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Drug Design

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Sequence-based analysis and prediction of lantibiotics: A machine learning approach.

Computational biology and chemistry
Lantibiotics, an important group of ribosomally synthesized peptides, represent an important arsenal of novel promising antimicrobials showing high potency in fighting against the prevalence of antibiotic resistance among microbial pathogens. However...

Deep Learning in Drug Discovery and Medicine; Scratching the Surface.

Molecules (Basel, Switzerland)
The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned f...

Comparison of multi-linear regression, particle swarm optimization artificial neural networks and genetic programming in the development of mini-tablets.

International journal of pharmaceutics
In the present study, the preparation of pharmaceutical mini-tablets was attempted in the framework of Quality by Design (QbD) context, by comparing traditionally used multi-linear regression (MLR), with artificially-intelligence based regression tec...

Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...

Conditional Molecular Design with Deep Generative Models.

Journal of chemical information and modeling
Although machine learning has been successfully used to propose novel molecules that satisfy desired properties, it is still challenging to explore a large chemical space efficiently. In this paper, we present a conditional molecular design method th...

Deep reinforcement learning for de novo drug design.

Science advances
We have devised and implemented a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcement Learning for Structural Evolution). On the basis of deep and reinforcement learning (RL) approaches, ...

Artificial intelligence in drug design.

Science China. Life sciences
Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology, the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and devel...

Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy.

Journal of proteome research
Cell-penetrating peptides (CPPs) can enter cells as a variety of biologically active conjugates and have various biomedical applications. To offset the cost and effort of designing novel CPPs in laboratories, computational methods are necessitated to...