α-Aminoxy Peptoids: A Unique Peptoid Backbone with a Preference for cis-Amide Bonds

Development of a Systematic and Extensible Force Field for Peptoids (STEPs)

Peptoids (N-substituted glycines) are a class of biomimetic polymers that have attracted significant attention due to their accessible synthesis and enzymatic and thermal stability relative to their naturally occurring counterparts (polypeptides). While these polymers provide the promise of more robust functional materials via hierarchical approaches, they present a new challenge for computational structure prediction for material design. The reliability of calculations hinges on the accuracy of interactions represented in the force field used to model peptoids. For proteins, structure prediction based on sequence and de novo design has made dramatic progress in recent years; however, these models are not readily transferable for peptoids. Current efforts to develop and implement peptoid-specific force fields are spread out, leading to replicated efforts and a fragmented collection of parameterized sidechains. Here, we developed a peptoid-specific force field containing 70 different side chains, using GAFF2 as starting point. The new model is validated based on the generation of Ramachandran-like plots from DFT optimization compared against force field reproduced potential energy and free energy surfaces as well as the reproduction of equilibrium cis/trans values for some residues experimentally known to form helical structures. Equilibrium cis/trans distributions (Kct) are estimated for all parameterized residues to identify which residues have an intrinsic propensity for cis or trans states in the monomeric state.

Development of a First-in-Class Small-Molecule Inhibitor of the C-Terminal Hsp90 Dimerization

Heat shock proteins 90 (Hsp90) are promising therapeutic targets due to their involvement in stabilizing several aberrantly expressed oncoproteins. In cancerous cells, Hsp90 expression is elevated, thereby exerting antiapoptotic effects, which is essential for the malignant transformation and tumor progression. Most of the Hsp90 inhibitors (Hsp90i) under investigation target the ATP binding site in the N-terminal domain of Hsp90. However, adverse effects, including induction of the prosurvival resistance mechanism (heat shock response or HSR) and associated dose-limiting toxicity, have so far precluded their clinical approval. In contrast, modulators that interfere with the C-terminal domain (CTD) of Hsp90 do not inflict HSR. Since the CTD dimerization of Hsp90 is essential for its chaperone activity, interfering with the dimerization process by small-molecule protein-protein interaction inhibitors is a promising strategy for anticancer drug research. We have developed a first-in-class small-molecule inhibitor (5b) targeting the Hsp90 CTD dimerization interface, based on a tripyrimidonamide scaffold through structure-based molecular design, chemical synthesis, binding mode model prediction, assessment of the biochemical affinity, and efficacy against therapy-resistant leukemia cells. 5b reduces xenotransplantation of leukemia cells in zebrafish models and induces apoptosis in BCR-ABL1⁺ (T315I) tyrosine kinase inhibitor-resistant leukemia cells, without inducing HSR.

Data-driven coarse-grained modeling of non-equilibrium systems

Modeling a high-dimensional Hamiltonian system in reduced dimensions with respect to coarse-grained (CG) variables can greatly reduce computational cost and enable efficient bottom-up prediction of main features of the system for many applications. However, it usually experiences significantly altered dynamics due to loss of degrees of freedom upon coarse-graining. To establish CG models that can faithfully preserve dynamics, previous efforts mainly focused on equilibrium systems. In contrast, various soft matter systems are known to be out of equilibrium. Therefore, the present work concerns non-equilibrium systems and enables accurate and efficient CG modeling that preserves non-equilibrium dynamics and is generally applicable to any non-equilibrium process and any observable of interest. To this end, the dynamic equation of a CG variable is built in the form of the non-stationary generalized Langevin equation (nsGLE), where the two-time memory kernel is determined from the data of the auto-correlation function of the observable of interest. By embedding the nsGLE in an extended dynamics framework, the nsGLE can be solved efficiently to predict the non-equilibrium dynamics of the CG variable. To prove and exploit the equivalence of the nsGLE and extended dynamics, the memory kernel is parameterized in a two-time exponential expansion. A data-driven hybrid optimization process is proposed for the parameterization, which integrates the differential-evolution method with the Levenberg-Marquardt algorithm to efficiently tackle a non-convex and high-dimensional optimization problem.

