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Membrane proteins play crucial roles in various cellular processes, and their interactions with other proteins in and on the membrane are essential for their proper functioning. While an increasing number of structures of more membrane proteins are being determined, the available structure data is still sparse. To gain insights into the mechanisms of membrane protein complexes, computational docking methods are necessary due to the challenge of experimental determination. Here, we introduce Mem-LZerD, a rigid-body membrane docking algorithm designed to take advantage of modern membrane modeling and protein docking techniques to facilitate the docking of membrane protein complexes. Mem-LZerD is based on the LZerD protein docking algorithm, which has been constantly among the top servers in many rounds of CAPRI protein docking assessment. By employing a combination of geometric hashing, newly constrained by the predicted membrane height and tilt angle, and model scoring accounting for the energy of membrane insertion, we demonstrate the capability of Mem-LZerD to model diverse membrane protein-protein complexes. Mem-LZerD successfully performed unbound docking on 13 of 21 (61.9%) transmembrane complexes in an established benchmark, more than shown by previous approaches. It was additionally tested on new datasets of 44 transmembrane complexes and 92 peripheral membrane protein complexes, of which it successfully modeled 35 (79.5%) and 15 (16.3%) complexes respectively. When non-blind orientations of peripheral targets were included, the number of successes increased to 54 (58.7%). We further demonstrate that Mem-LZerD produces complex models which are suitable for molecular dynamics simulation. Mem-LZerD is made available at https://lzerd.kiharalab.org., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Proteins are key components in many processes in living cells, and physical interactions with other proteins and nucleic acids often form key parts of their functions. In many cases, large flexibility of proteins as they interact is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D structures of such protein complexes. When such structures are not yet experimentally determined, protein docking has long been present to computationally generate useful structure models. However, protein docking has long had the limitation that the consideration of flexibility is usually limited to very small movements or very small structures. Methods have been developed which handle minor flexibility via normal mode or other structure sampling, but new methods are required to model ordered proteins which undergo large-scale conformational changes to elucidate their function at the molecular level. Here, we present Flex-LZerD, a framework for docking such complexes. Via partial assembly multidomain docking and an iterative normal mode analysis admitting curvilinear motions, we demonstrate the ability to model the assembly of a variety of protein-protein and protein-nucleic acid complexes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background & Aims: Acute kidney disease (AKD) is the persistence of acute kidney injury (AKI) for up to 3 months, which is proposed to be the time-window where critical interventions can be initiated to alter downstream outcomes of AKI. In cirrhosis, AKD and its impact on outcomes have been scantly investigated. We aimed to define the incidence and outcomes associated with AKD in a nationwide US cohort of hospitalized patients with cirrhosis and AKI., Methods: Hospitalized patients with cirrhosis and AKI in the Cerner-Health-Facts database from 1/2009-09/2017 (n = 6,250) were assessed for AKD and were followed-up for 180 days. AKI and AKD were defined based on KDIGO and ADQI AKD and renal recovery consensus criteria, respectively. The primary outcome measure was mortality, and the secondary outcome measure was de novo chronic kidney disease (CKD). Competing-risk multivariable models were used to determine the independent association of AKD with primary and secondary outcomes., Results: AKD developed in 32% of our cohort. On multivariable competing-risk analysis adjusting for significant confounders, patients with AKD had higher risk of mortality at 90 (subdistribution hazard ratio [sHR] 1.37; 95% CI 1.14-1.66; p = 0.001) and 180 (sHR 1.37; 95% CI 1.14-1.64; p = 0.001) days. The incidence of de novo CKD was 37.5%: patients with AKD had higher rates of de novo CKD (64.0%) compared to patients without AKD (30.7%; p <0.001). After adjusting for confounders, AKD was independently associated with de novo CKD (sHR 2.52; 95% CI 2.01-3.15; p <0.001) on