Data-Driven Drug Discovery and Molecular Informatics

Publications

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  • Currently displaying 21 - 40 of 580 publications
Author(s)
Publication title
Journal Name
Publication year
A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.
S Seal, M-A Trapotsi, O Spjuth, S Singh, J Carreras-Puigvert, N Greene, A Bender, AE Carpenter
ArXiv
(2024)
A Decade in a Systematic Review: The Evolution and Impact of Cell Painting
S Seal, M-A Trapotsi, O Spjuth, S Singh, J Carreras-Puigvert, N Greene, A Bender, AE Carpenter
(2024)
(doi: 10.48550/arxiv.2405.02767)
PromptSMILES: Prompting for scaffold decoration and fragment linking in chemical language models
M Thomas, M Ahmad, G Tresadern, G de Fabritiis
(2024)
(doi: 10.26434/chemrxiv-2024-z5jnt)
MolScore: A scoring and evaluation framework for de novo drug design
M Thomas, NM O'Boyle, A Bender, C de Graaf
(2024)
(doi: 10.26434/chemrxiv-2023-c4867)
PKSmart: An Open-Source Computational Model to Predict in vivo Pharmacokinetics of Small Molecules
S Seal, M-A Trapotsi, V Subramanian, O Spjuth, N Greene, A Bender
(2024)
(doi: 10.1101/2024.02.02.578658)
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank
S Seal, O Spjuth, L Hosseini-Gerami, M García-Ortegón, S Singh, A Bender, AE Carpenter
Journal of chemical information and modeling
(2024)
64
(doi: 10.1021/acs.jcim.3c01834)
Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity.
RI Horne, J Wilson-Godber, A González Díaz, ZF Brotzakis, S Seal, RC Gregory, A Possenti, S Chia, M Vendruscolo
Journal of Chemical Information and Modeling
(2024)
64
(doi: 10.1021/acs.jcim.3c01777)
From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability
S Seal, J Carreras-Puigvert, S Singh, AE Carpenter, O Spjuth, A Bender
Molecular Biology of the Cell
(2024)
35
(doi: 10.1091/mbc.E23-08-0298)
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations.
B Baillif, J Cole, I Giangreco, P McCabe, A Bender
J Cheminform
(2023)
15
(doi: 10.1186/s13321-023-00794-w)
Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules
E Gelžinytė, M Öeren, MD Segall, G Csányi
Journal of chemical theory and computation
(2023)
20
(doi: 10.1021/acs.jctc.3c00710)
Transferable Machine Learning Interatomic Potential for Bond Dissociation Energy Prediction of Drug-like Molecules
E Gelžinytė, M Öeren, MD Segall, G Csányi
(2023)
(doi: 10.26434/chemrxiv-2023-l85nf-v2)
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data
K Handa, MC Thomas, M Kageyama, T Iijima, A Bender
J Cheminform
(2023)
15
(doi: 10.1186/s13321-023-00781-1)
ACEpotentials.jl: A Julia implementation of the atomic cluster expansion
WC Witt, C van der Oord, E Gelžinytė, T Järvinen, A Ross, JP Darby, CH Ho, WJ Baldwin, M Sachs, J Kermode, N Bernstein, G Csányi, C Ortner
The Journal of Chemical Physics
(2023)
159
(doi: 10.1063/5.0158783)
Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA DICTrank.
S Seal, O Spjuth, L Hosseini-Gerami, M García-Ortegón, S Singh, A Bender, AE Carpenter
(2023)
(doi: 10.1101/2023.10.15.562398)
Machine Learning Interatomic Potentials to Predict Bond Dissociation Energies
E Gelzinyte
(2023)
(doi: 10.17863/CAM.104854)
MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny.
L Hosseini-Gerami, R Hernansaiz Ballesteros, A Liu, H Broughton, DA Collier, A Bender
BMC Bioinformatics
(2023)
24
(doi: 10.1186/s12859-023-05416-8)
ACEpotentials.jl: A Julia Implementation of the Atomic Cluster Expansion
WC Witt, CVD Oord, E Gelžinytė, T Järvinen, A Ross, JP Darby, CH Ho, WJ Baldwin, M Sachs, J Kermode, N Bernstein, G Csányi, C Ortner
(2023)
(doi: 10.48550/arxiv.2309.03161)
Editorial overview: Artificial intelligence (AI) methodology in structural biology
A Bender, C de Graaf, NM O'Boyle
Current Opinion in Structural Biology
(2023)
82
(doi: 10.1016/j.sbi.2023.102676)
wfl Python toolkit for creating machine learning interatomic potentials and related atomistic simulation workflows.
E Gelžinytė, S Wengert, TK Stenczel, HH Heenen, K Reuter, G Csányi, N Bernstein
The Journal of Chemical Physics
(2023)
159
(doi: 10.1063/5.0156845)
Improving de novo molecule generation for structure-based drug design
M Thomas
(2023)
(doi: 10.17863/CAM.107998)
Yusuf Hamied Department of Chemistry
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