MoRFs
   HOME

TheInfoList



OR:

Molecular recognition features (MoRFs) are small (10-70 residues) intrinsically disordered regions in
proteins Proteins are large biomolecules and macromolecules that comprise one or more long chains of amino acid residues. Proteins perform a vast array of functions within organisms, including catalysing metabolic reactions, DNA replication, respo ...
that undergo a disorder-to-order transition upon binding to their partners. MoRFs are implicated in protein-protein interactions, which serve as the initial step in
molecular recognition The term molecular recognition refers to the specific interaction between two or more molecules through noncovalent bonding such as hydrogen bonding, metal coordination, hydrophobic forces, van der Waals forces, π-π interactions, halogen b ...
. MoRFs are disordered prior to binding to their partners, whereas they form a common 3D structure after interacting with their partners. As MoRF regions tend to resemble disordered proteins with some characteristics of ordered proteins, they can be classified as existing in an extended semi-disordered state.


Categorization

MoRFs can be separated in 4 categories according to the shape they form once bound to their partners. The categories are: * α-MoRFs (when they form alpha-helixes) * β-MoRFs (when they form beta-sheets) * irregular-MoRFs (when they don't form any shape) * complex-MoRFs (combination of the above categories)


MoRF predictors

Determining protein structures experimentally is a very time-consuming and expensive process. Therefore, recent years have seen a focus on computational methods for predicting protein structure and structural characteristics. Some aspects of protein structure, such as
secondary structure Protein secondary structure is the three dimensional conformational isomerism, form of ''local segments'' of proteins. The two most common Protein structure#Secondary structure, secondary structural elements are alpha helix, alpha helices and beta ...
and intrinsic disorder, have benefited greatly from applications of
deep learning Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. De ...
on an abundance of annotated data. However, computational prediction of MoRF regions remains a challenging task due to the limited availability of annotated data and the rarity of the MoRF class itself. Most current methods have been trained and benchmarked on the sets released by the authors of MoRFPred in 2012, as well as another set released by the authors of MoRFChibi based on experimentally-annotated MoRF data. The table below, adapted from, details some methods currently available for MoRF prediction (as well as related problems).


Databases


mpMoRFsDBMutual Folding Induced by Binding (MFIB) database
ref>


References

{{Reflist Proteins