TY - JOUR A1 - Emonts, Jessica A1 - Buyel, Johannes Felix T1 - An overview of descriptors to capture protein properties – Tools and perspectives in the context of QSAR modeling JF - Computational and Structural Biotechnology Journal N2 - Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative. KW - Prediction of molecular features KW - Protein structure complexity KW - Quantitative structure activity relationship KW - Scalar parameters KW - Shape and surface properties Y1 - 2023 U6 - https://doi.org/10.1016/j.csbj.2023.05.022 SN - 2001-0370 (online-ressource) IS - 21 SP - 3234 EP - 3247 PB - Research Network of Computational and Structural Biotechnology CY - Gotenburg ER - TY - JOUR A1 - Eichler, Fabian A1 - Balc, Nicolae A1 - Bremen, Sebastian A1 - Nink, Philipp T1 - Investigation of laser powder bed fusion parameters with respect to their influence on the thermal conductivity of 316L samples JF - Journal of Manufacturing and Materials Processing N2 - The thermal conductivity of components manufactured using Laser Powder Bed Fusion (LPBF), also called Selective Laser Melting (SLM), plays an important role in their processing. Not only does a reduced thermal conductivity cause residual stresses during the process, but it also makes subsequent processes such as the welding of LPBF components more difficult. This article uses 316L stainless steel samples to investigate whether and to what extent the thermal conductivity of specimens can be influenced by different LPBF parameters. To this end, samples are set up using different parameters, orientations, and powder conditions and measured by a heat flow meter using stationary analysis. The heat flow meter set-up used in this study achieves good reproducibility and high measurement accuracy, so that comparative measurements between the various LPBF influencing factors to be tested are possible. In summary, the series of measurements show that the residual porosity of the components has the greatest influence on conductivity. The degradation of the powder due to increased recycling also appears to be detectable. The build-up direction shows no detectable effect in the measurement series. KW - Additive manufacturing KW - LPBF KW - SLM KW - Thermal conductivity KW - 316L Y1 - 2024 U6 - https://doi.org/10.3390/jmmp8040166 SN - 2504-4494 N1 - Corresponding author: Fabian Eichler VL - 8 IS - 4 PB - MDPI CY - Basel ER -