Stefan Boresch

Setting up MD Simulations of Biomolecules

Stefan Boresch is professor in the Department of Computational Biological Chemistry of the Faculty of Chemistry since 2011. An expert in biomolecular MD simulations, his research interests encompass, among others, methods development and applications of MD based free energy simulations, extending free energy simulations to hybrid QM/MM descriptions of interactions, and presently, he employs above techniques to understand complications resulting from tautomerism when computing free energy differences and works towards the automated setup of FES. He is a developer of the CHARMM biomolecular simulation package and regularly participates in the CHARMM developers' meetings.

Sharon Bryant

De-Risking Compound Structures for Neurotoxicity: The NeuroDeRisk Inte:Ligand Profiler

Sharon Bryant is CEO at Inte:Ligand GmbH, a company that develops computer aided molecular design software and provides research consulting services to pharmaceutical and life science industries in 88 countries worldwide. She has more than 30 years experience in computer-aided molecular design, molecular modeling and research consulting with pharmaceutical, cosmetic and nutrition industries involving a variety of targets, including cancer, antivirals and GPCRs. Sharon is also a Guest Professor at the University of Vienna, where she teaches courses in the Master in Drug Discovery and Pharmacy programs. Prior to joining Inte:Ligand, she was a Research Scientist at the National Institutes of Health (NIH), specializing in computer aided design, protein modeling and biophysical methods to develop small molecule and peptide derivatives targeting opioid receptors. Her work culminated in more than 130 research publications and patents covering opioid inventions. One of her current research interests, together with the Inte:Ligand and University of Vienna teams, involves developing predictive in silico tools for derisking molecules for neurotoxic adverse outcomes (NeuroDeRisk-IMI-2 Initiative, https://neuroderisk.eu/in-silico-toolbox/).

Andrea Cavalli

Dynamic docking and free energy estimation approaches to drug discovery

Andrea Cavalli is Professor of Medicinal Chemistry at the University of Bologna and Director of Computational and Chemical Biology at the Italian Istitute of Tecnology, Genova (Italy), where he is also Associate Director for the Research Domain ”Computational Sciences”. He is also Director of the PhD in Data Science and Computation of the University of Bologna. Prof. Cavalli received his PhD in Pharmaceutical Sciences from the University of Bologna in 1999 and did postdoctoral work at SISSA (Trieste, Italy) and ETH (Zurich, Switzerland). Prof. Cavalli’s research has combined computational chemistry with drug discovery, focusing on neurodegenerative diseases, cancer, and neglected tropical diseases. Recently, he has started research projects in the field of machine learning, combining genomics with clinical data. He has developed and applied algorithms and protocols to accelerate and enhance the discovery of novel lead and drug candidates. In particular, he has been a pioneer in the use of molecular dynamics simulations and related approaches to drug discovery. In an interdisciplinary effort, these approaches led to the identification and characterization of lead candidates within the framework of multitarget drug discovery and polypharmacology. He is an author of more than 250 scientific papers and inventor in several international patents. He has delivered more than 130 invited lectures and seminars at international congresses and prestigious institutions. He is member of the Editorial Board of several international journals, and in 2014 he founded a high-tech startup company (BiKi Technologies) focused on molecular dynamics and enhanced sampling methods for drug discovery. In 2003, he was awarded the Farmindustria Prize for Pharmaceutical Research.

Claire Colas

Structure based ligand discovery methods applied to Solute Carrier Transporters

Claire Colas is a postdoctoral scientist at in the Pharmacoinformatics research group (University of Vienna). She completed her PhD in 2011 at the Pasteur Institute in Paris, France and worked for two years as a postdoctoral scientist at the Institut de Chimie des Substances Naturelles at Gif-sur-Yvette, France. Since 2013, Dr. Colas’ research has been focused on the structural characterization of Solute Carrier (SLC) transporters. In humans, there are over 450 SLCs that transport a broad range of substrates, including neurotransmitters, metabolites, and drugs. Thus, SLCs are emerging as important therapeutic targets. First at the mount Sinai School of Medicine in New-York City (2013-2018) and then in Vienna (2018-present), Dr Colas has been working on distinct SLC families, involved in various diseases and disorders. Dr Colas uses various computational methods such as homology modeling and molecular docking to explore the structural determinants defining the substrate specificities of SLCs.

Daniela Digles

Analysing Solute Carrier (SLC) substrates with KNIME

Daniela Digles is post-doc as well as senior lecturer at the Department of Pharmaceutical Sciences, University of Vienna. She completed her PhD studies with a DOC-fFORTE-fellowship of the Austrian Academy of Sciences at the University of Vienna, in the Pharmacoinformatics Research Group of Prof. Gerhard Ecker. In 2012 she started her Post-doc within the Open PHACTS project (IMI), and later on within the Open PHACTS Foundation, where she was testing the developed system, creating KNIME workflows to access the data to answer research questions, as well as user support. Currently, she is involved in the RESOLUTE project (IMI), and is a curator of WikiPathways. Her main research interests are the usage and quality control of open data (especially for solute carrier proteins), classification schemes, and the application of workflow tools.

