Trajectory maps: molecular dynamics visualization and analysis

Comparison of two peroxidases with high potential for biotechnology applications - HRP vs. APEX2

Peroxidases are essential elements in many biotechnological applications. An especially interesting concept involves split enzymes, where the enzyme is separated into two smaller and inactive proteins that can dimerize into a fully active enzyme. Such split forms were developed for the horseradish peroxidase (HRP) and ascorbate peroxidase (APX) already. Both peroxidases have a high potential for biotechnology applications. In the present study, we performed biophysical comparisons of these two peroxidases and their split analogues. The active site availability is similar for all four structures. The split enzymes are comparable in stability with their native analogues, meaning that they can be used for further biotechnology applications. Also, the tertiary structures of the two peroxidases are similar. However, differences that might help in choosing one system over another for biotechnology applications were noticed. The main difference between the two systems is glycosylation which is not present in the case of APX/sAPEX2, while it has a high impact on the HRP/sHRP stability. Further differences are calcium ions and cysteine bridges that are present only in the case of HRP/sHRP. Finally, computational results identified sAPEX2 as the systems with the smallest structural variations during molecular dynamics simulations showing its dominant stability comparing to other simulated proteins. Taken all together, the sAPEX2 system has a high potential for biotechnological applications due to the lack of glycans and cysteines, as well as due to high stability.

Unraveling the Membrane Topology of TMEM151A: A Step Towards Understanding its Cellular Role

Transmembrane protein 151A (TMEM151A) has been identified as a causative gene for paroxysmal kinesigenic dyskinesia, though its molecular function remains almost completely unknown. Understanding the membrane topology of transmembrane proteins is crucial for elucidating their functions and possible interacting partners. In this study, we utilized molecular dynamics simulations, immunocytochemistry, and electron microscopy to define the topology of TMEM151A. Our results validate a starting AlphaFold model of TMEM151A and reveal that it comprises a transmembrane domain with two membrane-spanning alpha helices connected by a short extracellular loop and an intramembrane helix-hinge-helix structure. Notably, most of the protein is oriented towards the intracellular side of the membranes with a large cytosolic domain featuring a combination of alpha-helix and beta-sheet structures, as well as the protein N- and C-termini. These insights into TMEM151A's topology and orientation of its domains with respect of the cell membranes provide essential information for future functional studies and represent a first fundamental step for understanding its role in the pathogenesis of paroxysmal kinesigenic dyskinesia.

In-silico characterization of a hypothetical protein of Sulfobacillus sp. hq2 for degradation of phthalate diesters

Phthalate plasticizers are hazardous compounds capable of causing endocrine disruption, cancers, and developmental disorders. Phthalate diesters are commonly used plasticizers in plastic products (PVC pipes) that leach out into the environment due to changes in temperature, pressure, and pH, posing harmful effects on different life forms. Bioremediation of phthalate diesters utilizing bacterial esterase has been recognized as an efficient approach but few effective esterases capable of degrading a wide range of phthalate diesters have been identified. Further, the thermostability of these esterases is a highly desirable property for their applications in diverse in-situ conditions. In this present in-silico study a hypothetical protein (POB10642.1) as a high-potential esterase from a thermostable strain of Sulfobacillus sp. hq2 has been characterized. Analysis revealed a significant sequence identity of 42.67 % and structural similarity (RMSD 0.557) with known phthalate diester degrading EstS1 esterase and a high Tm range of 55-66 °C. Structural analysis revealed the presence of two cavities on the surface mediating toward the catalytic site forming a catalytic tunnel. The enzyme POB10642.1 has significant molecular docking binding energies in the range of -5.4 to -7.5 kcal/mol with several phthalate diesters, including Diethyl phthalate, Dipropyl phthalate, Dibutyl phthalate, Dipentyl phthalate, Dihexyl phthalate, Benzyl butyl phthalate, Dicyclohexyl phthalate, and Bis(2-ethylhexyl) phthalate. High stability of binding during 100 ns molecular dynamics simulations revealed efficient and stable binding of the enzyme with a wide range of phthalate diesters at its active site, demonstrating the ability of the identified esterase to interact with and degrade diverse phthalate diesters. Therefore, POB10642.1 esterase can be an efficient candidate to be utilized in the development of enzyme-based bioremediation technologies to reduce the toxic levels of phthalate diesters.

MDavocado: Analysis and Visualization of Protein Motion by Time-Dependent Angular Diagrams

Extracting meaningful information from atomistic molecular dynamics (MD) simulations of proteins remains a challenging task due to the high-dimensionality and complexity of the data. MD simulations yield trajectories that contain the positions of thousands of atoms in millions of steps. Gaining a comprehensive understanding of local dynamical events across the entire trajectory is often difficult. Here, we present a novel approach to visualize MD trajectories in the form of time-dependent Ramachandran plots. Specialized data aggregation techniques are employed to address the challenge of plotting millions of data points on a single image, thereby ensuring that the analysis is independent of the molecule size and/or length of the MD simulation. This approach facilitates quick identification of flexible and dynamic regions, and its strength is the ability to simultaneously observe the movements of all amino acids over time. The Python program MDavocado is freely available at GitHub (https://github.com/zoranstefanic/MDavocado).

Innovative tree-based method for sampling molecular conformations: exploring the ATP-binding cassette subfamily D member 1 (ABCD1) transporter as a case study

We introduce a novel tree-based method for visualizing molecular conformation sampling. Our method offers enhanced precision in highlighting conformational differences and facilitates the observation of local minimas within proteins fold space. The projection of empirical laboratory data on the tree allows us to create a link between protein conformations and disease relevant data. To demonstrate the efficacy of our approach, we applied it to the ATP-binding cassette subfamily D member 1 (ABCD1) transporter responsible for very long-chain fatty acids (VLCFAs) import into peroxisomes. The genetic disorder called X-linked adrenoleukodystrophy (XALD) is characterized by the accumulation of VLCFA due to pathogenic variants in the ABCD1 gene. Using in silico molecular simulation, we examined the behavior of 16 prevalent mutations alongside the wild-type protein, exploring both inward and outward open forms of the transporter through molecular simulations. We evaluated from resulting trajectories the energy potential related to the ABCD1 interactions with ATP molecules. We categorized XALD patients based on the severity and progression of their disease, providing a unique clinical perspective. By integrating this data into our numerical framework, our study aimed to uncover the molecular underpinnings of XALD, offering new insights into disease progression. As we explored molecular trajectories and conformations resulting from our study, the tree-based method not only contributes valuable insights into XALD but also lays a solid foundation for forthcoming drug design studies. We advocate for the broader adoption of our innovative approach, proposing it as a valuable tool for researchers engaged in molecular simulation studies.