Medicine and Health Sciences Commons^™

Exploring The Eating Disorder Examination Questionnaire, Clinical Impairment Assessment, And Autism Quotient To Identify Eating Disorder Vulnerability: A Cluster Analysis, Natalia Stewart Rosenfield, Erik Linstead

Engineering Faculty Articles and Research

Eating disorders are very complicated and many factors play a role in their manifestation. Furthermore, due to the variability in diagnosis and symptoms, treatment for an eating disorder is unique to the individual. As a result, there are numerous assessment tools available, which range from brief survey questionnaires to in-depth interviews conducted by a professional. One of the many benefits to using machine learning is that it offers new insight into datasets that researchers may not previously have, particularly when compared to traditional statistical methods. The aim of this paper was to employ k-means clustering to explore the Eating Disorder …

Capsaicin Is A Negative Allosteric Modulator Of The 5-Ht3 Receptor, Eslam El Nebrisi, Tatiana Prytkova, Dietrich Ernst Lorke, Luke Howarth, Asma Hassan Alzaabi, Keun-Hang Susan Yang, Frank Christopher Howarth, Murat Oz

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In this study, effects of capsaicin, an active ingredient of the capsicum plant, were investigated on human 5-hydroxytryptamine type 3 (5-HT₃) receptors. Capsaicin reversibly inhibited serotonin (5-HT)-induced currents recorded by two-electrode voltage clamp method in Xenopus oocytes. The inhibition was time- and concentration-dependent with an IC₅₀ = 62 μM. The effect of capsaicin was not altered in the presence of capsazepine, and by intracellular BAPTA injections or trans-membrane potential changes. In radio-ligand binding studies, capsaicin did not change the specific binding of the 5-HT₃ antagonist [³H]GR65630, indicating that it is a noncompetitive inhibitor of …

A Multicenter Mixed-Effects Model For Inference And Prediction Of 72-H Return Visits To The Emergency Department For Adult Patients With Trauma-Related Diagnoses, Ehsan Yaghmaei, Louis Ehwerhemuepha, William Feaster, David Gibbs, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Objective

Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classification algorithms, and we use the best performing approach to identify novel risk factors of ED return visits.

Methods

We analyzed 3.2 million ED encounters with at least one diagnosis under “injury, poisoning and certain other consequences of external causes” and “external causes of morbidity.” These encounters included patients 18 years or older from across 128 emergency room facilities in the …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

The Effects Of Zoledronate And Sleep Deprivation On The Distal Femur Trabecular Thickness Of Ovariectomized Rats: Application Of Different Statistical Methods, Erin Nolte

Student Scholar Symposium Abstracts and Posters

Osteoporosis is a disease that causes the degradation of bone, leading to an increased risk of fracture. 1 in 3 women over the age of 50 will be affected by Osteoporosis. This study aims to understand how bone is affected by sleep deprivation in estrogen-deficient rats, and how Zoledronate might negate the inimical effects of sleep deprivation on bone. As bone mineral density (BMD) is a crude evaluation of the architectural changes seen in Osteoporosis, trabecular thickness may serve as a better single evaluation of bone health. 31 Wistar female rats were ovariectomized and separated into 4 random groups. The …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

A 12-Lead Ecg Database To Identify Origins Of Idiopathic Ventricular Arrhythmia Containing 334 Patients, Jianwei Zhang, Guohua Fu, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Cardiac catheter ablation has shown the effectiveness of treating the idiopathic premature ventricular complex and ventricular tachycardia. As the most important prerequisite for successful therapy, criteria based on analysis of 12-lead ECGs are employed to reliably speculate the locations of idiopathic ventricular arrhythmia before a subsequent catheter ablation procedure. Among these possible locations, right ventricular outflow tract and left outflow tract are the major ones. We created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular …

A Nwb-Based Dataset And Processing Pipeline Of Human Single-Neuron Activity During A Declarative Memory Task, N. Chandravadia, D. Liang, A. G. P. Schjetnan, A. Carlson, M. Faraut, J. M. Chung, C. M. Reed, B. Dichter, Uri Maoz, S. K. Kalia, T. A. Valiante, A. N. Mamelak, U. Rutishauser

Psychology Faculty Articles and Research

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import …

Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead …

Image Restoration Using Automatic Damaged Regions Detection And Machine Learning-Based Inpainting Technique, Chloe Martin-King