Gerhard Ecker

Integrated approaches for toxicity prediction

Gerhard Ecker is Professor of Pharmacoinformatics and Head of the Pharmacoinformatics Research Group at the Department of Pharmaceutical Chemistry, University of Vienna. He also coordinates the research focus “Computational Life Sciences” of the Faculty of Life Sciences. Gerhard received his doctorate in natural sciences from the University of Vienna and performed his post-doctoral training at the group of J. Seydel in Borstel (Germany). His research focuses on computational drug design, with special emphasis on drug-transporter interaction and in silico safety assessment. He coordinated the Open PHACTS project, which created an Open Pharmacological Space by semantic integration of public databases. Gerhard served 2009 – 2011 as President of the European Federation for Medicinal Chemistry, and is currently Dean at the Faculty of Life Sciences. In 2018, he founded the company Phenaris, which leverages linked open data for safety assessment of drug candidates.

Stephan Ehrlich

Structure-based screening of large chemical libraries

Stephan Ehrlich works as Principal Scientist in Schrödinger's Applications Science team. Before joining Schrödinger in 2016, he did a postdoc at the University of Bonn where he cooperated with Bayer HealthCare to predict protein-ligand binding affinities using graphics card based quantum mechanical methods. He received his PhD from the University of Münster, where he was working on non-covalent interactions in small organic systems in the Group of Prof. Dr. Stefan Grimme. A chemist by training, Stephan has a broad background in the field of computational chemistry with a focus on non-covalent interactions and quantum-mechanical methods.

Margot Ernst

Homology modeling in the gray zone of low sequence similarity

Margot Ernst is Assoc. Prof. at the Medical University of Vienna, where she works since 2001 on the structure and pharmacology of GABAA receptors. Prior to her current computational focus – modelling of this protein family – she was trained as computational chemist and applied quantum chemical methods to diverse chemotypes. Her current research interests include the experimental calibration of computational scoring and ranking schemes, as well as the computational analysis of protein- ligand interactions. Course participants can expect to learn about homology modeling in the gray zone of low sequence similarity, dealing with variable regions,assessing protein functional states, treatment of highly mobile or flexible proteins, and efficient means to collaborate with experimental labs in the design of informative ligands or mini-libraries on the one hand, and informative mutational studies of the protein on the other hand.

Stuart Firth-Clark

Using Spark™ and Flare™ to design and prioritize novel molecules in a drug design project

Stuart Firth-Clark obtained his PhD in Chemistry from the University of Bath where he investigated the use of computational methodologies to study chemical reactivity. He then spent 20 years working for small biotech contract research organizations where he was responsible for developing and implementing their computational chemistry services to prospective and existing customers. Stuart is now a Senior Application Scientist at Cresset. His responsibilities include training and supporting Cresset customers so that they can achieve their scientific goals using Cresset’s ligand-based and structure-based software solutions.

Theres Friesacher

Molecular Dynamic Simulations of Ion Channels: Investigating a Rare Disease Mutation through the Computational Microscope

Theres Friesacher is a PhD student in the Molecular Modeling research group of Anna Weinzinger at the University of Vienna. She took up her PhD in June 2020 as a member of the doctoral program "Ion channels and transporters as molecular drug targets" (MolTag). During her undergraduate studies, Theres obtained a rich education with the main focus on bioinformatics, data analysis and programming. The emphasis of her current research is on the investigation of rare diseases associated with potassium channels using classical and coarse-grained MD simulations. Theres has contributed to two peer-reviewed papers and has an on-going collaboration with the group of Nathan Dascal at the University of Tel Aviv. Recently, she has been awarded the DOC-Fellowship of the Austrian Academy of Sciences (ÖAW).

Barbara Füzi

Pathway and network studies of toxic compounds

Barbara Füzi is a PhD student in the Pharmacoinformatics Research Group (University of Vienna). She is a member of the doctoral programs "Ion channels and transporters as molecular drug targets" (MolTag) and Europin. She is involved in the IMI project TransQST. In her undergraduate studies, she gained expertise in drug discovery and development, focusing on computational approaches. In her current project, Barbara works on in silico methods to find possible target proteins and biological processes for explaining and modeling toxic events triggered by pharmaceutically relevant compounds. She was a visiting student at the European Bioinformatics Institute (EMBL-EBI) and the Integrative Biomedical Informatics Group of the Research Programme on Biomedical Informatics, GRIB (IMIM- UPF). She is a student representative of the Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences (PhaNuSpo).

Marcus Gastreich

Navigating Septillion-Sized Chemical Spaces

Marcus Gastreich is BioSolveIT's Senior Director of Application Science acting as a strategic interface between pharma clients and IT development. BioSolveIT is a globally acting provider of drug modeling software and services and leads the field of Chemical Space navigation technologies. Marcus holds a diploma degree in chemistry from the University of Bonn, Germany. He did his doctorate in Theoretical Chemistry under supervision of Prof. Christel M. Marian on ab initio NMR simulation of solids and force field development for amorphous materials, with a minor in Bioinformatics. In the late 90’s, he went to London for a research stay with Julian Gale at Imperial College. In 1999, shortly before BioSolveIT had been founded as a spin-off from Fraunhofer Gesellschaft (FhG) in 2001, he joined Prof. Tom Lengauer's chem- and bioinformatics group in St. Augustin, Germany, where BioSolveIT's popular FlexX molecular docking program had initially been developed. Gastreich is (co-/)author of several dozens of scientific publications and has contributed to several books; his review on Chemical Space exploitation in Drug Discovery Today stayed in the top 10 of the most downloaded articles for months. Marcus's major interests lay in visually appealing, scientific app design, visualization of molecular information, and exploiting fast, interactive algorithms to help in drug design and development. His fingerprint can be clearly made out on tools such as SeeSAR, infiniSee, and PepSee, a therapeutic peptide analysis and design software. Marcus travels worldwide to understand users' & clients' needs, and to give presentations and workshops. He has insight into small and large organizations of both academic and industrial flavors. His responsibilities span from the US, across Europe, and to Japan.

Daria Goldmann

"Career Talk" & Predicting bioactivity in KNIME Analytics Platform

Daria Goldmann has background in computational chemistry and molecular modeling and is a data scientist in the Life Sciences team at KNIME. She joined KNIME in Berlin in 2017. Before that she worked as a computational toxicologist at Bayer CropScience. She developed her passion to visual programming with KNIME during her PhD research at the University of Vienna.

Melanie Grandits

Build Machine Learning Models using Jupyter Notebook

Melanie Grandits is working as Senior Scientist in the Pharmacoinformatics Research Group (Prof. Ecker) at the University of Vienna. She studied biotechnology at the University of Natural Resources and Life Sciences and did her doctoral research study under the supervision of Prof. Oostenbrink in the field of molecular modeling and simulations. Her focus was the study of protein-ligand interactions of various proteins amongst others the Auxin Binding protein 1 and Phospholipase A2 using molecular dynamics simulations. During her PostDoc, she was involved in the K4DD project by studying the heat shock protein 90 as well as the eTOX project with a specific focus on transporter proteins. At the moment she is using web-based applications to build classification models for FDA-relevant transporters to allow the prediction of small molecules. Recently, she also joined the newly started Horizon 2020 project RISK-HUNT3R which focuses on new risk assessment approaches to allow animal-free testing strategies.

Andrew Henry

MOEsaic: Guiding Multi-Parameter Optimization in Ligand-Based Design

Andrew Henry studied with Professor Tony Rees at the University of Bath, using homology modeling to help reduce the immunogenicity of therapeutic antibodies. This work continued at Oxford Molecular and Millennium Pharmaceuticals. Andrew has worked for Chemical Computing Group customer support group since 2003 and is now a Principal Scientist.

Gerhard Hessler

Computational Design of macrocyclic compounds

Dr. Gerhard Hessler is head of the group “Synthetic Molecular Design” in Integrated Drug Discover at Sanofi in Frankfurt, Germany. He is responsible for computational chemistry and data management, as well as experimental approaches like biophysical measurement and x-ray crystallography, for the identification of novel lead structures and subsequent lead optimization. Before, he headed teams in computer-aided drug design and structural biology since 2008. He joined Aventis in 2001 as a computational chemist, after working for four years in the computational chemistry group of the Central Research at Bayer AG. Dr. Gerhard Hessler did his Ph.D. at Technical University of Munich in NMR-based conformational analysis of biologically active peptides and oligonucleotides. During his industrial career the main focus of his work is the application of ligand- and structure-based design techniques to the development of drugs.

Alexander Hillisch

Design and Preclinical Characterization Program Towards BAY 2433334, an Oral Factor XIa Inhibitor for the Prevention and Treatment of Thromboembolic Disorders

Alexander Hillisch is a Vice President and Head of Computational Molecular Design at Bayer AG, Wuppertal, Germany. His team supports small molecule and biologics drug discovery in cardiology with computational chemistry, chemoinformatics, machine learning, in silico ADMET and structural bioinformatics techniques. From 1998 to 2003 he headed a research group at EnTec GmbH, Jena, Germany, a subsidiary of Schering AG, Berlin. There he was project manager in preclinical research and involved in the computer-aided design and pharmacological characterization of drugs against gynecological diseases and cancer. He conducted his Ph.D. thesis at the Institute of Molecular Biotechnology (IMB), Jena in the area of biophysics (NMR, FRET) and molecular modeling. Alexander Hillisch received his Ph.D. in Biochemistry with Prof. Peter Schuster in 1998 and his diploma in Pharmacy in 1995 from the University of Vienna, Austria. He is co-author of 48 research papers, 2 books and 62 pharmaceutical compound patents which led to 6 clinical development candidates. Alexander teaches “Molecular pharmacology and Drug Design” at the University of Cologne from which he received a honorary professorship in 2010. He is a member of the board of directors at the Structural Genomics Consortium (SGC, Toronto & Oxford), and at the scientific advisory board of Cresset and EUROPIN.

