scholarly journals MuSyC is a consensus framework that unifies multi-drug synergy metrics for combinatorial drug discovery

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David J. Wooten ◽  
Christian T. Meyer ◽  
Alexander L. R. Lubbock ◽  
Vito Quaranta ◽  
Carlos F. Lopez
Keyword(s):  
Drug Discovery ◽  
Drug Combination ◽  
Mass Action ◽  
Maximal Effect ◽  
Drug Synergy ◽  
Synergistic Interactions ◽  
Combination Treatments ◽  
Hill Slope ◽  
The Hill ◽  
The Relationship

AbstractDrug combination discovery depends on reliable synergy metrics but no consensus exists on the correct synergy criterion to characterize combined interactions. The fragmented state of the field confounds analysis, impedes reproducibility, and delays clinical translation of potential combination treatments. Here we present a mass-action based formalism to quantify synergy. With this formalism, we clarify the relationship between the dominant drug synergy principles, and present a mapping of commonly used frameworks onto a unified synergy landscape. From this, we show how biases emerge due to intrinsic assumptions which hinder their broad applicability and impact the interpretation of synergy in discovery efforts. Specifically, we describe how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact synergy classification in large combination screens, potentially misleading discovery efforts. Thus the proposed formalism can provide a consistent, unbiased interpretation of drug synergy, and accelerate the translatability of synergy studies.

scholarly journals A Consensus Framework Unifies Multi-Drug Synergy Metrics

2019 ◽  
Author(s):  
David J. Wooten ◽  
Christian T. Meyer ◽  
Vito Quaranta ◽  
Carlos Lopez
Keyword(s):  
Drug Combination ◽  
Mass Action ◽  
Maximal Effect ◽  
Drug Synergy ◽  
Synergistic Interactions ◽  
Broad Applicability ◽  
Hill Slope ◽  
The Hill ◽  
The Relationship

AbstractDrug combination discovery depends on reliable synergy metrics; however, no consensus exists on the appropriate synergy model to prioritize lead candidates. The fragmented state of the field confounds analysis, reproducibility, and clinical translation of combinations. Here we present a mass-action based formalism to accurately measure the synergy of drug combinations. In this work, we clarify the relationship between the dominant drug synergy principles and show how biases emerge due to intrinsic assumptions which hinder their broad applicability. We further present a mapping of commonly used frameworks onto a unified synergy landscape, which identifies fundamental issues impacting the interpretation of synergy in discovery efforts. Specifically, we infer how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact the classification of synergy in large combination screens misleading discovery efforts. The proposed approach has potential to accelerate the translatability and reproducibility of drug-synergy studies, by bridging the gap between the curative potential of drug mixtures and the complexity in their study.

scholarly journals COMP-09. A CANCER DRUG ATLAS ENABLES PREDICTION OF PARALLEL DRUG VULNERABILITIES OF GLIOBLASTOMA

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi62-vi63
Author(s):  
Ravi Narayan ◽  
Piet Molenaar ◽  
Fleur Cornelissen ◽  
Tom Wurdinger ◽  
Jan Koster ◽  
...  
Keyword(s):  
Drug Combination ◽  
Drug Response ◽  
Cancer Drug ◽  
Cancer Treatments ◽  
Drug Synergy ◽  
Map Data ◽  
Personalized Cancer ◽  
Synergistic Combinations ◽  
Synergistic Drug Combinations

Abstract Personalized cancer treatments using synergistic combinations of drugs is attractive but proves to be highly challenging. The combinatorial nature of such problems results in an enormous parameter space that cannot be resolved by empirical research, i.e. testing all combinations for all molecularly defined tumors. In addition, effective drug synergy is hard to predict. Here we present an approach to map data of drug-response encyclopedias and represent these as a drug atlas. This atlas consists of a framework of chemotherapeutic responses that represents a drug vulnerability landscape of cancer. Based on data from the literature we found that many synergistic drug combinations show distinct inter therapy responses and drug sensitivities. We confirmed this by performing a drug combination screen against glioblastoma where we used 270 combination experiments. From the identified dual therapies we were able to predict and validate a triple drug synergy which was validated in vivo. This new and generalizable strategy opens the door to unforeseen personalized multidrug combination approaches.

