Protein-nanoparticle interactions: the effects of surface compositional and structural heterogeneity are scale dependent

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Optical tweezers are devices that can manipulate nano- and microparticles using a laser. The principle of optical tweezers is to apply a force to an object using the momentum of light. This force is very small, but it is sufficient to move things in the mi ...

BackgroundAging in postmitotic tissues is associated with clonal expansion of somatic mitochondrial deletions, the origin of which is not well understood. Such deletions are often flanked by direct nucleotide repeats, but this alone does not fully explain ...

Solving native structures of such large molecules, like biomolecules, is often challenging, particularly due to the potentially infinite number of non-covalent interactions with water. In this thesis, we report the use of cold ion gas-phase action spectros ...

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the prot ...

Engineering protein biosensors that sensitively respond to specific biomolecules by triggering precise cellular responses is a major goal of diagnostics and synthetic cell biology. Previous biosensor designs have largely relied on binding structurally well ...

Proteins control nearly every facet of life on a molecular level. Proteins are formed from linear strings of amino acids, which fold into three-dimensional structures that can enact functions. Evolution has created highly efficient proteins in diverse fold ...

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

In this thesis, we discuss the problems of scattering and optical manipulation related to nanosystems of different complexities. The multipolar decomposition method is used to represent scattering processes in nanosystems as a series of elementary excitati ...

With DNA-based nanomaterials being designed for applicationsincellular environments, the need arises to accurately understand theirsurface interactions toward biological targets. As for any materialexposed to protein-rich cell culture conditions, a protein ...

Supported Co-based catalysts exhibit promising catalytic activities in the oxygen evolution reaction (OER) during alkaline water electrolysis. Surface functionalization of the support modulates the dispersion of the catalysts and their interaction with the ...

De novo protein design enhances our understanding of the principles that govern protein folding and interactions, and has the potential to revolutionize biotechnology through the engineering of novel protein functionalities. Despite recent progress in comp ...

Protein-nanoparticle interactions: the effects of surface compositional and structural heterogeneity are scale dependent

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Optical manipulation of plasmonic nanoparticles: Applications in surface chemistry and nano-optics

Secondary structure of the human mitochondrial genome affects formation of deletions

Bridging Native and Intrinsic Structures of Microhydrated Biomolecules by Cold Ion Spectroscopy

Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy

Computational design of dynamic receptor—peptide signaling complexes applied to chemotaxis

De novo designed proteins: a study in engineering novel folds and functions

A new age in protein design empowered by deep learning

Frequency and time domains interactions in nanophotonics

Stabilizing Polymer Coatings Alter the Protein Corona of DNA Origami and Can Be Engineered to Bias the Cellular Uptake

Understanding the role of surface oxygen-containing functional groups on carbon-supported cobalt catalysts for the oxygen evolution reaction

De novo protein design by inversion of the AlphaFold structure prediction network