arXiv subjects

Sanne Abeln

Publications and source records attributed to Sanne Abeln.

28 records · Page 2Linked to original sources

arXiv2023

Monte Carlo for Protein Structures

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. In the previous chapter "Molecular Dynamics" we have considered protein simulations from a dynamical point of view, using Newton's laws. In the current Chapter, we first take a step back and return to the bare minimum needed to simulate proteins, and show that proteins may be simulated in a more simple fashion, using the partition function directly. This means we do not have to calculate explicit forces, velocities, moments and do not even consider time explicitly. Instead, we will rely on the fact that for most systems we will want to simulate, the system is in a dynamic equilibrium; and that we want to find the most stable states in such systems by determining the relative stabilities between those states.

q-bio.BM↗

arXiv2021

Structure determination

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. The main emphasis of this work is to provide a background on experimental techniques for protein structure determination. The focus is set on X-ray crystallography and Nuclear Magnetic Resonance spectroscopy (NMR), which are by far the main methods used to determine the structure of soluble proteins. We will also introduce cryogenic Electron Microscopy (cryo-EM) and electron diffraction which are more suited to analyze membrane proteins and larger protein complexes. At the end, more qualitative techniques are summarized that are used to obtain insight on the overall structure and dynamics of proteins. Note that this introduction to protein structure determination aims at familiarizing the reader to different experimental techniques, their benefits and bottlenecks, but that a thorough mathematical and technical description of the concept is beyond the scope of this work.

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arXiv2021

Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language

Computational Workflows are widely used in data analysis, enabling innovation and decision-making. In many domains (bioinformatics, image analysis, & radio astronomy) the analysis components are numerous and written in multiple different computer languages by third parties. However, many competing workflow systems exist, severely limiting portability of such workflows, thereby hindering the transfer of workflows between different systems, between different projects and different settings, leading to vendor lock-ins and limiting their generic re-usability. Here we present the Common Workflow Language (CWL) project which produces free and open standards for describing command-line tool based workflows. The CWL standards provide a common but reduced set of abstractions that are both used in practice and implemented in many popular workflow systems. The CWL language is declarative, which allows expressing computational workflows constructed from diverse software tools, executed each through their command-line interface. Being explicit about the runtime environment and any use of software containers enables portability and reuse. Workflows written according to the CWL standards are a reusable description of that analysis that are runnable on a diverse set of computing environments. These descriptions contain enough information for advanced optimization without additional input from workflow authors. The CWL standards support polylingual workflows, enabling portability and reuse of such workflows, easing for example scholarly publication, fulfilling regulatory requirements, collaboration in/between academic research and industry, while reducing implementation costs. CWL has been taken up by a wide variety of domains, and industries and support has been implemented in many major workflow systems.

cs.DC↗

arXiv2021

How sticky are our proteins? Quantifying hydrophobicity of the human proteome

Proteins tend to bury hydrophobic residues inside their core during the folding process to provide stability to the protein structure and to prevent aggregation. Nevertheless, proteins do expose some 'sticky' hydrophobic residues to the solvent. These residues can play an important functional role, for example in protein-protein and membrane interactions. Here, we investigate how hydrophobic protein surfaces are by providing three measures for surface hydrophobicity: the total hydrophobic surface area, the relative hydrophobic surface area, and - using our MolPatch method - the largest hydrophobic patch. Secondly, we analyse how difficult it is to predict these measures from sequence: by adapting solvent accessibility predictions from NetSurfP2.0, we obtain well-performing prediction methods for the THSA and RHSA, while predicting LHP is more difficult. Finally, we analyse implications of exposed hydrophobic surfaces: we show that hydrophobic proteins typically have low expression, suggesting cells avoid an overabundance of sticky proteins.

