A benchmark data set of steroids with known affinity for sex hormone-binding globulin (SHBG) has been widely used to validate popular molecular field-based QSAR techniques. We have expanded the data set by adding a number of nonsteroidal SHBG ligands identified both from the literature and in our previous experimental studies. This updated molecular set has been used herein to develop 4D QSAR models based on "inductive" descriptors and to gain insight into the molecular basis of protein-ligand interactions. Molecular alignment was generated by means of docking active compounds into the active site of the SHBG. Surprisingly, the alignment of the benchmark steroids contradicted the classical ligand-based alignment utilized in previous CoMFA and CoMSIA models yet afforded models with higher statistical significance and predictive power. The resulting QSAR models combined with CoMFA and CoMSiA models as well as structure-based virtual screening allowed discovering several low-micromolar to nanomolar nonsteroidal inhibitors for human SHBG.
"Inductive descriptors (3D) have been derived from the LFER (Linear Free Energy Relationships)-based equations for inductive and steric substituent constants and can be computed for bound atoms, groups and molecules using intra-molecular distances, atomic electronegativities and covalent radii . "
[Show abstract][Hide abstract] ABSTRACT: The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.
"In fact, three out of four featured substances formed only one hydrogen bond, but actually demonstrate higher affinity toward the target, most likely because of more favorable hydrophobic interactions. It should be noted, however, that the affinities of these non-steroidal ligands are 2–4 orders of magnitude lower than that of estradiol, and DHT (Cherkasov et al., 2008). Thus, our in silico analyses have not only established various structural determinants of SHBG–ligand interaction and facilitated the development of a number of new computational screening tools, but have also significantly expanded the set of known SHBG ligands: all of which can be used to fine-tune computational discovery tools for further in silico studies of SHBG in humans and other species. "
[Show abstract][Hide abstract] ABSTRACT: Plasma sex hormone-binding globulin (SHBG) regulates the access of androgens and estrogens to their target tissues and cell types. An SHBG homologue, known as the androgen-binding protein, is expressed in Sertoli cells of many mammalians, but testicular expression of human SHBG is restricted to germ cells. The primary structure of SHBG comprises tandem laminin G-like (LG) domains. The amino-terminal LG-domain includes the steroid-binding site and dimerization interface, and its tertiary structure, resolved in complex with natural and synthetic sex steroids, has revealed unanticipated mechanisms of steroid binding at the atomic level. This LG-domain interacts with fibulin-1D and fibulin-2 in a ligand-specific manner, and this is attributed to the unique way estrogens reside within the steroid-binding site, and the ordering of an otherwise flexible loop structure covering the entrance of the steroid-binding pocket. This mechanism enables estradiol to enhance the sequestration of plasma SHBG by the stroma of some tissues through binding to these extra-cellular matrix-associated proteins. The human SHBG amino-terminal LG-domain also contains several cation-binding sites, and occupancy of a zinc-binding site influences its affinity for estradiol. The complete quaternary structure of SHBG remains unresolved but structural predictions suggest that the carboxy-terminal LG-domains extend laterally from the dimerized amino-terminal LG-domains. The carboxy-terminal LG-domain contains two N-glycosylation sites, but their biological significance remains obscure. Knowledge of the SHBG tertiary structure has helped develop computational techniques based on the use of a "bench-mark data set" of steroid ligands, and created novel drug discovery and toxicology risk assessment platforms.
"For zfSHBG, the same CoMFA and CoMSiA models described above were used. For hSHBG, the same procedure as described above for obtaining the CoMFA and CoMSiA models for zfSHBG was performed using a set of 87 steroids with experimental binding constants for hSHBG (Cherkasov et al., 2008). These models resulted in a total of four more predictors for the voting scheme: CoMFA and CoMSiA estimated pK i for both zfSHBG and hSHBG. "
[Show abstract][Hide abstract] ABSTRACT: Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We also screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [(3)H]5alpha-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 microM concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost.
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