Evolving cellular automata schemes for protein folding modeling using the Rosetta atomic representation

Protein folding is the dynamic process by which a protein folds into its final native structure. This is different to the traditional problem of the prediction of the final protein structure, since it requires a modeling of how protein components interact over time to obtain the final folded structure. In this study we test whether a model of the folding process can be obtained exclusively through machine learning. To this end, protein folding is considered as an emergent process and the cellular automata tool is used to model the folding process. A neural cellular automaton is defined, using a connectionist model that acts as a cellular automaton through the protein chain to define the dynamic folding. Differential evolution is used to automatically obtain the optimized neural cellular automata that provide protein folding. We tested the methods with the Rosetta coarse-grained atomic model of protein representation, using different proteins to analyze the modeling of folding and the structure refinement that the modeling can provide, showing the potential advantages that such methods offer, but also difficulties that arise.

Canalized morphogenesis driven by inherited tissue asymmetries in Hydra regeneration

The emergence and stabilization of a body axis is a major step in animal morphogenesis, determining the symmetry of the body plan as well as its polarity. To advance our understanding of the emergence of body-axis polarity we study regenerating Hydra. Axis polarity is strongly memorized in Hydra regeneration even in small tissue segments. What type of processes confer this memory? To gain insight into the emerging polarity, we utilize frustrating initial conditions by studying regenerating tissue strips which fold into hollow spheroids by adhering their distal ends, of opposite original polarities. Despite the convoluted folding process and the tissue rearrangements during regeneration, these tissue strips develop a new organizer in a reproducible location preserving the original polarity and yielding an ordered body plan. These observations suggest that the integration of mechanical and biochemical processes supported by their mutual feedback attracts the tissue dynamics towards a well-defined developmental trajectory biased by weak inherited cues from the parent animal. Hydra thus provide an example of dynamic canalization in which the dynamic rules themselves are inherited, in contrast to the classical picture where a detailed developmental trajectory is pre-determined.

Interactions between nascent proteins and the ribosome surface inhibit co-translational folding

Most proteins begin to fold during biosynthesis on the ribosome. It has been suggested that interactions between the emerging polypeptide and the ribosome surface might allow the ribosome itself to modulate co-translational folding. Here we combine protein engineering and NMR spectroscopy to characterize a series of interactions between the ribosome surface and unfolded nascent chains of the immunoglobulin-like FLN5 filamin domain. The strongest interactions are found for a C-terminal segment that is essential for folding, and we demonstrate quantitative agreement between the strength of this interaction and the energetics of the co-translational folding process itself. Mutations in this region that reduce the extent of binding result in a shift in the co-translational folding equilibrium towards the native state. Our results therefore demonstrate that a competition between folding and binding provides a simple, dynamic mechanism for the modulation of co-translational folding by the ribosome.

A low Smc flux avoids collisions and facilitates chromosome organization in B. subtilis

SMC complexes are widely conserved ATP-powered DNA-loop-extrusion motors indispensable for organizing and faithfully segregating chromosomes. How SMC complexes translocate along DNA for loop extrusion and what happens when two complexes meet on the same DNA molecule is largely unknown. Revealing the origins and the consequences of SMC encounters is crucial for understanding the folding process not only of bacterial, but also of eukaryotic chromosomes. Here, we uncover several factors that influence bacterial chromosome organization by modulating the probability of such clashes. These factors include the number, the strength, and the distribution of Smc loading sites, the residency time on the chromosome, the translocation rate, and the cellular abundance of Smc complexes. By studying various mutants, we show that these parameters are fine-tuned to reduce the frequency of encounters between Smc complexes, presumably as a risk mitigation strategy. Mild perturbations hamper chromosome organization by causing Smc collisions, implying that the cellular capacity to resolve them is limited. Altogether, we identify mechanisms that help to avoid Smc collisions and their resolution by Smc traversal or other potentially risky molecular transactions.

Folding Process Planning of Rigid Origami Using the Explicit Expression and Rapidly Exploring Random Tree Method

In this study, we propose a novel method for planning the folding process of a rigid origami mechanism, i.e., we explore the intermediate process of the mechanism from an initial state to a target state without self-intersection via a path-finding algorithm. A typical problem associated with a path-finding algorithm is that a feasible configuration space of rigid origami is a lower-dimensional subset of the entire parameter space. When all the folding angles are considered as free parameters to plan the folding process, it is generally not possible to obtain a feasible configuration via sampling. In this study, the parameters corresponding to the degree of freedom (DOF) are used as independent variables, and the remaining fold angles are considered as dependent variables that can be calculated via the explicit expression method (EEM). First, we explain the method for choosing the parameters related to DOF to represent the configuration of the origami mechanism. Then, we show the procedure for selecting a valid configuration from many possible configurations computed via EEM. For this purpose, we introduce criteria for each vertex to determine whether the two configurations can be continuously connected. Next, the method for planning the folding process of rigid origami is introduced via the rapidly-exploring random tree (RRT) method. Finally, we implemented the folding process simulation platform and applied it to different patterns. The results of the experiments are presented.

SBMOpenMM: A Builder of Structure-Based Models for OpenMM

<p>Here we introduce SBMOpenMM, a python library to build Structure-Based Models (SBMs), that uses the OpenMM framework to create and run SBM simulations. The code is flexible, user-friendly, and profits from high customizability and GPU performance provided by the OpenMM platform. We demonstrate its use in the evaluation of the two-step folding process of FoxP1 transcription factor protein. Our results indicate that the newly developed SBM can be successfully applied to elucidating the underlying mechanisms of biomolecular processes.</p><div><br></div>

Divergence Entropy-Based Evaluation of Hydrophobic Core in Aggressive and Resistant Forms of Transthyretin

The two forms of transthyretin differing slightly in the tertiary structure, despite the presence of five mutations, show radically different properties in terms of susceptibility to the amyloid transformation process. These two forms of transthyretin are the object of analysis. The search for the sources of these differences was carried out by means of a comparative analysis of the structure of these molecules in their native and early intermediate stage forms in the folding process. The criterion for assessing the degree of similarity and differences is the status of the hydrophobic core. The comparison of the level of arrangement of the hydrophobic core and its initial stages is possible thanks to the application of divergence entropy for the early intermediate stage and for the final forms. It was shown that the minimal differences observed in the structure of the hydrophobic core of the forms available in PDB, turned out to be significantly different in the early stage (ES) structure in folding process. The determined values of divergence entropy for both ES forms indicate the presence of the seed of hydrophobic core only in the form resistant to amyloid transformation. In the form of aggressively undergoing amyloid transformation, the structure lacking such a seed is revealed, being a stretched one with a high content of β-type structure. In the discussed case, the active presence of water in the structural transformation of proteins expressed in the fuzzy oil drop model (FOD) is of decisive importance for the generation of the final protein structure. It has been shown that the resistant form tends to generate a centric hydrophobic core with the possibility of creating a globular structure, i.e. a spherical micelle-like form. The aggressively transforming form reveals in the structure of its early intermediate, a tendency to form the ribbon-like micelle as observed in amyloid.

SBMOpenMM: A Builder of Structure-Based Models for OpenMM

<p>Here we introduce SBMOpenMM, a python library to build Structure-Based Models (SBMs), that uses the OpenMM framework to create and run SBM simulations. The code is flexible, user-friendly, and profits from high customizability and GPU performance provided by the OpenMM platform. We demonstrate its use in the evaluation of the two-step folding process of FoxP1 transcription factor protein. Our results indicate that the newly developed SBM can be successfully applied to elucidating the underlying mechanisms of biomolecular processes.</p><div><br></div>