Reprogramming the B1 Domain of Streptococcal Protein G (GB1)

Nature has the ability to cope with extreme pH, temperature and pressure, in addition to bestowing a wide array of functionalities to (bio)macromolecules. These specialized skills have attracted the interest of vast scientific communities especially in view of possible industrial or biomedical applications. In general, the design of functional and thermostable biological constructs is one of the overarching themes in biochemisty. Despite extensive research and some recent breakthroughs, the level of understanding of the factors that determine protein reactivity and stability is still modest. The use of computational methods for an atomic level understanding of the functionality and stability of biomacromolecules is therefore an attractive alternative. This dissertation presents a number of research projects that combine different computational methods in a close blend with experiments in order to identify the crucial determinants that can be used for a rational design of thermostable and catalytically active, (re-)engineered protein domains. The main findings are the following: Chapter 3 of the thesis presents the results of computational studies towards the design of biomimetic compounds capable of performing tetrazole formation based on Lewis acid catalysis. Our quantum chemical calculations suggest the incorporation of unnatural modifications of glutamate residues as a promising starting point for the development of an efficacious bioinspired catalytic system based on a zinc active site. Chapter 4 and 5 focuses on the computational design and re-engineering of the B1 domain of Streptococcal protein G (GB1) to introduce hydrolytic activity. In addition to exhibiting encouraging reaction rates, our computationally designed artificial enzymes are reasonably thermostable. Chapter 6 is about the design of a highly thermostable metallo variant of GB1. It describes the successful attempt to establish a stable tetrahedral zinc binding site in GB1 with the help of a computational protocol based on genetic algorithm optimization. A high resolution crystal structure of this metallo variant reveals a novel head-to-tail organization. Chapter 7 reports the design of two re-engineered thermostable GB1 sequences using a new computational method for thermostability prediction as well as on their expression and structural characterization. Interestingly, one of the mutants show an intertwined dimer organization in the crystal structure. The combined theoretical and experimental approaches reported herein provide valuable insights into the successful design of different GB1 variants with tailored properties and may help to open new avenues for the rational design of new thermostable and functional biomacromolecules.

Synthesis, Characterization, and Applications of Visible Light Active Metal-Organic Frameworks

Samantha Lynn Anderson

Understanding how crystalline materials are assembled is important for the rational design of metal-organic frameworks (MOFs). Controlling their formation can allow researchers to streamline the synthesis of new materials as well as control their properties for targeted applications. In the first chapter of this thesis we report the construction of two 3-dimensional TbIII based MOFs (SION-1 and SION-2). Here, SION-2 acts as a metastable MOF and intermediate phase that partially dissolves and transforms into the thermodynamically stable MOF, SION-1. This chemical transformation occurs in a DMF/water solvent mixture, and is triggered when additional energy is provided to the reaction. In situ studies reveal the partial dissolution of the metastable phase after which the MOF components are reassembled into the thermodynamically stable phase. The marked difference in thermal and chemical stability between the kinetically and thermodynamically controlled phases is contrasted by their identical chemical building unit composition. Following the understanding of this transformation, an isostructural family of SION-1 and SION-2 had been constructed using lanthanide metal salts, where LnIII-SION-1 is comprised of Ce, Nd, Eu, Gd, Tb, Dy, Ho, Er, Yb and Lu and LnIII-SION-2 is formed using Ce, Nd, Eu, Gd, Tb and Yb. The electronic properties of lanthanide based MOFs have not been extensively studied due to the general cognizance that LnIII ions behave as isolated free ions as their 4f orbitals do not contribute to bonding. Here, we systematically studied the electronic properties (UV-vis) of LnIII-SION-1 and LnIII-SION-2 and show that the higher the intensity of this absorption band in LnIII-SION-1 is due to the better overlap between Ln(5d) and ligand(pi*) orbitals and reveals that the lowest unoccupied crystalline orbitals are dispersed over an energy range and can be considered as a conduction band. We validated this observation by the non-linear I-V curves collected on CeIII- and YbIII-SION-1, both of which display dielectric properties. In the second chapter of this thesis, we rationally design a novel biologically derived MOF featuring unobstructed Watson-Crick faces of Ade pointing towards the MOF cavities. We show, through a combined experimental and computational approach, that Thy molecules diffuse through the pores of the MOF and become base-paired with Ade. The Ade-Thy pair binding at 40-45% loading reveals that Thy molecules are packed within the channels in a way that fulfill both the Woodward-Hoffmann and Schmidt rules, and upon UV irradiation, Thy molecules dimerize into ThyThy. This study highlights the utility of MOFs as nanoreactors for the synthesis of molecules that are otherwise difficult. Concluding this thesis, a biologically derived multimodal sensor MOF is synthesized and a formed into a device. The MOF, SION-9, is comprised of Ade and a porphyrin based ligand, and has tuneable conductive properties ranged from 2.69-4.20 x 10-8 - 7.43-7.34 x 10-6 S/cm. SION-9 is sensitive to both pressure and temperature simultaneously, and demonstrated both fast response times (< 60 ms) and a long shelf life (> 6 months).

