Functional genomic screening in Komagataella phaffii enabled by high-activity CRISPR-Cas9 library
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59 BASIC BIOLOGICAL SCIENCES↗
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Development of a military-specific mesh-type computational phantom library and its application to internal dosimetry and in-field radiological triage screening
Estimates of organ-absorbed and committed doses to individuals exposed to radioactive materials via acute inhalation often rely on internal dose coefficients and detector responses from reference human computational models. To achieve more accurate dose assessments to United States Armed Forces service members exposed in-field, computational models with varying morphometric parameters representative of this population are necessary. The International Commission on Radiological Protection (ICRP) Publication 145 provides detailed mesh reference computational phantoms (MRCPs) for adult males and females, with morphometric parameters matched to the 50th percentile. Previously, these phantoms were 2D and 3D scaled to match desired height, mass, and secondary anthropomorphic parameters in the creation of the University of Florida / Memorial Sloan Kettering (UF/MSK) computational phantom library. To achieve body fat percentage targets required for accession into the US Armed Forces, muscle and fat volumes were adjusted accordingly, thus, creating the UF/Department of Defence computational phantom library presented in this study. A comprehensive library of mesh-type computational human phantoms was created, including 57 adult males and 49 adult females with morphometric parameters aligned with United States Armed Forces service members. Phantoms were restricted to a body mass index between 19 and 27.5, with body fat percentages below 26% for males and 36% for females. Specific absorbed fractions were computed for selected source and target combinations, demonstrating how variations in height and body mass influence energy absorption in target regions relative to the ICRP MRCPs. Radiation detector responses were also computed, revealing that higher body masses resulted in decreased registered counts in the detection volume. These findings highlight the importance of incorporating morphometric variability in computational phantoms to achieve more accurate dose assessments and radiation detection responses for United States Armed Forces service members who inhale radioactive materials in-field.
computational phantoms↗
Identification of and Structural Insights into Hit Compounds Targeting N -Myristoyltransferase for Cryptosporidium Drug Development
Each year, approximately 50,000 children under 5 die as a result of diarrhea caused by Cryptosporidium parvum, a protozoan parasite. There are currently no effective drugs or vaccines available to cure or prevent Cryptosporidium infection, and there are limited tools for identifying and validating targets for drug or vaccine development. We previously reported a high throughput screening (HTS) of a large compound library against Plasmodium N-myristoyltransferase (NMT), a validated drug target in multiple protozoan parasite species. To identify molecules that could be effective against Cryptosporidium, we counter-screened hits from the Plasmodium NMT HTS against Cryptosporidium NMT. We identified two potential hit compounds and validated them against CpNMT to determine if NMT might be an attractive drug target also for Cryptosporidium. We tested the compounds against Cryptosporidium using both cell-based and NMT enzymatic assays. We then determined the crystal structure of CpNMT bound to Myristoyl-Coenzyme A (MyrCoA) and structures of ternary complexes with MyrCoA and the hit compounds to identify the ligand binding modes. The binding site architectures display different conformational states in the presence of the two inhibitors and provide a basis for rational design of selective inhibitors.
60 APPLIED LIFE SCIENCES↗
Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers
Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.
60 APPLIED LIFE SCIENCES↗
Diversity-oriented synthesis of polymer membranes with ion solvation cages
Microporous polymers feature shape-persistent free volume elements (FVEs), which are permeated by small molecules and ions when used as membranes for chemical separations, water purification, fuel cells, and batteries. It remains a significant challenge to identify FVEs with analyte specificity, due to difficulties in generating microporous polymer libraries with sufficient diversity for screening their properties. Here, we describe a diversity-oriented synthetic (DOS) strategy for microporous polymer membranes from which we identified those whose FVEs serve as solid solvation cages for lithium ions (Li + ). Furthermore, key elements of our strategy included diversification of bis(catechol)-type monomers via multi-component Mannich reactions to introduce Li+-coordinating functionality within individual FVEs, topology-enforcing polymerizations for generating macromolecular skeletal diversity for networking FVEs into different pore architectures, and several classes of on-polymer reactions for diversifying pore geometries and dielectric properties. Lead candidate polymer membranes featuring explicit ion solvation cages exhibited both higher ionic conductivity and higher cation transference number than control membranes where FVEs were aspecific, which indicates conventional bounds for membrane permeability and selectivity for ion transport can be overcome.4 These advantages are tied to enhanced Li + partitioning from the electrolyte when the cages are present, higher diffusion barriers for anions within the pores, and network-enforced restrictions on the number of solvent molecules bound to Li+ by comparison to the bulk electrolyte, which reduces the effective mass of the working ion. Such membranes show promise as anode-stabilizing interlayers in high-voltage lithium-metal batteries for electric mobility.
42 ENGINEERING↗
A ligand discovery toolbox for the WWE domain family of human E3 ligases
The WWE domain is a relatively under-researched domain found in twelve human proteins and characterized by a conserved tryptophan-tryptophan-glutamate (WWE) sequence motif. Six of these WWE domain-containing proteins also contain domains with E3 ubiquitin ligase activity. The general recognition of poly-ADP-ribosylated substrates by WWE domains suggests a potential avenue for development of Proteolysis-Targeting Chimeras (PROTACs). Here, we present novel crystal structures of the HUWE1, TRIP12, and DTX1 WWE domains in complex with PAR building blocks and their analogs, thus enabling a comprehensive analysis of the PAR binding site structural diversity. Furthermore, we introduce a versatile toolbox of biophysical and biochemical assays for the discovery and characterization of novel WWE domain binders, including fluorescence polarization-based PAR binding and displacement assays, 15 N-NMR-based binding affinity assays and 19 F-NMR-based competition assays. Through these assays, we have characterized the binding of monomeric iso -ADP-ribose ( iso -ADPr) and its nucleotide analogs with the aforementioned WWE proteins. Finally, we have utilized the assay toolbox to screen a small molecule fragment library leading to the successful discovery of novel ligands targeting the HUWE1 WWE domain.
59 BASIC BIOLOGICAL SCIENCES↗
In silico λ-dynamics predicts protein binding specificities to modified RNAs
Abstract RNA modifications shape gene expression through a variety of chemical changes to canonical RNA bases. Although numbering in the hundreds, only a few RNA modifications are well characterized, in part due to the absence of methods to identify modification sites. Antibodies remain a common tool to identify modified RNA and infer modification sites through straightforward applications. However, specificity issues can result in off-target binding and confound conclusions. This work utilizes in silico λ-dynamics to efficiently estimate binding free energy differences of modification-targeting antibodies between a variety of naturally occurring RNA modifications. Crystal structures of inosine and N6-methyladenosine (m6A) targeting antibodies bound to their modified ribonucleosides were determined and served as structural starting points. λ-Dynamics was utilized to predict RNA modifications that permit or inhibit binding to these antibodies. In vitro RNA-antibody binding assays supported the accuracy of these in silico results. High agreement between experimental and computed binding propensities demonstrated that λ-dynamics can serve as a predictive screen for antibody specificity against libraries of RNA modifications. More importantly, this strategy is an innovative way to elucidate how hundreds of known RNA modifications interact with biological molecules without the limitations imposed by in vitro or in vivo methodologies.
Biochemistry & Molecular Biology↗
Structure of the coding region and mRNA variants of the apyrase gene from pea (Pisum sativum)
Partial amino acid sequences of a 49 kDa apyrase (ATP diphosphohydrolase, EC 3.6.1.5) from the cytoskeletal fraction of etiolated pea stems were used to derive oligonucleotide DNA primers to generate a cDNA fragment of pea apyrase mRNA by RT-PCR and these primers were used to screen a pea stem cDNA library. Two almost identical cDNAs differing in just 6 nucleotides within the coding regions were found, and these cDNA sequences were used to clone genomic fragments by PCR. Two nearly identical gene fragments containing 8 exons and 7 introns were obtained. One of them (H-type) encoded the mRNA sequence described by Hsieh et al. (1996) (DDBJ/EMBL/GenBank Z32743), while the other (S-type) differed by the same 6 nucleotides as the mRNAs, suggesting that these genes may be alleles. The six nucleotide differences between these two alleles were found solely in the first exon, and these mutation sites had two types of consensus sequences. These mRNAs were found with varying lengths of 3' untranslated regions (3'-UTR). There are some similarities between the 3'-UTR of these mRNAs and those of actin and actin binding proteins in plants. The putative roles of the 3'-UTR and alternative polyadenylation sites are discussed in relation to their possible role in targeting the mRNAs to different subcellular compartments.
