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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗
DOE OSTI2025

Structural insights into VRC01-class bnAb precursors with diverse light chains elicited in the IAVI G001 human vaccine trial

The development of germline-targeting vaccines represents a potentially transformative strategy to elicit broadly neutralizing antibodies (bnAbs) against HIV and other antigenically diverse pathogens. Here, we report on structural characterization of vaccine-elicited VRC01-class bnAb precursors in the IAVI G001 Phase 1 clinical trial with the eOD-GT8 60mer nanoparticle as immunogen. High-resolution X-ray structures of eOD-GT8 monomer complexed with Fabs of five VRC01-class bnAb precursors with >90% germline identity revealed a conserved mode of binding to the HIV CD4-binding site via IGHV1-2-encoded heavy chains, mirroring mature bnAb interactions. The light-chain V-gene diversity emulated VRC01 bnAbs and stabilized antigen engagement, while their conserved five-residue LCDR3 motifs prevented steric clashes. Notably, the VRC01-class bnAb precursors accommodated the N276 glycan, a key barrier in HIV Env recognition, through structural rearrangements in HCDR3 or LCDR1, despite its absence in the immunogen. Surface plasmon resonance analysis showed that 87% of elicited antibodies retained glycan binding capacity, albeit with reduced affinity. These findings validate the ability of eOD-GT8 60mer nanoparticles to prime VRC01-class bnAb precursors with native-like paratopes but with intrinsic glycan adaptability. Structural mimicry of mature bnAbs was observed even with limited somatic hypermutation, indicating that critical features are encoded in the germline repertoire. The structures highlight how germline-encoded features drive bnAb-like recognition at early stages. This work provides molecular evidence supporting germline targeting in humans and provides guidance for designing booster immunogens to shepherd affinity maturation toward broad neutralization.

Science & Technology - Other Topics↗
DOE OSTI2021

Structure and Function of REP34 Implicates Carboxypeptidase Activity in Francisella tularensis Host Cell Invasion

Francisella tularensis is the etiological agent of tularemia, or rabbit fever. Although F. tularensis is a recognized biothreat agent with broad and expanding geographical range, its mechanism of infection and environmental persistence remain poorly understood. Previously, we identified seven F. tularensis proteins that induce a rapid encystment phenotype (REP) in the free-living amoeba, Acanthamoeba castellanii. Encystment is essential to the pathogen's long term intracellular survival in the amoeba. Here, we characterize the cellular and molecular function of REP34, a REP protein with a mass of 34 kDa. A REP34 knock-out strain of F. tularensis has a reduced ability to both induce encystment in A. castellanii and invade human macrophages. We determined the crystal structure of REP34 to 2.05-Å resolution and demonstrate robust carboxypeptidase B-like activity for the enzyme. REP34 is a zinc-containing monomeric protein with close structural homology to the metallocarboxypeptidase family of peptidases. REP34 possesses a novel topology and substrate binding pocket that deviates from the canonical funnelin structure of carboxypeptidases, putatively resulting in a catalytic role for a conserved tyrosine and distinct S1' recognition site. Taken together, these results identify REP34 as an active carboxypeptidase, implicate the enzyme as a potential key F. tularensis effector protein, and may help elucidate a mechanistic understanding of F. tularensis infection of phagocytic cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tandem sialoglycan-binding modules in a Streptococcus sanguinis serine-rich repeat adhesin create target dependent avidity effects

Sialic acid–binding immunoglobulin-like lectins (Siglec)–like domains of streptococcal serine-rich repeat (SRR) adhesins recognize sialylated glycans on human salivary, platelet, and plasma glycoproteins via a YTRY sequence motif. The SRR adhesin from Streptococcus sanguinis strain SK1 has tandem sialoglycan-binding domains and has previously been shown to bind sialoglycans with high affinity. However, both domains contain substitutions within the canonical YTRY motif, making it unclear how they interact with host receptors. To identify how the S. sanguinis strain SK1 SRR adhesin affects interactions with sialylated glycans and glycoproteins, we determined high-resolution crystal structures of the binding domains alone and with purified trisaccharides. These structural studies determined that the ligands still bind at the noncanonical binding motif, but with fewer hydrogen-bonding interactions to the protein than is observed in structures of other Siglec-like adhesins. Complementary biochemical studies identified that each of the two binding domains has a different selectivity profile. Interestingly, the binding of SK1 to platelets and plasma glycoproteins identified that the interaction to some host targets is dominated by the contribution of one binding domain, whereas the binding to other host receptors is mediated by both binding domains. These results provide insight into outstanding questions concerning the roles of tandem domains in targeting host receptors and suggest mechanisms for how pathogens can adapt to the availability of a range of related but nonidentical host receptors. They further suggest that the definition of the YTRY motif should be changed to ΦTRX, a more rigorous description of this sialic acid–recognition motif given recent findings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Trapping conformational states of a flavin-dependent N-monooxygenase in crystallo reveals protein and flavin dynamics