Dušanka Janežič

Protein Binding Sites Tools for Innovative Drug Design

Dušanka Janežič is full professor at the Faculty of Mathematics, Natural Sciences and Information Technologies at the University of Primorska (Slovenia). Has published 2 scientific books and 130 publications in SCI journals with over 2500 pure citations in Web of Science database, and h-index 22. One of the Editors in the ACS Journal of Chemical Information and Modeling (2001-2014). In 2013, Recipient of Žiga Zois Award for outstanding research achievements in mathematics in natural sciences. In 1999, Recipient of Ambassador in Science of the Republic of Slovenia Award. Since 2013 she is appointed by the government of Republic of Slovenia as council member of the National Agency of Qualitative Evaluation of Higher Education in Slovenia. She worked in the USA as a visiting researcher at the National Institute of Standards and Technology. As a Senior Fulbright Scholar she conducted research in the USA at the National Institutes of Health. She worked at the Technical University of Munich, Germany as a DAAD fellow. Her current research interests include graph theory development, prediction of protein-protein and protein-ligand binding sites, biomolecular simulations, and the application of these techniques to problems in pharmaceutical research and drug development.

Philipp Jäger

Integrative data approaches for smart PROTAC designs

Philipp Jäger is a Scientific Director at Boehringer Ingelheim in Vienna. There, he leads the High-Throughput Biology Group with a strong focus on new modality discovery for cancer research. Philipp holds a Diploma degree in biochemistry from the Free University Berlin, where he worked for his thesis on protein aggregation inhibitors with Erich Wanker at the Max Delbrück Center for Molecular Medicine. After spending a research year at the Prince of Wales Medical Research Institute in Sydney, Australia, he went on to conduct his PhD thesis research - elucidating the role of autophagy in Alzheimer’s disease - with Tony Wyss-Coray at Stanford University. In 2011 Philipp moved as a Post-Doc to the University of California San Diego, shifting his interests from neuroscience into systems biology. At UCSD, he developed cellular assays and bioinformatic tools for the phenotypic high-throughput screening of yeast mutant libraries and chemogenomics in Trey Ideker’s lab. After running his own biotech in San Diego and working as a Team Lead for assay development at the proteomics start-up Encodia Inc., Philipp joined Boehringer Ingelheim in 2020. Philipp is keenly interested in the application of large data sets (both public and private) for the discovery of new therapeutic approaches in oncology, utilizing structural information and detailed biochemical, biophysical, and cellular assays.

Johannes Kirchmair

In silico prediction of drug metabolism

Johannes Kirchmair is an associate professor in cheminformatics at the Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry of the University of Vienna and head of the Computational Drug Discovery and Design Group (COMP3D). After earning his PhD from the University of Innsbruck (2007), Johannes started his career as an application scientist at Inte:Ligand GmbH (Vienna). In 2010 he joined BASF SE (Ludwigshafen) as a postdoctoral research fellow. Thereafter he worked as a research associate at the University of Cambridge (2010-2013) and ETH Zurich (2013-2014). Johannes held a junior professorship in applied bioinformatics at the University of Hamburg (2014 to 2018) and an associate professorship in bioinformatics at the University of Bergen (2018 to 2019). His main research interests include the development and application of computational methods for the prediction of the biological activities, metabolic fate and toxicity of small molecules (including natural products) in the context of drug discovery.

Stefan Michael Kohlbacher

QPhAR: Quantitative Pharmacophore Activity Relationship

Stefan Kohlbacher is a doctoral student in the Cheminformatics Research Group at the University of Vienna under the supervision of Prof. Thierry Langer. Receiving a Bachelor’s degree in Chemistry, as well as a Master in Drug Discovery and Development, he could already gather extensive experience in the field of drug discovery. During his Master thesis, which focused on the application of neural networks for pharmacophore based de-novo design, he could extend his knowledge base into the field of informatics and machine learning. Continuing within the field of chemoinformatics, he is conducting his PhD under the scope of the NeuroDeRisk project, which aims to de-risk drug candidates from neurotoxic effects by developing and improving tools for preclinical prediction of such adverse events. The focus of his research is the development of AI-assisted next-generation pharmacophores. Special focus is put on explainable machine learning models applicable on small datasets, as often encountered in SAR-studies by medicinal chemists.

