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At least 145 records · Page 8

Structure-based mechanism and inhibition of cholesteryl ester transfer protein

Purpose of Review: Cholesteryl ester transfer proteins (CETP) regulate plasma cholesterol levels by transferring cholesteryl esters (CEs) among lipoproteins. Lipoprotein cholesterol levels correlate with the risk factors for atherosclerotic cardiovascular disease (ASCVD). This article reviews recent research on CETP structure, lipid transfer mechanism, and its inhibition. Recent Findings: Genetic deficiency in CETP is associated with a low plasma level of low-density lipoprotein cholesterol (LDL-C) and a profoundly elevated plasma level of high-density lipoprotein cholesterol (HDL-C), which correlates with a lower risk of atherosclerotic cardiovascular disease (ASCVD). However, a very high concentration of HDL-C also correlates with increased ASCVD mortality. Considering that the elevated CETP activity is a major determinant of the atherogenic dyslipidemia, i.e., pro-atherogenic reductions in HDL and LDL particle size, inhibition of CETP emerged as a promising pharmacological target during the past two decades. CETP inhibitors, including torcetrapib, dalcetrapib, evacetrapib, anacetrapib and obicetrapib, were designed and evaluated in phase III clinical trials for the treatment of ASCVD or dyslipidemia. Although these inhibitors increase in plasma HDL-C levels and/or reduce LDL-C levels, the poor efficacy against ASCVD ended interest in CETP as an anti-ASCVD target. Nevertheless, interest in CETP and the molecular mechanism by which it inhibits CE transfer among lipoproteins persisted. Insights into the structural-based CETP-lipoprotein interactions can unravel CETP inhibition machinery, which can hopefully guide the design of more effective CETP inhibitors that combat ASCVD. Summary: Individual-molecule 3D structures of CETP bound to lipoproteins provide a model for understanding the mechanism by which CETP mediates lipid transfer and which in turn, guide the rational design of new anti-ASCVD therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

2.5 Å-resolution structure of human CDK-activating kinase bound to the clinical inhibitor ICEC0942

The human CDK-activating kinase (CAK), composed of CDK7, cyclin H, and MAT1, is involved in the control of transcription initiation and the cell cycle. Because of these activities, it has been identified as a promising target for cancer chemotherapy. A number of CDK7 inhibitors have entered clinical trials, among them ICEC0942 (also known as CT7001). Structural information can aid in improving the affinity and specificity of such drugs or drug candidates, reducing side effects in patients. Here, we have determined the structure of the human CAK in complex with ICEC0942 at 2.5 Å-resolution using cryogenic electron microscopy. Our structure reveals conformational differences of ICEC0942 compared with previous X-ray crystal structures of the CDK2-bound complex, and highlights the critical ability of cryogenic electron microscopy to resolve structures of drug-bound protein complexes without the need to crystalize the protein target.

59 BASIC BIOLOGICAL SCIENCES↗

The coordination properties and ionic radius of actinium: A 120-year-old enigma

Actinium is an elusive element with untamed properties and represents a peculiar case in the periodic table, as its isotopes are all radioactive, the longest-lived one having only a 22-year half-life, and the availability of actinium isotopes remains very low (microgram level, at best), hindering research on its compounds. Despite being a natural element discovered more than 120 years ago, and despite an increasing interest in using one of its isotopes ( 225 Ac) for highly efficient cancer therapies, the chemistry of actinium is still largely unknown relative to other elements. Since Ac is the first element of the actinide series, it is accepted that its ion, Ac 3+ , is the most voluminous trivalent cation of the periodic table. However, the structural data available on Ac 3+ compounds are scarce and have mainly been collected in the 1940-1960's, when actinide chemistry was still in its infancy, and have not been put in perspective with the advances in the chemistry of other elements, making it difficult to accurately evaluate its actual size and coordination chemistry. Here, we review progress made on the chemistry of lanthanides and actinides and reevaluate the structural data published on Ac 3+ since the era of the Manhattan Project. The data are combined across different spectroscopic and characterization methods and presented in the context of periodic trends. When considering crystallographic data, solution chemistry results, and the nuclear properties of actinium isotopes, it appears that some structural parameters ascribed to the Ac 3+ ion may have been overestimated. This review can guide researchers interested in actinide sciences and those who are pursuing the development of actinium-based radiotherapies, from isotope production to clinical trials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗

A human antibody epitope map of Pfs230D1 derived from analysis of individuals vaccinated with a malaria transmission-blocking vaccine

Pfs230 domain 1 (Pfs230D1) is an advanced malaria transmission-blocking vaccine antigen demonstrating high functional activity in clinical trials. However, the structural and functional correlates of transmission-blocking activity are not defined. Here, we characterized a panel of human monoclonal antibodies (hmAbs) elicited in vaccinees immunized with Pfs230D1. These hmAbs exhibited diverse transmission-reducing activity, yet all bound to Pfs230D1 with nanomolar affinity. We compiled epitope-binning data for seventeen hmAbs and structures of nine hmAbs complexes to construct a high-resolution epitope map and revealed that potent transmission-reducing hmAbs bound to one face of Pfs230D1, while non-potent hmAbs bound to the opposing side. The structure of Pfs230D1D2 revealed that non-potent transmission-reducing epitopes were occluded by the second domain. The hmAb epitope map delineated binary hmAb combinations that synergized for extremely high-potency, transmission-reducing activity. Finally, this work provides a high-resolution guide for structure-based design of enhanced immunogens and informs diagnostics that measure the transmission-reducing response.

60 APPLIED LIFE SCIENCES↗

Diverse Antibody Responses to Conserved Structural Motifs in Plasmodium falciparum Circumsporozoite Protein

Malaria vaccine candidate RTS,S/AS01 is based on the central and C-terminal regions of the circumsporozoite protein (CSP) of P. falciparum. mAb397 was isolated from a volunteer in an RTS,S/AS01 clinical trial, and it protects mice from infection by malaria sporozoites. However, mAb397 originates from the less commonly used VH3-15 germline gene compared to the VH3-30/33 antibodies generally elicited by RTS,S to the central NANP repeat region of CSP. The crystal structure of mAb397 with an NPNA4 peptide shows that the central NPNA forms a type I β-turn and is the main recognition motif. In most anti-NANP antibodies studied to date, a germline-encoded Trp is used to engage the Pro in NPNA β-turns, but here the Trp interacts with the first Asn. This “conserved” Trp, however, can arise from different germline genes and be located in the heavy or the light chain. Variation in the terminal ψ angles of the NPNA β-turns results in different dispositions of the subsequent NPNA and, hence, different stoichiometries and modes of antibody binding to rsCSP. Diverse protective antibodies against NANP repeats are therefore not limited to a single germline gene response or mode of binding.

59 BASIC BIOLOGICAL SCIENCES↗

Nanodiamonds in Advancing Biomedical Sciences

Nanodiamonds (NDs), tetrahedral carbon frameworks with size ranging from 1 to 100 nanometers, have gained growing attention in recent years due to their distinct optical, thermal, and mechanical properties compared to other carbon nanomaterials (e.g., graphene, carbon nanotubes, carbon dots). Combined with a high surface-to-volume ratio and tunable and chemically versatile surfaces, these support broad applications across catalysis, electronics, and life sciences. Moreover, the biocompatible characteristics of NDs enable their controllable interfacial interactions with biological systems, positioning them as excellent candidates for advancing cutting-edge biomedical sciences, particularly through the engineering of efficient material-biointerfaces that facilitate optimal interactions with biological systems. Among various forms of NDs, fluorescent nanodiamonds (FNDs) have emerged as some of the most impactful and rapidly advancing materials, demonstrating strong potential in ultrasensitive spin-enhanced bioimaging, high-precision biosensing, traceable drug delivery, and quantum-enabled biomedical technologies. This Perspective introduces the key principles underlying NDs and FNDs, including their structural properties, synthesis methods, and surface functionalization strategies. It also highlights emerging biomedical applications of NDs and FNDs, with particular emphasis on neurological disorders. Last, the article discusses current challenges in advancing NDs as a multifunctional platform for neural therapies with translational potential toward clinical trials.

