1
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Giese TJ, Zeng J, Lerew L, McCarthy E, Tao Y, Ekesan Ş, York DM. Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields. J Phys Chem B 2024; 128:6257-6271. [PMID: 38905451 DOI: 10.1021/acs.jpcb.4c01466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
We present software infrastructure for the design and testing of new quantum mechanical/molecular mechanical and machine-learning potential (QM/MM-ΔMLP) force fields for a wide range of applications. The software integrates Amber's molecular dynamics simulation capabilities with fast, approximate quantum models in the xtb package and machine-learning potential corrections in DeePMD-kit. The xtb package implements the recently developed density-functional tight-binding QM models with multipolar electrostatics and density-dependent dispersion (GFN2-xTB), and the interface with Amber enables their use in periodic boundary QM/MM simulations with linear-scaling QM/MM particle-mesh Ewald electrostatics. The accuracy of the semiempirical models is enhanced by including machine-learning correction potentials (ΔMLPs) enabled through an interface with the DeePMD-kit software. The goal of this paper is to present and validate the implementation of this software infrastructure in molecular dynamics and free energy simulations. The utility of the new infrastructure is demonstrated in proof-of-concept example applications. The software elements presented here are open source and freely available. Their interface provides a powerful enabling technology for the design of new QM/MM-ΔMLP models for studying a wide range of problems, including biomolecular reactivity and protein-ligand binding.
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Affiliation(s)
- Timothy J Giese
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Jinzhe Zeng
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Lauren Lerew
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Erika McCarthy
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Yujun Tao
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Şölen Ekesan
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Darrin M York
- Laboratory for Biomolecular Simulation Research, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, United States
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2
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Zhao P, Xin BS, Ye L, Ma ZT, Yao GD, Shi R, He XH, Lin B, Huang XX, Song SJ. Structurally diverse rearranged sesquiterpenoids, including a pair of rare tautomers, from the aerial parts of Daphne penicillata. PHYTOCHEMISTRY 2024; 218:113950. [PMID: 38101591 DOI: 10.1016/j.phytochem.2023.113950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 11/26/2023] [Accepted: 12/05/2023] [Indexed: 12/17/2023]
Abstract
Eight structurally diverse rearranged sesquiterpenoids, including seven undescribed sesquiterpenoids (1a/1b and 3-8) were obtained from the aerial parts of Daphne penicillata. 1a/1b, 3, 5 and 6 possess rare rearranged guaiane skeletons and 4 represents the first example of rearranged carotene sesquiterpenoids. Their structures and absolute configurations were determined by extensive spectroscopic analyses, NMR and ECD calculations. Interestingly, 1a and 1b were a pair of magical interconverting epimers that may interconvert by retro-aldol condensation. The mechanism of interconversion has been demonstrated indirectly by 9-OH derivatization of 1a/1b and a hypothetical biogenetic pathway was proposed. All compounds were evaluated for anti-inflammatory and cytotoxic activities. Among them, 1a/1b and 2 exhibited potential inhibitory activities on the production of NO against LPS-induced BV2 microglial cells.
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Affiliation(s)
- Peng Zhao
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China
| | - Ben-Song Xin
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China
| | - Li Ye
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China
| | - Zhen-Tao Ma
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China
| | - Guo-Dong Yao
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China
| | - Rui Shi
- Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, International Ecological Foresty Research Center of Kunming, Horticulture and Landscape Architecture, Southwest Forestry University, Yunnan Kunming, 650224, China
| | - Xia-Hong He
- Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, International Ecological Foresty Research Center of Kunming, Horticulture and Landscape Architecture, Southwest Forestry University, Yunnan Kunming, 650224, China
| | - Bin Lin
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, 110016, China.
| | - Xiao-Xiao Huang
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China; Basic Science Research Center Base (Pharmaceutical Science), Shandong Province, Yantai University, Yantai, 264005, China.
| | - Shao-Jiang Song
- Key Laboratory of Computational Chemistry-Based Natural Antitumor Drug Research & Development, Liaoning Province, China; Engineering Research Center of Natural Medicine Active Molecule Research & Development, Liaoning Province, China; Key Laboratory of Natural Bioactive Compounds Discovery & Modification, Shenyang, China; School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, Liaoning, 110016, China.