Martin Kotev

"Career Talk"

Martin Kotev holds a BS degree in chemistry and Master’s degree (2004) in medicinal chemistry from the Sofia University (Sofia, Bulgaria). He obtained his PhD in computational chemistry at the Bulgarian Academy of Sciences (BAS) in 2008, working on a conformational analysis of complex chemical structures such as 16-membered macrolide antibiotics. After his PhD, he spent 3 years as a research fellow in BAS, followed by 6 years of postdoc in the computer-aided drug design in groups of prof. Modesto Orozco, prof. Ernest Giralt (IRB Barcelona, Spain), and prof. Victor Guallar (BSC, Spain), applying Monte Carlo and molecular dynamics simulations on a variety of projects and targets. Martin Kotev contributed to the successful beginning of the first IRB/BSC spin-off company Nostrum Biodiscovery (Barcelona, Spain), joining it in 2016. Lastly, in 2018 he started at Evotec (Toulouse, France) currently working as a senior research scientist and team leader in the computational drug design.

Thierry Langer

Adventures in Computer-Assisted Molecular Design

Thierry Langer is full professor for Pharmaceutical Chemistry and head of the department of Pharmaceutical Sciences at University of Vienna, Austria. Before that, he was CEO of Prestwick Chemical, France. He is author of more than 200 original papers and has long term expertise in computational medicinal chemistry. In 2003, with colleagues he founded the software development and consulting company Inte:Ligand GmbH. which he led until 2008. He was the coordinator of the Austrian academic drug discovery initiative wings4innovation and is also currently coordinating the EU IMI2 consortium NeuroDeRisk.

F. Javier Luque

From simple solvation models to applications in target druggability and screening of drug-like compounds

Javier Luque is professor of Physical Chemistry at the University of Barcelona. He is leading the Computational Biology and Drug Design group, which is ascribed to the Institute of Biomedicine (IBUB) and the Institute of Theoretical and Computational Chemistry (IQTCUB) in the Institute of Biomedicine at the University of Barcelona. The main focus of his research is the study of biomolecular systems using theoretical and computational methods of quantum chemistry, classical simulations and molecular modeling. Special emphasis is made on the structure-dynamics-function relationships in proteins, the molecular determinants of biomolecular association and the design of novel bioactive compounds, specifically in drug discovery. In this latter area, his main interests are focused on neurodegenerative and infectious diseases. He is scientific advisor at Pharmacelera.

Floriane Montanari

"Career Talk" & An introduction to explainable AI for small molecules

Floriane Montanari is a research scientist with years of experience in cheminformatics. She has a passion for useful machine learning approaches applied at all stages of the drug discovery pipeline. Since May 2017 she is working at Bayer, where she has been lucky enough to improve the daily routine of chemists company-wide by productionizing her work on deep learning for ADMET properties. Floriane is co-author of more than fifteen scientific publications and in 2016 she received a PhD from the University of Vienna, with a thesis focusing on ABC-transporters inhibition and best practices in model validation. She enjoys participating in competitions and in 2014 she submitted the best predictive model in the Teach-Discover-Treat challenge on Malaria HTS prediction.

Abhik Mukhopadhyay

Ligand based virtual screening in Drug discovery

Abhik is a Research and Applications Scientist in the Discovery Science team at the CCDC. He completed his PhD at the University of Hyderabad in the area of transitional metal complexes and small molecule crystallography. He then went on to a Postdoctoral Research position with the FCT in Portugal which focused on developing anti-inflammatory drugs through structure-based drug design. This grew his interest in how chemical and biological structures inform drug discovery, and he joined the Protein Data Bank in Europe at EMBL-EBI as a database curator. He joined the CCDC in 2019, where he remains active in research as well as managing and developing software tools for use in drug discovery. His present work centres on how structural data can inform and inspire future drug discovery, especially in informing the conformation, design and validation of novel therapeutics.

Doha Naga

Automated machine learning in drug discovery

Doha Naga is a Data Scientist at Hoffman La Roche and a PhD student in the Pharmacoinformatics Research Group of the University of Vienna since 2018. She acquired her Pharmacy degree in Ain Shams University, Egypt (2010-2015) and her MSc degree in Computational Drug Design and Bioinformatics (2015-2017) in Paris Diderot University, France. During her Master’s degree, she performed two research internships, in the field of molecular dynamics at the French National Institute of Health and Medical Research (INSERM) and in bioinformatics-oncology in the Novartis Institute of Biomedical Research (NIBR) where she compared the effect of chemical compounds vs RNA interference on cancer cell lines. Her PhD research at Roche and in collaboration with the University of Vienna is focused on developing machine learning (ML) tools (including deep learning and autoML) to predict drug toxicities in the early discovery space prior to synthesis and exploring high through put physiologically based pharmacokinetic (PBPK) modelling to minimize in-vivo PK testing. Currently she is focused on real world data analysis and leveraging clinical data to prioritize compounds in the drug discovery pipeline.

Theresa Noonan

Inhibiting Bacterial Ribosomal Assembly as a Novel Antibiotic Approach

Theresa Noonan is a doctoral candidate in the group of Professor Gerhard Wolber at the Freie Universität Berlin. She studied Biomedical Sciences at the University of Edinburgh from 2013 - 2017 and then obtained a Masters degree in Pharmaceutical Research at the Freie Universität Berlin in 2019. Theresa has been part of the EUROPIN doctoral program since 2020. Her research focuses on using computational methods to identify novel antibiotics by analyzing bacterial ribosomal assembly and identifying small molecule inhibitors of the assembly process. Aside from bacterial ribosomes, Theresa is interested in investigating human ribogenesis, with the aim of identifying anti-cancer therapeutics capable of disrupting eukaryotic ribosomal assembly.

