A Second-Generation Oral SARS-CoV-2 Main Protease Inhibitor Clinical Candidate for the Treatment of COVID-19.

Despite the record-breaking discovery, development and approval of vaccines and antiviral therapeutics such as Paxlovid, coronavirus disease 2019 (COVID-19) remained the fourth leading cause of death in the world and third highest in the United States in 2022. Here, we report the discovery and characterization of PF-07817883, a second-generation, orally bioavailable, SARS-CoV-2 main protease inhibitor with improved metabolic stability versus nirmatrelvir, the antiviral component of the ritonavir-boosted therapy Paxlovid. We demonstrate the in vitro pan-human coronavirus antiviral activity and off-target selectivity profile of PF-07817883. PF-07817883 also demonstrated oral efficacy in a mouse-adapted SARS-CoV-2 model at plasma concentrations equivalent to nirmatrelvir. The preclinical in vivo pharmacokinetics and metabolism studies in human matrices are suggestive of improved oral pharmacokinetics for PF-07817883 in humans, relative to nirmatrelvir. In vitro inhibition/induction studies against major human drug metabolizing enzymes/transporters suggest a low potential for perpetrator drug-drug interactions upon single-agent use of PF-07817883.

Probing the chemical 'reactome' with high-throughput experimentation data.

High-throughput experimentation (HTE) has the potential to improve our understanding of organic chemistry by systematically interrogating reactivity across diverse chemical spaces. Notable bottlenecks include few publicly available large-scale datasets and the need for facile interpretation of these data's hidden chemical insights. Here we report the development of a high-throughput experimentation analyser, a robust and statistically rigorous framework, which is applicable to any HTE dataset regardless of size, scope or target reaction outcome, which yields interpretable correlations between starting material(s), reagents and outcomes. We improve the HTE data landscape with the disclosure of 39,000+ previously proprietary HTE reactions that cover a breadth of chemistry, including cross-coupling reactions and chiral salt resolutions. The high-throughput experimentation analyser was validated on cross-coupling and hydrogenation datasets, showcasing the elucidation of statistically significant hidden relationships between reaction components and outcomes, as well as highlighting areas of dataset bias and the specific reaction spaces that necessitate further investigation.

Predictive Minisci late stage functionalization with transfer learning.

Structural diversification of lead molecules is a key component of drug discovery to explore chemical space. Late-stage functionalizations (LSFs) are versatile methodologies capable of installing functional handles on richly decorated intermediates to deliver numerous diverse products in a single reaction. Predicting the regioselectivity of LSF is still an open challenge in the field. Numerous efforts from chemoinformatics and machine learning (ML) groups have made strides in this area. However, it is arduous to isolate and characterize the multitude of LSF products generated, limiting available data and hindering pure ML approaches. We report the development of an approach that combines a message passing neural network and 13C NMR-based transfer learning to predict the atom-wise probabilities of functionalization for Minisci and P450-based functionalizations. We validated our model both retrospectively and with a series of prospective experiments, showing that it accurately predicts the outcomes of Minisci-type and P450 transformations and outperforms the well-established Fukui-based reactivity indices and other machine learning reactivity-based algorithms.

SORC: an integrated spatial omics resource in cancer.

The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.

Development and Comprehensive Benchmark of a High-Quality AMBER-Consistent Small Molecule Force Field with Broad Chemical Space Coverage for Molecular Modeling and Free Energy Calculation.

