Experiment-Guided Molecular Modeling of Protein–Protein Complexes Involving GPCRs

Experimental structure determination for G protein coupled receptors (GPCRs) and especially their complexes with protein and peptide ligands is at its infancy. In the absence of complex structures, molecular modeling and docking play a large role not only by providing a proper 3D context for interpretation of biochemical and biophysical data, but also by prospectively guiding experiments. Experimentally confirmed restraints may help improve the accuracy and information content of the computational models. Here we present a hybrid molecular modeling protocol that integrates heterogeneous experimental data with force field-based calculations in the stochastic global optimization of the conformations and relative orientations of binding partners. Some experimental data, such as pharmacophore-like chemical fields or disulfide-trapping restraints, can be seamlessly incorporated in the protocol, while other types of data are more useful at the stage of solution filtering. The protocol was successfully applied to modeling and design of a stable construct that resulted in crystallization of the first complex between a chemokine and its receptor. Examples from this work are used to illustrate the steps of the protocol. The utility of different types of experimental data for modeling and docking is discussed and caveats associated with data misinterpretation are highlighted

A graph-based approach to construct target-focused libraries for virtual screening

BACKGROUND: Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family. METHODS: Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns. RESULTS: We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated. CONCLUSIONS: eSynth can successfully reconstruct chemically feasible molecules from molecular fragments. Furthermore, in a procedure mimicking the real application, where one expects to discover novel compounds based on a small set of already developed bioactives, eSynth is capable of generating diverse collections of molecules with the desired activity profiles. Thus, we are very optimistic that our effort will contribute to targeted drug discovery. eSynth is freely available to the academic community at www.brylinski.org/content/molecular-synthesis. [Figure: see text

Modeling GPCRs

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Molecular characterization of two endothelin pathways in East African cichlid fishes

The adaptive radiations of cichlid fishes in East Africa have been associated with the acquisition of evolutionary novelties as well as the ecological opportunities existing in the East African Great lakes. Two remarkable evolutionary innovations are the pharyngeal jaw apparatus, found in all cichlid species, and the anal fin egg-spots of mouthbrooding cichlids. Based on their conserved functions during the development of both the jaw apparatus and pigmentation, the endothelin ligands and receptors form a putative link between these naturally and sexually selected traits. Here we study the evolutionary history of four members of two endothelin pathways (Edn1/EdnrAa and Edn3b/EdnrB1a) to elucidate their possible roles during the evolution and development of key innovations in East African cichlids species. The analyses performed on partial sequences (ca. 6,000 bp per taxon) show that all four endothelin family members evolved under purifying selection, although both ligands are characterized by an accelerated rate of protein evolution in comparison to the receptors. In accordance with earlier findings, we show that the mature protein sequence of Edn1 and Edn3 are highly conserved, also in cichlids, whereas the preproendothelin parts are variable indicating relaxed selective constraints. In the receptors, nonsynonymous substitutions were mainly found in the ligand-binding domains suggesting functional divergence. Gene expression assays with Real-Time PCR indeed reveal that the two studied endothelin pathways are expressed in the cichlid pharyngeal jaw and in the haplochromine egg-spot (among other pigment-cell containing tissues), suggesting their involvement during morphogenesis of naturally and sexually selected traits in cichlids