De-novo Model Research Articles

Structural features of carrot α-tubulin predetermining the natural resistance to dinitroaniline herbicides

Aim. To explain the natural resistance of Daucus carota L. to dinitroaniline herbicides. To clarify features of the carrot α-tubulin that may affect formation of the ligand-protein complex based on the structural and electrostatic analysis of the ligand-binding site. Methods. Reconstruction of the spatial structure of α-tubulin from D. carota and Toxoplasma gondii using profile (Swiss-Model) and de-novo (AlphaFold2) modeling. Molecular dynamics (MD) simulations of the built 3D-models in Gromacs. Analysis of the molecular electrostatics with PDB2PQR/APBS tools. Visualization and analysis of molecular structures in PyMOL. Results. It has been shown that along with the typical positive charge of the dinitroaniline-binding pocket, all isotypes of carrot α-tubulin demonstrate negatively charged regions that may cause conflicts with the nitro-groups of the ligands. Also, the MD-stable negatively charged "bridge" between Cys316 and the aryl-fragment of Phe255 was observed in all α-tubulin isotypes. In our opinion, it not only competes with the cyclic fragment of dinitroanilines, but overall prevent the opening of the site pocket in carrot α-tubulin. Conclusions. It was clarified that natural resistance of D. carota to dinitroaniline herbicides may be associated with steric and electrostatic conflicts observed in in all α-tubulin isotypes. In our opinion, it prevents interaction with dinitroaniline compounds at the stage of primary site recognition on the early stages of protein-ligand complex formation.

EE119 Development of a De Novo Model to Assess the Cost-Effectiveness of a New Treatment Option for Patients With Primary Immunoglobulin a Nephropathy (IgAN)

EE119 Development of a De Novo Model to Assess the Cost-Effectiveness of a New Treatment Option for Patients With Primary Immunoglobulin a Nephropathy (IgAN)

3D U-Net for automated detection of multiple sclerosis lesions: utility of transfer learning from other pathologies.

Deep learning algorithms for segmentation of multiple sclerosis (MS) plaques generally require training on large datasets. This manuscript evaluates the effect of transfer learning from segmentation of another pathology to facilitate use of smaller MS-specific training datasets. That is, a model trained for detection of one type of pathology was re-trained to identify MS lesions and active demyelination. In this retrospective study using MRI exams from 149 patients spanning 4/18/2014 to 7/8/2021, 3D convolutional neural networks were trained with a variable number of manually-segmented MS studies. Models were trained for FLAIR lesion segmentation at a single timepoint, new FLAIR lesion segmentation comparing two timepoints, and enhancing (actively demyelinating) lesion segmentation on T1 post-contrast imaging. Models were trained either de-novo or fine-tuned with transfer learning applied to a pre-existing model initially trained on non-MS data. Performance was evaluated with lesionwise sensitivity and positive predictive value (PPV). For single timepoint FLAIR lesion segmentation with 10 training studies, a fine-tuned model demonstrated improved performance [lesionwise sensitivity 0.55 ± 0.02 (mean ± standard error), PPV 0.66 ± 0.02] compared to a de-novo model (sensitivity 0.49 ± 0.02, p = 0.001; PPV 0.32 ± 0.02, p < 0.001). For new lesion segmentation with 30 training studies and their prior comparisons, a fine-tuned model demonstrated similar sensitivity (0.49 ± 0.05) and significantly improved PPV (0.60 ± 0.05) compared to a de-novo model (sensitivity 0.51 ± 0.04, p = 0.437; PPV 0.43 ± 0.04, p = 0.002). For enhancement segmentation with 20 training studies, a fine-tuned model demonstrated significantly improved overall performance (sensitivity 0.74 ± 0.06, PPV 0.69 ± 0.05) compared to a de-novo model (sensitivity 0.44 ± 0.09, p = 0.001; PPV 0.37 ± 0.05, p = 0.001). By fine-tuning models trained for other disease pathologies with MS-specific data, competitive models identifying existing MS plaques, new MS plaques, and active demyelination can be built with substantially smaller datasets than would otherwise be required to train new models.

