Literature DB >> 30519952

Web-Based Tools for Polypharmacology Prediction.

Mahendra Awale1, Jean-Louis Reymond2.   

Abstract

Drug promiscuity or polypharmacology is the ability of small molecules to interact with multiple protein targets simultaneously. In drug discovery, understanding the polypharmacology of potential drug molecules is crucial to improve their efficacy and safety, and to discover the new therapeutic potentials of existing drugs. Over the past decade, several computational methods have been developed to study the polypharmacology of small molecules, many of which are available as Web services. In this chapter, we review some of these Web tools focusing on ligand based approaches. We highlight in particular our recently developed polypharmacology browser (PPB) and its application for finding the side targets of a new inhibitor of the TRPV6 calcium channel.

Entities:  

Keywords:  Drug–target interactions; Molecular fingerprints; Polypharmacology; Similarity searching; Target prediction

Mesh:

Substances:

Year:  2019        PMID: 30519952     DOI: 10.1007/978-1-4939-8891-4_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  7 in total

1.  Updates to Binding MOAD (Mother of All Databases): Polypharmacology Tools and Their Utility in Drug Repurposing.

Authors:  Richard D Smith; Jordan J Clark; Aqeel Ahmed; Zachary J Orban; James B Dunbar; Heather A Carlson
Journal:  J Mol Biol       Date:  2019-05-22       Impact factor: 5.469

2.  One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome.

Authors:  Alice Capecchi; Daniel Probst; Jean-Louis Reymond
Journal:  J Cheminform       Date:  2020-06-12       Impact factor: 5.514

3.  Morphological Profiling Identifies a Common Mode of Action for Small Molecules with Different Targets.

Authors:  Tabea Schneidewind; Alexandra Brause; Axel Pahl; Annina Burhop; Tom Mejuch; Sonja Sievers; Herbert Waldmann; Slava Ziegler
Journal:  Chembiochem       Date:  2020-07-24       Impact factor: 3.164

4.  Multi-Target In Silico Prediction of Inhibitors for Mitogen-Activated Protein Kinase-Interacting Kinases.

Authors:  Amit Kumar Halder; M Natália D S Cordeiro
Journal:  Biomolecules       Date:  2021-11-10

5.  A Comparative Study of the Performance for Predicting Biodegradability Classification: The Quantitative Structure-Activity Relationship Model vs the Graph Convolutional Network.

Authors:  Myeonghun Lee; Kyoungmin Min
Journal:  ACS Omega       Date:  2022-01-14

6.  The Multistage Antimalarial Compound Calxinin Perturbates P. falciparum Ca2+ Homeostasis by Targeting a Unique Ion Channel.

Authors:  Yash Gupta; Neha Sharma; Snigdha Singh; Jesus G Romero; Vinoth Rajendran; Reagan M Mogire; Mohammad Kashif; Jordan Beach; Walter Jeske; Bernhards R Ogutu; Stefan M Kanzok; Hoseah M Akala; Jennifer Legac; Philip J Rosenthal; David J Rademacher; Ravi Durvasula; Agam P Singh; Brijesh Rathi; Prakasha Kempaiah
Journal:  Pharmaceutics       Date:  2022-06-28       Impact factor: 6.525

7.  A novel graph mining approach to predict and evaluate food-drug interactions.

Authors:  Md Mostafizur Rahman; Srinivas Mukund Vadrev; Arturo Magana-Mora; Jacob Levman; Othman Soufan
Journal:  Sci Rep       Date:  2022-01-20       Impact factor: 4.379

  7 in total

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