Determination of the Potential of Drug Candidates to Cause Severe Skin Disorders Using Computational Modeling

2013 ◽  
Vol 32 (3) ◽  
pp. 303-312
Author(s):  
Yuye He ◽  
Frederica Hui Ting Chong ◽  
Junianti Lim ◽  
Rina Jia Tien Lee ◽  
Chun Wei Yap
Keyword(s):  
Computational Modeling ◽  
Skin Disorders ◽  
Drug Candidates

scholarly journals Computational modeling of distribution coefficients and their correlations with pharmacokinetic properties of 17α-picolyl and 17(E)-picolinylidene androstane derivatives

2019 ◽  
pp. 123-133
Author(s):  
Strahinja Kovacevic ◽  
Milica Karadzic-Banjac ◽  
Sanja Podunavac-Kuzmanovic ◽  
Jovana Ajdukovic
Keyword(s):  
Computational Modeling ◽  
Ph Value ◽  
Living Organism ◽  
Distribution Coefficients ◽  
Skin Permeability ◽  
Anticancer Activities ◽  
Drug Candidates ◽  
Brain Barrier Permeability ◽  
Androstane Derivatives

The present study describes the computational modeling of distribution coefficient (logD) of 17?-picolyl and 17(E)-picolinylidene androstane derivatives, as a group of compounds with significant anticancer activities. The determination of logD is practically important for estimation and prediction of pharmacokinetic and pharmacodynamic behavior of compounds in a living organism and it is related to blood-brain barrier permeability, skin permeability, gastrointestinal absorption, binding to plasma proteins, etc. These features are crucial for the determination of potential drug candidates as well. The results presented in this study include determination of pH versus logD profiles, pH versus molecular charge profiles and determination of isoelectric point of eleven 17?- picolyl androstane derivatives and thirteen 17(E)-picolinylidene androstane derivatives. Since the pH of the organism differs depending on the organ (for example, the pH of the blood is significantly different from the pH of the stomach), these profiles are significant because they indicate in what form the molecule will exist and how it will be distributed between different phases at certain pH value. The influence of tautomerization and resonance was taken into account during the modeling of logD parameters. Eventually, the correlations between logD values and specific absorption, distribution, metabolism, and excretion (ADME) properties, such as human intestinal absorption (HIA) and permeability of heterogeneous human epithelial colorectal adenocarcinoma cells (Caco-2), were determined.

scholarly journals An Empirical Biomarker-based Calculator for Autosomal Recessive Polycystic Kidney Disease The Nieto-Narayan Formula

2016 ◽  
Author(s):  
Jake A Nieto ◽  
Michael A Yamin ◽  
Itzhak D. Goldberg ◽  
Prakash Narayan
Keyword(s):  
Clinical Trials ◽  
Kidney Disease ◽  
Polycystic Kidney Disease ◽  
Imaging Modality ◽  
Pediatric Population ◽  
Polycystic Kidney ◽  
Drug Candidates ◽  
Serial Determination ◽  
Stage Renal Disease

Autosomal polycystic kidney disease (ARPKD) is associated with progressive enlargement of the kidneys fuelled by the formation and expansion of fluid-filled cysts. The disease is congenital and children that do not succumb to it during the neonatal period will, by age 10 years, more often than not, require nephrectomy+renal replacement therapy for management of both pain and renal insufficiency. Since increasing cystic index (CI; percent of kidney occupied by cysts) drives both renal expansion and organ dysfunction, management of these patients, including decisions such as elective nephrectomy and prioritization on the transplant waitlist, could clearly benefit from serial determination of CI. So also, clinical trials in ARPKD evaluating efficacy of novel drug candidates could benefit from serial determination of CI. Although ultrasound is currently the imaging modality of choice for diagnosis of ARPKD, its utilization for assessing disease progression is highly limited. Magnetic resonance imaging or computed tomography, although more reliable for determination of CI, are expensive, time-consuming and somewhat impractical in the pediatric population. Using a well-established mammalian model of ARPKD, we undertook a big data-like analysis of minimally- or non-invasive serum and urine biomarkers of renal injury/dysfunction to derive a family of equations for estimating CI. We then applied a signal averaging protocol to distil these equations to a single empirical formula for calculation of CI. Such a formula will eventually find use in identifying and monitoring patients at high risk for progressing to end-stage renal disease and aid in the conduct of clinical trials.

scholarly journals Computational determination of hERG-related cardiotoxicity of drug candidates

2019 ◽  
Vol 20 (S10) ◽  
Author(s):  
Hyang-Mi Lee ◽  
Myeong-Sang Yu ◽  
Sayada Reemsha Kazmi ◽  
Seong Yun Oh ◽  
Ki-Hyeong Rhee ◽  
...  
Keyword(s):  
Drug Candidates

Robust Electrophysiological Assays using Solid Supported Membranes: the Organic Cation Transporter OCT2

2011 ◽  
Vol 64 (1) ◽  
pp. 31 ◽  
Author(s):  
Olga Gaiko ◽  
Ingo Janausch ◽  
Sven Geibel ◽  
Henning Vollert ◽  
Petra Arndt ◽  
...  
Keyword(s):  
Cell Lines ◽  
Organic Cation ◽  
Chinese Hamster ◽  
Organic Cation Transporter ◽  
Supported Membranes ◽  
Cho Cell ◽  
Drug Candidates ◽  
Substrate Affinities ◽  
Solid Supported Membranes

