We investigate the connection between sequence evolution of the human immunodeficiency virus (HIV) type 1 protease under neutral selection or selective pressure induced by protease inhibitors and the ...functional and molecular-stability characteristics of the molecule in the physical domain. To this end we analyze sequence data on more than 45,000 patients with bioinformatical tools, namely mutual information between residue pairings. In addition we perform extensive computations on the molecular mechanics of the molecule subject to artificial mutations. The changes in the mechanics and dynamics of the molecule in three-dimensional space upon perturbation are then related to the sequence stability as described by the mutual information. We distinguish physical interactions by their evolutionary background and give hints for potential new drug targets. In addition we discuss how such targets can be efficiently chosen to give the HI virus less opportunity to develop resistance towards such drugs while maintaining the protease function at the same time. The interactions between residue no. 28 and 23′ in different chains as well as the interaction between residue no. 92 and 94 within one chain were identified as particular crucial. In addition we find interactions in the
β-sheet-dimerization interface to be important for conserving the protein function and stability while these are at the same time evolutionary conserved — implications of and comparisons to experimental results are finally discussed.
We develop a microeconomical model to investigate the impact of technological change onto production decisions of suppliers-modeling an effective feedback mechanism of the market. An important ...property-the time horizon of production planning-is related to the Kolmogorov entropy of the one-dimensional maps describing price dynamics. We simulate this price dynamics in an ensemble representing the whole macroeconomy. We show how this model can be used to support ongoing research in economic growth and incorporate the obtained microeconomic findings into the discussion about appropriate macroeconomic quantities such as the production function-thus effectively underpinning macroeconomics with microeconomical dynamics. From there we can show that the model exhibits different dynamical regimes (suggesting "phase transitions") with respect to an order parameter. The non-linear feedback under technological change was found to be the crucial mechanism. The implications of the obtained regimes are finally discussed.
Global optimization is one of the key challenges in computational physics as several problems, e.g. protein structure prediction, the low-energy landscape of atomic clusters, detection of community ...structures in networks, or model-parameter fitting can be formulated as global optimization problems. Extremal optimization (EO) has become in recent years one particular, successful approach to the global optimization problem. As with almost all other global optimization approaches, EO is driven by an internal dynamics that depends crucially on one or more parameters. Recently, the existence of an optimal scheme for this internal parameter of EO was proven, so as to maximize the performance of the algorithm. However, this proof was not constructive, that is, one cannot use it to deduce the optimal parameter itself
a priori. In this study we analyze the dynamics of EO for a test problem (spin glasses). Based on the results we propose an online measure of the performance of EO and a way to use this insight to reformulate the EO algorithm in order to construct optimal values of the internal parameter online without any input by the user. This approach will ultimately allow us to make EO parameter free and thus its application in general global optimization problems much more efficient.
Elastic network models in their different flavors have become useful models for the dynamics and functions of biomolecular systems such as proteins and their complexes. Perturbation to the ...interactions occur due to randomized and fixated changes (in molecular evolution) or designed modifications of the protein structures (in bioengineering). These perturbations are modifications in the topology and the strength of the interactions modeled by the elastic network models. We discuss how a naive approach to compute properties for a large number of perturbed structures and interactions by repeated diagonalization can be replaced with an identity found in linear algebra. We argue about the computational complexity and discuss the advantages of the protocol. We apply the proposed algorithm to the acetylcholinesterase, a well-known enzyme in neurobiology, and show how one can gain insight into the “breathing dynamics” of a structural funnel necessary for the function of the protein. The computational speed-up was a 60-fold increase in this example.
β-keto esters are used as precursors for the synthesis of β-amino acids, which are building blocks for some classes of pharmaceuticals. Here we describe the comparison of screening procedures for ...hydrolases to be used for the hydrolysis of β-keto esters, the first step in the preparation of β-amino acids. Two of the tested high throughput screening (HTS) assays depend on coupled enzymatic reactions which detect the alcohol released during ester hydrolysis by luminescence or absorption. The third assay detects the pH shift due to acid formation using an indicator dye. To choose the most efficient approach for screening, we assessed these assays with different statistical methods-namely, the classical Z'-factor, standardized mean difference (SSMD), the Kolmogorov-Smirnov-test, and t-statistics. This revealed that all three assays are suitable for HTS, the pH assay performing best. Based on our data we discuss the explanatory power of different statistical measures. Finally, we successfully employed the pH assay to identify a very fast hydrolase in an enzyme-substrate screening.
The small K+ channel Kcv represents the pore module of complex potassium channels. It was found that its gating can be modified by sensor domains, which are N-terminally coupled to the pore. This ...implies that the short N-terminus of the channel can transmit conformational changes from upstream sensors to the channel gates. To understand the functional role of the N-terminus in the context of the entire channel protein, we apply combinatorial screening of the mechanical coupling and long-range interactions in the Kcv potassium channel by reduced molecular models. The dynamics and mechanical connections in the channel complex show that the N-terminus is indeed mechanically connected to the pore domain. This includes a long rang coupling to the pore and the inner and outer transmembrane domains. Since the latter domains host the two gates of the channel, the data support the hypothesis that mechanical perturbation of the N-terminus can be transmitted to the channel gates. This effect is solely determined by the topology of the channel; sequence details only have an implicit effect on the coarse-grained dynamics via the fold and not through biochemical details at a smaller scale. This observation has important implications for engineering of synthetic channels on the basis of a K+ channel pore.
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•A reduced molecular model uncovers mechanic connections in small K+ channel Kcv.•Cytosolic N-terminus exhibits coupling to pore and transmembrane domains.•Model and experiments show domain in the N-terminus, which is essential for channel function.•The effect is solely determined by channel topology and not by sequence details.
As molecular biology is creating an increasing amount of sequence and structure data, the multitude of software to analyze this data is also rising. Most of the programs are made for a specific task, ...hence the user often needs to combine multiple programs in order to reach a goal. This can make the data processing unhandy, inflexible and even inefficient due to an overhead of read/write operations. Therefore, it is crucial to have a comprehensive, accessible and efficient computational biology framework in a scripting language to overcome these limitations.
We have developed the Python package Biotite: a general computational biology framework, that represents sequence and structure data based on NumPyndarrays. Furthermore the package contains seamless interfaces to biological databases and external software. The source code is freely accessible at https://github.com/biotite-dev/biotite .
Biotite is unifying in two ways: At first it bundles popular tasks in sequence analysis and structural bioinformatics in a consistently structured package. Secondly it adresses two groups of users: novice programmers get an easy access to Biotite due to its simplicity and the comprehensive documentation. On the other hand, advanced users can profit from its high performance and extensibility. They can implement their algorithms upon Biotite, so they can skip writing code for general functionality (like file parsers) and can focus on what their software makes unique.
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