The siderophore biosynthetic enzyme A (SidA) ornithine hydroxylase from Aspergillus fumigatus is a fungal disease drug target involved in the production of hydroxamate-containing siderophores, which are used by the pathogen to sequester iron. SidA is an N -monooxygenase that catalyzes the NADPH-dependent hydroxylation of l -ornithine through a multistep oxidative mechanism, utilizing a C4a-hydroperoxyflavin intermediate. Here we present four new crystal structures of SidA in various redox and ligation states, including the first structure of oxidized SidA without NADP(H) or l -ornithine bound (resting state). The resting state structure reveals a new out active site conformation characterized by large rotations of the FAD isoalloxazine around the C1–'C2' and N10–C1' bonds, coupled to a 10-Å movement of the Tyr-loop. Additional structures show that either flavin reduction or the binding of NADP(H) is sufficient to drive the FAD to the in conformation. The structures also reveal protein conformational changes associated with the binding of NADP(H) and l -ornithine. Some of these residues were probed using site-directed mutagenesis. Docking was used to explore the active site of the out conformation. These calculations identified two potential ligand-binding sites. Altogether, our results provide new information about conformational dynamics in flavin-dependent monooxygenases. Overall, understanding the different active site conformations that appear during the catalytic cycle may allow fine-tuning of inhibitor discovery efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Broad and potent neutralizing human antibodies to tick-borne flaviviruses protect mice from disease

Tick-borne encephalitis virus (TBEV) is an emerging human pathogen that causes potentially fatal disease with no specific treatment. Mouse monoclonal antibodies are protective against TBEV, but little is known about the human antibody response to infection. Here, we report on the human neutralizing antibody response to TBEV in a cohort of infected and vaccinated individuals. Expanded clones of memory B cells expressed closely related anti-envelope domain III (EDIII) antibodies in both groups of volunteers. However, the most potent neutralizing antibodies, with IC50s below 1 ng/ml, were found only in individuals who recovered from natural infection. These antibodies also neutralized other tick-borne flaviviruses, including Langat, louping ill, Omsk hemorrhagic fever, Kyasanur forest disease, and Powassan viruses. Structural analysis revealed a conserved epitope near the lateral ridge of EDIII adjoining the EDI–EDIII hinge region. Prophylactic or early therapeutic antibody administration was effective at low doses in mice that were lethally infected with TBEV.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Contrasting the characteristics of atmospheric pressure plasma jets operated with single and double dielectric material: physicochemical characteristics and application to bacterial killing

Abstract This study reports an experimental comparison of two types of atmospheric pressure plasma jets in terms of their fundamental plasma characteristics and efficacy in bacterial sterilization. The plasma jets are fabricated by inserting a high voltage electrode inside a one-end closed (double DBD plasma jet) or both ends open (single DBD plasma jet) quartz tubes which are further enclosed inside a second quartz tube containing a ground electrode. Both plasma jets are operated in contact with water surface by using a unipolar pulsed DC power supply with helium as the working gas. Results from electrical and time-resolved imaging show that the single DBD configuration induces 3–4 times higher accumulation of charges onto the water surface with significantly faster propagation of plasma bullets. These results are accompanied by the higher discharge intensity as well as stronger emissions from short-lived reactive species which were analyzed through optical emission spectroscopy at the plasma-water interface. The rotational temperature for the single DBD configuration was observed to be higher making it unsafe for direct treatments of sensitive biological targets. These characteristics of the single DBD configuration result in the production of more than two times higher concentration of H 2 O 2 in plasma activated water. Shielding of the HV electrode reduces the plasma potential which in turn reduces the electric field & electron energy at the plasma-water interface. The reduced electric field for the double DBD configuration was lower by ≈463 Td than the single DBD configuration. The bactericidal efficacy of the two configurations of the plasma jets were tested against Escherichia coli , a well studied Gram-negative bacterium that can be commensal and pathogenic in human body. Our results demonstrate that although single DBD plasma jet result in stronger antibacterial effects, the double DBD configuration could be safer.