36 MATERIALS SCIENCE↗

A Single Immunization with Spike-Functionalized Ferritin Vaccines Elicits Neutralizing Antibody Responses against SARS-CoV-2 in Mice

The development of a safe and effective SARS-CoV-2 vaccine is a public health priority. We designed subunit vaccine candidates using self-assembling ferritin nanoparticles displaying one of two multimerized SARS-CoV-2 spikes: full-length ectodomain (S-Fer) or a C-terminal 70 amino-acid deletion (SΔC-Fer). Ferritin is an attractive nanoparticle platform for production of vaccines, and ferritin-based vaccines have been investigated in humans in two separate clinical trials. We confirmed proper folding and antigenicity of spike on the surface of ferritin by cryo-EM and binding to conformation-specific monoclonal antibodies. After a single immunization of mice with either of the two spike ferritin particles, a lentiviral SARS-CoV-2 pseudovirus assay revealed mean neutralizing antibody titers at least 2-fold greater than those in convalescent plasma from COVID-19 patients. Additionally, a single dose of SΔC-Fer elicited significantly higher neutralizing responses as compared to immunization with the spike receptor binding domain (RBD) monomer or spike ectodomain trimer alone. After a second dose, mice immunized with SΔC-Fer exhibited higher neutralizing titers than all other groups. Taken together, these results demonstrate that multivalent presentation of SARS-CoV-2 spike on ferritin can notably enhance elicitation of neutralizing antibodies, thus constituting a viable strategy for single-dose vaccination against COVID-19.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insights into the Structure of Ultrasmall Fluorescent Core–Shell Silica Nanoparticles

Ultrasmall fluorescent core–shell nanoparticles (NPs) with a silica core and poly(ethylene glycol) ligand shell are the earliest example of hybrid NPs that have received U.S. investigational new drug FDA approval. They are among only a few inorganic NPs translated to safety, diagnostic, and therapeutic human clinical trials. Despite these achievements, little is known about the exact structure of their 3–4 nm sized silica cores. We report the surprising discovery of a well-defined pentagonal bipyramidal core structure preferentially formed in the aqueous synthesis built from seven primary silica NPs. A combination of reverse-phase high-performance liquid chromatography, cryogenic transmission electron microscopy, and coarse-grained simulations provides fundamental insights into this magic-size cluster formation and its unusual stability. Here, results rationalize the successful NP synthesis scale-up from 1 mL to 50 L, provide clues to the recent discovery of their self-therapeutic properties in oncology via ferroptosis, an iron-dependent cell death mechanism, and promise improved control of particle size distribution via chromatographic separations.

cluster chemistry↗

An integrated multi-omics approach identifies the landscape of interferon-α-mediated responses of human pancreatic beta cells

Proinflammatory cytokines are important mediators of pancreatic beta cell dysfunction and demise in the early stages of type 1 diabetes (T1D). Interferon-a (IFNa), a type I interferon member, is expressed in the islets of T1D individuals and it is expression and signaling is regulated by both genetic (T1D risk variants) and environmental factors (viral infections) associated to T1D. We presently characterized human beta cells responses to IFNa by combining ATAC-seq, RNA-seq and proteomics assays. The initial beta cell response to IFNa was characterized by major chromatin remodeling, followed by marked changes in transcriptional and translational regulation. IFNa-induced changes in alternative splicing (AS) and first exon usage increased the diversity of transcripts expressed by beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may significantly expand the peptide repertoire presented by beta cells to the immune system. On the other hand, beta cells up-regulated checkpoint proteins, such as PDL1 and HLA-E, that may protect them against the autoimmune assault. Data mining of the present multi-omics analysis led to the identification of two compound classes that revert IFNa effects on human beta cells and may be translated to clinical trials.

