Kristoffer E. Johansson
University of Copenhagen
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Featured researches published by Kristoffer E. Johansson.
BMC Bioinformatics | 2010
Tim Harder; Wouter Boomsma; Martin Paluszewski; Jes Frellsen; Kristoffer E. Johansson; Thomas Hamelryck
BackgroundAccurately covering the conformational space of amino acid side chains is essential for important applications such as protein design, docking and high resolution structure prediction. Today, the most common way to capture this conformational space is through rotamer libraries - discrete collections of side chain conformations derived from experimentally determined protein structures. The discretization can be exploited to efficiently search the conformational space. However, discretizing this naturally continuous space comes at the cost of losing detailed information that is crucial for certain applications. For example, rigorously combining rotamers with physical force fields is associated with numerous problems.ResultsIn this work we present BASILISK: a generative, probabilistic model of the conformational space of side chains that makes it possible to sample in continuous space. In addition, sampling can be conditional upon the proteins detailed backbone conformation, again in continuous space - without involving discretization.ConclusionsA careful analysis of the model and a comparison with various rotamer libraries indicates that the model forms an excellent, fully continuous model of side chain conformational space. We also illustrate how the model can be used for rigorous, unbiased sampling with a physical force field, and how it improves side chain prediction when used as a pseudo-energy term. In conclusion, BASILISK is an important step forward on the way to a rigorous probabilistic description of protein structure in continuous space and in atomic detail.
Journal of Computational Chemistry | 2013
Wouter Boomsma; Jes Frellsen; Tim Harder; Sandro Bottaro; Kristoffer E. Johansson; Pengfei Tian; Kasper Stovgaard; Christian Andreetta; Simon Olsson; Jan B. Valentin; Lubomir D. Antonov; Anders S. Christensen; Mikael Borg; Jan H. Jensen; Kresten Lindorff-Larsen; Jesper Ferkinghoff-Borg; Thomas Hamelryck
We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force‐fields are available within the framework: PROFASI and OPLS‐AA/L, the latter including the generalized Born surface area solvent model. A flexible command‐line and configuration‐file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms.
Journal of Chemical Theory and Computation | 2012
Sandro Bottaro; Wouter Boomsma; Kristoffer E. Johansson; Christian Andreetta; Thomas Hamelryck; Jesper Ferkinghoff-Borg
Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.
Acta Crystallographica Section C-crystal Structure Communications | 2014
Xiaozhou Li; Andrew D. Bond; Kristoffer E. Johansson; Jacco van de Streek
The crystal structure of (Z)-N-(5-ethyl-2,3-dihydro-1,3,4-thiadiazol-2-ylidene)-4-methylbenzenesulfonamide contains an imine tautomer, rather than the previously reported amine tautomer. The tautomers can be distinguished using dispersion-corrected density functional theory calculations and by comparison of calculated and measured 13C solid-state NMR spectra.
Proteins | 2013
Kristoffer E. Johansson; Thomas Hamelryck
Protein structure prediction methods typically use statistical potentials, which rely on statistics derived from a database of know protein structures. In the vast majority of cases, these potentials involve pairwise distances or contacts between amino acids or atoms. Although some potentials beyond pairwise interactions have been described, the formulation of a general multibody potential is seen as intractable due to the perceived limited amount of data. In this article, we show that it is possible to formulate a probabilistic model of higher order interactions in proteins, without arbitrarily limiting the number of contacts. The success of this approach is based on replacing a naive table‐based approach with a simple hierarchical model involving suitable probability distributions and conditional independence assumptions. The model captures the joint probability distribution of an amino acid and its neighbors, local structure and solvent exposure. We show that this model can be used to approximate the conditional probability distribution of an amino acid sequence given a structure using a pseudo‐likelihood approach. We verify the model by decoy recognition and site‐specific amino acid predictions. Our coarse‐grained model is compared to state‐of‐art methods that use full atomic detail. This article illustrates how the use of simple probabilistic models can lead to new opportunities in the treatment of nonlocal interactions in knowledge‐based protein structure prediction and design. Proteins 2013; 81:1340–1350.