Physics↗
DOE OSTI2022

Surface ionization waves propagating over non-planar substrates: wavy surfaces, cut-pores and droplets

Atmospheric pressure plasmas intersecting with dielectric surfaces will often transition into surface ionization waves (SIWs). Several applications of these discharges are purposely configured to be SIWs. During propagation of an SIW over a dielectric surface, the plasma charges the surface while responding to changes in geometrical and electrical material properties. This is particularly important for non-planar surfaces where polarization of the dielectric results in local electric field enhancement. In this paper, we discuss results from computational investigations of negative and positive SIWs propagating over nonplanar dielectrics in three configurations—wavy surfaces, cuts through porous materials and water droplets on flat surfaces. Here we found that negative SIWs are particularly sensitive to the electric field enhancement that occurs at the crests of non-planar surfaces. The local increase in ionization rates by the electric field enhancement can result in the SIW detaching from the surface, which produces non-uniform plasma exposure of the surface. Positive SIWs tend to adhere to the surface to a greater degree. These trends indicate that treatment of pathogen containing droplets on surfaces may be best performed by positive SIWs. The same principles apply to the surfaces cut through pores. Buried pores with small openings to the SIW may be filled by plasma by either flow of plasma into the pore (large opening) or initiated by photoionization (small opening), depending on the size of the opening compared to the Debye length.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Tree mortality in a warming world: causes, patterns, and implications

This ERL focus collection has published 17 papers that have advanced our understanding of different dimensions of warming-induced tree mortality. Here we summarize these focus collection papers, organized by four topics related to tree mortality: pathogens, droughts/heat waves, fire/bark beetles, and teleconnections/air pollution. This focus collection illustrates a variety of methods in measuring and modeling tree-mortality, and adds significant new research findings into the scientific literature on tree mortality from hotter droughts. Some of these results also are useful for policymakers and forest managers in addressing amplified forest stress and tree mortality as a result of increasingly severe warming-induced climate and weather extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Disturbances in North American boreal forest and Arctic tundra: impacts, interactions, and responses

Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hydrology controls thermokarst and alters carbon cycling and methane emissions in peatlands near the southern limit of permafrost

Permafrost peatlands store vast amounts of frozen carbon across northern landscapes. When ground ice melts, surface subsidence produces thermokarst landforms that expand wetlands at the edges of permafrost plateaus. Thermokarst represents an accelerating climate feedback, but uncertainties remain about how ground ice, hydrology, and vegetation interact to shape landscape change and carbon fluxes. We extended the process-based model ecosys to simulate thermokarst dynamics in laterally coupled 2D transects at a well-characterized boreal peatland site in Canada’s Northwest Territories. After benchmarking against site observations, we varied ground ice content and hydrologic boundary conditions across ranges typical near the southern permafrost limit. Simulations revealed distinct degradation regimes governed by the elevation difference between the frost table and the external water table. Rates of lateral retreat, the thaw-driven encroachment of wetlands into adjacent plateaus, ranged from 0 to >2 m yr −1 under identical weather forcing, consistent with observations and highlighting the strong role of WT and ground ice. Simulated vegetation dynamics indicate that black spruce mortality cannot be explained by anoxia alone, pointing to additional stressors such as root damage, pathogens, or physical destabilization. Despite large hydrologic shifts, net ecosystem CO 2 exchange remained a slight sink after collapse, while methane (CH 4 ) emissions rose by one to two orders of magnitude. As a result, lateral retreat substantially increases the greenhouse warming potential of permafrost peatlands (1.7 million km 2 in area), with simulated emissions of 0.1–10 Mt CO 2 -eq decade −1 depending on hydrology and retreat rates. These results underscore the need to account for both ground ice and hydrologic dynamics when assessing thermokarst-driven climate feedbacks.

carbon cycling↗
DOE OSTI2021

Biodiversity and Global Health: Intersection of Health, Security, and the Environment

One of the biggest consequences of large-scale environmental change is the loss of biodiversity. Recent studies predict a loss of 1 million species in the near future. Biodiversity loss and land use change through anthropogenic disturbance are known to affect disease exposure, disease severity, and disease impacts. It is becoming increasingly clear that biodiversity loss will lead to an increase in infectious diseases in certain regions. Changes in biodiversity may contain important signatures for prediction of infectious diseases and outbreaks. Here, we argue that areas of high or rapid biodiversity loss will be critical to monitor under the umbrella of global health security. Global Health Security consists of the actions and activities required to reduce the impact of public health events in populations living in different geographic regions and across international borders. Like infectious diseases, climate change and other causes of environmental changes do not respect international borders and are becoming more widespread in all parts of the world. Here, the relationships among biodiversity, climate and environmental changes, and pathogen prevalence are dynamic, context dependent, and complex. Accounting for this complexity requires the inclusion of the environment sector, presently missing, when evaluating the potential of global health security actions for mitigating disease risks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Recognition of nuclear export signals by CRM1 carrying the oncogenic E571K mutation

The E571K mutation of CRM1 is highly prevalent in some cancers, but its mechanism of tumorigenesis is unclear. Glu571 of CRM1 is located in its nuclear export signal (NES)-binding groove, suggesting that binding of select NESs may be altered. We generated HEK 293 cells with either monoallelic CRM1WT/E571K or biallelic CRM1E571K/E571K using CRISPR/Cas9. We also combined analysis of binding affinities and structures of 27 diverse NESs for wild-type and E571K CRM1 with structure-based bioinformatics. While most NESs bind the two CRM1 similarly, NESs from Mek1, eIF4E-transporter, and RPS2 showed >10-fold affinity differences. These NESs have multiple charged side chains binding close to CRM1 position 571, but this feature alone was not sufficient to predict different binding to CRM1(E571K). Consistent with eIF4E-transporter NES binding weaker to CRM1(E571K), eIF4E-transporter was mislocalized in tumor cells carrying CRM1(E571K). This serves as proof of concept that understanding how CRM1(E571K) affects NES binding provides a platform for identifying cargoes that are mislocalized in cancer upon CRM1 mutation. Finally, we showed that large affinity changes seen with some NES peptides (of Mek1 and RPS2) do not always translate to the full-length cargoes, suggesting limitations with current NES prediction methods. Therefore, comprehensive studies like ours are imperative to identify CRM1 cargoes with real pathogenic potential.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting

Abstract Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as underlying pathogenic mechanisms are broad and associated with multiple genomic pathways. The scientific community has exerted significant efforts to generate public drug screening datasets, giving a path to various machine learning models that attempt to reason over complex data space of small compounds and biological characteristics of tumors. However, the data depth is still lacking compared to application domains like computer vision or natural language processing domains, limiting current learning capabilities. To combat this issue and improves the generalizability of the DRP models, we are exploring strategies that explicitly address the imbalance in the DRP datasets. We reframe the problem as a multi-objective optimization across multiple drugs to maximize deep learning model performance. We implement this approach by constructing Multi-Objective Optimization Regularized by Loss Entropy loss function and plugging it into a Deep Learning model. We demonstrate the utility of proposed drug discovery methods and make suggestions for further potential application of the work to achieve desirable outcomes in the healthcare field.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Persistent minimal sequences of SARS-CoV-2

Abstract Motivation Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 14 million cases and more than half million deaths. Given the absence of implemented therapies, new analysis, diagnosis and therapeutics are of great importance. Results Analysis of SARS-CoV-2 genomes from the current outbreak reveals the presence of short persistent DNA/RNA sequences that are absent from the human genome and transcriptome (PmRAWs). For the PmRAWs with length 12, only four exist at the same location in all SARS-CoV-2. At the gene level, we found one PmRAW of size 13 at the Spike glycoprotein coding sequence. This protein is fundamental for binding in human ACE2 and further use as an entry receptor to invade target cells. Applying protein structural prediction, we localized this PmRAW at the surface of the Spike protein, providing a potential targeted vector for diagnostics and therapeutics. In addition, we show a new pattern of relative absent words (RAWs), characterized by the progressive increase of GC content (Guanine and Cytosine) according to the decrease of RAWs length, contrarily to the virus and host genome distributions. New analysis shows the same property during the Ebola virus outbreak. At a computational level, we improved the alignment-free method to identify pathogen-specific signatures in balance with GC measures and removed previous size limitations. Availability and implementation https://github.com/cobilab/eagle. Supplementary information Supplementary data are available at Bioinformatics online.

