Thrombin inhibitors identified by computer-assisted multiparameter design

Abstract

Here, we present a series of thrombin inhibitors that were generated by using powerful computer-assisted multiparameter optimization process. The process was organized in design cycles, starting with a set of randomly chosen molecules. Each cycle combined combinatorial synthesis, multiparameter characterization of compounds in a variety of bioassays, and algorithmic processing of the data to devise a set of compounds to be synthesized in the next cycle. The identified lead compounds exhibited thrombin inhibitory constants in the lower nanomolar range. They are by far the most selective synthetic thrombin inhibitors, with selectivities of >100,000-fold toward other proteases such as Factor Xa, Factor XIIa, urokinase, plasmin, and Plasma kallikrein. Furthermore, these compounds exhibit a favorable profile, comprising nontoxicity, high metabolic stability, low serum protein binding, good solubility, high anticoagulant activity, and a slow and exclusively renal elimination from the circulation in a rat model. Finally, x-ray crystallographic analysis of a thrombin-inhibitor complex revealed a binding mode with a neutral moiety in the S1 pocket of thrombin.crystallographic structure ͉ drug design ͉ early adsorption ͉ toxicity ͉ genetic algorithm

Tick anti-hemostatics: targets for future vaccines and therapeutics

“…This can be ascribed to the vast number of criteria these compounds must meet before being allowed for use clinically, such as high selectivity, metabolic stability, low serum protein binding, low toxicity and slow elimination from the blood stream, among others [16]. To date, only preliminary validation of TAP and ixolaris as possible therapeutics has been performed in vivo using animal models.…”

“…Current anti-thrombotic agents have limitations and the development of new drugs continues to be researched actively [15]. The various tick thrombin inhibitors that interact with either the active site and/or exosite 1 are thus valuable as research tools in the rational design of small-molecule [16] and peptide [17,18] anti-thrombotics. Currently, only the synthetic derivative of hirudin, from the leech Hirudo medicinalis, has been approved for clinical use [15,19].…”

Novel Analytic Criteria and Effective Plate Designs for Quality Control in Genome-Scale RNAi Screens

“…11,[13][14][15][16][17][18][19] However, this criterion does not consider the fact that positive controls in different experiments may have different sizes of effects. As a result, applying the same criterion to positive controls with different sizes of effects will lead to misleading results.…”

“…11,[13][14][15][16][17][18][19][20][21][22] Signal-tobackground ratio and signal-to-noise ratio have problems in capturing data variability; consequently, QC results reached using signal-to-background ratio and signal-to-noise ratio are misleading. 15,19,21,23 Signal window, assay variability ratio, and Z factor all capture data variability.…”

Integrating Experimental and Analytic Approaches to Improve Data Quality in Genome-wide RNAi Screens

“…Currently, a Z-factorbased criterion is widely used for evaluating data quality. 12,17,[21][22][23][24][25][26][27] However, the probabilistic and statistical basis of Z factor is not as strong as that of strictly standardized mean difference (SSMD). [28][29][30] The Z-factor-based criterion is unable to obtain consistent evaluation results for positive controls with different strengths of effects.…”