Just spotted a very interesting paper "Fast calculation of hydrogen-bond strengths and free energy of hydration of small molecules" DOI.

Jazzy is a Python library that allows you to calculate a set of atomic/molecular descriptors which include the Gibbs free energy of hydration (kJ/mol), its polar/apolar components, and the hydrogen-bond strength of donor and acceptor atoms using either SMILES or MOL/SDF inputs. Jazzy is easy to use, does not require expensive hardware, and produces accurate estimations within milliseconds to seconds for drug-like molecules. The library also exposes functionalities to depict molecules with atomistic hydrogen-bond strengths in two or three dimensions.

Code is on GitHub https://github.com/AstraZeneca/jazzy

And there is a really useful cookbook with examples. https://jazzy.readthedocs.io/en/latest/cookbook.html.

The UK-QSAR Spring 2023 meeting will held on Thursday 20th April 2023 / 9:00 AM – 17:00 PM at the Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK .

The meeting is organised jointly by EMBL-EBI and Sosei Heptares, and as always is free. The theme this time is “Learning from data” and for the occasion three of the most relevant databases for our fields will be introduced (PubChem, ChEMBL and the Cambridge Structural Database). The afternoon sessions will be focused on protein structure-based techniques (including use of AlphaFold, and ML for virtual screening) and reaction informatics (including applications of Enamine REAL, and machine learning).

Registration is now open. Please register using the following link: https://www.eventsforce.net/embl/93/register

The Sheffield Conference on Cheminformatics is always one of the highlights of the calendar, it will be held at The Edge, University of Sheffield, UK, Monday 19th – Wednesday 21st June, 2023. https://cisrg.shef.ac.uk/shef2023/.

As usual a great lineup of speakers

Confirmed Attendees & Titles of Paper:

• Adele Hardie A World of Probabilities: An sMD/MSM Approach for Rational Design of Allosteric Modulators
• Aras Asaad Persistence homological statistical summaries for ligand-based virtual screening
• Benoit Baillif Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations
• Dan Woodward Coverage Score: A Model Agnostic Method to Efficiently Explore Chemical Space
• David Palmer Simultaneous Entropy, Enthalpy and Free Energy Prediction using a Physics-Informed Neural Network and Multi-task Learning
• Lauren Reid SARkush®: Automated Markush-like structure generation using matched pairs and generic atom scaffolds
• Helle van den Maagdenberg QSPRpred: a Flexible and Open Quantitative Structure-Property Relationship Modelling Tool
• Henriette Willems PI5P4K subtype-selective inhibitors: three binding modes from one privileged motif
• James Webster An in-silico benchmarking platform for generative de novo drug design
• Marc Lehner Partial Charge Prediction and Pattern Extraction from a AttentiveFP Graph Neural Network
• Maria J Falaguera Illuminating the Chemical Space of Untargeted Proteins
• Matteo Ferla Fragmenstein: stitching compounds together
• Maximilian Beckers Prediction of small molecule developability using large-scale in silico ADMET models
• Moritz Walter Integrating heterogeneous assay data for ML-based ADME prediction
• Noel O’Boyle Handling large chemical spaces in Structure-Based Drug Design
• Rajarshi Guha Virtual Screening of Virtual Libraries using a Genetic Algorithm
• Richard Gowers The Open Free Energy Consortium: Alchemistry for everyone
• Richard Sherhod Glolloc: a global-local mixture of experts model and its application to small molecule drug discovery
• Roger Sayle FNGRPRNTS: Processing just the bits you need, and none of the 1s you don’t.
• Roxana-Maria Rujan Resolving code names to structures from the medicinal chemistry literature: not as FAIR as it should be
• Samuel Genheden AiZynthFinder: developments and learnings from three years of industrial application
• Sébastien Guesné Beyond balanced accuracy: balanced Matthews’ correlation coefficient.
• Sohvi Luukkonen DrugEx: deep learning for de novo drug design — a case for A2B selective ligands
• Srijit Seal PKSmart: An Open-Source Computational Model to Predict in vivo Pharmacokinetics of Small Molecules
• Tuomo Kalliokoski Efficient structure-based virtual screening of ultra-large enumerated chemical spaces using macHine leArning booSTEd dockiNg (HASTEN)
• Uschi Dolfus Full modification control over retrosynthetic routes for guided optimization of lead structures

Just came across this project, MZmine is an open-source project delivering a graphical, interactive software for mass-spectrometry data processing.

https://github.com/mzmine

StarDrop 7.4. This latest release contains several new features.

https://optibrium.com/downloads/StarDrop%207.4%20Quick%20Start%20Guide.pdf.