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3
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Pan X, Zhao F, Zhang Y, Wang X, Xiao X, Zhang JZH, Ji C. MolTaut: A Tool for the Rapid Generation of Favorable Tautomer in Aqueous Solution. J Chem Inf Model 2023; 63:1833-1840. [PMID: 36939644 DOI: 10.1021/acs.jcim.2c01393] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2023]
Abstract
Fast and proper treatment of the tautomeric states for drug-like molecules is critical in computer-aided drug discovery since the major tautomer of a molecule determines its pharmacophore features and physical properties. We present MolTaut, a tool for the rapid generation of favorable states of drug-like molecules in water. MolTaut works by enumerating possible tautomeric states with tautomeric transformation rules, ranking tautomers with their relative internal energies and solvation energies calculated by AI-based models, and generating preferred ionization states according to predicted microscopic pKa. Our test shows that the ranking ability of the AI-based tautomer scoring approach is comparable to the DFT method (wB97X/6-31G*//M062X/6-31G*/SMD) from which the AI models try to learn. We find that the substitution effect on tautomeric equilibrium is well predicted by MolTaut, which is helpful in computer-aided ligand design. The source code of MolTaut is freely available to researchers and can be accessed at https://github.com/xundrug/moltaut. To facilitate the usage of MolTaut by medicinal chemists, we made a free web server, which is available at http://moltaut.xundrug.cn. MolTaut is a handy tool for investigating the tautomerization issue in drug discovery.
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Affiliation(s)
- Xiaolin Pan
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Fanyu Zhao
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.,Department of Chemistry, New York University, New York 10003, United States
| | - Yueqing Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Xingyu Wang
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - Xudong Xiao
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - John Z H Zhang
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China.,Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.,Department of Chemistry, New York University, New York 10003, United States.,Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
| | - Changge Ji
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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4
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Liu Z, Zubatiuk T, Roitberg A, Isayev O. Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. J Chem Inf Model 2022; 62:5373-5382. [PMID: 36112860 DOI: 10.1021/acs.jcim.2c00817] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Computational programs accelerate the chemical discovery processes but often need proper three-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing a huge space of stereoisomers and conformers. We developed the Python-based Auto3D package for generating the low-energy 3D structures using SMILES as the input. Auto3D is based on state-of-the-art algorithms and can automatize the isomer enumeration and duplicate filtering process, 3D building process, geometry optimization, and ranking process. Tested on 50 molecules with multiple unspecified stereocenters, Auto3D is guaranteed to find the stereoconfiguration that yields the lowest-energy conformer. With Auto3D, we provide an extension of the ANI model. The new model, dubbed ANI-2xt, is trained on a tautomer-rich data set. ANI-2xt is benchmarked with DFT methods on geometry optimization and electronic and Gibbs free energy calculations. Compared with ANI-2x, ANI-2xt provides a 42% error reduction for tautomeric reaction energy calculations when using the gold-standard coupled-cluster calculation as the reference. ANI-2xt can accurately predict the energies and is several orders of magnitude faster than DFT methods.