Biomolecular simulations have become an essential tool in contemporary drug discovery, and molecular mechanics force fields (FFs) constitute its cornerstone. Developing a high quality and broad coverage general FF is a significant undertaking that requires substantial expert knowledge and computing resources, which is beyond the scope of general practitioners. Existing FFs originate from only a limited number of groups and organizations, and they either suffer from limited numbers of training sets, lower than desired quality because of oversimplified representations, or are costly for the molecular modeling community to access. To address these issues, in this work, we developed an AMBER-consistent small molecule FF with extensive chemical space coverage, and we provide Open Access parameters for the entire modeling community. To validate our FF, we carried out benchmarks of quantum mechanics (QM)/molecular mechanics conformer comparison and free energy perturbation calculations on several benchmark data sets. Our FF achieves a higher level of performance at reproducing QM energies and geometries than two popular open-source FFs, OpenFF2 and GAFF2. In relative binding free energy calculations for 31 protein-ligand data sets, comprising 1079 pairs of ligands, the new FF achieves an overall root-mean-square error of 1.19 kcal/mol for ΔΔG and 0.92 kcal/mol for ΔG on a subset of 463 ligands without bespoke fitting to the data sets. The results are on par with those of the leading commercial series of OPLS FFs.

Report of intersex individuals from a southeastern Chinese Choroterpes facialis (Gillies, 1951) population (Ephemeroptera: Leptophlebiidae).

Previously there were only three cases of mayfly gynandromorphism reported from Asia, occurring in the families Baetidae and Heptageniidae. Here, we report two intersex individuals of Choroterpes facialis (Gillies, 1951) (Ephemeroptera: Leptophlebiidae) from southeastern China. They have similar external morphologies (each having two different eyes, two shortened penes, and female sternum IX) but with one being predominately male and the other being predominately female (one with eggs in the abdomen, but the other apparently with sperm). We believe this to be the first report of a feminized male individual. This phenomenon implies their intersexuality is caused by some similar reasons, such as temperature or parasitism. Remarkably, two intersex specimens found among 1,736 normal individuals shows that gynandromorphism does occur rarely, and only six normal males in the sampling suggest the species C. facialis is partially parthenogenetic at least.

Discovery of the Potent and Selective MC4R Antagonist PF-07258669 for the Potential Treatment of Appetite Loss.

The melanocortin-4 receptor (MC4R) is a centrally expressed, class A GPCR that plays a key role in the regulation of appetite and food intake. Deficiencies in MC4R signaling result in hyperphagia and increased body mass in humans. Antagonism of MC4R signaling has the potential to mitigate decreased appetite and body weight loss in the setting of anorexia or cachexia due to underlying disease. Herein, we report on the identification of a series of orally bioavailable, small-molecule MC4R antagonists using a focused hit identification effort and the optimization of these antagonists to provide clinical candidate 23. Introduction of a spirocyclic conformational constraint allowed for simultaneous optimization of MC4R potency and ADME attributes while avoiding the production of hERG active metabolites observed in early series leads. Compound 23 is a potent and selective MC4R antagonist with robust efficacy in an aged rat model of cachexia and has progressed into clinical trials.

Species differences in plasma protein binding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease inhibitor nirmatrelvir.

Plasma protein binding (PPB) studies on the SARS-CoV-2 main protease inhibitor nirmatrelvir revealed considerable species differences primarily in dog and rabbit, which prompted further investigations into the biochemical basis for these differences.The unbound fraction (fu) of nirmatrelvir in dog and rabbit plasma was concentration (2-200 µM)-dependent (dog fu,p 0.024-0.69, rabbit fu,p 0.010-0.82). Concentration (0.1-100 µM)-dependent binding in serum albumin (SA) (fu,SA 0.040-0.82) and alpha-1-acid glycoprotein (AAG) (fu,AAG 0.050-0.64) was observed in dogs. Nirmatrelvir showed minimal binding to rabbit SA (1-100 µM: fu,SA 0.70-0.79), while binding to rabbit AAG was concentration-dependent (0.1-100 µM: fu,AAG 0.024-0.66). In contrast, nirmatrelvir (2 µM) revealed minimal binding (fu,AAG 0.79-0.88) to AAG from rat and monkeys. Nirmatrelvir showed minimal-to-moderate binding to SA (1-100 µM; fu,SA 0.70-1.0) and AAG (0.1-100 µM; fu,AAG 0.48-0.58) from humans across tested concentrations.Nirmatrelvir molecular docking studies using published crystal structures and homology models of human and preclinical species SA and AAG were used to rationalise the species differences to plasma proteins. This suggested that species differences in PPB are primarily driven by molecular differences in albumin and AAG resulting in differences in binding affinity.

