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Results for “Drug Design”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A multiplexed bacterial two-hybrid for rapid characterization of protein–protein interactions and iterative protein design

Protein-protein interactions (PPIs) are crucial for biological functions and have applications ranging from drug design to synthetic cell circuits. Coiled-coils have been used as a model to study the sequence determinants of specificity. However, building well-behaved sets of orthogonal pairs of coiled-coils remains challenging due to inaccurate predictions of orthogonality and difficulties in testing at scale. To address this, we develop the next-generation bacterial two-hybrid (NGB2H) method, which allows for the rapid exploration of interactions of programmed protein libraries in a quantitative and scalable way using next-generation sequencing readout. We design, build, and test large sets of orthogonal synthetic coiled-coils, assayed over 8,000 PPIs, and used the dataset to train a more accurate coiled-coil scoring algorithm (iCipa). After characterizing nearly 18,000 new PPIs, we identify to the best of our knowledge the largest set of orthogonal coiled-coils to date, with fifteen on-target interactions. Our approach provides a powerful tool for the design of orthogonal PPIs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Neutron diffraction reveals protonation states in pyridoxal‐5′‐phosphate‐free and glycine external aldimine‐bound serine hydroxymethyltransferase

Serine hydroxymethyltransferase (SHMT) is a critical enzyme in the one-carbon (1C) metabolism pathway catalyzing the reversible conversion of L-Ser into Gly and concurrent transfer of 1C unit to tetrahydrofolate (THF) to give 5,10-methylene-THF (5,10-MTHF), which is used in the downstream syntheses of biomolecules critical for cell proliferation. The cellular 1C metabolism is hijacked by many cancer types to support cancer cell proliferation, making SHMT a promising target for the design and development of novel small-molecule antimetabolite chemotherapies. To advance structure-assisted drug design, knowledge of SHMT catalysis is crucial, but can only be fully realized when the atomic details of each reaction step governed by the acid–base catalysis are elucidated by visualizing active site hydrogen atoms. Here, we used room-temperature neutron crystallography to directly determine protonation states in Thermus thermophilus SHMT (TthSHMT), capturing protomer A in the apo form lacking the coenzyme pyridoxal 5′-phosphate (PLP), and protomer B as a ternary complex with PLP–Gly-external aldimine and (6S)-5-methyltetrahydrofolate (5MTHF). We observed protonation of the Schiff base nitrogen in PLP–Gly and neutrality of the catalytic Lys226 side chain in the ternary complex, whereas Lys226 is protonated and positively charged in the apo-active site. Furthermore, we obtained an X-ray structure of TthSHMT in complex with the substrate THF, which binds identically as 5MTHF at the peripheral binding site. In conclusion, the unique structural and functional information provided by neutron crystallography, in combination with X-ray structures, can be employed in the rational design of SHMT inhibitors.

X-ray crystallography↗
DOE OSTI2021

Rational approach to drug discovery for human schistosomiasis

Human schistosomiasis is a debilitating, life-threatening disease affecting more than 229 million people in as many as 78 countries. There is only one drug of choice effective against all three major species of Schistosoma, praziquantel (PZQ). However, as with many monotherapies, evidence for resistance is emerging in the field and can be selected for in the laboratory. Previously used therapies include oxamniquine (OXA), but shortcomings such as drug resistance and affordability resulted in discontinuation. Employing a genetic, biochemical and molecular approach, a sulfotransferase (SULT-OR) was identified as responsible for OXA drug resistance. By crystallizing SmSULT- OR with OXA, the mode of action of OXA was determined. This information allowed a rational approach to novel drug design. Our team approach with schistosome biologists, medicinal chemists, structural biologists and geneticists has enabled us to develop and test novel drug derivatives of OXA to treat this disease. Using an iterative process for drug development, we have successfully identified derivatives that are effective against all three species of the parasite. One derivative CIDD-0149830 kills 100% of all three human schistosome species within 5 days. The goal is to generate a second therapeutic with a different mode of action that can be used in conjunction with praziquantel to overcome the ever-growing threat of resistance and improve efficacy. The ability and need to design, screen, and develop future, affordable therapeutics to treat human schistosomiasis is critical for successful control program outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

De novo design of drug-binding proteins with predictable binding energy and specificity

The de novo design of small molecule–binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase–1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule–binding proteins with tuned interaction energies is feasible entirely from computation.

