Literature DB >> 32108318

User guide for the discovery of potential drugs via protein structure prediction and ligand docking simulation.

Bilal Shaker1, Myung-Sang Yu1, Jingyu Lee1, Yongmin Lee1, Chanjin Jung1, Dokyun Na2.   

Abstract

Due to accumulating protein structure information and advances in computational methodologies, it has now become possible to predict protein-compound interactions. In biology, the classic strategy for drug discovery has been to manually screen multiple compounds (small scale) to identify potential drug compounds. Recent strategies have utilized computational drug discovery methods that involve predicting target protein structures, identifying active sites, and finding potential inhibitor compounds at large scale. In this protocol article, we introduce an in silico drug discovery protocol. Since multi-drug resistance of pathogenic bacteria remains a challenging problem to address, UDP-N-acetylmuramate-L-alanine ligase (murC) of Acinetobacter baumannii was used as an example, which causes nosocomial infection in hospital setups and is responsible for high mortality worldwide. This protocol should help microbiologists to expand their knowledge and research scope.

Entities:  

Keywords:  ADMET; docking; drug discovery; protein structure prediction

Year:  2020        PMID: 32108318     DOI: 10.1007/s12275-020-9563-z

Source DB:  PubMed          Journal:  J Microbiol        ISSN: 1225-8873            Impact factor:   3.422


  5 in total

Review 1.  Rediscovery of antimicrobial peptides as therapeutic agents.

Authors:  Minkyung Ryu; Jaeyeong Park; Ji-Hyun Yeom; Minju Joo; Kangseok Lee
Journal:  J Microbiol       Date:  2021-02-01       Impact factor: 3.422

2.  Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening.

Authors:  Md Nazmus Samdani; Niaz Morshed; Rumman Reza; Muhammad Asaduzzaman; Abul Bashar Mir Md Khademul Islam
Journal:  Mol Divers       Date:  2022-06-12       Impact factor: 3.364

3.  Structure based pharmacophore modeling, virtual screening, molecular docking and ADMET approaches for identification of natural anti-cancer agents targeting XIAP protein.

Authors:  Firoz A Dain Md Opo; Mohammed M Rahman; Foysal Ahammad; Istiak Ahmed; Mohiuddin Ahmed Bhuiyan; Abdullah M Asiri
Journal:  Sci Rep       Date:  2021-02-18       Impact factor: 4.379

4.  Omics-based microbiome analysis in microbial ecology: from sequences to information.

Authors:  Jang-Cheon Cho
Journal:  J Microbiol       Date:  2021-03       Impact factor: 3.422

5.  Concatenation of molecular docking and molecular simulation of BACE-1, γ-secretase targeted ligands: in pursuit of Alzheimer's treatment.

Authors:  Nasimudeen R Jabir; Md Tabish Rehman; Khadeejah Alsolami; Shazi Shakil; Torki A Zughaibi; Raed F Alserihi; Mohd Shahnawaz Khan; Mohamed F AlAjmi; Shams Tabrez
Journal:  Ann Med       Date:  2021-12       Impact factor: 4.709

  5 in total

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