GPCRLigNet: rapid screening for GPCR active ligands using machine learning.

Molecules with bioactivity towards G protein-coupled receptors represent a subset of the vast space of small drug-like molecules. Here, we compare machine learning models, including dilated graph convolutional networks, that conduct binary classification to quickly identify molecules with activity towards G protein-coupled receptors. The models are trained and validated using a large set of over 600,000 active, inactive, and decoy compounds. The best performing machine learning model, dubbed GPCRLigNet, was a surprisingly simple feedforward dense neural network mapping from Morgan fingerprints to activity. Incorporation of GPCRLigNet into a high-throughput virtual screening workflow is demonstrated with molecular docking towards a particular G protein-coupled receptor, the pituitary adenylate cyclase-activating polypeptide receptor type 1. Through rigorous comparison of docking scores for molecules selected with and without using GPCRLigNet, we demonstrate an enrichment of potentially potent molecules using GPCRLigNet. This work provides a proof of principle that GPCRLigNet can effectively hone the chemical search space towards ligands with G protein-coupled receptor activity.

Helical Molecular Springs with Varying Spring Constants.

We report a general synthetic route toward helical ladder polymers with varying spring constants, built with chirality-assisted synthesis (CAS). Under tension and compression, these shape-persistent structures do not unfold, but rather stretch and compress akin classical Hookean springs. Our synthesis is adaptable to helices with different pitch and diameter, which allowed us to investigate how molecular flexibility in solution depends on the exact geometry of the ladder polymers. Specifically, we showed with molecular dynamic simulations and by measuring the longitudinal 1 H NMR relaxation times (T1 ) for our polymers at different Larmor frequencies, that increasing the helix diameter leads to increased flexibility. Our results present initial design rules for tuning the mechanical properties of intrinsically helical ladder polymers in solution, which will help inspire a new class of robust, spring-like molecular materials with varying mechanical properties.

Enhanced sampling protocol to elucidate fusion peptide opening of SARS-CoV-2 spike protein.

Large-scale conformational transitions in the spike protein S2 domain are required during host-cell infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although conventional molecular dynamics simulations have been extensively used to study therapeutic targets of SARS-CoV-2, it is still challenging to gain molecular insight into the key conformational changes because of the size of the spike protein and the long timescale required to capture these transitions. In this work, we have developed an efficient simulation protocol that leverages many short simulations, a dynamic selection algorithm, and Markov state models to interrogate the structural changes of the S2 domain. We discovered that the conformational flexibility of the dynamic region upstream of the fusion peptide in S2 is coupled to the proteolytic cleavage state of the spike protein. These results suggest that opening of the fusion peptide likely occurs on a submicrosecond timescale after cleavage at the S2' site. Building on the structural and dynamical information gained to date about S2 domain dynamics, we provide proof of principle that a small molecule bound to a seam neighboring the fusion peptide can slow the opening of the fusion peptide, leading to a new inhibition strategy for experiments to confirm. In aggregate, these results will aid the development of drug cocktails to inhibit infections caused by SARS-CoV-2 and other coronaviruses.

Essential Dynamics Ensemble Docking for Structure-Based GPCR Drug Discovery.

The lack of biologically relevant protein structures can hinder rational design of small molecules to target G protein-coupled receptors (GPCRs). While ensemble docking using multiple models of the protein target is a promising technique for structure-based drug discovery, model clustering and selection still need further investigations to achieve both high accuracy and efficiency. In this work, we have developed an original ensemble docking approach, which identifies the most relevant conformations based on the essential dynamics of the protein pocket. This approach is applied to the study of small-molecule antagonists for the PAC1 receptor, a class B GPCR and a regulator of stress. As few as four representative PAC1 models are selected from simulations of a homology model and then used to screen three million compounds from the ZINC database and 23 experimentally validated compounds for PAC1 targeting. Our essential dynamics ensemble docking (EDED) approach can effectively reduce the number of false negatives in virtual screening and improve the accuracy to seek potent compounds. Given the cost and difficulties to determine membrane protein structures for all the relevant states, our methodology can be useful for future discovery of small molecules to target more other GPCRs, either with or without experimental structures.

