Important recent papers in computational and theoretical chemistry
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An evolutionary algorithm for interpretable molecular representations

Philipp M. Pflüger, Marius Kühnemund, Felix Katzenburg, Herbert Kuchen, and Frank Glorius (2024) Highlighted by Jan Jensen Parts of Figures 2 and 6 combined. (c) 2024 Elsevier, Inc This paper presents a very novel approach to XAI that allows for direct comparison with chemical intuition. Molecular fingerprints (either binary or count) are defined using...

Sun Mar 31, 2024 14:26
AiZynth Impact on Medicinal Chemistry Practice at AstraZeneca

Jason D. Shields, Rachel Howells, Gillian Lamont, Yin Leilei, Andrew Madin, Christopher E. Reimann, Hadi Rezaei, Tristan Reuillon, Bryony Smith, Clare Thomson, Yuting Zhengc and Robert E. Ziegler (2024) Highlighted by Jan Jensen Figure 3 from this paper (c) the authors 2020. Reproduced under the CC-BY licenseThis is one of the rare papers where experimental...

Wed Feb 28, 2024 14:36
TS-Tools: Rapid and Automated Localization of Transition States Based on a Textual Reaction SMILES Input

Thijs Stuyver (2024) Highlighted by Jan Jensen Figure 2 from the paper. (c) the author 2024 reproduced under the CC-BY-NC-ND licence This paper caught my eye for several reasons. It's an open source implementation of Maeda's AFIR method, but modified for double-ended TS searches. The setup is completely automated and interfaced to  xTB so it is fast....

Wed Jan 31, 2024 14:09
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model

Chenru Duan, Yuanqi Du, Haojun Jia, and Heather J. Kulik (2023) Highlighted by Jan Jensen Part of Figure 1 from the paper. As anyone who has tried it will know, finding TSs is one of the most difficult, fiddly, and frustrating tasks in computational chemistry. While there are several methods aimed at automating the process, they tend to have a mixed...

Sat Dec 30, 2023 13:53
Growing strings in a chemical reaction space for searching retrosynthesis pathways

Federico Zipoli, Carlo Baldassari, Matteo Manica, Jannis Born, and Teodoro Laino (2023) Highlighted by Jan Jensen Part of Figure 10 from the paper. (c) The authors 2023. Reproduced under the CC-NC-ND Prediction of retrosynthetic reaction trees are typically done by stringing together individual retrosynthetic steps that have the highest predicted confidences....

Thu Nov 30, 2023 13:15
Few-Shot Learning for Low-Data Drug Discovery

Daniel Vella and Jean-Paul Ebejer (2023) Highlighted by Jan JensenTOC graphic from the articleThis paper is an update and expansion to this seminal paper by Pande and co-workers (you should definitely read both). It compares the ability to distinguish active and inactive compounds for few-shots methods to more conventional approaches for very small...

Tue Oct 31, 2023 16:42

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