A5050450017- Computational Drug Discovery Methods
- Bioinformatics and Genomic Networks
- Genetic Associations and Epidemiology
- Genomics and Rare Diseases
- Alzheimer's disease research and treatments
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Metabolomics and Mass Spectrometry Studies
- Neuroscience and Neuropharmacology Research
- Receptor Mechanisms and Signaling
- Analytical Chemistry and Chromatography
- Machine Learning in Materials Science
- Nutrition, Genetics, and Disease
- Glaucoma and retinal disorders
- Parasites and Host Interactions
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Nicotinic Acetylcholine Receptors Study
- Cytokine Signaling Pathways and Interactions
- Cholesterol and Lipid Metabolism
- Helicobacter pylori-related gastroenterology studies
- Fungal and yeast genetics research
- Genomics and Chromatin Dynamics
- Pharmacovigilance and Adverse Drug Reactions
- Pharmacogenetics and Drug Metabolism
- Systemic Lupus Erythematosus Research
Case Western Reserve University
2015-2024
Vanderbilt University
2009-2023
University School
2015-2018
Dr. John T. Macdonald Foundation
2017
University of Miami
2017
Genetic and environmental factors that increase the risk of late-onset Alzheimer disease are now well recognized but cause variable progression rates phenotypes sporadic Alzheimer's is largely unknown. We aimed to investigate relationship between diverse structural assemblies amyloid-β clinical decline in disease. Using novel biophysical methods, we analysed levels, particle size, conformational characteristics posterior cingulate cortex, hippocampus cerebellum 48 cases with distinctly...
With the rapidly increasing availability of High-Throughput Screening (HTS) data in public domain, such as PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have potential to accelerate and reduce cost probe development efforts academia. We assemble nine sets from realistic HTS campaigns representing major families target proteins benchmarking LB-CADD methods. Each set is domain through carefully collated confirmation screens validating active compounds....
Selective potentiators of glutamate response at metabotropic receptor subtype 5 (mGluR5) have exciting potential for the development novel treatment strategies schizophrenia. A total 1,382 compounds with positive allosteric modulation (PAM) mGluR5 were identified through high-throughput screening (HTS) a diverse library 144,475 substances utilizing functional assay measuring receptor-induced intracellular release calcium. Primary hits tested concentration-dependent activity, and potency data...
The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to joint analysis. Here we bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen centers Alzheimer's Disease Sequencing Project. joint-genotype called variant-called format (VCF) file contains only positions within union kits. VCF was then processed specifically account batch effects arising from use different...
Annotation of genomic variants is an increasingly important and complex part the analysis sequence-based analyses. Computational predictions variant function are routinely incorporated into gene-based analyses rare-variants, though to date most studies use limited information for assessing that often agnostic disease being studied.
<h3>Objective</h3> To identify genetic variation influencing late-onset Alzheimer disease (LOAD), we used a large data set of non-Hispanic white (NHW) extended families multiply-affected by LOAD performing whole genome sequencing (WGS). <h3>Methods</h3> As part the Disease Sequencing Project, WGS were generated for 197 NHW participants from 42 (affected individuals and unaffected, elderly relatives). A two-pronged approach was taken. First, variants prioritized using heterogeneity logarithm...
The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction core BCL functionality, showing how tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined learning. addition, have...
<b><i>Background/Aims:</i></b> The Alzheimer’s Disease Sequencing Project (ADSP) aims to identify novel genes influencing disease (AD). Variants within known cause dementias other than AD have previously been associated with risk. We describe evidence of co-segregation and associations between variants in dementia clinically diagnosed the ADSP. <b><i>Methods:</i></b> summarize properties pathogenic genes, annotated as “pathogenic” ClinVar new...
Availability of high-throughput screening (HTS) data in the public domain offers great potential to foster development ligand-based computer-aided drug discovery (LB-CADD) methods crucial for efforts academia and industry. LB-CADD method depends on high-quality HTS assay data, i.e., datasets that contain both active inactive compounds. These compounds are hits from primary screens have been tested concentration-response experiments where target-specificity has validated through suitable...
Purpose: Sex hormones may be associated with primary open-angle glaucoma (POAG), although the mechanisms are unclear. We previously observed that gene variants involved estrogen metabolism were collectively POAG in women but not men; here we assessed related to testosterone and risk. Methods: used two datasets: one from United States (3853 cases 33,480 controls) another Australia (1155 1992 controls). Both datasets contained densely called genotypes imputed 1000 Genomes reference panel....
Autoimmune diseases represent a significant medical burden affecting up to 5-8% of the U.S.While genetics is known play role, studies common autoimmune are complicated by phenotype heterogeneity, limited sample sizes, and single disease approach. Here we performed targeted genetic association study for cases multiple sclerosis (MS), rheumatoid arthritis (RA), Crohn's (CD) assess which variants contribute individually pleiotropically risk. Joint modeling pathway analysis combining three...
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as active or inactive with respect a specific target system. This paper presents comparison of artificial neural networks (ANN), support vector machines (SVM), decision trees (DT) in an effort identify potentiators metabotropic glutamate receptor 5 (mGluR5), that have potential novel treatments against schizophrenia. When...
Abstract Motivation: We present an update to the pathway enrichment analysis tool ‘Pathway Analysis by Randomization Incorporating Structure (PARIS)’ that determines aggregated association signals generated from genome-wide study results. Pathway-based analyses highlight biological pathways associated with phenotypes. PARIS uses a unique permutation strategy evaluate genomic structure of interrogated pathways, through testing features, thus eliminating many over-testing concerns arising...
Several machine learning techniques were evaluated for the prediction of logP. The algorithms used include artificial neural networks (ANN), support vector machines (SVM) with extension regression, and kappa nearest neighbor (k-NN). Molecules described using optimized feature sets derived from a series scalar, two- three-dimensional descriptors including 2-D 3-D autocorrelation, radial distribution function. Feature optimization was performed as sequential forward selection. data set...
Stereochemistry is an important determinant of a molecule’s biological activity. Stereoisomers can have different degrees efficacy or even opposing effects when interacting with target protein. molecular property difficult to represent in 2D-QSAR as it inherently three-dimensional phenomenon. A major drawback most proposed descriptors for 3D-QSAR that encode stereochemistry they require heuristic defining all stereocenters and rank-ordering its substituents. Here we propose novel descriptor...
Quantitative structure activity relationship (QSAR) modeling using high-throughput screening (HTS) data is a powerful technique which enables the construction of predictive models. These models are utilized for in silico libraries molecules experimental methods both cost- and time-expensive. Machine learning techniques excel QSAR where between often complex non-linear. As these HTS sets continue to increase number compounds screened, extensive feature selection cross validation becomes...
As part of the G-protein coupled receptor (GPCR) family, metabotropic glutamate (mGlu) receptors play an important role as drug targets cognitive diseases. Selective allosteric modulators mGlu subtype 5 (mGlu5) have potential to alleviate symptoms numerous central nervous system disorders such schizophrenia in a more targeted fashion. Multiple mGlu5 positive (PAMs), 1-(3-fluorophenyl)-N-((3-fluorophenyl)-methylideneamino)-methanimine (DFB), 3-cyano-N-(1,3-diphenyl-1H-pyrazol-5-yl)-benzamide...