AIMC Topic: Biological Products

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Machine Learning Methods to Predict the Terrestrial and Marine Origin of Natural Products.

Molecular informatics
In recent years there has been a growing interest in studying the differences between the chemical and biological space represented by natural products (NPs) of terrestrial and marine origin. In order to learn more about these two chemical spaces, ma...

Machine Learning for Biologics: Opportunities for Protein Engineering, Developability, and Formulation.

Trends in pharmacological sciences
Successful biologics must satisfy multiple properties including activity and particular physicochemical features that are globally defined as developability. These multiple properties must be simultaneously optimized in a very broad design space of p...

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...

Development challenges of high concentration monoclonal antibody formulations.

Drug discovery today. Technologies
High concentration monoclonal antibody drug products represent a special segment of biopharmaceuticals. In contrast to other monoclonal antibody products, high concentration monoclonal antibodies are injected subcutaneously helping increase patient c...

Virtual Screening for Reactive Natural Products and Their Probable Artifacts of Solvolysis and Oxidation.

Biomolecules
Chemically unstable natural products are prone to show their reactivity in the procedures of extraction, purification, or identification and turn into contaminants as so-called "artifacts". However, identification of artifacts requires considerable i...

Computational planning of the synthesis of complex natural products.

Nature
Training algorithms to computationally plan multistep organic syntheses has been a challenge for more than 50 years. However, the field has progressed greatly since the development of early programs such as LHASA, for which reaction choices at each s...

Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...

Privileged Scaffold Analysis of Natural Products with Deep Learning-based Indication Prediction Model.

Molecular informatics
Natural products play a vital role in the drug discovery and development process as an important source of reliable and novel lead structures. But the existing criteria for drug leads were usually developed for synthetic compounds and cannot be direc...

The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics.

BMC medical genomics
In this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9-11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this suppl...

A Convolutional Neural Network-Based Approach for the Rapid Annotation of Molecularly Diverse Natural Products.

Journal of the American Chemical Society
This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural produc...