A computational study of cooperative binding to multiple SARS-CoV-2 proteins.

Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to searching for compounds that selectively target individual proteins, we investigated the potential interactions between eight proteins related to SARS-CoV-2 and more than 600 compounds from a traditional Chinese medicine which has proven effective at treating the viral infection. Our original ensemble docking and cooperative docking approaches, followed by a total of over 16-micorsecond molecular simulations, have identified at least 9 compounds that may generally bind to key SARS-CoV-2 proteins. Further, we found evidence that some of these compounds can simultaneously bind to the same target, potentially leading to cooperative inhibition to SARS-CoV-2 proteins like the Spike protein and the RNA-dependent RNA polymerase. These results not only present a useful computational methodology to systematically assess the anti-viral potential of small molecules, but also point out a new avenue to seek cooperative compounds toward cocktail therapeutics to target more SARS-CoV-2-related proteins.

Measurement of electric-field noise from interchangeable samples with a trapped-ion sensor.

We demonstrate the use of a single trapped ion as a sensor to probe electric-field noise from interchangeable test surfaces. As proof of principle, we measure the magnitude and distance dependence of electric-field noise from two ion-trap-like samples with patterned Au electrodes. This trapped-ion sensor could be combined with other surface characterization tools to help elucidate the mechanisms that give rise to electric-field noise from ion-trap surfaces. Such noise presents a significant hurdle for performing large-scale trapped-ion quantum computations.

Iterative Exponential Growth of Oxygen-Linked Aromatic Polymers Driven by Nucleophilic Aromatic Substitution Reactions.

This work presents the first transition metal-free synthesis of oxygen-linked aromatic polymers by integrating iterative exponential polymer growth (IEG) with nucleophilic aromatic substitution (SNAr) reactions. Our approach applies methyl sulfones as the leaving groups, which eliminate the need for a transition metal catalyst, while also providing flexibility in functionality and configuration of the building blocks used. As indicated by 1) 1H-1H NOESY NMR spectroscopy, 2) single-crystal X-ray crystallography, and 3) density functional theory (DFT) calculations, the unimolecular polymers obtained are folded by nonclassical hydrogen bonds formed between the oxygens of the electron-rich aromatic rings and the positively polarized C-H bonds of the electron-poor pyrimidine functions. Our results not only introduce a transition metal-free synthetic methodology to access precision polymers but also demonstrate how interactions between relatively small, neutral aromatic units in the polymers can be utilized as new supramolecular interaction pairs to control the folding of precision macromolecules.

Size-selective Catalytic Polymer Acylation with a Molecular Tetrahedron.

Selective catalysis at the molecular level represents a cornerstone of chemical synthesis. However, it still remains an open question how to elevate tunable catalysis to larger length scales to functionalize whole polymer chains in a selective manner. We now report a hydrazone-linked tetrahedron with wide openings, which acts as a catalyst to size-selectively functionalize polydisperse polymer mixtures. Our experimental and computational evidence supports a dual role of the hydrazone-linked tetrahedron. To accelerate functionalization of the polymer substrates, the tetrahedron (i) unfolds the polymer substrates and/or breaks the polymer aggregates as well as (ii) enables target sites (amino groups) on the polymers to coordinate with catalytic units (triglyme) attached to the tetrahedron. With the tetrahedron as the catalyst, we find that the reactivity of the shorter polymers increases selectively. Our findings enable the possibility to engineer hydrolytically stable molecular polyhedra as organocatalysts for size-selective polymer modification.

Selective USP7 inhibition elicits cancer cell killing through a p53-dependent mechanism.

