Experimentally Validated Novel Factor XIIa Inhibitors Identified by Docking and Quantum Chemical Post-processing

New Triazole-Based Potent Inhibitors of Human Factor XIIa as Anticoagulants

Factor XIIa (FXIIa) functions as a plasma serine protease within the contact activation pathway. Various animal models have indicated a substantial role for FXIIa in thromboembolic diseases. Interestingly, individuals and animals with FXII deficiency seem to maintain normal hemostasis. Consequently, inhibiting FXIIa could potentially offer a viable therapeutic approach for achieving effective and safer anticoagulation without the bleeding risks associated with the existing anticoagulants. Despite the potential, only a limited number of small molecule inhibitors targeting human FXIIa have been documented. Thus, we combined a small library of 32 triazole and triazole-like molecules to be evaluated for FXIIa inhibition by using a chromogenic substrate hydrolysis assay under physiological conditions. Initial screening at 200 μM involved 18 small molecules, revealing that 4 molecules inhibited FXIIa more than 20%. In addition to being the most potent inhibitor identified in the first round, inhibitor 8 also exhibited a substantial margin of selectivity against related serine proteases, including factors XIa, Xa, and IXa. However, the molecule also inhibited thrombin with a similar potency. It also prolonged the clotting time of human plasma, as was determined in the activated partial thromboplastin time and prothrombin time assays. Subsequent structure-activity relationship studies led to the identification of several inhibitors with submicromolar activity, among which inhibitor 22 appears to demonstrate significant selectivity not only over factors IXa, Xa, and XIa, but also over thrombin. In summary, this study introduces novel triazole-based small molecules, specifically compounds 8 and 22, identified as potent and selective inhibitors of human FXIIa. The aim is to advance these inhibitors for further development as anticoagulants to provide a more effective and safer approach to preventing and/or treating thromboembolic diseases.

Docking and other computing tools in drug design against SARS-CoV-2

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.