multivariable competing-risk analysis., Conclusions: AKD develops in 1 in 3 hospitalized patients with cirrhosis and AKI and it is associated with worse survival and de novo CKD. Interventions that target AKD may improve outcomes of patients with cirrhosis and AKI., Lay Summary: In a nationwide US cohort of hospitalized patients with cirrhosis and acute kidney injury, acute kidney disease developed in 1 in 3 patients and was associated with worse survival and chronic kidney disease. Interventions that target acute kidney disease may improve outcomes of patients with cirrhosis and acute kidney injury., Competing Interests: Conflicts of interest Dr. Naga Chalasani has ongoing paid consulting activities (or had in preceding 12 months) with Abbvie, Madrigal, Foresite, Galectin, Zydus, and Boehringer-Ingelheim, Altimmune. These consulting activities are generally in the areas of non-alcoholic fatty liver disease and drug hepatotoxicity. Dr. Chalasani receives research grant support from Exact Sciences, DSM, and Galectin Therapeutics where his institution receives the funding. He has equity interest in RestUp, a healthcare staffing start-up company Remaining authors have no disclosures to report. None of the aforementioned disclosures are related to the study. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2022 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

Lung cancer is a leading cause of death throughout the world. Because the prompt diagnosis of tumors allows oncologists to discern their nature, type, and mode of treatment, tumor detection and segmentation from CT scan images is a crucial field of study. This paper investigates lung tumor segmentation via a two-dimensional Discrete Wavelet Transform (DWT) on the LOTUS dataset (31,247 training, and 4458 testing samples) and a Deeply Supervised MultiResUNet model. Coupling the DWT, which is used to achieve a more meticulous textural analysis while integrating information from neighboring CT slices, with the deep supervision of the model architecture results in an improved dice coefficient of 0.8472. A key characteristic of our approach is its avoidance of 3D kernels (despite being used for a 3D segmentation task), thereby making it quite lightweight., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital challenges present in the deployment of EEG-based biometrics, which is stable and capable of handling the real-world scenario. One of the key challenges is the large signal variability of EEG when recorded on different days or sessions which impedes the performance of biometric systems significantly. To address this issue, a session invariant multimodal Self-organized Operational Neural Network (Self-ONN) based ensemble model combining EEG and keystroke dynamics is proposed in this paper. Our model is tested successfully on a large number of sessions (10 recording days) with many challenging noisy and variable environments for the identification and authentication tasks. In most of the previous studies, training and testing were performed either over a single recording session (same day) only or without ensuring appropriate splitting of the data on multiple recording days. Unlike those studies, in our work, we have rigorously split the data so that train and test sets do not share the data of the same recording day. The proposed multimodal Self-ONN based ensemble model has achieved identification accuracy of 98% in rigorous validation cases and outperformed the equivalent ensemble of deep CNN models. A novel Self-ONN Siamese network has also been proposed to measure the similarity of templates during the authentication task instead of the commonly used simple distance measure techniques. The multimodal Siamese network reduces the Equal Error Rate (EER) to 1.56% in rigorous authentication. The obtained results indicate that the proposed multimodal Self-ONN model can automatically extract session invariant unique non-linear features to identify and authenticate users with high accuracy., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: This study aimed to investigate the prevalence and factors associated with oral anticoagulant undertreatment of atrial fibrillation (AF) among a cohort of rural patients with stroke outcomes and examine how undertreatment may influence a patient's one-year survival after stroke., Methods: This retrospective cohort study examined ischemic stroke patients with pre-stroke AF diagnosis from September 2003 to May 2019 and divided them into proper treatment and undertreatment group. Analysis included chi-square test, variance analysis, Kruskal-Wallis test, logistic regression, Kaplan-Meier estimator, and Cox proportional-hazards