NASA Discipline Plant Biology↗
An early ethylene up-regulated gene encoding a calmodulin-binding protein involved in plant senescence and death
35S-Labeled calmodulin (CaM) was used to screen a tobacco anther cDNA library. A positive clone (NtER1) with high homology to an early ethylene-up-regulated gene (ER66) in tomato, and an Arabidopsis homolog was isolated and characterized. Based on the helical wheel projection, a 25-mer peptide corresponding to the predicted CaM-binding region of NtER1 (amino acids 796-820) was synthesized. The gel-mobility shift assay showed that the peptide formed a stable complex with CaM only in the presence of Ca(2+). CaM binds to NtER1 with high affinity (K(d) approximately 12 nm) in a calcium-dependent manner. Tobacco flowers at different stages of development were treated with ethylene or with 1-methylcyclopropene for 2 h before treating with ethylene. Northern analysis showed that the NtER1 was rapidly induced after 15 min of exposure to ethylene. However, the 2-h 1-methylcyclopropene treatment totally blocked NtER1 expression in flowers at all stages of development, suggesting that NtER1 is an early ethylene-up-regulated gene. The senescing leaves and petals had significantly increased NtER1 induction as compared with young leaves and petals, implying that NtER1 is developmentally regulated and acts as a trigger for senescence and death. This is the first documented evidence for the involvement of Ca(2+)/CaM-mediated signaling in ethylene action.
Non-NASA Center↗
PyFaults: A Python Toolkit for Stacking Fault Screening
PyFaults is an open-source Python library designed to model stacking fault disorder in crystalline materials and qualitatively assess the characteristic selective broadening effects in powder X-ray diffraction (PXRD). Here, the main capabilities of PyFaults are presented, including unit cell and supercell model construction, PXRD pattern calculation, assessment against experimental PXRD, and methods for rapid screening of candidate models within a set of possible stacking vectors and fault occurrence probabilities. This program aims to serve as a computationally inexpensive tool for identifying and screening potential stacking fault models in materials with planar disorder. Three diverse case studies, involving GaN, Li2MnO3 and Li3YCl6, are presented to illustrate the program functionality across a range of structure types and stacking fault modalities.
MATHEMATICS AND COMPUTING↗
Identification of a Class of WNK Isoform-Specific Inhibitors Through High-Throughput Screening
Introduction: WNK [with no lysine (K)] kinases are serine/threonine kinases associated with familial hyperkalemic hypertension (FHHt). WNKs are therapeutic targets for blood pressure regulation, stroke and several cancers including triple negative breast cancer and glioblastoma. Here, we searched for and characterized novel WNK kinase inhibitors. Methods: We used a ~210,000-compound library in a high-throughput screen, re-acquisition and assay, commercial specificity screens and crystallography to identify WNK-isoform-selective inhibitors. Results: We identified five classes of compounds that inhibit the kinase activity of WNK1: quinoline compounds, halo-sulfones, cyclopropane-containing thiazoles, piperazine-containing compounds, and nitrophenol-derived compounds. The compounds are strongly pan-WNK selective, inhibiting all four WNK isoforms. A class of quinoline compounds was identified that further shows selectivity among the WNK isoforms, being more potent toward WNK3 than WNK1. The crystal structure of the quinoline-derived SW120619 bound to the kinase domain of WNK3 reveals active site binding, and comparison to the WNK1 structure reveals the potential origin of isoform specificity. Discussion: The newly discovered classes of compounds may be starting points for generating pharmacological tools and potential drugs treating hypertension and cancer.
60 APPLIED LIFE SCIENCES↗
Toward Fast Screening of Organic Solar Cell Blends
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99 GENERAL AND MISCELLANEOUS↗
A substrate-multiplexed platform for profiling enzymatic potential of plant family 1 glycosyltransferases
Plants have expanded various biosynthetic enzyme families to produce a wide diversity of natural products; however, most enzymes encoded in plant genomes remain uncharacterized, highlighting the need for new functional genomic approaches. Here, we report a platform enabling the rapid functional characterization of plant family 1 glycosyltransferases, which serve important roles in plant development, defense, and communication. Using substrate-multiplexed reactions, mass spectrometry, and automated analysis, we screen 85 enzymes against a diverse library of 453 natural products, for a total of nearly 40,000 possible reactions. The resulting dataset reveals a widespread promiscuity and a strong preference for planar, hydroxylated aromatic substrates among family 1 glycosyltransferases. We also characterize glycosyltransferases with an unusually wide substrate scope and with a non-canonical Cys-Asp catalytic dyad. This work establishes a widely-applicable enzymatic screening pipeline, reflects the immense glycosylation capability of plants, and has implications in biocatalysis, metabolic engineering, and gene discovery.