Structural basis of the acyl-transfer mechanism of human GPAT1.

Glycerol-3-phosphate acyltransferase (GPAT)1 is a mitochondrial outer membrane protein that catalyzes the first step of de novo glycerolipid biosynthesis. Hepatic expression of GPAT1 is linked to liver fat accumulation and the severity of nonalcoholic fatty liver diseases. Here we present the cryo-EM structures of human GPAT1 in substrate analog-bound and product-bound states. The structures reveal an N-terminal acyltransferase domain that harbors important catalytic motifs and a tightly associated C-terminal domain that is critical for proper protein folding. Unexpectedly, GPAT1 has no transmembrane regions as previously proposed but instead associates with the membrane via an amphipathic surface patch and an N-terminal loop-helix region that contains a mitochondrial-targeting signal. Combined structural, computational and functional studies uncover a hydrophobic pathway within GPAT1 for lipid trafficking. The results presented herein lay a framework for rational inhibitor development for GPAT1.

A new Neoleptophlebia Kluge, 1997 species from eastern China (Ephemeroptera: Leptophlebiidae).

The genus Neoleptophlebia Kluge, 1997 includes five Asian species. Three of them were reported from northeastern Asia and two were found from Chinese Taiwan Island, leaving a huge geographic gap on the Chinese mainland. Here we find a new one, which is named N. uncinata Zhou sp. nov., from Nanjing municipality, eastern China. Via field collecting and indoor rearing, all life stages were obtained, and its nymphs are found living in small creeks (with a width less than 1 m) and shallow waters (with a depth less than 30 cm). Diagnostically, the imago of this new species has larger lateral penial appendages than its congeners, and its nymph has subequal broadened segments II and III of maxillary and labial palpi. Biogeographically, this species bridges two northern and southern groups of the genus.

Surface charge modulation enhanced high stability of gold oxidation intermediates for electrochemical glucose sensors.

Rapid and accurate blood glucose detection is significant for diagnosing and treating diabetes. Herein, ultra-low-content gold nanoparticles were loaded on different metal foams and applied to electrochemical enzyme-free glucose sensors via simple displacement reactions. The structures and properties of the produced catalysts were determined by various characterization methods. The performance of the glucose sensor was examined in relation to the interactions between three different metal substrates and gold. The one with the best performance is the sample of gold nanoparticles grown on copper foam (Au300 Cu Foam). It has the advantage of a porous three-dimensional network, a large electroactive surface area, and the high catalytic activity of gold. The combination of Cu and Au increased the valence state of Au, thus favoring the catalytic activity for glucose oxidation. Cyclic voltammetry and chronoamperometry measurements revealed that Au is responsible for the electrocatalytic oxidation of glucose. The sensitivity of Au300 Cu Foam was found to be 10 839 µA mM-1 cm-2 in the linear range of 0.00596-0.0566 mM, with a detection limit (LOD) of 0.223 µM, and 2-3 s response time at 0.4 V vs. Ag/AgCl. The Au300 Cu Foam glucose sensor also offered outstanding stability and anti-interference performance. The prepared Au300 Cu Foam electrode was also successfully applied to detect different levels of glucose in human body fluids, such as saliva. These characteristics make Au300 Cu Foam promising for non-invasive glucose detection.

Acylsugar protection of Nicotiana benthamiana confers mortality and transgenerational fitness costs in Spodoptera litura.

