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Results for “Drug discovery”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

From PROTAC to inhibitor: Structure-guided discovery of potent and orally bioavailable BET inhibitors

An X-ray structure of a CLICK chemistry-based BET PROTAC bound to BRD2(BD2) inspired synthesis of JQ1 derived heterocyclic amides. This effort led to the discovery of potent BET inhibitors displaying overall improved profiles when compared to JQ1 and birabresib. A thiadiazole derived 1q (SJ1461) displayed excellent BRD4 and BRD2 affinity and high potency in the panel of acute leukaemia and medulloblastoma cell lines. A structure of 1q co-crystalised with BRD4-BD1 revealed polar interactions with the AZ/BC loops, in particular with Asn140 and Tyr139, rationalising the observed affinity improvements. In addition, exploration of pharmacokinetic properties of this class of compounds suggest that the heterocyclic amide moiety improves drug-like features. Finally, our study led to the discovery of potent and orally bioavailable BET inhibitor 1q (SJ1461) as a promising candidate for further development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A transcriptional relationship with a natural product disrupts mitochondrial biogenesis

Discovery of new compound leads and oncology targets to treat cancer will require overcoming resistance to traditional therapies such as BRAF and mitogen-activated protein kinase inhibitors (MAPKi). In addition, potent new therapies will benefit from selective localization at the cancer site rather than general cell toxicity which can lead to undesired side effects. This selectivity can be gained by identifying new compound leads that are “prodrugs”, that is they are activated by mechanisms selective to cancer cells leading to strong pharmacological activity (Zhang, 2017). Continuing discovery of anticancer agents that overcome resistance and take advantage of cancer cell mechanisms will be greatly augmented by returning to the potent well of natural products; in fact, an analysis of a 70-year period ending in 2014 showed that nearly 50% of approved anticancer drugs are or are derived from natural products (Newman, 2016). Discovery of new agents with high potency and selectivity will require natural product research focused on discovering biologically active compounds with unique structures and mechanisms of action that utilize target cell functions.

Wright, Aaron T.↗
DOE OSTI2024

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction

BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed. METHODS: To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies of opioid use disorder and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex of people who died of opioid overdose and control individuals. RESULTS: Here we identified 211 highly interrelated genes identified by genome-wide association studies or dysregulation in the dorsolateral prefrontal cortex of people who died of opioid overdose that implicated the Akt, BDNF (brain-derived neurotrophic factor), and ERK (extracellular signal-regulated kinase) pathways, identifying 414 drugs targeting 48 of these opioid addiction–associated genes. Some of the identified drugs are approved to treat other substance use disorders or depression. CONCLUSIONS: Our synthesis of multiomics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Autonomous alloy composition optimization using molecular dynamics guided by a large language model

Here, we present an autonomous materials discovery framework that couples a large language model (LLM) with molecular dynamics (MD) simulations to optimize Fe–Cr–Mn alloy compositions for tensile strength. Starting from six distinct compositions, the LLM operated as an intelligent agent, iteratively proposing changes based on prior simulation results and constraints. Over 50 iterations per case, the LLM adaptively explored the composition space, identifying high-strength regions, not easily accessible by conventional methods. The highest strength, 18.7 GPa, was achieved with Fe 71 Cr 25 Mn 4 composition, identified from a Fe 75 Cr 20 Mn 5 starting point. The LLM autonomously adjusted its strategy in real time, demonstrating closed-loop decision-making using commodity hardware. This approach showcases the potential of LLMs as scientific co-pilots, capable of accelerating materials discovery and generalizable to other domains like biology and drug design.

Autonomy↗
DOE OSTI2024

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Pressurized DNA state inside herpes capsids—A novel antiviral target

Drug resistance in viruses represents one of the major challenges of healthcare. As part of an effort to provide a treatment that avoids the possibility of drug resistance, we discovered a novel mechanism of action (MOA) and specific compounds to treat all nine human herpesviruses and animal herpesviruses. The novel MOA targets the pressurized genome state in a viral capsid, “turns off” capsid pressure, and blocks viral genome ejection into a cell nucleus, preventing viral replication. This work serves as a proof-of-concept to demonstrate the feasibility of a new antiviral target—suppressing pressure-driven viral genome ejection —that is likely impervious to developing drug resistance. This pivotal finding presents a platform for discovery of a new class of broad-spectrum treatments for herpesviruses and other viral infections with genome-pressure-dependent replication. A biophysical approach to antiviral treatment such as this is also a vital strategy to prevent the spread of emerging viruses where vaccine development is challenged by high mutation rates or other evasion mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In search of autophagy biomarkers in breast cancer: Receptor status and drug agnostic transcriptional changes during autophagy flux in cell lines

