scholarly journals The Overlap of Small Molecule and Protein Binding Sites within Families of Protein Structures

2010 ◽  
Vol 6 (2) ◽  
pp. e1000668 ◽  
Author(s):  
Fred P. Davis ◽  
Andrej Sali
Keyword(s):  
Protein Binding ◽  
Small Molecule ◽  
Binding Sites ◽  
Protein Structures ◽  
Protein Binding Sites

A QUANTITATIVE ANALYSIS OF INTERFACIAL AMINO ACID CONSERVATION IN PROTEIN-PROTEIN HETERO COMPLEXES

2005 ◽  
Vol 03 (05) ◽  
pp. 1137-1150 ◽  
Author(s):  
BOOJALA V. B. REDDY ◽  
YIANNIS N. KAZNESSIS
Keyword(s):  
Amino Acid ◽  
Protein Binding ◽  
Binding Sites ◽  
Protein Structures ◽  
Complex Structures ◽  
Protein Surface ◽  
Protein Surfaces ◽  
Protein Binding Sites ◽  
Interaction Sites ◽  
Conserved Residue

A long-standing question in molecular biology is whether interfaces of protein-protein complexes are more conserved than the rest of the protein surfaces. Although it has been reported that conservation can be used as an indicator for predicting interaction sites on proteins, there are recent reports stating that the interface regions are only slightly more conserved than the rest of the protein surfaces, with conservation signals not being statistically significant enough for predicting protein-protein binding sites. In order to properly address these controversial reports we have studied a set of 28 well resolved hetero complex structures of proteins that consists of transient and non-transient complexes. The surface positions were classified into four conservation classes and the conservation index of the surface positions was quantitatively analyzed. The results indicate that the surface density of highly conserved positions is significantly higher in the protein-protein interface regions compared with the other regions of the protein surface. However, the average conservation index of the patches in the interface region is not significantly higher compared with other surface regions of the protein structures. This finding demonstrates that the number of conserved residue positions is a more appropriate indicator for predicting protein-protein binding sites than the average conservation index in the interacting region. We have further validated our findings on a set of 59 benchmark complex structures. Furthermore, an analysis of 19 complexes of antigen-antibody interactions shows that there is no conservation of amino acid positions in the interacting regions of these complexes, as expected, with the variable region of the immunoglobulins interacting mostly with the antigens. Interestingly, antigen interacting regions also have a higher number of non-conserved residue positions in the interacting region than the rest of the protein surface.

scholarly journals DeeplyTough: Learning Structural Comparison of Protein Binding Sites

2019 ◽  
Author(s):  
Martin Simonovsky ◽  
Joshua Meyers
Keyword(s):  
Protein Binding ◽  
Binding Sites ◽  
Protein Function ◽  
Large Scale ◽  
Protein Structures ◽  
Three Dimensional ◽  
Protein Binding Sites ◽  
Data Driven Approach ◽  
Benchmark Datasets ◽  
New Perspective

AbstractMotivationProtein binding site comparison (pocket matching) is of importance in drug discovery. Identification of similar binding sites can help guide efforts for hit finding, understanding polypharmacology and characterization of protein function. The design of pocket matching methods has traditionally involved much intuition, and has employed a broad variety of algorithms and representations of the input protein structures. We regard the high heterogeneity of past work and the recent availability of large-scale benchmarks as an indicator that a data-driven approach may provide a new perspective.ResultsWe propose DeeplyTough, a convolutional neural network that encodes a three-dimensional representation of protein binding sites into descriptor vectors that may be compared efficiently in an alignment-free manner by computing pairwise Euclidean distances. The network is trained with supervision: (i) to provide similar pockets with similar descriptors, (ii) to separate the descriptors of dissimilar pockets by a minimum margin, and (iii) to achieve robustness to nuisance variations. We evaluate our method using three large-scale benchmark datasets, on which it demonstrates excellent performance for held-out data coming from the training distribution and competitive performance when the trained network is required to generalize to datasets constructed independently.Availabilityhttps://github.com/BenevolentAI/[email protected],[email protected]

EVALUATION OF TISSUE STEROID BINDING IN VITRO

1971 ◽  
Vol 68 (1_Suppl) ◽  
pp. S223-S246 ◽  
Author(s):  
C. R. Wira ◽  
H. Rochefort ◽  
E. E. Baulieu
Keyword(s):  
Protein Binding ◽  
Binding Sites ◽  
Experimental System ◽  
Specific Protein ◽  
Coupling Mechanism ◽  
Target Tissue ◽  
Protein Binding Sites ◽  
Definition Of ◽  
Hormone Specificity

ABSTRACT The definition of a RECEPTOR* in terms of a receptive site, an executive site and a coupling mechanism, is followed by a general consideration of four binding criteria, which include hormone specificity, tissue specificity, high affinity and saturation, essential for distinguishing between specific and nonspecific binding. Experimental approaches are proposed for choosing an experimental system (either organized or soluble) and detecting the presence of protein binding sites. Techniques are then presented for evaluating the specific protein binding sites (receptors) in terms of the four criteria. This is followed by a brief consideration of how receptors may be located in cells and characterized when extracted. Finally various examples of oestrogen, androgen, progestagen, glucocorticoid and mineralocorticoid binding to their respective target tissues are presented, to illustrate how researchers have identified specific corticoid and mineralocorticoid binding in their respective target tissue receptors.

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