Identification of a Small Molecule That Modulates Platelet Glycoprotein Ib-von Willebrand Factor Interaction

Broos, Katrijn; Trekels, Mieke; Jose, Rani A.; Demeulemeester, Jonas; Vandenbulcke, Aline; Vandeputte, Nele; Venken, Tom; Egle, Brecht; Borggraeve, Wim M. De; Deckmyn, Hans; Maeyer, Marc De

doi:10.1074/jbc.m111.311431

Cited by 12 publications

(10 citation statements)

References 68 publications

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“…Aspirin, exerting inhibitory effects on platelet activation by acetylating the serine 529 residue of cyclooxygenase (COX), reduces the risk of myocardial infarction and stroke, and is thus widely used in the prevention and treatment of cardiovascular diseases. 4 , 5 However, individual variations in the platelet response to aspirin limits its use in some patients, including patients who experience ischemic events despite regular aspirin therapy. 6 – 8 …”

Section: Introductionmentioning

confidence: 99%

Predictors of high on-aspirin platelet reactivity in elderly patients with coronary artery disease

Zhang

Liu

McCaffrey

et al. 2017

CIA

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ObjectivesPrevious studies have illustrated the link between high on-aspirin platelet reactivity (HAPR) with increasing thrombotic risks. The aim of our study was to investigate relative risk factors of HAPR in elderly patients with coronary artery disease.MethodsElderly, hospitalized coronary artery disease patients on regular aspirin treatment were enrolled from January 2014 to September 2016. Medical records of each patient were collected, including demographic information, cardiovascular risk factors, concomitant drugs and routine biological parameters. Arachidonic acid (AA, 0.5 mg/mL) and adenosine diphosphate (ADP, 5 µmol/L) induced platelet aggregation were measured via light transmission assay (LTA) to evaluate antiplatelet responses, referred as LTA–AA and LTA–ADP.ResultsA total of 275 elderly patients were included, with mean age of 77.2±8.1 years, and males accounted for 81.8%. HAPR was defined as LTA–AA in the upper quartile of the enrolled population. HAPR patients tended to have lower renal function (P=0.052). Higher serum uric acid (SUA) level, as well as lower platelet count, hemoglobin and hematocrit were observed in HAPR patients, with a higher proportion of diuretics use (P<0.05). Multivariate analysis revealed that SUA (OR: 1.004, 95% CI: 1.000–1.007, P=0.048), platelet count (OR: 0.994, 95% CI: 0.989–1.000, P=0.045), hematocrit (OR: 0.921, 95% CI: 0.864–0.981, P=0.011) and concomitant P2Y12 receptor inhibitors use (OR: 1.965, 95% CI: 1.075–3.592, P=0.028) were correlated with HAPR. Spearman’s correlation analysis demonstrated an inverse association of LTA–AA with hematocrit (r=−0.234, P<0.001), hemoglobin (r=−0.209, P<0.001) and estimated glomerular filtration rate (r=−0.132, P=0.031).ConclusionSUA, platelet count, hematocrit and P2Y12 receptor inhibitors use were independently correlated with HAPR. These parameters might provide novel therapeutic targets for optimizing antiplatelet therapy.

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Section: Introductionmentioning

confidence: 99%

Predictors of high on-aspirin platelet reactivity in elderly patients with coronary artery disease

Zhang

Liu

McCaffrey

et al. 2017

CIA

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“…The molecular access system (MACCS) fingerprint [81] is one of the most popular molecular fingerprint [15,16]. Additionally, MACCS fingerprints are routinely used to improve the VS hit rate by identifying structural analogs of hit compounds [52,[90][91][92]. Additionally, MACCS fingerprints are routinely used to improve the VS hit rate by identifying structural analogs of hit compounds [52,[90][91][92].…”

Section: Similarity Search -Molecular Dockingmentioning

confidence: 99%

Hierarchical virtual screening approaches in small molecule drug discovery

Kumar¹,

Zhang²

2015

Methods

140

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Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.

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“…A challenging PPI inhibitor design was reported by Broos et al [206] in which the proteins that interact change the conformation upon binding. In such cases, the inhibitors may not bind to the PPI interface, rather, they bind near the PPI interface.…”

Section: Identification Of Hot Spots On Proteins and Docking In Ppimentioning

confidence: 99%

“…Note the marked oval shape where there is a change in the conformation between the free and bound states of GPIbα. This region is the most probable hot spot on the protein to be involved in binding of a PPI inhibitor [206]. PyMol (Schrodinger LLC) was used to generate the figure based on the information from Broos et al [206].…”

Section: Identification Of Hot Spots On Proteins and Docking In Ppimentioning

confidence: 99%

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors

Sable

Jois

2015

Molecules

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Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

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Identification of a Small Molecule That Modulates Platelet Glycoprotein Ib-von Willebrand Factor Interaction

Cited by 12 publications

References 68 publications

Predictors of high on-aspirin platelet reactivity in elderly patients with coronary artery disease

Predictors of high on-aspirin platelet reactivity in elderly patients with coronary artery disease

Hierarchical virtual screening approaches in small molecule drug discovery

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors

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