Docking with AutoDock4.

AutoDock is one of the most popular receptor-ligand docking simulation programs. It was first released in the early 1990s and is in continuous development and adapted to specific protein targets. AutoDock has been applied to a wide range of biological systems.

Development of CDK-targeted scoring functions for prediction of binding affinity.

Cyclin-dependent kinase (CDK) is an interesting biological macromolecule due to its role in cell cycle progression, transcription control, and neuronal development, to mention the most studied biological activities. Furthermore, the availability of hundreds of structural studies focused on the intermolecular interactions of CDK with competitive inhibitors makes possible to develop computational models to predict binding affinity, where the atomic coordinates of binary complexes involving CDK and ligands can be used to train a machine learning model. The present work is focused on the development of new machine learning models to predict binding affinity for CDK.

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) for which half-maximal inhibitory concentration (IC) data is available.

Supervised Machine Learning Methods Applied to Predict Ligand- Binding Affinity.

Background: Calculation of ligand-binding affinity is an open problem in computational medicinal chemistry. The ability to computationally predict affinities has a beneficial impact in the early stages of drug development, since it allows a mathematical model to assess protein-ligand interactions. Due to the availability of structural and binding information, machine learning methods have been applied to generate scoring functions with good predictive power.

Understanding the Structural Basis for Inhibition of Cyclin-Dependent Kinases. New Pieces in the Molecular Puzzle.

Background: Cyclin-dependent kinases (CDKs) comprise an important protein family for development of drugs, mostly aimed for use in treatment of cancer but there is also potential for development of drugs for neurodegenerative diseases and diabetes. Since the early 1990s, structural studies have been carried out on CDKs, in order to determine the structural basis for inhibition of this protein target.

Objective: Our goal here is to review recent structural studies focused on CDKs.

SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions.

Background: Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the leads that were later developed as drugs.