Biochemistry | 2016
Casper Højgaard; Christian Kofoed; Roall Espersen; Kristoffer E. Johansson; Mara Villa; Martin Willemoës; Kresten Lindorff-Larsen; Kaare Teilum; Jakob R. Winther
Charges are considered an integral part of protein structure and function, enhancing solubility and providing specificity in molecular interactions. We wished to investigate whether charged amino acids are indeed required for protein biogenesis and whether a protein completely free of titratable side chains can maintain solubility, stability, and function. As a model, we used a cellulose-binding domain from Cellulomonas fimi, which, among proteins of more than 100 amino acids, presently is the least charged in the Protein Data Bank, with a total of only four titratable residues. We find that the protein shows a surprising resilience toward extremes of pH, demonstrating stability and function (cellulose binding) in the pH range from 2 to 11. To ask whether the four charged residues present were required for these properties of this protein, we altered them to nontitratable ones. Remarkably, this chargeless protein is produced reasonably well in Escherichia coli, retains its stable three-dimensional structure, and is still capable of strong cellulose binding. To further deprive this protein of charges, we removed the N-terminal charge by acetylation and studied the protein at pH 2, where the C-terminus is effectively protonated. Under these conditions, the protein retains its function and proved to be both soluble and have a reversible folding-unfolding transition. To the best of our knowledge, this is the first time a soluble, functional protein with no titratable side chains has been produced.
Acta Crystallographica Section B Structural Crystallography and Crystal Chemistry | 2016
Jaroslav Teteruk; Jürgen Glinnemann; Winfried Heyse; Kristoffer E. Johansson; Jacco van de Streek; Martin U. Schmidt
The cis- and trans-isomers of the polycyclic aromatic compound perinone, C26H12N4O2, form a solid solution (Vat Red 14). This solid solution is isotypic to the crystal structures of cis-perinone (Pigment Red 194) and trans-perinone (Pigment Orange 34) and exhibits a combined positional and orientational disorder: In the crystal, each molecular position is occupied by either a cis- or trans-perinone molecule, both of which have two possible molecular orientations. The structure of cis-perinone exhibits a twofold orientational disorder, whereas the structure of trans-perinone is ordered. The crystal structure of the solid solution was determined by single-crystal X-ray analysis. Extensive lattice-energy minimizations with force-field and DFT-D methods were carried out on combinatorially complete sets of ordered models. For the disordered systems, local structures were calculated, including preferred local arrangements, ordering lengths, and probabilities for the arrangement of neighbouring molecules. The superposition of the atomic positions of all energetically favourable calculated models corresponds well with the experimentally determined crystal structures, explaining not only the atomic positions, but also the site occupancies and anisotropic displacement parameters.
Journal of Molecular Biology | 2016
Kristoffer E. Johansson; Nicolai Tidemand Johansen; Signe M.U. Christensen; Scott Horowitz; James C. A. Bardwell; Johan G. Olsen; Martin Willemoës; Kresten Lindorff-Larsen; Jesper Ferkinghoff-Borg; Thomas Hamelryck; Jakob R. Winther
Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations.
Nature Chemical Biology | 2018
Kristoffer E. Johansson; Jakob R. Winther
Early stages of protein evolution are inherently difficult to study. Genetic selection in Escherichia coli has now identified a life-sustaining de novo enzyme arising from a simple scaffold that is completely different from the native enzyme.
Current Opinion in Structural Biology | 2018
Kristoffer E. Johansson; Kresten Lindorff-Larsen
Recent years have witnessed substantial progress in our ability to design proteins with specific structures and to introduce new functionalities into existing protein scaffolds. Such protein design efforts test our understanding of the biophysical and functional mechanisms of naturally evolved proteins. At the same time, we also know that proteins are dynamical entities, and that many proteins rely on detailed dynamical mechanisms for regulation and function. Thus, the success of design methods, especially in relation to functional proteins, might benefit from explicit considerations of conformational heterogeneity and dynamics. In this review, we compare results from the field of protein design with laboratory protein evolution with a focus on dynamics. Recent studies show that structural dynamics is altered during evolutionary trajectories, and that allosteric effects are pronounced. Interaction networks and the resulting coupling of structure and dynamics are suggested to facilitate these effects.