ES-Screen: A Novel Electrostatics-Driven Method for Drug Discovery Virtual Screening

被引:1
作者
Issa, Naiem T. [1 ]
Byers, Stephen W. [1 ]
Dakshanamurthy, Sivanesan [1 ]
机构
[1] Georgetown Univ, Lombardi Comprehens Canc Ctr, Dept Oncol, Med Ctr, Washington, DC 20057 USA
关键词
electrostatics; electrostatic potential; electrostatic energy; free energy; virtual screening; hit-to-lead identification; drug discovery; LIGAND-BINDING; 3D SHAPE; PROTEIN; DOCKING; MEBENDAZOLE; TARGETS; ACETYLCHOLINESTERASE; KINETICS; RECEPTOR; DATABASE;
D O I
10.3390/ijms232314830
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Electrostatic interactions drive biomolecular interactions and associations. Computational modeling of electrostatics in biomolecular systems, such as protein-ligand, protein-protein, and protein-DNA, has provided atomistic insights into the binding process. In drug discovery, finding biologically plausible ligand-protein target interactions is challenging as current virtual screening and adjuvant techniques such as docking methods do not provide optimal treatment of electrostatic interactions. This study describes a novel electrostatics-driven virtual screening method called 'ES-Screen' that performs well across diverse protein target systems. ES-Screen provides a unique treatment of electrostatic interaction energies independent of total electrostatic free energy, typically employed by current software. Importantly, ES-Screen uses initial ligand pose input obtained from a receptor-based pharmacophore, thus independent of molecular docking. ES-Screen integrates individual polar and nonpolar replacement energies, which are the energy costs of replacing the cognate ligand for a target with a query ligand from the screening. This uniquely optimizes thermodynamic stability in electrostatic and nonpolar interactions relative to an experimentally determined stable binding state. ES-Screen also integrates chemometrics through shape and other physicochemical properties to prioritize query ligands with the greatest physicochemical similarities to the cognate ligand. The applicability of ES-Screen is demonstrated with in vitro experiments by identifying novel targets for many drugs. The present version includes a combination of many other descriptor components that, in a future version, will be purely based on electrostatics. Therefore, ES-Screen is a first-in-class unique electrostatics-driven virtual screening method with a unique implementation of replacement electrostatic interaction energies with broad applicability in drug discovery.
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页数:23
相关论文
共 47 条
  • [1] [Anonymous], 2013, Schrodinger Release 2013-2: LigPrep, version 2.7
  • [2] [Anonymous], 2013, Small-Molecule Drug Discovery Suite 2013-1: Glide
  • [3] Drug repositioning: Identifying and developing new uses for existing drugs
    Ashburn, TT
    Thor, KB
    [J]. NATURE REVIEWS DRUG DISCOVERY, 2004, 3 (08) : 673 - 683
  • [4] Antiparasitic mebendazole shows survival benefit in 2 preclinical models of glioblastoma multiforme
    Bai, Ren-Yuan
    Staedtke, Verena
    Aprhys, Colette M.
    Gallia, Gary L.
    Riggins, Gregory J.
    [J]. NEURO-ONCOLOGY, 2011, 13 (09) : 974 - 982
  • [5] Electrostatic potential of nucleotide-free protein is sufficient for discrimination between adenine and guanine-specific binding sites
    Basu, G
    Sivanesan, D
    Kawabata, T
    Go, N
    [J]. JOURNAL OF MOLECULAR BIOLOGY, 2004, 342 (03) : 1053 - 1066
  • [6] The Protein Data Bank
    Berman, HM
    Westbrook, J
    Feng, Z
    Gilliland, G
    Bhat, TN
    Weissig, H
    Shindyalov, IN
    Bourne, PE
    [J]. NUCLEIC ACIDS RESEARCH, 2000, 28 (01) : 235 - 242
  • [7] Bockris J.O.M., 1998, MODERN ELECTROCHEMIS
  • [8] FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols
    Bohari, Mohammed H.
    Sastry, G. Narahari
    [J]. JOURNAL OF MOLECULAR MODELING, 2012, 18 (09) : 4263 - 4274
  • [9] On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods
    Bolcato, Giovanni
    Heid, Esther
    Bostrom, Jonas
    [J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, 62 (06) : 1388 - 1398
  • [10] Case DA., 2012, AMBER 13