Medicine and Health Sciences Commons^™

Mutational Analysis Of The Nitrogenase Carbon Monoxide Protective Protein Cown Reveals That A Conserved C‑Terminal Glutamic Acid Residue Is Necessary For Its Activity, Dustin L. Willard, Joshuah J. Arellano, Mitch Underdahl, Terrence M. Lee, Avinash S. Ramaswamy, Gabriella Fumes, Agatha Kliman, Emily Y. Wong, Cedric P. Owens

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Nitrogenase is the only enzyme that catalyzes the reduction of nitrogen gas into ammonia. Nitrogenase is tightly inhibited by the environmental gas carbon monoxide (CO). Many nitrogen fixing bacteria protect nitrogenase from CO inhibition using the protective protein CowN. This work demonstrates that a conserved glutamic acid residue near the C-terminus of Gluconacetobacter diazotrophicus CowN is necessary for its function. Mutation of the glutamic acid residue abolishes both CowN’s protection against CO inhibition and the ability of CowN to bind to nitrogenase. In contrast, a conserved C-terminal cysteine residue is not important for CO protection by CowN. Overall, this work …

One Font Doesn’T Fit All: The Influence Of Digital Text Personalization On Comprehension In Child And Adolescent Readers, Shannon M. Sheppard, Susanne L. Nobles, Anton Palma, Sophie Kajfez, Marjorie Jordan, Kathy Crowley, Sofie Beier

Communication Sciences and Disorders Faculty Articles and Research

Reading comprehension is an essential skill. It is unclear whether and to what degree typography and font personalization may impact reading comprehension in younger readers. With advancements in technology, it is now feasible to personalize digital reading formats in general technology tools, but this feature is not yet available for many educational tools. The current study aimed to investigate the effect of character width and inter-letter spacing on reading speed and comprehension. We enrolled 94 children (kindergarten–8th grade) and compared performance with six font variations on a word-level semantic decision task (Experiment 1) and a passage-level comprehension task (Experiment 2). …

Additive Effects Of Cyclic Peptide [R4w4] When Added Alongside Azithromycin And Rifampicin Against Mycobacterium Avium Infection, Melissa Kelley, Kayvan Sasaninia, Arbi Abnousian, Ali Badaoui, James Owens, Abrianna Beever, Nala Kachour, Rakesh Kumar Tiwari, Vishwanath Venketaraman

Pharmacy Faculty Articles and Research

Mycobacterium avium (M. avium), a type of nontuberculous mycobacteria (NTM), poses a risk for pulmonary infections and disseminated infections in immunocompromised individuals. Conventional treatment consists of a 12-month regimen of the first-line antibiotics rifampicin and azithromycin. However, the treatment duration and low antibiotic tolerability present challenges in the treatment of M. avium infection. Furthermore, the emergence of multidrug-resistant mycobacterium strains prompts a need for novel treatments against M. avium infection. This study aims to test the efficacy of a novel antimicrobial peptide, cyclic [R4W4], alongside the first-line antibiotics azithromycin and rifampicin in reducing M. avium survival. Colony-forming unit (CFU) …

Development And Validation Of A Uplc-Ms/Ms Method To Investigate The Plasma Pharmacokinetics Of A KCa2.2/KCa2.3 Positive Allosteric Modulator In Mice, Mohammad Asikur Rahman, Devaraj Venkatapura Chandrashekar, Young-Woo Nam, Basir Syed, David Salehi, Hamidreza Montazeri Aliabadi, Miao Zhang, Reza Mehvar

Pharmacy Faculty Articles and Research

Rationale

There is currently no treatment for spinocerebellar ataxias (SCAs), which are a group of genetic disorders that often cause a lack of coordination, difficulty walking, slurred speech, tremors, and eventually death. Activation of K_Ca2.2/K_Ca2.3 channels reportedly exerts beneficial effects in SCAs. Here, we report the development and validation of an analytical method for quantitating a recently-developed positive allosteric modulator of K_Ca2.2/K_Ca2.3 channels (compound 2q) in mouse plasma.

Methods

Mouse plasma samples (10 μL) containing various concentrations of 2q were subjected to protein precipitation in the presence of a structurally similar internal …

Balancing Functional Tradeoffs Between Protein Stability And Ace2 Binding In The Sars-Cov-2 Omicron Ba.2, Ba.2.75 And Xbb Lineages: Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic And Energetic Changes, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

Evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity for ACE2, conformational plasticity, protein stability and allosteric modulation. In this study, we systematically characterize conformational dynamics, structural stability and binding affinities of the SARS-CoV-2 Spike Omicron complexes with the host receptor ACE2 for BA.2, BA.2.75, XBB.1 and XBB.1.5 variants. We combined multiscale molecular simulations and dynamic analysis of allosteric interactions together with the ensemble-based mutational scanning of the protein residues and network modeling of epistatic interactions. This multifaceted computational study characterized molecular mechanisms and …

