Royal Society of Chemistry will make all its journals open access | News | Chemistry World
https://www.chemistryworld.com/news/royal-society-of-chemistry-will-make-all-its-journals-open-access/4016468.article
https://www.chemistryworld.com/news/royal-society-of-chemistry-will-make-all-its-journals-open-access/4016468.article
Chemistry World
Royal Society of Chemistry will make all its journals open access
All RSC journals will be free to read within five years
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#internationalworkshop #genomics
International Virtual Workshop ennoscriptd on Computational Genomics for NGS data analysis: Concepts, Methods & Applications
Jointly organised by
- Delhi School of public Health, Institute of Eminence
- DBC I4 Center Deshbandhu College
- Hansraj College, North Campus
- Dr.M.G.R Educational & Research Institute University, India
- NyBerMan Bioinformatics Europe, Orleans, France
- Quanta Calculus Pvt Ltd, India
🗓 26-30th November 2022
👨💻Register now:
https://bit.ly/3WeHk0S
📚Check for more details in the flyer
https://drive.google.com/file/d/1rLL-xFH2zuEwrRGs6GuFeCnVIdnOb3jy/view?usp=share_link
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Channel @llbschool
Forum @letslearnbioinformatics
International Virtual Workshop ennoscriptd on Computational Genomics for NGS data analysis: Concepts, Methods & Applications
Jointly organised by
- Delhi School of public Health, Institute of Eminence
- DBC I4 Center Deshbandhu College
- Hansraj College, North Campus
- Dr.M.G.R Educational & Research Institute University, India
- NyBerMan Bioinformatics Europe, Orleans, France
- Quanta Calculus Pvt Ltd, India
🗓 26-30th November 2022
👨💻Register now:
https://bit.ly/3WeHk0S
📚Check for more details in the flyer
https://drive.google.com/file/d/1rLL-xFH2zuEwrRGs6GuFeCnVIdnOb3jy/view?usp=share_link
📢«««««««
Channel @llbschool
Forum @letslearnbioinformatics
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NIST Breakthrough: Simple Material Could Scrub Carbon Dioxide From Power Plant Smokestacks
https://scitechdaily.com/nist-breakthrough-simple-material-could-scrub-carbon-dioxide-from-power-plant-smokestacks/
https://scitechdaily.com/nist-breakthrough-simple-material-could-scrub-carbon-dioxide-from-power-plant-smokestacks/
SciTechDaily
NIST Breakthrough: Simple Material Could Scrub Carbon Dioxide From Power Plant Smokestacks
Easily synthesized chemical filter could stop the greenhouse gas from reaching the atmosphere. How can carbon dioxide, a greenhouse gas, be removed from the exhaust of fossil fuel power plants before it ever enters the atmosphere? New research findings suggest…
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Single-molecule magnetic memory is the first to work at room temperature | Research | Chemistry World
https://www.chemistryworld.com/news/single-molecule-magnetic-memory-is-the-first-to-work-at-room-temperature/4016482.article
https://www.chemistryworld.com/news/single-molecule-magnetic-memory-is-the-first-to-work-at-room-temperature/4016482.article
Chemistry World
Single-molecule magnetic memory is the first to work at room temperature
Anionic iron complex breaks the rules of magnetic molecules and opens up opportunities to miniaturise data storage
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Controversy surrounds corrected chemical structures | Research | Chemistry World
https://www.chemistryworld.com/research/controversy-surrounds-corrected-chemical-structures/4016494.article
https://www.chemistryworld.com/research/controversy-surrounds-corrected-chemical-structures/4016494.article
Chemistry World
Controversy surrounds corrected chemical structures
Researchers used machine learning-powered NMR prediction to correct improbable structures - but some of their revisions have been challenged
Calculation of Mass Spectra with the QCxMS Method for Negatively and Multiply Charged Molecules
