In Silico Discovery of a Compound with Nanomolar Affinity to Antithrombin Causing Partial Activation and Increased Heparin Affinity

Abstract

The medical and socioeconomic relevance of thromboembolic disorders promotes an ongoing effort to develop new anticoagulants. Heparin is widely used as activator of antithrombin but incurs side effects. We screened a large database in silico to find alternative molecules and predicted d-myo-inositol 3,4,5,6-tetrakisphosphate (TMI) to strongly interact with antithrombin. Isothermal titration calorimetry confirmed a TMI affinity of 45 nM, higher than the heparin affinity (273 nM). Functional studies, fluorescence analysis, and citrullination experiments revealed that TMI induced a partial activation of antithrombin that facilitated the interaction with heparin and low affinity heparins. TMI improved antithrombin inhibitory function of plasma from homozygous patients with antithrombin deficiency with a heparin binding defect and also in a model with endothelial cells. Our in silico screen identified a new, non-polysaccharide scaffold able to interact with the heparin binding domain of antithrombin. The functional consequences of this interaction were experimentally characterized and suggest potential anticoagulant therapeutic applications.

The Need for an Integrated Computational/Experimental Approach in the Discovery and Design of New Drugs

“…Nevertheless, recent results demonstrate the discovery using Virtual Screening (VS) of a novel molecular scaffold [5], different to the previous ones based on heparin. Using this alternate approach, a large database of millions of chemical compounds is screened insilico and affinity-ranking is used to identify some at least weaklyapproach to tap into the wealth of available structural information [8,9].…”

A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

“…For our evaluations, three different ligand-protein cases are chosen, whose ligands conveniently represent chemical diversity of large compound databases. They are referred to as ligands A, B, and C. Ligand A is a blood clotting cofactor recently discovered by us [19]. Ligand B and ligand C have been extracted from their Protein Data Bank [20] complexes with the respective IDS 2 byr and 3 p 4 w .…”

Application of Computational Drug Discovery Techniques for Designing New Drugs against Zika Virus

“…The available crystal structures from parts of the virus and new homology models might be already used as an early state of a computational protocol. More advanced docking techniques, including Blind Docking simulations could be subsequently applied to process large databases of compound libraries [7][8][9][10][11]. Ligand-based virtual screening (LBVS) methods might be also helpful in the search of new drugs against ZIKV since their performance does not depend directly on the availability of crystallographic structures of the protein targets.…”