Computational Tools for Design of Selective Small Molecules Targeting RNA: From Small Molecule Microarrays to Chemical Similarity Searching

2017 ◽  
pp. 1-16 ◽  
Author(s):  
Matthew G. Costales ◽  
Jessica L. Childs-Disney ◽  
Matthew D. Disney
Keyword(s):  
Small Molecules ◽  
Small Molecule ◽  
Similarity Searching ◽  
Chemical Similarity ◽  
Computational Tools

Overview of Free Software Developed for Designing Drugs Based on Protein-Small Molecules Interaction

2018 ◽  
Vol 18 (13) ◽  
pp. 1146-1167 ◽  
Author(s):  
Piyush Agrawal ◽  
Pawan Kumar Raghav ◽  
Sherry Bhalla ◽  
Neelam Sharma ◽  
Gajendra P.S. Raghava
Keyword(s):  
Small Molecules ◽  
Small Molecule ◽  
Structure Prediction ◽  
Computational Tools ◽  
Pharmacophore Modelling ◽  
Drug Molecules ◽  
Software Packages ◽  
Binding Pockets ◽  
Major Emphasis ◽  
Molecule Interaction

One of the fundamental challenges in designing drug molecule against a disease target or protein is to predict binding affinity between target and drug or small molecule. In this review, our focus will be on advancement in the field of protein-small molecule interaction. This review has been divided into four major sections. In the first section, we will cover software developed for protein structure prediction. This will include prediction of binding pockets and post-translation modifications in proteins. In the second section, we will discuss software packages developed for predicting small-molecule interacting residues in a protein. Advances in the field of docking particularly advancement in the knowledgebased force fields will be discussed in the third part of the review. This section will also cover the method developed for predicting affinity between protein and drug molecules. The fourth section of the review will describe miscellaneous techniques used for designing drug molecules, like pharmacophore modelling. Our major emphasis in this review will be on computational tools that are available free for academic use.

scholarly journals Prediction of small molecule inhibitors targeting the novel coronavirus (SARS-CoV-2) RNA-dependent RNA polymerase

2020 ◽  
Author(s):  
Mohammed Ahmed ◽  
Abhisek Dwivedy ◽  
Richard Mariadasse ◽  
Satish Tiwari ◽  
Jeyaraman Jeyakanthan ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Small Molecules ◽  
Small Molecule ◽  
Small Molecule Inhibitors ◽  
Viral Proteins ◽  
The Novel ◽  
Rna Dependent Rna Polymerase ◽  
Computational Tools ◽  
Gtp Binding ◽  
Novel Coronavirus

The current COVID-19 outbreak calls for a multi-disciplinary approach towards the design and development of novel anti-COVID therapeutics including vaccines and small molecule inhibitors targeting the viral proteins of causative agent, SARS-CoV-2. Using a combination of bioinformatics and computational tools, we have modelled the 3-D structure of the RNA-dependent RNA-polymerase (RdRp) of SARS-CoV-2 and predicted its probable GTP-binding site. This site was computationally targeted using small molecules inhibitors reported in a previous study on the RdRp of the Hepatitis C virus. Further optimizations have suggested a lead molecule that may prove fruitful in development of inhibitors against RdRp of SARS-CoV-2.

Medicinal Chemistry Database GDBMedChem

2019 ◽  
Author(s):  
Mahendra Awale ◽  
Finton Sirockin ◽  
Nikolaus Stiefl ◽  
Jean-Louis Reymond
Keyword(s):  
Small Molecules ◽  
Natural Product ◽  
Medicinal Chemistry ◽  
3D Visualization ◽  
Molecular Size ◽  
Similarity Searching ◽  
Complex Molecules ◽  
Synthetic Accessibility ◽  
Simple Chemical ◽  
Reduced Complexity

<div>The generated database GDB17 enumerates 166.4 billion possible molecules up to 17 atoms of C, N, O, S and halogens following simple chemical stability and synthetic feasibility rules, however medicinal chemistry criteria are not taken into account. Here we applied rules inspired by medicinal chemistry to exclude problematic functional groups and complex molecules from GDB17, and sampled the resulting subset evenly across molecular size, stereochemistry and polarity to form GDBMedChem as a compact collection of 10 million small molecules.</div><div><br></div><div>This collection has reduced complexity and better synthetic accessibility than the entire GDB17 but retains higher sp 3 - carbon fraction and natural product likeness scores compared to known drugs. GDBMedChem molecules are more diverse and very different from known molecules in terms of substructures and represent an unprecedented source of diversity for drug design. GDBMedChem is available for 3D-visualization, similarity searching and for download at http://gdb.unibe.ch.</div>

scholarly journals STEM-20. A CANCER STEM CELL-SELECTIVE APOPTOSIS-INDUCING SMALL MOLECULE FOR THE TREATMENT OF GBM

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii200-ii200
Author(s):  
Stephen Skirboll ◽  
Natasha Lucki ◽  
Genaro Villa ◽  
Naja Vergani ◽  
Michael Bollong ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cancer Stem Cells ◽  
Small Molecules ◽  
Small Molecule ◽  
Large Scale ◽  
Critical Role ◽  
Tumor Formation ◽  
Cell Type ◽  
Caspase 1 ◽  
Activation Assay