Sirirungruang, Sasilada↗
Harnessing the power of ab initio calculations, distributed computing and machine learning to efficiently locate extreme molecules for use in carbon-based solar cells (Final Technical Report)
The use of high-throughput virtual screening (HTVS) tools is a powerful tool to expedite the materials discovery of commercially relevant materials. In previous years, our group has developed a molecular discovery platform to generate libraries in order to obtain suitable candidates for different applications, starting from the Harvard Clean Energy Project. This platform is suitable to test in-silico on traditional supercomputing clusters and shared resources, for example, in the IBM World Community Grid. In this project, we used the molecular discovery platform to create and screen a library of candidates of organic photovoltaic (OPVs) molecules. Based on a set of candidates created with combinations of molecular moieties, we were able to filter, by conformation stability, the energy of electronic orbitals and approximated power conversion efficiencies (PCE). To improve the predictions of orbital energies calculated and the PCEs, we used Gaussian Process regression and two sets of molecules. These sets correspond to electronic structure calculations of a higher level of theory and experimental PCE values, respectively. Finally, we selected a subset of the best candidates (molecules with a PCE higher than 10%) to understand its absorbance properties with TD-DFT. This project has demonstrated the capabilities of our molecular discovery platform for HTVS. Finally, machine learning can help us to introduce more complex effects included in bulk conditions and computational intensive calculations on models.
14 SOLAR ENERGY↗
Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor
Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.
59 BASIC BIOLOGICAL SCIENCES↗
acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens
Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.
59 BASIC BIOLOGICAL SCIENCES↗
Solubility Behavior of CO 2 in Ionic Liquids Based on Ionic Polarity Index Analyses
Ionic liquids (ILs) can serve as effective CO 2 solvents with an appropriate selection of different anions and cations. However, due to the large library of potential IL compositions, rapid screening methods are needed for characterizing and ranking the expected properties. We have recently proposed the ionic polarity index (IPI) parameter, effectively connecting volume-based approaches and electrostatic potential analyses, providing a single metric that can potentially be used to rapidly screen for desirable IL properties. In this work, the corresponding anion and cation IPIs are used to generate correlations with respect to the CO 2 volumetric solubility in ILs. The relationships are generally applicable to groups of ILs within a homologous ion series, and this can be particularly valuable for pre-screening different ion pairings for maximizing gas solvation performance.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Triacetic Acid Lactone and 4-Hydroxycoumarin as Bioprivileged Molecules for the Development of Performance-Advantaged Organic Corrosion Inhibitors
Biomass conversion, especially the development of bioprivileged molecules utilizing integration of biological and chemical processes, has shown potential to produce novel chemicals with enhanced properties. Here, organic corrosion inhibitors based on triacetic acid lactone and 4-hydroxycoumarin have been synthesized in good yield and tested for corrosion inhibition on mild steel in both sulfuric acid and hydrochloric acid. Sixteen novel corrosion inhibitors derived from triacetic acid lactone and 4-hydroxycoumarin were efficiently synthesized and twelve of them showed high corrosion inhibition efficiency as confirmed by electrochemical impedance spectroscopy (giving values greater than 78%) and polarization analysis. While triacetic acid lactone-based compounds showed good corrosion inhibition performance, the 4-hydroxycoumarin-based compounds showed further improvement in corrosion inhibition performance. Scanning electron microscopy (SEM) analysis of the mild steel coupon in the presence of selected inhibitors showed that corrosion was significantly diminished, with complementary X-ray photoelectron spectroscopy (XPS) analysis suggesting the inhibitor molecules strongly adsorbed on the steel surface. Quantum chemical calculations showed poor correlation between calculated parameters and the performance of these molecules. This large set of corrosion inhibitors containing a dozen promising corrosion inhibitors is useful for future rational design of corrosion inhibitors. In conclusion, the results demonstrate a new direction for the development of bioprivileged molecules.
09 BIOMASS FUELS↗