60 APPLIED LIFE SCIENCES↗

Directed evolution of and structural insights into antibody-mediated disruption of a stable receptor-ligand complex

Antibody drugs exert therapeutic effects via a range of mechanisms, including competitive inhibition, allosteric modulation, and immune effector mechanisms. Facilitated dissociation is an additional mechanism where antibody-mediated “disruption” of stable high-affinity macromolecular complexes can potentially enhance therapeutic efficacy. However, this mechanism is not well understood or utilized therapeutically. Here, we investigate and engineer the weak disruptive activity of an existing therapeutic antibody, omalizumab, which targets IgE antibodies to block the allergic response. We develop a yeast display approach to select for and engineer antibody disruptive efficiency and generate potent omalizumab variants that dissociate receptor-bound IgE. We determine a low resolution cryo-EM structure of a transient disruption intermediate containing the IgE-Fc, its partially dissociated receptor and an antibody inhibitor. Our results provide a conceptual framework for engineering disruptive inhibitors for other targets, insights into the failure in clinical trials of the previous high affinity omalizumab HAE variant and anti-IgE antibodies that safely and rapidly disarm allergic effector cells.

59 BASIC BIOLOGICAL SCIENCES↗

A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation

The early stages of Alzheimer’s disease (AD) involve interactions between multiple pathophysiological processes. Although these processes are well studied, we still lack robust tools to predict individualised trajectories of disease progression. Here, we employ a robust and interpretable machine learning approach to combine multimodal biological data and predict future pathological tau accumulation. In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal lobe atrophy, tau and APOE 4) at mildly impaired and asymptomatic stages of AD. Using baseline non-tau markers we derive a prognostic index that: (a) stratifies patients based on future pathological tau accumulation, (b) predicts individualised regional future rate of tau accumulation, and (c) translates predictions from deep phenotyping patient cohorts to cognitively normal individuals. Our results propose a robust approach for fine scale stratification and prognostication with translation impact for clinical trial design targeting the earliest stages of AD.

60 APPLIED LIFE SCIENCES↗

Structural basis for the subtype-selectivity of K Ca 2.2 channel activators

Small-conductance (K Ca 2.2) and intermediate-conductance (K Ca 3.1) Ca 2+ -activated K + channels are gated by a Ca 2+ -calmodulin dependent mechanism. NS309 potentiates the activity of both K Ca 2.2 and K Ca 3.1, while rimtuzalcap selectively activates K Ca 2.2. Rimtuzalcap has been used in clinical trials for the treatment of spinocerebellar ataxia and essential tremor. We report cryo-electron microscopy structures of NS309-bound K Ca 2.2 and K Ca 3.1, in addition to structures of rimtuzalcap-bound K Ca 2.2 and mutant K Ca 3.1_R355K. The different conformations of calmodulin and the cytoplasmic HC helices in the two channels underlie the subtype-selectivity of rimtuzalcap for K Ca 2.2. NS309 binds to pre-existing pockets in both channels, while the bulkier rimtuzalcap binds in an induced-fit pocket in K Ca 2.2 requiring conformational changes. In K Ca 2.2, calmodulin’s N-lobes are sufficiently far apart to enable conformational changes to accommodate either NS309 or rimtuzalcap. In K Ca 3.1, calmodulin’s N-lobes are closer to each other and constrained by K Ca 3.1’s HC helices, which allows binding of NS309 but not rimtuzalcap. Replacement of arginine-355 in K Ca 3.1’s HB helix with lysine (K Ca 3.1_R355K) allows the binding of rimtuzalcap and renders the mutant channel sensitive to rimtuzalcap. These structures provide a framework for structure-based drug design targeting K Ca 2.2 channels.

