scholarly journals Small molecule recognition of disease-relevant RNA structures

2020 ◽  
Vol 49 (19) ◽  
pp. 7167-7199 ◽  
Author(s):  
Samantha M. Meyer ◽  
Christopher C. Williams ◽  
Yoshihiro Akahori ◽  
Toru Tanaka ◽  
Haruo Aikawa ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
Rna Structures ◽  
Drug Discovery And Development ◽  
New Frontier ◽  
Molecule Recognition

Targeting RNAs with small molecules, a new frontier in drug discovery and development.

scholarly journals Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Paul Erhardt ◽  
Kenneth Bachmann ◽  
Donald Birkett ◽  
Michael Boberg ◽  
Nicholas Bodor ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecule ◽  
Chemical Structure ◽  
Early Stage ◽  
Xenobiotic Metabolism ◽  
Drug Discovery And Development ◽  
Small Molecule Drug ◽  
Technical Report ◽  
Wide Range ◽  
Draft Version

Abstract This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

scholarly journals Discovery and Optimization of Selective Inhibitors of Meprin α (Part II)

2020 ◽  
Author(s):  
Chao Wang ◽  
Juan Diez ◽  
Hajeung Park ◽  
Christoph Becker-Pauly ◽  
Gregg B. Fields ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
Hydroxamic Acid ◽  
Therapeutic Potential ◽  
Preceding Paper ◽  
Close Relative ◽  
Specific Inhibition ◽  
Selective Inhibitors

Meprin α is a zinc metalloproteinase (metzincin) that has been implicated in multiple diseases, including fibrosis and cancers. It has proven difficult to find small molecules that are capable of selectively inhibiting meprin α, or its close relative meprin β, over numerous other metzincins which, if inhibited, would elicit unwanted effects. We recently identified possible molecular starting points for meprin α-specific inhibition through an HTS effort (see part I, preceding paper). In part II we report the optimization of a potent and selective hydroxamic acid meprin α inhibitor probe which may help define the therapeutic potential for small molecule meprin α inhibition and spur further drug discovery efforts in the area of zinc metalloproteinase inhibition.

scholarly journals A New Big-Data Paradigm for Target Identification and Drug Discovery

2017 ◽  
Author(s):  
Neel S. Madhukar ◽  
Prashant K. Khade ◽  
Linda Huang ◽  
Kaitlyn Gayvert ◽  
Giuseppe Galletti ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Clinical Application ◽  
Small Molecule ◽  
Target Identification ◽  
Clinical Development ◽  
Data Types ◽  
Public Data ◽  
Drug Target Identification ◽  
Approved Drugs

AbstractDrug target identification is one of the most important aspects of pre-clinical development yet it is also among the most complex, labor-intensive, and costly. This represents a major issue, as lack of proper target identification can be detrimental in determining the clinical application of a bioactive small molecule. To improve target identification, we developed BANDIT, a novel paradigm that integrates multiple data types within a Bayesian machine-learning framework to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using only public data BANDIT achieved an accuracy of approximately 90% over 2000 different small molecules – substantially better than any other published target identification platform. We applied BANDIT to a library of small molecules with no known targets and generated ∼4,000 novel molecule-target predictions. From this set we identified and experimentally validated a set of novel microtubule inhibitors, including three with activity on cancer cells resistant to clinically used anti-microtubule therapies. We next applied BANDIT to ONC201 – an active anti- cancer small molecule in clinical development – whose target has remained elusive since its discovery in 2009. BANDIT identified dopamine receptor 2 as the unexpected target of ONC201, a prediction that we experimentally validated. Not only does this open the door for clinical trials focused on target-based selection of patient populations, but it also represents a novel way to target GPCRs in cancer. Additionally, BANDIT identified previously undocumented connections between approved drugs with disparate indications, shedding light onto previously unexplained clinical observations and suggesting new uses of marketed drugs. Overall, BANDIT represents an efficient and highly accurate platform that can be used as a resource to accelerate drug discovery and direct the clinical application of small molecule therapeutics with improved precision.

Quantitative Structure Activity Relationship (QSAR) study predicts small molecule binding to RNA structure

2021 ◽  
Author(s):  
Zhengguo Cai ◽  
Martina Zafferani ◽  
Olanrewaju Akande ◽  
Amanda Hargrove
Keyword(s):  
High Resolution ◽  
Small Molecules ◽  
Small Molecule ◽  
Rna Structure ◽  
Quantitative Structure ◽  
Rna Structures ◽  
Qsar Study ◽  
Structure Activity ◽  
Qsar Models ◽  
Hiv 1

The diversity of RNA structural elements and their documented role in human diseases make RNA an attractive therapeutic target. However, progress in drug discovery and development has been hindered by challenges in the determination of high-resolution RNA structures and a limited understanding of the parameters that drive RNA recognition by small molecules, including a lack of validated quantitative structure-activity relationships (QSAR). Herein, we developed QSAR models that quantitatively predict both thermodynamic and kinetic-based binding parameters of small molecules and the HIV-1 TAR model RNA system. A set of small molecules bearing diverse scaffolds was screened against the HIV-1-TAR construct using surface plasmon resonance, which provided the binding kinetics and affinities. The data was then analyzed using multiple linear regression (MLR) combined with feature selection to afford robust models for binding of diverse RNA-targeted scaffolds. The predictivity of the model was validated on untested small molecules. The QSAR models presented herein represent the first application of validated and predictive 2D-QSAR using multiple scaffolds against an RNA target. We expect the workflow to be generally applicable to other RNA structures, ultimately providing essential insight into the small molecule descriptors that drive selective binding interactions and, consequently, providing a platform that can exponentially increase the efficiency of ligand design and optimization without the need for high-resolution RNA structures.