Pratas, Diogo↗
DOE OSTI2022

RF-Net 2: fast inference of virus reassortment and hybridization networks

Abstract Motivation A phylogenetic network is a powerful model to represent entangled evolutionary histories with both divergent (speciation) and convergent (e.g. hybridization, reassortment, recombination) evolution. The standard approach to inference of hybridization networks is to (i) reconstruct rooted gene trees and (ii) leverage gene tree discordance for network inference. Recently, we introduced a method called RF-Net for accurate inference of virus reassortment and hybridization networks from input gene trees in the presence of errors commonly found in phylogenetic trees. While RF-Net demonstrated the ability to accurately infer networks with up to four reticulations from erroneous input gene trees, its application was limited by the number of reticulations it could handle in a reasonable amount of time. This limitation is particularly restrictive in the inference of the evolutionary history of segmented RNA viruses such as influenza A virus (IAV), where reassortment is one of the major mechanisms shaping the evolution of these pathogens. Results Here, we expand the functionality of RF-Net that makes it significantly more applicable in practice. Crucially, we introduce a fast extension to RF-Net, called Fast-RF-Net, that can handle large numbers of reticulations without sacrificing accuracy. In addition, we develop automatic stopping criteria to select the appropriate number of reticulations heuristically and implement a feature for RF-Net to output error-corrected input gene trees. We then conduct a comprehensive study of the original method and its novel extensions and confirm their efficacy in practice using extensive simulation and empirical IAV evolutionary analyses. Availability and implementation RF-Net 2 is available at https://github.com/flu-crew/rf-net-2. Supplementary information Supplementary data are available at Bioinformatics online.

Markin, Alexey (ORCID:0000000332809050)↗
DOE OSTI2022

EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts

Abstract Summary Genomics has become an essential technology for surveilling emerging infectious disease outbreaks. A range of technologies and strategies for pathogen genome enrichment and sequencing are being used by laboratories worldwide, together with different and sometimes ad hoc, analytical procedures for generating genome sequences. A fully integrated analytical process for raw sequence to consensus genome determination, suited to outbreaks such as the ongoing COVID-19 pandemic, is critical to provide a solid genomic basis for epidemiological analyses and well-informed decision making. We have developed a web-based platform and integrated bioinformatic workflows that help to provide consistent high-quality analysis of SARS-CoV-2 sequencing data generated with either the Illumina or Oxford Nanopore Technologies (ONT). Using an intuitive web-based interface, this workflow automates data quality control, SARS-CoV-2 reference-based genome variant and consensus calling, lineage determination and provides the ability to submit the consensus sequence and necessary metadata to GenBank, GISAID and INSDC raw data repositories. We tested workflow usability using real world data and validated the accuracy of variant and lineage analysis using several test datasets, and further performed detailed comparisons with results from the COVID-19 Galaxy Project workflow. Our analyses indicate that EC-19 workflows generate high-quality SARS-CoV-2 genomes. Finally, we share a perspective on patterns and impact observed with Illumina versus ONT technologies on workflow congruence and differences. Availability and implementation https://edge-covid19.edgebioinformatics.org, and https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multimodal representation learning for predicting molecule–disease relations

Motivation: Predicting molecule–disease indications and side effects is important for drug development and pharmacovigilance. Comprehensively mining molecule–molecule, molecule–disease and disease–disease semantic dependencies can potentially improve prediction performance. Methods: We introduce a Multi-Modal REpresentation Mapping Approach to Predicting molecular-disease relations (M2REMAP) by incorporating clinical semantics learned from electronic health records (EHR) of 12.6 million patients. Specifically, M2REMAP first learns a multimodal molecule representation that synthesizes chemical property and clinical semantic information by mapping molecule chemicals via a deep neural network onto the clinical semantic embedding space shared by drugs, diseases and other common clinical concepts. To infer molecule–disease relations, M2REMAP combines multimodal molecule representation and disease semantic embedding to jointly infer indications and side effects. Results: We extensively evaluate M2REMAP on molecule indications, side effects and interactions. Results show that incorporating EHR embeddings improves performance significantly, for example, attaining an improvement over the baseline models by 23.6% in PRC-AUC on indications and 23.9% on side effects. Further, M2REMAP overcomes the limitation of existing methods and effectively predicts drugs for novel diseases and emerging pathogens. Availability and implementation: The code is available at https://github.com/celehs/M2REMAP, and prediction results are provided at https://shiny.parse-health.org/drugs-diseases-dev/.

59 BASIC BIOLOGICAL SCIENCES↗