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Affiliation(s)
- Zhen Liu
- Department of Chemistry, Mellon College of Science, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States
| | - Tetiana Zubatiuk
- Department of Chemistry, Mellon College of Science, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States
| | - Adrian Roitberg
- Department of Chemistry, University of Florida, Gainesville, Florida32611, United States
| | - Olexandr Isayev
- Department of Chemistry, Mellon College of Science, Carnegie Mellon University, Pittsburgh, Pennsylvania15213, United States
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5
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Brovarets’ OO, Muradova A, Hovorun DM. Novel horizons of the conformationally-tautomeric transformations of the G·T base pairs: quantum-mechanical investigation. Mol Phys 2022. [DOI: 10.1080/00268976.2022.2026510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Ol’ha O. Brovarets’
- Department of Molecular and Quantum Biophysics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Alona Muradova
- Department of Molecular Biotechnology and Bioinformatics, Institute of High Technologies, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Dmytro M. Hovorun
- Department of Molecular and Quantum Biophysics, Institute of Molecular Biology and Genetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
- Department of Molecular Biotechnology and Bioinformatics, Institute of High Technologies, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
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6
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Deev SL, Shestakova TS, Shenkarev ZO, Paramonov AS, Khalymbadzha IA, Eltsov OS, Charushin VN, Chupakhin ON. 15N Chemical Shifts and JNN-Couplings as Diagnostic Tools for Determination of the Azide-Tetrazole Equilibrium in Tetrazoloazines. J Org Chem 2021; 87:211-222. [PMID: 34941254 DOI: 10.1021/acs.joc.1c02225] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Selectively 15N-labeled tetrazolo[1,5-b][1,2,4]triazines and tetrazolo[1,5-a]pyrimidines bearing one, two, or three 15N labels were synthesized. The synthesized compounds were studied by 1H, 13C, and 15N NMR spectroscopy in DMSO and TFA solutions, where the azide-tetrazole equilibrium can lead to the formation of two tetrazole (T, T') isomers and one azide (A) isomer for each compound. Incorporation of the 15N-label(s) leads to the appearance of 15N-15N coupling constants (JNN), which can be easily measured via simple 1D 15N NMR spectra, even at natural abundance between labeled and unlabeled 15N atoms. The chemical shifts for the 15N nuclei in the azole moiety are very sensitive to the ring opening and azide formation, thus providing information about the azido-tetrazole equilibrium. At the same time, the 1-2JNN couplings between 15N-labeled atoms in the azole and azine fragments unambiguously determine the fusion type between tetrazole and azine rings in the cyclic isomers T and T'. Thus, combined analysis of 15N chemical shifts and JNN values in selectively isotope-enriched compounds provides an effective diagnostic tool for direct structural determination of tetrazole isomers and azide form in solution. This method was found to be the most simple and efficient way to study the azido-tetrazole equilibrium.
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Affiliation(s)
- Sergey L Deev
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia
| | - Tatyana S Shestakova
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia
| | - Zakhar O Shenkarev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10 Miklukho-Maklaya Street, 117997 Moscow, Russia
| | - Alexander S Paramonov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10 Miklukho-Maklaya Street, 117997 Moscow, Russia
| | - Igor A Khalymbadzha
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia
| | - Oleg S Eltsov
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia
| | - Valery N Charushin
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia.,I. Ya. Postovsky Institute of Organic Synthesis of Ural Branch of the Russian Academy of Sciences, 22 Sofya Kovalevskaya Street, 620108 Yekaterinburg, Russia
| | - Oleg N Chupakhin
- Ural Federal University named after the first President of Russia B. N. Yeltsin, 19 Mira Street, 620002 Yekaterinburg, Russia.,I. Ya. Postovsky Institute of Organic Synthesis of Ural Branch of the Russian Academy of Sciences, 22 Sofya Kovalevskaya Street, 620108 Yekaterinburg, Russia
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7
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Wieder M, Fass J, Chodera JD. Fitting quantum machine learning potentials to experimental free energy data: predicting tautomer ratios in solution. Chem Sci 2021; 12:11364-11381. [PMID: 34567495 PMCID: PMC8409483 DOI: 10.1039/d1sc01185e] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 07/05/2021] [Indexed: 11/21/2022] Open
Abstract