Core Application​:

• Added the ability to colour StarDrop data sets based on property values (“heatmapping”)
• Added the ability to specify the size and position of structure in chart pop-ups
• Added the ability to specify default properties to be displayed in chart pop-ups
• Added the ability to synchronise the display of chart pop-ups and labels
• Added the ability to convert chart pop-ups into labels
• Added the ability to show chart pop-ups whenever compounds are selected

Scripting:

• Added the ability to edit data set entries from a script
• Added the ability to refresh a data set from a script

Query Interface:

• Added the ability to query on pre-defined SMARTS and TEXT values
• Added support for categorical data types

The InChi group are running a short survey to find out more about the use. It would be really helpful if you have 2-3 mins to complete the survey

https://iupac.org/inchi-usage-survey/

The International Chemical Identifier (InChI) is a textual identifier for chemical substances, designed to provide a standard way to encode molecular information and to facilitate the search for such information in databases and on the web. InChIs differ from the widely used registry numbers in three respects: firstly, they are freely usable and non-proprietary; secondly, they can be computed from structural information and do not have to be assigned by some organization; and thirdly, most of the information in an InChI is human readable (with a lot of practice). The InChIKey is a fixed length (27 character) condensed digital representation of the InChI that is not designed to be human-understandable.

More details are on the InChiTrust Website https://www.inchi-trust.org.

More updates to the superb MayaChemTools. A new command line script named PyMOLExtractSelection.py to extract an arbitrary PyMOL selection from a macromolecule and write it out to a file. In addition, the Psi4CalculateEnergy.py and Psi4PerformMinimization.py scripts have been updated to perform these calculations in solution using domain-decomposition-based continuum solvation models. These scripts rely on Psi4 interface to the DDX module to perform the calculations. Two solvation models are supported: COnductor-like Screening MOdel (COSMO) and Polarizable Continuum Model (PCM). A number of enhancements have been made to the PyMOLVisualizeMacromolecules.py script including identification of arbitrary distance contacts between heavy atoms in pocket residues and docked poses, visualization of solvents and inorganics in the pocket around docked poses, and visualization of B factor values for chains.

LFortran is a modern open-source (BSD licensed) interactive Fortran compiler built on top of LLVM. It can execute user’s code interactively to allow exploratory work (much like Python, MATLAB or Julia) as well as compile to binaries with the goal to run user’s code on modern architectures such as multi-core CPUs and GPUs.

LFortran is in development (alpha stage), we have released a Minimum Viable Product (MVP) version at the end of the summer 2021, see the MVP announcement for more information.

Main repository at GitHub: https://github.com/lfortran/lfortran

Try LFortran in your browser using WebAssembly: https://dev.lfortran.org/

LFortran can be used as a Jupyter kernel, allowing Python/Julia-style rapid prototyping and an exploratory workflow (conda install jupyter lfortran). It can also be used from the command-line with an interactive prompt (REPL).

An interesting initiative, OpenBioSim

We work with industrial partners to facilitate integration of open-source software solutions as components of technology platforms. We also provide ongoing software support and maintenance to open-source projects to ensure compatibility with our customer’s technology infrastructure.

Does this sound familiar?

We’ve had companies come along wanting to use one of our research software, but the academic who developed it had moved on, and we couldn’t offer robust technical support. So OpenBioSim allows us to hire staff for the purpose of building on top of existing OSS and providing long-term support.

Ongoing support is the Achilles heel of open source scientific software, it is often written to address a particular scientific problem and not with the idea of use by other (often non-programmers) scientists.

The dates for the 6th RSC-BMCS/RSC-CICAG Artificial Intelligence in Chemistry are now set, be sure to put them in your calendar. The call for oral and poster abstracts will be opening very soon as will registration. This will be a hybrid meeting with both in person and virtual attendance options. #AIChem23.

Spread the word, this is always a fantastic meeting and there are already a number of great speakers in place

Confirmed Speakers:

Andrew White, University of Rochester and VIAL, US
Kathryn Furnival, AstraZeneca, UK
Laksh Aithani, Charm Therapeutics, UK
Michael Bronstein, University of Oxford, UK
Michelle L. Gill, NVIDIA, US
Noor Shaker, Glamorous AI and X-Chem, UK

Conference website is https://www.rscbmcs.org/events/aichem23/.

ChemDoodle 2D v11.13.0 https://ichemlabs.com/news/read?post=cd2d1113released is a feature update wrapping up their latest massive work on stereochemistry. A new advanced CIP descriptor engine is implemented for the most accurate and consistent CIP assignments and the MDL/BIOVIA stereochemical drawing interpretation algorithm is now implemented along side the IUPAC specification. iChemLabs believe ChemDoodle is now the industry leader for handling stereochemistry, especially in 2D drawings. Several improvements are also included.

This update is free for all ChemDoodle subscriptions, Lifetime and Site licenses. Licenses are as little as $18, and they have a free trial available at: https://www.chemdoodle.com/.

Wed 8 Feb at 4pm at https://www.ccdc.cam.ac.uk

pro Fit, a macOS application for curve fitting (linear and nonlinear regression), plotting, and data analysis for macOS. It runs natively on both Apple Silicon and Intel processors, has Python and LaTeX support and lets you prepare high-quality graphs for publication.

pro Fit comes in a free version, which limits the number of concurrently open documents but is still powerful enough for numerous tasks. To remove all limits, upgrade to the full version.

