Literature DB >> 19349252

Computational multiscale modeling in protein--ligand docking.

Michela Taufer1, Roger Armen, Jianhan Chen, Patricia Teller, Charles Brooks.   

Abstract

In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19349252     DOI: 10.1109/MEMB.2009.931789

Source DB:  PubMed          Journal:  IEEE Eng Med Biol Mag        ISSN: 0739-5175


  4 in total

1.  A survey of algorithms for transforming molecular dynamics data into metadata for in situ analytics based on machine learning methods.

Authors:  Michela Taufer; Trilce Estrada; Travis Johnston
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2020-01-20       Impact factor: 4.226

2.  Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

Authors:  Obaidur Rahaman; Trilce P Estrada; Douglas J Doren; Michela Taufer; Charles L Brooks; Roger S Armen
Journal:  J Chem Inf Model       Date:  2011-06-06       Impact factor: 4.956

3.  A molecular mechanics approach to modeling protein-ligand interactions: relative binding affinities in congeneric series.

Authors:  Chaya Rapp; Chakrapani Kalyanaraman; Aviva Schiffmiller; Esther Leah Schoenbrun; Matthew P Jacobson
Journal:  J Chem Inf Model       Date:  2011-08-09       Impact factor: 4.956

4.  Identification of the functional binding pocket for compounds targeting small-conductance Ca²⁺-activated potassium channels.

Authors:  Miao Zhang; John M Pascal; Marcel Schumann; Roger S Armen; Ji-Fang Zhang
Journal:  Nat Commun       Date:  2012       Impact factor: 14.919

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.