation in the GAMESS program. The method combines the DFT-D3 dispersion correction by Grimme et al. with a modified version of the H+ hydrogen bond correction by Korth. This work also included the implementation of the new HF-3c method in GAMESS and its interface with the fragmentation method FMO. Overall, the interaction energy of PM6-D3H+ is very similar to PM6-DH2 and PM6-DH+, with RMSD and MAD values within 0.02 kcal/mol of one another. HF-3c also shows interaction energies within the same order of accuracy as the PM6 based methods. The main difference is that the geometry optimizations of 88 complexes result in 82, 6, 0, and 0 geometries with 0, 1, 2, and 3 or more imaginary frequencies using PM6-D3H+ implemented in GAMESS, while the corresponding numbers for PM6-DH+ implemented in MOPAC are 54, 17, 15, and 2. PM6-D3H+ and FMO2-HF- 3c in GAMESS was used to optimize two small proteins which resulted in a much more reliable structure compared to the reference structures, than PM6-DH+ in MOPAC, most likely due to the different optimization algorithms associated with the programs. The PM6-D3H+ method as implemented in GAMESS offers an attractive alternative to PM6-DH+ in MOPAC in cases where the LBFGS optimizer must be used and a vibrational analysis is needed, e.g., when computing vibrational free energies. While the GAMESS implementation is up to 10 times slower for geometry optimizations of proteins in bulk solvent compared to MOPAC, it is sufficiently fast to make geometry optimizations of small proteins practically feasible.

scholarly journals New methods for computational drug design

2015 ◽  
Author(s):  
Jimmy Charnley Kromann
Keyword(s):  
Hydrogen Bond ◽  
Vibrational Analysis ◽  
Attractive Alternative ◽  
Interaction Energies ◽  
Free Energies ◽  
Order Of Accuracy ◽  
Computational Drug Design ◽  
New Methods ◽  
Small Proteins ◽  
The University

This thesis describes the work that has been carried out in connection with my Masters at the University of Copenhagen. This work has led to new dispersion and hydrogen bond corrections to the PM6 method, PM6-D3H+, and its implementation in the GAMESS program. The method combines the DFT-D3 dispersion correction by Grimme et al. with a modified version of the H+ hydrogen bond correction by Korth. This work also included the implementation of the new HF-3c method in GAMESS and its interface with the fragmentation method FMO. Overall, the interaction energy of PM6-D3H+ is very similar to PM6-DH2 and PM6-DH+, with RMSD and MAD values within 0.02 kcal/mol of one another. HF-3c also shows interaction energies within the same order of accuracy as the PM6 based methods. The main difference is that the geometry optimizations of 88 complexes result in 82, 6, 0, and 0 geometries with 0, 1, 2, and 3 or more imaginary frequencies using PM6-D3H+ implemented in GAMESS, while the corresponding numbers for PM6-DH+ implemented in MOPAC are 54, 17, 15, and 2. PM6-D3H+ and FMO2-HF- 3c in GAMESS was used to optimize two small proteins which resulted in a much more reliable structure compared to the reference structures, than PM6-DH+ in MOPAC, most likely due to the different optimization algorithms associated with the programs. The PM6-D3H+ method as implemented in GAMESS offers an attractive alternative to PM6-DH+ in MOPAC in cases where the LBFGS optimizer must be used and a vibrational analysis is needed, e.g., when computing vibrational free energies. While the GAMESS implementation is up to 10 times slower for geometry optimizations of proteins in bulk solvent compared to MOPAC, it is sufficiently fast to make geometry optimizations of small proteins practically feasible.

scholarly journals Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Christoph A. Bauer ◽  
Gisbert Schneider ◽  
Andreas H. Göller
Keyword(s):  
Machine Learning ◽  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Training Data ◽  
Free Energies ◽  
Hydrogen Bond Donor ◽  
Chemical Application ◽  
Hydrogen Bond Acceptor ◽  
Donor And Acceptor ◽  
Target Values

Abstract We present machine learning (ML) models for hydrogen bond acceptor (HBA) and hydrogen bond donor (HBD) strengths. Quantum chemical (QC) free energies in solution for 1:1 hydrogen-bonded complex formation to the reference molecules 4-fluorophenol and acetone serve as our target values. Our acceptor and donor databases are the largest on record with 4426 and 1036 data points, respectively. After scanning over radial atomic descriptors and ML methods, our final trained HBA and HBD ML models achieve RMSEs of 3.8 kJ mol−1 (acceptors), and 2.3 kJ mol−1 (donors) on experimental test sets, respectively. This performance is comparable with previous models that are trained on experimental hydrogen bonding free energies, indicating that molecular QC data can serve as substitute for experiment. The potential ramifications thereof could lead to a full replacement of wetlab chemistry for HBA/HBD strength determination by QC. As a possible chemical application of our ML models, we highlight our predicted HBA and HBD strengths as possible descriptors in two case studies on trends in intramolecular hydrogen bonding.