Chris Oostenbrink

Applications of free energy calculations from molecular dynamics simulations

Chris Oostenbrink is professor at the University of Natural Resources and Life Sciences in Vienna and heads the Institute of Molecular Modeling and Simulation (BOKU). He has published almost 200 peer-reviewed papers involving computational approaches to describe complex biomolecular systems. He was brought to BOKU on a Vienna Science Chair by the Vienna Science and Technology Fund (WWTF) in 2009 and was a recipient of a Starting Grant of the European Research Council (ERC). He heads the doctoral program Biomolecular Technology of Proteins (BioToP) in which 50 doctoral candidates are currently enrolled. His main research interests are the structure and function of complex biomolecular systems, through molecular simulations and the accurate description of molecular interactions.

Manuel Pastor

Application of knowledge-based computational methods in Toxicology

Manuel Pastor is associate professor at the Universitat Pompeu Fabra (UPF, Spain) and head of the PharmacoInformatics group of the IMIM-UPF joint Research Programme on Biomedical Informatics (GRIB). He obtained a degree in Pharmacy in 1987 and a PhD in 1994 at the University of Alcalá (Spain). MP spent two years post-doctoral stay at the Laboratory of Chemometics, University of Perugia (Italy), under the supervision of Sergio Clementi and Gabriele Cruciani. As a post-doctoral researcher, he worked as Scientific Leader for Multivariate Infometric Analysis Srl. in Perugia, between 1998 and 2000. MP is author of more than 100 scientific articles and book chapters and main responsible of numerous research projects in the field of pharmacoinformatics and in silico toxicology. MP developed numerous scientific software of widespread use in pharmaceutical companies and academic institutions (GOLPE, ALMOND, Greater, SHOP, Pentacle, eTOXlab, Flame).

Christian Permann

Greedy 3-Point Search (G3PS) - A novel algorithm for pharmacophore alignment

Christian Permann is a PhD student in the Cheminformatics Research Group at the University of Vienna under the supervision of Prof. Thierry Langer. He finished his Bachelor’s and thereafter Master’s degree in Computer Science with a Scientific Computing focus at the University of Vienna. His expertise lies in the design and implementation of high-performance algorithms for scientific applications. For his Master’s thesis, he developed a tool for visual cluster analysis and simplified semi-supervised consensus clustering. Currently, he is working with the “Research Platform Next Generation Macrocycles to Address Challenging Protein Interfaces” as part of his PhD which aims to improve the state of the art in the domain of computer-aided drug discovery, with special emphasis on macrocyclic molecules. His current work focuses on methods for the alignment of molecules based on their chemical features and the applicability of those methods for virtual screening. Another topic is the designing of similarity measures for molecular structures that can be used for a variety of supervised or unsupervised data analysis tasks and predictive models. Special attention is put on the scalability and generalizability of the methods such that they can be used accurately for all kinds of datasets while utilizing the available hardware resources as efficiently as possible.

Klaus-Jürgen Schleifer

Learning from Ligands

Prof. Schleifer studied pharmacy in Berlin. After his PhD in synthetic pharmaceutical chemistry he prepared his Habilitation in the computational working group of Prof. Höltje. In 2001 he changed from academia to industry and succeeded Prof. Kubinyi as head of Molecular Modelling at BASF Ludwigshafen. Today he is responsible for Computational Chemistry and Cheminformatics in BASF’s Digitalization in R&D organisation.

Doris Schütz

"Career Talk"

Doris Schuetz studied pharmacy at the University of Vienna. After she had finished her Master’s degree, she went to work in different pharmacies for more than 5 years, before she returned to the Department of Pharmaceutical Chemistry. She completed her PhD in the Pharmacoinformatics Research Group beginning of 2018 and while working as an application scientist for Inte:Ligand in 2017 and 2018. Since September 2018 she is part of the computational chemistry team at the Institute for Research in Immunology and Cancer (IRIC) in Montréal, Canada. Doris finished her postdoctoral studies end of 2019 and has become a research advisor after that. She is working in structure-based drug design, with a strong focus on oncology and cardiovascular targets. She is participating in academic projects, and working in close collaboration with big pharmaceutical companies. Her research focuses on macrocycle design and optimization, protein-protein interfaces, and small molecule hit to lead optimization.

