18th German Conference on Cheminformatics (GCC 2024)

November 3 - 6, 2024 in Bad Soden am Taunus/Germany

Poster list

P 01
COCONUT 2.0 and automated literature mining using DECIMER.ai

K. Rajan, Jena/DE, V. Chandrasekhar, Jena/DE, S. Kanakam, Jena/DE, N. Sharma, Jena/DE, J. Schaub, Jena/DE, A. Zielesny, Recklinghausen/DE, C. Steinbeck, Jena/DE

P 02
STOUT V2: Improved Translation Between SMILES/SELFIES and IUPAC Nomenclature Using Transformer Models

K. Rajan, Jena/DE, A. Zielesny, Recklinghausen/DE, C. Steinbeck, Jena/DE

P 03
Advancements in Hand-Drawn Chemical Structure Recognition through an Enhanced DECIMER Architecture

K. Rajan, Jena/DE, A. Zielesny, Recklinghausen/DE, C. Steinbeck, Jena/DE

P 04
Smart Experimentation: Adaptive Strategies for Efficient Kinetic Learning in Catalytic Reactors

M. Kouyate, Berlin/DE, G. Ducci, Berlin/DE, C. Scheurer, Berlin/DE, K. Reuter, Berlin/DE

P 05
From real to synthetic: Probing machine learning tools with synthetic tasks derived from bioactivity data

L. Kinzel, Braunschweig/DE, K. Baumann, Braunschweig/DE

P 06
Graph Neural Networks as Implicit Solvents

P. Katzberger, Zurich/CH

P 07
Machine Learning-Assisted Evaluation of Potential Risk of Human Exposure to Chemicals

S. Singh, Freising/DE, D. Schicker, Freising/DE, T. Sauerwald, Freising/DE

P 08
Toward Structural Search of Chemical Compounds by Using BERT

Y. Kuzumoto, Higashi-Osaka City/JP, H. Handa, Higashi-Osaka City/JP, A. Vashilevich, Higashi-Osaka City/JP, T. Kihara, Higashi-Osaka City/JP

P 09
Growing Innovation: Generative Chemistry in Crop Protection Research

A. S. Kamenik-Albertini, Stein/CH

P 10
A “Solvated” ANI-type Machine Learning Potential for Modeling Solvent-Mediated Free Energy Surfaces

S. Maste, Dortmund/DE, C. Chodun, Dortmund/DE, M. Strobl, Dortmund/DE, K. K. Huddleston, Gainesville/US, I. J. Pickering, Gainesville/US, A. E. Roitberg, Gainesville/US

P 11
Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches

S. K. R. Homberg, Münster/DE, M. L. Modlich, Münster/DE, J. Menke, Gothenborg/SE, G. M. Morris, Oxford/GB, B. Risse, Münster/DE, O. Koch, Münster/DE

P 12
Variational-LoRA: Parameter-Efficient Uncertainty Quantification for Molecular Property Prediction

I. S. Jayasekera, London/GB, J. Sieg, Ludwigshafen/DE, M. Mathea, Ludwigshafen/DE, Y. Li, London/GB

P 13
A Comparison of Selective State Space Models and Transformers for Single-Step Retrosynthetic Reaction Prediction

L. Roth, Hamburg/DE, K. Schöning-Stierand, Hamburg/DE, S. Remus, Hamburg/DE

P 14
The next generation of the IUPAC International Chemical Identifier (InChI)

G. Blanke, Essen/DE, N. Khan, Aachen/DE, F. Lange, Aachen/DE, S. Herres-Pawlis, Aachen/DE, I. Bruno, Cambridge/GB, J. Goodman, Cambridge/GB, R. Hartshorn, Christchurch/NZ, H. Rey, Darmstadt/DE, U. Schatzschneider, Würzburg/DE, C. Tovee, Cambridge/GB, A Yerin, Porto/PT, D. Baljozovic, Aachen/DE, F. Bänsch, Frankfurt/Main/DE, J. Brammer, Aachen/DE

P 15
The Cheminformatics Microservice: An Open Solution for Accessing Multiple Cheminformatics Toolkits

S. Kanakam, Jena/DE, V. Nainala, Jena/DE, J. Schaub, Jena/DE, N. Sharma, Jena/DE, C. Steinbeck, Jena/DE, K. Rajan, Jena/DE

P 16
Water Monitoring of the Future: Quantification of Non-Target Screening Data Using Publicly Available Data

E. Rosenheinrich, Berlin/DE, T. Backhaus, Aachen/DE, K. Jewell, Koblenz/DE, A. L. Kronsbein, Berlin/DE, T. Schulze, Berlin/DE, E. L. Schymanski, Belval/LU, J. Koschorreck, Berlin/DE

