We conduct problem-oriented computational research, i.e. we select the most suitable methods to solve scientific questions. We also develop our own computational tools. Recurrent scientific questions are related to ligand binding and ligand design, and to protein sequence-structure-function relationships and molecular evolution. Our expertise covers many aspects of chemoinformatics (databases, QSAR and machine learning, ligand-based approaches) as well as molecular modeling (modeling and docking simulations, virtual screens, ligand optimization). Our ligand discovery projects are conducted in collaboration with a network of experimentalists: pharmacologists and molecular biologists, medicinal chemists, structural biologists. We have a long expertise in modeling membrane proteins (GPCRs, ABC and monoamine transporters, membrane-bound pyrophosphatases). In recent years we have lead projects involving data mining and analysis, in particular machine learning and deep-learning technologies. Our expertise encompasses chemogenomic drug-target networks, genomic data, and structural data on protein-ligand complexes (see here and here).
A selection of projects is presented below.
G protein-coupled receptors belong to a superfamily (about 800 in human) of key signaling molecules, many of which are target for therapeutic intervention. Yet, how ligand binding may triggers signaling responses and what is the scope of their interactome is far from being understood. Our key interests are tied to understanding the similarities and differences in binding and activation across receptors and ligands. In order to do so, we strive to build accurate three-dimensional models of molecular complexes across pharmacological relevant conformations. We have a long experience with these receptors (first work of PI with GPCRs in 1998), in particular the amine family (see Xhaard et al. J. Med Chem. 2006) and the orexin receptors from the peptide family. We are members of COST action ERNEST CA18133.
Protozoan parasites are major causes of morbidity and mortality across the world, and new specific therapies are greatly needed. Several of them are classified as “neglected diseases” by WHO. They also cause health problems in developed countries: Toxoplasma causes congenital toxoplasmosis and infections in immunosuppressed individuals. Membrane-bound pyrophosphatases, large (15-17 transmembrane segments) with no human homologues are essential in such parasites and as such represent a novel potential target. The group of A. Goldman recently showed that mPPases have a unique structure (Kellosalo et al., 2012). The aim of this proposal is to develop substrate mimic inhibitors. In addition, we aim to discover another class of compounds that act on a different conformation of the mPPases, collapsing ionic gradients and thereby killing effectively the cells. State of art computational methods will be used in synergy with experimental components, X-ray crystallography, medicinal chemistry, and biophysical methods.
This project is funded by the Finnish Academy (2017-2021) and by the jane and Aatos Erkko foundation (2015-2018).
We have now discovered several classes of inhibitors of the test system thermosensible mPPase Thermotoga maritima and are working to translate the compound and assay to pathogenic mPPases. One X-ray structure has been published (PDB code 6QXA, Vidilaseris et al., Science Advances, 2019).
Our goal is to derive a knowledge-based scoring function for bound ligands that can be used for pose generation, pose selection, and affinity prediction. Different types of tracks are followed in parallel, such as scoring the fit atoms within protein-ligand complexes (protein, ligand, water, metals), scoring molecular fragments, and associating chemogenomic data (compound and structural changes along series, target, affinities) to the scores. Currently, we are working on different molecular representations in particular based on graphs. Unlike (our) previous work based on scripts, we now take advantage of organized data structures such as databases. We essentially use PDB data and affinities extracted from chemogenomic databases.
The Drug Discovery and Chemical Biology (DDCB) Consortium is a Biocenter Finland -funded national research infrastructure for academic researchers in Finland.
DDCB coordinates infrastructure and expertise in the areas of drug discovery and chemical biology, and makes it available to the scientific community. It is formed by Institute for Molecular Medicine Finland (University of Helsinki, UH), Biocenter Kuopio (University of Eastern Finland, UEF), Faculty of Pharmacy at the University of Helsinki, BioCity Turku (University of Turku and Åbo Academy University) and CSC – IT Center for Science. The principal investigator of the DDCB consortium is Dr. Päivi Tammela (UH).
In 2017, DDCB services were used by 134 research groups, of which 9 were non-academic.
Several new technologies have been utilized, and DDCB has participated actively in European activities such as EU-OPENSCREEN.
Central to our work is the data mining services: the IDAAPM database, freely accessible at http://idaapm.helsinki.fi see Legehar et al., J Chemoinf., 2016
Collaborative work expert data handling and mining. See Cortes et al., Oncogene, 2018
The environmental impacts of pharmaceuticals are a growing global problem. Whilst societies become increasingly urbanized and the world population grows in size and age, the use of pharmaceuticals and thus the chemical burden upon the environment increases. Emissions are produced throughout a pharmaceutical’s life cycle, from development to production, consumption and disposal.
SUDDEN, short for Sustainable Drug Discovery and Development with End-of-Life Yield, is a research project that aims at reducing the environmental hazards related to the life cycle of pharmaceuticals. The project’s other objective is to enhance the sustainability of the pharmaceutical industry. We wish to create possibilities for sustainable growth by solving environmental issues related to the life cycle of pharmaceuticals. Moreover, SUDDEN will develop tools, solutions and policy recommendations which will create possibilities for sustainable growth by solving environmental issues in the life-cycle of a pharmaceutical.
SUDDEN is funded by the Strategic Research Council of the Academy of Finland from 2018 to 2021 and from 2022 to 2023. The project is carried out by the University of Helsinki, University of Eastern Finland, Lappeenranta-Lahti University of Technology LUT, Aalto University, Finnish Environment Institute and Demos Helsinki.
Understanding chronic pain and new druggable targets: Focus on glial-opioid receptor interface
GLORIA was an international, cross-disciplinary collaborative project funded by the Framework Programme Seven of the European Union. Researchers from five European partner sites are working together to unravel the role of glial activation and neuroinflammation in chronic pain conditions such as neuropathic pain, osteoarthritis and fibromyalgia.
Work programme topic: FP7‐HEALTH‐2013‐INNOVATION‐1
Project number: 602919
Project started: October 1, 2013
Duration: 60 months
Coordinator: Professor Eija Kalso, University of Helsinki
3i Regeneration
The 3iRegeneration project wa led by Professor Heikki Ruskoaho from the Faculty of Pharmacy, University of Helsinki. The project has received funding from TEKES (€4,8M 2014-2016; €11,9M total budget, 2014-2018), as part of a large strategic opening. The vision of the project is to enhance regeneration by induction of new cells locally in the heart and brain by innovative pharmaceuticals and drug delivery systems. The partners of this radical and challenging Large Strategic Opening are the University of Helsinki, Aalto University and Helsinki University Central Hospital, combining expertise in areas of life sciences, chemistry, physics, engineering sciences and medicine in an innovative fashion.