Matt Segall

Multi-parameter Optimisation in Drug Discovery: Targeting compounds with a high chance of success

Matt is CEO of Optibrium. He has a Master of Science in computation from the University of Oxford and a Ph.D. in theoretical physics from the University of Cambridge. As Associate Director at Camitro (UK), ArQule Inc. and then Inpharmatica, he led a team developing predictive ADME models and state-of-the-art intuitive decision-support and visualization tools for drug discovery. In January 2006, he became responsible for management of Inpharmatica's ADME business, including experimental ADME services and the StarDrop software platform. Following acquisition of Inpharmatica, Matt became Senior Director responsible for BioFocus DPI's ADMET division and in 2009 led a management buyout of the StarDrop business to found Optibrium, which develops software for small molecule design, optimisation and data analysis. Matt has published over 30 peer-reviewed papers and book chapters on computational chemistry, cheminformatics and drug discovery.

Wolfgang Sippl

Structure based design of selective ligands for epigenetic targets

Wolfgang Sippl is Professor for Medicinal Chemistry at the Martin-Luther-University of Halle-Wittenberg (Germany). He obtained a Ph. D. in 1997 in Pharmaceutical Chemistry at the University of Düsseldorf in the group of Hans-Dieter Höltje and was a post-doctoral fellow at the Université Louis-Pasteur in Strasbourg (France) where he worked with Camille G. Wermuth. Since 2003 he is Full Professor at the University of Halle-Wittenberg and since 2010 he is Director of the Institute of Pharmacy in Halle. He has published more than 180 articles mainly related to drug design, virtual screening and structure-based optimization of epigenetic modulators. He has edited four books including and gave more than 100 invited lectures. His research focuses on the drug design of epigenetic modulators, which not only led to the development of successful virtual screening methods, but also resulted in the development and biological characterization of novel epigenetic modulators for the treatment of cancer and parasitic diseases.

Gunther Stahl

Virtual Screening - From small to LARGE scale - from local to the cloud

Gunther Stahl received his license as pharmacist in 1996 after his study at the University of Bonn. He continued his education as Ph.D. student under Prof. Höltje at the University of Düsseldorf where he received his doctorate degree in 2001 focusing on Homology Modeling and Molecular Dynamics. He then joined Tripos GmbH as Application Scientist to work with industrial and academic customers to help them apply the different computational chemistry tools available. After different roles at Tripos (Application Scientist at the US East Coast and later again from Germany as manager of the PacRim distributors) he joined OpenEye in 2012 to work with all their European customers.

Dominique Sydow

KiSSim: Subpocket-Enhanced Kinase Similarity Assessment for Off-Target Prediction

Dominique Sydow has been a PhD student part of the Volkamer Lab (Charité - Universitätsmedizin Berlin) since 2018 with a background in Molecular Life Science and Biophysics. She is interested in developing tools that help to detect and understand binding site similarity and protein-ligand interactions. During her master thesis conducted at the Wolber Lab (Freie Universität Berlin), she worked on a tool for dynamic protein-ligand interaction mapping and visualization (dynophores). Currently, she develops kinase-focused tools to explain and predict kinase polypharmacology using binding site encoding and comparison (kissim) and to explore and extend the chemical space of kinase inhibitors by subpocket-based fragmentation and recombination (KinFragLib). Passionate about passing on what she has learned herself about coding and drug design, Dominique is one of the maintainers of TeachOpenCADD, a teaching platform for open source cheminformatics and structural bioinformatics.

Freya Trasischker

Workshop: SAR Analysis using MOEsaic (CCG)

Freya Trasischker received her PhD from the University of Vienna for performing structure-based design studies on ABC transporters in the research group of Prof. Gerhard F. Ecker. Before joining CCG she did her post-doctoral studies in the HTS lab at the Center of Molecular Medicine (CeMM) in Vienna, where she moved from transporters to epigenetic proteins and trained her support skills by working closely with the wet-lab scientists of the HTS team and molecular biologists. Since 2014 she has been part of the customer support group at CCG and is now Senior Applications Scientist.

Alžběta Türková

"Career Talk"

Alžběta Türková is a postdoc in Peter Kasson lab at Uppsala University, supported by Wenner-Gren postdoctoral fellowship. Her current research interest lies in membrane fusion processes between enveloped viruses and host cells. Method-wise, Alžběta seeks to integrate physics-based modeling with data science approaches to deliver a comprehensive insight into the molecular mechanisms of infectious diseases. In 2017-2020, Alžběta pursued her PhD study in Barbara Zdrazil lab at the University of Vienna. PhD thesis of Alžběta was oriented on exploring small (organic) molecule interactions with hepatocellular solute carrier transporters by combining structure-based modeling and cheminformatic approaches. In 2016-2017, Alžběta spent three short-term research stays at EMBL-EBI (Hinxton) to contribute to the development of the Complex Portal database of protein-protein interaction data. In 2015-2017, Alžběta performed multiscale simulations of membrane pore formation induced by antimicrobial peptides in the framework of her undergraduate studies at Masaryk University in Brno (Robert Vacha Lab). Alžběta is a (co-/)author of seven peer-reviewed publications covering the above-mentioned projects.