Exploring the rare S—H...S hydrogen bond using charge density analysis in isomers of mercaptobenzoic acid

2017 ◽  
Vol 73 (4) ◽  
pp. 626-633 ◽  
Author(s):  
Mysore. S Pavan ◽  
Sounak Sarkar ◽  
Tayur N. Guru Row
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Charge Density ◽  
Interaction Energy ◽  
Electron Density ◽  
Type I ◽  
Weak Hydrogen Bond ◽  
Topological Features ◽  
Density Analysis ◽  
Density Study

Experimental and theoretical charge density analyses on isomers of mercaptobenzoic acid have been carried out to quantify the hydrogen bonding of the hitherto less explored thiols, to assess the strength of the interactions using the topological features of the electron density. The electron density study offers interesting insights into the nature of the S—H...S interaction. The interaction energy is comparable with that of a weak hydrogen bond. The strength and directionality of the S—H...S hydrogen bond is demonstrated to be mainly due to the conformation locking potential of the intramolecular S...O chalcogen bond in 2-mercaptobenzoic acid and is stronger than in 3-mercaptobenzoic acid, which lacks the intramolecular S...O bond. Thepara-substituted mercaptobenzoic acid depicts a type I S...S interaction.

A hand-twisted helical crystal based solely on hydrogen bonding

2017 ◽  
Vol 53 (47) ◽  
pp. 6371-6374 ◽  
Author(s):  
Subhankar Saha ◽  
Gautam R. Desiraju
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Crystal Engineering ◽  
Halogen Bond ◽  
Third Generation

Third-generation crystal engineering: using halogen bond/hydrogen bond equivalence.

Interaction of Gold Atom with Clusters of Water: Few Computational Mise-En-Scènes with Hydrogen Bonding Motif

2008 ◽  
Vol 73 (11) ◽  
pp. 1457-1474 ◽  
Author(s):  
Eugene S. Kryachko
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Computational Model ◽  
Photoelectron Spectroscopy ◽  
Water Clusters ◽  
Gold Atom ◽  
Proton Acceptor ◽  
Anion Photoelectron Spectroscopy ◽  
Relationship Of ◽  
First Time

The present work outlines the fair relationship of the computational model with the experiments on anion photoelectron spectroscopy for the gold-water complexes [Au(H2O)1≤n≤2]- that is established between the auride anion Au- and water monomer and dimer thanks to the nonconventional hydrogen bond where Au- casts as the nonconventional proton acceptor. This work also extends the computational model to the larger complexes [Au(H2O)3≤n≤5]- where gold considerably thwarts the shape of water clusters and even particularly breaks their conventional hydrogen bonding patterns. The fascinating phenomenon of the lavish proton acceptor character of Au- to form at least six hydrogen bonds with molecules of water is computationally unveiled in the present work for the first time.

Theoretical study of hydrogen bonding interactions in substituted nitroxide radicals

2021 ◽  
Author(s):  
Thufail M. Ismail ◽  
Neetha Mohan ◽  
P. K. Sajith
Keyword(s):  
Hydrogen Bonding ◽  
Interaction Energy ◽  
Electrostatic Potential ◽  
Molecular Electrostatic Potential ◽  
Theoretical Study ◽  
Nitroxide Radicals ◽  
Hydrogen Bonding Interactions ◽  
Bonded Complexes ◽  
Hydrogen Bonded

Interaction energy (Eint) of hydrogen bonded complexes of nitroxide radicals can be assessed in terms of the deepest minimum of molecular electrostatic potential (Vmin).

Rietveld refinement of the cocrystal 2,4-dihydroxybenzoic acid–N′-(propan-2-ylidene)nicotinohydrazide (1/1)

2012 ◽  
Vol 68 (9) ◽  
pp. o335-o337 ◽  
Author(s):  
Saul H. Lapidus ◽  
Andreas Lemmerer ◽  
Joel Bernstein ◽  
Peter W. Stephens
Keyword(s):  
Hydrogen Bond ◽  
Hydrogen Bonding ◽  
Powder Diffraction ◽  
Supramolecular Assembly ◽  
Covalent Bond ◽  
Analytical Tool ◽  
Powder Diffraction Data ◽  
Dihydroxybenzoic Acid ◽  
Bond Forming ◽  
Hydrogen Bond Interactions

A further example of using a covalent-bond-forming reaction to alter supramolecular assembly by modification of hydrogen-bonding possibilities is presented. This concept was introduced by Lemmerer, Bernstein & Kahlenberg [CrystEngComm(2011),13, 55–59]. The title structure, C9H11N3O·C7H6O4, which consists of a reacted niazid molecule,viz.N′-(propan-2-ylidene)nicotinohydrazide, and 2,4-dihydroxybenzoic acid, was solved from powder diffraction data using simulated annealing. The results further demonstrate the relevance and utility of powder diffraction as an analytical tool in the study of cocrystals and their hydrogen-bond interactions.

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