Computational methods and NMR spectroscopy: Tools for improving our understanding of proteins

Computational modeling can be a powerful tool for understanding biochemical systems. When combined with NMR spectroscopy and other techniques, these models can help uncover the structural dynamics of biological functions in disordered proteins, potentially revealing insights that could aid in understanding neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and others.

Kresten Lindorff-Larsen is a professor at SBiNlab at the Department of Biology at the University of Copenhagen. His group focuses on combining computational methods with experimental data to study the structure, function, dynamics and folding of proteins.

Kresten Lindorff-Larsen studied biochemistry at the University of Copenhagen. During this time, he developed a strong interest in biophysics and subsequently wrote his bachelor’s and master’s projects in at the Carlsberg Laboratory under the supervision of Flemming M. Poulsen and Jakob R. Winther. After graduation, Kresten traveled to England to pursue his Ph.D. at University of Cambridge.

At Cambridge, he was introduced to a new research field and worked on a project that involved integrating experimental biophysical data with computer simulations, including NMR spectroscopy. During his time at Cambridge, he collaborated with scientists from various fields, including biochemistry, biophysics, and NMR spectroscopy, giving him a strong interdisciplinary understanding of the scientific world. Among his different contributions at the time, he combined NMR and simulations to study protein dynamics and to provide one of the first structural models of an intrinsically disordered protein.

Following his time in Cambridge, he returned to Copenhagen where he worked as an assistant professor for a few years before embarking on a career change and joined a private research organization called D. E. Shaw Research (DESRES) in New York City. DESRES focuses on developing simulation models for proteins with a goal to improve computational methods to study biology and develop new drugs. In 2011, after a successful scientific period in New York, Kresten returned to Denmark as an associate professor, and has since 2016 been full professor in computational protein biophysics.

A crucial aspect of Kresten’s work involves developing and using computational methods. When analyzing experiments, the measurements often contain a wealth of information about the molecules under study, but extracting this information can be challenging.

In Kresten’s group, computational models serve as a valuable tool for effectively extracting this data in various ways. One common approach that the group uses is to create models of the biomolecules under study; these models integrate our current general understanding of proteins and other molecules and are further refined to be consistent with the experimental measurements. These simulation tools thereby provide molecular interpretations of experimental data and are useful especially when dealing with complex and dynamic systems or multiple measurements from the same system, as this data can be hard to understand otherwise. The simulations then provide valuable insights into protein structure, dynamics, and interactions, and in turn help guide new experiments.

Kresten’s group is unique within the Danish NMR community by the fact that they don’t actively engage in NMR experiments in their own group but only through collaboration with others, who are then responsible for the practical aspects of the experiments. Kresten and his group instead focus on developing and using modeling tools to interpret the results of these collaborations, and together to design the experiments.

Kresten’s group typically consists of around ten to fifteen members at any given time, with some students specializing in developing methods to interpret structural dynamics, others focusing on structural bioinformatics, and some specializing in the study of protein structures and dynamics with a stronger connection to biophysics.

At the moment, we are initiating a new ERC Synergy project where three group members will collaborate closely with an NMR group in Lund and a Crystallography group in Hamburg. Our focus will be on integrating NMR and simulations to gain a better understanding of dynamic processes in proteins.

While their NMR spectroscopy use exclusively involves collaboration with other groups, they do actively develop computational methods to understand NMR data and use NMR data to validate their simulation tools. This involves predicting NMR results through simulations and then running experiments to validate or contradict these predictions, helping to improve their tools for future use.

NMR spectroscopy offers a unique way to study dynamic molecules in solution, providing information on structure, timescales, and dynamics all at once. NMR spectroscopy provides detailed local atomic information and insights into dynamical properties, which few other techniques can offer.

We have especially tried to describe how molecules look in solution and how their structure in solution gives rise to particular functions in the proteins.

Understanding dynamic properties of proteins is essential, as they are often closely related to the biological function, particularly for understanding interactions with other molecules and enzyme functions.

Now AlphaFold and advanced experiments have provided us with a wealth of structural models, we increasingly need to understand how the motions of these molecules affect their functions.

NMR is instrumental in studying various protein dynamics, from local dynamics in globular folded proteins to larger-scale dynamics in different folded domains. Even completely disordered proteins, which appear random, exhibit non-random movements and interactions that can be studied using simulation tools.

Fibril structures are known to be implicated in various neurodegenerative diseases, including Parkinson’s and Alzheimer’s. However, not all fibril proteins are harmful; some have essential functional roles in bacteria and humans.

Kresten and his group have previously studied bacterial amyloids systems. One example is a protein that can help form the cytoskeleton with an amyloid structure. Here, they used NMR data to determine the structure of these cytoskeleton fibril proteins, making use of bioinformatics tools to analyze protein sequences and correlate them with NMR data. This process involves multiple sequence alignments, examining amino acid covariation over evolutionary sequences to determine the global structure of these fibril proteins, which his group then combines with NMR and simulation tools to gain local information about secondary structures.

Our work showed that the simulation method, protein sequence analysis, and NMR data each provided unique and complementary information that enabled us to determine the structure of the amyloid subunit”, says Kresten Lindorff-Larsen.

Kresten has collaborated with various scientists both nationally and internationally. At BIO, he frequently collaborates with the other groups in SBiNlab, combining their expertise in NMR spectroscopy with his own. He has also worked closely with colleagues from the department, including Rasmus Hartmann-Petersen, Amelie Stein, Jakob R. Winther, Martin Willemoës, and Peter Brodersen.

Beyond UCPH, Kresten has collaborated with a group of structural biologists in Aarhus. He has also engaged in other collaborations outside Denmark, including Sweden, Germany, Switzerland, England, and the United States. In many of these he applies his methods to study protein dynamics and combines them with the interests of his collaborators.

In the past, studying disordered proteins was challenging due to their lack of clear structures or dynamics for analysis. With improved techniques including those developed in Kresten’s group, it may soon become possible to design disordered proteins with specific structural properties. This is one of the projects Kresten is currently working on and plans to continue in the future. In another project, the group merges biophysics with genomic studies to understand the mechanisms behind diseases by interpreting the effects of mutations on protein structure, folding, stability, and dynamics.

The new ERC synergy project with Lund and Hamburg involves using NMR spectroscopy and X-ray diffraction methods to investigate the binding of small molecules to proteins. While the initial and final structures of many complexes are well known, the pathway for how a ligand binds and the energetics involved remain poorly understood. To address this, Kresten’s group aims to combine simulations with NMR and crystallography to study the entire protein binding process, although the precision and timescale of their models impose limitations.

Here, NMR provides insights into the equilibrium, thermodynamics, and kinetics, along with general structural information about protein dynamics and molecular interactions. Crystallography offers well-defined structural information, but it lacks dynamical insights. By integrating these methods, the three groups aim to gain a comprehensive understanding of the dynamical processes of ligand binding and the associated dynamical motions in the protein.

I think that we have often been able to apply the newest methods when they become available, even if we have not been a part of the development of them ourselves. We are good at keeping up with international method development and their applications, which I think is very important.

In the area of biomolecular solution NMR, which I am most familiar with, I think we have been good at using NMR when it’s the most appropriate technique, and to combine NMR with other techniques to solve complex biological problems. From my own perspective, it has been fun to combine molecular modelling and simulation tools with NMR data, and I see this kind of integration both at the University of Copenhagen and elsewhere in Denmark.

Computational methods and NMR spectroscopy: Tools for improving our understanding of proteins

Leave a Reply

Your email address will not be published. Required fields are marked *

Scroll to top