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Predicting human plasma protein binding of drugs using plasma protein interaction QSAR analysis (PPI‐QSAR)

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/bip.21314openalex-snapshot

Exploration of human serum albumin binding sites by docking and molecular dynamics flexible ligand–protein interactions

inferredcites →https://doi.org/10.1002/jps.20059openalex-snapshot

Computational prediction of the plasma protein‐binding percent of diverse pharmaceutical compounds

inferredcites →https://doi.org/10.1002/med.10039openalex-snapshot

In silico prediction of drug‐binding strengths to human serum albumin

inferredcites →https://doi.org/10.1002/prot.21847openalex-snapshot

High quality binding modes in docking ligands to proteins

inferredcites →https://doi.org/10.1007/s10822-005-9012-4openalex-snapshot

Prediction of plasma protein binding of drugs using Kier–Hall valence connectivity indices and 4D-fingerprint molecular similarity analyses

inferredcites →https://doi.org/10.1016/b0-08-045044-x/00151-6openalex-snapshot

In Silico Prediction of Plasma and Tissue Protein Binding

inferredcites →https://doi.org/10.1016/j.bmc.2005.08.035openalex-snapshot

Constructing plasma protein binding model based on a combination of cluster analysis and 4D-fingerprint molecular similarity analyses

inferredcites →https://doi.org/10.1016/j.bmc.2006.02.008openalex-snapshot

In silico ADME modelling 2: Computational models to predict human serum albumin binding affinity using ant colony systems

inferredcites →https://doi.org/10.1016/j.farmac.2005.04.010openalex-snapshot

A molecular dynamics study of human serum albumin binding sites

inferredcites →https://doi.org/10.1016/j.jpba.2008.03.023openalex-snapshot

Prediction models of human plasma protein binding rate and oral bioavailability derived by using GA–CG–SVM method

inferredcites →https://doi.org/10.1016/s0006-2952(02)01074-2openalex-snapshot

Predicting plasma protein binding of drugs: a new approach

inferredcites →https://doi.org/10.1021/ci049820bopenalex-snapshot

QSAR Models for the Prediction of Binding Affinities to Human Serum Albumin Using the Heuristic Method and a Support Vector Machine

inferredcites →https://doi.org/10.1021/ed079p524openalex-snapshot

Utilization of SciFinder Scholar at an Undergraduate Institution

inferredcites →https://doi.org/10.1021/jm000407eopenalex-snapshot

Property-Based Design: Optimization of Drug Absorption and Pharmacokinetics

inferredcites →https://doi.org/10.1021/jm010960bopenalex-snapshot

Cheminformatic Models To Predict Binding Affinities to Human Serum Albumin

inferredcites →https://doi.org/10.1021/jm051245vopenalex-snapshot

QSAR Modeling of Human Serum Protein Binding with Several Modeling Techniques Utilizing Structure−Information Representation

inferredcites →https://doi.org/10.1021/jm060981bopenalex-snapshot

Plasma Protein Binding Affinity and Its Relationship to Molecular Structure: An In-silico Analysis

inferredcites →https://doi.org/10.1023/a:1011932516717openalex-snapshot

Species Differences of Serum Albumins: II. Chemical and Thermal Stability

inferredcites →https://doi.org/10.1023/a:1012138604016openalex-snapshot

Species Differences of Serum Albumins: I. Drug Binding Sites

inferredcites →https://doi.org/10.1023/b:modi.0000006562.93049.36openalex-snapshot

In silico prediction of aqueous solubility, human plasma protein binding and volume of distribution of compounds from calculated pKa and AlogP98 values

inferredcites →https://doi.org/10.1111/j.1747-0285.2007.00528.xopenalex-snapshot

ANN‐QSAR Model of Drug‐binding to Human Serum Albumin

inferredcites →https://doi.org/10.1177/026119290503300508openalex-snapshot

QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review

inferredcites →https://doi.org/10.1289/ehp.5758openalex-snapshot

Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs.

inferredcites →https://doi.org/10.1517/17425255.4.6.759openalex-snapshot

Structure – ADME relationship: still a long way to go?

inferredcites →https://doi.org/10.2174/138920008786485065openalex-snapshot

Plasma / Serum Protein Binding Determinations

inferredcites →https://doi.org/10.2174/157018007781788480openalex-snapshot

In Silico Prediction of Human Plasma Protein Binding Using Hologram QSAR

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/minf.201700029openalex-snapshot

Comprehensive Network Map of ADME‐Tox Databases

inferred← citeshttps://doi.org/10.1007/978-3-319-09976-7_12openalex-snapshot

ADMET Prediction Based on Protein Structures

inferred← citeshttps://doi.org/10.1007/s11095-013-1023-6openalex-snapshot

The Use of Pseudo-Equilibrium Constant Affords Improved QSAR Models of Human Plasma Protein Binding

inferred← citeshttps://doi.org/10.1016/b978-0-12-814421-3.00021-xopenalex-snapshot

