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Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules. In the past, such representations were utilized to compare protein structures on global and local scales and have shed light on functional properties of proteins. Here we describe RosettaSurf, a surface-centric computational design protocol, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering, offering a unique approach for the design of proteins and their functions. The RosettaSurf protocol combines the explicit optimization of molecular surface features with a global scoring function during the sequence design process, diverging from the typical design approaches that rely solely on an energy scoring function. With this computational approach, we attempt to address a fundamental problem in protein design related to the design of functional sites in proteins, even when structurally similar templates are absent in the characterized structural repertoire. Surface-centric design exploits the premise that molecular surfaces are, to a certain extent, independent of the underlying sequence and backbone configuration, meaning that different sequences in different proteins may present similar surfaces. We benchmarked RosettaSurf on various sequence recovery datasets and showcased its design capabilities by generating epitope mimics that were biochemically validated. Overall, our results indicate that the explicit optimization of surface features may lead to new routes for the design of functional proteins.

Objective: This article includes the examination of potential methodological problems of the application of a forced choice response format in facial emotion recognition. Methodology: 33 subjects were presented with validated facial stimuli. The task was to make a decision about which emotion was shown. In addition, the subjective certainty concerning the decision was recorded. Results: The detection rates are 68% for fear, 81% for sadness, 85% for anger, 87% for surprise, 88% for disgust, and 94% for happiness, and are thus well above the random probability. Conclusion: This study refutes the concern that the use of forced choice formats may not adequately reflect actual recognition performance. The use of standardized tests to examine emotion recognition ability leads to valid results and can be used in different contexts. For example, the images presented here appear suitable for diagnosing deficits in emotion recognition in the context of psychological disorders and for mapping treatment progress., GMS Psycho-Social-Medicine; 10:Doc04; ISSN 1860-5214

As the flowing pressure in a condensate well declines below dew-point pressure a radial zone develops around the wellbore with decreasing condensate liquid saturation, which reduces the permeability to gas, i.e. well productivity. The well productivity impairment is a function of the magnitude of a two-phase zone, retrograde condensate saturation and gas-condensate relative permeability, which in turn depend on the composition and p, T-behavior of a particular gas-condensate system. Realistic calculation of gas condensate well productivity in a two-phase flow region requires that experimental fluid phase behavior and phase flow data are known. In this work, laboratory techniques and methods for determination of the effective gas permeability vs retrograde liquid saturation and relative permeability data are presented. Additional lab procedures, required to obtain a full suite of relative permeability data necessary for accurate well productivity prediction by mathematical modeling are discussed.

Proteins are fundamental components in biological systems and crucial for a variety of biological functions. Over the last decades, significant progress in structural biology has facilitated the study of proteins and their interactions with molecular partners, shedding light on the relationship between protein structure and function. Progressing beyond the natural protein repertoire, the development of computational methods has enabled the design of novel proteins, primarily focusing on defined structural and biophysical properties. However, consistently introducing new functions into proteins has remained an ambitious challenge. Continuous refinement of computational design methods may prove key to solve emerging biomedical needs. One major challenge where functional protein design could have profound impact is the development of improved vaccines for pathogens that have resisted current vaccine development strategies. Among these pathogens are the influenza and hepatitis C virus (HCV) that cause severe morbidity and mortality across the population. In recent years, several broadly protective antibodies targeting conserved antigenic sites have been isolated and the structural characterization in complex with their cognate epitopes has revealed the structural aspects of these interactions. Computational design of tailor-made immunogens could be an effective tool in inducing a robust neutralizing antibody response against these key antigenic sites. To address these problems, my thesis work introduces a novel surface-centric computational design approach, that focuses on the molecular surface shape and electrostatic properties as means for protein engineering. The surface-centric design approach presents a general framework to design proteins that mimic functional sites, including complex structural motifs characterized by irregular or discontinuous segments. Beyond the design of potent immunogens mimicking epitopes, the protocol allows computational screening for highly specific protein binders and together provide potentially new routes for the design of functional proteins through the optimization of surface features. Building upon the introduced design concepts, my work demonstrates for the first time the successful design of influenza epitope mimetics derived from heterologous protein scaffolds for a conserved, structurally complex antigenic site. The designed immunogens elicited subtype cross-reactive antibodies in vivo and a preliminary study suggests protection of mice from lethal viral infection. Additionally, engineered epitope-specific immunogens for HCV conferred significant cross-neutralization activity against a panel of different HCV genotypes displaying varying neutralization resistance. Diverging from traditional vaccine design approaches, these results provide a general roadmap to engineer novel immunogens eliciting a focused immune response for other pathogens. Overall, the work presented in this thesis introduces a versatile protein design approach for the development of sophisticated functional proteins and showcases the design of precision immunogens. The development of functional proteins could be transformative to solve biomedical questions including not only the design of novel immunogens but also protein components for synthetic biology or other protein-based biotechnologies.

Anti-CRISPR (Acr) proteins are powerful tools to control CRISPR-Cas technologies. However, the available Acr repertoire is limited to naturally occurring variants. Here, we applied structure-based design on AcrIIC1, a broad-spectrum CRISPR-Cas9 inhibitor, to improve its efficacy on different targets. We first show that inserting exogenous protein domains into a selected AcrIIC1 surface site dramatically enhances inhibition of Neisseria meningitidis (Nme)Cas9. Then, applying structure-guided design to the Cas9-binding surface, we converted AcrIIC1 into AcrIIC1X, a potent inhibitor of the Staphylococcus aureus (Sau)Cas9, an orthologue widely applied for in vivo genome editing. Finally, to demonstrate the utility of AcrIIC1X for genome engineering applications, we implemented a hepatocyte-specific SauCas9 ON-switch by placing AcrIIC1X expression under regulation of microRNA-122. Our work introduces designer Acrs as important biotechnological tools and provides an innovative strategy to safeguard CRISPR technologies.