Science & Technology - Other Topics↗
DOE OSTI2020

The antibiotic sorangicin A inhibits promoter DNA unwinding in a Mycobacterium tuberculosis rifampicin-resistant RNA polymerase

Rifampicin (Rif) is a first-line therapeutic used to treat the infectious disease tuberculosis (TB), which is caused by the pathogen Mycobacterium tuberculosis (Mtb). The emergence of Rif-resistant (Rif R ) Mtb presents a need for new antibiotics. Rif targets the enzyme RNA polymerase (RNAP). Sorangicin A (Sor) is an unrelated inhibitor that binds in the Rif-binding pocket of RNAP. Sor inhibits a subset of Rif R RNAPs, including the most prevalent clinical Rif R RNAP substitution found in Mtb infected patients (S456>L of the β subunit). In this paper, we present structural and biochemical data demonstrating that Sor inhibits the wild-type Mtb RNAP by a similar mechanism as Rif: by preventing the translocation of very short RNAs. By contrast, Sor inhibits the RifR S456L enzyme at an earlier step, preventing the transition of a partially unwound promoter DNA intermediate to the fully opened DNA and blocking the template-strand DNA from reaching the active site in the RNAP catalytic center. By defining template-strand blocking as a mechanism for inhibition, we provide a mechanistic drug target in RNAP. Our finding that Sor inhibits the wild-type and mutant RNAPs through different mechanisms prompts future considerations for designing antibiotics against resistant targets. Also, we show that Sor has a better pharmacokinetic profile than Rif, making it a suitable starting molecule to design drugs to be used for the treatment of TB patients with comorbidities who require multiple medications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Quantum machine learning for chemistry and physics

Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural asymmetry in FGF23 signaling

Chen et al. have derived cryogenic electron microscopy (cryo-EM) structures of signaling complexes of the endocrine hormone fibroblast growth factor 23 (FGF23) with fibroblast growth factor receptor (FGFR), α-Klotho, and heparin sulfate. Furthermore, these structures are asymmetric, leading to questions concerning in vivo function, and will facilitate structure-based drug design to modulate FGF23 signaling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sulfonamidoboronic Acids as “Cross-Class” Inhibitors of an Expanded-Spectrum Class C Cephalosporinase, ADC-33, and a Class D Carbapenemase, OXA-24/40: Strategic Compound Design to Combat Resistance in Acinetobacter baumannii

Acinetobacter baumannii is a Gram-negative organism listed as an urgent threat pathogen by the World Health Organization (WHO). Carbapenem-resistant A. baumannii (CRAB), especially, present therapeutic challenges due to complex mechanisms of resistance to β-lactams. One of the most important mechanisms is the production of β-lactamase enzymes capable of hydrolyzing β-lactam antibiotics. Co-expression of multiple classes of β-lactamases is present in CRAB; therefore, the design and synthesis of “cross-class” inhibitors is an important strategy to preserve the efficacy of currently available antibiotics. To identify new, nonclassical β-lactamase inhibitors, we previously identified a sulfonamidomethaneboronic acid CR167 active against Acinetobacter-derived class C β-lactamases (ADC-7). The compound demonstrated affinity for ADC-7 with a K i = 160 nM and proved to be able to decrease MIC values of ceftazidime and cefotaxime in different bacterial strains. Herein, we describe the activity of CR167 against other β-lactamases in A. baumannii: the cefepime-hydrolysing class C extended-spectrum β-lactamase (ESAC) ADC-33 and the carbapenem-hydrolyzing OXA-24/40 (class D). These investigations demonstrate CR167 as a valuable cross-class (C and D) inhibitor, and the paper describes our attempts to further improve its activity. Five chiral analogues of CR167 were rationally designed and synthesized. The structures of OXA-24/40 and ADC-33 in complex with CR167 and select chiral analogues were obtained. The structure activity relationships (SARs) are highlighted, offering insights into the main determinants for cross-class C/D inhibitors and impetus for novel drug design.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Complex of human Melanotransferrin and SC57.32 Fab fragment reveals novel interdomain arrangement with ferric N-lobe and open C-lobe