Analysis and validation of a mass spectrometry (MS) experiment are usually performed by comparison to reference spectra. However, if references are missing, measured spectra cannot be properly matched. To close this gap, the Quantum Chemical Mass Spectrometry (QCxMS) program has been developed. It enables fully automatic calculations of electron ionization (EI) and positive ion collision-induced dissociation (CID) mass spectra of singly charged molecular ions. In this work, the extension to negative and multiple ion charge for the CID run mode is presented. QCxMS is now capable of calculating structures carrying any charge, without the need for pretabulated fragmentation pathways or machine learning of database spectra. Mass spectra of four single negatively charged and two multiple positively charged organic ions with molecular sizes from 12 to 92 atoms were computed and compared to reference spectra. The underlying Born–Oppenheimer molecular dynamics (MD) calculations were conducted using the semiempirical quantum mechanical GFN2-xTB method, while for some small molecules, ab initio DFT-based MD simulations were performed. Detailed insights into the fragmentation pathways were gained, and the effects of the computed charge assignments on the resulting spectrum are discussed. Especially for the negative ion mode, the influence of the deprotonation site to create the anion was found to be substantial. Doubly charged fragments could successfully be calculated fully automatically for the first time, while higher charged structures introduced severe assignment problems. Overall, this extension of the QCxMS program further enhances its applicability and underlines its value as a sophisticated toolkit for CID-based tandem MS structure elucidation.
https://pubs.acs.org/doi/10.1021/jasms.2c00209
Analysis and validation of a mass spectrometry (MS) experiment are usually performed by comparison to reference spectra. However, if references are missing, measured spectra cannot be properly matched. To close this gap, the Quantum Chemical Mass Spectrometry (QCxMS) program has been developed. It enables fully automatic calculations of electron ionization (EI) and positive ion collision-induced dissociation (CID) mass spectra of singly charged molecular ions. In this work, the extension to negative and multiple ion charge for the CID run mode is presented. QCxMS is now capable of calculating structures carrying any charge, without the need for pretabulated fragmentation pathways or machine learning of database spectra. Mass spectra of four single negatively charged and two multiple positively charged organic ions with molecular sizes from 12 to 92 atoms were computed and compared to reference spectra. The underlying Born–Oppenheimer molecular dynamics (MD) calculations were conducted using the semiempirical quantum mechanical GFN2-xTB method, while for some small molecules, ab initio DFT-based MD simulations were performed. Detailed insights into the fragmentation pathways were gained, and the effects of the computed charge assignments on the resulting spectrum are discussed. Especially for the negative ion mode, the influence of the deprotonation site to create the anion was found to be substantial. Doubly charged fragments could successfully be calculated fully automatically for the first time, while higher charged structures introduced severe assignment problems. Overall, this extension of the QCxMS program further enhances its applicability and underlines its value as a sophisticated toolkit for CID-based tandem MS structure elucidation.
https://pubs.acs.org/doi/10.1021/jasms.2c00209
ACS Publications
Calculation of Mass Spectra with the QCxMS Method for Negatively and Multiply Charged Molecules
Analysis and validation of a mass spectrometry (MS) experiment are usually performed by comparison to reference spectra. However, if references are missing, measured spectra cannot be properly matched. To close this gap, the Quantum Chemical Mass Spectrometry…
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Forwarded from Henrique
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We are looking for students interested in a Ph.D. in computational organic chemistry! Come help us gain a better understanding of #bioorthogonal reactions. Interested students should contact me directly: https://www.dsvatunek.com/ .
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DeepChem
DeepChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology.
https://github.com/deepchem/deepchem
DeepChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology.
https://github.com/deepchem/deepchem
GitHub
GitHub - deepchem/deepchem: Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology - deepchem/deepchem
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Join the 3000+ scientists from academia and industry who have taken Schrodinger’s online courses. All courses are completely asynchronous and include access to curated lists of resources/references, web-based versions of Schrodinger software, hands-on case studies, and expert feedback/support. Course participation does not require any hardware or software.
