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MS-WHIM Scores for Amino Acids: A New 3D-Description for Peptide QSAR and QSPR Studies
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Outgoing claims: the papers this work cites, builds on, or argues with.
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The Quantitative Description of Amino Acid, Peptide, and Protein Properties and Bioactivities
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New molecular descriptors for 2D and 3D structures. Theory
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Amino Acids Characterization by GRID and Multivariate Data Analysis
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Contribution of Hydration to Protein Folding Thermodynamics
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Neural Network Model of the Genetic Code is Strongly Correlated to the GES Scale of Amino Acid Transfer Free Energies
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Die Funktion des Arginins in den Enzymen
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Statistical analysis of the physical properties of the 20 naturally occurring amino acids
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Tertiary templates for proteins
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Relations between chemical structure and biological activity in peptides
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Modeling and prediction by using whim descriptors in QSAR studies: toxicity of heterogeneous chemicals on Daphnia magna
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Weighted holistic invariant molecular descriptors. Part 2. Theory development and applications on modeling physicochemical properties of polyaromatic hydrocarbons
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Affinities of amino acid side chains for solvent water
inferredcites →https://doi.org/10.1021/jm00014a022openalex-snapshot
Amino Acid Side Chain Descriptors for Quantitative Structure-Activity Relationship Studies of Peptide Analogs
inferredcites →https://doi.org/10.1021/jm00145a002openalex-snapshot
A computational procedure for determining energetically favorable binding sites on biologically important macromolecules
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Comparative computer graphics and solution studies of the DNA interaction of substituted anthraquinones based on doxorubicin and mitoxantrone
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Peptide quantitative structure-activity relationships, a multivariate approach
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C3-Methylated 5-hydroxy-2-(dipropylamino)tetralins: conformational and steric parameters of importance for central dopamine receptor activation
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MS-WHIM, new 3D theoretical descriptors derived from molecular surface properties: A comparative 3D QSAR study in a series of steroids
inferredcites →https://doi.org/10.1023/a:1008142124682openalex-snapshot
Global 3D-QSAR methods: MS-WHIM and autocorrelation
inferredcites →https://doi.org/10.3891/acta.chem.scand.40b-0135openalex-snapshot
The Prediction of Bradykinin Potentiating Potency of Pentapeptides. An Example of a Peptide Quantitative Structure-activity Relationship.
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Machine learning methods for unveiling the potential of antioxidant short peptides in goat milk-derived proteins during in vitro gastrointestinal digestion
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Ensemble-AHTPpred: A Robust Ensemble Machine Learning Model Integrated With a New Composite Feature for Identifying Antihypertensive Peptides
inferred← citeshttps://doi.org/10.3389/fimmu.2024.1426173openalex-snapshot
TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets
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Molecular Mingling: Multimodal Predictions of Ligand Promiscuity in Pentameric Ligand-Gated Ion Channels
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What Makes GPCRs from Different Families Bind to the Same Ligand?
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Sequence–Activity Relationship of Angiotensin-Converting Enzyme Inhibitory Peptides Derived from Food Proteins, Based on a New Deep Learning Model
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QSAR Implementation for HIC Retention Time Prediction of mAbs Using Fab Structure: A Comparison between Structural Representations
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Ensemble of Multiple Classifiers for Multilabel Classification of Plant Protein Subcellular Localization
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EnsembleNPPred: A Robust Approach to Neuropeptide Prediction and Recognition Using Ensemble Machine Learning and Deep Learning Methods
inferred← citeshttps://doi.org/10.3390/molecules24152846openalex-snapshot
Quantitative Structure–Activity Relationship Study of Bitter Di-, Tri- and Tetrapeptides Using Integrated Descriptors
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Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review
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NbX: Machine Learning-Guided Re-Ranking of Nanobody–Antigen Binding Poses
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Traditional and Computational Screening of Non-Toxic Peptides and Approaches to Improving Selectivity
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HomoSAR: An Integrated Approach Using Homology Modeling and Quantitative Structure-Activity Relationship for Activity Prediction of Peptides
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Study of Peptides QSAR Based on Multidimensional Attributes (E) Using Multiple Linear Regression
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AbSolution: interactive exploration of sequence-derived features in AIRR-seq repertoires
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Applications of proteochemometrics (PCM) : from species extrapolation to cell-line sensitivity modelling
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A deep learning based ensemble approach for protein allergen classification
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