AI Medical Compendium Journal:
Current computer-aided drug design

Showing 11 to 20 of 23 articles

Identification of Potential Drug Therapy for Dermatofibrosarcoma Protuberans with Bioinformatics and Deep Learning Technology.

Current computer-aided drug design
BACKGROUND: Dermatofibrosarcoma protuberans (DFSP) is a rare mesenchymal tumor that is primarily treated with surgery. Targeted therapy is a promising approach to help reduce the high rate of recurrence. This study aims to identify the potential targ...

Identification of Key Features of CNS Drugs Based on SVM and Greedy Algorithm.

Current computer-aided drug design
INTRODUCTION: The research and development of drugs, related to the central nervous system (CNS) diseases is a long and arduous process with high cost, long cycle and low success rate. Identification of key features based on available CNS drugs is of...

A Drug Decision Support System for Developing a Successful Drug Candidate Using Machine Learning Techniques.

Current computer-aided drug design
BACKGROUND: Virtual screening of candidate drug molecules using machine learning techniques plays a key role in pharmaceutical industry to design and discovery of new drugs. Computational classification methods can determine drug types according to t...

Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Current computer-aided drug design
Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on th...

Virtual Screening Meets Deep Learning.

Current computer-aided drug design
BACKGROUND: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening,...

The Application of Machine Learning Techniques in Clinical Drug Therapy.

Current computer-aided drug design
INTRODUCTION: The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adv...

CAPi: Computational Model for Apicoplast Inhibitors Prediction Against Plasmodium Parasite.

Current computer-aided drug design
BACKGROUND: Discovery of apicoplast as a drug target offers a new direction in the development of novel anti-malarial compounds, especially against the drug-resistant strains. Drugs such as azithromycin were reported to block the apicoplast developme...

5-Year Trends in QSAR and its Machine Learning Methods.

Current computer-aided drug design
BACKGROUND: Quantitative Structure-Activity Relationships (QSAR) is a well-established branch of computational chemistry. The presence of QSAR papers is decreasing for the last few years.