Computational and Data Sciences (PhD) Dissertations

In this dissertation we propose two novel image restoration schemes. The first pertains to automatic detection of damaged regions in old photographs and digital images of cracked paintings. In cases when inpainting mask generation cannot be completely automatic, our detection algorithm facilitates precise mask creation, particularly useful for images containing damage that is tedious to annotate or difficult to geometrically define. The main contribution of this dissertation is the development and utilization of a new inpainting technique, region hiding, to repair a single image by training a convolutional neural network on various transformations of that image. Region hiding is also …

Evaluation Of Tumor Necrosis Factor Alpha In Sleep-Deprived Menopausal- Induced Rats And The Impact On Bone Health, Nicole Ellsworth, Dwight Curry Iii, Cj Deleon, Frank Frisch

Student Scholar Symposium Abstracts and Posters

Post-menopausal osteoporosis as a consequence of estrogen depletion is a growing concern for women in the United States. As more women take on executive positions and experience sleep deprivation, there is the potential for up regulation of pro-inflammatory cytokines, such as tumor necrosis factor alpha. It follows that the homeostatic imbalance of osteoclastic and osteoblastic activity leads to a greater risk of disease. Bisphosphonates generally, and Zolendronate specifically works by decreasing the number of osteoclasts. This current study investigated the impact of Zolendronate on the concentrations of tumor necrosis factor alpha-type (TNFɑ) in 32 ovariectomized Wistar rats. Throughout a five …

Improving Medication Information Presentation Through Interactive Visualization In Mobile Apps: Human Factors Design, Don Roosan, Yan Li, Anandi Law, Huy Truong, Mazharul Karim, Jay Chok, Moom Roosan

Pharmacy Faculty Articles and Research

Background: Despite the detailed patient package inserts (PPIs) with prescription drugs that communicate crucial information about safety, there is a critical gap between patient understanding and the knowledge presented. As a result, patients may suffer from adverse events. We propose using human factors design methodologies such as hierarchical task analysis (HTA) and interactive visualization to bridge this gap. We hypothesize that an innovative mobile app employing human factors design with an interactive visualization can deliver PPI information aligned with patients’ information processing heuristics. Such an app may help patients gain an improved overall knowledge of medications.

Objective: The …

Establishing Computational Approaches Towards Identifying Malarial Allosteric Modulators: A Case Study Of Plasmodium Falciparum Hsp70s, Arnold Amusengeri, Lindy Astl, Kevin Lobb, Gennady M. Verkhivker, Özlem Tastan Bishop

Mathematics, Physics, and Computer Science Faculty Articles and Research

Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric …

Coccidioidomycosis: Medical And Spatio-Temporal Perspectives, Nikias Sarafoglou, Rafael Laniado-Laborin, Menas Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

Coccidioidomycosis (CM) is a disease of major public health importance due to the challenges in its diagnosis and treatment. To understand CM requires the attributes of a multidisciplinary network analysis to appreciate the complexity of the medical, the environmental and the social issues involved: public health, public policy, geology, atmospheric science, agronomy, social sciences and finally humanities, all which provide insight into this population transformation.

In section 1 of this paper, we describe the CM-epidemiology, the clinical features, the diagnosis and finally the treatment.

In section 2, we highlight the most important contributions and controversies in the history of the …

Identifying Depression In The National Health And Nutrition Examination Survey Data Using A Deep Learning Algorithm, Jihoon Oh, Kyongsik Yun, Uri Maoz, Tae-Suk Kim, Jeong-Ho Chae

Psychology Faculty Articles and Research

Background

As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.

Methods

Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.

Results

A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) …

Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …

Using Green Emitting Ph-Responsive Nanogels To Report Environmental Changes Within Hydrogels: A Nanoprobe For Versatile Sensing, Mingning Zhu, Dongdong Lu, Shanglin Wu, Qing Lian, Wenkai Wang, L. Andrew Lyon, Weiguang Wang, Paulo Bártolo, Brian R. Saunders

Engineering Faculty Articles and Research

Remotely reporting the local environment within hydrogels using inexpensive laboratory techniques has excellent potential to improve our understanding of the nanometer-scale changes that cause macroscopic swelling or deswelling. Whilst photoluminescence (PL) spectroscopy is a popular method for such studies this approach commonly requires bespoke and time-consuming synthesis to attach fluorophores which may leave toxic residues. A promising and more versatile alternative is to use a pre-formed nanogel probe that contains a donor/acceptor pair and then “dope” that into the gel during gel assembly. Here, we introduce green-emitting methacrylic acid-based nanogel probe particles and use them to report the local environment …

A Virtual Reality System For Practicing Conversation Skills For Children With Autism, Natalia Stewart Rosenfield, Kathleen Lamkin, Jennifer Re, Kendra Day, Louanne E. Boyd, Erik J. Linstead

Engineering Faculty Articles and Research

We describe a virtual reality environment, Bob’s Fish Shop, which provides a system where users diagnosed with Autism Spectrum Disorder (ASD) can practice social interactions in a safe and controlled environment. A case study is presented which suggests such an environment can provide the opportunity for users to build the skills necessary to carry out a conversation without the fear of negative social consequences present in the physical world. Through the repetition and analysis of these virtual interactions, users can improve social and conversational understanding.

