Session RED
Analysis of Large Chemical Data Sets
P01 | HASTENing structure-based virtual screening of large chemical libraries Tuomo Sakari Kalliokoski ![]() | ||
P03 | DEL design at Ryvu Marcin A. Król, Ryvu Therapeutics | ||
P05 | 40 million PubChem structures from patents: both treasure trove and junk yard Christopher Southan ![]() |
Artificial Intelligence Approaches
Cheminformatics Approaches
Dealing with Biological Complexity
Structure-Activity and Structure-Property Prediction
P31 | Testing the limits of prediction in QSPR models considering their applicability domain Modest von Korff, Idorsia Pharmaceuticals Ltd | ||
P33 | Predictive-based selection of drug candidates for Autosomal Dominant Polycystic Kidney Disease (ADPKD) David Figueiredo Vidal ![]() | ||
P35 | Virtual Distillation of Naphthas Using Molecular Property Prediction Algorithms Maarten R. Dobbelaere, Ghent University | ||
P37 | Use of semi-quantitative (censored) data for QSAR modeling of hERG inhibitory potency Andrius Sazonovas, VsI Aukstieji Algoritmai PDF | ||
P39 | DFT and ML modeling of peptide properties for cytotoxicity prediction Anzhelika Markovnikova, ITMO University |
Structure-Based Approaches
P41 | Conservation Analysis of anti-TB Target DnaE1 and Identification of Potential Interactions of DnaE1 Inhibitor Nargenicin on the Human Proteome Rosan Kuin, Leiden University | ||
P43 | Tracing the difference: Comparative modeling of human Uridine 5’-diphosphoglucuronosyltransferase guided by molecular dynamics simulations Sijie Liu, Freie Universität Berlin | ||
P45 | Structural Investigations of Protein Kinases with GeoMine Christiane Ehrt ![]() | ||
P47 | Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses Andreas Luttens, Uppsala University | ||
P49 | GenCReM: de novo generation of synthetically feasible compounds based on genetic algorithm Aleksandra Ivanová ![]() | ||
P51 | MD pharmacophore-based search for novel MARK4 inhibitors Alina Kutlushina, Palacky University |
Session BLUE
Analysis of Large Chemical Data Sets
Artificial Intelligence Approaches
P06 | The DECIMER (Deep lEarning for Chemical ImagE Recognition) project Kohulan Rajan ![]() ![]() | ||
P08 | New approaches for antimicrobial peptides prediction using Machine-Learning Colin Titouan Bournez, Leiden University | ||
P10 | Application of DeepSMILES to machine-learning of chemical structures Noel Michael O’Boyle ![]() | ||
P12 | Towards Predicting Enzyme Activity by Traversing Biomedical Knowledge Graphs Terence Egbelo, University of Sheffield PDF | ||
P14 | TERP: a machine learning approach for predicting and prioritizing specialized metabolite tailoring enzyme products David Meijer ![]() | ||
P16 | Enzeptional: enzyme optimization via a generative language modeling-based evolutionary algorithm Yves Gaetan Nana Teukam ![]() |