Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.
Sign Up to like & getrecommendations! Published in 2017 at "Accounts of chemical research"
DOI: 10.1021/acs.accounts.6b00491
Abstract: In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole… read more here.
Keywords: scoring function; scoring functions; protein ligand; ligand interaction ... See more keywords
Development of a New Scoring Function for Virtual Screening: APBScore
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00474
Abstract: In this study, we developed a new physical-based scoring function, Atom Pair-Based Scoring function (APBScore), which includes pairwise van der Waals (VDW), electrostatic interaction, and hydrogen bond energies between the receptor and ligand. Despite the… read more here.
Keywords: apbscore; scoring functions; development new; scoring function ... See more keywords
Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00485
Abstract: Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding the… read more here.
Keywords: scoring ranking; ligand scoring; scoring functions; machine learning ... See more keywords
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.3c00322
Abstract: Over the past few years, many machine learning-based scoring functions for predicting the binding of small molecules to proteins have been developed. Their objective is to approximate the distribution which takes two molecules as input… read more here.
Keywords: function; scoring functions; scoring function; machine learning ... See more keywords
Protein-Ligand Scoring with Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2017 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.6b00740
Abstract: Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding… read more here.
Keywords: scoring functions; scoring function; ligand scoring; convolutional neural ... See more keywords
The Development of Target-Specific Machine Learning Models as Scoring Functions for Docking-Based Target Prediction
Sign Up to like & getrecommendations! Published in 2019 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.8b00773
Abstract: The identification of possible targets for a known bioactive compound is of the utmost importance for drug design and development. Molecular docking is one possible approach for in-silico protein target prediction, whereas a molecule is… read more here.
Keywords: scoring functions; target specific; target; target prediction ... See more keywords
Prediction of the Favorable Hydration Sites in a Protein Binding Pocket and Its Application to Scoring Function Formulation
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.9b00619
Abstract: The important role of water molecules in protein-ligand binding energetics has attracted wide attention in recent years. A range of computational methods have been developed to predict the favorable locations of water molecules in a… read more here.
Keywords: scoring functions; binding pocket; water; hydration sites ... See more keywords
TocoDecoy: A New Approach to Design Unbiased Datasets for Training and Benchmarking Machine-Learning Scoring Functions.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of medicinal chemistry"
DOI: 10.1021/acs.jmedchem.2c00460
Abstract: Development of accurate machine-learning-based scoring functions (MLSFs) for structure-based virtual screening against a given target requires a large unbiased dataset with structurally diverse actives and decoys. However, most datasets for the development of MLSFs were… read more here.
Keywords: new approach; scoring functions; training benchmarking; machine learning ... See more keywords
A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions
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DOI: 10.1021/acsomega.7b01194
Abstract: The prediction of protein–ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying… read more here.
Keywords: molecular pairs; scoring functions; diverse benchmark; matched molecular ... See more keywords
Learning from the ligand: using ligand-based features to improve binding affinity prediction
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz665
Abstract: MOTIVATION Machine learning scoring functions for protein-ligand binding affinity prediction have been found to consistently outperform classical scoring functions. Structure-based scoring functions for universal affinity prediction typically use features describing interactions derived from the protein-ligand… read more here.
Keywords: ligand based; scoring functions; based features; ligand ... See more keywords
Machine Learning-Based Scoring Functions. Development and Applications with SAnDReS.
Sign Up to like & getrecommendations! Published in 2020 at "Current medicinal chemistry"
DOI: 10.2174/0929867327666200515101820
Abstract: BACKGROUND Analysis of atomic coordinates of protein-ligand complexes can provide three-dimensional data to generate computational models to evaluate binding affinity and thermodynamic state functions. Application of machine learning techniques can create models to assess protein-ligand… read more here.
Keywords: scoring functions; machine learning; development; binding affinity ... See more keywords