P 17
Towards systematic initiations of minimum energy path calculations

M. Mücke, Göttingen/DE, R. Mata, Göttingen/DE

P 18
NAOPI: A Python-Driven Workflow Engine for Complex Structure-BasedDesign Tasks

J. Pletzer-Zelgert, Hamburg/DE, T. Kuhrt, Hamburg/DE, T. Gutermuth, Hamburg/DE, B. Kuhn, Basel/CH, M. Rarey, Hamburg/DE

P 19
MolBar: A molecular identifier for inorganic and organic molecules with full support of stereoisomerism

N. van Staalduinen, Aachen/DE, C. Bannwarth, Aachen/DE

P 20
Vision language models for large scale chemical data extraction

M. Elstner, Oslo/NO

P 22
Identification of promiscuous scaffolds and their relevant binding pockets for fragment-based design

A.-K. Prinz, Münster/DE, O. Koch, Münster/DE

P 23
Machine Learning Models to Predict Activities of Kinase Inhibitors

J.-Y. Guo, Berlin/DE, A. Nunes-Alves, Berlin/DE

P 25
Version 2024 of the Synthetically Accessible Virtual Inventory (SAVI)

M. Nicklaus, Frederick/US, P. Judson, Harrogate/GB, W. Ihlenfeldt, Glashütten/DE, O. Grushin, Frederick/US, N. Tarasova, Frederick/US

P 26
(Quick) Shape Screening in the Age of Ultra-large Libraries

T. Knehans, Mannheim/DE, S. Dixon , New York/US, J. Duan, Mannheim/DE, C. von Bargen, New York/US, V. Babin, New York/US, N. Boyles, Portland/US, S. Jerome, New York/US, M. Repasky, Portland/US

P 27
MORTAR: a rich client application for in silico molecule fragmentation and fragment feature vector-based clustering

J. Schaub, Jena/DE, F. Bänsch, Recklinghausen/DE, B. Sevindik, Recklinghausen/DE, S. Behr, Recklinghausen/DE, M. Rottmann, Recklinghausen/DE, Z. Dagtekin, Recklinghausen/DE, C. Steinbeck, Jena/DE, A. Zielesny, Recklinghausen/DE

P 28
Crystallographic Fragment Screening Unveils Kinase Binders with Enhanced Three-Dimensionality Derived from Natural Products

A. Santura, Mainz/DE, I. Tutzschky, Mainz/DE, S. Glinca, Hamburg/DE, P. Czodrowski, Mainz/DE

P 29
Patent Analysis → Scaffold Hopping → Improved ADMET Properties

L. Reid, Macclesfield/GB, J. Stacey, Macclesfield/GB, P. de Sousa, Macclesfield/GB, D. James, Macclesfield/GB, B. Kahn, Macclesfield/GB, D. Cousins, Macclesfield/GB, A. Leach, Manchester/GB, E. Griffen, Macclesfield/GB, A. Dossetter, Macclesfield/GB

P 30
Molecular CrossDocking Study of Components of Ten Medicinal Plants in the Philippines Against Selected Protein Targets of Mycobacterium tuberculosis

J. Billones, Manila/PH, R. Castro, Manila/PH

P 31
Novel approaches for data augmentation in de novo drug design: Deletion, masking and substitution

H. Brinkmann, Eindhoven/NL, A. Argante, Eindhoven/NL, H. ter Steege, Eindhoven/NL, F. Grisoni, Eindhoven/NL

P 32
Understanding and Quantifying Flexibility: Torsion Angular Bin Strings

J. Braun, Zurich/CH

P 33
Avoiding chemotype bias in virtual screening: diverse chemical space exploration using 3D electrostatic field and shape descriptors

O. Hills, Cambridge/GB, N. Kidley, Cambridge/GB

P 34
BILN – A Human-readable Line Notation for Complex Peptides

T. Fox, Biberach/DE, M. Bieler, Biberach/DE, P. Haebel, Biberach/DE, R. Ochoa, Biberach/DE, S. Peters, Biberach/DE, A. Weber, Biberach/DE

P 35
Rough estimate of the prediction error from data set topology

A. Asanoski, Baunschweig/DE

P 36
Evaluation of Molecular Representations for Virtual Screening and Molecular Machine Learning: A holistic benchmark framework

M. Grieswelle, Münster/DE, S. Homberg, Münster/DE, M. Modlich , Münster/DE, B. Risse, Münster/DE, O. Koch, Münster/DE

P 37
Fragment-Based Drug Design Towards New Antituberculotics: Crystallographic Fragment Screening and What We have Learned About Fragment-Binding

F. Becker, Münster/DE, P. Janssen, Münster/DE, F. T. Füsser, Münster/DE, D. Kümmel, Münster/DE, M. S. Weiss, Berlin/DE, O. Koch, Münster/DE

P 38
Fragment libraries: How sociable are they, and can we do better?