CHARMM is a very highly regarded biomolecular simulation and modelling package. pyCHARMM allows the user to access CHARMM functionality from python.

We anticipate that pyCHARMM will be a robust platform for the development of comprehensive and complex workflows utilizing Python and its extensive functionality as well as an optimal platform for users to learn molecular modeling methods and practices within a Python-friendly environment such as Jupyter Notebooks.

The publication is here https://doi.org/10.26434/chemrxiv-2023-j6wt1

And there is a GitHub repo for a workshop here https://github.com/clbrooksiii/pyCHARMM-Workshop

A really detailed account of how to set up an Apple Silicon MacBook under macOS Ventura 13.1 for computational materials science. https://aronwalsh.github.io/applesilicon/.

There is also useful update on Crystallography on MacOS https://scottlab.ucsc.edu/xtal/wiki/index.php/CrystallographyonOS_X. It is also worth noting https://subversion.xray.aps.anl.gov/trac/pyGSAS.

I've already detailed Setting up ML and AI tools on Apple Silicon https://www.macinchem.org/reviews/AIML/SettingAIML.php.

The latest RSC CICAG newsletter is now available http://www.rsccicag.org/indexhtmfiles/CICAG%20Newsletter%20Winter%202022-23%20FINAL.pdf.

This is a really bumper issue

Contents Chemical Information and Computer Applications Group Chair’s Report
CICAG Planned and Proposed Future Meetings
Social Media Migration – Opening up Mastodon as a Tool for Scholarly Communication
Cheminformatics: A Digital History ‒ Part 2. A Personal Perspective of the Role of the Web During the Period 1993-1996
InChI Technical Developments
Update from the Royal Society of Chemistry Library
The Open Free Energy Project
Meeting Report: SCI-RSC Workshop on Computational Tools for Drug Discovery 2022
A Crystallography Papermill: The CSD Response
Meeting Report: Ultra-Large Chemical Libraries
Open Science in the Royal Society of Chemistry
The Davy Notebooks Project
This JACS Does Not Exist: Generating Chemistry Abstracts with Machine Learning
Meeting Report: RSC-CICAG and RSC-BMCS 5th Artificial Intelligence in Chemistry Conference.
EU-OPENSCREEN ERIC: an Open-access Research Infrastructure for Chemical Biology and Early Drug Discovery
DECIMER ‒ An Open Toolkit for Optical Chemical Structure Recognition and Document Analysis
Cryo-EM for Industrial-Scale Structure-Based Drug Design
Cryo-EM & Drug Discovery
2022 CSD Updates
News from ACS CINF
News from CAS
RSC Databases Update
UKeiG: Winners of the Prestigious Tony Kent Strix Award 2022
AI4SD News
Book Review: Digital Transformation: New Tools and Methods for Mining Technological Intelligence
Cheminformatics and Chemical Information Books
2022 Reflections on Life at the Catalyst Science and Discovery Centre and Museum in Widnes
Other Chemical Information News

Contributions to the CICAG Newsletter are welcome from all sources ‒ please send to the Newsletter Editor Dr Helen Cooke FRSC: email helen.cooke100@gmail.com

When you renew your Royal Society of Chemistry membership you can choose “Chemical Information and Computer Applications Group” (group 86) as one of your groups to be a member of. Use the “Connecting with others” button at https://members.rsc.org/ If you have already submitted your form you can make a request to join a group via email (membership@rsc.org) or telephone (01223 432141)

Gephi 0.10.0 is here! Download it from https://gephi.org, now supports Apple Silicon, It loads much faster and complex operations such as layouts run smoother.

Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results.

Bastian M., Heymann S., Jacomy M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.

At the end of each year I have a look at the website analytics to see which items were the most popular.

Over the year there were over 110,000 visitors spending an average of 1.5 minutes per session. Whilst the US and the UK were the two top countries but as the table below shows, there has been a steady following around the world. As might be expected the majority are Mac users (57%) but there are a substantial number of Windows (25%) and Linux users (4%). The mobile platforms iOS (9%) and Android (5%) make up most of the remainder.

The most popular page was again the Fortran on a Mac page, followed by the M1chip category page. The iBabel page is in third place. Interestingly, the next most popular page was Python coding within Xcode. Perhaps, suggesting that Apple should consider making it a bit more seamless to use Xcode with Python.

The Mobile Science site has seen increased visitor numbers.

The most popular apps viewed were.

Merck PTE
IBM Micromedex Drug Info
Python3IDE
PocketCAS: Mathematics Toolkit
Molecular Constructor
Visual Math 4D

Also popular were

Human Anatomy Atlas 2019
ChemTube3D.
The Periodic Table Project
Periodic Table

The Twitter feed @macinchem has steadily attracted new followers and currently has 1415followers.

The most popular tweets were

Multicentre Cheminformatics Meeting
AI/ML on Apple Silicon
Structure-based searching SQLite databases
Clearing out the greenhouse

There is also now a feed on Mastodon @macinchem@sciencemastodon.com.