Abstract
BackgroundTraditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target.MethodologyWe developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery.ConclusionsThis article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking.
Highlights
The formation of a fibrin clot at the site of an injury to the wall of a blood vessel is an essential part in stop blood loss after vascular injury
For receptor/ligand complex with crystal structure, the binding site was defined as the grid points around the ligand which were unoccupied by receptor atoms, whereas for a receptor without crystal complex structure, potential binding sites were found based on the shape of the receptor
The nodes cover most of the important enzymes that participate in the clotting cascade, such as thrombin, factor X, factor V, TF, etc
Summary
The formation of a fibrin clot at the site of an injury to the wall of a blood vessel is an essential part in stop blood loss after vascular injury. Conclusions: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking. A novel approach was developed by integrating the predictions based on multi-target docking studies through biological network efficiency analysis to estimate the biological potency[26,29,30,31].
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