A knowledge-based halogen bonding scoring function for predicting protein-ligand interactions

2013 ◽  
Vol 19 (11) ◽  
pp. 5015-5030 ◽  
Author(s):  
Yingtao Liu ◽  
Zhijian Xu ◽  
Zhuo Yang ◽  
Kaixian Chen ◽  
Weiliang Zhu
Keyword(s):  
Scoring Function ◽  
Halogen Bonding ◽  
Knowledge Based ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

A quantum mechanics-based halogen bonding scoring function for protein-ligand interactions

2015 ◽  
Vol 21 (6) ◽  
Author(s):  
Zhuo Yang ◽  
Yingtao Liu ◽  
Zhaoqiang Chen ◽  
Zhijian Xu ◽  
Jiye Shi ◽  
...  
Keyword(s):  
Quantum Mechanics ◽  
Scoring Function ◽  
Halogen Bonding ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Knowledge-based scoring function to predict protein-ligand interactions

2000 ◽  
Vol 295 (2) ◽  
pp. 337-356 ◽  
Author(s):  
Holger Gohlke ◽  
Manfred Hendlich ◽  
Gerhard Klebe
Keyword(s):  
Scoring Function ◽  
Knowledge Based ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

scholarly journals ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Xujun Zhang ◽  
Chao Shen ◽  
Xueying Guo ◽  
Zhe Wang ◽  
Gaoqi Weng ◽  
...  
Keyword(s):  
High Efficiency ◽  
Low Cost ◽  
Pearson Correlation ◽  
Scoring Function ◽  
Web Server ◽  
Scoring Functions ◽  
Protein Ligand Interactions ◽  
Prediction Module ◽  
Ligand Interactions ◽  
Benchmark Datasets

AbstractVirtual screening (VS) based on molecular docking has emerged as one of the mainstream technologies of drug discovery due to its low cost and high efficiency. However, the scoring functions (SFs) implemented in most docking programs are not always accurate enough and how to improve their prediction accuracy is still a big challenge. Here, we propose an integrated platform called ASFP, a web server for the development of customized SFs for structure-based VS. There are three main modules in ASFP: (1) the descriptor generation module that can generate up to 3437 descriptors for the modelling of protein–ligand interactions; (2) the AI-based SF construction module that can establish target-specific SFs based on the pre-generated descriptors through three machine learning (ML) techniques; (3) the online prediction module that provides some well-constructed target-specific SFs for VS and an additional generic SF for binding affinity prediction. Our methodology has been validated on several benchmark datasets. The target-specific SFs can achieve an average ROC AUC of 0.973 towards 32 targets and the generic SF can achieve the Pearson correlation coefficient of 0.81 on the PDBbind version 2016 core set. To sum up, the ASFP server is a powerful tool for structure-based VS.

scholarly journals Halogen Bonding: An Underestimated Player in Membrane–drug Interactions

2020 ◽  
Author(s):  
Rafael Nunes ◽  
Diogo Vila Viçosa ◽  
Paulo J. Costa
Keyword(s):  
Drug Discovery ◽  
Chemical Space ◽  
Noncovalent Interactions ◽  
Halogen Bonding ◽  
Lewis Bases ◽  
Protein Ligand Interactions ◽  
Biochemical Systems ◽  
Ligand Interactions ◽  
Dynamics Simulations

<div>Halogen bonds (HaBs) are noncovalent interactions where halogen atoms act as electrophilic species interacting with Lewis bases. These interactions are relevant in biochemical systems being increasingly explored in drug discovery, mainly to modulate protein–ligand interactions. In this work, we report evidence for the existence of HaB-mediated halogen–phospholipid recognition phenomena as our molecular dynamics simulations support the existence of favorable interactions between halobenzene derivatives and both phosphate (PO) or ester (CO) oxygen acceptors from model phospholipid bilayers, thus providing insights into the role of HaBs in driving the permeation of halogenated drug like molecules across biological membranes. This represents a relevant molecular mechanism, previously overlooked, determining the pharmacological activity of halogenated molecules with implications in drug discovery and development, a place where halogenated molecules account for a significant part of the chemical space. Our data also shows that, as the ubiquitous hydrogen bond, HaBs should be accounted for in the development of membrane permeability models.</div>

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