AI Medical Compendium Topic:
Molecular Docking Simulation

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Sequence assignment for low-resolution modelling of protein crystal structures.

Acta crystallographica. Section D, Structural biology
The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for...

Combined Ensemble Docking and Machine Learning in Identification of Therapeutic Agents with Potential Inhibitory Effect on Human CES1.

Molecules (Basel, Switzerland)
The human carboxylesterase 1 (CES1), responsible for the biotransformation of many diverse therapeutic agents, may contribute to the occurrence of adverse drug reactions and therapeutic failure through drug interactions. The present study is designed...

AGL-Score: Algebraic Graph Learning Score for Protein-Ligand Binding Scoring, Ranking, Docking, and Screening.

Journal of chemical information and modeling
Although algebraic graph theory-based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in the analysis and prediction of biomolecular properties, confirming the common belief that "one cannot ...

Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function.

Journal of cellular biochemistry
Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleotide polymorphisms (SNPs) using wet laboratory experiments is an arduous task hence the computational ...

Analysis of the Deleterious Single Nucleotide Polymorphisms Impact on Estrogen Receptor Alpha-p53 Interaction: A Machine Learning Approach.

International journal of molecular sciences
Breast cancer is a leading cancer type and one of the major health issues faced by women around the world. Some of its major risk factors include body mass index, hormone replacement therapy, family history and germline mutations. Of these risk facto...

A Structure-Based Drug Discovery Paradigm.

International journal of molecular sciences
Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for fut...

Machine Learning Models Combined with Virtual Screening and Molecular Docking to Predict Human Topoisomerase I Inhibitors.

Molecules (Basel, Switzerland)
In this work, random forest (RF), support vector machine, k-nearest neighbor and C4.5 decision tree, were used to establish classification models for predicting whether an unknown molecule is an inhibitor of human topoisomerase I (Top1) protein. All ...

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs.

Molecules (Basel, Switzerland)
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Muc...

Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.

ChemMedChem
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...

Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space.

Structure (London, England : 1993)
Flexibility is often a key determinant of protein function. To elucidate the link between their molecular structure and role in an organism, computational techniques such as molecular dynamics can be leveraged to characterize their conformational spa...