Acylsugars are secondary metabolites that are produced in the trichomes of some solanaceous species and can help control several herbivorous insect pests. Previously, knockout mutations (asat2 mutants) were shown to significantly reduce the acylsugar content of Nicotiana benthamiana, and significantly improve the fitness of six generalist insect herbivores. The current study compared the significant mortality and fitness costs in Spodoptera litura conferred by acylsugar protection of N. benthamiana (wild-type plants) compared to S. litura strains reared in acylsugar-deficient plants with depleted acylsugar biosynthesis. Acylsugar protection prolonged the developmental duration and decreased viability in the larval stages. Further, the fecundity of females and the hatching rate of eggs significantly decreased under acylsugar protection. For F1 offspring, acylsugar protection still exerted significant negative effects on larval survival rate and fecundity per female. The net reproductive rate and relative fitness of the S. litura strain were strongly affected by acylsugar. Altogether, these results indicate that acylsugar could contribute to plant protection due to toxicity to pests, diffused availability, and low environmental persistence. This could represent a complementary and alternative strategy to control populations of insect pests.

Genetic Surveillance of SARS-CoV-2 Mpro Reveals High Sequence and Structural Conservation Prior to the Introduction of Protease Inhibitor Paxlovid.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to represent a global health emergency as a highly transmissible, airborne virus. An important coronaviral drug target for treatment of COVID-19 is the conserved main protease (Mpro). Nirmatrelvir is a potent Mpro inhibitor and the antiviral component of Paxlovid. The significant viral sequencing effort during the ongoing COVID-19 pandemic represented a unique opportunity to assess potential nirmatrelvir escape mutations from emerging variants of SARS-CoV-2. To establish the baseline mutational landscape of Mpro prior to the introduction of Mpro inhibitors, Mpro sequences and its cleavage junction regions were retrieved from ~4,892,000 high-quality SARS-CoV-2 genomes in the open-access Global Initiative on Sharing Avian Influenza Data (GISAID) database. Any mutations identified from comparison to the reference sequence (Wuhan-Hu-1) were catalogued and analyzed. Mutations at sites key to nirmatrelvir binding and protease functionality (e.g., dimerization sites) were still rare. Structural comparison of Mpro also showed conservation of key nirmatrelvir contact residues across the extended Coronaviridae family (α-, ß-, and γ-coronaviruses). Additionally, we showed that over time, the SARS-CoV-2 Mpro enzyme remained under purifying selection and was highly conserved relative to the spike protein. Now, with the emergency use authorization (EUA) of Paxlovid and its expected widespread use across the globe, it is essential to continue large-scale genomic surveillance of SARS-CoV-2 Mpro evolution. This study establishes a robust analysis framework for monitoring emergent mutations in millions of virus isolates, with the goal of identifying potential resistance to present and future SARS-CoV-2 antivirals. IMPORTANCE The recent authorization of oral severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antivirals, such as Paxlovid, has ushered in a new era of the COVID-19 pandemic. The emergence of new variants, as well as the selective pressure imposed by antiviral drugs themselves, raises concern for potential escape mutations in key drug binding motifs. To determine the potential emergence of antiviral resistance in globally circulating isolates and its implications for the clinical response to the COVID-19 pandemic, sequencing of SARS-CoV-2 viral isolates before, during, and after the introduction of new antiviral treatments is critical. The infrastructure built herein for active genetic surveillance of Mpro evolution and emergent mutations will play an important role in assessing potential antiviral resistance as the pandemic progresses and Mpro inhibitors are introduced. We anticipate our framework to be the starting point in a larger effort for global monitoring of the SARS-CoV-2 Mpro mutational landscape.

Characterization of Field-Evolved Resistance to Afidopyropen, a Novel Insecticidal Toxin Developed from Microbial Secondary Metabolites, in Bemisia tabaci.