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arXiv2019

The hydrophobic effect characterises the thermodynamic signature of amyloid fibril growth

Many proteins have the potential to aggregate into amyloid fibrils, which are associated with a wide range of human disorders including Alzheimer's and Parkinson's disease. In contrast to that of folded proteins, the thermodynamic stability of amyloid fibrils is not well understood: specifically the balance between entropic and enthalpic terms, including the chain entropy and the hydrophobic effect, are poorly characterised. Using simulations of a coarse-grained protein model we delineate the enthalpic and entropic contributions dominating amyloid fibril elongation, predicting a characteristic temperature-dependent enthalpic signature. We confirm this thermodynamic signature by performing calorimetric experiments and a meta-analysis over published data. From these results, we can also elucidate the necessary conditions to observe cold denaturation of amyloid fibrils. Overall, we show that amyloid fibril elongation is associated with a negative heat capacity, the magnitude of which correlates closely with the hydrophobic surface area that is buried upon fibril formation, highlighting the importance of hydrophobicity for fibril stability.

cond-mat.soft↗

arXiv2017

Introduction to Protein Structure Prediction

This chapter gives a graceful introduction to problem of protein three- dimensional structure prediction, and focuses on how to make structural sense out of a single input sequence with unknown structure, the 'query' or 'target' sequence. We give an overview of the different classes of modelling techniques, notably template-based and template free. We also discuss the way in which structural predictions are validated within the global com- munity, and elaborate on the extent to which predicted structures may be trusted and used in practice. Finally we discuss whether the concept of a sin- gle fold pertaining to a protein structure is sustainable given recent insights. In short, we conclude that the general protein three-dimensional structure prediction problem remains unsolved, especially if we desire quantitative predictions. However, if a homologous structural template is available in the PDB model or reasonable to high accuracy may be generated.

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arXiv2017

Strategies for protein structure model generation

This chapter deals with approaches for protein three-dimensional structure prediction, starting out from a single input sequence with unknown struc- ture, the 'query' or 'target' sequence. Both template based and template free modelling techniques are treated, and how resulting structural models may be selected and refined. We give a concrete flowchart for how to de- cide which modelling strategy is best suited in particular circumstances, and which steps need to be taken in each strategy. Notably, the ability to locate a suitable structural template by homology or fold recognition is crucial; without this models will be of low quality at best. With a template avail- able, the quality of the query-template alignment crucially determines the model quality. We also discuss how other, courser, experimental data may be incorporated in the modelling process to alleviate the problem of missing template structures. Finally, we discuss measures to predict the quality of models generated.

q-bio.BM↗

arXiv2015

Consistent treatment of hydrophobicity in protein lattice models accounts for cold denaturation

The hydrophobic effect stabilizes the native structure of proteins by minimizing the unfavourable interactions between hydrophobic residues and water through the formation of a hydrophobic core. Here we include the entropic and enthalpic contributions of the hydrophobic effect explicitly in an implicit solvent model. This allows us to capture two important effects: a length-scale dependence and a temperature dependence for the solvation of a hydrophobic particle. This consistent treatment of the hydrophobic effect explains cold denaturation and heat capacity measurements of solvated proteins.

cond-mat.soft↗

arXiv2015

The competition between surface adsorption and folding of fibril-forming polypeptides

Self-assembly of polypeptides into fibrillar structures can be initiated by planar surfaces that interact favorably with certain residues. Using a coarse grained model, we systematically studied the folding and adsorption behavior of a $β$-roll forming polypeptide. We find that there are two different folding pathways depending on the temperature: (i) at low temperature, the polypeptide folds in solution into a $β$-roll before adsorbing onto the attractive surface, (ii) at higher temperature, the polypeptide first adsorbs in a disordered state, and folds while on the surface. The folding temperature increases with increasing attraction, as the folded $β$-roll is stabilized by the surface. Surprisingly, further increasing the attraction lowers the folding temperature again, as strong attraction also stabilizes the adsorbed disordered state, which competes with folding of the polypeptide. Our results suggest that to enhance the folding, one should use a weakly attractive surface. They also explain the recent experimental observation of the non-monotonic effect of charge on the fibril formation on an oppositely charged surface [C. Charbonneau, et al., ACS Nano, 8, 2328 (2014)].

cond-mat.soft↗

arXiv2013

Interplay between folding and assembly of fibril-forming polypeptides

Polypeptides can self-assemble into hierarchically organized fibrils consisting of a stack of individually folded polypeptides driven together by hydrophobic interaction. Using a coarse grained model, we systematically studied this self-assembly as a function of temperature and hydrophobicity of the residues on the outside of the building block. We find the self-assembly can occur via two different pathways - a random aggregation-folding route, and a templated-folding process - thus indicating a strong coupling between folding and assembly. The simulation results can explain experimental evidence that assembly through stacking of folded building blocks is rarely observed, at the experimental concentrations. The model thus provides a generic picture of hierarchical fibril formation.

cond-mat.soft↗