Gregory Sliwoski

Computational Methods in Drug Discovery

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

Protocols for Molecular Modeling with Rosetta3 and RosettaScripts

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987–2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

An Acquired HER2 T798I Gatekeeper Mutation Induces Resistance to Neratinib in a Patient with HER2 Mutant-Driven Breast Cancer

We report a HER2T798I gatekeeper mutation in a patient with HER2L869R-mutant breast cancer with acquired resistance to neratinib. Laboratory studies suggested that HER2L869R is a neratinib-sensitive, gain-of-function mutation that upon dimerization with mutant HER3E928G, also present in the breast cancer, amplifies HER2 signaling. The patient was treated with neratinib and exhibited a sustained partial response. Upon clinical progression, HER2T798I was detected in plasma tumor cell-free DNA. Structural modeling of this acquired mutation suggested that the increased bulk of isoleucine in HER2T798I reduces neratinib binding. Neratinib blocked HER2-mediated signaling and growth in cells expressing HER2L869R but not HER2L869R/T798I In contrast, afatinib and the osimertinib metabolite AZ5104 strongly suppressed HER2L869R/T798I-induced signaling and cell growth. Acquisition of HER2T798I upon development of resistance to neratinib in a breast cancer with an initial activating HER2 mutation suggests HER2L869R is a driver mutation. HER2T798I-mediated neratinib resistance may be overcome by other irreversible HER2 inhibitors like afatinib.Significance: We found an acquired HER2 gatekeeper mutation in a patient with HER2-mutant breast cancer upon clinical progression on neratinib. We speculate that HER2T798I may arise as a secondary mutation following response to effective HER2 tyrosine kinase inhibitors (TKI) in other cancers with HER2-activating mutations. This resistance may be overcome by other irreversible HER2 TKIs, such as afatinib. Cancer Discov; 7(6); 575-85. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 539.

Pancreatic Polypeptide Is Recognized by Two Hydrophobic Domains of the Human Y4 Receptor Binding Pocket

Background: The Y4R is involved in regulation of food intake and gastrointestinal transport. Results: Mutagenesis studies revealed several residues displaying a significant loss of potency for hPP. Conclusion: Tops of TM2, TM6, and TM7 interact with the hY4R native agonist hPP. Significance: Characterizing the structure of the Y4R binding pocket is crucial for the development of new anti-obesity drugs. Structural characterization of the human Y4 receptor (hY4R) interaction with human pancreatic polypeptide (hPP) is crucial, not only for understanding its biological function but also for testing treatment strategies for obesity that target this interaction. Here, the interaction of receptor mutants with pancreatic polypeptide analogs was studied through double-cycle mutagenesis. To guide mutagenesis and interpret results, a three-dimensional comparative model of the hY4R-hPP complex was constructed based on all available class A G protein-coupled receptor crystal structures and refined using experimental data. Our study reveals that residues of the hPP and the hY4R form a complex network consisting of ionic interactions, hydrophobic interactions, and hydrogen binding. Residues Tyr2.64, Asp2.68, Asn6.55, Asn7.32, and Phe7.35 of Y4R are found to be important in receptor activation by hPP. Specifically, Tyr2.64 interacts with Tyr27 of hPP through hydrophobic contacts. Asn7.32 is affected by modifications on position Arg33 of hPP, suggesting a hydrogen bond between these two residues. Likewise, we find that Phe7.35 is affected by modifications of hPP at positions 33 and 36, indicating interactions between these three amino acids. Taken together, we demonstrate that the top of transmembrane helix 2 (TM2) and the top of transmembrane helices 6 and 7 (TM6–TM7) form the core of the peptide binding pocket. These findings will contribute to the rational design of ligands that bind the receptor more effectively to produce an enhanced agonistic or antagonistic effect.

