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Physical Sciences and Mathematics Commons™
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- Keyword
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- Drug design (2)
- Machine learning (2)
- Molecular dynamics simulations (2)
- ACE2 host receptor (1)
- Allosteric inhibitors (1)
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- Aminoacyl-tRNA synthetase (1)
- Antibiotic resistance (1)
- Apigenin (1)
- Arrhythmia (1)
- Artificial intelligence (1)
- Autism spectrum disorder (1)
- BTBR mice (1)
- Bayesian network algorithm (1)
- Binding energetics (1)
- Classification (1)
- Conformational landscapes (1)
- Core-Shell (1)
- Drug–target binding kinetics (1)
- Electrocardiogram (1)
- Electrophysiology (1)
- Encoder–decoder (1)
- FFAR4 (1)
- Generative model (1)
- Generative pre-trained transformer (1)
- Heat shock protein 90 (HSP90) (1)
- Hippocampal brain slices (1)
- Hollow Core (1)
- Methionine (1)
- Molecular docking (1)
- Nanogel (1)
- Publication
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- Mathematics, Physics, and Computer Science Faculty Articles and Research (4)
- Biology, Chemistry, and Environmental Sciences Faculty Articles and Research (3)
- Engineering Faculty Articles and Research (1)
- Library Presentations, Posters, and Audiovisual Materials (1)
- Pharmacy Faculty Articles and Research (1)
Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Making The Most Of Artificial Intelligence And Large Language Models: A Novel Approach For Book Recommendation And Discovery In Medical Libraries, Ivan Portillo, David Carson
Making The Most Of Artificial Intelligence And Large Language Models: A Novel Approach For Book Recommendation And Discovery In Medical Libraries, Ivan Portillo, David Carson
Library Presentations, Posters, and Audiovisual Materials
This poster presentation evaluates the use of Artificial Intelligence and large language models (LLMs) to assist health science libraries in recommending and discovering book titles as part of their collection development. Using pre-determined prompts, the researchers evaluated ChatGPT 4.0, Bing Chat, and Google Bard as recommender systems for book discovery and ranking existing titles.
Exploring Binding Pockets In The Conformational States Of The Sars-Cov-2 Spike Trimers For The Screening Of Allosteric Inhibitors Using Molecular Simulations And Ensemble-Based Ligand Docking, Grace Gupta, Gennady M. Verkhivker
Exploring Binding Pockets In The Conformational States Of The Sars-Cov-2 Spike Trimers For The Screening Of Allosteric Inhibitors Using Molecular Simulations And Ensemble-Based Ligand Docking, Grace Gupta, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and …
Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam
Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam
Student Scholar Symposium Abstracts and Posters
Nanogels have emerged as a notably safer and more effective means for drug delivery, primarily due to their adjustable drug-loading capabilities. Hollow-core nanoparticles offer some unique properties that are desirable for drug delivery applications. Initially, silica core nanoparticles were synthesized using the Stöber process at different temperatures where Tetraethoxysilane (TEOS) undergoes hydrolysis in the presence of ethanol and then a condensation reaction to form silica nanoparticles. Scanning Electron Microscopy (SEM) and Optical Microscopy (OM) analysis revealed that the size of silica core particles varied with the synthesis temperature (300 nm at 30°C to 150 at 60°C). The core silica particles …
Predicting Ffar4 Agonists Using Structure-Based Machine Learning Approach Based On Molecular Fingerprints, Zaid Anis Sherwani, Syeda Sumayya Tariq, Mamona Mushtaq, Ali Raza Siddiqui, Mohammad Nur-E-Alam, Aftab Ahmed, Zaheer Ul-Haq
Predicting Ffar4 Agonists Using Structure-Based Machine Learning Approach Based On Molecular Fingerprints, Zaid Anis Sherwani, Syeda Sumayya Tariq, Mamona Mushtaq, Ali Raza Siddiqui, Mohammad Nur-E-Alam, Aftab Ahmed, Zaheer Ul-Haq
Pharmacy Faculty Articles and Research
Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intracellular signaling pathways that regulate various physiological processes. FFAR4 agonists are associated with enhancing insulin release and mitigating the atherogenic, obesogenic, pro-carcinogenic, and pro-diabetogenic effects, normally associated with the free fatty acids bound to FFAR4. In this research, molecular structure-based machine-learning techniques were employed to evaluate compounds as potential agonists for FFAR4. Molecular structures were encoded into bit arrays, serving as molecular fingerprints, which were subsequently analyzed using the Bayesian network algorithm to identify patterns for screening the data. The shortlisted hits obtained via machine learning protocols …
Ultrasoft Platelet-Like Particles Stop Bleeding In Rodent And Porcine Models Of Trauma, Kimberly Nellenbach, Emily Mihalko, Seema Nandi, Drew W. Koch, Jagathpala Shetty, Leandra Moretti, Jennifer Sollinger, Nina Moiseiwitsch, Ana Sheridan, Sanika Pandit, Maureane Hoffman, Lauren V. Schnabel, L. Andrew Lyon, Thomas H. Barker, Ashley C. Brown
Ultrasoft Platelet-Like Particles Stop Bleeding In Rodent And Porcine Models Of Trauma, Kimberly Nellenbach, Emily Mihalko, Seema Nandi, Drew W. Koch, Jagathpala Shetty, Leandra Moretti, Jennifer Sollinger, Nina Moiseiwitsch, Ana Sheridan, Sanika Pandit, Maureane Hoffman, Lauren V. Schnabel, L. Andrew Lyon, Thomas H. Barker, Ashley C. Brown
Engineering Faculty Articles and Research