model., Results: Out of 1062 ischemic stroke patients with a pre-stroke AF diagnosis, 1015 patients had a CHA 2 DS 2 -VASc score ≥2, and 532 (52.4%) of those were undertreated. Median time from AF diagnosis to index stroke was significantly lower among undertreated patients (1.9 years vs. 3.6 years, p < 0.001). Other thromboembolism, excluding stroke, TIA, and myocardial infarction (OR 0.41, p < 0.001), the number of encounters per year (OR 0.90, p < 0.001), and the median time between AF diagnosis and stroke event (OR 0.86, p < 0.001) were negatively associated with undertreatment. Kaplan-Meier estimator showed no statistical difference in the one-year survival probability between groups (log-rank test, p = 0.29), while the Cox-Hazard model showed that age (HR 1.05, p < 0.001) and history of congestive heart failure (HR 1.88, p < 0.001) increased the risk of mortality., Conclusions: More than half of our rural stroke patients with a pre-index AF diagnosis were not on guideline-recommended treatment. The study highlights a large care gap and an opportunity to improve AF management., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Phage G has the largest capsid and genome of any known propagated phage. Many aspects of its structure, assembly, and replication have not been elucidated. Herein, we present the dsDNA-packed and empty phage G capsid at 6.1 and 9 Å resolution, respectively, using cryo-EM for structure determination and mass spectrometry for protein identification. The major capsid protein, gp27, is identified and found to share the HK97-fold universally conserved in all previously solved dsDNA phages. Trimers of the decoration protein, gp26, sit on the 3-fold axes and are thought to enhance the interactions of the hexameric capsomeres of gp27, for other phages encoding decoration proteins. Phage G's decoration protein is longer than what has been reported in other phages, and we suspect the extra interaction surface area helps stabilize the capsid. We identified several additional capsid proteins, including a candidate for the prohead protease responsible for processing gp27. Furthermore, cryo-EM reveals a range of partially full, condensed DNA densities that appear to have no contact with capsid shell. Three analyses confirm that the phage G host is a Lysinibacillus, and not Bacillus megaterium: identity of host proteins in our mass spectrometry analyses, genome sequence of the phage G host, and host range of phage G., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Methods that determine the relative purity of biopharmaceuticals represent the most widely used form of analysis for the pharmaceutical industry. The ability to rapidly assess method capability or the uncertainty of measurements under actual use conditions continues to present significant challenges. We have refined and applied the model of Uncertainty Based on Current Information to predict the precision of the purity measurements and compared the predicted precision to the measured variability for several different types of purity methods. The measured method variability was derived from the analysis of data sets ranging from hundreds to thousands of measurements for each different method type. The predicted precision was found to be in excellent agreement with the statistically obtained values with R 2  = 0.94. This demonstration of concurrence between the predicted and actual precision provides an opportunity for streamlining laborious conventional (statically derived) assessment of method precision and leveraging the Uncertainty Based on Current Information model utilizing much smaller data sets or even a single experiment., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Direct comparison of three-dimensional (3D) objects is computationally expensive due to the need for translation, rotation, and scaling of the objects to evaluate their similarity. In applications of 3D object comparison, often identifying specific local regions of objects is of particular interest. We have recently developed a set of 2D moment invariants based on discrete orthogonal Krawtchouk polynomials for comparison of local image patches. In this work, we extend them to 3D and construct 3D Krawtchouk descriptors (3DKDs) that are invariant under translation, rotation, and scaling. The new descriptors have the ability to extract local features of a 3D surface from any region-of-interest. This property enables comparison of two arbitrary local surface regions from different 3D objects. We present the new formulation of 3DKDs and apply it to the local shape comparison of protein surfaces in order to predict ligand molecules that bind to query proteins.