Prostaglandin E 2 glyceryl ester is an endogenous agonist of the nucleotide receptor P2Y 6

Cyclooxygenase-2 catalyses the biosynthesis of prostaglandins from arachidonic acid but also the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. Previous studies identified PG-Gs as signalling molecules involved in inflammation. Thus, the glyceryl ester of prostaglandin E2, PGE2-G, mobilizes Ca2+ and activates protein kinase C and ERK, suggesting the involvement of a G protein-coupled receptor (GPCR). To identify the endogenous receptor for PGE2-G, we performed a subtractive screening approach where mRNA from PGE2-G response-positive and -negative cell lines was subjected to transcriptome-wide RNA sequencing analysis. We found several GPCRs that are only expressed in the PGE2-G responder cell lines. Using a set of functional readouts in heterologous and endogenous expression systems, we identified the UDP receptor P2Y6 as the specific target of PGE2-G. We show that PGE2-G and UDP are both agonists at P2Y6, but they activate the receptor with extremely different EC50 values of ~1 pM and ~50 nM, respectively. The identification of the PGE2-G/P2Y6 pair uncovers the signalling mode of PG-Gs as previously under-appreciated products of cyclooxygenase-2.

Discovery of Small-Molecule Modulators of the Human Y4 Receptor.

The human neuropeptide Y4 receptor (Y4R) and its native ligand, pancreatic polypeptide, are critically involved in the regulation of human metabolism by signaling satiety and regulating food intake, as well as increasing energy expenditure. Thus, this receptor represents a putative target for treatment of obesity. With respect to new approaches to treat complex metabolic disorders, especially in multi-receptor systems, small molecule allosteric modulators have been in the focus of research in the last years. However, no positive allosteric modulators or agonists of the Y4R have been described so far. In this study, small molecule compounds derived from the Niclosamide scaffold were identified by high-throughput screening to increase Y4R activity. Compounds were characterized for their potency and their effects at the human Y4R and as well as their selectivity towards Y1R, Y2R and Y5R. These compounds provide a structure-activity relationship profile around this common scaffold and lay the groundwork for hit-to-lead optimization and characterization of positive allosteric modulators of the Y4R.

BCL::EMAS — Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR

Stereochemistry is an important determinant of a molecule’s biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS) that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF) determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r2 = 0.89, q2 = 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891).

Identification and Characterization of the First Selective Y4 Receptor Positive Allosteric Modulator

The human Y4 receptor (Y4R) and its cognate ligand, pancreatic polypeptide (PP), are involved in the regulation of energy expenditure, satiety, and food intake. This system represents a potential target for the treatment of metabolic diseases and has been extensively investigated and validated in vivo. Here, we present the compound tBPC (tert-butylphenoxycyclohexanol), a novel and selective Y4R positive allosteric modulator that potentiates Y4R activation in G-protein signaling and arrestin3 recruitment experiments. The compound has no effect on the binding of the orthosteric ligands, implying its allosteric mode of action at the Y4R and evidence for a purely efficacy-driven positive allosteric modulation. Finally, the ability of tBPC to selectively potentiate Y4R agonism initiated by PP was confirmed in mouse descending colon mucosa preparations expressing native Y4R, demonstrating Y4R positive allosteric modulation in vitro.

PIK3CA C2 Domain Deletions Hyperactivate Phosphoinositide 3-kinase (PI3K), Generate Oncogene Dependence, and Are Exquisitely Sensitive to PI3Kα Inhibitors

Purpose: We describe herein a novel P447_L455 deletion in the C2 domain of PIK3CA in a patient with an ER+ breast cancer with an excellent response to the PI3Kα inhibitor alpelisib. Although PIK3CA deletions are relatively rare, a significant portion of deletions cluster within amino acids 446–460 of the C2 domain, suggesting these residues are critical for p110α function. Experimental Design: A computational structural model of PIK3CAdelP447-L455 in complex with the p85 regulatory subunit and MCF10A cells expressing PIK3CAdelP447-L455 and PIK3CAH450_P458del were used to understand the phenotype of C2 domain deletions. Results: Computational modeling revealed specific favorable inter-residue contacts that would be lost as a result of the deletion, predicting a significant decrease in binding energy. Coimmunoprecipitation experiments showed reduced binding of the C2 deletion mutants with p85 compared with wild-type p110α. The MCF10A cells expressing PIK3CA C2 deletions exhibited growth factor–independent growth, an invasive phenotype, and higher phosphorylation of AKT, ERK, and S6 compared with parental MCF10A cells. All these changes were ablated by alpelisib treatment. Conclusions: C2 domain deletions in PIK3CA generate PI3K dependence and should be considered biomarkers of sensitivity to PI3K inhibitors. Clin Cancer Res; 24(6); 1426–35. ©2017 AACR.