Modulating target engagement of small molecules via drug delivery: approaches and applications in drug discovery and development

2020 ◽  
Author(s):  
Wenzhan Yang ◽  
Shobha N. Bhattachar ◽  
Phenil J. Patel ◽  
Margaret Landis ◽  
Dipal Patel ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Drug Discovery ◽  
Small Molecules ◽  
Target Engagement ◽  
Drug Discovery And Development

In depth analysis of kinase cross screening data to identify chemical starting points for inhibition of the nek family of kinases

2017 ◽  
Author(s):  
Carrow I. Wells ◽  
Nirav R. Kapadia ◽  
Rafael M. Couñago ◽  
David H. Drewry
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
Kinase Inhibitors ◽  
Biological Functions ◽  
Chemical Probes ◽  
High Quality ◽  
Depth Analysis ◽  
Number Of Citations ◽  
Shed Light

AbstractPotent, selective, and cell active small molecule kinase inhibitors are useful tools to help unravel the complexities of kinase signaling. As the biological functions of individual kinases become better understood, they can become targets of drug discovery efforts. The small molecules used to shed light on function can also then serve as chemical starting points in these drug discovery efforts. The Nek family of kinases has received very little attention, as judged by number of citations in PubMed, yet they appear to play many key roles and have been implicated in disease. Here we present our work to identify high quality chemical starting points that have emerged due to the increased incidence of broad kinome screening. We anticipate that this analysis will allow the community to progress towards the generation of chemical probes and eventually drugs that target members of the Nek family.

Niche-Based Screening Reveals Leukemia Stem Cell Specific Therapeutics

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 760-760
Author(s):  
Kimberly A. Hartwell ◽  
Peter G. Miller ◽  
Alison L. Stewart ◽  
Alissa R. Kahn ◽  
David J. Logan ◽  
...  
Keyword(s):  
Stem Cells ◽  
Bone Marrow ◽  
Stem Cell ◽  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
High Throughput ◽  
Hematopoietic Cells ◽  
Leukemia Stem Cells

Abstract Abstract 760 Recent insights into the molecular and cellular processes that drive leukemia have called attention to the limitations intrinsic to traditional drug discovery approaches. To date, the majority of cell-based functional screens have relied on probing cell lines in vitro in isolation to identify compounds that decrease cellular viability. The development of novel therapeutics with greater efficacy and decreased toxicity will require the identification of small molecules that selectively target leukemia stem cells (LSCs) within the context of their microenvironment, while sparing normal cells. We hypothesized that it would be possible to systematically identify LSC susceptibilities by modeling key elements of bone marrow niche interactions in high throughput format. We tested this hypothesis by creating and optimizing an assay in which primary murine stem cell-enriched leukemia cells are plated on bone marrow stromal cells in 384-well format, and examined by a high content image-based readout of cobblestoning, an in vitro morphological surrogate of cell health and self-renewal. AML cells cultured in this way maintained their ability to reinitiate disease in mice with as few as 100 cells. 14,720 small molecule probes across diverse chemical space were screened at 5uM in our assay. Retest screening was performed in the presence of two different bone marrow stromal types in parallel, OP9s and primary mesenchymal stem cells (MSCs). Greater than 60% of primary screen hits positively retested (dose response with IC50 at or below 5 μM) on both types of stroma. Compounds that inhibited leukemic cobblestoning merely by killing the stroma were identified by CellTiter-Glo viability analysis and excluded. Compounds that killed normal primary hematopoietic stem and progenitor cell inputs, as assessed by a related co-culture screen, were also excluded. Selectivity for leukemia over normal hematopoietic cells was additionally examined in vitro by comingling these cells on stroma within the same wells. Primary human CD34+ AML leukemia and normal CD34+ cord blood cells were also tested, by way of the 5 week cobblestone area forming cell (CAFC) assay. Additionally, preliminary studies of human AML cells pulse-treated with small molecules ex vivo, followed by in vivo transplantation, provided further evidence of potent leukemia kill across genotypes. A biologically complex functional approach to drug discovery, such as the novel method described here, has previously been thought impossible, due to presumed incompatibility with high throughput scale. We show that it is possible, and that it bears fruit in a first pilot screen. By these means, we discover small molecule perturbants that act selectively in the context of the microenvironment to kill LSCs while sparing stroma and normal hematopoietic cells. Some hits act cell autonomously, and some do not, as evidenced by observed leukemia kill when only the stromal support cells are treated prior to the plating of leukemia. Some hits are known, such as parthenolide and celastrol, and some are previously underappreciated, such as HMG-CoA reductase inhibition. Others are entirely new, and would not have been revealed by conventional approaches to therapeutic discovery. We therefore present a powerful new approach, and identify drug candidates with the potential to selectively target leukemia stem cells in clinical patients. Disclosures: No relevant conflicts of interest to declare.

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