The discovery of molecules that can inhibit the action of phytopathogens is essential to find alternative to current pesticides. Pectin methylesterases (PME), enzymes that fine-tune the degree of methylesterification of plant cell wall pectins, play a key role in the pathogenicity of fungi or bacteria. Here we report the synthesis of new lactoside derivatives and their analysis as potential PME inhibitors using three plants and one fungal PME. Because of its structure, abundance and reduced cost, lactose was chosen as a case study. Lactoside derivatives were obtained by TEMPO-mediated oxidation of methyl lactoside, followed by an esterification procedure. Three derivatives were synthesized: sodium (methyl-lactosid)uronate, methyl (methyl-lactosid)uronate and butyl (methyl-lactosid)uronate. The inhibition of the plant and pathogen enzyme activities by lactoside derivatives was measured in vitro, showing the importance of the substitution on lactose: methyl (methyl-lactosid)uronate was more efficient than butyl (methyl-lactosid)uronate. These results were confirmed by docking analysis showing the difference in the interaction between lactoside derivatives and PME proteins. In conclusion, this study identified novel inhibitors of pectin remodeling enzymes., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Intrinsically disordered proteins (IDPs) or regions (IDRs) perform diverse cellular functions, but are also prone to forming promiscuous and potentially deleterious interactions. We investigate the extent to which the properties of, and content in, IDRs have adapted to enable functional diversity while limiting interference from promiscuous interactions in the crowded cellular environment. Information on protein sequences, their predicted intrinsic disorder, and 3D structure contents is related to data on protein cellular concentrations, gene co-expression, and protein-protein interactions in the well-studied yeast Saccharomyces cerevisiae. Results reveal that both the protein IDR content and the frequency of "sticky" amino acids in IDRs (those more frequently involved in protein interfaces) decrease with increasing protein cellular concentration. This implies that the IDR content and the amino acid composition of IDRs experience negative selection as the protein concentration increases. In the S. cerevisiae protein-protein interaction network, the higher a protein's IDR content, the more frequently it interacts with IDR-containing partners, and the more functionally diverse the partners are. Employing a clustering analysis of Gene Ontology terms, we newly identify ~600 putative multifunctional proteins in S. cerevisiae. Strikingly, these proteins are enriched in IDRs and contribute significantly to all the observed trends. In particular, IDRs of multi-functional proteins feature more sticky amino acids than IDRs of their non-multifunctional counterparts, or the surfaces of structured yeast proteins. This property likely affords sufficient binding affinity for the functional interactions, commonly mediated by short IDR segments, thereby counterbalancing the loss in overall IDR conformational entropy upon binding., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The objective of this paper is to investigate the respective influence of various urban pattern characteristics on inundation flow. A set of 2000 synthetic urban patterns were generated using an urban procedural model providing locations and shapes of streets and buildings over a square domain of 1×1km 2 . Steady two-dimensional hydraulic computations were performed over the 2000 urban patterns with identical hydraulic boundary conditions. To run such a large amount of simulations, the computational efficiency of the hydraulic model was improved by using an anisotropic porosity model. This model computes on relatively coarse computational cells, but preserves information from the detailed topographic data through porosity parameters. Relationships between urban characteristics and the computed inundation water depths have been based on multiple linear regressions. Finally, a simple mechanistic model based on two district-scale porosity parameters, combining several urban characteristics, is shown to capture satisfactorily the influence of urban characteristics on inundation water depths. The findings of this study give guidelines for more flood-resilient urban planning., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Tailed bacteriophages and herpesviruses consist of a structurally well conserved dodecameric portal at a special 5-fold vertex of the capsid. The portal plays critical roles in head assembly, genome packaging, neck/tail attachment, and genome ejection. Although the structures of portals from phages φ29, SPP1, and P22 have been determined, their mechanistic roles have not been well understood. Structural analysis of phage T4 portal (gp20) has been hampered because of its unusual interaction with the Escherichia coli inner membrane. Here, we predict atomic models for the T4 portal monomer and dodecamer, and we fit the dodecamer into the cryo-electron microscopy density of the phage portal vertex. The core structure, like that from other phages, is cone shaped with the wider end containing the "wing" and "crown" domains inside the phage head. A long "stem" encloses a central channel, and a narrow "stalk" protrudes outside the capsid. A biochemical approach was developed to analyze portal function by incorporating plasmid-expressed portal protein into phage heads and determining the effect of mutations on head assembly, DNA translocation, and virion production. We found that the protruding loops of the stalk domain are involved in assembling the DNA packaging motor. A loop that connects the stalk to the channel might be required for communication between the motor and the portal. The "tunnel" loops that project into the channel are essential for sealing the packaged head. These studies established that the portal is required throughout the DNA packaging process, with different domains participating at different stages of genome packaging., (© 2013.)