scholarly journals Avidity observed between a bivalent inhibitor and an enzyme monomer with a single active site

2021 ◽  
Author(s):  
Shiran Lacham-Hartman ◽  
Yulia Shmidov ◽  
Evette S. Radisky ◽  
Ronit Bitton ◽  
David B. Lukatsky ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Protein Interactions ◽  
Protein Complex ◽  
Binding Sites ◽  
Biological Interactions ◽  
Protein Protein Interactions ◽  
Regulatory Pathways ◽  
Multiple Binding Sites ◽  
Ligand Binding Sites

AbstractAlthough myriad protein–protein interactions in nature use polyvalent binding, in which multiple ligands on one entity bind to multiple receptors on another, to date an affinity advantage of polyvalent binding has been demonstrated experimentally only in cases where the target receptor molecules are clustered prior to complex formation. Here, we demonstrate cooperativity in binding affinity (i.e., avidity) for a protein complex in which an engineered dimer of the amyloid precursor protein inhibitor (APPI), possessing two fully functional inhibitory loops, interacts with mesotrypsin, a soluble monomeric protein that does not self-associate or cluster spontaneously. We found that each inhibitory loop of the purified APPI homodimer was over three-fold more potent than the corresponding loop in the monovalent APPI inhibitor. This observation is consistent with a suggested mechanism whereby the two APPI loops in the homodimer simultaneously and reversibly bind two corresponding mesotrypsin monomers to mediate mesotrypsin dimerization. We propose a simple model for such dimerization that quantitatively explains the observed cooperativity in binding affinity. Binding cooperativity in this system reveals that the valency of ligands may affect avidity in protein–protein interactions including those of targets that are not surface-anchored and do not self-associate spontaneously. In this scenario, avidity may be explained by the enhanced concentration of ligand binding sites in proximity to the monomeric target, which may favor rebinding of the multiple ligand binding sites with the receptor molecules upon dissociation of the protein complex.Impact statementLacham-Hartman et al. demonstrate enhancement of binding affinity through avidity in a complex between a bivalent ligand and a soluble monomeric target with a single binding site. Avidity effects have previously been demonstrated only for clustered receptor molecules presenting multiple binding sites. Our model may explain how polyvalent ligands can agonize or antagonize biological interactions involving nonclustered target molecules that are crucial for intra- and extracellular structural, metabolic, signaling, and regulatory pathways.

scholarly journals Avidity observed between a bivalent inhibitor and an enzyme monomer with a single active site

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0249616
Author(s):  
Shiran Lacham-Hartman ◽  
Yulia Shmidov ◽  
Evette S. Radisky ◽  
Ronit Bitton ◽  
David B. Lukatsky ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Protein Interactions ◽  
Protein Complex ◽  
Binding Sites ◽  
Protein Protein Interactions ◽  
Multiple Receptors ◽  
Ligand Binding Sites ◽  
Multiple Ligands ◽  
Multiple Ligand

Although myriad protein–protein interactions in nature use polyvalent binding, in which multiple ligands on one entity bind to multiple receptors on another, to date an affinity advantage of polyvalent binding has been demonstrated experimentally only in cases where the target receptor molecules are clustered prior to complex formation. Here, we demonstrate cooperativity in binding affinity (i.e., avidity) for a protein complex in which an engineered dimer of the amyloid precursor protein inhibitor (APPI), possessing two fully functional inhibitory loops, interacts with mesotrypsin, a soluble monomeric protein that does not self-associate or cluster spontaneously. We found that each inhibitory loop of the purified APPI homodimer was over three-fold more potent than the corresponding loop in the monovalent APPI inhibitor. This observation is consistent with a suggested mechanism whereby the two APPI loops in the homodimer simultaneously and reversibly bind two corresponding mesotrypsin monomers to mediate mesotrypsin dimerization. We propose a simple model for such dimerization that quantitatively explains the observed cooperativity in binding affinity. Binding cooperativity in this system reveals that the valency of ligands may affect avidity in protein–protein interactions including those of targets that are not surface-anchored and do not self-associate spontaneously. In this scenario, avidity may be explained by the enhanced concentration of ligand binding sites in proximity to the monomeric target, which may favor rebinding of the multiple ligand binding sites with the receptor molecules upon dissociation of the protein complex.

scholarly journals Targeting the cryptic sites: NMR-based strategy to improve protein druggability by controlling the conformational equilibrium

2020 ◽  
Vol 6 (40) ◽  
pp. eabd0480
Author(s):  
Yumiko Mizukoshi ◽  
Koh Takeuchi ◽  
Yuji Tokunaga ◽  
Hitomi Matsuo ◽  
Misaki Imai ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Protein Interactions ◽  
Binding Sites ◽  
Drug Targets ◽  
Conformational Equilibrium ◽  
Wild Type ◽  
Protein Protein Interactions ◽  
Hit Rate ◽  
Open Conformation ◽  
Ligand Binding Sites

Cryptic ligand binding sites, which are not evident in the unligated structures, are beneficial in tackling with difficult but attractive drug targets, such as protein-protein interactions (PPIs). However, cryptic sites have thus far not been rationally pursued in the early stages of drug development. Here, we demonstrated by nuclear magnetic resonance that the cryptic site in Bcl-xL exists in a conformational equilibrium between the open and closed conformations under the unligated condition. While the fraction of the open conformation in the unligated wild-type Bcl-xL is estimated to be low, F143W mutation that is distal from the ligand binding site can substantially elevate the population. The F143W mutant showed a higher hit rate in a phage-display peptide screening, and the hit peptide bound to the cryptic site of the wild-type Bcl-xL. Therefore, by controlling the conformational equilibrium in the cryptic site, the opportunity to identify a PPI inhibitor could be improved.

scholarly journals Hidden partners: Using cross-docking calculations to predict binding sites for proteins with multiple interactions

2018 ◽  
Author(s):  
Nathalie Lagarde ◽  
Alessandra Carbone ◽  
Sophie Sacquin-Mora
Keyword(s):  
Nucleic Acid ◽  
Binding Site ◽  
Protein Interactions ◽  
Binding Sites ◽  
Protein Protein Interactions ◽  
Protein Binding Sites ◽  
Cross Docking ◽  
Multiple Binding Sites ◽  
Multiple Binding ◽  
Docking Calculations

AbstractProtein-protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein-protein interactions. Cross-docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross-docking simulations of 358 proteins with two different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity-sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross-docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, i.e. partners not included in the original cross-docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.AbbreviationsANOVA: ANalysis Of Variance; AUC: Area Under the Curve; Best Interface: BI; CAPRI: Critical Assessment of Prediction of Interactions; CC-D: Complete Cross-Docking; DNA: DesoxyriboNucleic Acid; FDR: False Discovery Rate; FRIres(type): Fraction of each Residue type in the Interface; FP: False Positives; GI: Global Interface; HCMD: Help Cure Muscular Dystrophy; JET: Joint Evolutionary Tree; MAXDo: Molecular Association via Cross Docking; NAI: Nucleic Acid Interface; NPV: Negative Predicted Value; PDB: Protein Data Bank; PIP: Protein Interface Propensity; PiQSi: Protein Quaternary Structure investigation; PPIs: Protein-Protein Interactions; PPV: Positive Predicted Value; Prec.: Precision; PrimI: Primary Interface; RNA: RiboNucleic Acid; ROC: Receiver Operating Characteristic; SecI: Secondary Interface; Sen.: Sensitivity; Spe.: Specificity; TN: True Negatives; TP: True Positives; WCG: World Community Grid.

scholarly journals A Comprehensive Review on Current Advances in Peptide Drug Development and Design

2019 ◽  
Vol 20 (10) ◽  
pp. 2383 ◽  
Author(s):  
Andy Chi-Lung Lee ◽  
Janelle Louise Harris ◽  
Kum Kum Khanna ◽  
Ji-Hong Hong
Keyword(s):  
Drug Development ◽  
Binding Affinity ◽  
Protein Interactions ◽  
Binding Sites ◽  
Drug Targets ◽  
Peptide Drug ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Endogenous Protein ◽  
Binding Interfaces

Protein–protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide–protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide–protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide–protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.

scholarly journals Structural dynamics of the β-coronavirus Mpro protease ligand binding sites

2021 ◽  
Author(s):  
Eunice Cho ◽  
Margarida Rosa ◽  
Ruhi Anjum ◽  
Saman Mehmood ◽  
Mariya Soban ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Protein Interactions ◽  
Binding Sites ◽  
Adaptive Sampling ◽  
Conformational Dynamics ◽  
Current Crisis ◽  
Ligand Binding Sites ◽  
Structural Conservation ◽  
State Models ◽  
Viral Components

Abstractβ-coronaviruses alone have been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a back-up against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensible role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all non-redundant ligand-binding sites available for SARS-CoV2, SARS-CoV and MERS-CoV Mpro. Extensive adaptive sampling has been used to explore conformational dynamics employing convolutional variational auto encoder-based deep learning, and investigates structural conservation of the ligand binding sites using Markov state models across β-coronavirus homologs. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-coronavirus homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.

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