Structure-Based design, synthesis and sAR of a novel series of thiopheneamidine urokinase plasminogen activator inhibitors

Urokinase plasminogen activator as an anti-metastasis target: inhibitor design principles, recent amiloride derivatives, and issues with human/mouse species selectivity

The urokinase plasminogen activator (uPA) is a widely studied anticancer drug target with multiple classes of inhibitors reported to date. Many of these inhibitors contain amidine or guanidine groups, while others lacking these groups show improved oral bioavailability. Most of the X-ray co-crystal structures of small molecule uPA inhibitors show a key salt bridge with the side chain carboxylate of Asp189 in the S1 pocket of uPA. This review summarises the different classes of uPA inhibitors, their binding interactions and experimentally measured inhibitory potencies and highlights species selectivity issues with attention to recently described 6-substituted amiloride and 5‑N,N-(hexamethylene)amiloride (HMA) derivatives.

Dual vicinal functionalisation of heterocycles via an interrupted Pummerer coupling/[3,3]-sigmatropic rearrangement cascade

A dual vicinal functionalisation cascade involving the union of heterocycles and allyl sulfoxides is described. In particular, the approach provides efficient one-step access to biologically relevant and synthetically important C3 thio, C2 carbo substituted indoles. The reaction operates under mild, metal free conditions and without directing groups, via an interrupted Pummerer coupling of activated allyl sulfoxides, generating allyl heteroaryl sulfonium salts that are predisposed to a charge accelerated [3,3]-sigmatropic rearrangement.

Application of molecular modeling to urokinase inhibitors development

Urokinase-type plasminogen activator (uPA) plays an important role in the regulation of diverse physiologic and pathologic processes. Experimental research has shown that elevated uPA expression is associated with cancer progression, metastasis, and shortened survival in patients, whereas suppression of proteolytic activity of uPA leads to evident decrease of metastasis. Therefore, uPA has been considered as a promising molecular target for development of anticancer drugs. The present study sets out to develop the new selective uPA inhibitors using computer-aided structural based drug design methods. Investigation involves the following stages: computer modeling of the protein active site, development and validation of computer molecular modeling methods: docking (SOL program), postprocessing (DISCORE program), direct generalized docking (FLM program), and the application of the quantum chemical calculations (MOPAC package), search of uPA inhibitors among molecules from databases of ready-made compounds to find new uPA inhibitors, and design of new chemical structures and their optimization and experimental examination. On the basis of known uPA inhibitors and modeling results, 18 new compounds have been designed, calculated using programs mentioned above, synthesized, and tested in vitro. Eight of them display inhibitory activity and two of them display activity about 10 μM.

Insight into the Structural Requirements of Urokinase-Type Plasminogen Activator Inhibitors Based on 3D QSAR CoMFA/CoMSIA Models

Urokinase-type plasminogen activator (uPA), a trypsin-like serine protease, has been implicated in large number of malignancies, tumor cell invasion, angiogenesis and metastasis; hence, the potent and selective inhibitors of uPA may therefore be therapeutically useful drugs for treatment of various forms of cancer. A three-dimensional quantitative structure-activity relationship (3D QSAR) study was performed on five different chemical series reported as selective uPA inhibitors employing comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) techniques to investigate the structural requirements for substrates and derive a predictive model that may be used for the design of novel uPA inhibitors. ClogP has been used as an additional descriptor in the CoMFA analysis to study the effects of lipophilic parameters on activity. Inclusion of ClogP did not improve the models significantly and exhibited comparable correlation coefficients with CoMFA steric and electrostatic models. 3D QSAR models were derived for 2-pyridinylguanidines (training set N = 25, test set N = 8), 4-aminoarylguanidines and 4-aminoarylbenzamidines (training set N = 29, test set N = 8), thiophene-2-carboxamindines (training set N = 64, test set N = 19), 2-naphthamidines (training set N = 32, test set N = 8), and 1-isoquinolinylguanidines (training set N = 29, test set N = 7). The CoMFA models with steric and electrostatic fields exhibited r(2)(cv) 0.452-0.722, r(2)(ncv) 0.812-0.986, r(2)(pred) 0.597-0.870, whereas CoMFA ClogP models showed r(2)(cv) 0.420-0.707, r(2)(ncv) 0.849-0.957, r(2)(pred) 0.600-0.870. The CoMSIA models displayed r(2)(cv) 0.663-0.729, r(2)(ncv) 0.909-0.998, r(2)(pred) 0.554-0.855. 3D contour maps generated from these models were analyzed individually, which provides the regions in space where interactive fields may influence the activity. The superimposition of contour maps on the active site of serine proteases additionally helps in understanding the structural requirements of these inhibitors. Further, the predictive ability of 3D QSAR models was affirmed by predicting the activity of novel 2-naphthamidines. 3D QSAR models developed may be used in designing and predicting the uPA inhibitory activity of novel molecules.