We have designed four generations of a low molecular weight fragment library for use in NMR-based screening against protein targets. The library initially contained 723 fragments which were selected manually from the Available Chemicals Directory. A series of in silico filters and property calculations were developed to automate the selection process, allowing a larger database of 1.79 M available compounds to be searched for a further 357 compounds that were added to the library. A kinase binding pharmacophore was then derived to select 174 kinase-focused fragments. Finally, an additional 61 fragments were selected to increase the number of different pharmacophores represented within the library. All of the fragments added to the library passed quality checks to ensure they were suitable for the screening protocol, with appropriate solubility, purity, chemical stability, and unambiguous NMR spectrum. The successive generations of libraries have been characterized through analysis of structural properties (molecular weight, lipophilicity, polar surface area, number of rotatable bonds, and hydrogen-bonding potential) and by analyzing their pharmacophoric complexity. These calculations have been used to compare the fragment libraries with a drug-like reference set of compounds and a set of molecules that bind to protein active sites. In addition, an analysis of the overall results of screening the library against the ATP binding site of two protein targets (HSP90 and CDK2) reveals different patterns of fragment binding, demonstrating that the approach can find selective compounds that discriminate between related binding sites.

The three-dimensional quantitative structure-activity relationship (3D-QSAR) approach using comparative molecular field analysis (CoMFA) was applied to an extensive series of 305 varied diarylheterocyclic derivatives known as COX-2 selective inhibitors. X-ray crystal structure of COX-2 bound with SC-558, a selective COX-2 inhibitor, was used to derive the putative bioactive conformation of these inhibitors. Five statistically significant models were obtained from the randomly constituted training sets (229 compounds) and subsequently validated with the corresponding test sets (76 compounds). The best predictive model (n = 229, q(2) = 0.714, N = 8, r(2) = 0.905, s = 0.291, F = 261.545) was selected for further comparison of the CoMFA contour maps obtained for steric, electrostatic, and lipophilic fields with the enzyme structure. The high level of compatibility with the COX-2 enzyme topology shows the great accuracy of this model that can predict inhibitory activities for a wide range of compounds and offers important structural insight into designing novel antiinflammatory drugs prior to their synthesis.

Bispecific immunoglobulins (Igs) typically contain at least two distinct variable domains (Fv) that bind to two different target proteins. They are conceived to facilitate clinical development of biotherapeutic agents for diseases where improved clinical outcome is obtained or expected by combination therapy compared to treatment by single agents. Almost all existing formats are linear in their concept and differ widely in drug-like and manufacture-related properties. To overcome their major limitations, we designed cross-over dual variable Ig-like proteins (CODV-Ig). Their design is akin to the design of circularly closed repeat architectures. Indeed, initial results showed that the traditional approach of utilizing (G4S) x linkers for biotherapeutics design does not identify functional CODV-Igs. Therefore, we applied an unprecedented molecular modeling strategy for linker design that consistently results in CODV-Igs with excellent biochemical and biophysical properties. CODV architecture results in a circular self-contained structure functioning as a self-supporting truss that maintains the parental antibody affinities for both antigens without positional effects. The format is universally suitable for therapeutic applications targeting both circulating and membrane-localized proteins. Due to the full functionality of the Fc domains, serum half-life extension as well as antibody-or complement-dependent cytotoxicity may support biological efficiency of CODV-Igs. We show that judicious choice in combination of epitopes and paratope orientations of bispecific biotherapeutics is anticipated to be critical for clinical outcome. Uniting the major advantages of alternative bispecific biotherapeutics, CODV-Igs are applicable in a wide range of disease areas for fast-track multi-parametric drug optimization.