Cryo-EM Analysis and de Novo Modeling of E. coli dihydrolipoamide Succinyltransferase Catalytic Domain Structure

Journal Article Cryo-EM Analysis and de Novo Modeling of E. coli dihydrolipoamide Succinyltransferase Catalytic Domain Structure Get access Vasily Mikirtumov, Vasily Mikirtumov Moscow Lomonosov University, moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Evgeny Pichkur, Evgeny Pichkur Kurchatov Institute, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Olga Tikhonova, Olga Tikhonova Orekhovich Research Institute of Biomedical Chemistry RAS, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Lidia Kurochkina, Lidia Kurochkina Belozersky Research Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Olga Sokolova Olga Sokolova Lomonosov Moscow State University, Faculty of Biology, Moscow, Moskva, Russia Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 26, Issue S2, 1 August 2020, Pages 1288–1291, https://doi.org/10.1017/S1431927620017596 Published: 01 August 2020

Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo-Electron Microscopy Maps.

In recent years, three‐dimensional density maps reconstructed from single particle images obtained by electron cryo‐microscopy (cryo‐EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the constituting structures require de‐novo model building or are very mobile. Herein, we demonstrate the potential of convolutional neural networks for the annotation of cryo‐EM maps: our network Haruspex has been trained on a carefully curated set of 293 experimentally derived reconstruction maps to automatically annotate RNA/DNA as well as protein secondary structure elements. It can be straightforwardly applied to newly reconstructed maps in order to support domain placement or as a starting point for main‐chain placement. Due to its high recall and precision rates of 95.1 % and 80.3 %, respectively, on an independent test set of 122 maps, it can also be used for validation during model building. The trained network will be available as part of the CCP‐EM suite.

P244 Determining factors related to poor quality of life in patients with axSpA: results from the British Society for Rheumatology Biologics Register

Abstract Background The aim when treating people with axial spondyloarthropathies (axSpA) is to maintain/improve their Quality of Life (QoL), traditionally through reducing disease activity. Previously, the Scotland Registry for Ankylosing Spondylitis (SIRAS) demonstrated, however, that although important, disease activity may not be the only factor influencing QoL. Indeed, function was a better predictor, with fatigue, chronic widespread pain and spinal mobility also important. The aim of the current study was to validate the previous findings in a large nationwide population, and determine if other factors, not collected in the previous study (such as mood and sleep) are also important. Methods The British Society for Rheumatology Biologics Register in Ankylosing Spondylitis (BSRBR-AS) is a prospective cohort of axSpA patients from 83 secondary care centres across Great Britain. Clinical data was collected during routine clinic visits and questionnaires provided patient reported outcomes including: the Ankylosing Spondylitis QoL questionnaire (ASQoL: scored 0 (best) to 18 (worst)), the Bath AS indices for disease &amp; physical activity ((BASDAI/BASFI: scored 0 (best) - 10 (worst)), sleep disturbance (Jenkins: 0 (best) - 20 (worst)), depression (hospital anxiety &amp; depression scales: scored 0 (best) - 21 (worst)) and the modification of the 2010 fibromyalgia criteria (widespread pain index (WPI): scored 0 (best) - 19 (worst) &amp; symptom severity score (SSS): 0 (best) -12 (worst)). Using data collected at BSRBR-AS registration, multivariate linear regression models, predicting ASQoL, were used to validate the previous SIRAS model. Additionally, a de-novo forward stepwise model was developed to assess consistency across both populations and to determine if any additional factors (such as mood and sleep) predicted QoL. Results 1,810 BSRBR-AS participants were eligible for the current study, 67% of whom were male, median age 49 years (interquartile range 38-61). 80% of those tested were HLA-B27 positive and the majority of patients (67%) met the modified New York Criteria for AS. Of the five factors included in the SIRAS model; disease activity, physical function, fatigue and widespread pain remained significantly associated with QoL in the BSRBR-AS study. Spinal mobility was no longer significantly associated. Within the de-novo model eight independent factors predicted ASQoL score: disease activity (coefficient 0.31, 95% (confidence interval 0.14, 0.47)), physical function (0.59 (0.45, 0.73)), depression (HADS: 0.16 (0.09, 0.24)), sleep disturbance (0.08 (0.04, 0.13)), activity impairment (0.04 (0.02, 0.05)), fibromyalgia (SSS: 0.24 (0.13, 0.35), WPI: 0.10 (0.03, 0.17)) and tobacco smoking (vs. non-smoker: 0.66 (0.10, 1.21)). Conclusion Current EULAR guidelines for management of axSpA targeting disease activity and physical function are supported by the current findings which suggest both are consistently important predictors of QoL. However, additional factors such as fatigue, sleep disturbance and mood also contribute to QoL and should be considered additional targets within future axSpA management strategies. Disclosures L.E. Dean None. O. Rotariu None. G.T. Jones None. E. Pathan Other; E.P. has received salary funding from Jansen (2019) and Merck (2018). G.J. Macfarlane None.

Resistance models to EGFR inhibition and chemotherapy in non-small cell lung cancer via analysis of tumour size dynamics

PurposeImaging time-series data routinely collected in clinical trials are predominantly explored for covariates as covariates for survival analysis to support decision-making in oncology drug development. The key objective of this study was to assess if insights regarding two relapse resistance modes, de-novo (treatment selects out a pre-existing resistant clone) or acquired (resistant clone develops during treatment), could be inferred from such data.MethodsIndividual lesion size time-series data were collected from ten Phase III study arms where patients were treated with either first-generation EGFR inhibitors (erlotinib or gefitinib) or chemotherapy (paclitaxel/carboplatin combination or docetaxel). The data for each arm of each study were analysed via a competing models framework to determine which of the two mathematical models of resistance, de-novo or acquired, best-described the data.ResultsWithin the first-line setting (treatment naive patients), we found that the de-novo model best-described the gefitinib data, whereas, for paclitaxel/carboplatin, the acquired model was preferred. In patients pre-treated with paclitaxel/carboplatin, the acquired model was again preferred for docetaxel (chemotherapy), but for patients receiving gefitinib or erlotinib, both the acquired and de-novo models described the tumour size dynamics equally well. Furthermore, in all studies where a single model was preferred, we found a degree of correlation in the dynamics of lesions within a patient, suggesting that there is a degree of homogeneity in pharmacological response.ConclusionsThis analysis highlights that tumour size dynamics differ between different treatments and across lines of treatment. The analysis further suggests that these differences could be a manifestation of differing resistance mechanisms.

Spontaneous Structure Formation in the Products of UV-Initiated Formose Reaction in De-Novo Model

The structure formation in xerogels of aqueous solutions of products of the UV-initiated formose reaction has been studied in the context of the problem of the spontaneous formation of prebiological structures. Of the 11 variants of xerogels, only in the talopyranose xerogel show the presence of anisometric strings with distinct periodic (in particular, helical) structure, which form characteristic elements of biomimetic structures by interlacing. Under the conditions simulating the primitive Earth’s atmosphere (formaldehyde, water, UV), spontaneous formation of anisometric superhelical structures has been modeled and the type of the sugars forming these structures has been identified.

Su1510 - Time to Development of Hepatic Events, and a Simple De Novo Model, to Predict Hepatic Events in Patients with Nonalcoholic Fatty Liver Disease

Su1510 - Time to Development of Hepatic Events, and a Simple De Novo Model, to Predict Hepatic Events in Patients with Nonalcoholic Fatty Liver Disease

Protein domain mapping by internal labeling and single particle electron microscopy.

In recent years, electron microscopy (EM) and single particle analysis have emerged as essential tools for investigating the architecture of large biological complexes. When high resolution is achievable, crystal structure docking and de-novo modeling allows for precise assignment of individual protein domain sequences. However, the achievable resolution may limit the ability to do so, especially when small or flexible complexes are under study. In such cases, protein labeling has emerged as an important complementary tool to characterize domain architecture and elucidate functional mechanistic details. All labeling strategies proposed to date are either focused on the identification of the position of protein termini or require multi-step labeling strategies, potentially interfering with the final labeling efficiency. Here we describe a strategy for determining the position of internal protein domains within EM maps using a recombinant one-step labeling approach named Efficient Mapping by Internal Labeling (EMIL). EMIL takes advantage of the close spatial proximity of the GFP's N- and C-termini to generate protein chimeras containing an internal GFP at desired locations along the main protein chain. We apply this method to characterize the subunit domain localization of the human Polycomb Repressive Complex 2.