Wind tunnel tests and dynamic analysis of wind-induced response of a transmission tower on a hill

2021 ◽  
pp. 136943322110339
Author(s):  
Jian Guo ◽  
Changliang Xiao ◽  
Jiantao Li
Keyword(s):  
Wind Tunnel ◽  
Wind Field ◽  
Dynamic Responses ◽  
Interactive Effects ◽  
Induced Response ◽  
Transmission Tower ◽  
Structural Dynamic ◽  
Wind Tunnel Tests ◽  
Hill Slope ◽  
The Hill

A hill with a lattice transmission tower presents complex wind field characteristics. The commonly used computational fluid dynamics (CFD) simulations are difficult to analyze the wind resistance and dynamic responses of the transmission tower due to structural complexity. In this study, wind tunnel tests and numerical simulations are conducted to analyze the wind field of the hill and the dynamic responses of the transmission tower built on it. The hill models with different slopes are investigated by wind tunnel tests to measure the wind field characteristics, such as mean speed and turbulence intensity. The study shows that the existence of a transmission tower reduces the wind speed on the leeward slope significantly but has little effect on the windward slope. To study the dynamic behavior of the transmission tower, a hybrid analysis procedure is used by introducing the measured experimental wind information to the finite element tower model established using ANSYS. The effects of hill slope on the maximum displacement response of the tower are studied. The results show that the maximum value of the response is the largest when the hill slope is 25° compared to those when hill slope is 15° and 35°. The results extend the knowledge concerning wind tunnel tests on hills of different terrain and provide a comprehensive understanding of the interactive effects between the hill and existing transmission tower regarding to the wind field characteristics and structural dynamic responses.

Effect of osmotic swelling and shrinkage on Na(+)-K+ pump activity in mammalian cardiac myocytes

1993 ◽  
Vol 265 (5) ◽  
pp. C1201-C1210 ◽  
Author(s):  
D. W. Whalley ◽  
L. C. Hool ◽  
R. E. Ten Eick ◽  
H. H. Rasmussen
Keyword(s):  
Ventricular Myocytes ◽  
Pump Current ◽  
Hill Equation ◽  
Cell Swelling ◽  
Intracellular Na Activity ◽  
Single Ventricular Myocytes ◽  
Hyperosmolar Solutions ◽  
Hill Coefficients ◽  
The Hill ◽  
The Relationship

The effect on the sarcolemmal Na(+)-K+ pump of exposure to anisosmolar solutions was examined using whole cell patch clamping and ion-selective microelectrodes. Na(+)-K+ pump currents were measured in single ventricular myocytes by using pipette Na+ concentrations ([Na]pip) of 0-70 mM. The relationship between [Na]pip and pump current was well described by the Hill equation. The [Na]pip for half-maximal pump current (K0.5) was 21.4 mM in isosmolar (310 mosM) solution. K0.5 was 12.8 mM during cell swelling in hyposmolar solution (240 mosM) and 39.0 mM during cell shrinkage in hyperosmolar solution (464 mosM). The maximal pump currents, derived from the best fit of the Hill equation, and the Hill coefficients were similar in isosmolar, hyposmolar, and hyperosmolar solutions. A sustained (> 20 min) decrease in the intracellular Na+ activity developed during exposure of intact papillary muscles to hyposmolar solutions, and a sustained increase developed during exposure to hyperosmolar solutions. We conclude that osmotic myocyte swelling stimulates the sarcolemmal Na(+)-K+ pump at near-physiological levels of intracellular Na+, whereas shrinkage inhibits the pump. These changes are due to increases and decreases, respectively, in the apparent affinity of the pump for Na+.

Perspective on the relationship between GABAA receptor activity and the apparent potency of an inhibitor

2021 ◽  
Vol 19 ◽  
Author(s):  
Allison L. Germann ◽  
Spencer R. Pierce ◽  
Alex S. Evers ◽  
Joe Henry Steinbach ◽  
Gustav Akk
Keyword(s):  
Gabaa Receptor ◽  
Hill Equation ◽  
Response Relationship ◽  
Inhibition Concentration ◽  
Level Of Activity ◽  
Control Response ◽  
The Hill ◽  
The Relationship ◽  
Inhibition Curve ◽  
Receptor Channel

