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 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 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.

scholarly journals Present-Day Radiocarbon Content of Select Flavoring Compounds Reveals Vanillin Production Pathway

Radiocarbon ◽  
2013 ◽  
Vol 55 (3) ◽  
pp. 1819-1826 ◽  
Author(s):  
Randy Culp ◽  
G V Ravi Prasad
Keyword(s):  
Stable Isotope ◽  
Fossil Fuel ◽  
Agricultural Products ◽  
Clove Oil ◽  
Isotopic Data ◽  
Established Method ◽  
New Methods ◽  
Isotopic Methods ◽  
Isotope Studies ◽  
The University

Radiocarbon and stable isotope determination in foods, flavors, and beverages, for the authentication of source material and process of formation, is a well-established method of identity used in industry. New methods of provenance determination, using stable isotopes of oxygen and hydrogen, have added to the host of other isotopic methods used for characterizing natural or botanically derived products. The unambiguous determinant of a product's fossil fuel origin be it from petroleum, natural gas, or coal, is through the measurement of its 14C content. The 14C content can also be used to determine the fraction dilution of recently grown and harvested material with that derived from fossil fuel, and even confirms the vintage of agricultural products based on the well-established decrease of bomb-produced atmospheric 14C. This paper documents 14C measurements at the University of Georgia's Center for Applied Isotope Studies accelerator mass spectrometry and stable isotope laboratories, over the last 3 yr, for 10 important flavoring compounds. By establishing an accurate and current level of 14C in botanically derived products, we were able to confirm a particular source for vanilla production, the most popular consumer flavor in the marketplace. Over the years, vanilla extract has been produced less and less from vanilla beans (Vanilla planifolia), particularly those from Madagascar and the Comoros Islands, and more from other botanical precursors such as ferulic acid, clove oil, and guaiacol. We report isotopic data to support this precursor for vanilla production based on high 14C levels accumulated during the tree's life, incorporated in the tree rings and their associated stable isotope abundances.

Free energies of solvation with quantum mechanical interaction energies from classical mechanical simulations

1999 ◽  
Vol 110 (3) ◽  
pp. 1329-1337 ◽  
Author(s):  
Robert H. Wood ◽  
Eric M. Yezdimer ◽  
Shinichi Sakane ◽  
Jose A. Barriocanal ◽  
Douglas J. Doren
Keyword(s):  
Quantum Mechanical ◽  
Interaction Energies ◽  
Free Energies ◽  
Mechanical Interaction

Benzene and Tropilium Metal Complexes. Intra- and Intermolecular Interaction Evidenced by Vibrational Analysis:  The Blue-Shift Hydrogen Bond

2006 ◽  
Vol 25 (21) ◽  
pp. 5024-5030 ◽  
Author(s):  
Pier Luigi Stanghellini ◽  
Eliano Diana ◽  
Aldo Arrais ◽  
Andrea Rossin ◽  
Sidney F. A. Kettle
Keyword(s):  
Hydrogen Bond ◽  
Metal Complexes ◽  
Intermolecular Interaction ◽  
Vibrational Analysis ◽  
Blue Shift

HeadTalk, HandTalk and the corpus: towards a framework for multi-modal, multi-media corpus development

Corpora ◽  
2009 ◽  
Vol 4 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Dawn Knight ◽  
David Evans ◽  
Ronald Carter ◽  
Svenja Adolphs
Keyword(s):  
Social Science ◽  
Research Community ◽  
Ethical Challenges ◽  
Multiple Streams ◽  
New Methods ◽  
Naturally Occurring ◽  
Multi Media ◽  
The University ◽  
New Generation ◽  
Textual Records

In this paper, we address a number of key methodological challenges and concerns faced by linguists in the development of a new generation of corpora: the multi-modal, multi-media corpus – that which combines video, audio and textual records of naturally occurring discourse. We contextualise these issues according to a research project which is currently developing such a corpus: the ESRC-funded Understanding New Digital Records for e-Social Science (DReSS) project based at the University of Nottingham. 2 2 For further information, results and publications related to the project, please refer to the main DReSS website, at: http://web.mac.com/andy.crabtree/NCeSS_Digital_Records_Node/Welcome.html This paper primarily explores the questions of the functionality of the corpus, identifying the problems we faced in making multi-modal corpora ‘usable’ for further research. We focus on the need for new methods for categorising and marking up multiple streams of data, using, as examples, the coding of head nods and hand gestures. We also consider the challenges faced when integrating and representing the data in a functional corpus tool, to allow for further synthesis and analysis. Here, we also underline some of the ethical challenges faced in the development of this tool, exploring the issues faced both in the collection of data and in the future distribution of video corpora to the wider research community.

Hydrogen-bond directionality at the donor H atom—analysis of interaction energies and database statistics

CrystEngComm ◽  
2009 ◽  
Vol 11 (8) ◽  
pp. 1563 ◽  
Author(s):  
Peter A. Wood ◽  
Frank H. Allen ◽  
Elna Pidcock
Keyword(s):  
Hydrogen Bond ◽  
Interaction Energies
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