P. Janssen, Münster/DE, F. Becker, Münster/DE, T. Matviyuk, Kyiv/UA, I. Kondratov, Kyiv/UA, O. Koch, Münster/DE

P 39
Novel Kinase Ligand Generation using Subpocket-Based Docking

K. Buchthal, Saarbrücken/DE, P. L. Kramer, Saarbrücken/DE, A. Volkamer, Saarbrücken/DE

P 40
Why is Miransertib effective against the AKT1-E17K mutation?

E. Primavera, Perugia/IT, G. Pérez-Hernández, Berlin/DE, R. López-Ríos de Castro, Berlin/DE, A. Astolfi, Perugia/IT, A. Volkamer, Saarbrücken/DE, M. L. Barreca, Perugia/IT

P 41
SOMba: Performant Self-Organizing Maps for Drug Discovery

J. Kaminski, Münster/DE, F. Victoria-Muñoz, Münster/DE, J. Massa, Münster/DE, O. Koch, Münster/DE

P 42
Structural Activity Prediction Models Recover Known Kinase Binding Modes

M. Backenköhler, Saarbrücken/DE, J. Groß, Saarbrücken/DE, P. L. Kramer, Saarbrücken/DE, V. Wolf, Saarbrücken/DE, A. Volkamer, Saarbrücken/DE

P 43
Applicability of Graph Neural Networks for the prediction of peptides’ bitter taste

A. Steuer, Freising/DE, P. Srivastava, Rostock/DE, S. Bej, Rostock/DE, O. Wolkenhauer, Rostock/DE, A. Di Pizio, Freising/DE

P 44
Active Learning for Fragment-Based Kinase Inhibitor Design using Docking

P. L. Kramer, Saarbrücken/DE, M. Backenköhler, Saarbrücken/DE, A. Volkamer, Saarbrücken/DE

P 45
MolDockLab: Data-Driven Workflow for Best Balanced Consensus Docking Pipeline for Hit Identification

H. Ibrahim, Saarbrücken/DE, M. Backenköhler, Saarbrücken/DE, A. Lacour, Saarbrücken/DE, I. Exapicheidou, Saarbrücken/DE, M. Hamed, Saarbrücken/DE, A. K. H. Hirsch, Saarbrücken/DE, A. Volkamer, Saarbrücken/DE

P 46
Systematic Exploration of a Multi-Promoter Catalyst Composition Space with Limited Experiments

C. W. P. Pare, Berlin/DE

P 47
Enhancing material property predictions using quantum chemical bonding descriptors.

A. Naik, Berlin/DE, P. Benner, Berlin/DE, G-M. Rignanese, Louvain-la-Neuve/BE, J. George, Berlin/DE

P 48
Understanding the role of aromaticity in tautomeric equilibria

M. Lim, Mainz/DE, O. Palomino-Hernández, Mainz/DE, P. Czodrowski, Mainz/DE

P 49
Boost your Atomistic Simulations via NHR@FAU

H. Lanig, Erlangen/DE, A. Horn, Erlangen/DE

P 50
Structural alert mining by MS2LDA topic modelling in untargeted computational tandem mass spectrometry

J. Dietrich, Wageningen/NL, R. Torres Ortega, Wageningen/NL, H. Mol, Wageningen/NL, J. J. J. van der Hooft, Wageningen/NL

P 51
Current State of the EC-RISM Solvation Model Integrationin ORCA and Turbomole

P. Kibies, Dortmund/DE, N. Tielker, Dortmund/DE, J. Haberhauer, Bochum/DE, Ö. F. C. Tiska, Bochum/DE, M. A. Garcia-Ratés, Köln/DE, C. Riplinger, Köln/DE, F. Neese, Mülheim/DE, C. Hättig, Bochum/DE, S. M. Kast, Dortmund/DE

P 52
Investigation of the bottlenecks and pathways for inhibitor dissociation from [NiFe] hydrogenase using simulations and machine learning

F. Sohraby, Berlin/DE, A. Nunes-Alves, Berlin/DE, J. Guo, Berlin/DE

P 53
Parallel Sampling of Protein-Ligand Dynamics

M. Masters, Basel/CH, A. Mahmoud, Basel/CH, M. Lill, Basel/CH

P 54
Unravelling the role of medium-chain free fatty acids on the activity of the phospholipase PlaF from P. aeruginosa

R. Gentile, Düsseldorf/DE, M. Modric, Jülich/DE, K.-E. Jaeger, Jülich/DE, F. Kovacic, Jülich/DE, S. Schott-Verdugo, Jülich/DE, H. Gohlke, Düsseldorf/DE

P 56
An automated Calculation Pipeline for Differential Pair Interaction Energies with Molecular Force Fields using the Tinker Molecular Modeling Package

F. Bänsch, Recklinghausen/DE, M. Daniel, Recklinghausen/DE, H. Lanig, Erlangen/DE, C. Steinbeck, Jena/DE, A. Zielesny, Recklinghause/DE