Background : In electrophysiological experiments inhibition of a receptor-channel, such as the GABAA receptor, is measured by co-applying an agonist producing a predefined control response with an inhibitor to calculate the fraction of the control response remaining in the presence of the inhibitor. The properties of the inhibitor are determined by fitting the inhibition concentration-response relationship to the Hill equation to estimate the midpoint (IC50) of the inhibition curve. Objective: We sought to estimate here the sensitivity of the fitted IC50 to the level of activity of the control response. Methods: The inhibition concentration-response relationships were calculated for models with distinct mechanisms of inhibition. In Model I, the inhibitor acts allosterically to stabilize the resting state of the receptor. In Model II, the inhibitor competes with the agonist for a shared binding site. In Model III, the inhibitor stabilizes the desensitized state. Results: The simulations indicate that the fitted IC50 of the inhibition curve is sensitive to the degree of activity of the control response. In Models I and II, the IC50 of inhibition was increased as the probability of being in the active state (PA) of the control response increased. In Model III, the IC50 of inhibition was reduced at higher PA. Conclusions: We infer that the apparent potency of an inhibitor depends on the PA of the control response. While the calculations were carried out using the activation and inhibition properties that are representative of the GABAA receptor, the principles and conclusions apply to a wide variety of receptor-channels.

Preclinical evaluation of the ETS inhibitor TK216 against relapsed and refractory childhood leukemia.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10033-10033
Author(s):  
Ritul Sharma ◽  
Satbir Thakur ◽  
Mohit Jain ◽  
Chunfen Zhang ◽  
Anne-Marie Langevin ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cell Line ◽  
Drug Combination ◽  
Childhood Leukemia ◽  
Sensitive Cell Line ◽  
Pediatric Leukemia ◽  
Drug Synergy ◽  
Molecular Abnormalities ◽  
Anti Cancer ◽  
Combination Studies

10033 Background: Although survival rates have improved in the recent past, relapse and refractory disease remain a significant cause of death in children with leukemia. This calls for an urgent need for the development of novel therapies that could effectively treat leukemias in children. The E26 transformation specific (ETS) family of transcription factors regulate various normal cellular functions but are abnormally expressed in various cancers, including leukemia. TK216 is an ETS inhibitor, that has shown pre-clinical activity and clinical efficacy in solid tumors. In this study, we explore the feasibility of using TK216 as a therapeutic agent for the treatment of high risk refractory pediatric leukemia. Methods: A panel of pediatric leukemia derived cell lines and primary blast cells representing a spectrum of molecular abnormalities seen in pediatric leukemia were treated in vitro with TK216 to determine cytotoxicity. Normal lymphocytes were used as controls and cell viability was determined 72 hours post-treatment by Alamar blue assay. The induction of tumor cell apoptosis and target modulation were detected by Western blotting. Alterations in the cell cycle were assessed by FACS analysis with PI staining. Drug combination studies were carried out with established anti-leukemic agents to identify synergy for greater therapeutic efficiency. Results: TK216 decreased cell viability in leukemia cells compared to normal lymphocyte controls in a dose-dependent manner with variations in sensitivity noted with inherent molecular abnormalities. The IC50 values observed ranged from 0.22 µM for the most sensitive cell line, MV4-11 to 0.95 µM for least sensitive cell line, SUP-B15. Apoptosis induction upon TK216 treatment was confirmed by PARP cleavage and caspase 3 activation. Cell cycle analysis demonstrated increased sub-G1 population of cells after TK216 treatment. A strong correlation between sub-G1 population and sensitivity of the cell line towards TK216 (47% in MV4-11 vs 3.72% in SUP-B15) was observed. Screening of a panel of 200 FDA approved anti-cancer agents in drug combination studies identified potential agents for drug synergy. Significant drug synergy was noted with TK216 in combination with the epigenetic modifier 5-azacytidine and the Bcl-2 inhibitor, Venetoclax. [Combination Index for Venetoclax and TK216, mean = 0.65 for MV4-11 and 0.33 for SUP-B15]. Conclusions: Data from our study demonstrate that the ETS inhibitor TK216 induces apoptosis and cell cycle arrest in pediatric leukemia cells at physiologically relevant concentrations. Our combination studies identified distinct anti-cancer agents that could be used for developing effective drug combination regimens with TK216. Overall, our findings provide essential preclinical data for the consideration of TK216 in early phase clinical trials for the treatment of selected high-risk and refractory childhood leukemia.