A Novel Cyclic Mobile Transporter Can Induce Apoptosis by Facilitating Chloride Anion Transport into Cells

We report here the preparation of an aminoxy amide-based pseudopeptide-derived building block using furanoid sugar molecules. Through the cyclo-oligomerization reaction, we generate a hybrid triazole/aminoxy amide macrocycle using the as-prepared building block. The novel conformation of the macrocycle has been characterized using NMR and molecular modeling studies, which show a strong resemblance of our synthesized compound to d-,l-α-aminoxy acid-based cyclic peptides that contain uniform backbone chirality. We observe that the macrocycle can efficiently and selectively bind Cl^- ion and transport Cl^- ion across a lipid bilayer. ¹H NMR anion binding studies suggest a coherent relationship between the acidity of aminoxy amide N-H and triazole C-H proton binding strength. Using time-based fluorescence assay, we show that the macrocycle acts as a mobile transporter and follows an antiport mechanism. Our synthesized macrocycle imposes cancer cell death by disrupting ionic homeostasis through Cl^- ion transport. The macrocycle induced cytochrome c leakage and changes in mitochondrial membrane potential along with activation of family of caspases, suggesting that the cellular apoptosis occurs through a caspase-dependent intrinsic pathway. The present results suggest the possibility of using the macrocycle as a biological tool of high therapeutic value.

Design, synthesis and biological evaluation of β-peptoid-capped HDAC inhibitors with anti-neuroblastoma and anti-glioblastoma activity

Histone deacetylases (HDACs) have been identified as promising epigenetic drug targets for the treatment of neuroblastoma and glioblastoma. In this work, we have rationally designed a novel class of peptoid-based histone deacetylase inhibitors (HDACi). A mini library of β-peptoid-capped HDACi was synthesized using a four-step protocol. All compounds were screened in biochemical assays for their inhibition of HDAC1 and HDAC6 and docking studies were performed to rationalize the observed selectivity profile. The synthesized compounds were further examined for tumor cell-inhibitory activity against a panel of neuroblastoma and glioblastoma cell lines. In particular, non-selective compounds with potent activity against HDAC1 and HDAC6 showed strong antiproliferative effects. The most promising HDACi, compound 6i, displayed submicromolar tumor cell-inhibitory potential (IC₅₀: 0.21-0.67 μM) against all five cancer cell lines investigated and exceeded the activity of the FDA-approved HDACi vorinostat.

Design, Multicomponent Synthesis, and Anticancer Activity of a Focused Histone Deacetylase (HDAC) Inhibitor Library with Peptoid-Based Cap Groups

In this work, we report the multicomponent synthesis of a focused histone deacetylase (HDAC) inhibitor library with peptoid-based cap groups and different zinc-binding groups. All synthesized compounds were tested in a cellular HDAC inhibition assay and an MTT assay for cytotoxicity. On the basis of their noteworthy activity in the cellular HDAC assays, four compounds were further screened for their inhibitory activity against recombinant HDAC1-3, HDAC6, and HDAC8. All four compounds showed potent inhibition of HDAC1-3 as well as significant inhibition of HDAC6 with IC₅₀ values in the submicromolar concentration range. Compound 4j, the most potent HDAC inhibitor in the cellular HDAC assay, revealed remarkable chemosensitizing properties and enhanced the cisplatin sensitivity of the cisplatin-resistant head-neck cancer cell line Cal27CisR by almost 7-fold. Furthermore, 4j almost completely reversed the cisplatin resistance in Cal27CisR. This effect is related to a synergistic induction of apoptosis as seen in the combination of 4j with cisplatin.