Afidopyropen, a newly identified chemical, is a derivative of pyripyropene A, which is produced by the filamentous fungus Penicillium coprobium. It is a promising novel pesticide applied against whiteflies in agriculture. In this study, the reversion and selection, cross-resistance patterns, synergistic effects, and fitness costs of afidopyropen resistance were studied in a field-developed resistant population of B. tabaci. Compared to a reference MED-S strain, the field-developed resistant Haidian (HD) population showed 36.5-fold resistance to afidopyropen. Significant reversion of resistance to afidopyropen was found in the HD population when it was kept with no selective pressure of the insecticide. The HD-Afi strain, developed from the HD population with afidopyropen pressure, developed 104.3-fold resistance to afidopyropen and significant cross-resistance to sulfoxaflor. Piperonyl butoxide (PBO) largely inhibited afidopyropen resistance in the HD-Afi strain, which indicates that P450 monooxygenase could be involved in the resistance. Significant fitness costs associated with afidopyropen resistance were observed in HD-Afi. This study indicates that a rotation of afidopyropen with other chemical control agents could be useful for impeding afidopyropen resistance in B. tabaci. In addition, we expanded upon the understanding of resistance to afidopyropen, offering evidence suggesting the importance of devising better strategies for the management of whiteflies.

TorsionNet: A Deep Neural Network to Rapidly Predict Small-Molecule Torsional Energy Profiles with the Accuracy of Quantum Mechanics.

Fast and accurate assessment of small-molecule dihedral energetics is crucial for molecular design and optimization in medicinal chemistry. Yet, accurate prediction of torsion energy profiles remains challenging as the current molecular mechanics (MM) methods are limited by insufficient coverage of drug-like chemical space and accurate quantum mechanical (QM) methods are too expensive. To address this limitation, we introduce TorsionNet, a deep neural network (DNN) model specifically developed to predict small-molecule torsion energy profiles with QM-level accuracy. We applied active learning to identify nearly 50k fragments (with elements H, C, N, O, F, S, and Cl) that maximized the coverage of our corporate compound library and leveraged massively parallel cloud computing resources for density functional theory (DFT) torsion scans of these fragments, generating a training data set of 1.2 million DFT energies. After training TorsionNet on this data set, we obtain a model that can rapidly predict the torsion energy profile of typical drug-like fragments with DFT-level accuracy. Importantly, our method also provides an uncertainty estimate for the predicted profiles without any additional calculations. In this report, we show that TorsionNet can accurately identify the preferred dihedral geometries observed in crystal structures. Our TorsionNet-based analysis of a diverse set of protein-ligand complexes with measured binding affinity shows a strong association between high ligand strain and low potency. We also present practical applications of TorsionNet that demonstrate how consideration of DNN-based strain energy leads to substantial improvement in existing lead discovery and design workflows. TorsionNet500, a benchmark data set comprising 500 chemically diverse fragments with DFT torsion profiles (12k MM- and DFT-optimized geometries and energies), has been created and is made publicly available.

An oral SARS-CoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19.

The worldwide outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic. Alongside vaccines, antiviral therapeutics are an important part of the healthcare response to countering the ongoing threat presented by COVID-19. Here, we report the discovery and characterization of PF-07321332, an orally bioavailable SARS-CoV-2 main protease inhibitor with in vitro pan-human coronavirus antiviral activity and excellent off-target selectivity and in vivo safety profiles. PF-07321332 has demonstrated oral activity in a mouse-adapted SARS-CoV-2 model and has achieved oral plasma concentrations exceeding the in vitro antiviral cell potency in a phase 1 clinical trial in healthy human participants.

Total flavonoids of Rhizoma drynariae ameliorate steroid­induced avascular necrosis of the femoral head via the PI3K/AKT pathway.