Abstract INTRODUCTION Glioblastoma multiforme (GBM) is the most aggressive form of primary brain cancer. A subpopulation of multipotent cells termed GBM cancer stem cells (CSCs) play a critical role in tumor initiation and maintenance, drug resistance, and recurrence following surgery. New therapeutic strategies for the treatment of GBM have recently focused on targeting CSCs. Here we have used an unbiased large-scale screening approach to identify drug-like small molecules that induce apoptosis in GBM CSCs in a cell type-selective manner. METHODS A luciferase-based survival assay of patient-derived GBM CSC lines was established to perform a large-scale screen of ∼one million drug-like small molecules with the goal of identifying novel compounds that are selectively toxic to chemoresistant GBM CSCs. Compounds found to kill GBM CSC lines as compared to control cell types were further characterized. A caspase activation assay was used to evaluate the mechanism of induced cell death. A xenograft animal model using patient-derived GBM CSCs was employed to test the leading candidate for suppression of in vivo tumor formation. RESULTS We identified a small molecule, termed RIPGBM, from the cell-based chemical screen that induces apoptosis in primary patient-derived GBM CSC cultures. The cell type-dependent selectivity of RIPGBM appears to arise at least in part from redox-dependent formation of a proapoptotic derivative, termed cRIPGBM, in GBM CSCs. cRIPGBM induces caspase 1-dependent apoptosis by binding to receptor-interacting protein kinase 2 (RIPK2) and acting as a molecular switch, which reduces the formation of a prosurvival RIPK2/TAK1 complex and increases the formation of a proapoptotic RIPK2/caspase 1 complex. In an intracranial GBM xenograft mouse model, RIPGBM was found to significantly suppress tumor formation. CONCLUSIONS Our chemical genetics-based approach has identified a small molecule drug candidate and a potential drug target that selectively targets cancer stem cells and provides an approach for the treatment of GBMs.

Preparation of a porous polymer monolithic column with an ionic liquid as a porogen and its applications for the separation of small molecules in high performance liquid chromatography

2015 ◽  
Vol 7 (18) ◽  
pp. 7879-7888 ◽  
Author(s):  
Jiafei Wang ◽  
Xiaoya Jiang ◽  
Hang Zhang ◽  
Sha Liu ◽  
Ligai Bai ◽  
...  
Keyword(s):  
Ionic Liquid ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Small Molecules ◽  
Small Molecule ◽  
High Performance ◽  
Monolithic Column ◽  
Porous Polymer ◽  
Column Efficiency ◽  
Polymer Monolithic Column

A monolith based on an ionic liquid as a porogen was prepared to enhance the column efficiency of small molecule separation in HPLC.

scholarly journals A journey in bioinspired supramolecular chemistry: from molecular tweezers to small molecules that target myotonic dystrophy

2016 ◽  
Vol 12 ◽  
pp. 125-138 ◽  
Author(s):  
Steven C Zimmerman
Keyword(s):  
Small Molecules ◽  
Supramolecular Chemistry ◽  
Myotonic Dystrophy ◽  
Small Molecule ◽  
Early Life ◽  
Rational Design ◽  
Early Experience ◽  
Therapeutic Agents ◽  
Early Career ◽  
Molecular Tweezers

This review summarizes part of the author’s research in the area of supramolecular chemistry, beginning with his early life influences and early career efforts in molecular recognition, especially molecular tweezers. Although designed to complex DNA, these hosts proved more applicable to the field of host–guest chemistry. This early experience and interest in intercalation ultimately led to the current efforts to develop small molecule therapeutic agents for myotonic dystrophy using a rational design approach that heavily relies on principles of supramolecular chemistry. How this work was influenced by that of others in the field and the evolution of each area of research is highlighted with selected examples.

Elucidating Protein-protein Interactions Through Computational Approaches and Designing Small Molecule Inhibitors Against them for Various Diseases

2018 ◽  
Vol 18 (20) ◽  
pp. 1719-1736 ◽  
Author(s):  
Sharanya Sarkar ◽  
Khushboo Gulati ◽  
Manikyaprabhu Kairamkonda ◽  
Amit Mishra ◽  
Krishna Mohan Poluri
Keyword(s):  
Small Molecule ◽  
Protein Interactions ◽  
Small Molecule Inhibitors ◽  
Computational Techniques ◽  
Protein Protein Interactions ◽  
Computational Tools ◽  
Computational Approaches ◽  
Protein Protein Interaction ◽  
Wide Range ◽  
Therapeutic Measures

Background: To carry out wide range of cellular functionalities, proteins often associate with one or more proteins in a phenomenon known as Protein-Protein Interaction (PPI). Experimental and computational approaches were applied on PPIs in order to determine the interacting partners, and also to understand how an abnormality in such interactions can become the principle cause of a disease. Objective: This review aims to elucidate the case studies where PPIs involved in various human diseases have been proven or validated with computational techniques, and also to elucidate how small molecule inhibitors of PPIs have been designed computationally to act as effective therapeutic measures against certain diseases. Results: Computational techniques to predict PPIs are emerging rapidly in the modern day. They not only help in predicting new PPIs, but also generate outputs that substantiate the experimentally determined results. Moreover, computation has aided in the designing of novel inhibitor molecules disrupting the PPIs. Some of them are already being tested in the clinical trials. Conclusion: This review delineated the classification of computational tools that are essential to investigate PPIs. Furthermore, the review shed light on how indispensable computational tools have become in the field of medicine to analyze the interaction networks and to design novel inhibitors efficiently against dreadful diseases in a shorter time span.

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 &alpha; 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 &alpha;, or its close relative meprin &beta;, over numerous other metzincins which, if inhibited, would elicit unwanted effects. We recently identified possible molecular starting points for meprin &alpha;-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 &alpha; inhibitor probe which may help define the therapeutic potential for small molecule meprin &alpha; inhibition and spur further drug discovery efforts in the area of zinc metalloproteinase inhibition.

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