Nam, Young-Woo [Chapman Univ., Irvine, CA (United ↗

Development of spirulina for the manufacture and oral delivery of protein therapeutics

The use of the edible photosynthetic cyanobacterium Arthrospira platensis (spirulina) as a biomanufacturing platform has been limited by a lack of genetic tools. Here we report genetic engineering methods for stable, high-level expression of bioactive proteins in spirulina, including large-scale, indoor cultivation and downstream processing methods. Following targeted integration of exogenous genes into the spirulina chromosome (chr), encoded protein biopharmaceuticals can represent as much as 15% of total biomass, require no purification before oral delivery and are stable without refrigeration and protected during gastric transit when encapsulated within dry spirulina. Oral delivery of a spirulina-expressed antibody targeting campylobacter—a major cause of infant mortality in the developing world—prevents disease in mice, and a phase 1 clinical trial demonstrated safety for human administration. Spirulina provides an advantageous system for the manufacture of orally delivered therapeutic proteins by combining the safety of a food-based production host with the accessible genetic manipulation and high productivity of microbial platforms.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs

Tuberculosis (TB) is the deadliest infectious disease worldwide. The design of new treatments for TB is hindered by the large number of candidate drugs, drug combinations, dosing choices, and complex pharmaco-kinetics/dynamics (PK/PD). Here we study the interplay of these factors in designing combination therapies by linking a machine-learning model, INDIGO-MTB, which predicts in vitro drug interactions using drug transcriptomics, with a multi-scale model of drug PK/PD and pathogen-immune interactions called GranSim. We calculate an in vivo drug interaction score (iDIS) from dynamics of drug diffusion, spatial distribution, and activity within lesions against various pathogen sub-populations. The iDIS of drug regimens evaluated against non-replicating bacteria significantly correlates with efficacy metrics from clinical trials. Our approach identifies mechanisms that can amplify synergistic or mitigate antagonistic drug interactions in vivo by modulating the relative distribution of drugs. Our mechanistic framework enables efficient evaluation of in vivo drug interactions and optimization of combination therapies.

59 BASIC BIOLOGICAL SCIENCES↗

Hepatitis C virus NS3/4A inhibitors and other drug-like compounds as covalent binders of SARS-CoV-2 main protease

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), threatens global public health. The world needs rapid development of new antivirals and vaccines to control the current pandemic and to control the spread of the variants. Among the proteins synthesized by the SARS-CoV-2 genome, main protease (M pro also known as 3CL pro ) is a primary drug target, due to its essential role in maturation of the viral polyproteins. In this study, we provide crystallographic evidence, along with some binding assay data, that three clinically approved anti hepatitis C virus drugs and two other drug-like compounds covalently bind to the M pro Cys145 catalytic residue in the active site. Also, molecular docking studies can provide additional insight for the design of new antiviral inhibitors for SARS-CoV-2 using these drugs as lead compounds. One might consider derivatives of these lead compounds with higher affinity to the M pro as potential COVID-19 therapeutics for further testing and possibly clinical trials.

36 MATERIALS SCIENCE↗

Data-driven causal model discovery and personalized prediction in Alzheimer's disease

Abstract With the explosive growth of biomarker data in Alzheimer’s disease (AD) clinical trials, numerous mathematical models have been developed to characterize disease-relevant biomarker trajectories over time. While some of these models are purely empiric, others are causal, built upon various hypotheses of AD pathophysiology, a complex and incompletely understood area of research. One of the most challenging problems in computational causal modeling is using a purely data-driven approach to derive the model’s parameters and the mathematical model itself, without any prior hypothesis bias. In this paper, we develop an innovative data-driven modeling approach to build and parameterize a causal model to characterize the trajectories of AD biomarkers. This approach integrates causal model learning, population parameterization, parameter sensitivity analysis, and personalized prediction. By applying this integrated approach to a large multicenter database of AD biomarkers, the Alzheimer’s Disease Neuroimaging Initiative, several causal models for different AD stages are revealed. In addition, personalized models for each subject are calibrated and provide accurate predictions of future cognitive status.

Zheng, Haoyang (ORCID:0000000168358242)↗