EPFL2019

Complex networks

Cécile Caretta Cartozo

The last decade has witnessed a fundamental change in the role of network theory. Side by side with the increasing relevance of interdisciplinarity, this ensemble of mathematical tools and methods has known such a success and such a wide range of different applications to transform it in the proper scientific field of complex networks that groups researchers from different communities. Two different approaches can be distinguished. The first one is descriptive, tightly related to the experimental world. Reality is permeated with complex systems that lend themselves naturally to a network representation. The amount of data on natural, social and artificial systems is constantly increasing, and network theory provides a powerful framework for the analysis of such large datasets. The second is theoretical, aimed at producing models and analytical solutions for the reproduction and understanding of real networks properties. The results presented in this Thesis reflect the interdisciplinarity of the field of complex networks as well as its twofold nature. The first part of the manuscript describes new methods for the study of gene expression and protein interactions. Biological systems are highly complex and sensitive to the environment. Experimental data are affected by errors and poor reproducibility. We propose a method for the comparative analysis of similar datasets. We present an application to three independent studies on gene expression in the cell cycle of the fission yeast that show very poor agreement. In an attempt to reconcile them, we define a periodic genes network in which each node represents a gene identified as periodically regulated in the cell cycle and an edge between two nodes is drawn according to the phase difference between the expression peaks of the corresponding genes. The analysis of the topological structure of the network reveals a universal picture that overcomes the discrepancies and that is strongly related to the biological structure of the cell cycle and to the regulation of its progression. The method is able to group genes that are co-expressed during the cell cycle and to identify putative regulators of the transition from one phase to the next. Proteins are the fundamental product of gene expression. They are characterized by a modular structure comprising independent domains that act as mediators of protein interactions and are common to evolutionary related proteins. We propose the study of domain-centered interaction networks as a complementary tool for the understanding of protein interactions. We explore their topological structure looking for stable similarity groups and we investigate domain-peptide correlations that could be used as patterns for the prediction of the properties and functions to unknown proteins. The second part of this Thesis presents an exact theoretical solution for the navigability of small world networks with an inverse power-law distribution of the length of the connections. Optimal navigability is crucial for real networks involving transportation or communication processes (Internet, electric power grid, neural networks). Most of these systems are small worlds, characterized by a surprisingly small distance between any two nodes that grows only logarithmically with the size. How they are able to exploit this property for optimized performances without a complete knowledge of the structure is still an open question. It has been shown that a small world can arise from a proper compromise between local and long-range connections. In the specific case in which the length of the connections is power-law distributed and a greedy algorithm is used to forward a message from a source to a target, we obtained an original exact solution for the behavior of the expected delivery time in any dimension. We discussed the resulting scenario for the navigability and the implication of different structural parameters.

EPFL2009

Synthesis, Characterization, and Applications of Visible Light Active Metal-Organic Frameworks

Samantha Lynn Anderson

EPFL2019

Complex networks

Cécile Caretta Cartozo

EPFL2009