Uncontrolled bleeding after trauma represents a substantial clinical problem. The current standard of care to treat bleeding after trauma is transfusion of blood products including platelets; however, donated platelets have a short shelf life, are in limited supply, and carry immunogenicity and contamination risks. Consequently, there is a critical need to develop hemostatic platelet alternatives. To this end, we developed synthetic platelet-like particles (PLPs), formulated by functionalizing highly deformable microgel particles composed of ultralow cross-linked poly (N-isopropylacrylamide) with fibrin-binding ligands. The fibrin-binding ligand was designed to target to wound sites, and the cross-linking of fibrin polymers was designed …
Apigenin Alleviates Autistic-Like Stereotyped Repetitive Behaviors And Mitigates Brain Oxidative Stress In Mice, Petrilla Jayaprakash, Dmytro Isaev, Keun-Hang Susan Yang, Rami Beiram, Murat Oz, Bassem Sadek
Apigenin Alleviates Autistic-Like Stereotyped Repetitive Behaviors And Mitigates Brain Oxidative Stress In Mice, Petrilla Jayaprakash, Dmytro Isaev, Keun-Hang Susan Yang, Rami Beiram, Murat Oz, Bassem Sadek
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Studying the involvement of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in neuropsychiatric brain disorders such as autism spectrum disorder (ASD) has gained a growing interest. The flavonoid apigenin (APG) has been confirmed in its pharmacological action as a positive allosteric modulator of α7-nAChRs. However, there is no research describing the pharmacological potential of APG in ASD. The aim of this study was to evaluate the effects of the subchronic systemic treatment of APG (10–30 mg/kg) on ASD-like repetitive and compulsive-like behaviors and oxidative stress status in the hippocampus and cerebellum in BTBR mice, utilizing the reference drug aripiprazole (ARP, 1 …
Cardiogpt: An Ecg Interpretation Generation Model, Guohua Fu, Jianwei Zheng, Islam Abudayyeh, Chizobam Ani, Cyril Rakovski, Louis Ehwerhemuepha, Hongxia Lu, Yongjuan Guo, Shenglin Liu, Huimin Chu, Bing Yang
Cardiogpt: An Ecg Interpretation Generation Model, Guohua Fu, Jianwei Zheng, Islam Abudayyeh, Chizobam Ani, Cyril Rakovski, Louis Ehwerhemuepha, Hongxia Lu, Yongjuan Guo, Shenglin Liu, Huimin Chu, Bing Yang
Mathematics, Physics, and Computer Science Faculty Articles and Research
Numerous supervised learning models aimed at classifying 12-lead electrocardiograms into different groups have shown impressive performance by utilizing deep learning algorithms. However, few studies are dedicated to applying the Generative Pre-trained Transformer (GPT) model in interpreting electrocardiogram (ECG) using natural language. Thus, we are pioneering the exploration of this uncharted territory by employing the CardioGPT model to tackle this challenge. We used a dataset of ECGs (standard 10s, 12-channel format) from adult patients, with 60 distinct rhythms or conduction abnormalities annotated by board-certified, actively practicing cardiologists. The ECGs were collected from The First Affiliated Hospital of Ningbo University and Shanghai …
Accurate Characterization Of Binding Kinetics And Allosteric Mechanisms For The Hsp90 Chaperone Inhibitors Using Ai-Augmented Integrative Biophysical Studies, Chao Xu, Xianglei Zhang, Lianghao Zhao, Gennady M. Verkhivker, Fang Bai
Accurate Characterization Of Binding Kinetics And Allosteric Mechanisms For The Hsp90 Chaperone Inhibitors Using Ai-Augmented Integrative Biophysical Studies, Chao Xu, Xianglei Zhang, Lianghao Zhao, Gennady M. Verkhivker, Fang Bai
Mathematics, Physics, and Computer Science Faculty Articles and Research
The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure–kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate …
Methionyl-Trna Synthetase Synthetic And Proofreading Activities Are Determinants Of Antibiotic Persistence, Whitney N. Wood, Miguel Angel Rubio, Lorenzo Eugenio Leiva, Gregory J. Phillips, Michael Ibba
Methionyl-Trna Synthetase Synthetic And Proofreading Activities Are Determinants Of Antibiotic Persistence, Whitney N. Wood, Miguel Angel Rubio, Lorenzo Eugenio Leiva, Gregory J. Phillips, Michael Ibba
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Bacterial antibiotic persistence is a phenomenon where bacteria are exposed to an antibiotic and the majority of the population dies while a small subset enters a low metabolic, persistent, state and are able to survive. Once the antibiotic is removed the persistent population can resuscitate and continue growing. Several different molecular mechanisms and pathways have been implicated in this phenomenon. A common mechanism that may underly bacterial antibiotic persistence is perturbations in protein synthesis. To investigate this mechanism, we characterized four distinct metG mutants for their ability to increase antibiotic persistence. Two metG mutants encode changes near the catalytic site …
Β-Sheets Mediate The Conformational Change And Allosteric Signal Transmission Between The Aslov2 Termini, Sian Xiao, Mayar Terek Ibrahim, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao
Β-Sheets Mediate The Conformational Change And Allosteric Signal Transmission Between The Aslov2 Termini, Sian Xiao, Mayar Terek Ibrahim, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao
Mathematics, Physics, and Computer Science Faculty Articles and Research
Avena sativa phototropin 1 light-oxygen-voltage 2 domain (AsLOV2) is a model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change begins with the unfolding of the N-terminal A'α helix in the dark state followed by the unfolding of the C-terminal Jα helix. The light state is characterized by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets are identified as crucial components for mediating allosteric signal transmission between the two termini. Through combined experimental and computational investigations, the Hβ …
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …