Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI

As the importance of high-throughput screening (HTS) continues to grow due to its value in early stage drug discovery and data generation for training machine learning models, there is a growing need for robust methods for pre-screening compounds to identify and prevent false-positive hits. Small, colloidally aggregating molecules are one of the primary sources of false-positive hits in high-throughput screens, making them an ideal candidate to target for removal from libraries using predictive pre-screening tools. However, a lack of understanding of the causes of molecular aggregation introduces difficulty in the development of predictive tools for detecting aggregating molecules. Herein, we present an examination of the molecular features differentiating datasets of aggregating and non-aggregating molecules, as well as a machine learning approach to predicting molecular aggregation. Our method uses explainable graph neural networks and counterfactuals to reliably predict and explain aggregation, giving additional insights and design rules for future screening. The integration of this method in HTS approaches will help combat false positives, providing better lead molecules more rapidly and thus accelerating drug discovery cycles.Comment: 17 pages, plus S

a CLARIFY trial sub-study

Publisher Copyright: © 2022Background: The difference between expert level (L3) reader and artificial intelligence (AI) performance for quantifying coronary plaque and plaque components is unknown. Objective: This study evaluates the interobserver variability among expert readers for quantifying the volume of coronary plaque and plaque components on coronary computed tomographic angiography (CCTA) using an artificial intelligence enabled quantitative CCTA analysis software as a reference (AI-QCT). Methods: This study uses CCTA imaging obtained from 232 patients enrolled in the CLARIFY (CT EvaLuation by ARtificial Intelligence For Atherosclerosis, Stenosis and Vascular MorphologY) study. Readers quantified overall plaque volume and the % breakdown of noncalcified plaque (NCP) and calcified plaque (CP) on a per vessel basis. Readers categorized high risk plaque (HRP) based on the presence of low-attenuation-noncalcified plaque (LA-NCP) and positive remodeling (PR; ≥1.10). All CCTAs were analyzed by an FDA-cleared software service that performs AI-driven plaque characterization and quantification (AI-QCT) for comparison to L3 readers. Reader generated analyses were compared among readers and to AI-QCT generated analyses. Results: When evaluating plaque volume on a per vessel basis, expert readers achieved moderate to high interobserver consistency with an intra-class correlation coefficient of 0.78 for a single reader score and 0.91 for mean scores. There was a moderate trend between readers 1, 2, and 3 and AI with spearman coefficients of 0.70, 0.68 and 0.74, respectively. There was high discordance between readers and AI plaque component analyses. When quantifying %NCP v. %CP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.23, 0.34 and 0.24, respectively, compared to AI with a spearman coefficient of 0.38, 0.51, and 0.60, respectively. The intra-class correlation coefficient among readers for plaque composition assessment was 0.68. With respect to HRP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.22, 0.26, and 0.17, respectively, and a spearman coefficient of 0.36, 0.35, and 0.44, respectively. Conclusion: Expert readers performed moderately well quantifying total plaque volumes with high consistency. However, there was both significant interobserver variability and high discordance with AI-QCT when quantifying plaque composition.publishersversionpublishe

Treatment with Anti-HER2 Chimeric Antigen Receptor Tumor-Infiltrating Lymphocytes (CAR-TILs) Is Safe and Associated with Antitumor Efficacy in Mice and Companion Dogs

Patients with metastatic melanoma have a historically poor prognosis, but recent advances in treatment options, including targeted therapy and immunotherapy, have drastically improved the outcomes for some of these patients. However, not all patients respond to available treatments, and around 50% of patients with metastatic cutaneous melanoma and almost all patients with metastases of uveal melanoma die of their disease. Thus, there is a need for novel treatment strategies for patients with melanoma that do not benefit from the available therapies. Chimeric antigen receptor-expressing T (CAR-T) cells are largely unexplored in melanoma. Traditionally, CAR-T cells have been produced by transducing blood-derived T cells with a virus expressing CAR. However, tumor-infiltrating lymphocytes (TILs) can also be engineered to express CAR, and such CAR-TILs could be dual-targeting. To this end, tumor samples and autologous TILs from metastasized human uveal and cutaneous melanoma were expanded in vitro and transduced with a lentiviral vector encoding an anti-HER2 CAR construct. When infused into patient-derived xenograft (PDX) mouse models carrying autologous tumors, CAR-TILs were able to eradicate melanoma, even in the absence of antigen presentation by HLA. To advance this concept to the clinic and assess its safety in an immune-competent and human-patient-like setting, we treated four companion dogs with autologous anti-HER2 CAR-TILs. We found that these cells were tolerable and showed signs of anti-tumor activity. Taken together, CAR-TIL therapy is a promising avenue for broadening the tumor-targeting capacity of TILs in patients with checkpoint immunotherapy-resistant melanoma

Influenza A virus evolution and spatio-temporal dynamics in Eurasian wild birds: a phylogenetic and phylogeographical study of whole-genome sequence data.

Low pathogenic avian influenza A viruses (IAVs) have a natural host reservoir in wild waterbirds and the potential to spread to other host species. Here, we investigated the evolutionary, spatial and temporal dynamics of avian IAVs in Eurasian wild birds. We used whole-genome sequences collected as part of an intensive long-term Eurasian wild bird surveillance study, and combined this genetic data with temporal and spatial information to explore the virus evolutionary dynamics. Frequent reassortment and co-circulating lineages were observed for all eight genomic RNA segments over time. There was no apparent species-specific effect on the diversity of the avian IAVs. There was a spatial and temporal relationship between the Eurasian sequences and significant viral migration of avian IAVs from West Eurasia towards Central Eurasia. The observed viral migration patterns differed between segments. Furthermore, we discuss the challenges faced when analysing these surveillance and sequence data, and the caveats to be borne in mind when drawing conclusions from the apparent results of such analyses.We thank all ornithologists and other collaborators for their continuous support. We thank V. Munster, E. Skepner, O. Vuong, C. Baas, J. Guldemeester, M. Schutten, G. van der Water, D. Smith and E. Bortz for technical support and stimulating discussions. This manuscript was prepared while D.E. Wentworth was employed at the JCVI. The opinions expressed in this article are the author’s own and do not reflect the view of the Centers for Disease Control, the Department of Health and Human Services, or the United States government. This work was supported by NIAID/NIH contract HHSN266200700010C, HHSN272201400008C, HHSN272201400006C and HHSN272200900007C, a Wellcome Trust Fellowship Strategic Travel Award under contract WT089235MF, a DTRA FRCWMD Broad Agency Announcement under contract HDTRA1-09-14-FRCWMD GRANT11177182, by the EU Framework six program NewFluBird (044490) by contracts with the Dutch Ministry of Economic Affairs and a NIAID/NIH CEIRS travel grant under contract HHSN266200700010C. The Swedish sampling and analysis was supported by the Swedish Research Councils VR and FORMAS.This is the final version of the article. It first appeared from the Society for General Microbiology via http://dx.doi.org/10.1099/vir.0.00015

Science CONOPS for Application of SPORT Mission Data to Study Large (~1000km) Ionospheric Plasma Depletions

The Scintillation Prediction Observations Research Task (SPORT) mission is a single 6U CubeSat space weather satellite planned for an October 2022 launch into an ISS-like orbit. The primary purpose of the SPORT mission is to determine the longitudinal effects on equatorial plasma bubble (EPB) growth resulting from the offset dipole magnetic field of the Earth. By combining field and plasma measurements from SPORT with other low-altitude (i.e., alt \u3c 1000 km) spacecraft, it is possible to investigate large-scale (\u3e 1000 km) EPB structures. The types of investigation made possible by measurements from SPORT and other contemporaneous missions include 1) dynamics of depleted magnetic flux tubes; 2) dynamics of field-aligned EPB expansion versus propagation speed; 3) EPB vertical extent; and 4) EPB temporal evolution. To support these investigation types, the respective modes of conjunctions are: 1) simultaneous intersection of a magnetic flux tube; 2) intersection of magnetic flux tube separated in time; 3) Simultaneous Latitude/Longitude position conjunction; and 4) Non-simultaneous latitude/longitude position conjunction. This paper will summarize the SPORT satellite and data used for Science CONOPS to accomplish these objectives

mir-181A/B-1 controls thymic selection of treg cells and tunes their suppressive capacity

The interdependence of selective cues during development of regulatory T cells (Treg cells) in the thymus and their suppressive function remains incompletely understood. Here, we analyzed this interdependence by taking advantage of highly dynamic changes in expression of microRNA 181 family members miR-181a-1 and miR-181b-1 (miR-181a/b-1) during late T-cell development with very high levels of expression during thymocyte selection, followed by massive down-regulation in the periphery. Loss of miR-181a/b-1 resulted in inefficient de novo generation of Treg cells in the thymus but simultaneously permitted homeostatic expansion in the periphery in the absence of competition. Modulation of T-cell receptor (TCR) signal strength in vivo indicated that miR-181a/b-1 controlled Treg-cell formation via establishing adequate signaling thresholds. Unexpectedly, miR-181a/b-1–deficient Treg cells displayed elevated suppressive capacity in vivo, in line with elevated levels of cytotoxic T-lymphocyte–associated 4 (CTLA-4) protein, but not mRNA, in thymic and peripheral Treg cells. Therefore, we propose that intrathymic miR-181a/b-1 controls development of Treg cells and imposes a developmental legacy on their peripheral function