Computer-Aided Prediction of Pharmacokinetic (ADMET) Properties

inferred← citeshttps://doi.org/10.1016/b978-0-12-814423-7.00011-3openalex-snapshot

Protein and Tissue Binding

inferred← citeshttps://doi.org/10.1016/j.addr.2015.03.011openalex-snapshot

In vitro, in silico and integrated strategies for the estimation of plasma protein binding. A review

inferred← citeshttps://doi.org/10.1016/j.addr.2022.114237openalex-snapshot

Deciphering albumin-directed drug delivery by imaging

inferred← citeshttps://doi.org/10.1016/j.chemolab.2020.103962openalex-snapshot

A novel strategy for prediction of human plasma protein binding using machine learning techniques

inferred← citeshttps://doi.org/10.1016/j.coph.2013.06.001openalex-snapshot

In silico methods to predict drug toxicity

inferred← citeshttps://doi.org/10.1016/j.drudis.2013.04.006openalex-snapshot

Global analytical strategy to measure drug–plasma protein interactions: from high-throughput to in-depth analysis

inferred← citeshttps://doi.org/10.1016/j.ejps.2013.08.020openalex-snapshot

Tissue-to-blood distribution coefficients in the rat: Utility for estimation of the volume of distribution in man

inferred← citeshttps://doi.org/10.1016/j.envadv.2022.100284openalex-snapshot

Rapid determination of serum albumin partition coefficients using affinity chromatography

inferred← citeshttps://doi.org/10.1016/j.ymeth.2015.04.021openalex-snapshot

Virtual screening, ADMET profiling, molecular docking and dynamics approaches to search for potent selective natural molecules based inhibitors against metallothionein-III to study Alzheimer’s disease

inferred← citeshttps://doi.org/10.1017/s0033583515000190openalex-snapshot

In silico ADME/T modelling for rational drug design

inferred← citeshttps://doi.org/10.1039/9781788010139-00281openalex-snapshot

Application of Molecular Modelling to Speed-up the Lead Discovery Process

inferred← citeshttps://doi.org/10.1080/1062936x.2015.1133700openalex-snapshot

Predicting binding affinities of diverse pharmaceutical chemicals to human serum plasma proteins using QSPR modelling approaches

inferred← citeshttps://doi.org/10.1080/17425255.2017.1389897openalex-snapshot

In silicoADME-Tox modeling: progress and prospects

inferred← citeshttps://doi.org/10.1093/bioinformatics/btab726openalex-snapshot

Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning

inferred← citeshttps://doi.org/10.1155/2022/1017341openalex-snapshot

Estimating the Physical Properties of Nanofluids Using a Connectionist Intelligent Model Known as Gaussian Process Regression Approach

inferred← citeshttps://doi.org/10.1186/s13065-018-0417-2openalex-snapshot

Study on the interaction between active components from traditional Chinese medicine and plasma proteins

inferred← citeshttps://doi.org/10.1371/journal.pone.0093323openalex-snapshot

A Structure-Based Model for Predicting Serum Albumin Binding

inferred← citeshttps://doi.org/10.1517/17460441.2013.777424openalex-snapshot

In silicoprediction of human serum albumin binding for drug leads

inferred← citeshttps://doi.org/10.2131/jts.40.77openalex-snapshot

Prediction of genotoxic potential of cosmetic ingredients by an in silico battery system consisting of a combination of an expert rule-based system and a statistics-based system

inferred← citeshttps://doi.org/10.31640/ls-2012-(3-4)-01openalex-snapshot

Квантово-хімічні основи фармакокінетики (огляд літератури та власні дослідження)

inferred← citeshttps://doi.org/10.32598/pbr.8.4.1086.1openalex-snapshot

A Novel Methodology for Human Plasma Protein Binding: Prediction, Validation, and Applicability Domain

inferred← citeshttps://doi.org/10.3390/ijms24031815openalex-snapshot

Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction

inferred← citeshttps://doi.org/10.3390/ph14030202openalex-snapshot

In Silico Plasma Protein Binding Studies of Selected Group of Drugs Using TLC and HPLC Retention Data

inferred← citeshttps://doi.org/10.34172/apb.2023.078openalex-snapshot

A Quantitative Structure-Activity Relationship for Human Plasma Protein Binding: Prediction, Validation and Applicability Domain

inferred← citeshttps://doi.org/10.5772/intechopen.86174openalex-snapshot

ADME Profiling in Drug Discovery and a New Path Paved on Silica

inferred← citeshttps://doi.org/10.70675/562e0758zcff7z49c4za806z3dded388daa0openalex-snapshot

Développement d'une plateforme de prédiction in silico des propriétés ADME-Tox

inferred← citeshttps://doi.org/10.70675/b9dba6ccz7705z4da9zbc0czfb5f99be8d9bopenalex-snapshot

Evaluation des paramètres toxicocinétiques des analogues de bisphénols : développement d'approches de type Relation Quantitative Structure-Activité (QSAR)

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