Click here [1] to learn about Schrodinger Online Courses and to register for the upcoming 2023 sessions.
Current courses:
* Introduction to Molecular Modeling in Drug Discovery
* Introduction to Computational Antibody Engineering
* Molecular Modeling for Materials Science Applications: Organic Electronics
* Molecular Modeling for Materials Science Applications: Homogeneous Catalysis and Reactivity
* Molecular Modeling for Materials Science Applications: Surface Chemistry
* Molecular Modeling for Materials Science Applications: Pharmaceutical Formulations
* Molecular Modeling for Materials Science Applications: Polymeric Materials
* Molecular Modeling for Materials Science Applications: Consumer Packaged Goods
* High-Throughput Virtual Screening for Hit Finding and Evaluation
* Free Energy Calculations for Drug Design with FEP+
[1] - https://shorturl.at/dzDOQ
Click here [1] to learn about Schrodinger Online Courses and to register for the upcoming 2023 sessions.
Current courses:
* Introduction to Molecular Modeling in Drug Discovery
* Introduction to Computational Antibody Engineering
* Molecular Modeling for Materials Science Applications: Organic Electronics
* Molecular Modeling for Materials Science Applications: Homogeneous Catalysis and Reactivity
* Molecular Modeling for Materials Science Applications: Surface Chemistry
* Molecular Modeling for Materials Science Applications: Pharmaceutical Formulations
* Molecular Modeling for Materials Science Applications: Polymeric Materials
* Molecular Modeling for Materials Science Applications: Consumer Packaged Goods
* High-Throughput Virtual Screening for Hit Finding and Evaluation
* Free Energy Calculations for Drug Design with FEP+
[1] - https://shorturl.at/dzDOQ
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Chemists propose unifying theory of musk
https://cen.acs.org/biological-chemistry/biochemistry/Chemists-propose-unifying-theory-musk/100/web/2022/11
https://cen.acs.org/biological-chemistry/biochemistry/Chemists-propose-unifying-theory-musk/100/web/2022/11
The world's largest quantum chemistry dataset to empower new materials design and drug discovery
https://phys.org/news/2022-11-world-largest-quantum-chemistry-dataset.html
https://phys.org/news/2022-11-world-largest-quantum-chemistry-dataset.html
phys.org
The world's largest quantum chemistry dataset to empower new materials design and drug discovery
Predicting the properties of an object is a most natural task for machine learning (ML) algorithms, and molecules or crystals are not an exception. Every drug discovery or materials design pipeline depends ...
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8th ORCA User Meeting, 6th and 7th of December 2022
Dear ORCA users, this is a short reminder of the 8th ORCA User Meeting, taking place on the 6th and 7th of December 2022: "ORCA - Environmental effects, from solids to biology" (open Webinar, times are CET!)
# Day 1 - 6.12.2022:
* 14.45 Frank Neese (Welcome)
* 15.00-15.30 Christoph Riplinger /FACCTS (QM/MM and ONIOM in ORCA)
* 15.40 - 16.00 Simon Müller / TUHH (openCOSMO-RS: efficient parameterization from the ground up)
* 16.00 - 16.20 Giovanni Bistoni, Lorenzo / Univ. Perugia (computational modeling of electrocatalytic processes on coordination polymers)
* 16.20 - 16.40 Johannes Gorges / Mulliken Center Bonn (reliable prediction of association (free) energies of supramolecular complexes with heavy main group elements - the HS13L benchmark set)
* 16.40 - 17.00 Dimitrios Manganas / MPI KoFo (theoretical spectroscopy protocols for solids and surfaces)
* 17.30 - 19.00 POSTER SESSION I
# Day 2 - 7.12.2022:
* 14.30 - 15.00 Patrick Kibies / TU Dortmund (the EC-RISM integral equation-based solvation model for ORCA calculations)
* 15.00 - 15.30 Abhishek Sirohiwal / Stockholm Univ. (Multiscale Simulations of Light Harvesting Assemblies)
* 15.40 - 16.00 Martin Brehm / Halle (tba)
* 16.00 - 16.20 Alexander Auer/ MPI KoFo (calculating NMR chemical shifts in solds)
* 16.30 - 18.00 POSTER SESSION II
* 18.15 - 19.00 Frank Neese (concluding remarks - next evolution steps of ORCA)
The meeting will take place as a ZOOM webinar and you don't need to apply or register for participation. We will post the link for the webinar the day before the meeting in the ORCA forum.
