Exploring the Universe of Protein Structures beyond the Protein Data Bank

It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds

Exploring the correlation between the folding rates of proteins and the entanglement of their native states

The folding of a protein towards its native state is a rather complicated process. However there are empirical evidences that the folding time correlates with the contact order, a simple measure of the spatial organisation of the native state of the protein. Contact order is related to the average length of the main chain loops formed by amino acids which are in contact. Here we argue that folding kinetics can be influenced also by the entanglement that loops may undergo within the overall three dimensional protein structure. In order to explore such possibility, we introduce a novel descriptor, which we call "maximum intrachain contact entanglement". Specifically, we measure the maximum Gaussian entanglement between any looped portion of a protein and any other non-overlapping subchain of the same protein, which is easily computed by discretized line integrals on the coordinates of the $C_{\alpha}$ atoms. By analyzing experimental data sets of two-state and multistate folders, we show that also the new index is a good predictor of the folding rate. Moreover, being only partially correlated with previous methods, it can be integrated with them to yield more accurate predictions.Comment: 8 figures. v2: new titl

Protein sequence and structure: Is one more fundamental than the other?

We argue that protein native state structures reside in a novel "phase" of matter which confers on proteins their many amazing characteristics. This phase arises from the common features of all globular proteins and is characterized by a sequence-independent free energy landscape with relatively few low energy minima with funnel-like character. The choice of a sequence that fits well into one of these predetermined structures facilitates rapid and cooperative folding. Our model calculations show that this novel phase facilitates the formation of an efficient route for sequence design starting from random peptides.Comment: 7 pages, 4 figures, to appear in J. Stat. Phy

De novo protein design:How do we expand into the universe of possible protein structures?

Protein scientists are paving the way to a new phase in protein design and engineering. Approaches and methods are being developed that could allow the design of proteins beyond the confines of natural protein structures. This possibility of designing entirely new proteins opens new questions: What do we build? How do we build into protein-structure space where there are few, if any, natural structures to guide us? To what uses can the resulting proteins be put? And, what, if anything, does this pursuit tell us about how natural proteins fold, function and evolve? We describe the origins of this emerging area of fully de novo protein design, how it could be developed, where it might lead, and what challenges lie ahead

A structural biology community assessment of AlphaFold2 applications

Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested. Here, we evaluate the use of AlphaFold2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modeling of interactions; and modeling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank. AF2-based predictions of protein disorder and complexes surpass dedicated tools, and AF2 models can be used across diverse applications equally well compared with experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life-science research

What is hidden in the darkness? Characterization of AlphaFold structural space

The recent public release of the latest version of the AlphaFold database has given us access to over 200 million predicted protein structures. We use a textquotedblleftshape-mertextquotedblright approach, a structural fragmentation method analogous to sequence k-mers, to describe these structures and look for novelties - both in terms of proteins with rare or novel structural composition and possible functional annotation of under-studied proteins. Data and code will be made available at https://github.com/TurtleTools/afdb-shapemer-darknes

Exploration of Uncharted Regions of the Protein Universe

Determination of first protein structures, from hundreds of families of unknown function, have shown that divergence, rather than novelty, is the dominant force that shapes the evolution of the protein universe

Protein physics by advanced computational techniques: conformational sampling and folded state discrimination

Proteins are essential parts of organisms and participate in virtually every process within cells. Many proteins are enzymes that catalyze biochemical reactions and are vital to metabolism. Proteins also have structural or mechanical functions, such as actin and myosin in muscle that are in charge of motion and locomotion of cells and organisms. Others proteins are important for transporting materials, cell signaling, immune response, and several other functions. Proteins are the main building blocks of life. A protein is a polymer chain of amino acids whose sequence is defined in a gene: three nucleo type basis specify one out of the 20 natural amino acids. All amino acids possess common structural features. They have an \u3b1-carbon to which an amino group, a carboxyl group, a hydrogen atom and a variable side chain are attached. In a protein, the amino acids are linked together by peptide bonds between the carboxyl and amino groups of adjacent residues..