Steroid­induced avascular necrosis of the femoral head (SANFH) is a common orthopaedic disease that is difficult to treat. The present study investigated the effects of total flavonoids of Rhizoma drynariae (TFRD) on SANFH and explored its underlying mechanisms. The SANFH rat model was induced by intramuscular injection of lipopolysaccharides and methylprednisolone. Osteoblasts were isolated from the calvariae of neonatal rats and then cultured with dexamethasone (Dex). TFRD was used in vitro and in vivo, respectively. Haematoxylin and eosin staining was used to assess the pathological changes in the femoral head. Terminal deoxynucleotidyl transferase­mediated deoxyuridine triphosphate nick end labelling assay and flow cytometry were conducted to detect apoptosis of osteoblasts. The 2',7'­dichlorofluorescein­diacetate staining method was used to detect reactive oxygen species (ROS) levels in osteoblasts and the 3­(4,5­dimethylthiazol­2­yl)­2,5­diphenyltetrazolium bromide assay was used to detect osteoblast proliferation. The expression of caspase­3, Bax, Bcl­2, VEGF, runt­related transcription factor 2 (RUNX2), osteoprotegerin (OPG), osteocalcin (OCN), receptor activator of nuclear factor κB ligand (RANKL) and phosphoinositide 3­kinase (PI3K)/AKT pathway related­proteins were detected via western blotting. It was found that TFRD reduced the pathological changes, inhibited apoptosis, increased the expression of VEGF, RUNX2, OPG and OCN, decreased RANKL expression and activated the PI3K/AKT pathway in SANFH rats. TFRD promoted proliferation, inhibited apoptosis and reduced ROS levels by activating the PI3K/AKT pathway in osteoblasts. In conclusion, TFRD protected against SANFH in a rat model. In addition, TFRD protected osteoblasts from Dex­induced damage through the PI3K/AKT pathway. The findings of the present study may contribute to find an effective treatment for the management of SANFH.

MiR-22 restrains proliferation of rheumatoid arthritis by targeting IL6R and may be concerned with the suppression of NF-κB pathway.

It has demonstrated that miR-22 overexpression can suppress the inflammation process of rheumatoid arthritis (RA) in synoviocytes. But, the underlying mechanism of miR-22 expression in regulating RA is still not well illustrated. In this study, we investigated the functional role and underlying mechanism of miR-22 in regulating RA. Human RA fibroblast-like synoviocyte (FLS) cell line MH7A cells was transfected by miR-22 mimic and its control. CCK8 was utilized to detect cell proliferation. Cell apoptosis was analyzed by flow cytometry. MH7A cells stimulating with interleukin-1ß (IL-1ß) were transfected with miR-22 mimic. Quantitative real time polymerase chain reaction (qRT-PCR) and western blot assays were utilized to detect mRNA and protein expression. miR-22 targets were predicted and validated by Targetscan and luciferase reporter assay. We revealed that miR-22 showed downregulated expression in MH7A after stimulation with IL-1ß. Additionally, miR-22 overexpression suppressed the proliferation and facilitated apoptosis in MH7A cells. IL6R was a target of miR-22. Besides, miR-22 overexpression inhibited the expression of IL6R and also suppressed inflammatory pathway NF-κB. These results indicated that miR-22 overexpression could restrain the activity of inflammation cells in RA by targeting IL6R and might be concerned with the inhibition of NF-κB pathway.

Optimal designs for pairwise calculation: An application to free energy perturbation in minimizing prediction variability.

Pairwise-based methods such as the free energy perturbation (FEP) method have been widely deployed to compute the binding free energy differences between two similar host-guest complexes. The calculated pairwise free energy difference is either directly adopted or transformed to absolute binding free energy for molecule rank ordering. We investigated, through both analytic derivations and simulations, how the selection of pairs in the experiment could impact the overall prediction precision. Our studies showed that (1) the estimated absolute binding free energy ( ΔG^ ) derived from calculated pairwise differences (ΔΔG) through weighted least squares fitting is more precise in prediction than the pairwise difference values when the number of pairs is more than the number of ligands and (2) prediction precision is influenced by both the total number of pairs and the specifically selected pairs, the latter being critically important when the number of calculated pairs is limited. Furthermore, we applied optimal experimental design in pair selection and found that the optimally selected pairs can outperform randomly selected pairs in prediction precision. In an illustrative example, we showed that, upon weighing ligand structure similarity into design optimization, the weighted optimal designs are more efficient than the literature reported designs. This work provides a new approach to assess retrospective pairwise-based prediction results, and a method to design new prospective pairwise-based experiments for molecular lead optimization. © 2019 Wiley Periodicals, Inc.