The Team
These are the Volkamer Lab members.
Group Leader
JProf. Dr. Andrea Volkamer
Group leader
Members
Dr. Jaime Rodríguez-Guerra
Postdoc
Scalable alchemical free energy calculations and machine learning for kinase drug discovery
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
Andrea Morger
PhD candidate
In silico toxicity prediction and application to external data
Dominique Sydow
PhD candidate
Binding site comparison for off-target and polypharmacology prediction
Talia B. Kimber
PhD candidate
Machine learning for kinase drug discovery
Yonghui Chen
PhD candidate
Virtual screening and deep learning for drug discovery
Lisa Chiara Gosch
Dr. med. candidate
Computational and experimental testing of novel EGFR and HDAC inhibitors (co-supervised with Prof. Höpfner)
Students
- Michele Wichmann (Master student)
Dynamic pharmacophore modeling from apo structures - Allen Dumler (Bachelor student)
Standardization pipelines in computer-aided drug design - Mareike Leja (Intern)
Advancing TeachOpenCADD with MD simulation notebooks - Sakshi Misra (Intern)
Advancing TeachOpenCADD with machine learning notebooks
Alumni
- 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)