A short commentary on indents and edges of β-sheets
Khare, H.; Ramakumar, S.
Show abstract
{beta}-sheets in proteins are formed by extended polypeptide chains, called {beta}-strands. While there is a general consensus on two types of {beta}-strands, viz. edge strands (or edges) and inner strands (or central strands), the possibility of distinguishing between different regions of inner strands remains less explored. In this paper, we address the portions of inner strands of {beta}-sheets that stick out on either or both sides. We call these portions the indent strands or indents because they give the typical indented appearance to {beta}-sheets. Similar to the edge strands, the indent strands also have {beta}-bridge partner residues on one side while the other side is still open for backbone hydrogen bonds. Despite this similarity, the indent strands differ from the edge strands in terms of various properties such as {beta}-bulges and amino acid composition due to their localization within {beta}-sheets and therefore within folded proteins to certain extent. The localization of indents and edges within folded proteins seems to govern the strategies deployed to deter unhindered {beta}-sheet propagation through {beta}-strand stacking interactions. Our findings suggest that, edges and indents differ in their strategies to avoid further {beta}-strand stacking. Short length itself is a good strategy to avoid stacking and a majority of indents are two residue or shorter in length. Edge strands on the other hand are overall longer. While long edges are known to use various negative design strategies like {beta}-bulges, prolines, strategically placed charges, inward-pointing charged side chains and loop coverage to avoid further {beta}-strand stacking, long indents seem to favor mechanisms such as enrichment in flexible residues with high solvation potential and depletion in hydrophobic residues in response to their less solvent exposed nature. Such subtle differences between indents and edges could be leveraged for designing novel {beta}-sheet architectures.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular Dynamics Study on the Effects of Charged Amino Acid Distribution Under low pH Condition to the Unfolding of Hen Egg White Lysozyme and Formation of Beta Strands. 95%
- Phage libraries screening on P53: yield improvement by zinc and a new parasites integrating analysis and rationale 95%
- Using AlphaFold to predict the impact of single mutations on protein stability and function 95%
Similar papers in this journal
- Influence of spatial structure on protein damage susceptibility - A bioinformatics approach 96%
- Time Dependent Dihedral Angle Oscillations of the Spike Protein of SARS-CoV-2 Reveal Favored Frequencies of Dihedral Angle Rotations 95%
- Mechanistic insights into the deleterious role of nasu-hakola disease associated TREM2 variants 95%
Similar papers in this journal
- III. Geometrical framework for thinking about globular proteins: turns in proteins 94%
- Role of Mutual Information Profile Shifts in Assessing the Pathogenicity of Mutations on Protein Functions: The Case of Pyrin Variants Associated with Familial Mediterranean Fever 94%
- Analysis of distance-based protein structure prediction by deep learning in CASP13 94%
Similar papers in this journal
- Computationally Grafting an IgE Epitope onto a Scaffold: Implications for a Pan Anti-Allergy Vaccine Design 95%
- SpatialPPI: three-dimensional space protein-protein interaction prediction with AlphaFold Multimer 94%
- Co-evolutionary Landscape at the Interface and Non-Interface Regions of Protein-Protein Interaction Complexes 93%
Similar papers in this journal
- Revisiting structural organization of proteins at high temperature from network perspective 95%
- Computational study and design of effective siRNAs to silence structural proteins associated genes of Indian SARS-CoV-2 strains 92%
- Discovery of Natural MCL1 Inhibitors using Pharmacophore modelling, QSAR, Docking, ADMET, Molecular Dynamics, and DFT Analysis 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.