An electrophysiological assay platform based on solid supported membranes (SSM) for the organic cation transporter (OCT) is presented. Stable Chinese hamster ovary (CHO) cell lines overexpressing the human (hOCT2) and rat transporters (rOCT2) were generated and validated. Membrane preparations from the cell lines were investigated using SSM-based electrophysiology. Baculovirus transfected insect cells (HighFive and Mimic Sf9) were also tested with the same assay but yielded less than optimal results. The assays were validated by the determination of substrate affinities and inhibition by standard inhibitors. The study demonstrates the suitability of the SSM-based electrophysiological OCT assay for rapid and automatic screening of drug candidates.

scholarly journals A Graph-Directed Approach for Creation of a Homology Modeling Library: Application to Venom Structure Prediction

2019 ◽  
Author(s):  
Rachael A Mansbach ◽  
Srirupa Chakraborty ◽  
Timothy Travers ◽  
S. Gnanakaran
Keyword(s):  
Homology Modeling ◽  
Structure Prediction ◽  
Three Dimensional ◽  
Threat Assessment ◽  
Drug Candidates ◽  
The Family ◽  
Template Library ◽  
Therapeutic Leads ◽  
Candidate Identification

Many toxins are short, cysteine-rich peptides that are of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. To perform initial candidate identification for design of a drug impacting a particular receptor or for threat assessment as a harmful toxin, one requires a set of candidate structures of reasonable accuracy with potential for interaction with the target receptor. In this article, we introduce a graph-based algorithm for identifying good extant template structures from a library of evolutionarily-related cysteine-containing sequences for structural determination of target sequences by homology modeling. We employ this approach to study the conotoxins, a set of toxin peptides produced by the family of aquatic cone snails. Currently, of the approximately six thousand known conotoxin sequences, only about three percent have experimentally characterized three-dimensional structures, leading to a serious bottleneck in identifying potential drug candidates. We demonstrate that the conotoxin template library generated by our approach may be employed to perform homology modeling and greatly increase the number of characterized conotoxin structures. We also show how our approach can guide experimental design by identifying and ranking sequences for structural characterization in a similar manner. Overall, we present and validate an approach for venom structure modeling and employ it to expand the library of extant conotoxin structures by almost 300% through homology modeling employing the template library determined in our approach.

scholarly journals A simple method to determine the elimination half-life of drugs displaying noncumulative toxicity

2019 ◽  
Author(s):  
Deepesh Nagarajan ◽  
Preetham Venkatesh ◽  
Chandrani Thakur ◽  
Akshay Datey ◽  
Nagasuma Chandra ◽  
...  
Keyword(s):  
Half Life ◽  
Mass Spectrometric ◽  
Drug Candidate ◽  
Spectrometric Method ◽  
Mass Spectrometric Method ◽  
Simple Method ◽  
Drug Candidates ◽  
Elimination Half ◽  
The Many

ABSTRACTThe pharmacokinetic characterization of a drug, especially the determination of its biological half-life, is an essential step during the early phases of drug development. An adequate half-life is amongst the many properties needed for selecting a drug candidate for clinical trials. Conversely, drug candidates possessing inadequate half-lives may be modified or eliminated from the drug discovery pipeline altogether. Several methods exist for determining the half-lives of drugs, namely HPLC, fluorescence assays, radioassays, radioimmunoassays, and elemental mass spectrometric assays. However, all these techniques are resource and labor-intensive, and cannot be used for the high-throughput half-life determination of hundreds of drug candidates. Here, we describe TOXHL: a simple technique to determine the half-lives of compounds displaying noncumulative toxicity. To calculate the half life, TOXHL only relies on the survival outcomes of three experiments performed on an animal model: an acute toxicity experiment, a cumulative toxicity experiment, and a multi-dose experiment at different dosing intervals. As a proof of concept, we use TOXHL to determine the peritoneal half-life of Ω76, an antimicrobial peptide. The half-life of Ω76 determined by TOXHL is in good agreement with results from a standard mass spectrometric method, validating this approach.

scholarly journals Validated Determination of NRG1 Ig-like Domain Structure by Mass Spectrometry Coupled with Computational Modeling

2021 ◽  
Author(s):  
Niloofar Abolhasani Khaje ◽  
Alexander Eletsky ◽  
Sarah E. Biehn ◽  
Charles K. Mobley ◽  
Monique J. Rogals ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Computational Modeling ◽  
Solvent Exposure ◽  
Uncharacterized Protein ◽  
Single Experiment ◽  
Protein Footprinting ◽  
Hydroxyl Radical Protein Footprinting ◽  
Unknown Structure

High resolution hydroxyl radical protein footprinting (HR-HRPF) is a mass spectrometry-based method that measures the solvent exposure of multiple amino acids in a single experiment, offering constraints for experimentally-informed computational modeling. HR-HRPF-based modeling has previously been used to accurately model the structure of proteins of known structure, but the technique has never been used to determine the structure of a protein of unknown structure leaving questions of unintentional bias and applicability to unknown structures unresolved. Here, we present the use of HR-HRPF-based modeling to determine the structure of the Ig-like domain of NRG1, a protein with no close homolog of known structure. Independent determination of the protein structure by both HR-HRPF-based modeling and heteronuclear NMR was carried out, with results compared only after both processes were complete. The HR-HRPF-based model was highly similar to the lowest energy NMR model, with a backbone RMSD of 1.6 Å. To our knowledge, this is the first use of HR-HRPF-based modeling to determine a previously uncharacterized protein structure.

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