High-throughput Screening Pipeline Research Articles

Multiplexed CRISPR-Cas9 mutagenesis of rice PSBS1 noncoding sequences for transgene-free overexpression.

Understanding CRISPR-Cas9's capacity to produce native overexpression (OX) alleles would accelerate agronomic gains achievable by gene editing. To generate OX alleles with increased RNA and protein abundance, we leveraged multiplexed CRISPR-Cas9 mutagenesis of noncoding sequences upstream of the rice PSBS1 gene. We isolated 120 gene-edited alleles with varying non-photochemical quenching (NPQ) capacity in vivo-from knockout to overexpression-using a high-throughput screening pipeline. Overexpression increased OsPsbS1 protein abundance two- to threefold, matching fold changes obtained by transgenesis. Increased PsbS protein abundance enhanced NPQ capacity and water-use efficiency. Across our resolved genetic variation, we identify the role of 5'UTR indels and inversions in driving knockout/knockdown and overexpression phenotypes, respectively. Complex structural variants, such as the 252-kb duplication/inversion generated here, evidence the potential of CRISPR-Cas9 to facilitate significant genomic changes with negligible off-target transcriptomic perturbations. Our results may inform future gene-editing strategies for hypermorphic alleles and have advanced the pursuit of gene-edited, non-transgenic rice plants with accelerated relaxation of photoprotection.

Identification of novel pharmacological activators of circadian clock with anti-adipogenic properties

The circadian clock drives rhythmic oscillations of metabolic processes to orchestrate metabolic homeostasis, and disruption of this mechanism predisposes to obesity and insulin resistance. Preserving or augmenting clock function could be a potential therapeutic target for metabolic diseases, particularly with the wide-spread of circadian misalignment in a modern lifestyle. To date, targeting the clock for metabolic disease prevention or treatment remains to be explored. Adipocyte possesses cell-autonomous clocks that exert transcriptional control of the Wnt pathway to inhibit adipocyte development. Using a high through-put screening pipeline, we recently identified Chlorhexidine as a novel clock-activating molecule that targets the key driver of the circadian clock transcriptional feedback loop, the CLOCK protein. Based on clock function in suppressing adipogenesis, we hypothesize that Chlorhexidine and related compounds may possess adipogenic-inhibitory properties suitable for anti-obesity drug development. In distinct adipogenic progenitor models, we demonstrate the activity of Chlorhexidine in inhibiting adipogenic lineage commitment and terminal differentiation. Furthermore, we report the structural optimization of Chlorhexidine chemical scaffold that led to the discovery of new analogs with improved anti-adipogenic effcacy. Consistent with its activity for clock activation, in adipogenic progenitors containing a Period2::dLuc luciferase reporter, Chlorhexidine induced significant shortening of clock period length with induction of core clock components. Chlorhexidine treatment of adipogenic mesenchymal precursors robustly suppressed their adipogenic maturation, with a comparable effect observed on inhibiting terminal differentiation of primary preadipocytes in a clock-dependent manner. Mechanistically, Chlorhexidine stimulates clock-controlled Wnt signaling that mediates its anti-adipogenic effect. Through medicinal chemistry modification of its chemical scaffold, we generated a panel of Chlorhexidine analogs with validation for their clock-modulatory activities. Structure activity relationship analysis of these analogs led to the identification of CM002 as a new clock activator with improved clock-dependent anti-adipogenic activity. Collectively, our findings uncovered a new class of clock-modulatory compounds that inhibit adipocyte development for potential anti-obesity drug discovery and provide clock-targeting chemical probes for dissecting clock function in metabolic physiology. This project was supported by grants from National Institute of Aging R56AG080294 and Arthur Riggs-Diabetes & Metabolism Research Institute T2D and T1D Innovative Awards to KM. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

A high-throughput target-based screening approach for the identification and assessment of Mycobacterium tuberculosis mycothione reductase inhibitors.

The growing anti-microbial resistance poses a global public health threat, impeding progress toward eradicating tuberculosis. Despite decades of active research, there is still a dire need for the discovery of drugs with novel modes of action and exploration of combination drug regimens. Within the European RespiriTB consortium, we explore Mycobacterium tuberculosis energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we present the development of a high-throughput screening pipeline that led to the identification of M. tuberculosis mycothione reductase inhibitors.

Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative

Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with specific patient populations which makes their generalizability unclear. This study aims to characterize PASC using the EHR data warehouses from two large Patient-Centered Clinical Research Networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) area and 16.8 million patients in Florida respectively. With a high-throughput screening pipeline based on propensity score and inverse probability of treatment weighting, we identified a broad list of diagnoses and medications which exhibited significantly higher incidence risk for patients 30–180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We identified more PASC diagnoses in NYC than in Florida regarding our screening criteria, and conditions including dementia, hair loss, pressure ulcers, pulmonary fibrosis, dyspnea, pulmonary embolism, chest pain, abnormal heartbeat, malaise, and fatigue, were replicated across both cohorts. Our analyses highlight potentially heterogeneous risks of PASC in different populations.

Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions

Sluggish oxygen evolution reaction (OER) in acid conditions is one of the bottlenecks that prevent the wide adoption of proton exchange membrane water electrolyzer for green hydrogen production. Despite recent advancements in developing high-performance catalysts for acid OER, the current electrocatalysts still rely on iridium- and ruthenium-based materials, urging continuous efforts to discover better performance catalysts as well as reduce the usage of noble metals. Pyrochlore structured oxide is a family of potential high-performance acid OER catalysts with a flexible compositional space to tune the electrochemical capabilities. However, exploring the large composition space of pyrochlore compounds demands an imperative approach to enable efficient screening. Here we present a high-throughput screening pipeline that integrates density functional theory calculations and a transfer learning approach to predict the critical properties of pyrochlore compounds. The high-throughput screening recommends three sets of candidates for potential acid OER applications, totaling 61 candidates from 6912 pyrochlore compounds. In addition to 3d-transition metals, p-block metals are identified as promising dopants to improve the catalytic activity of pyrochlore oxides. This work demonstrates not only an efficient approach for finding suitable pyrochlores towards acid OER but also suggests the great compositional flexibility of pyrochlore compounds to be considered as a new materials platform for a variety of applications.

High-throughput screening to identify modulators of membrane protein raft affinity in giant plasma membrane vesicles.

Lipid rafts remain an active area of membrane biophysics research. Due to their diffraction-limited size and transient nature direct studies of rafts and their resident proteins in cells remains intractable. The lack of tools to manipulate raft-resident proteins has also stymied our ability to study raft function and raft partitioning of proteins. Giant plasma membrane vesicles (GPMVs), which spontaneously separate into ordered (raft) and disordered (non-raft) phases, are a practical a tool for studying rafts in biological membranes. We recently developed a high-throughput screening pipeline combining high-content imaging with a custom image-analysis software package, VesA, to identify small molecule modulators of phase separation in GPMVs. Using this approach, we are conducting an on-going screen 20,000 of small molecules from the Vanderbilt University Discover collection to find compounds that alter the phase partitioning of the peripheral myelin protein 22 (PMP22). PMP22, a major component of myelin in Schwann cells of the peripheral nervous system, shows a high affinity for ordered phases of GPMVs. Disease causing mutations in PMP22 exhibit both varying degrees of misfolding and decreased raft partitioning which strongly correlate to disease severity. We hypothesize that PMP22 fold stability is necessary for both raft partitioning and trafficking to the plasma membrane. From the screen, we are identifying hits that we sort into different categories based on their effects on (1) PMP22 raft partitioning (2) GPMV phase composition and (3) raft partitioning of other proteins. Identification of small molecules that non-specifically alter raft affinity will be useful tools for dissecting how and why proteins prefer rafts. The identification of small molecules that selectively bind to PMP22 and alter its phase partitioning will be crucial to investigating the relationship between PMP22 structure, raft affinity, and trafficking.

Finding the First Squarates Nonlinear Optical Crystal NaHC4O4·H2O with Strong Second Harmonic Generation and Giant Birefringence

With the development of laser technology, nonlinear optical (NLO) crystals with optimal performance are urgently required. Finding new NLO-active units is necessary to expand the exploration systems for NLO materials. Herein, a π-conjugated planar hydrogensquarate (HC4O4)− with large hyperpolarizabilities and giant polarizability anisotropies is identified as a new NLO-active unit. On the basis of this idea, a new NLO crystal NaHC4O4·H2O is found by using the first-principles high-throughput screening pipeline for nonlinear optical materials (FHSP-NLO). It is the first NLO crystal found in squarates. Subsequently, the crystal with a size of 30 × 6 × 5 mm was grown by a facile aqueous solution method. NaHC4O4·H2O shows a strong powder SHG effect of 2.3 × KDP and a giant birefringence of 0.52 at 1064 nm. Electronic structure calculation and analysis reveal that the π orbitals of the (HC4O4)− groups are the dominant source of the SHG coefficient. This study provides novel NLO-active units and a materials system to design and find NLO crystals.

The application and development of the first principles calculation in nonlinear optical materials

<p indent=0mm>Nonlinear optical (NLO) crystals need to meet multiple criteria, so it is a challenging and time-consuming task to find new NLO materials. The computational method that based on first-principles can screen out materials from a large number of materials by predicting their properties. In addition, the NLO-active groups of the materials can be identified by studying the “composition-structure-properties” relationship, which provides guidance for the synthesis of new materials. This paper summarizes the role and recent cases of computational materials in the discovery of new NLO materials. The first-principles high-throughput screening pipeline system for nonlinear optical materials (FHSP-NLO) is introduced emphatically. The system combines density functional theory (DFT) codes, linear and nonlinear optical property calculation codes, and data transformation and extraction codes, and can be automatically run to calculate and analyze a large number of materials at once. It has been successfully applied in systems including borates, germanates and nitride silicates, which provide a powerful and effective tool for searching new NLO materials.

High-Throughput Detection of Autoantigen-Specific B Cells Among Distinct Functional Subsets in Autoimmune Donors.

Antigen-specific B cells (ASBCs) can drive autoimmune disease by presenting autoantigen to cognate T cells to drive their activation, proliferation, and effector cell differentiation and/or by differentiating into autoantibody-secreting cells. Autoantibodies are frequently used to predict risk and diagnose several autoimmune diseases. ASBCs can drive type 1 diabetes even when immune tolerance mechanisms block their differentiation into antibody-secreting cells. Furthermore, anti-histidyl tRNA synthetase syndrome patients have expanded IgM+ Jo-1-binding B cells, which clinically diagnostic IgG Jo-1 autoantibodies may not fully reflect. Given the potential disconnect between the pathologic function of ASBCs and autoantibody secretion, direct study of ASBCs is a necessary step towards developing better therapies for autoimmune diseases, which often have no available cure. We therefore developed a high-throughput screening pipeline to 1) phenotypically identify specific B cell subsets, 2) expand them in vitro, 3) drive them to secrete BCRs as antibody, and 4) identify wells enriched for ASBCs through ELISA detection of antibody. We tested the capacity of several B cell subset(s) to differentiate into antibody-secreting cells following this robust stimulation. IgM+ and/or IgD+, CD27- memory, memory, switched memory, and BND B cells secreted B cell receptor (BCR) as antibody following in vitro stimulation, whereas few plasmablasts responded. Bimodal responses were observed across autoimmune donors for IgM+ CD21lo and IgM- CD21lo B cells, consistent with documented heterogeneity within the CD21lo subset. Using this approach, we detected insulin-binding B cell bias towards CD27- memory and CD27+ memory subsets in pre-symptomatic type 1 diabetes donors. We took advantage of routine detection of Jo-1-binding B cells in Jo-1+ anti-histidyl tRNA synthetase syndrome patients to show that Jo-1-binding B cells and total B cells expanded 20-30-fold using this culture system. Overall, these studies highlight technology that is amenable to small numbers of cryopreserved peripheral blood mononuclear cells that enables interrogation of phenotypic and repertoire attributes of ASBCs derived from autoimmune patients.

Finding Optimal Mid-Infrared Nonlinear Optical Materials in Germanates by First-Principles High-Throughput Screening and Experimental Verification.

Owing to wide infrared (IR) transparency ranges, high laser damage thresholds, and being easy to grow in open air, germanates are emerging as promising mid-infrared (mid-IR) nonlinear optical (NLO) materials. However, the germanates as NLO materials have not been investigated comprehensively and the crystals with large second harmonic generation (SHG) response have not been identified. Herein, we used the first-principles high-throughput screening pipeline for NLO materials to search for excellent NLO crystals from germanates collected in the inorganic crystal structure database. After two steps of screening, three crystals are picked out from 128 structures based on their predicted energy gaps, birefringences, and SHG coefficients. Subsequently, the three germanates are synthesized and measured. The results show that Pb3Ga2Ge4O14 and Ba2TiGe2O8 exhibit a wide energy gap (>3.1 eV) and a strong phase-matchable SHG intensity that are comparable to the benchmark AgGaS2 (0.8 and 1.2 × AgGaS2, respectively). In addition, the statistical analyses of different categories classified according to their cations show that the d0-transition metal and lone pair cations are more conducive to achieving a larger SHG response and birefringence compared to other cations in germanates. It gives a guideline for exploring new mid-IR NLO materials.