Ecological Determinants Of Respiratory Health: Examining Associations Between Asthma Emergency Department Visits, Diesel Particulate Matter, And Public Parks And Open Space In Los Angeles, California, Jason A. Douglas, Reginald S. Archer, Serena E. Alexander

Health Sciences and Kinesiology Faculty Articles

Los Angeles County (LAC) low-income communities of color experience uneven asthma rates, evidenced by asthma emergency department visits (AEDV). This has partly been attributed to inequitable exposure to diesel particulate matter (DPM). Promisingly, public parks and open space (PPOS) contribute to DPM mitigation. However, low-income communities of color with limited access to PPOS may be deprived of associated public health benefits. Therefore, this novel study investigates the AEDV, DPM, PPOS nexus to address this public health dilemma and inform public policy in at-risk communities. Optimized Hotspot Analysis was used to examine geographic clustering of AEDVs, DPM, and PPOS at the …

Purification And Characterization Of A Nonspecific Lipid Transfer Protein 1 (Nsltp1) From Ajwain (Trachyspermum Ammi) Seeds, Meshal Nazeer, Humera Waheed, Maria Saeed, Saman Yousuf Ali, M. Iqbal Choudhary, Zaheer Ul-Haq, Aftab Ahmed

Pharmacy Faculty Articles and Research

Ajwain (Trachyspermum ammi) belongs to the family Umbelliferae, is commonly used in traditional, and folk medicine due to its carminative, stimulant, antiseptic, diuretic, antihypertensive, and hepatoprotective activities. Non-specific lipid transfer proteins (nsLTPs) reported from various plants are known to be involved in transferring lipids between membranes and in plants defense response. Here, we describe the complete primary structure of a monomeric non-specific lipid transfer protein 1 (nsLTP1), with molecular weight of 9.66 kDa, from ajwain seeds. The nsLTP1 has been purified by combination of chromatographic techniques, and further characterized by mass spectrometry, and Edman degradation. The ajwain nsLTP1 …

Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead

Engineering Faculty Articles and Research

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …

Allosteric Mechanism Of The Circadian Protein Vivid Resolved Through Markov State Model And Machine Learning Analysis, Hongyu Zhou, Zheng Dong, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an …

Synthesis, Biological Evaluation And Molecular Modeling Studies Of Novel Chromone/Aza-Chromone Fused Α-Aminophosphonates As Src Kinase Inhibitors, S. Bapat, N. Viswanadh, M. Mujahid, Amir Nasrolahi Shirazi, Rakesh Tiwari, Keykavous Parang, M. Karthikeyan, M. Muthukrishnan, Renu Vyas

Pharmacy Faculty Articles and Research

A series of novel chromone/aza-chromone fused α-aminophosphonate derivatives were synthesized in good yields using silica chloride as the catalyst. All the synthesized compounds were tested for their c-Src kinase inhibitory activity. Aza-chromone compound showed Src kinase inhibition with an IC50 value of 15.8 µM. The compounds were subjected to molecular docking and dynamics simulations to study the atomic level interactions with an unphosphorylated proto-oncogenic tyrosine protein kinase Src (PDB code 1Y57) as well as phosphorylated tyrosine protein kinase Src (PDB code 2H8H). Docking and molecular dynamic results revealed phosphorylated Src tyrosine kinase protein better results than unphosphorylated tyrosine Src kinase …

Leveling The Playing Field: Supporting Neurodiversity Via Virtual Realities, Louanne E. Boyd, Kendra Day, Natalia Stewart, Kaitlyn Abdo, Kathleen Lamkin, Erik J. Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

Neurodiversity is a term that encapsulates the diverse expression of human neurology. By thinking in broad terms about neurological development, we can become focused on delivering a diverse set of design features to meet the needs of the human condition. In this work, we move toward developing virtual environments that support variations in sensory processing. If we understand that people have differences in sensory perception that result in their own unique sensory traits, many of which are clustered by diagnostic labels such as Autism Spectrum Disorder (ASD), Sensory Processing Disorder, Attention-Deficit/Hyperactivity Disorder, Rett syndrome, dyslexia, and so on, then we …

