Modeling Cell-Free Protein Synthesis Systems-Approaches and Applications

Advancements in Functional Nanomaterials Inspired by Viral Particles

Virus-like particles (VLPs) are nanostructures composed of one or more structural proteins, exhibiting stable and symmetrical structures. Their precise compositions and dimensions provide versatile opportunities for modifications, enhancing their functionality. Consequently, VLP-based nanomaterials have gained widespread adoption across diverse domains. This review focuses on three key aspects: the mechanisms of viral capsid protein self-assembly into VLPs, design methods for constructing multifunctional VLPs, and strategies for synthesizing multidimensional nanomaterials using VLPs. It provides a comprehensive overview of the advancements in virus-inspired functional nanomaterials, encompassing VLP assembly, functionalization, and the synthesis of multidimensional nanomaterials. Additionally, this review explores future directions, opportunities, and challenges in the field of VLP-based nanomaterials, aiming to shed light on potential advancements and prospects in this exciting area of research.

Amino acid balancing for the prediction and evaluation of protein concentrations in cell-free protein synthesis systems

Cell-free protein synthesis (CFPS) systems are an attractive method to complement the usual cell-based synthesis of proteins, especially for screening approaches. The literature describes a wide variety of CFPS systems, but their performance is difficult to compare since the reaction components are often used at different concentrations. Therefore, we have developed a calculation tool based on amino acid balancing to evaluate the performance of CFPS by determining the fractional yield as the ratio between theoretically achievable and experimentally achieved protein molar concentration. This tool was applied to a series of experiments from our lab and to various systems described in the literature to identify systems that synthesize proteins very efficiently and those that still have potential for higher yields. The well-established Escherichia coli system showed a high efficiency in the utilization of amino acids, but interestingly, less considered systems, such as those based on Vibrio natriegens or Leishmania tarentolae, also showed exceptional fractional yields of over 70% and 90%, respectively, implying very efficient conversions of amino acids. The methods and tools described here can quickly identify when a system has reached its maximum or has limitations. We believe that this approach will facilitate the evaluation and optimization of existing CFPS systems and provides the basis for the systematic development of new CFPS systems.

The Long Road to a Synthetic Self-Replicating Central Dogma

The construction of a biochemical system capable of self-replication is a key objective in bottom-up synthetic biology. Throughout the past two decades, a rapid progression in the design of in vitro cell-free systems has provided valuable insight into the requirements for the development of a minimal system capable of self-replication. The main limitations of current systems can be attributed to their macromolecular composition and how the individual macromolecules use the small molecules necessary to drive RNA and protein synthesis. In this Perspective, we discuss the recent steps that have been taken to generate a minimal cell-free system capable of regenerating its own macromolecular components and maintaining the homeostatic balance between macromolecular biogenesis and consumption of primary building blocks. By following the flow of biological information through the central dogma, we compare the current versions of these systems to date and propose potential alterations aimed at designing a model system for self-replicative synthetic cells.

Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods

Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract knowledge from existing databases. This review is focused on mathematical modeling used to analyze dynamics and robustness of these networks. This paper presents a review of selected modeling methods that facilitate advances in molecular biology.

In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology

Living systems are studied using three complementary approaches: living cells, cell-free systems and computer-mediated modelling. Progresses in understanding, allowing researchers to create novel chassis and industrial processes rest on a cycle that combines in vivo, in vitro and in silico studies. This design-build-test-learn iteration loop cycle between experiments and analyses combines together physiology, genetics, biochemistry and bioinformatics in a way that keeps going forward. Because computer-aided approaches are not directly constrained by the material nature of the entities of interest, we illustrate here how this virtuous cycle allows researchers to explore chemistry which is foreign to that present in extant life, from whole chassis to novel metabolic cycles. Particular emphasis is placed on the importance of evolution.

SARS-CoV-2 spike evolutionary behaviors; simulation of N501Y mutation outcomes in terms of immunogenicity and structural characteristic

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), a large number of mutations in its genome have been reported. Some of the mutations occur in noncoding regions without affecting the pathobiology of the virus, while mutations in coding regions are significant. One of the regions where a mutation can occur, affecting the function of the virus is at the receptor‐binding domain (RBD) of the spike protein. RBD interacts with angiotensin‐converting enzyme 2 (ACE2) and facilitates the entry of the virus into the host cells. There is a lot of focus on RBD mutations, especially the displacement of N501Y which is observed in the UK/Kent, South Africa, and Brazilian lineages of SARS‐CoV‐2. Our group utilizes computational biology approaches such as immunoinformatics, protein–protein interaction analysis, molecular dynamics, free energy computation, and tertiary structure analysis to disclose the consequences of N501Y mutation at the molecular level. Surprisingly, we discovered that this mutation reduces the immunogenicity of the spike protein; also, displacement of Asn with Tyr reduces protein compactness and significantly increases the stability of the spike protein and its affinity to ACE2. Moreover, following the N501Y mutation secondary structure and folding of the spike protein changed dramatically.