Macromolecular assembly | EPFL Graph Search

The term macromolecular assembly (MA) refers to massive chemical structures such as viruses and non-biologic nanoparticles, cellular organelles and membranes and ribosomes, etc. that are complex mixtures of polypeptide, polynucleotide, polysaccharide or other polymeric macromolecules. They are generally of more than one of these types, and the mixtures are defined spatially (i.e., with regard to their chemical shape), and with regard to their underlying chemical composition and structure. Macromolecules are found in living and nonliving things, and are composed of many hundreds or thousands of atoms held together by covalent bonds; they are often characterized by repeating units (i.e., they are polymers). Assemblies of these can likewise be biologic or non-biologic, though the MA term is more commonly applied in biology, and the term supramolecular assembly is more often applied in non-biologic contexts (e.g., in supramolecular chemistry and nanotechnology). MAs of macromolecules ar

Self-Assembly of a Designed Nucleoprotein Architecture through Multimodal Interactions

Henning Paul-Julius Stahlberg, Ling Zhang

The co-self-assembly of proteins and nucleic acids (NAs) produces complex biomolecular machines (e.g., ribosomes and telomerases) that represent some of the most daunting targets for biomolecular design. Despite significant advances in protein and DNA or RNA nanotechnology, the construction of artificial nucleoprotein complexes has largely been limited to cases that rely on the NA-mediated spatial organization of protein units, rather than a cooperative interplay between protein-and NA-mediated interactions that typify natural nucleoprotein assemblies. We report here a structurally well-defined synthetic nucleoprotein assembly that forms through the synergy of three types of intermolecular interactions: Watson-Crick base pairing, NA-protein interactions, and protein-metal coordination. The fine thermodynamic balance between these interactions enables the formation of a crystalline architecture under highly specific conditions.

American Chemical Society (ACS)2018

Multiscale simulations of protein dynamics

Enrico Spiga

Characteristic timescales associated with the function of biomolecules, like proteins, range from femtoseconds up to minutes, whereas their corresponding spatial extent ranges from few ̊A to μm when associating in large macromolecular complexes. Moreover, biomolecules are functional in a large variety of different physico-chemical conditions strongly dependent on pH, ionic strength, crowding agents, etc. This huge complexity is hard to be studied with an arbitrary level of resolution embracing all these spatial and temporal scales. Molecular simulation is a well established approach to gain mechanistic insights into the function of biomolecular systems, producing atomistically detailed models of in vitro and/or in vivo conditions. I present in this thesis two projects that aim at improving on the current limitations of multiscale molecular simulations, namely (i) the sampling of large systems, and (ii) the detailed representation and description of realistic physiological conditions. Addressing the first issue, I propose a new coarse-grained model for proteins to be used in molecular dynamics simulations. This coarse-grained model is based on a more accurate description of protein electrostatics, which accounts for dipolar contributions. The parameterization of this force field is based on force-matching methods and on the use of a particle swarm optimization heuristic algorithm. The obtained results are encouraging being structural and electrostatic properties accurately reproduced with the coarse-grained model for a variety of protein folds. Moreover, the parameterization procedure can be straightforwardly applied to any protein, and can be extended to a larger dataset to generate a fully transferable coarse-grained force field, to be applied to any protein and any large macromolecular assemblies for which long all-atom simulations are still a challenge. While the development and use of coarse-grained models are important to tackle the limited sampling of large systems, it is still important to use all-atom molecular dynamics simulation to investigate with high accuracy in physiological conditions protein dynamics. For this reason, I present here the results of state-of-art molecular dynamics simulations applied to study the influence of crowding agents on the internal dynamics of the protein ubiquitin. Their analysis allows to describe how ubiquitin dynamics is slaved by crowding agents. This work demonstrates that the description of protein dynamics should take into account its intrinsic multiscale nature. The development and applications of coarse-grained models permit to simulate proteins at low computational cost, the use of atomistic simulations allows to accurately describe proteins in absence and presence of crowding agents, and both of them permit to highlight the essence of protein dynamics.

EPFL2013

New Methods for the Integrative Dynamic Modeling of Biomolecular Structures

Sylvain Träger

The true understanding of most cellular functions is only really achievable through the structural determination of their underlying macromolecular assemblies. However, their size, large number of individual components and metastable states make their elucidation by canonical structural biology techniques a vain effort in many situations. As a result, integrative approaches have been in high demand in the recent years. By combining any available data, both computational and experimental, integrative or hybrid modeling strategies have been able to tackle biomolecular structures otherwise intractable by any singular method alone. Over the past decade, structural biology has undergone a significant revolution in the form of cryo-electron microscopy (cryo-EM). With more than 12.000 models of biomolecular structures under its name, cryo-EM however still struggles to approach larger, flexible assemblies at atomic resolution. Instead, such assemblies now routinely fall in an intermediate resolution range, opening new avenues for the development of hybrid approaches primarily based on cryo-EM data. However, the large degrees of flexibility of such assemblies imposes the inclusion of dynamics in the modeling process. Unfortunately, this only makes the already challenging task of defining a scoring function even more difficult. In general, current integrative strategies are thus unable to approach flexible assemblies in a reliable manner. To tackle these issues, two new methods made available to the community are presented in this thesis in addition to their applications to a variety of systems. A new clustering analysis tool, CLoNe, is first introduced. As a significant upgrade to the recent Density Peaks algorithm, we show that CLoNe rivals and outperforms many state-of-the-art algorithms even beyond structural biology. Then, we show how CLoNe is able to extract a variety of information from structural ensembles in general or reduce large ensembles to key components, enabling their successful integration into hybrid modeling approaches. Second, the MaD software is presented. Taking inspiration from traditional computer vision concepts and methods, MaD bypasses the need of a traditional scoring function through the generation of local macromolecular feature descriptors. MaD takes full advantage of the ongoing cryo-EM resolution revolution by integrating local structural information from both cryo-EM data and existing atomic structures. Specifically, MaD is able to predict the quaternary structure of large assemblies regardless of symmetry and conformational variability. Finally, the MaD-CLoNe combination enabled the modeling of molecular chaperones with unprecedented ease. Chaperonins are of crucial importance to ensure proper protein folding and proteostasis. Perturbation of these processes are implicated in neurodegenerative diseases and cancer. In the specific case of the group II chaperonin Mm-Cpn, the use of MaD-CLoNe along with molecular dynamics simulations uncovered new structural models and insight into the chaperonin's functional pathway.

EPFL2021