Note that we have two poster session in which you have the chance to present and discuss your projects with the community and the developers.
Send us your poster abstract !!
(Send the abstract to: orca-cfp@kofo.mpg.de, deadline November 27th )
Dear ORCA users, this is a short reminder of the 8th ORCA User Meeting, taking place on the 6th and 7th of December 2022: "ORCA - Environmental effects, from solids to biology" (open Webinar, times are CET!)
# Day 1 - 6.12.2022:
* 14.45 Frank Neese (Welcome)
* 15.00-15.30 Christoph Riplinger /FACCTS (QM/MM and ONIOM in ORCA)
* 15.40 - 16.00 Simon Müller / TUHH (openCOSMO-RS: efficient parameterization from the ground up)
* 16.00 - 16.20 Giovanni Bistoni, Lorenzo / Univ. Perugia (computational modeling of electrocatalytic processes on coordination polymers)
* 16.20 - 16.40 Johannes Gorges / Mulliken Center Bonn (reliable prediction of association (free) energies of supramolecular complexes with heavy main group elements - the HS13L benchmark set)
* 16.40 - 17.00 Dimitrios Manganas / MPI KoFo (theoretical spectroscopy protocols for solids and surfaces)
* 17.30 - 19.00 POSTER SESSION I
# Day 2 - 7.12.2022:
* 14.30 - 15.00 Patrick Kibies / TU Dortmund (the EC-RISM integral equation-based solvation model for ORCA calculations)
* 15.00 - 15.30 Abhishek Sirohiwal / Stockholm Univ. (Multiscale Simulations of Light Harvesting Assemblies)
* 15.40 - 16.00 Martin Brehm / Halle (tba)
* 16.00 - 16.20 Alexander Auer/ MPI KoFo (calculating NMR chemical shifts in solds)
* 16.30 - 18.00 POSTER SESSION II
* 18.15 - 19.00 Frank Neese (concluding remarks - next evolution steps of ORCA)
The meeting will take place as a ZOOM webinar and you don't need to apply or register for participation. We will post the link for the webinar the day before the meeting in the ORCA forum.
Note that we have two poster session in which you have the chance to present and discuss your projects with the community and the developers.
Send us your poster abstract !!
(Send the abstract to: orca-cfp@kofo.mpg.de, deadline November 27th )
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A Brief Review of Density Functional Theory and Solvation Model
https://chemrxiv.org/engage/chemrxiv/article-details/6231c8042c5010f92a7d0bd6
https://chemrxiv.org/engage/chemrxiv/article-details/6231c8042c5010f92a7d0bd6
ChemRxiv
A Brief Review of Density Functional Theory and Solvation Model
In recent years, the applications of first-principles density functional theory (DFT) is diversified and expanded in a wide range due to the development of robust algorithms and more powerful computer systems. In general, DFT is used in condensed matter physics…
Discovery reveals 'brain-like computing' at molecular level is possible
https://phys.org/news/2022-11-discovery-reveals-brain-like-molecular.html
https://phys.org/news/2022-11-discovery-reveals-brain-like-molecular.html
phys.org
Discovery reveals 'brain-like computing' at molecular level is possible
A discovery at University of Limerick in Ireland has revealed for the first time that unconventional brain-like computing at the tiniest scale of atoms and molecules is possible.
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