In vitro synergistic interactions of oleanolic acid in combination with isoniazid, rifampicin or ethambutol against Mycobacterium tuberculosis

2010 ◽  
Vol 59 (5) ◽  
pp. 567-572 ◽  
Author(s):  
Fa Ge ◽  
Fanli Zeng ◽  
Siguo Liu ◽  
Na Guo ◽  
Haiqing Ye ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Oleanolic Acid ◽  
Antimycobacterial Activity ◽  
Vero Cells ◽  
Drug Resistant ◽  
Synergistic Interactions ◽  
Combination Treatments ◽  
Low Cytotoxicity ◽  
Drug Resistant Strains

Reports have shown that oleanolic acid (OA), a triterpenoid, exists widely in food, medicinal herbs and other plants, and that it has antimycobacterial activity against the Mycobacterium tuberculosis strain H37Rv (ATCC 27294). In this study it was found that OA had antimycobacterial properties against eight clinical isolates of M. tuberculosis and that the MICs of OA against drug-sensitive and drug-resistant isolates were 50–100 and 100–200 μg ml−1, respectively. The combination of OA with isoniazid (INH), rifampicin (RMP) or ethambutol (EMB) showed favourable synergistic antimycobacterial effects against six drug-resistant strains, with fractional inhibitory concentration indices of 0.121–0.347, 0.113–0.168 and 0.093–0.266, respectively. The combination treatments of OA/INH, OA/RMP and OA/EMB displayed either a synergistic interaction or did not show any interaction against two drug-sensitive strains. No antagonism resulting from the OA/INH, OA/RMP or OA/EMB combination was observed for any of the strains tested. OA exhibited a relatively low cytotoxicity in Vero cells. These results indicate that OA may serve as a promising lead compound for future antimycobacterial drug development.

scholarly journals Integrated Simulation Modeling Approach for Investigating Pore Water Pressure Induced Landslides

2022 ◽  
Author(s):  
Sahila Beegum ◽  
P J Jainet ◽  
Dawn Emil ◽  
K P Sudheer ◽  
Saurav Das
Keyword(s):  
Pore Water ◽  
Factor Of Safety ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Simulation Models ◽  
Integrated Simulation ◽  
Hill Slope ◽  
Slope Factor ◽  
The Stability ◽  
The Hill

Abstract Soil pore water pressure analysis is crucial for understanding landslide initiation and prediction. However, field-scale transient pore water pressure measurements are complex. This study investigates the integrated application of simulation models (HYDRUS-2D/3D and GeoStudio–Slope/W) to analyze pore water pressure-induced landslides. The proposed methodology is illustrated and validated using a case study (landslide in India, 2018). Model simulated pore water pressure was correlated with the stability of hillslope, and simulation results were found to be co-aligned with the actual landslide that occurred in 2018. Simulations were carried out for natural and modified hill slope geometry in the study area. The volume of water in the hill slope, temporal and spatial evolution of pore water pressure, and factor of safety were analysed. Results indicated higher stability in natural hillslope (factor of safety of 1.243) compared to modified hill slope (factor of safety of 0.946) despite a higher pore water pressure in the natural hillslope. The study demonstrates the integrated applicability of the physics-based models in analyzing the stability of hill slopes under varying pore water pressure and hill slope geometry and its accuracy in predicting future landslides.

scholarly journals Comparative analysis of molecular representations in prediction of cancer drug combination synergy and sensitivity

2021 ◽  
Author(s):  
Bulat Zagidullin ◽  
Ziyan Wang ◽  
Yuanfang Guan ◽  
Esa Pitkänen ◽  
Jing Tang
Keyword(s):  
Drug Combination ◽  
High Throughput Screening ◽  
Data Driven ◽  
Cancer Drug ◽  
Molecular Fingerprints ◽  
Rule Based ◽  
Drug Synergy ◽  
The Past ◽  
Optimal Representation ◽  
Preclinical Drug Development

Application of machine and deep learning (ML/DL) methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel DL solutions in relation to established techniques. To this end we compare rule-based and data-driven molecular representations in prediction of drug combination sensitivity and drug synergy scores using standardized results of 14 high throughput screening studies, comprising 64,200 unique combinations of 4,153 molecules tested in 112 cancer cell lines. We evaluate the clustering performance of molecular fingerprints and quantify their similarity by adapting Centred Kernel Alignment metric. Our work demonstrates that in order to identify an optimal representation type it is necessary to supplement quantitative benchmark results with qualitative considerations, such as model interpretability and robustness, which may vary between and throughout preclinical drug development projects.

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