Small Community Water Systems Have The Highest Prevalence Of Mn In Drinking Water In California, Usa, Miranda Aiken, Samantha C. Ying

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Manganese (Mn) is currently regulated as a secondary contaminant in California, USA; however, recent revisions of the World Health Organization drinking water guidelines have increased regulatory attention of Mn in drinking water due to increasing reports of neurotoxic effects in infants and children. In this study, Mn concentrations reported to California’s Safe Drinking Water Information System were used to estimate the potentially exposed population within California based on system size. We estimate that between 2011 and 2021, over 525,000 users in areas with reported Mn data are potentially exposed to Mn concentrations exceeding the WHO health-based guideline (80 μg L …

Structure-Guided Mutagenesis Reveals The Catalytic Residue That Controls The Regiospecificity Of C6-Indole Prenyltransferases, Ahmed R. Aoun, Nagaraju Mupparapu, Diem N. Nguyen, Tae Ho Kim, Christopher M. Nguyen, Zhengfeiyue Pan, Sherif I. Elshahawi

Pharmacy Faculty Articles and Research

Indole is a significant structural moiety and functionalization of the C−H bond in indole-containing molecules expands their chemical space, and modifies their properties and/or activities. Indole prenyltransferases (IPTs) catalyze the direct regiospecific installation of prenyl moieties on indole-derived compounds. IPTs have shown relaxed substrate flexibility enabling them to be used as tools for indole functionalization. However, the mechanism by which certain IPTs target a specific carbon position is not fully understood. Herein, we use structure-guided site-directed mutagenesis, in vitro enzymatic reactions, kinetics and structural-elucidation of analogs to verify the key catalytic residues that control the regiospecificity of all characterized regiospecific …

Dense & Attention Convolutional Neural Networks For Toe Walking Recognition, Junde Chen, Rahul Soangra, Marybeth Grant-Beuttler, Y. A. Nanehkaran, Yuxin Wen

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are …

From Deep Mutational Mapping Of Allosteric Protein Landscapes To Deep Learning Of Allostery And Hidden Allosteric Sites: Zooming In On “Allosteric Intersection” Of Biochemical And Big Data Approaches, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric …

Computational Design And Molecular Modeling Of Morphine Derivatives For Preferential Binding In Inflamed Tissue, Makena Augenstein, Nayiri Alexander, Matthew Gartner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The opioid epidemic has impacted over 10 million Americans in 2019. Opioids, like morphine, bind non-selectively in both peripheral tissue, leading to effective pain relief, and central tissue, resulting in dangerous side effects and addiction. The inflamed conditions of injured tissues have a lower pH (pH = 6–6.5) environment than healthy tissue (pH = 7.4). We aim to design a morphine derivative that binds selectively within inflamed tissue using molecular extension and dissection techniques. Morphine binds to the μ-opioid receptor (MOR) when the biochemically active amine group is protonated. Fluorination of a β-carbon from the tertiary amine group led to …

Coarse-Grained Molecular Simulations And Ensemble-Based Mutational Profiling Of Protein Stability In The Different Functional Forms Of The Sars-Cov-2 Spike Trimers: Balancing Stability And Adaptability In Ba.1, Ba.2 And Ba.2.75 Variants, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

Evolutionary and functional studies have suggested that the emergence of Omicron variants can be determined by multiple fitness tradeoffs including immune escape, binding affinity, conformational plasticity, protein stability, and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability, and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined the conformational dynamics of the spike trimers that agree with the recent functional studies, suggesting that BA.2.75 trimers are the most stable …

Virtual And In Vitro Screening Of Natural Products Identifies Indole And Benzene Derivatives As Inhibitors Of Sars-Cov-2 Main Protease (MPro), Dony Ang, Riley Kendall, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with …

Predicting Suicidal And Self-Injurious Events In A Correctional Setting Using Ai Algorithms On Unstructured Medical Notes And Structured Data, Hongxia Lu, Alex Barrett, Albert Pierce, Jianwei Zheng, Yun Wang, Chun Chiang, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Suicidal and self-injurious incidents in correctional settings deplete the institutional and healthcare resources, create disorder and stress for staff and other inmates. Traditional statistical analyses provide some guidance, but they can only be applied to structured data that are often difficult to collect and their recommendations are often expensive to act upon. This study aims to extract information from medical and mental health progress notes using AI algorithms to make actionable predictions of suicidal and self-injurious events to improve the efficiency of triage for health care services and prevent suicidal and injurious events from happening at California's Orange County Jails. …

Not A Waste: Wastewater Surveillance To Enhance Public Health, Anna Gitter, Jeremiah Oghuan, Anuja Rajendra Godbole, Carlos A. Chavarria, Carlos Monserrat, Tao Hu, Yun Wang, Anthony W. Maresso, Blake M. Hanson, Kristina D. Mena, Fuqing Wu

Pharmacy Faculty Articles and Research

Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve …