Research Groups and R&D Platforms: Hit to lead

R&D Platform:
Screening Unit

The screening unit offers academic researchers and industrial customers a broad range of services for identifying and optimising bioactive molecules for the drug discovery process. These include molecular modelling and in silico screening, development of screening assays and compound library screens, in vitro and in situ hit validation, hit optimisation and SAR analyses. A suite of cell and tissue-based disease models for oncology and neurological diseases are available for further validation of optimised hits or for independent phenotypic screens. High-throughput kinetic assays of changes in morphology or intracellular signalling over time may be integrated into chemical, genetic or optogenetic perturbation screens. A library of reporters in gene-delivery vectors are available for this purpose. The unit also has experience performing screens and toxicological evaluations in small animal models.

Contact details

High-throughput screens, screen-compatible assays, high-throughput microscopy, libraries, optogenetics, cell-based neurological disease models:

3D oncology models, phenotypic screens, high-content screens:

Medicinal chemistry, virtual screening and molecular modelling:

Assay development, Basic research, Disease models, High throughput imaging, Hit to lead, Lead optimization, Medicinal chemistry, Molecular modelling, R&D Platforms, Screening, Signaling, Target discovery

Research Group:
Bio-Organic Chemistry

Tuomas Lönnberg

Department of Chemistry,
University of Turku

Bioorganic Group

Basic research, Biomolecular chemistry, Diagnostics, Fluorescence spectroscopy, Hit to lead, In Vitro Diagnostics, Lead optimization, NMR, Nucleic acids, Organic Chemistry, Organic compounds, Synthetic chemistry

Research Group:
Structural bioinformatics for drug discovery and development

Mark S. Johnson
finmark54 at icloud dot com

Åbo Akademi University

Ageing-related diseases, Autoimmune diseases, Basic research, Biochemistry, Bioinformatics, Biomolecular chemistry, Biopharmaceuticals, Biotechnology, Cancer, Chemical Physics, Computer Science, Diabetes, Drug target, Hit to lead, Inflammation, Inherited diseases, Lead optimization, Lung cancer, Medicinal chemistry, Metabolic diseases, Molecular modelling, Musculoskeletal disorders, Nucleic acids, Organic compounds, Pattern recognition, Personalized medicine, Physico-chemical properties, Preclinical development, Receptor, Signaling, Structural Biology, Surface area, Target discovery, X-ray crystallography

Research Group:
Systems Molecular Engineering

Jianwei Li[at]

Department of Chemistry,
University of Turku

Atomic-force microscopy, Basic research, Biochemistry, Biomarker, Biomedicine, Biomolecular chemistry, Biotechnology, Cancer, Chemical Physics, Combinatorial chemistry, Drug delivery, Drug target, Electron microscopy, Fluorescence spectroscopy, FTIR or RAMAN spectroscopy, Hit to lead, Imaging, Infection, Inflammation, Lead optimization, Medicinal chemistry, Microstructure analysis, Molecular modelling, Nanoparticles, Natural Compounds, Next-generation sequencing, NMR, Nucleic acids, Organic Chemistry, Organic compounds, Particle size analysis, Physico-chemical properties, Powder X-ray diffraction, Preclinical development, Proteomics, Screening, Structural Biology, Synthetic Biology, Synthetic chemistry, Thermal analysis, X-ray crystallography

Research Group:
Medicinal Chemistry

Olli Pentikäinen

Institute of Biomedicine,
University of Turku

Autoimmune diseases, Basic research, Bioinformatics, Biomedicine, Cancer, Hit to lead, Inflammation, Inherited diseases, Lead optimization, Medicinal chemistry, Molecular modelling, Organic compounds, Pharmacology, Physico-chemical properties, Receptor, Screening, Signaling, Structural Biology, Synthetic chemistry

Research Group:
High Content Screening Laboratory

Matthias Nees (Principal Investigator)

Malin Åkerfelt (Contact person, in picture)

Institute of Biomedicine,
Univesity of Turku


Assay development, Bioinformatics, Biomedicine, Biotechnology, Breast cancer, Cancer, Disease models, Drug target, High throughput imaging, Hit to lead, Imaging, Inflammation, Lead optimization, Lung cancer, Machine learning, Molecular Cell Biology, Natural Compounds, Prostate cancer, Screening, Target discovery