First-Principles High-Throughput Screening Pipeline for Nonlinear Optical Materials: Application to Borates

Discovering new nonlinear optical (NLO) materials that require an optimization between multiple properties is a time-consuming and high-cost process. To speed up material development, a First-princ...

Progressive myoclonic epilepsy-associated gene Kctd7 regulates retinal neurovascular patterning and function

Neuron function relies on and instructs the development and precise organization of neurovascular units that in turn support circuit activity. However, our understanding of the molecular cues that regulate this relationship remains sparse. Using a high-throughput screening pipeline, we recently identified several new regulators of vascular patterning. Among these was the potassium channel tetramerization domain-containing protein 7 (KCTD7). Mutations in KCTD7 are associated with progressive myoclonic epilepsy, but how KCTD7 regulates neural development and function remains poorly understood. To begin to identify such mechanisms, we focus on mouse retina, a tractable part of the central nervous system that contains precisely ordered neuron subtypes supported by a trilaminar vascular network. We find that deletion of Kctd7 induces defective patterning of the adult retina vascular network, resulting in increased branching, vessel length, and lacunarity. These alterations reflect early and specific defects in vessel development, as emergence of the superficial and deep vascular layers were delayed. These defects are likely due to a role for Kctd7 in inner retina neurons. Kctd7 is absent from vessels but present in neurons in the inner retina, and its deletion resulted in a corresponding increase in the number of bipolar cells in development and increased vessel branching in adults. These alterations were accompanied by retinal function deficits. Together, these data suggest that neuronal Kctd7 drives growth and patterning of the vasculature and that neurovascular interactions may participate in the pathogenesis of KCTD7-related human diseases.

Application of high-throughput, capillary-based Western analysis to modulated cleavage of the cellular prion protein

The cellular prion protein (PrPC) is a glycoprotein that is processed through several proteolytic pathways. Modulators of PrPC proteolysis are of interest because full-length PrPC and its cleavage fragments differ in their propensity to misfold, a process that plays a key role in the pathogenesis of prion diseases. PrPC may also act as a receptor for neurotoxic, oligomeric species of other proteins that are linked to neurodegeneration. Importantly, the PrPC C-terminal fragment C1 does not contain the reported binding sites for these oligomers. Western blotting would be a simple end point detection method for cell-based screening of compound libraries for effects on PrPC proteolysis or overall expression level. However, traditional Western blotting methods provide unreliable quantification and have only low throughput. Consequently, we explored capillary-based Western technology as a potential alternative; we believe that this study is the first to report analysis of PrPC using such an approach. We successfully optimized the detection and quantification of the deglycosylated forms of full-length PrPC and its C-terminal cleavage fragments C1 and C2, including simultaneous quantification of β-tubulin levels to control for loading error. We also developed and tested a method for performing all cell culture, lysis, and deglycosylation steps in 96-well microplates prior to capillary Western analysis. These advances represent steps along the way to the development of an automated, high-throughput screening pipeline to identify modulators of PrPC expression levels or proteolysis.

Identifying new clotting factor XIa inhibitors in virtual high-throughput screens using PCA-GA-SVM models and signature.

Blood Clotting Factor XI is an important actor in the clotting mechanism: it activates downstream zymogen involved in the clotting process. It can be targeted for activation or inhibition depending on treatment goals to enhance or inhibit clotting. In terms of antithrombosis treatment, Factor XI has emerged as a promising target to focus on. In this work, an iterative virtual high-throughput screening pipeline was proposed that can supplement current efforts to find inhibitors. The first iteration identified 11 compounds to test with 3 active for a hit-rate of 27.3%. The second iteration of the pipeline identified another 11 compounds to test with 7 active for a hit-rate of 63.6%. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1553-1565, 2018.