PRM85 - A DE-NOVO Model to Predict Outcomes of a New Hypothetical Intervention to Reduce CV Risk in Post Mi Patients

PRM85 - A DE-NOVO Model to Predict Outcomes of a New Hypothetical Intervention to Reduce CV Risk in Post Mi Patients

Abstract 4791: The role of microRNA-15a/16 in early B1 cell development in a mouse model of chronic lymphocytic leukemia

Abstract New Zealand Black (NZB) mouse is a de-novo model of chronic lymphocytic leukemia (CLL) that has been studied as a model of B-cell lymphoproliferative disorder. In most human CLL and NZB there is decreased expression of the microRNA miR15a/16. In NZB (and some CLL patients) this is due a point mutation six bases downstream from pre-miR-16 region. In both NZB mouse model and human CLL, the disease is characterized by the presence of a malignant clone of B-1 cells expressing dull levels of CD5 (T cell marker), CD11b (myeloid marker) and B220 (B cell marker). In this report we investigated the molecular pathways that result in increased B-1 lineage development in the mouse model of CLL. Initially we observed that in NZB, the B-1 lineage cells had reduced expression of Pu.1 when compared to NZB B-2 cells. PU.1 is a transcription factor required for B lineage differentiation and PU.1 knockout mice were previously found by others to have only B-1 lineage cell differentiation. To study early B1/B2 divergent cell development pathways in the context of CLL and shed light on the potential malignant cell origin of this disease, we generated induced pluripotent stem cells (iPS) from NZB spleen stromal fibroblasts. Our in vivo and in vitro studies on NZB iPS and hematopoietic progenitors (LSK) differentiation towards B-cell lineage cells followed by multicolor flow based cell sorting revealed a substantial block in the maturation of NZB iPS cells compared to wild type counterparts. Preliminary data using congenic NZB mice with corrected mir-15a/16-1 locus demonstrated that normal levels of miR-15a/16 regulate B-cell differentiation towards a higher expression of PU.1 and B220 (CD45R) and lower levels of CD11b suggestive of an enhanced B2 cell maturation pathway. Our results support the hypothesis that decreased miR-15a plays a role in B1 lymphocyte development bias in the course of B cell maturation by regulating the expression of a number of genes such as B220, PU.1 and CD11b. This work will help further uncover early molecular events which determine the increased B1 versus B2 lineage commitment associated with low levels of miR-15a/16 as an initial lesion in the development of CLL. Citation Format: Chingiz Underbayev, Siddha Kasar, Heba Degheidy, Gerald Marti, Marilyn Lightfoote, Elizabeth Raveche. The role of microRNA-15a/16 in early B1 cell development in a mouse model of chronic lymphocytic leukemia. [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 4791. doi:10.1158/1538-7445.AM2014-4791

De Novo modeling of Envelope 2 protein of HCV isolated from Pakistani patient and epitopes prediction for vaccine development.

Hepatitis C virus (HCV) is a universal health issue and a significant risk factor leading to hepatocellular carcinoma. HCV has infected approximately 170 million individuals worldwide. It is a member of Flaviviridae with positive sense RNA genome. In the absence of any effective vaccine against HCV, pegylated interferon with ribavirin is the standard of treatment against HCV infection. In this study, sequence and structural analysis of envelope 2 (E2) protein was performed which was isolated from patients of HCV genotype 3a in Pakistan. Then, epitopes were predicted which were specific for both B-cells and T-cells. Later, conservancy of epitopes was checked with the HCV 3a and 1a sequences from different countries. A total of 6 conserved epitopes were found from extra-membranous regions of E2 protein. Presence of conserved epitopes in E2 protein generates the possibility that these epitopes can be used to elicit the immune response against HCV.

Solving the Secondary Structure Matching Problem in Cryo-EM De Novo Modeling Using a Constrained K-Shortest Path Graph Algorithm.

Electron cryomicroscopy is becoming a major experimental technique in solving the structures of large molecular assemblies. More and more three-dimensional images have been obtained at the medium resolutions between 5 and 10 Å. At this resolution range, major α-helices can be detected as cylindrical sticks and β-sheets can be detected as plain-like regions. A critical question in de novo modeling from cryo-EM images is to determine the match between the detected secondary structures from the image and those on the protein sequence. We formulate this matching problem into a constrained graph problem and present an O(Δ(2)N(2)2(N)) algorithm to this NP-Hard problem. The algorithm incorporates the dynamic programming approach into a constrained K-shortest path algorithm. Our method, DP-TOSS, has been tested using α-proteins with maximum 33 helices and α-β proteins up to five helices and 12 β-strands. The correct match was ranked within the top 35 for 19 of the 20 α-proteins and all nine α-β proteins tested. The results demonstrate that DP-TOSS improves accuracy, time and memory space in deriving the topologies of the secondary structure elements for proteins with a large number of secondary structures and a complex skeleton.

A structural Role for Serotonin Transporter Terminal Domains in Uptake Regulation

Serotonin transporter (SERT) is a member of the Na+/Cl--dependent neurotransmitter transporter family (NSS or SLC6), which also includes norepinephrine transporter (NET) and dopamine transporter (DAT). SERT mediates rapid removal and recycling of released serotonin following neuronal stimulation. The activity of SERT is tightly regulated, as its misfunction is associated with diseases such as autism, bipolar disorder, depression, obsessive-compulsive disorder, migraine and anxiety. Regulation is modulated by post-translational modifications, including phosphorylation, glycosylation as well as by interaction with other proteins. The majority of this regulatory behavior involves the N- and/or C-terminal domains of the protein, the structure of which is not known. In order to determine the structural determinants of the SERT regulation we have generated a model of full-length SERT using a combination of template-based and de Novo modeling methodologies. The modeling process was carried out in three stages: a) modeling of the transmembrane segment of SERT using the X-ray structure of the bacterial homolog LeuT, b) modeling of both N- and C-terminal domains of the protein using a de Novo folding approach (Rosetta) and c) modeling of the full complex. The last two steps required extensive conformational sampling to ensure that native-like states were modeled. The best models were selected out using clustering and energetic criteria. We present a comparison of the models to the available experimental data.

De-novo modeling and ESR validation of a cyanobacterial F oF 1–ATP synthase subunit bb′ left-handed coiled coil

The structure and functional role of the dimeric external stalk of F oF 1–ATP synthases have been very actively researched over the last years. To understand the function, detailed knowledge of the structure and protein packing interactions in the dimer is required. In this paper we describe the application of structural prediction and molecular modeling approaches to elucidate the structural packing interaction of the cyanobacterial ATP synthase external stalk. In addition we present biophysical evidence derived from ESR spectroscopy and site directed spin labeling of stalk proteins that supports the proposed structural model. The use of the heterodimeric bb′ dimer from a cyanobacterial ATP synthase ( Synechocystis sp. PCC 6803) allowed, by specific introduction of spin labels along each individual subunit, the evaluation of the overall tertiary structure of the subunits by calculating inter-spin distances. At defined positions in both b and b′ subunits, reporter groups were inserted to determine and confirm inter-subunit packing. The experiments showed that an approximately 100 residue long section of the cytoplasmic part of the bb′-dimer exists mostly as an elongated α-helix. The distant C-terminal end of the dimer, which is thought to interact with the δ-subunit, seemed to be disordered in experiments using soluble bb′ proteins. A left-handed coiled coil packing of the dimer suggested from structure prediction studies and shown to be feasible in molecular modeling experiments was used together with the measured inter-spin distances of the inserted reporter groups determined in ESR experiments to support the hypothesis that a significant portion of the bb′ structure exists as a left-handed coiled coil.