Protein space: A natural method for realizing the nature of protein universe

2013 ◽  
Vol 318 ◽  
pp. 197-204 ◽  
Author(s):  
Chenglong Yu ◽  
Mo Deng ◽  
Shiu-Yuen Cheng ◽  
Shek-Chung Yau ◽  
Rong L. He ◽  
...  
Keyword(s):  
Protein Universe ◽  
Protein Space ◽  
Natural Method

Fine tuned exploration of evolutionary relationships within the protein universe

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Danilo Gullotto
Keyword(s):  
Sequence Similarity ◽  
Hierarchical Classification ◽  
Domain Size ◽  
Protein Motifs ◽  
Physical Constraints ◽  
Protein Universe ◽  
Sequence Profiles ◽  
Polypeptide Chains ◽  
Hierarchical Features ◽  
Protein Space

Abstract In the regime of domain classifications, the protein universe unveils a discrete set of folds connected by hierarchical relationships. Instead, at sub-domain-size resolution and because of physical constraints not necessarily requiring evolution to shape polypeptide chains, networks of protein motifs depict a continuous view that lies beyond the extent of hierarchical classification schemes. A number of studies, however, suggest that universal sub-sequences could be the descendants of peptides emerged in an ancient pre-biotic world. Should this be the case, evolutionary signals retained by structurally conserved motifs, along with hierarchical features of ancient domains, could sew relationships among folds that diverged beyond the point where homology is discernable. In view of the aforementioned, this paper provides a rationale where a network with hierarchical and continuous levels of the protein space, together with sequence profiles that probe the extent of sequence similarity and contacting residues that capture the transition from pre-biotic to domain world, has been used to explore relationships between ancient folds. Statistics of detected signals have been reported. As a result, an example of an emergent sub-network that makes sense from an evolutionary perspective, where conserved signals retrieved from the assessed protein space have been co-opted, has been discussed.

scholarly journals BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space

2021 ◽  
Vol 22 (15) ◽  
pp. 7773
Author(s):  
Neann Mathai ◽  
Conrad Stork ◽  
Johannes Kirchmair
Keyword(s):  
Large Scale ◽  
Computational Approach ◽  
Large Sets ◽  
Compound Libraries ◽  
Wide Range ◽  
Protein Space ◽  
High Chance ◽  
Large Scale Screening ◽  
Early Drug ◽  
Selection Of

Experimental screening of large sets of compounds against macromolecular targets is a key strategy to identify novel bioactivities. However, large-scale screening requires substantial experimental resources and is time-consuming and challenging. Therefore, small to medium-sized compound libraries with a high chance of producing genuine hits on an arbitrary protein of interest would be of great value to fields related to early drug discovery, in particular biochemical and cell research. Here, we present a computational approach that incorporates drug-likeness, predicted bioactivities, biological space coverage, and target novelty, to generate optimized compound libraries with maximized chances of producing genuine hits for a wide range of proteins. The computational approach evaluates drug-likeness with a set of established rules, predicts bioactivities with a validated, similarity-based approach, and optimizes the composition of small sets of compounds towards maximum target coverage and novelty. We found that, in comparison to the random selection of compounds for a library, our approach generates substantially improved compound sets. Quantified as the “fitness” of compound libraries, the calculated improvements ranged from +60% (for a library of 15,000 compounds) to +184% (for a library of 1000 compounds). The best of the optimized compound libraries prepared in this work are available for download as a dataset bundle (“BonMOLière”).

Armchair travel trough the human protein universe

2006 ◽  
Vol 7 (7) ◽  
pp. 492-492
Author(s):  
Magdalena Skipper
Keyword(s):  
Human Protein ◽  
Protein Universe

scholarly journals Structural genomics: keeping up with expanding knowledge of the protein universe

2007 ◽  
Vol 17 (3) ◽  
pp. 347-353 ◽  
Author(s):  
Marek Grabowski ◽  
Andrzej Joachimiak ◽  
Zbyszek Otwinowski ◽  
Wladek Minor
Keyword(s):  
Structural Genomics ◽  
Protein Universe

scholarly journals Dark Proteome Database: Studies on Dark Proteins

2019 ◽  
Author(s):  
Nelson Perdigão
Keyword(s):  
Natural Killer Cells ◽  
Homology Modeling ◽  
3D Structure ◽  
Model Organisms ◽  
Human Organism ◽  
Experimental Characterization ◽  
Proteome Database ◽  
Protein Universe ◽  
Cervical Mucosa ◽  
Higher Eukaryotes