Melanotransferrin (MTf) is an iron-binding member of the transferrin superfamily that can be membrane-anchored or secreted in serum. On cells, it can mediate transferrin-independent iron uptake and promote proliferation. In serum, it is a transcytotic iron transporter across the blood–brain barrier. MTf has been exploited as a drug delivery carrier to the brain and as an antibody-drug conjugate (ADC) target due to its oncogenic role in melanoma and its elevated expression in triple-negative breast cancer (TNBC). For treatment of TNBC, an MTf-targeting ADC completed a phase I clinical trial (NCT03316794). The structure of its murine, unconjugated Fab fragment (SC57.32) is revealed here in complex with MTf. The MTf N-lobe is in an active and iron-bound, closed conformation while the C-lobe is in an open conformation incompatible with iron binding. This combination of active and inactive domains displays a novel inter-domain arrangement in which the C2 subdomain angles away from the N-lobe. The C2 subdomain also contains the SC57.32 glyco-epitope, which comprises ten protein residues and two N-acetylglucosamines. Our report reveals novel features of MTf and provides a point of reference for MTf-targeting, structure-guided drug design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Topobexin targets the Topoisomerase II ATPase domain for beta isoform-selective inhibition and anthracycline cardioprotection

Abstract Topoisomerase II alpha and beta (TOP2A and TOP2B) isoenzymes perform essential and non-redundant cellular functions. Anthracyclines induce their potent anti-cancer effects primarily via TOP2A, but at the same time they induce a dose limiting cardiotoxicity through TOP2B. Here we describe the development of theobexclass of TOP2 inhibitors that bind to a previously unidentified druggable pocket in the TOP2 ATPase domain to act as allosteric catalytic inhibitors by locking the ATPase domain conformation with the capability of isoform-selective inhibition. Through rational drug design we have developed topobexin, which interacts with residues that differ between TOP2A and TOP2B to provide inhibition that is both selective for TOP2B and superior to dexrazoxane. Topobexin is a potent protectant against chronic anthracycline cardiotoxicity in an animal model. This demonstration of TOP2 isoform-specific inhibition underscores the broader potential to improve drug specificity and minimize adverse effects in various medical treatments.

Science & Technology - Other Topics↗
DOE OSTI2024

Structural basis of selective TRPM7 inhibition by the anticancer agent CCT128930

TRP channels are implicated in various diseases, but high structural similarity between them makes selective pharmacological modulation challenging. Here, we study the molecular mechanism underlying specific inhibition of the TRPM7 channel, which is essential for cancer cell proliferation, by the anticancer agent CCT128930 (CCT). Using cryo-EM, functional analysis, and MD simulations, we show that CCT binds to a vanilloid-like (VL) site, stabilizing TRPM7 in the closed non-conducting state. Similar to other allosteric inhibitors of TRPM7, NS8593 and VER155008, binding of CCT is accompanied by displacement of a lipid that resides in the VL site in the apo condition. Moreover, we demonstrate the principal role of several residues in the VL site enabling CCT to inhibit TRPM7 without impacting the homologous TRPM6 channel. Hence, our results uncover the central role of the VL site for the selective interaction of TRPM7 with small molecules that can be explored in future drug design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host–microbiome metabolic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structurally Defined Water‐Soluble Metallofullerene Derivatives towards Biomedical Applications

Abstract Endohedral metallofullerenes (EMFs) are excellent carriers of rare‐earth element (REE) ions in biomedical applications because they preclude the release of toxic metal ions. However, existing approaches to synthesize water‐soluble EMF derivatives yield mixtures that inhibit precise drug design. Here we report the synthesis of metallobuckytrio (MBT), a three‐buckyball system, as a modular platform to develop structurally defined water‐soluble EMF derivatives with ligands by choice. Demonstrated with PEG ligands, the resulting water‐soluble MBTs show superb biocompatibility. The Gd MBTs exhibit superior T 1 relaxivity than typical Gd complexes, potentially superseding current clinical MRI contrast agents in both safety and efficiency. The Lu MBTs generated reactive oxygen species upon light irradiation, showing promise as photosensitizers. With their modular nature to incorporate other ligands, we anticipate the MBT platform to open new paths towards bio‐specific REE drugs.

