Recent years have brought a flood of interest in developing compounds that selectively degrade protein targets in cells, as exemplified by PROTACs. Fully realizing the promise of PROTACs to transform chemical biology by delivering degraders of diverse and undruggable protein targets has been impeded, however, by the fact that designing a suitable chemical linker between the functional moieties requires extensive trial and error. Here, we describe a structure-based computational method to predict PROTAC activity. We envision that this approach will allow design and optimization of PROTACs for efficient target degradation, selection of E3 ligases best suited for pairing with a given target protein, and understanding the basis by which PROTACs can exhibit different target selectivity than their component warheads..

The sesquiterpenoid juvenile hormone (JH) is vital to insect development and reproduction. Intracellular JH receptors have recently been established as basic helix-loop-helix transcription factor (bHLH)/PAS proteins in Drosophila melanogaster known as germ cell–expressed (Gce) and its duplicate paralog, methoprene-tolerant (Met). Upon binding JH, Gce/Met activates its target genes. Insects possess multiple native JH homologs whose molecular activities remain unexplored, and diverse synthetic compounds including insecticides exert JH-like effects. How the JH receptor recognizes its ligands is unknown. To determine which structural features define an active JH receptor agonist, we tested several native JHs and their nonnative geometric and optical isomers for the ability to bind the Drosophila JH receptor Gce, to induce Gce-dependent transcription, and to affect the development of the fly. Our results revealed high ligand stereoselectivity of the receptor. The geometry of the JH skeleton, dictated by two stereogenic double bonds, was the most critical feature followed by the presence of an epoxide moiety at a terminal position. The optical isomerism at carbon C11 proved less important even though Gce preferentially bound a natural JH enantiomer. The results of receptor-ligand–binding and cell-based gene activation assays tightly correlated with the ability of different geometric JH isomers to induce gene expression and morphogenetic effects in the developing insects. Molecular modeling supported the requirement for the proper double-bond geometry of JH, which appears to be its major selective mechanism. The strict stereoselectivity of Gce toward the natural hormone contrasts with the high potency of synthetic Gce agonists of disparate chemistries.

To date, no suitable vaccine or specific antiviral drug is available to treat Chikungunya viral (CHIKV) fever. Hence, it is essential to identify drug candidates that could potentially impede CHIKV infection. Here, we present the development of a homology model of nsP2 protein based on the crystal structure of the nsP2 protein of Venezuelan equine encephalitis virus (VEEV). The protein modeled was optimized using molecular dynamics simulation; the junction peptides of a nonstructural protein complex were then docked in order to investigate the possible protein-protein interactions between nsP2 and the proteins cleaved by nsP2. The modeling studies conducted shed light on the binding modes, and the critical interactions with the peptides provide insight into the chemical features needed to inhibit the CHIK virus infection. Energy-optimized pharmacophore mapping was performed using the junction peptides. Based on the results, we propose the pharmacophore features that must be present in an inhibitor of nsP2 protease. The resulting pharmacophore model contained an aromatic ring, a hydrophobic and three hydrogen-bond donor sites. Using these pharmacophore features, we screened a large public library of compounds (Asinex, Maybridge, TOSLab, Binding Database) to find a potential ligand that could inhibit the nsP2 protein. The compounds that yielded a fitness score of more than 1.0 were further subjected to Glide HTVS and Glide XP. Here, we report the best four compounds based on their docking scores; these compounds have IDs of 27943, 21362, ASN 01107557 and ASN 01541696. We propose that these compounds could bind to the active site of nsP2 protease and inhibit this enzyme. Furthermore, the backbone structural scaffolds of these four lead compounds could serve as building blocks when designing drug-like molecules for the treatment of Chikungunya viral fever.

PROTACs are molecules that combine a target-binding warhead with an E3 ligase-recruiting moiety; by drawing the target protein into a ternary complex with the E3 ligase, PROTACs induce target protein degradation. While PROTACs hold exciting potential as chemical probes and as therapeutic agents, development of a PROTAC typically requires synthesis of numerous analogs to thoroughly explore variations on the chemical linker; without extensive trial and error, it is unclear how to link the two protein-recruiting moieties to promote formation of a productive ternary complex. Here, we describe a structure-based computational method for evaluating suitability of a given linker for ternary complex formation. Our method uses Rosetta to dock the protein components, then builds the PROTAC from its component fragments into each binding mode; complete models of the ternary complex are then refined.We apply this approach to retrospectively evaluate multiple PROTACs from the literature, spanning diverse target proteins. We find that modeling ternary complex formation is sufficient to explain both activity and selectivity reported for these PROTACs, implying that other cellular factors are not key determinants of activity in these cases. We further find that interpreting PROTAC activity is best approached using an ensemble of structures of the ternary complex rather than a single static conformation, and that members of a structurally-conserved protein family can be recruited by the same PROTAC through vastly different binding modes. To encourage adoption of these methods and promote further analyses, we disseminate both the computational methods and the models of ternary complexes. Significance StatementRecent years have brought a flood of interest in developing compounds that selectively degrade protein targets in cells, as exemplified by PROTACs. Fully realizing the promise of PROTACs to transform chemical biology by delivering degraders of diverse and undruggable protein targets has been impeded, however, by the fact that designing a suitable chemical linker between the functional moieties requires extensive trial and error. Here, we describe a structure-based computational method to predict PROTAC activity. We envision that this approach will allow design and optimization of PROTACs for efficient target degradation, selection of E3 ligases best suited for pairing with a given target protein, and understanding the basis by which PROTACs can exhibit different target selectivity than their component warheads.

