Computational Chemistry and Biochemistry Group

We use computer simulations to better understand how biologically-relevant and other interesting molecules behave. By using computer modelling and simulations we can get a better understanding of complex diseases, such as cancer.

Our research

The motion of atoms is a key aspect of life as we know it. Everything moves in our bodies – from water that comprise most of our body weight to neuronal signals that are carried to the brain. Understanding biology and chemistry therefore goes far beyond the comprehension of a static state. Experiments can capture many aspects of motion, but computer simulations are often needed to fill in the gaps, where the system under study is too small or too dynamic.

Computer simulations enable us to generate atomistic movies, and lead to new hypotheses that can often be examined by experiments at a later stage. This demands powerful computers and modern software – but a creative mind and interest in physical chemistry and biochemistry are even more important.

Our main interests are: 

  1. Interactions between metal ions and biomolecules or drug molecules
  2. Modelling of biologically relevant dynamic processes, particularly those related to cancer
  3. Applying theoretical, physical-chemistry based methods to biology and chemistry

Computer simulations in cancer research 

Biological networks associated to diseases are studied by numerical simulation using dynamical systems and control analysis. Principles of physical biochemistry and enzyme kinetics are employed to represent signalling networks mathematically focussing on experimentally accessible aspects for therapeutic intervention.The generality of the approach allows applications of our mathematical models to study mechanisms of cancer resistance as well as gene regulation in microbial populations.

Drug resistance against targeted cancer therapy

Beginning in 2001, some cancer patients receive targeted therapy – drugs that are prescribed to inhibit aberrant behaviour of proteins that promote the disease, rather than traditional chemotherapy that systematically destroys dividing cells. Unfortunately, many of these patients eventually become insensitive to such targeted treatment because the tumour cells develop drug resistance through mutations of the proteins that make the drug targets. The mutant proteins are able to avoid binding the inhibitor while maintaining the function that is important for tumour growth. We used various computational methods to study such mutations.

Interactions between metal ions and proteins

Ions are indespensable for life. Many of the essential nutrients are in fact metal ions. Yet, many aspects of the interactions between ions and living matter continue to elude us. Whereas it is possible to use spectroscopic measurements to gain knowledge on the structure of proteins bound to ions, the small size of the metal ions make it cumbersome to follow the process of metal-binding by experiments.

Computer simulations can be useful in this respect, owing to their ability to follow processes in femtosecond to microsecond time scales and atomic resolution. The main objective is to develop parameters that would allow the calculation of the interaction of metal ions and proteins at the same speed but better accuracy then available today.

Passive transport of drugs across membranes

In order for drug molecules to reach their molecular targets they must typically be transported across lipid bilayer membrane barriers. Detailed computational studies of such processes will lead to a detailed understanding about the kinetics and thermodynamics involved in cellular transport and help us to understand and predict bioavailability of drugs. Knowledge about factors influencing bioavailability can then be used to develop better drugs as well as novel strategies for drug-delivery.

Methods that we employ include:

  • Molecular dynamics simulations
  • Quantum chemistry – DFT, geometry optimisation, atomistic simulations with QM potentials
  • Stochastic simulations (model-based)

Recent findings

  • Resistance to drugs is often due to mutations in the proteins that bind the drugs. How do mutations lead to drug resistance? One clear mechanism is when a mutation makes the protein unable to bind the drug, but often this is not the case. A study from our lab showed that there are mutations that actually make the target protein more efficient in what it does [1]. In another case, computer simulations suggested that the reason for resistance is stabilisation of an active form of the protein to which the drug binds. [2]
  • Combination therapy, where two or more drugs are combined in order to attack the disease from different angles is commonplace in treatment of cancers and infectious diseases. In cancers, it is often difficult to estimate what sort of combination therapy will be useful for a given patient. Using computer simulations of interactions networks, we have studied the pros and cons of different combination therapies in two different cancers, and highlighted the proteins whose expression may lead to the success – or failure – of such therapies. [3,4]
  • Protein-ion interactions are often studied by calculations, but how accurate are these calculations, and what can be done to improve them? This was studied by us focusing on Zn [5] and alkali cations [6]. The results showed that it may be possible to simulate the dynamics of Zn ions in proteins by the use of a polarisable force-field, and suggested some practices to achieve reasonable results for alkali cations.



  • Understanding the sensitivity and resistance to targeted therapies in cancer
  • Evolutionary aspects of drug resistance in cancers
  • Quantum chemical calculations of protein-drug interactions
  • Simulations of macromolecule-ion interactions





  • Felipe Luis Pineda de Castro, PhD, former Post-doc – left for a position as a senior computational chemist at the University of Gdańsk, Poland
  • Olga Becconi, former Master student
  • Stella H Maganhi, former Post-doc – currently at the Federal University of São Carlos, Brazil

About us

The Computational Chemistry and Biochemistry Group (CCBG) is part of the Department of Chemistry and Biomedical Sciences and the Linnæus University Centre of Excellence (LNUC) for Biomaterials Chemistry. We work in Kalmar, a small and beautiful Swedish town with rich history, that was one of the most important cities in Scandinavia some 700 years ago. Today, Kalmar is a lively university town, and the nearby area is great for recreational activity (and boasts very beautiful scenery and beaches).

Our research is funded by the university (through the LNUC Biomaterials Chemistry), the Crafoord Foundation, the Royal Swedish Academy of Sciences, the Carl Tryggers Foundation and the Holcim Foundation (Switzerland). Further support comes from the Swedish National Infrastructure for Computing (SNIC), through which we obtain excellent computational resources. This allow us to carry out routine molecular dynamics simulations using multiple processes and quantum-chemical calculations using the computer program GAMESS where we employ up to 2,000 processors.

The personnel costs in Sweden are very high. Thus, in spite of the very generous funding received along the years, we are usually not able to accept any co-workers unless they come with (or are willing to obtain) their own funding. Such funding may come from national organisations (e.g., the SNSF in Switzerland), international organisations such as EMBO or FEBS, or the Swedish Institute. Excellent, hard-working and creative individuals who are looking for a PhD or Post-doc position within the group are however welcome to contact us. If you decide to submit an unsolicited job application, please make sure that you explain why would you like to work with us and include your CV and research interests. If we identify a potential funding source we will be happy to help you with the application.

You're welcome to browse this page for details on our past and present studies. Should you have any questions or comments, please contact us using the contact cards on the page. Thank you for your interest!