Session RED

Analysis of Large Chemical Data Sets

P01HASTENing structure-based virtual screening of large chemical libraries
Tuomo Sakari Kalliokoski , Orion Pharma PDF
P03DEL design at Ryvu
Marcin A. Król, Ryvu Therapeutics
P0540 million PubChem structures from patents: both treasure trove and junk yard
Christopher Southan , Medicines Discovery Catapult PDF

Artificial Intelligence Approaches

P07Artificial Intelligence for Compound Design and Automation of DMTA Cycles
Susanne Sauer, Sanofi-Aventis Deutschland GmbH
P09Multi-target uncertainty quantification for de novo drug design
Sohvi Iiri Maria Luukkonen , Leiden University
P11Planning of chemical synthesis of focused libraries of similars to a given compound
Adeliia Fatykhova, Kazan Federal University
P13MoleculeACE: a benchmark for machine learning with activity cliffs
Derek van Tilborg , Eindhoven University of Technology
P15The chemistry puppeteer: enhancing the diversity of single-step retrosynthesis
Alessandra Toniato , IBM Research Europe

Cheminformatics Approaches

P17GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics (updates and perspective)
Martin Šícho , Leiden University
P19Applying machine learning for virtual drug discovery and development of adenosine A2A ligands combining in silico medicinal chemistry and quantitative systems pharmacology
Helle Willemijn Van Den Maagdenberg, Leiden University
P21Combining shape and electrostatics in a spectral geometry-based 3D molecular descriptor
James Alexander Middleton, University of Sheffield
P23Using Matched Molecular Pairs for CoreDesign®
Jess Stacey, MedChemica Ltd
P25The Future of InChI
Gerd Blanke , StructurePendium Technologies GmbH

Dealing with Biological Complexity

P27PKD-KG: A drug repurposing knowledge graph for Autosomal Dominant Polycystic Kidney Disease (ADPKD)
Bola Khalil , Janssen Pharmaceutica / Leiden University
P29Molecular dynamics-based elucidation of Flap endonuclease 1 flexibility for DNA cleavage
Zied Hosni, University of Sheffield

Structure-Activity and Structure-Property Prediction

P31Testing the limits of prediction in QSPR models considering their applicability domain
Modest von Korff, Idorsia Pharmaceuticals Ltd
P33Predictive-based selection of drug candidates for Autosomal Dominant Polycystic Kidney Disease (ADPKD)
David Figueiredo Vidal , Leiden University
P35Virtual Distillation of Naphthas Using Molecular Property Prediction Algorithms
Maarten R. Dobbelaere, Ghent University
P37Use of semi-quantitative (censored) data for QSAR modeling of hERG inhibitory potency
Andrius Sazonovas, VsI Aukstieji Algoritmai PDF
P39DFT and ML modeling of peptide properties for cytotoxicity prediction
Anzhelika Markovnikova, ITMO University

Structure-Based Approaches

P41Conservation Analysis of anti-TB Target DnaE1 and Identification of Potential Interactions of DnaE1 Inhibitor Nargenicin on the Human Proteome
Rosan Kuin, Leiden University
P43Tracing the difference: Comparative modeling of human Uridine 5’-diphosphoglucuronosyltransferase guided by molecular dynamics simulations
Sijie Liu, Freie Universität Berlin
P45Structural Investigations of Protein Kinases with GeoMine
Christiane Ehrt , Universität Hamburg
P47Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses
Andreas Luttens, Uppsala University
P49GenCReM: de novo generation of synthetically feasible compounds based on genetic algorithm
Aleksandra Ivanová , Institute of Molecular and Translational Medicine
P51MD pharmacophore-based search for novel MARK4 inhibitors
Alina Kutlushina, Palacky University

Session BLUE

Analysis of Large Chemical Data Sets

P02Ring systems in natural products: structural diversity, physicochemical properties, and
coverage by synthetic compounds
Ya Chen , University of Vienna
P04Utilizing the semantic web and network tools to integrate pharmacokinetic, -dynamic, and
OMICS data with metabolic (disease) pathways
Denise Slenter , Maastricht University

Artificial Intelligence Approaches

P06The DECIMER (Deep lEarning for Chemical ImagE Recognition) project
Kohulan Rajan , Friedrich Schiller University, code
P08New approaches for antimicrobial peptides prediction using Machine-Learning
Colin Titouan Bournez, Leiden University
P10Application of DeepSMILES to machine-learning of chemical structures
Noel Michael O’Boyle , Sosei Heptares
P12Towards Predicting Enzyme Activity by Traversing Biomedical Knowledge Graphs
Terence Egbelo, University of Sheffield PDF
P14TERP: a machine learning approach for predicting and prioritizing specialized metabolite tailoring enzyme products
David Meijer , Wageningen University
P16Enzeptional: enzyme optimization via a generative language modeling-based evolutionary algorithm
Yves Gaetan Nana Teukam , IBM Research Europe

Cheminformatics Approaches

P18Algorithmic Advances in Diverse Fingerprint Selection
Andrew Dalke, Andrew Dalke Scientific
P20Human Pharmacokinetic Prediction using Predicted Animal Pharmacokinetic Parameters and Computed Physicochemical Properties
Srijit Seal , University of Cambridge
P22Prediction of new active ligands for the Vitamin D Receptor
Maria Isabel Agea Lorente, University of Chemistry and Technology Prague
P24Reaction InChI: Present and Future
Gerd Blanke , StructurePendium Technologies GmbH
P26PIKAChU: a Python-based Informatics Kit for Analysing CHemical Units
Barbara R. Terlouw , Wageningen University

Dealing with Biological Complexity

P28Building classifiers to link hepatic transcriptomic profile in humans with varying degree of hepatic fibrosis
Manuel Alejandro Gonzalez Hernandez , Leiden University
P30An automated workflow to expand AOP-Wiki Stressor chemical knowledge and identify potential activators of Adverse Outcome Pathways
Marvin Martens , Maastricht University

Structure-Activity and Structure-Property Prediction

P32Exploring aspartic protease inhibitor binding to design selective antimalarials
Raitis Latvian Bobrovs , Institute of Organic Synthesis
P34Proteochemometric modeling identifies chemically diverse norepinephrine transporter inhibitors
Brandon J. Bongers , Leiden University
P36Multi-Instance Learning Approach to Predictive Modeling of Catalyst Enantioselectivity
Dmitry Zankov, Kazan Federal University
P38VHP4Safety: building a virtual human for safety assessment
Linde Schoenmaker, Universiteit Leiden

Structure-Based Approaches

P40In silico identification of dual targeting potential BACE1 and GSK-3β inhibitors for Alzheimer’s disease
Nilesh Gajanan Bajad, Indian Institute of Technology, BHU, Varanasi
P42Atomistic insight into substrate activity of SARS-CoV-2 papain-like protease and human casein kinase 1
Laura Tesmer , Abbvie
P44Extracting 3D pharmacophores from molecular dynamics simulations: a case study
Szymon Pach , Freie Universität Berlin
P46The application of the MM/GBSA method in the binding pose prediction of FGFR inhibitors
Yu Chen , Freie Universität Berlin
P48Automated design of synthetically accessible compounds
Pavlo Polishchuk , Palacky University
P50Structure-based generation of synthetically feasible molecules
Guzel Minibaeva , Palacký University Olomouc
P52Automated determination of optimal λ schedules for free energy calculations
Hannes Loeffler, Cresset