Molecular Modeling of the Peptide Agonist-binding Site in a Neurokinin-2 Receptor

The neurokinin-2 receptor is a member of the rhodopsin family of G-protein coupled receptors, which represents one of the most relevant target families in small-molecule drug design. NK-2 receptors have been implicated in playing a pathophysiological role in asthma. Activation of the NK-2 receptor by its endogenous peptide agonist, tachykinins, is associated with diverse biological … Continued

Structure of the Complex between Phosphorylated Substrates and the SCF β-TrCP Ubiquitin Ligase Receptor: A Combined NMR, Molecular Modeling, and Docking Approach

The binding of phosphorylated peptides to the receptor plays a major role in many basic cellular processes in a variety of pathological states. Human β-TrCP is a key component of a recently characterized E3 ubiquitin ligase complex that regulates protein degradation through the ubiquitin-dependent proteasome pathway. Docking studies were carried out to explore the structural … Continued

Virtual Screening for R-groups, Including Predicted pIC50 Contributions, within Large Structural Databases, using Topomer CoMFA

Multiple R-groups (monovalent fragments) are implicitly accessible within most of the molecular structures that populate large structural databases. R-group searching would desirably consider pIC50 contribution forecasts as well as ligand similarities or docking scores. However, R-group searching, with or without pIC50 forecasts, is currently not practical. The most prevalent and reliable source of pIC50 predictions, … Continued

Information Theory-based Scoring Function for the Structure-based Prediction of Protein-ligand Binding Affinity

The development and validation of a new knowledge based scoring function (SIScoreJE) to predict binding energy between proteins and ligands is presented. SIScoreJE efficiently predicts the binding energy between a small molecule and its protein receptor. Protein-ligand atomic contact information was derived from a Non-Redundant Data set (NRD) of over 3000 X-ray crystal structures of … Continued

Accurate and Interpretable Computational Modeling of Chemical Mutagenicity

We describe a method for modeling chemical mutagenicity in terms of simple rules based on molecular features. A classification model was built using a rule-based ensemble method called RuleFit, developed by Friedman and Popescu. We show how performance compares favorably against literature methods. Performance was measured through the use of cross-validation and testing on external … Continued

Molecular Docking of Intercalators and Groove-binders to Nucleic Acids Using Autodock and Surflex

The molecular docking tools Autodock and Surflex accurately reproduce the crystallographic structures of a collection of small molecule ligands that have been shown to bind nucleic acids. Docking studies were performed with the intercalators daunorubicin and ellipticine and the minor groove binders distamycin and pentamidine. Autodock and Surflex dock daunorubicin and distamycin to their nucleic … Continued

An Anchor-dependent Molecular Docking Process for Docking Small Flexible Molecules into Rigid Protein Receptors

A molecular docking method designated as ADDock, anchor-dependent molecular docking process for docking small flexible molecules into rigid protein receptors, is presented in this article. ADDock makes the bond connection lists for atoms based on anchors chosen for building molecular structures for docking small flexible molecules or ligands into rigid active sites of protein receptors. … Continued

Hot-spots-guided Receptor-based Pharmacophores (HS-Pharm): A Knowledge-based Approach to Identify Ligand-anchoring Atoms in Protein Cavities and Prioritize Structure-based Pharmacophores

The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. … Continued

Receptor-based Virtual Ligand Screening for the Identification of Novel CDC25 Phosphatase Inhibitors

CDC25 phosphatases play critical roles in cell cycle regulation and are attractive targets for anticancer therapies. Several small non-peptide molecules are known to inhibit CDC25, but many of them appear to form a covalent bond with the enzyme or act through oxidation of the thiolate group of the catalytic cysteine. Structure-based virtual ligand screening computations … Continued

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