AIMC Topic: Models, Molecular

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Machine Estimation of Drug Melting Properties and Influence on Solubility Prediction.

Molecular pharmaceutics
There has been much recent interest in machine learning (ML) and molecular quantitative structure property relationships (QSPR). The present research evaluated modern ML-based methods implemented in commercial software (COSMOquick and Molecular Model...

The Study on the hERG Blocker Prediction Using Chemical Fingerprint Analysis.

Molecules (Basel, Switzerland)
Human ether-a-go-go-related gene (hERG) potassium channel blockage by small molecules may cause severe cardiac side effects. Thus, it is crucial to screen compounds for activity on the hERG channels early in the drug discovery process. In this study,...

Predicting RNA SHAPE scores with deep learning.

RNA biology
Secondary structure prediction approaches rely typically on models of equilibrium free energies that are themselves based on in vitro physical chemistry. Recent transcriptome-wide experiments of in vivo RNA structure based on SHAPE-MaP experiments pr...

Learning Molecular Representations for Medicinal Chemistry.

Journal of medicinal chemistry
The accurate modeling and prediction of small molecule properties and bioactivities depend on the critical choice of molecular representation. Decades of informatics-driven research have relied on expert-designed molecular descriptors to establish qu...

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...

Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo-Electron Microscopy Maps.

Angewandte Chemie (International ed. in English)
In recent years, three-dimensional density maps reconstructed from single particle images obtained by electron cryo-microscopy (cryo-EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the const...

Matched Molecular Series Analysis for ADME Property Prediction.

Journal of chemical information and modeling
Generation and prioritization of new molecules are the most central part of the drug design process. Matched molecular series analysis (MMSA) has recently been proposed as a formal approach that captures both of these key elements of design. In order...

Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions.

Journal of computer-aided molecular design
Difficulties in interpreting machine learning (ML) models and their predictions limit the practical applicability of and confidence in ML in pharmaceutical research. There is a need for agnostic approaches aiding in the interpretation of ML models re...

Machine Learning Approaches for Quality Assessment of Protein Structures.

Biomolecules
Protein structures play a very important role in biomedical research, especially in drug discovery and design, which require accurate protein structures in advance. However, experimental determinations of protein structure are prohibitively costly an...