The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch

Mathematics, Physics, and Computer Science Faculty Articles and Research

Osteoporosis is the most common metabolic bone disease and goes largely undiagnosed throughout the world, due to the inaccessibility of DXA machines. Multivariate analyses of serum bone turnover markers were evaluated in 226 Orange County, California, residents with the intent to determine if serum osteocalcin and serum pyridinoline cross-links could be used to detect the onset of osteoporosis as effectively as a DXA scan. Descriptive analyses of the demographic and lab characteristics of the participants were performed through frequency, means and standard deviation estimations. We implemented logistic regression modeling to find the best classification algorithm for osteoporosis. All calculations and …

Isolation Of Rna From A Mixture And Its Detection By Utilizing A Microgel-Based Optical Device, Molla R. Islam, Shakiba Azimi, Faranak Teimoory, Glen Loppnow, Michael J. Serpe

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In this investigation, we show that RNA can be separated from a solution containing DNA and RNA and the isolated RNA can be detected using poly (N-isopropylacrylamide-co-N-(3-aminopropyl) methacrylamide hydrochloride) microgel-based optical devices (etalons). The isolation of RNA was accomplished by using hairpin-functionalized magnetic beads (MMPDNA) and differential melting, based on the fact that the DNA–RNA hybrid duplex is stronger (i.e., high melting temperature) than the DNA–DNA duplex (i.e., low melting temperature). By performing concurrent etalon sensing and fluorescent studies, we found that the MMPDNA combined with differential melting was capable of selectively separating RNA from DNA. This selective separation and …

1h And 13c Nmr Assignments For (N-Methyl)-(−)-(Α)-Isosparteinium Iodide And (N-Methyl)-(−)-Sparteinium Iodide, Kavoos Kolahdouzan, O. Maduka Ogba, Daniel J. O'Leary

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

(‒)-Sparteine (1) and (–)-(α)-isosparteine (2) are members of the lupine alkaloid family.^[1-2] Sparteine has found extensive use in asymmetric organic transformations, including lithiations^[3] and Pd-catalyzed oxidations.^[4-7] (α)-Isosparteine, which can be made from sparteine, has been utilized as a chiral ligand for a limited number of stereoselective reactions.^[8-9] The two compounds differ in that 1 displays an exo-endo arrangement of the bridgehead hydrogens at C-11 and C-6, respectively, while 2 retains an exo-exo arrangement of these atoms (Figure 1). This study is focused on assigning 1H chemical shifts and coupling constants and 13C chemical shifts for N-methyl …

Astromimetics: The Dawn Of A New Era For (Bio)Materials Science?, Vuk Uskoković, Victoria M. Wu

Pharmacy Faculty Articles and Research

Composite, multifunctional fine particles are likely to be at the frontier of materials science in the foreseeable future. Here we present a submicron composite particle that mimics the stratified structure of the Earth by having a zero-valent iron core, a silicate/silicide mantle, and a thin carbonaceous crust resembling the biosphere and its biotic deposits. Particles were formulated in a stable colloidal form and made to interact with various types of healthy and cancer cells in vitro. A selective anticancer activity was observed, promising from the point of view of the intended use of the particles for tumor targeting across the …

Microgel Core/Shell Architectures As Targeted Agents For Fibrinolysis, Purva Kodlekere, L. Andrew Lyon

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

We demonstrate the utility of microgel core/shell structures conjugated to fibrin-specific peptides as fibrinolytic agents. Poly(N-isopropylmethacrylamide) (pNIPMAm) based microgels conjugated to the peptide GPRPFPAC (GPRP) were observed to bring about fibrin clot erosion, merely through exploitation of the dynamic nature of the clots. These results suggest the potential utility of peptide–microgel hybrids in clot disruption and clotting modulation.

Dissecting Structure-Encoded Determinants Of Allosteric Cross-Talk Between Post-Translational Modification Sites In The Hsp90 Chaperones, Gabrielle Stetz, Amanda Tse, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Post-translational modifications (PTMs) represent an important regulatory instrument that modulates structure, dynamics and function of proteins. The large number of PTM sites in the Hsp90 proteins that are scattered throughout different domains indicated that synchronization of multiple PTMs through a combinatorial code can be invoked as an important mechanism to orchestrate diverse chaperone functions and recognize multiple client proteins. In this study, we have combined structural and coevolutionary analysis with molecular simulations and perturbation response scanning analysis of the Hsp90 structures to characterize functional role of PTM sites in allosteric regulation. The results reveal a small group of conserved PTMs …