Autophagy drives drug resistance and drug-induced cancer cell cytotoxicity. Targeting the autophagy process could greatly improve chemotherapy outcomes. The discovery of specific inhibitors or activators has been hindered by challenges with reliably measuring autophagy levels in a clinical setting. We investigated drug-induced autophagy in breast cancer cell lines with differing ER/PR/Her2 receptor status by exposing them to known but divergent autophagy inducers each with a unique molecular target, tamoxifen, trastuzumab, bortezomib or rapamycin. Differential gene expression analysis from total RNA extracted during the earliest sign of autophagy flux showed both cell- and drug-specific changes. We analyzed the list of differentially expressed genes to find a common, cell- and drug-agnostic autophagy signature. Twelve mRNAs were significantly modulated by all the drugs and 11 were orthogonally verified with Q-RT-PCR (Klhl24, Hbp1, Crebrf, Ypel2, Fbxo32, Gdf15, Cdc25a, Ddit4, Psat1, Cd22, Ypel3). The drug agnostic mRNA signature was similarly induced by a mitochondrially targeted agent, MitoQ. In-silico analysis on the KM-plotter cancer database showed that the levels of these mRNAs are detectable in human samples and associated with breast cancer prognosis outcomes of Relapse-Free Survival in all patients (RSF), Overall Survival in all patients (OS), and Relapse-Free Survival in ER + Patients (RSF ER + ). High levels of Klhl24, Hbp1, Crebrf, Ypel2, CD22 and Ypel3 were correlated with better outcomes, whereas lower levels of Gdf15, Cdc25a, Ddit4 and Psat1 were associated with better prognosis in breast cancer patients. This gene signature uncovers candidate autophagy biomarkers that could be tested during preclinical and clinical studies to monitor the autophagy process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Fragment optimization and elaboration strategies – the discovery of two lead series of PRMT5/MTA inhibitors from five fragment hits

Here we describe the early stages of a fragment-based lead discovery (FBLD) project for a recently elucidated synthetic lethal target, the PRMT5/MTA complex, for the treatment of MTAP-deleted cancers. Starting with five fragment/PRMT5/MTA X-ray co-crystal structures, we employed a two-phase fragment elaboration process encompassing optimization of fragment hits and subsequent fragment growth to increase potency, assess synthetic tractability, and enable structure-based drug design. Two lead series were identified, one of which led to the discovery of the clinical candidate MRTX1719.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Drugsniffer: An Open Source Workflow for Virtually Screening Billions of Molecules for Binding Affinity to Protein Targets

The SARS-CoV2 pandemic has highlighted the importance of efficient and effective methods for identification of therapeutic drugs, and in particular has laid bare the need for methods that allow exploration of the full diversity of synthesizable small molecules. While classical high-throughput screening methods may consider up to millions of molecules, virtual screening methods hold the promise of enabling appraisal of billions of candidate molecules, thus expanding the search space while concurrently reducing costs and speeding discovery. Here, we describe a new screening pipeline, called drugsniffer, that is capable of rapidly exploring drug candidates from a library of billions of molecules, and is designed to support distributed computation on cluster and cloud resources. As an example of performance, our pipeline required ~40,000 total compute hours to screen for potential drugs targeting three SARS-CoV2 proteins among a library of ~3.7 billion candidate molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

Non-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The PTPN2/PTPN1 inhibitor ABBV-CLS-484 unleashes potent anti-tumour immunity

Immune checkpoint blockade is effective for some patients with cancer, but most are refractory to current immunotherapies and new approaches are needed to overcome resistance. The protein tyrosine phosphatases PTPN2 and PTPN1 are central regulators of inflammation, and their genetic deletion in either tumour cells or immune cells promotes anti-tumour immunity. However, phosphatases are challenging drug targets; in particular, the active site has been considered undruggable. Here we present the discovery and characterization of ABBV-CLS-484 (AC484), a first-in-class, orally bioavailable, potent PTPN2 and PTPN1 active-site inhibitor. AC484 treatment in vitro amplifies the response to interferon and promotes the activation and function of several immune cell subsets. In mouse models of cancer resistant to PD-1 blockade, AC484 monotherapy generates potent anti-tumour immunity. We show that AC484 inflames the tumour microenvironment and promotes natural killer cell and CD8 + T cell function by enhancing JAK–STAT signalling and reducing T cell dysfunction. Inhibitors of PTPN2 and PTPN1 offer a promising new strategy for cancer immunotherapy and are currently being evaluated in patients with advanced solid tumours (ClinicalTrials.gov identifier NCT04777994). More broadly, our study shows that small-molecule inhibitors of key intracellular immune regulators can achieve efficacy comparable to or exceeding that of antibody-based immune checkpoint blockade in preclinical models. Finally, to our knowledge, AC484 represents the first active-site phosphatase inhibitor to enter clinical evaluation for cancer immunotherapy and may pave the way for additional therapeutics that target this important class of enzymes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Structure-based development of a subtype-selective orexin 1 receptor antagonist