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

Structurally Defined Water‐Soluble Metallofullerene Derivatives towards Biomedical Applications

Abstract Endohedral metallofullerenes (EMFs) are excellent carriers of rare‐earth element (REE) ions in biomedical applications because they preclude the release of toxic metal ions. However, existing approaches to synthesize water‐soluble EMF derivatives yield mixtures that inhibit precise drug design. Here we report the synthesis of metallobuckytrio (MBT), a three‐buckyball system, as a modular platform to develop structurally defined water‐soluble EMF derivatives with ligands by choice. Demonstrated with PEG ligands, the resulting water‐soluble MBTs show superb biocompatibility. The Gd MBTs exhibit superior T 1 relaxivity than typical Gd complexes, potentially superseding current clinical MRI contrast agents in both safety and efficiency. The Lu MBTs generated reactive oxygen species upon light irradiation, showing promise as photosensitizers. With their modular nature to incorporate other ligands, we anticipate the MBT platform to open new paths towards bio‐specific REE drugs.

Li, Yanbang↗
DOE OSTI2024

Mechanism of allosteric inhibition of human p97/VCP ATPase and its disease mutant by triazole inhibitors

Human p97 ATPase is crucial in various cellular processes, making it a target for inhibitors to treat cancers, neurological, and infectious diseases. Triazole allosteric p97 inhibitors have been demonstrated to match the efficacy of CB-5083, an ATP-competitive inhibitor, in cellular models. However, the mechanism is not well understood. This study systematically investigates the structures of new triazole inhibitors bound to both wild-type and disease mutant forms of p97 and measures their effects on function. These inhibitors bind at the interface of the D1 and D2 domains of each p97 subunit, shifting surrounding helices and altering the loop structures near the C-terminal α2 G helix to modulate domain-domain communications. A key structural moiety of the inhibitor affects the rotameric conformations of interacting side chains, indirectly modulating the N-terminal domain conformation in p97 R155H mutant. The differential effects of inhibitor binding to wild-type and mutant p97 provide insights into drug design with enhanced specificity, particularly for oncology applications.

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

3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds

The prerequisite of therapeutic drug design is to identify novel molecules with desired biophysical and biochemical properties. Deep generative models have demonstrated their ability to find such molecules by exploring a huge chemical space efficiently. An effective way to obtain molecules with desired target properties is the preservation of critical scaffolds in the generation process. To this end, we propose a domain aware generative framework called 3D-Scaffold that takes 3D coordinates of a desired scaffold as an input and generates 3D coordinates of novel therapeutic candidates as an output while always preserving the desired scaffolds in generated structures. We show that our framework generates predominantly valid, unique, novel, and experimentally synthesizable molecules that have drug-like properties similar to the molecules in the training set. Using domain specific datasets, we generate covalent and non-covalent antiviral inhibitors. Therefore, to measure the success of our framework in generating therapeutic candidates, generated structures were subjected to high throughput virtual screening via docking simulations, which shows favorable interaction against SARS-CoV-2 main protease and non-structural protein endoribonuclease (NSP15) targets. Most importantly, our model performs well with relatively small volumes of training data and generalizes to new scaffolds, making it applicable to other domain.

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

Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists

The α2a adrenoceptor is a particularly medically relevant subtype of the G protein-couple receptor family. Unfortunately, high-throughput techniques aimed at producing novel drug leads targeted to this receptor have been largely unsuccessful due to the complex pharmacology of adrenergic receptors. As such, cutting-edge in silico ligand- and structure-based assessment and de novo deep learning methods are well-positioned to provide new insights into protein-ligand interactions and potential active compounds. In this work, we (i) collect a dataset of α2a adrenoceptor agonists and provide it as a resource for the drug design community; (ii) use the dataset as a basis to generate candidate active structures via deep learning; and (iii) apply computational ligand- and structure-based analysis techniques to gain new insight into α2a adrenoceptor agonists and assess the quality of the computer-generated compounds. Additionally, we further describe how such assessment techniques can be applied to putative chemical probes with a case study involved proposed medetomidine-based probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