P 57
PySSA: end-user protein structure prediction and visual analysis with ColabFold and PyMOL

A. Zielesny, Recklinghausen/DE, H. Kullik, Recklinghausen/DE, M. Urban, Recklinghausen/DE, J. Schaub, Jena/DE, A. Loidl-Stahlhofen, Recklinghausen/DE

P 58
Pocketomes at an evolutionary scale

H. Zillmer, Potsdam/DE, D. Walther, Potsdam/DE

P 59
On the difficulty of allosteric site and conformational state prediction with current deep learning methods

C. Tyrchan, Möldnal/SE, G. Testa, Mölndal/SE, A. Tibo, Mölndal/SE, E. Nittinger, Mölndal/SE, G. Olanders, Mölndal/SE

P 60
Identifying a potential binding site of the inhibitor oleic acid in Cv2025 using MD simulations

J. Kaiser, Düsseldorf/DE, D. Becker, Düsseldorf/DE, R. Gentile, Düsseldorf/DE, S. Schott-Verdugo, Jülich/DE, H. Gohlke, Düsseldorf/DE

P 61
Exploring the interactions of multivalent ligands with C-type lectin homotetramers

Y. L. Ho, Düsseldorf/DE, M. Bonus, Düsseldorf/DE, J. Cramer, Düsseldorf/DE, H. Gohlke, Düsseldorf/DE

P 62
Free energy surfaces of the ion conduction through the small viral potassium channel KcvPBCV-1

J. Borchert, Dortmund/DE, L. E. Schumann, Dortmund/DE, G. Thiel, Darmstadt/DE, S. M. Kast, Dortmund/DE

P 63
How do autoencoders help explore the conformational space of MD simulations of cyclic peptides?

L. M. Windeln, Southampton/GB, C. Holdship, Southampton/GB, J. G. Frey, Southampton/GB, J. W. Essex, Southampton/GB

P 64
FPR2: Elucidating the Binding Mode of Small Molecules

J. Massa, Münster/DE, J. Calderón, Erlangen/DE, S. Maskri, Münster/DE, T. Clark, Erlangen/DE, O. Koch, Münster/DE

P 65
Solvent-Controlled Separation of Integratively Self-Sorted Supramolecular Coordination Cages

F. Sendzik, Dortmund/DE, K. E. Ebbert, Dortmund/DE, L. Neukirch, Dortmund/DE, L. Eberlein, Dortmund/DE, A. Platzek, Dortmund/DE, G. H. Clever, Dortmund/DE, S. M. Kast, Dortmund/DE

P 66
Mutanobactin D from the Human Microbiome: Computational and Experimental Structure Activity Relationship Studies

P. Brandl, Zürich/CH, M. E. Hansen, Zürich/CH, F. Pultar, Zürich/CH, E. M. Carreira, Zürich/CH, S. Riniker, Zürich/CH

P 67
Read-Across the Targetome – An integrated structure- and ligand-based workbench for computational design of novel tool compounds

Y. Zhang, Saarbrücken/DE, D. Sydow, Cambridge/GB, A. Volkamer, Saarbrücken/DE

P 68
Automated curation of protein structural data with InVivoPDB

F. König, Düsseldorf/DE, T. El Harrar, Jülich/DE, S. Schott-Verdugo, Jülich/DE, H. Gohlke, Jülich/DE

P 69
The Devil is in the detail: Protonation states analysis of protein-complexed and uncomplexed ligands

S. Clower, Mainz/DE, P. Czodrowski, Mainz/DE

P 70
Machine Learning Derived QSAR Models Furnished Potentially COX2 Active Newly Designed Coxiblike and Similar Compounds

L. Billones, Manila/PH, A. Gonzaga, Manila/PH

P 71
GP3-xTB: A general purpose self-consistent Tight-Binding Quantum Chemical Method

T. Froitzheim, Bonn/DE, M. Müller, Bonn/DE, A. Hansen, Bonn/DE, S. Grimme, Bonn/DE

P 72
Morphological Data Analysis: From Descriptor Development to Predictive Modelling

F. Odje, Saarbrucken/DE, L.-M. Rolli, Saarbrücken/DE, A. Volkamer, Saarbrücken/DE

P 73
Domain adaptation as a computationally efficient approach for improving transformer models for molecular property prediction

A. Sultan, Saarbruecken/DE, M. Rausch-Dopunt, Saarbruecken/DE, X. Yu, Saarbruecken/DE, A. Volkamer, Saarbruecken/DE, D. Klakow, Saarbruecken/DE

P 74
Development of a low-scaling density fitted NEO-DFT implementation

M. Breitenbach, Göttingen/DE

P 75
Sweet Or Bitter?

S. El-atawneh, Münster/DE