Andrea Volkamer

In silico Tools to Support Risk Assessment of Small Molecules

Andrea Volkamer is an assistant professor in structural bioinformatics and in silico toxicology at the Institute of Physiology, Charité Universitätsmedizin Berlin. After earning her PhD from the University of Hamburg (2013), with focus on computational active site and druggability predictions, Andrea worked at BioMedX Innovation Center, Heidelberg, as a PostDoc researcher on tools to assist the development of selective kinase inhibitors in collaboration with Merck KGaA (2013-2016). Her main research focus is method development and application at the interface of structural bioinformatics and cheminformatics, with particular interest in structure-enabled machine learning approaches, applied in the context of computational drug design and in silico toxicology.

Oliver Wieder

Improved lipophilicity and aqueous solubility prediction with composite graph neural networks.

Oliver Wieder studied Biology, Sinology, Watermanagement and Environmental Engineering at the University of Vienna as well as the University of Natural Resources and Life Sciences (Austria). During his studies he had several internships, including at the Institute of Statistics (STAT, BOKU) as well as working at the Institute of Hydrology and Water Management (IHW, BOKU), where he was mainly involved in machine-learning related projects. After he finished his Dipl.-Ing. degree with distinction in 2016, he started working as a software-developer for Inte:Ligand GmbH (Vienna) and worked there till 2018, when he started his PhD in the Cheminformatics Research Group within the Department of Pharmaceutical Chemistry in collaboration with Laboratoires Servier (France) and Inte:Ligand Gmbh. His main area of research lays in the development of AI guided applications for early drug discovery - in particular graph based deep learning methods for lead optimization.

Gerhard Wolber

In silico pharmacology: Pyrod and dynophores as powerful computational microscopes to decode receptor function

Gerhard Wolber is professor for Pharmaceutical Chemistry and head of the computational chemistry group at the Institute of Pharmacy at the Freie Universität Berlin since 2010. After his studies of pharmacy at the University of Innsbruck and Computer Science at the Technical University of Vienna, he received his PhD in pharmaceutical chemistry at the University of Innsbruck. In 2003 he co-founded the molecular modeling software company Inte:Ligand. In 2008 he changed back to academia as assistant professor at the University of Innsbruck before changing to the Freie Universität Berlin in 2010. His lab bridges algorithmic design and applied computational drug discovery to develop quantitative models for the effects of small molecules on macromolecules and cellular pathways. To achieve this, the group uses a combination of biophysical in vitro methods with statistical molecular mechanics and heuristically derived interaction patterns (3D pharmacophores, dynophores).

Lorena Zara

Learn how to navigate the vast and rich protein structural space with 3decision

Lorena Zara is a Scientific Project Manager at Discngine, working in the 3decision team. 3decision is Discngine’s solution for knowledge management which helps scientists with ideation and decision-making in structure-based drug design. Lorena is responsible for external collaboration with R&D teams in pharma, onboarding, and scientific project support. Lorena has a background in computational chemistry and X-ray crystallography. She performed her Ph.D. research at the Vrije Universiteit of Amsterdam (VU), focusing on the in-silico investigation of structure-activity and structure-kinetic relationships to guide the rational design and optimization of small molecules against various drug targets, among which phosphodiesterases (PDEs). During her Ph.D., Lorena gained international research experience in other academic groups, such as in the computational lab of Prof. Xavier Barril (University of Barcelona) and the crystallography group of Prof. David Brown (University of Kent). She also worked on interdisciplinary projects with industrial partners of the FragNet consortium: ZoBio (The Netherlands) and Beactica AB (Sweden), collaborating with synthetic chemists, biophysicists, and crystallographers.

Barbara Zdrazil

Deciphering the molecular basis of ligand-recognition and selectivity in hepatic Organic Anion Transporting Polypeptides

Barbara Zdrazil is a group leader at the University of Vienna, and works as a safety data scientist for the European Bioinformatics Institute (EMBL-EBI). Barbara’s research is concentrated on integrating Data Science approaches into the Computational Molecular Design process. She focuses on off-targets (mainly hepatic uptake transporters of the SLC family), and develops automatized computational techniques to link heterogeneous data sources, perform bioactivity profiling, and generate predictive models – especially for toxicity predictions. In addition, Barbara is interested in large-scale data analyses including time trend analyses by utilizing public domain data. At EMBL-EBI, Barbara is contributing to Open Targets, a project which aims to enable systematic target identification and prioritization. Barbara received her PhD from the University of Vienna. During her PhD, Barbara mainly focused on ligand-based models for P-glycoprotein inhibitors in Gerhard Eckers’ lab. In her postdoctoral studies at the University of Düsseldorf under the supervision of Hans-Dieter Höltje she focused on structure-based modelling of DNA polymerase inhibitors. Barbara contributed to many EU-funded projects (including eTOX, OpenPHACTS, EU-ToxRisk) and is leading a nationally funded FWF project focusing on modelling of hepatic transporters since 2017. In 2019, Barbara accomplished her Habilitation in Pharmacoinformatics at the University of Vienna.