The computation of tautomer ratios of druglike molecules is enormously important in computer-aided drug discovery, as over a quarter of all approved drugs can populate multiple tautomeric species in solution. Unfortunately, accurate calculations of aqueous tautomer ratios—the degree to which these species must be penalized in order to correctly account for tautomers in modeling binding for computer-aided drug discovery—is surprisingly difficult. While quantum chemical approaches to computing aqueous tautomer ratios using continuum solvent models and rigid-rotor harmonic-oscillator thermochemistry are currently state of the art, these methods are still surprisingly inaccurate despite their enormous computational expense. Here, we show that a major source of this inaccuracy lies in the breakdown of the standard approach to accounting for quantum chemical thermochemistry using rigid rotor harmonic oscillator (RRHO) approximations, which are frustrated by the complex conformational landscape introduced by the migration of double bonds, creation of stereocenters, and introduction of multiple conformations separated by low energetic barriers induced by migration of a single proton. Using quantum machine learning (QML) methods that allow us to compute potential energies with quantum chemical accuracy at a fraction of the cost, we show how rigorous relative alchemical free energy calculations can be used to compute tautomer ratios in vacuum free from the limitations introduced by RRHO approximations. Furthermore, since the parameters of QML methods are tunable, we show how we can train these models to correct limitations in the underlying learned quantum chemical potential energy surface using free energies, enabling these methods to learn to generalize tautomer free energies across a broader range of predictions. We show how alchemical free energies can be calculated with QML potentials to identify deficiencies in RRHO approximations for computing tautomeric free energies, and how these potentials can be learned from experiment to improve prediction accuracy.![]()
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Affiliation(s)
- Marcus Wieder
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center New York NY 10065 USA
| | - Josh Fass
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center New York NY 10065 USA .,Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Graduate School of Medical Sciences New York NY 10065 USA
| | - John D Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center New York NY 10065 USA
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8
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Vazquez-Salazar LI, Boittier ED, Unke OT, Meuwly M. Impact of the Characteristics of Quantum Chemical Databases on Machine Learning Prediction of Tautomerization Energies. J Chem Theory Comput 2021; 17:4769-4785. [PMID: 34288675 DOI: 10.1021/acs.jctc.1c00363] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
An essential aspect for adequate predictions of chemical properties by machine learning models is the database used for training them. However, studies that analyze how the content and structure of the databases used for training impact the prediction quality are scarce. In this work, we analyze and quantify the relationships learned by a machine learning model (Neural Network) trained on five different reference databases (QM9, PC9, ANI-1E, ANI-1, and ANI-1x) to predict tautomerization energies from molecules in Tautobase. For this, characteristics such as the number of heavy atoms in a molecule, number of atoms of a given element, bond composition, or initial geometry on the quality of the predictions are considered. The results indicate that training on a chemically diverse database is crucial for obtaining good results and also that conformational sampling can partly compensate for limited coverage of chemical diversity. The overall best-performing reference database (ANI-1x) performs on average by 1 kcal/mol better than PC9, which, however, contains about 2 orders of magnitude fewer reference structures. On the other hand, PC9 is chemically more diverse by a factor of ∼5 as quantified by the number of atom-in-molecule-based fragments (amons) it contains compared with the ANI family of databases. A quantitative measure for deficiencies is the Kullback-Leibler divergence between reference and target distributions. It is explicitly demonstrated that when certain types of bonds need to be covered in the target database (Tautobase) but are undersampled in the reference databases, the resulting predictions are poor. Examples of this include the poor performance of all databases analyzed to predict C(sp2)-C(sp2) double bonds close to heteroatoms and azoles containing N-N and N-O bonds. Analysis of the results with a Tree MAP algorithm provides deeper understanding of specific deficiencies in predicting tautomerization energies by the reference datasets due to inadequate coverage of chemical space. Capitalizing on this information can be used to either improve existing databases or generate new databases of sufficient diversity for a range of machine learning (ML) applications in chemistry.
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Affiliation(s)
| | - Eric D Boittier
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland
| | - Oliver T Unke
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany.,DFG Cluster of Excellence "Unifying Systems in Catalysis" (UniSysCat), Technische Universität Berlin, 10623 Berlin, Germany
| | - Markus Meuwly
- Department of Chemistry, University of Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland.,Department of Chemistry, Brown University, Providence, Rhode Island 02912, United States
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9
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Brovarets' OO, Muradova A, Hovorun DM. Novel mechanisms of the conformational transformations of the biologically important G·C nucleobase pairs in Watson–Crick, Hoogsteen and wobble configurations via the mutual rotations of the bases around the intermolecular H-bonds: a QM/QTAIM study. RSC Adv 2021; 11:25700-25730. [PMID: 35478902 PMCID: PMC9036977 DOI: 10.1039/d0ra08702e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 06/09/2021] [Indexed: 01/12/2023] Open
Abstract
It was established conformational transformations of the G·C nucleobase pairs, occurring via the mutual rotation of the G and C bases around the intermolecular H-bonds.
