The Team
These are the Volkamer Lab members.
Group Leader
Prof. Dr. Andrea Volkamer
![](/images/team/andreavolkamer.jpg)
Group leader
Administrative Assistance
Stefanie Wessinger
![](/images/team/stefaniepilhofer.jpg)
Administrative assistance
Members
Dr. Michael Backenköhler
![](/images/team/michael.jpg)
PostDoc (UdS)
Neuro-explicit models for drug discovery
Dr. Raquel López-Ríos de Castro
![](/images/team/raquellopezcastro.jpg)
Einstein BIH PostDoc (Charité)
Machine learning for kinase drug discovery
Dr. Pérez Hernández Guillermo
![](/images/team/perezhernandezguillermo.jpg)
Einstein BIH PostDoc (Charité)
Molecular Dynamics, Kinase Drug Discovery and Software Development
Antoine Lacour
![](/images/team/antoinelacour.jpg)
PostDoc
DockM8 Development, Virtual Screening for NextAID, and Machine Learning for Drug Discovery
Yonghui Chen
![](/images/team/yonghuichen.jpg)
PhD candidate (FU Berlin)
Virtual screening and deep learning for drug discovery
Paula Linh Kramer
![](/images/team/paulakramer.jpg)
PhD candidate (UdS)
Deep learning for novel kinase inhibitors (in co-supervision with Prof. Dr. Verena Wolf)
Floriane Odje
PhD candidate (UdS)
Development of DL models based on morphological and molecular data. BMBF-funded MORPHEUS project
Afnan Sultan
![](/images/team/afnansultan.jpg)
PhD candidate (UdS/BASF)
Generative AI for molecules with non-toxic properties
Yanyuan Zhang
![](/images/team/yanyuanzhang.jpeg)
PhD candidate (UdS)
Read-Across the Targetome
Hamza Ibrahim
![](/images/team/hamzaibrahim.jpg)
PhD candidate (UdS)
Structure-based Machine Learning
Associated members
Alexander Gujarnov
![](/images/team/GurjanovProfilfoto.jpg)
PhD candidate (Bayer)
Biostatistics and in silico toxicology for development of virtual control groups at Bayer AG
Erika Primavera
![](/images/team/erika.primavera.jpg)
Visiting PhD candidate (UniPg)
Molecular Dynamics and Virtual Screening for novel AKT1 inhibitors/non-conventional degraders. Co-financed by NRRP (EU) and Sibylla Biotech S.p.A.
Students
Armin Ariamajd
![](/images/team/ArminAriamajd.jpg)
Master student, Chemistry (FU Berlin)
Modeling of target-focused dynamic pharmacophores, using molecular dynamics simulations.
Katharina Buchthal
![](/images/team/katharinabuchthal.jpg)
Master student, Bioinformatics (UdS)
Novel kinase ligand generation using subpocket-based docking
Lisa-Marie Rolli
![](/images/team/lisamarierolli.jpg)
Master student, Bioinformatics (UdS)
MORPHEUS project, pre-procesing data from images to morphological profiles
Fatemeh Moghaddam
![](/images/team/fatemehmoghaddam.jpg)
Master student, Bioinformatics (UdS)
Interpretable E3-GNN affinity models
Premnath Madanagopal
![](/images/team/premmadan.jpg)
Master student, Bioinformatics (UdS)
Biologically-informed neural networks for molecule production
Maximilian Bähr
![](/images/team/maxbaehr.jpg)
Bachelor student, Bioinformatics (UdS)
Active Learning
Alumni
- Talia B. Kimber (PhD candidate)
Website
Machine learning for kinase drug discovery - Dominique Sydow (PhD candidate)
LinkedIn
Binding site comparison for off-target and polypharmacology prediction - Dr. David Schaller (Postdoc)
Free energy calculations and machine learning for kinase drug discovery with focus on mutations - Dr. Corey Taylor (Postdoc)
Machine learning and method development for kinase drug discovery - Jacqueline Krohn (Master student)
Data splitting schemes to evaluate the performance of ML-based molecular activity prediction - Mareike Leja (Master student)
Virtual Screening Pipeline for Drug-Like PPIP5K2 Inhibitors - Sonja Rothkugel (Master student)
Custom-KinFragLib - Exploring filter strategies to reduce the library size - Julian Pipart (Bachelor student)
Structural Alignment tool for Python - Dr. Jaime Rodríguez-Guerra (Postdoc [NOW - Software Engineer at Quansite])
Scalable alchemical free energy calculations and machine learning for kinase drug discovery - Andrea Morger (PhD candidate)
In silico toxicity prediction and application to external data - Lisa Chiara Gosch (Dr. med. candidate)
Computational and experimental testing of novel EGFR and HDAC inhibitors (co-supervised with Prof. Höpfner) - Franziska Fritz (Master student project work)
PLIPify: Protein-Ligand Interaction Frequencies across Multiple Structures. - Michele Wichmann (Master student)
Dynamic pharmacophore modeling from apo structures - Allen Dumler (Bachelor student)
Standardization pipelines in computer-aided drug design - Sakshi Misra (Intern)
Advancing TeachOpenCADD with machine learning notebooks - Paula Schmiel (Master student and short term scientist)
Subpocket-based fragmentation and recombination of kinase inhibitors - Robert Strothmann (Bachelor student)
Automatic generation of T²F-Flex pharmacophores based on MD simulations - Henry Webel (Scientist)
Predicting cytotoxicity using deep neural networks - Boran Adas (Master thesis and GoogleSummerOfCode)
Robust machine learning pipeline for classification problems in cheminformatics - Dr. Jérémie Mortier (Scientist)
Truly target-focused pharmacophore modeling (T²F-Pharm) - Shalini Muralikumar (Intern)
In silico investigation of protein-protein interactions during sumoylation of Smyd1 - Pratik Dhakal (Student assistant and Master thesis)
Truly target-focused (dynamic) pharmacophore modeling (T²F-Pharm and T²F-Flex) - Eva Aßmann (Bachelor thesis)
Predicting kinase similarity using a novel fingerprint-based binding site comparison method - Jacob Gora (Student assistant and Master thesis with Novartis)
Machine learning for kinase activity prediction & Active learning for compound optimization - Maximilian Driller (Master student project work)
Computer-aided drug design - an interactive Python pipeline (TeachOpenCADD) - Angelika Szengel (Master student project work)
Structure-based computational target prediction (review)