Ubiquitin specific peptidase 7 (USP7) is a deubiquitinating enzyme (DUB) that removes ubiquitin tags from specific protein substrates in order to alter their degradation rate and sub-cellular localization. USP7 has been proposed as a therapeutic target in several cancers because it has many reported substrates with a role in cancer progression, including FOXO4, MDM2, N-Myc, and PTEN. The multi-substrate nature of USP7, combined with the modest potency and selectivity of early generation USP7 inhibitors, has presented a challenge in defining predictors of response to USP7 and potential patient populations that would benefit most from USP7-targeted drugs. Here, we describe the structure-guided development of XL177A, which irreversibly inhibits USP7 with sub-nM potency and selectivity across the human proteome. Evaluation of the cellular effects of XL177A reveals that selective USP7 inhibition suppresses cancer cell growth predominantly through a p53-dependent mechanism: XL177A specifically upregulates p53 transcriptional targets transcriptome-wide, hotspot mutations in TP53 but not any other genes predict response to XL177A across a panel of ~500 cancer cell lines, and TP53 knockout rescues XL177A-mediated growth suppression of TP53 wild-type (WT) cells. Together, these findings suggest TP53 mutational status as a biomarker for response to USP7 inhibition. We find that Ewing sarcoma and malignant rhabdoid tumor (MRT), two pediatric cancers that are sensitive to other p53-dependent cytotoxic drugs, also display increased sensitivity to XL177A.

Enhanced quantum efficiency of the visible light photon counter in the ultraviolet wavelengths.

The visible light photon counter (VLPC) is a very high quantum efficiency (QE, 88% at 694 nm) single photon detector in the visible wavelengths. The QE in the ultraviolet (UV) wavelenghths is poor in these devices due to absorption in the degenerate front contact. We introduce the ultraviolet photon counter (UVPC), where the QE in the near UV wavelength range (300-400 nm) is dramatically enhanced. The degenerate Si front contact of the VLPC is replaced with a Ti Schottky contact, which reduces the absorption of incident photons within the contact layer. We demonstrate a system QE of 5.3% at 300 nm and 11% at 370 nm for a UVPC with a Ti Schottky contact and a single layer MgF(2) antireflection coating.

MEPicides: α,ß-Unsaturated Fosmidomycin Analogues as DXR Inhibitors against Malaria.

Severe malaria due to Plasmodium falciparum remains a significant global health threat. DXR, the second enzyme in the MEP pathway, plays an important role to synthesize building blocks for isoprenoids. This enzyme is a promising drug target for malaria due to its essentiality as well as its absence in humans. In this study, we designed and synthesized a series of α,ß-unsaturated analogues of fosmidomycin, a natural product that inhibits DXR in P. falciparum. All compounds were evaluated as inhibitors of P. falciparum. The most promising compound, 18a, displays on-target, potent inhibition against the growth of P. falciparum (IC50 = 13 nM) without significant inhibition of HepG2 cells (IC50 > 50 µM). 18a was also tested in a luciferase-based Plasmodium berghei mouse model of malaria and showed exceptional in vivo efficacy. Together, the data support MEPicide 18a as a novel, potent, and promising drug candidate for the treatment of malaria.

Micro-fabricated stylus ion trap.

An electroformed, three-dimensional stylus Paul trap was designed to confine a single atomic ion for use as a sensor to probe the electric-field noise of proximate surfaces. The trap was microfabricated with the UV-LIGA technique to reduce the distance of the ion from the surface of interest. We detail the fabrication process used to produce a 150 µm tall stylus trap with feature sizes of 40 µm. We confined single, laser-cooled, (25)Mg(+) ions with lifetimes greater than 2 h above the stylus trap in an ultra-high-vacuum environment. After cooling a motional mode of the ion at 4 MHz close to its ground state ( = 0.34 ± 0.07), the heating rate of the trap was measured with Raman sideband spectroscopy to be 387 ± 15 quanta/s at an ion height of 62 µm above the stylus electrodes.

A ultra-high-vacuum wafer-fusion-bonding system.

The design of heterojunction devices is typically limited by material integration constraints and the energy band alignment. Wafer bonding can be used to integrate material pairs that cannot be epitaxially grown together due to large lattice mismatch. Control of the energy band alignment can be provided by formation of interface dipoles through control of the surface chemistry. We have developed an ultra-high-vacuum system for wafer-fusion-bonding semiconductors with in situ control and measurement of surface properties relevant to interface dipoles. A wafer-fusion-bonding chamber with annealing capabilities was integrated into an ultra-high-vacuum system with a sputtering chamber and an x-ray photoelectron spectroscopy system for preparing and measuring the surface chemistry of wafers prior to bonding. The design of the system along with initial results for the fusion-bonded InGaAs/Si heterojunction is presented.