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Affiliation(s)
- Ol'ha O. Brovarets'
- Department of Molecular and Quantum Biophysics
- Institute of Molecular Biology and Genetics
- National Academy of Sciences of Ukraine
- Kyiv
- Ukraine
| | - Alona Muradova
- Department of Molecular Biotechnology and Bioinformatics
- Institute of High Technologies
- Taras Shevchenko National University of Kyiv
- Kyiv
- Ukraine
| | - Dmytro M. Hovorun
- Department of Molecular and Quantum Biophysics
- Institute of Molecular Biology and Genetics
- National Academy of Sciences of Ukraine
- Kyiv
- Ukraine
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10
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Flores-Reyes JC, Islas-Jácome A, González-Zamora E. The Ugi three-component reaction and its variants. Org Chem Front 2021. [DOI: 10.1039/d1qo00313e] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
A broad variety of α-aminoamide-based compounds have been synthesized via the three-component version of the Ugi reaction (U-3CR) or by any of its variants (Ugi-Zhu-3CR, Orru-3CR, Ugi-4C-3CR, Ugi-Joullié-3CR, GBB-3CR, Ugi-Reissert-3CR, and so on).
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Affiliation(s)
- Julio César Flores-Reyes
- Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, C.P. 09340, Ciudad de Mexico
| | - Alejandro Islas-Jácome
- Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, C.P. 09340, Ciudad de Mexico
| | - Eduardo González-Zamora
- Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, C.P. 09340, Ciudad de Mexico
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11
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Baker CM, Kidley NJ, Papachristos K, Hotson M, Carson R, Gravestock D, Pouliot M, Harrison J, Dowling A. Tautomer Standardization in Chemical Databases: Deriving Business Rules from Quantum Chemistry. J Chem Inf Model 2020; 60:3781-3791. [PMID: 32644790 DOI: 10.1021/acs.jcim.0c00232] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Databases of small, potentially bioactive molecules are ubiquitous across the industry and academia. Designed such that each unique compound should appear only once, the multiplicity of ways in which many compounds can be represented means that these databases require methods for standardizing the representation of chemistry. This is commonly achieved through the use of "Chemistry Business Rules", sets of predefined rules that describe the "house style" of the database in question. At Syngenta, the historical approach to the design of chemistry business rules has been to focus on consistency of representation, with chemical relevance given secondary consideration. In this work, we overturn that convention. Through the use of quantum chemistry calculations, we define a set of chemistry business rules for tautomer standardization that reproduces gas-phase energetic preferences. We go on to show that, compared to our historic approach, this method yields tautomers that are in better agreement with those observed experimentally in condensed phases and that are better suited for use in predictive models.
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Affiliation(s)
- Christopher M Baker
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
| | - Nathan J Kidley
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
| | | | - Matthew Hotson
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
| | - Rob Carson
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
| | - David Gravestock
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
| | - Martin Pouliot
- Syngenta Crop Protection, Schaffhauserstrasse, Stein CH-4332, Switzerland
| | - Jim Harrison
- Datacraft Technologies, 110 Parkwood Place, Anstead, QLD 4070, Australia
| | - Alan Dowling
- Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, U.K
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Levine DS, Watson MA, Jacobson LD, Dickerson CE, Yu HS, Bochevarov AD. Pattern-free generation and quantum mechanical scoring of ring-chain tautomers. J Comput Aided Mol Des 2020; 35:417-431. [PMID: 32830300 DOI: 10.1007/s10822-020-00334-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 07/21/2020] [Indexed: 11/24/2022]
Abstract
In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless, for some types of organic compounds, including sugars, warfarin analogs, fluorescein dyes and some drug-like compounds, ring-chain tautomerism cannot be ignored. In this work, a novel ring-chain tautomer generation algorithm is presented. It differs from previously proposed solutions in that it does not rely on hard-coded patterns of proton migrations and bond rearrangements, and should therefore be more general and maintainable. We deploy this algorithm as part of a workflow which provides an automated solution for tautomer generation and scoring. The workflow identifies protonatable and deprotonatable sites in the molecule using a previously described approach based on rapid micro-pKa prediction. These data are used to distribute the active protons among the protonatable sites exhaustively, at which point alternate resonance structures are considered to obtain pairs of atoms with opposite formal charge. These pairs are connected with a single bond and a 3D undistorted geometry is generated. The scoring of the generated tautomers is performed with a subsequent density functional theory calculation employing an implicit solvent model. We demonstrate the performance of our workflow on several types of organic molecules known to exist in ring-chain tautomeric equilibria in solution. In particular, we show that some ring-chain tautomers not found using previously published algorithms are successfully located by ours.
