scholarly journals The structure of SALSA/DMBT1 SRCR domains reveal the conserved ligand-binding mechanism of the ancient SRCR-fold

2019 ◽  
Author(s):  
Martin P. Reichhardt ◽  
Vuokko Loimaranta ◽  
Susan M. Lea ◽  
Steven Johnson
Keyword(s):  
Ligand Binding ◽  
Scavenger Receptor ◽  
Cation Binding ◽  
Binding Mechanism ◽  
Ligand Interaction ◽  
Srcr Domain ◽  
Binding Interface ◽  
Cation Binding Site ◽  
Ligand Interactions ◽  
High Level

AbstractThe scavenger receptor cysteine-rich (SRCR) family of proteins comprise more than 20 membrane-associated and secreted molecules. Characterised by the presence of one or more copies of the ~110 amino acid SRCR domain, this class of proteins have widespread functions as anti-microbial molecules, scavenger- and signalling-receptors. Despite the high level of structural conservation of SRCR domains, no molecular basis for ligand interaction has been described. The SRCR protein SALSA, also known as dmbt1/gp340, is a key player in mucosal immunology. Based on detailed structures of the SALSA SRCR domains 1 and 8, we here reveal a novel universal ligand binding mechanism for SALSA ligands. The binding interface incorporates a dual cation binding site, which is highly conserved across the SRCR super family. Along with the well-described cation dependency on most SRCR domain-ligand interactions, our data suggest that the binding mechanism described for the SALSA SRCR domains is applicable to all SRCR domains. We thus propose to have identified in SALSA a conserved functional mechanism for ligand recognition by the SRCR class of proteins.

scholarly journals Structures of SALSA/DMBT1 SRCR domains reveal the conserved ligand-binding mechanism of the ancient SRCR fold

2020 ◽  
Vol 3 (4) ◽  
pp. e201900502 ◽  
Author(s):  
Martin P Reichhardt ◽  
Vuokko Loimaranta ◽  
Susan M Lea ◽  
Steven Johnson
Keyword(s):  
Ligand Binding ◽  
Scavenger Receptor ◽  
Structural Data ◽  
Cation Binding ◽  
Binding Mechanism ◽  
Ligand Interaction ◽  
Srcr Domain ◽  
Binding Interface ◽  
Cation Binding Site ◽  
High Level

The scavenger receptor cysteine-rich (SRCR) family of proteins comprises more than 20 membrane-associated and secreted molecules. Characterised by the presence of one or more copies of the ∼110 amino-acid SRCR domain, this class of proteins have widespread functions as antimicrobial molecules, scavenger receptors, and signalling receptors. Despite the high level of structural conservation of SRCR domains, no unifying mechanism for ligand interaction has been described. The SRCR protein SALSA, also known as DMBT1/gp340, is a key player in mucosal immunology. Based on detailed structural data of SALSA SRCR domains 1 and 8, we here reveal a novel universal ligand-binding mechanism for SALSA ligands. The binding interface incorporates a dual cation-binding site, which is highly conserved across the SRCR superfamily. Along with the well-described cation dependency on most SRCR domain–ligand interactions, our data suggest that the binding mechanism described for the SALSA SRCR domains is applicable to all SRCR domains. We thus propose to have identified in SALSA a conserved functional mechanism for the SRCR class of proteins.

Epitopes of adhesion-perturbing monoclonal antibodies map within a predicted alpha-helical domain of the integrin beta 1 subunit

1997 ◽  
Vol 110 (20) ◽  
pp. 2619-2628
Author(s):  
D.T. Shih ◽  
D. Boettiger ◽  
C.A. Buck
Keyword(s):  
Ligand Binding ◽  
Critical Role ◽  
Alpha Helix ◽  
Cation Binding ◽  
Affinity Column ◽  
Integrin Subunit ◽  
Amino Acid Residues ◽  
Helix Formation ◽  
Ligand Interactions ◽  
Integrin Ligand

Several recent studies have demonstrated the involvement of various domains of the beta 1 integrin subunit in ligand binding. Thus, specific amino acids have been shown to be important in divalent cation binding, and others have been implicated by peptide crosslinking to play an intimate role in integrin-ligand interactions. Added to these data are previous observations that a group of adhesion-blocking anti-chicken beta 1 antibodies mapped within the first 160 amino acid residues of the subunit. These observations suggested that this region plays a critical role in integrin ligand recognition. In order to further define the domain in which the epitopes for these antibodies are clustered, a series of mouse/chicken chimeric beta 1 constructs were examined for their reactivity with each of these antibodies. Most of the antibodies recognize a region between residues 124 to 160 of the chicken beta 1 subunit. Computer modeling predicted a possible amphipathic alpha-helical configuration for the region between residues 141 to 160. Consistent with this prediction, circular dichroism and NMR analysis revealed a tendency for a synthetic peptide containing these residues to form an alpha-helix. The significance of this structural characteristic was demonstrated by a mutation at residue 149 that disrupted the alpha-helix formation and resulted in a loss of the ability to form heterodimers with alpha subunits, localize to focal contacts, or be transported to the cell surface. The direct involvement of residues 141 to 160 in ligand binding was supported by the ability of a peptide with this sequence to elute integrins from a fibronectin affinity column. Thus, our data suggest that residues 141 to 160 of the integrin beta 1 subunit, when arranged in an alpha-helix configuration, participate in ligand binding.

scholarly journals Graphlet signature-based scoring method to estimate protein–ligand binding affinity

2014 ◽  
Vol 1 (4) ◽  
pp. 140306 ◽  
Author(s):  
Omkar Singh ◽  
Kunal Sawariya ◽  
Polamarasetty Aparoy
Keyword(s):  
Hydrogen Bond ◽  
Ligand Binding ◽  
Interaction Networks ◽  
Scoring Method ◽  
Ligand Interaction ◽  
Ligand Affinity ◽  
Protein Ligand Interactions ◽  
Residue Interaction ◽  
Ligand Interactions ◽  
Cox 2

Over the years, various computational methodologies have been developed to understand and quantify receptor–ligand interactions. Protein–ligand interactions can also be explained in the form of a network and its properties. The ligand binding at the protein-active site is stabilized by formation of new interactions like hydrogen bond, hydrophobic and ionic. These non-covalent interactions when considered as links cause non-isomorphic sub-graphs in the residue interaction network. This study aims to investigate the relationship between these induced sub-graphs and ligand activity. Graphlet signature-based analysis of networks has been applied in various biological problems; the focus of this work is to analyse protein–ligand interactions in terms of neighbourhood connectivity and to develop a method in which the information from residue interaction networks, i.e. graphlet signatures, can be applied to quantify ligand affinity. A scoring method was developed, which depicts the variability in signatures adopted by different amino acids during inhibitor binding, and was termed as GSUS (graphlet signature uniqueness score). The score is specific for every individual inhibitor. Two well-known drug targets, COX-2 and CA-II and their inhibitors, were considered to assess the method. Residue interaction networks of COX-2 and CA-II with their respective inhibitors were used. Only hydrogen bond network was considered to calculate GSUS and quantify protein–ligand interaction in terms of graphlet signatures. The correlation of the GSUS with pIC 50 was consistent in both proteins and better in comparison to the Autodock results. The GSUS scoring method was better in activity prediction of molecules with similar structure and diverse activity and vice versa. This study can be a major platform in developing approaches that can be used alone or together with existing methods to predict ligand affinity from protein–ligand complexes.

scholarly journals Homology modelling of integrin EF-hands. Evidence for widespread use of a conserved cation-binding site

1992 ◽  
Vol 285 (1) ◽  
pp. 325-331 ◽  
Author(s):  
D S Tuckwell ◽  
A Brass ◽  
M J Humphries
Keyword(s):  
Ligand Binding ◽  
Homology Modelling ◽  
Cation Binding ◽  
Binding Motif ◽  
Binding Model ◽  
Bivalent Cation ◽  
Cation Binding Site ◽  
Ef Hand ◽  
Ef Hands

Integrin alpha-subunits contain three or four peptide sequences that are similar to the EF-hand, a 13-residue bivalent cation-binding motif found in calmodulin and parvalbumin. The integrin sequences differ from classical EF-hands in that they lack a co-ordinating residue at position 12. One hypothesis to explain integrin-ligand binding is that aspartate-containing recognition sequences in integrin ligands, which bind at or near to the EF-hand-like sequences, may take the place of the missing residue and co-ordinate directly to the bound cation. In this report, homology modelling of integrin EF-hand-like sequences has been performed using the X-ray structure of calmodulin as a template in order to assess the functional activity of the integrin sequences. In the calmodulin-integrin hybrid structures, integrin EF-hand-like sequences were able to retain cations whereas control sequences did not. Structural analyses demonstrated that the integrin sequences in the hybrid proteins closely resembled conventional EF-hands. The integrin sequences are therefore highly likely to bind Ca2+ ions in vivo, a prerequisite for the ligand-binding model. Database searching with a matrix derived from known integrin EF-hand-like sequences has been used to identify other proteins containing the integrin EF-hand-like motif. Annexin V (anchorin CII), atrial natriuretic peptide receptors and the 70 kDa heat-shock protein were identified by the matrix; the functions of these proteins are known from previous studies to be bivalent cation-dependent. These findings suggest that the integrin EF-hand-like sequence may be a more common motif than originally thought.

scholarly journals SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Surendra Kumar ◽  
Mi-hyun Kim
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Scoring Functions ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Fingerprint Pattern ◽  
Comparable Performance ◽  
Direct Interpretation ◽  
Benchmark Datasets ◽  
Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

scholarly journals Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional

2021 ◽  
Author(s):  
Lennart Gundelach ◽  
Christofer S Tautermann ◽  
Thomas Fox ◽  
Chris-Kriton Skylaris
Keyword(s):  
Drug Discovery ◽  
Ligand Binding ◽  
Dft Calculations ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Ligand Interaction ◽  
Exchange Correlation ◽  
Ligand Free ◽  
Protein Ligand Interaction ◽  
Binding Free Energies

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of...

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