The dark proteome as we define it, is the part of the proteome where 3D structure has not been observed either by homology modeling or by experimental characterization in the protein universe. From the 550.116 proteins available in Swiss-Prot (as of July 2016) 43.2% of the Eukarya universe and 49.2% of the Virus universe are part of the dark proteome. In Bacteria and Archaea, the percentage of the dark proteome presence is significantly less, with 12.6% and 13.3% respectively. In this work, we present the map of the dark proteome in Human and in other model organisms. The most significant result is that around 40%- 50% of the proteome of these organisms are still in the dark, where the higher percentages belong to higher eukaryotes (mouse and human organisms). Due to the amount of darkness present in the human organism being more than 50%, deeper studies were made, including the identification of ‘dark’ genes that are responsible for the production of the so-called dark proteins, as well as, the identification of the ‘dark’ organs where dark proteins are over represented, namely heart, cervical mucosa and natural killer cells. This is a step forward in the direction of the human dark proteome.

Evidence for the Emergence of β-Trefoils by ‘Peptide Budding’ from an IgG-like β-Sandwich

2021 ◽  
Author(s):  
Liam M. Longo ◽  
Rachel Kolodny ◽  
Shawn E. McGlynn
Keyword(s):  
De Novo ◽  
General Trend ◽  
Sequence Structure ◽  
Structure Comparison ◽  
Related Sequence ◽  
Structure Space ◽  
Protein Universe ◽  
Remote Islands ◽  
Comparison Algorithms ◽  
Hallmark Feature

AbstractAs sequence and structure comparison algorithms gain sensitivity, the intrinsic interconnectedness of the protein universe has become increasingly apparent. Despite this general trend, β-trefoils have emerged as an uncommon counterexample: They are an isolated protein lineage for which few, if any, sequence or structure associations to other lineages have been identified. If β-trefoils are, in fact, remote islands in sequence-structure space, it implies that the oligomerizing peptide that founded the β-trefoil lineage itself arose de novo. To better understand β-trefoil evolution, and to probe the limits of fragment sharing across the protein universe, we identified both ‘β-trefoil bridging themes’ (evolutionarily-related sequence segments) and ‘β-trefoil-like motifs’ (structure motifs with a hallmark feature of the β-trefoil architecture) in multiple, ostensibly unrelated, protein lineages. The success of the present approach stems, in part, from considering β-trefoil sequence segments or structure motifs rather than the β-trefoil architecture as a whole, as has been done previously. The newly uncovered inter-lineage connections presented here suggest a novel hypothesis about the origins of the β-trefoil fold itself – namely, that it is a derived fold formed by ‘budding’ from an Immunoglobulin-like β-sandwich protein. These results demonstrate how the emergence of a folded domain from a peptide need not be a signature of antiquity and underpin an emerging truth: few protein lineages escape nature’s sewing table.

scholarly journals Dark Proteome Database: Studies on Dark Proteins

2019 ◽  
Vol 8 (2) ◽  
pp. 8 ◽  
Author(s):  
Nelson Perdigão ◽  
Agostinho Rosa
Keyword(s):  
Homology Modeling ◽  
3D Structure ◽  
Model Organisms ◽  
Human Organism ◽  
Special Importance ◽  
Experimental Characterization ◽  
Proteome Database ◽  
Protein Universe ◽  
Cervical Mucosa ◽  
Higher Eukaryotes

The dark proteome, as we define it, is the part of the proteome where 3D structure has not been observed either by homology modeling or by experimental characterization in the protein universe. From the 550.116 proteins available in Swiss-Prot (as of July 2016), 43.2% of the eukarya universe and 49.2% of the virus universe are part of the dark proteome. In bacteria and archaea, the percentage of the dark proteome presence is significantly less, at 12.6% and 13.3% respectively. In this work, we present a necessary step to complete the dark proteome picture by introducing the map of the dark proteome in the human and in other model organisms of special importance to mankind. The most significant result is that around 40% to 50% of the proteome of these organisms are still in the dark, where the higher percentages belong to higher eukaryotes (mouse and human organisms). Due to the amount of darkness present in the human organism being more than 50%, deeper studies were made, including the identification of ‘dark’ genes that are responsible for the production of so-called dark proteins, as well as the identification of the ‘dark’ tissues where dark proteins are over represented, namely, the heart, cervical mucosa, and natural killer cells. This is a step forward in the direction of gaining a deeper knowledge of the human dark proteome.

Sign in / Sign up

Export Citation Format

Share Document