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Drug Design

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Accelerating Drug Design against Novel Proteins Using Deep Learning.

Journal of chemical information and modeling
In the world plagued by the emergence of new diseases, it is essential that we accelerate the drug design process to develop new therapeutics against them. In recent years, deep learning-based methods have shown some success in ligand-based drug desi...

A comprehensive comparison of molecular feature representations for use in predictive modeling.

Computers in biology and medicine
Machine learning methods are commonly used for predicting molecular properties to accelerate material and drug design. An important part of this process is deciding how to represent the molecules. Typically, machine learning methods expect examples r...

OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design.

Journal of chemical information and modeling
Deep learning models have demonstrated outstanding results in many data-rich areas of research, such as computer vision and natural language processing. Currently, there is a rise of deep learning in computational chemistry and materials informatics,...

Multi-objective optimization methods in novel drug design.

Expert opinion on drug discovery
: In multi-objective drug design, optimization gains importance, being upgraded to a discipline that attracts its own research. Current strategies are broadly classified into single - objective optimization (SOO) and multi-objective optimization (MOO...

Improved Deep Learning Based Method for Molecular Similarity Searching Using Stack of Deep Belief Networks.

Molecules (Basel, Switzerland)
Virtual screening (VS) is a computational practice applied in drug discovery research. VS is popularly applied in a computer-based search for new lead molecules based on molecular similarity searching. In chemical databases similarity searching is us...

Design of novel orotransmucosal vaccine-delivery platforms using artificial intelligence.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
The linings of the oral cavity are excellent needle-free vaccination sites, able to induce immune responses at distal sites and confer systemic protection. However, owing to the mucosal tissues' intrinsic characteristics, the design of effective anti...

AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning.

Journal of chemical information and modeling
Molecular scaffolds are widely used in drug design. Many methods and tools have been developed to utilize the information in scaffolds. Scaffold diversification is frequently used by medicinal chemists in tasks such as lead compound optimization, but...

Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.

International journal of molecular sciences
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...

Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural networks using simple molecular descriptors.

Bioorganic chemistry
Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inp...

Scaffold-Constrained Molecular Generation.

Journal of chemical information and modeling
One of the major applications of generative models for drug discovery targets the lead-optimization phase. During the optimization of a lead series, it is common to have scaffold constraints imposed on the structure of the molecules designed. Without...