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