Guided genetic screen to identify genes essential in the regeneration of hair cells and other tissues

Regenerative medicine holds great promise for both degenerative diseases and traumatic tissue injury which represent significant challenges to the health care system. Hearing loss, which affects hundreds of millions of people worldwide, is caused primarily by a permanent loss of the mechanosensory receptors of the inner ear known as hair cells. This failure to regenerate hair cells after loss is limited to mammals, while all other non-mammalian vertebrates tested were able to completely regenerate these mechanosensory receptors after injury. To understand the mechanism of hair cell regeneration and its association with regeneration of other tissues, we performed a guided mutagenesis screen using zebrafish lateral line hair cells as a screening platform to identify genes that are essential for hair cell regeneration, and further investigated how genes essential for hair cell regeneration were involved in the regeneration of other tissues. We created genetic mutations either by retroviral insertion or CRISPR/Cas9 approaches, and developed a high-throughput screening pipeline for analyzing hair cell development and regeneration. We screened 254 gene mutations and identified 7 genes specifically affecting hair cell regeneration. These hair cell regeneration genes fell into distinct and somewhat surprising functional categories. By examining the regeneration of caudal fin and liver, we found these hair cell regeneration genes often also affected other types of tissue regeneration. Therefore, our results demonstrate guided screening is an effective approach to discover regeneration candidates, and hair cell regeneration is associated with other tissue regeneration.

Small angle X-ray scattering as a high-throughput method to classify antimicrobial modes of action

Multi-drug resistant bacteria are currently undermining our health care system worldwide. While novel antimicrobial drugs, such as antimicrobial peptides, are urgently needed, identification of new modes of action is money and time consuming, and in addition current approaches are not available in a high throughput manner. Here we explore how small angle X-ray scattering (SAXS) as high throughput method can contribute to classify the mode of action for novel antimicrobials and therefore supports fast decision making in drug development. Using data bases for natural occurring antimicrobial peptides or predicting novel artificial peptides, many candidates can be discovered that will kill a selected target bacterium. However, in order to narrow down the selection it is important to know if these peptides follow all the same mode of action. In addition, the mode of action should be different from conventional antibiotics, in consequence peptide candidates can be developed further into drugs against multi-drug resistant bacteria. Here we used one short antimicrobial peptide with unknown mode of action and compared the ultrastructural changes of Escherichia coli cells after treatment with the peptide to cells treated with classic antibiotics. The key finding is that SAXS as a structure sensitive tool provides a rapid feedback on drug induced ultrastructural alterations in whole E. coli cells. We could demonstrate that ultrastructural changes depend on the used antibiotics and their specific mode of action. This is demonstrated using several well characterized antimicrobial compounds and the analysis of resulting SAXS curves by principal component analysis. To understand the result of the PCA analysis, the data is correlated with TEM images. In contrast to real space imaging techniques, SAXS allows to obtain nanoscale information averaged over approximately one million cells. The measurement takes only seconds, while conventional tests to identify a mode of action require days or weeks per single substance. The antimicrobial peptide showed a different mode of action as all tested antibiotics including polymyxin B and is therefore a good candidate for further drug development. We envision SAXS to become a useful tool within the high-throughput screening pipeline of modern drug discovery. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert.

Abstract 1520: Development of low-cost high throughput screening pipeline for detecting germline cancer causing mutations in Hispanic populations

Abstract Cancer is a leading cause of non-communicable morbidity and mortality worldwide. Hispanics are the largest and fastest growing ethnic group in the U.S. and the largest population group in the Americas. Due to health care disparities, this population remains understudied and under-screened for cancer causing gene mutations. While many genes that predispose individuals for different cancers have been discovered, the prevalence of mutations in these genes remains largely undetermined in many populations. Developing customized screening panels and screening for novel variants for large population samples can be expensive and time consuming. We have developed a low-cost, high-throughput pipeline and method to screen 480 customizable amplicons (∼20 genes, ∼144Kbp) for up to 384 samples per run. By combining a bioinformatics pipeline for design and analysis with Fluidigm microfluidics PCR and Illumina MiSeq, we can quickly screen multiple cancer panels at a high depth of coverage, at a low cost per sample. The amplicon design pipeline provides ability to develop amplicon primer sets and pooling strategies. Libraries of 384 barcoded samples are run in a single MiSeq lane. Sequencing data is analyzed by an automated pipeline, which aligns using BWA-MEM, calls variants using VarScan 2, and annotates variants using multiple datasets using Annovar. We have applied these pipelines and methods to identify mutation in known cancer genes, such as APC, MSH2, MLH1, BRCA1, and BRCA2, in several hundred Hispanic individuals with familial and early-onset colon and breast cancer. While many of the mutations have been previously reported, we have identified several novel mutations that appear to have Amerindian origin. Moreover, a few are shared among many individuals in isolated geographic locations, suggesting founder effects are common in some of these populations. Over 50% of the patients screened to date have no mutations in our cancer panels; we plan to use these samples to screen for novel genes using whole exome or genome sequencing in the next phase of our study. In conclusion, we have developed a low-cost, high-throughput pipeline for screening customizable panels for known and novel mutations. Our study is an initial step to assess prevalence of known cancer causing genes and identify novel genes/mutations that contribute to different cancers in the Hispanic community. These discoveries provide a foundation for early detection, prevention, and treatment of familial cancers in Hispanic populations. Citation Format: Paul Lott, Ruta Sahasrabudhe, Anna Marie Tuazon, John Williamson, Ana Estrada, Mabel Bohorquez, Rodrigo Prieto, Angel Criollo, Alejandro Velez, Jorge Castro, Gilbert Mateus, María Magdalena Echeverry, Luis Carvajal-Carmona. Development of low-cost high throughput screening pipeline for detecting germline cancer causing mutations in Hispanic populations. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1520. doi:10.1158/1538-7445.AM2014-1520

