Literature DB >> 31621012

The Pharmacophore Concept and Its Applications in Computer-Aided Drug Design.

Thomas Seidel1, Doris A Schuetz2, Arthur Garon3, Thierry Langer3.   

Abstract

Pharmacophore-based techniques currently are an integral part of many computer-aided drug design workflows and have been successfully and extensively applied for tasks such as virtual screening, de novo design, and lead optimization. Pharmacophore models can be derived both in a receptor-based and in a ligand-based manner, and provide an abstract description of essential non-bonded interactions that typically occur between small-molecule ligands and macromolecular targets. Due to their simplistic and abstract nature, pharmacophores are both perfectly suited for efficient computer processing and easy to comprehend by life and physical scientists. As a consequence, they have also proven to be a valuable tool for communicating between computational and medicinal chemists.This chapter aims to provide a short overview of the pharmacophore concept and its applications in modern computer-aided drug design. The chapter is divided into three distinct parts. The first section contains a brief introduction to the pharmacophore concept. The second section provides a description of the most common nonbonded interaction types and their representation as pharmacophoric features. Furthermore, it gives an overview of the various methods for pharmacophore generation and important pharmacophore-based techniques in drug design. This part concludes with examples for recent pharmacophore concept-related research and development. The last section is dedicated to a review of research in the field of natural product chemistry as carried out by employing pharmacophore-based drug design methods.

Keywords:  De novo design; Drug design; Pharmacophore; Virtual screening

Mesh:

Substances:

Year:  2019        PMID: 31621012     DOI: 10.1007/978-3-030-14632-0_4

Source DB:  PubMed          Journal:  Prog Chem Org Nat Prod        ISSN: 0071-7886


  12 in total

1.  Identification of novel inhibitors of S-adenosyl-L-homocysteine hydrolase via structure-based virtual screening and molecular dynamics simulations.

Authors:  Cong Chen; Xiang-Hui Zhou; Wa Cheng; Yan-Fen Peng; Qi-Ming Yu; Xiang-Duan Tan
Journal:  J Mol Model       Date:  2022-09-30       Impact factor: 2.172

Review 2.  Drug Design by Pharmacophore and Virtual Screening Approach.

Authors:  Deborah Giordano; Carmen Biancaniello; Maria Antonia Argenio; Angelo Facchiano
Journal:  Pharmaceuticals (Basel)       Date:  2022-05-23

3.  Virtual Screening of Natural Compounds as Potential PI3K-AKT1 Signaling Pathway Inhibitors and Experimental Validation.

Authors:  Serena Dotolo; Carmen Cervellera; Maria Russo; Gian Luigi Russo; Angelo Facchiano
Journal:  Molecules       Date:  2021-01-18       Impact factor: 4.411

Review 4.  Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: lessons from the pandemic and preparing for future health crises.

Authors:  Natesh Singh; Bruno O Villoutreix
Journal:  Comput Struct Biotechnol J       Date:  2021-04-26       Impact factor: 7.271

5.  Teaching and Learning Computational Drug Design: Student Investigations of 3D Quantitative Structure-Activity Relationships through Web Applications.

Authors:  Rino Ragno; Valeria Esposito; Martina Di Mario; Stefano Masiello; Marco Viscovo; Richard D Cramer
Journal:  J Chem Educ       Date:  2020-06-23       Impact factor: 2.979

6.  Development of IKATP Ion Channel Blockers Targeting Sulfonylurea Resistant Mutant KIR6.2 Based Channels for Treating DEND Syndrome.

Authors:  Marien J C Houtman; Theres Friesacher; Xingyu Chen; Eva-Maria Zangerl-Plessl; Marcel A G van der Heyden; Anna Stary-Weinzinger
Journal:  Front Pharmacol       Date:  2022-01-14       Impact factor: 5.988

7.  Greedy 3-Point Search (G3PS)-A Novel Algorithm for Pharmacophore Alignment.

Authors:  Christian Permann; Thomas Seidel; Thierry Langer
Journal:  Molecules       Date:  2021-11-27       Impact factor: 4.411

8.  Computational guided identification of potential leads from Acacia pennata (L.) Willd. as inhibitors for cellular entry and viral replication of SARS-CoV-2.

Authors:  James H Zothantluanga; Neelutpal Gogoi; Anshul Shakya; Dipak Chetia; H Lalthanzara
Journal:  Futur J Pharm Sci       Date:  2021-10-09

9.  Design, Synthesis, Docking, DFT, MD Simulation Studies of a New Nicotinamide-Based Derivative: In Vitro Anticancer and VEGFR-2 Inhibitory Effects.

Authors:  Eslam B Elkaeed; Reda G Yousef; Hazem Elkady; Ibraheem M M Gobaara; Bshra A Alsfouk; Dalal Z Husein; Ibrahim M Ibrahim; Ahmed M Metwaly; Ibrahim H Eissa
Journal:  Molecules       Date:  2022-07-19       Impact factor: 4.927

10.  Antimicrobial Random Peptide Mixtures Eradicate Acinetobacter baumannii Biofilms and Inhibit Mouse Models of Infection.

Authors:  Hannah E Caraway; Jonathan Z Lau; Bar Maron; Myung Whan Oh; Yael Belo; Aya Brill; Einav Malach; Nahed Ismail; Zvi Hayouka; Gee W Lau
Journal:  Antibiotics (Basel)       Date:  2022-03-19
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.