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Affiliation(s)
- Daniel S Levine
- Schrödinger, Inc., 120 West 45th St, New York, NY, 10036, USA
| | - Mark A Watson
- Schrödinger, Inc., 120 West 45th St, New York, NY, 10036, USA
| | - Leif D Jacobson
- Schrödinger, Inc., 120 West 45th St, New York, NY, 10036, USA.,Schrödinger, Inc., Suite 1300, 101 SW Main Street, Portland, OR, 97204, USA
| | - Claire E Dickerson
- Schrödinger, Inc., 120 West 45th St, New York, NY, 10036, USA.,College of Chemistry & Biochemistry, University of California, Los Angeles, CA, 90095, USA
| | - Haoyu S Yu
- Schrödinger, Inc., 120 West 45th St, New York, NY, 10036, USA
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Desens W, Jiao H, Langer P, Michalik D. NMR Spectroscopic and Theoretical Studies on Tautomerism and Isomerism of Perfluoroalkyl‐Substituted 1,5‐Benzodiazepines. ChemistrySelect 2020. [DOI: 10.1002/slct.201904639] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Willi Desens
- Institut für ChemieUniversität Rostock Albert-Einstein-Str. 3a Rostock 18059 Germany
| | - Haijun Jiao
- Leibniz-Institut für Katalyse (LIKAT) Albert-Einstein-Str. 29a Rostock 18059 Germany
| | - Peter Langer
- Institut für ChemieUniversität Rostock Albert-Einstein-Str. 3a Rostock 18059 Germany
- Leibniz-Institut für Katalyse (LIKAT) Albert-Einstein-Str. 29a Rostock 18059 Germany
| | - Dirk Michalik
- Institut für ChemieUniversität Rostock Albert-Einstein-Str. 3a Rostock 18059 Germany
- Leibniz-Institut für Katalyse (LIKAT) Albert-Einstein-Str. 29a Rostock 18059 Germany
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Dhaked DK, Ihlenfeldt WD, Patel H, Delannée V, Nicklaus MC. Toward a Comprehensive Treatment of Tautomerism in Chemoinformatics Including in InChI V2. J Chem Inf Model 2020; 60:1253-1275. [PMID: 32043883 DOI: 10.1021/acs.jcim.9b01080] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
We have collected 86 different transforms of tautomeric interconversions. Out of those, 54 are for prototropic (non-ring-chain) tautomerism, 21 for ring-chain tautomerism, and 11 for valence tautomerism. The majority of these rules have been extracted from experimental literature. Twenty rules, covering the most well-known types of tautomerism such as keto-enol tautomerism, were taken from the default handling of tautomerism by the chemoinformatics toolkit CACTVS. The rules were analyzed against nine differerent databases totaling over 400 million (non-unique) structures as to their occurrence rates, mutual overlap in coverage, and recapitulation of the rules' enumerated tautomer sets by InChI V.1.05, both in InChI's Standard and a Nonstandard version with the increased tautomer-handling options 15T and KET turned on. These results and the background of this study are discussed in the context of the IUPAC InChI Project tasked with the redesign of handling of tautomerism for an InChI version 2. Applying the rules presented in this paper would approximately triple the number of compounds in typical small-molecule databases that would be affected by tautomeric interconversion by InChI V2. A web tool has been created to test these rules at https://cactus.nci.nih.gov/tautomerizer.
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Affiliation(s)
- Devendra K Dhaked
- Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, NIH, Frederick, Maryland 21702, United States
| | | | - Hitesh Patel
- Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, NIH, Frederick, Maryland 21702, United States
| | - Victorien Delannée
- Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, NIH, Frederick, Maryland 21702, United States
| | - Marc C Nicklaus
- Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, NIH, Frederick, Maryland 21702, United States
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