High-throughput screening for broad-spectrum chemical inhibitors of RNA viruses.

RNA viruses are responsible for major human diseases such as flu, bronchitis, dengue, Hepatitis C or measles. They also represent an emerging threat because of increased worldwide exchanges and human populations penetrating more and more natural ecosystems. A good example of such an emerging situation is chikungunya virus epidemics of 2005-2006 in the Indian Ocean. Recent progresses in our understanding of cellular pathways controlling viral replication suggest that compounds targeting host cell functions, rather than the virus itself, could inhibit a large panel of RNA viruses. Some broad-spectrum antiviral compounds have been identified with host target-oriented assays. However, measuring the inhibition of viral replication in cell cultures using reduction of cytopathic effects as a readout still represents a paramount screening strategy. Such functional screens have been greatly improved by the development of recombinant viruses expressing reporter enzymes capable of bioluminescence such as luciferase. In the present report, we detail a high-throughput screening pipeline, which combines recombinant measles and chikungunya viruses with cellular viability assays, to identify compounds with a broad-spectrum antiviral profile.

Distant homology modeling of LCAT and its validation through in silico targeting and in vitro and in vivo assays.

LCAT (lecithin:cholesterol acyltransferase) catalyzes the transacylation of a fatty acid of lecithin to cholesterol, generating a cholesteryl ester and lysolecithin. The knowledge of LCAT atomic structure and the identification of the amino acids relevant in controlling its structure and function are expected to be very helpful to understand the enzyme catalytic mechanism, as involved in HDL cholesterol metabolism. However - after an early report in the late ‘90 s - no recent advance has been made about LCAT three-dimensional structure. In this paper, we propose an LCAT atomistic model, built following the most up-to-date molecular modeling approaches, and exploiting newly solved crystallographic structures. LCAT shows the typical folding of the α/β hydrolase superfamily, and its topology is characterized by a combination of α-helices covering a central 7-strand β-sheet. LCAT presents a Ser/Asp/His catalytic triad with a peculiar geometry, which is shared with such other enzyme classes as lipases, proteases and esterases. Our proposed model was validated through different approaches. We evaluated the impact on LCAT structure of some point mutations close to the enzyme active site (Lys218Asn, Thr274Ala, Thr274Ile) and explained, at a molecular level, their phenotypic effects. Furthermore, we devised some LCAT modulators either designed through a de novo strategy or identified through a virtual high-throughput screening pipeline. The tested compounds were proven to be potent inhibitors of the enzyme activity.

Automated quantification of zebrafish somites based on PDE method

With the availability of high-throughput imaging machines and a large number of zebrafish embryos, zebrafish are clearly among the most cost-effective vertebrate systems for high-throughput or high-content screens with applications in drug discovery and biological pathway analysis. With the tremendous volume of images generated from large numbers of zebrafish screens, computerized image analysis for accurate and efficient data interpretation becomes essential. This paper presents an automated algorithm for a high-throughput screening pipeline for quantification of zebrafish somite. First, the main body is segmented using the level set method; then the head is removed; after that, the body is aligned and a coherence-enhancing filter is carried out so as to facilitate the somite detection. Finally, the somites can be easily extracted. Preliminary evaluation results are reported to demonstrate the good performance of the algorithm.