Orexin receptors belong to the superfamily of G-protein–coupled receptors (GPCRs) which represent the largest class of drug targets in humans. Despite the recent progress in structural biology, the development of subtype-selective orexin receptor and GPCR ligands in general remains challenging, due to the high sequence similarity among individual receptor subtypes. However, subtype-selective molecules are key to discerning the individual contributions of receptor subtypes to (patho-)physiology. Starting from the clinically used, non–subtype-selective orexin receptor antagonist suvorexant, we demonstrate how docking, crystallography, medicinal chemistry, and in vitro pharmacology can be combined to exploit single amino acid sequence differences for the discovery of subtype-selective probes. Such compounds will help to better understand orexin receptor pharmacology and develop promising drug candidates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structure-based design of SARS-CoV-2 papain-like protease inhibitors

The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus with high transmissibility and mutation rate. Given the paucity of orally bioavailable antiviral drugs to combat SARS-CoV-2 infection, there is a critical need for additional antivirals with alternative mechanisms of action. Papain-like protease (PL pro ) is one of the two SARS-CoV-2 encoded viral cysteine proteases essential for viral replication. PL pro cleaves at three sites of the viral polyproteins. In addition, PLpro antagonizes the host immune response upon viral infection by cleaving ISG15 and ubiquitin from host proteins. Therefore, PL pro is a validated antiviral drug target. In this study, we report the X-ray crystal structures of papain-like protease (PL pro ) with two potent inhibitors, Jun9722 and Jun9843 . Subsequently, we designed and synthesized several series of analogs to explore the structure-activity relationship, which led to the discovery of PL pro inhibitors with potent enzymatic inhibitory activity and antiviral activity against SARS-CoV-2. Together, the lead compounds are promising drug candidates for further development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Multivariate chemogenomic screening prioritizes new macrofilaricidal leads

Development of direct acting macrofilaricides for the treatment of human filariases is hampered by limitations in screening throughput imposed by the parasite life cycle. In vitro adult screens typically assess single phenotypes without prior enrichment for chemicals with antifilarial potential. We developed a multivariate screen that identified dozens of compounds with submicromolar macrofilaricidal activity, achieving a hit rate of >50% by leveraging abundantly accessible microfilariae. Adult assays were multiplexed to thoroughly characterize compound activity across relevant parasite fitness traits, including neuromuscular control, fecundity, metabolism, and viability. Seventeen compounds from a diverse chemogenomic library elicited strong effects on at least one adult trait, with differential potency against microfilariae and adults. Our screen identified five compounds with high potency against adults but low potency or slow-acting microfilaricidal effects, at least one of which acts through a novel mechanism. We show that the use of microfilariae in a primary screen outperforms model nematode developmental assays and virtual screening of protein structures inferred with deep learning. These data provide new leads for drug development, and the high-content and multiplex assays set a new foundation for antifilarial discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Combinatorial Biosynthesis of Sulfated Benzenediol Lactones with a Phenolic Sulfotransferase from Fusarium graminearum PH-1

Total biosynthesis or whole-cell biocatalytic production of sulfated small molecules relies on the discovery and implementation of appropriate sulfotransferase enzymes. Although fungi are prominent biocatalysts and have been used to sulfate drug-like phenolics, no gene encoding a sulfotransferase enzyme has been functionally characterized from these organisms. Here, we identify a phenolic sulfotransferase, FgSULT1, by genome mining from the plant-pathogenic fungus Fusarium graminearum PH-1. We expressed FgSULT1 in a Saccharomyces cerevisiae chassis to modify a broad range of benzenediol lactones and their nonmacrocyclic congeners, together with an anthraquinone, with the resulting unnatural natural product (uNP) sulfates displaying increased solubility. FgSULT1 shares low similarity with known animal and plant sulfotransferases. Instead, it forms a sulfotransferase family with putative bacterial and fungal enzymes for phase II detoxification of xenobiotics and allelochemicals. Among fungi, putative FgSULT1 homologues are encoded in the genomes of Fusarium spp. and a few other genera in nonsyntenic regions, some of which may be related to catabolic sulfur recycling. Computational structure modeling combined with site-directed mutagenesis revealed that FgSULT1 retains the key catalytic residues and the typical fold of characterized animal and plant sulfotransferases. Our work opens the way for the discovery of hitherto unknown fungal sulfotransferases and provides a synthetic biological and enzymatic platform that can be adapted to produce bioactive sulfates, together with sulfate ester standards and probes for masked mycotoxins, precarcinogenic toxins, and xenobiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structure-Based Discovery and Development of Highly Potent Dihydroorotate Dehydrogenase Inhibitors for Malaria Chemoprevention

Malaria remains a serious global health challenge, yet treatment and control programs are threatened by drug resistance. Dihydroorotate dehydrogenase (DHODH) was clinically validated as a target for treatment and prevention of malaria through human studies with DSM265, but currently no drugs against this target are in clinical use. We used structure-based computational tools including free energy perturbation (FEP+) to discover highly ligand efficient, potent, and selective pyrazolebased Plasmodium DHODH inhibitors through a scaffold hop from a pyrrole-based series. Optimized pyrazole-based compounds were identified with low nM-to-pM Plasmodium falciparum cell potency and oral activity in a humanized SCID mouse malaria infection model. The lead compound DSM1465 is more potent and has improved absorption, distribution, metabolism and excretion/pharmacokinetic (ADME/PK) properties compared to DSM265 that support the potential for once-monthly chemoprevention at a low dose. This compound meets the objective of identifying compounds with potential to be used for monthly chemoprevention in Africa to support malaria elimination efforts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Discovery of Marburg virus neutralizing antibodies from virus-naïve human antibody repertoires using large-scale structural predictions

Marburg virus (MARV) disease is lethal, with fatality rates up to 90%. Neutralizing antibodies (Abs) are promising drug candidates to prevent or treat the disease. Current efforts are focused in part on vaccine development to induce such MARV-neutralizing Abs. We analyzed the antibody repertoire from healthy unexposed and previously MARV-infected individuals to assess if naïve repertoires contain suitable precursor antibodies that could become neutralizing with a limited set of somatic mutations. Here, we computationally searched the human Ab variable gene repertoire for predicted structural homologs of the neutralizing Ab MR78 that is specific to the receptor binding site (RBS) of MARV glycoprotein (GP). Eight Ab heavy-chain complementarity determining region 3 (HCDR3) loops from MARV-naïve individuals and one from a previously MARV-infected individual were selected for testing as HCDR3 loop chimeras on the MR78 Ab framework. Three of these chimerized antibodies bound to MARV GP. We then tested a full-length native Ab heavy chain encoding the same 17-residue-long HCDR3 loop that bound to the MARV GP the best among the chimeric Abs tested. Despite only 57% amino acid sequence identity, the Ab from a MARV-naïve donor recognized MARV GP and possessed neutralizing activity against the virus. Crystallization of both chimeric and full-length native heavy chain-containing Abs provided structural insights into the mechanism of binding for these types of Abs. Our work suggests that the MARV GP RBS is a promising candidate for epitope-focused vaccine design to induce neutralizing Abs against MARV.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Discovery of Novel Rhizoctonia solani DHFR Inhibitors as Fungicides Using Virtual Screening

Dihydrofolate reductase (DHFR) is an essential enzyme in the folate pathway and has been recognized as a well-known target for antibacterial and antifungal drugs. We discovered eight compounds from the ZINC database using virtual screening to inhibit Rhizoctonia solani (R. solani), a fungal pathogen in crops. These compounds were evaluated with in vitro assays for enzymatic and antifungal activity. Among these, compound Hit8 is the most active R. solani DHFR inhibitor, with the IC 50 of 10.2 μM. The selectivity of inhibition is 22.3 against human DHFR with the IC 50 of 227.7 μM. Moreover, Hit8 has higher antifungal activity against R. solani (EC 50 of 38.2 mg L –1 ) compared with validamycin A (EC 50 of 67.6 mg L –1 ), a well-documented fungicide. These results suggest that Hit8 may be a potential fungicide. Finally, our study exemplifies a computer-aided method to discover novel inhibitors that could target plant pathogenic fungi.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