No abstract

Cyclin-dependent kinase 9 (CDK9) plays a key role in transcription elongation, and more recently it was also identified as the molecular target of a series of diaminothiazole compounds that reverse epigenetic silencing in a phenotypic assay. To better understand the structural basis underlying these compounds' activity and selectivity, we developed a comparative modeling approach that we describe herein. Briefly, this approach draws upon the strong structural conservation across the active conformation of all protein kinases, and their shared pattern of interactions with Type I inhibitors.Because of this, we hypothesized that the large collection of inhibitor/kinase structures available in the Protein Data Bank (PDB) would enable accurate modeling of this diaminothiazole series in complex with each CDK family member. We apply this new comparative modeling pipeline to build each of these structural models, and then demonstrate that these models provide retrospective rationale for the structure-activity relationships that ultimately guided optimization to the lead diaminothiazole compound MC180295 (14e). We then solved the crystal structure of the 14e/CDK9 complex, and found the resulting structure to be in excellent agreement with our corresponding comparative model. Finally, inspired by these models, we demonstrate how structural changes to 14e can be used to rationally tune this compound's selectivity profile. With the emergence of CDK9 as a promising target for therapeutic intervention in cancer, we anticipate that comparative modeling can provide a valuable tool to guide optimization of potency and selectivity of new inhibitors targeting this kinase.anti-tumoral activity coupled with immunosensitization [28]. With respect to selectivity, the preference of 14e for CDK9 over CDK2 and CDK7 was especially notable: due to their structural and functional similarities, most CDK9 inhibitors also inhibit CDK2 and CDK7 [29,30]. In our first study, we explored selectivity of 14e by developing a comparative modeling approach to build a model of the 14e/CDK9 complex, and then using this model to propose a structural basis for the observed selectivity [28].In the present study we expand our understanding of the structure-activity relationship (SAR) of the series and use these data to critically evaluate our comparative modeling approach. In particular, we present the SAR of 77 compounds related to 14e, and retrospectively assess the extent to which comparative modeling could have driven optimization. We also characterize 14e selectivity further, in light of a recent study demonstrating the surprising lack of selectivity in compounds ostensibly selective for other CDKs [6], and a report summarizing the broad selectivity profiles of CDK9 inhibitors that have advanced to clinical trials [22]. Finally, to definitively evaluate the accuracy of our comparative modeling for this application, we solve the crystal structure of 14e in complex with CDK9. Results and DiscussionOur previous study culminated with the identification and c...

We tested the role of substituents at the C3' and C3'N positions of the taxane molecule to identify taxane derivatives capable of overcoming acquired resistance to paclitaxel. Paclitaxel-resistant sublines SK-BR-3/PacR and MCF-7/PacR as well as the original paclitaxel-sensitive breast cancer cell lines SK-BR-3 and MCF-7 were used for testing. Increased expression of the ABCB1 transporter was found to be involved in the acquired resistance. We tested three groups of taxane derivatives: (1) phenyl group at both C3' and C3'N positions, (2) one phenyl at one of the C3' and C3'N positions and a non-aromatic group at the second position, (3) a non-aromatic group at both C3' and C3'N positions. We found that the presence of phenyl groups at both C3' and C3'N positions is associated with low capability of overcoming acquired paclitaxel resistance compared to taxanes containing at least one non-aromatic substituent at the C3' and C3'N positions. The increase in the ATPase activity of ABCB1 transporter after the application of taxanes from the first group was found to be somewhat higher than after the application of taxanes from the third group. Molecular docking studies demonstrated that the docking score was the lowest, i.e. the highest binding affinity, for taxanes from the first group. It was intermediate for taxanes from the second group, and the highest for taxanes from the third group. We conclude that at least one non-aromatic group at the C3' and C3'N positions of the taxane structure, resulting in reduced affinity to the ABCB1 transporter, brings about high capability of taxane to overcome acquired resistance of breast cancer cells to paclitaxel, due to less efficient transport of the taxane compound out of the cancer cells.

Glioblastoma multiforme (GBM) is considered to be the most common and often deadly disorder which affects the brain. It is caused by the over expression of proteins such as ephrin type-A receptor 2 (EphA2), epidermal growth factor receptor (EGFR) and EGFRvIII. These 3 proteins are considered to be the potential therapeutic targets for GBM. Among these, EphA2 is reported to be over-expressed in ˜90% of GBM. Herein we selected 35 compounds from marine actinomycetes, 5 in vitro and in vivo studied drug candidates and 4 commercially available drugs for GBM which were identified from literature and analysed by using comparative docking studies. Based on the glide scores and other in silico parameters available in Schrödinger, two selected marine actinomycetes compounds which include Tetracenomycin D and Chartreusin exhibited better binding energy among all the compounds studied in comparative docking. In this study we have demonstrated the inhibition of the 3 selected targets by the two bioactive compounds from marine actinomycetes through in-silico docking studies. Furthermore molecular dynamics simulation were also been performed to check the stability and the amino acids interacted with the 3 molecular targets (EphA2 receptor, EGFR, EGFRvIII) for GBM. Our results suggest that Tetracinomycin D and Chartreusin are the novel and potential inhibitor for the treatment of GBM.