scholarly journals Local frustration determines loop opening during the catalytic cycle of an oxidoreductase

2019 ◽  
Author(s):  
Lukas L. Stelzl ◽  
Despoina A.I. Mavridou ◽  
Emmanuel Saridakis ◽  
Diego Gonzalez ◽  
Andrew J. Baldwin ◽  
...  
Keyword(s):  
Active Site ◽  
Binding Sites ◽  
Protein Function ◽  
Catalytic Cycle ◽  
Biomolecular Recognition ◽  
Competing Interactions ◽  
Protein Binding Sites ◽  
Loop Region ◽  
Cysteine Thiols ◽  
Small Chemical

AbstractLocal structural frustration, the existence of mutually exclusive competing interactions, may explain why some proteins are dynamic while others are rigid. Frustration is thought to underpin biomolecular recognition and the flexibility of protein binding sites. Here we show how a small chemical modification, the oxidation of two cysteine thiols to a disulfide bond, during the catalytic cycle of the N-terminal domain of the key bacterial oxidoreductase DsbD (nDsbD), introduces frustration ultimately influencing protein function. In oxidized nDsbD, local frustration disrupts the packing of the protective cap-loop region against the active site allowing loop opening. By contrast, in reduced nDsbD the cap loop is rigid, always protecting the active-site thiols from the oxidizing environment of the periplasm. Our results point towards an intricate coupling between the dynamics of the active-site cysteines and of the cap loop which modulates the association reactions of nDsbD with its partners resulting in optimized protein function.

scholarly journals Local frustration determines loop opening during the catalytic cycle of an oxidoreductase

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Lukas S Stelzl ◽  
Despoina AI Mavridou ◽  
Emmanuel Saridakis ◽  
Diego Gonzalez ◽  
Andrew J Baldwin ◽  
...  
Keyword(s):  
Active Site ◽  
Binding Sites ◽  
Protein Function ◽  
Catalytic Cycle ◽  
Biomolecular Recognition ◽  
Competing Interactions ◽  
Protein Binding Sites ◽  
Loop Region ◽  
Cysteine Thiols ◽  
Small Chemical

Local structural frustration, the existence of mutually exclusive competing interactions, may explain why some proteins are dynamic while others are rigid. Frustration is thought to underpin biomolecular recognition and the flexibility of protein-binding sites. Here, we show how a small chemical modification, the oxidation of two cysteine thiols to a disulfide bond, during the catalytic cycle of the N-terminal domain of the key bacterial oxidoreductase DsbD (nDsbD), introduces frustration ultimately influencing protein function. In oxidized nDsbD, local frustration disrupts the packing of the protective cap-loop region against the active site allowing loop opening. By contrast, in reduced nDsbD the cap loop is rigid, always protecting the active-site thiols from the oxidizing environment of the periplasm. Our results point toward an intricate coupling between the dynamics of the active-site cysteines and of the cap loop which modulates the association reactions of nDsbD with its partners resulting in optimized protein function.

scholarly journals Heavy Metals and Human Health: Possible Exposure Pathways and the Competition for Protein Binding Sites

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 6060
Author(s):  
Danuta Witkowska ◽  
Joanna Słowik ◽  
Karolina Chilicka
Keyword(s):  
Heavy Metals ◽  
Human Health ◽  
Toxic Metals ◽  
Binding Sites ◽  
Protein Function ◽  
Protein Binding Sites ◽  
Biochemical Effects ◽  
Native Proteins ◽  
Global Problems ◽  
Physiological And Biochemical

Heavy metals enter the human body through the gastrointestinal tract, skin, or via inhalation. Toxic metals have proven to be a major threat to human health, mostly because of their ability to cause membrane and DNA damage, and to perturb protein function and enzyme activity. These metals disturb native proteins’ functions by binding to free thiols or other functional groups, catalyzing the oxidation of amino acid side chains, perturbing protein folding, and/or displacing essential metal ions in enzymes. The review shows the physiological and biochemical effects of selected toxic metals interactions with proteins and enzymes. As environmental contamination by heavy metals is one of the most significant global problems, some detoxification strategies are also mentioned.

SitePrint: Three-Dimensional Pharmacophore Descriptors Derived from Protein Binding Sites for Family Based Active Site Analysis, Classification, and Drug Design.

ChemInform ◽  
2005 ◽  
Vol 36 (9) ◽  
Author(s):  
James R. Arnold ◽  
Keith W. Burdick ◽  
Scott C.-H. Pegg ◽  
Samuel Toba ◽  
Michelle L. Lamb ◽  
...  
Keyword(s):  
Drug Design ◽  
Protein Binding ◽  
Active Site ◽  
Binding Sites ◽  
Three Dimensional ◽  
Protein Binding Sites ◽  
Site Analysis ◽  
Family Based

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.

Predicting the Strength of Stacking Interactions Between Heterocycles and Aromatic Amino Acid Side Chains

2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler
Keyword(s):  
Amino Acid ◽  
Binding Sites ◽  
Aromatic Amino Acid ◽  
Aromatic Amino Acids ◽  
Biologically Active ◽  
Side Chains ◽  
Stacking Interactions ◽  
Inhibitor Binding ◽  
Protein Binding Sites ◽  
Amino Acid Side Chains

<p>Despite the ubiquity of stacking interactions between heterocycles and aromatic amino acids in biological systems, our ability to predict their strength, even qualitatively, is limited. Based on rigorous <i>ab initio</i> data, we have devised a simple predictive model of the strength of stacking interactions between heterocycles commonly found in biologically active molecules and the amino acid side chains Phe, Tyr, and Trp. This model provides rapid predictions of the stacking ability of a given heterocycle based on readily-computed heterocycle descriptors. We show that the values of these descriptors, and therefore the strength of stacking interactions with aromatic amino acid side chains, follow simple predictable trends and can be modulated by changing the number and distribution of heteroatoms within the heterocycle. This provides a simple conceptual model for understanding stacking interactions in protein binding sites and optimizing inhibitor binding in drug design.</p>

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