AIMC Topic: Structure-Activity Relationship
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The SAR Matrix Method and an Artificially Intelligent Variant for the Identification and Structural Organization of Analog Series, SAR Analysis, and Compound Design.
Molecular informatics
Apr 20, 2020
The SAR Matrix (SARM) approach was originally conceived for the systematic identification of analog series, their structural organization, and graphical structure-activity relationship (SAR) analysis. For structurally related series, SARMs also produ...
Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.
Pharmacological research
Apr 8, 2020
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...
Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets.
Stroke and vascular neurology
Mar 29, 2020
The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures ...
Deep Learning-driven research for drug discovery: Tackling Malaria.
PLoS computational biology
Feb 18, 2020
Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is ...
Improving the Structure-Function Relationship in Glaucomatous Visual Fields by Using a Deep Learning-Based Noise Reduction Approach.
Ophthalmology. Glaucoma
Jan 11, 2020
PURPOSE: To investigate whether processing visual field (VF) measurements using a variational autoencoder (VAE) improves the structure-function relationship in glaucoma.
Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability.
Journal of chemical information and modeling
Jan 3, 2020
Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chemical structure representation. The classical approach ...
Latest trends in structure based drug design with protein targets.
Advances in protein chemistry and structural biology
Dec 18, 2019
Structure based drug designing is an important endeavor in the field of structural bioinformatics. Previously the entire process was dependent on the wet-lab experiments to build libraries of ligand molecules. And the molecules used to be tested to d...
Machine Learning
Anti-Bacterial Agents
Molecular Docking Simulation
Drug Design
Antineoplastic Agents
Anti-HIV Agents
Protein Binding
Thermodynamics
Structure-Activity Relationship
Humans
Computational Biology
Drugs, Investigational
Molecular Dynamics Simulation
Neuroprotective Agents
Ligands
Proteins
Binding Sites
Synthesis and in vitro activity of asymmetric indole-based bisamidine compounds against Gram-positive and Gram-negative pathogens.
Bioorganic & medicinal chemistry letters
Dec 13, 2019
A series of new asymmetric bisamidine was designed, synthesized, and tested for their in-vitro antibacterial activity using a range of Gram-positive and Gram-negative pathogens. Most compounds demonstrated powerful antibacterial activity, and interes...
Machine learning techniques for protein function prediction.
Proteins
Nov 14, 2019
Proteins play important roles in living organisms, and their function is directly linked with their structure. Due to the growing gap between the number of proteins being discovered and their functional characterization (in particular as a result of ...
Artificial intelligence and big data facilitated targeted drug discovery.
Stroke and vascular neurology
Nov 7, 2019
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...
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