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BetaDL: A protein beta-sheet predictor utilizing a deep learning model and independent set solution.

Computers in biology and medicine
The sequence-based prediction of beta-residue contacts and beta-sheet structures contain key information for protein structure prediction. However, the determination of beta-sheet structures poses numerous challenges due to long-range beta-residue in...

A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.

Scientific reports
Directed evolution is an important research activity in synthetic biology and biotechnology. Numerous reports describe the application of tedious mutation/screening cycles for the improvement of proteins. Recently, knowledge-based approaches have fac...

Two New Heuristic Methods for Protein Model Quality Assessment.

IEEE/ACM transactions on computational biology and bioinformatics
Protein tertiary structure prediction is an important open challenge in bioinformatics and requires effective methods to accurately evaluate the quality of protein 3-D models generated computationally. Many quality assessment (QA) methods have been p...

Dihydropteroate synthase based sensor for screening multi-sulfonamides residue and its comparison with broad-specific antibody based immunoassay by molecular modeling analysis.

Analytica chimica acta
A biosensor that could simultaneously detect multi-analyte as many as in a single test is more favored when facing lots of samples for screening purpose. In such a biosensor, the recognition element with broad specificity and highly affinity is a key...

TopScore: Using Deep Neural Networks and Large Diverse Data Sets for Accurate Protein Model Quality Assessment.

Journal of chemical theory and computation
The value of protein models obtained with automated protein structure prediction depends primarily on their accuracy. Protein model quality assessment is thus critical to select the model that can best answer biologically relevant questions from an e...

Perturbation Theory-Machine Learning Study of Zeolite Materials Desilication.

Journal of chemical information and modeling
Zeolites are important materials for research and industrial applications. Mesopores are often introduced by desilication but other properties are also affected, making its optimization difficult. In this work, we demonstrate that Perturbation Theory...

Extraction, identification and structure-activity relationship of antioxidant peptides from sesame (Sesamum indicum L.) protein hydrolysate.

Food research international (Ottawa, Ont.)
To elucidate the sequence, origin and structure-activity relationship of antioxidant peptides from sesame protein, sesame protein was hydrolysed by a dual-enzyme system comprised alcalase and trypsin, then this hydrolysate was fractionated by ultrafi...

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery.

Journal of chemical information and modeling
The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, method comparison is difficult because of various flaws of the currently employed evaluation metrics. We...

Algorithmic Analysis of Cahn-Ingold-Prelog Rules of Stereochemistry: Proposals for Revised Rules and a Guide for Machine Implementation.

Journal of chemical information and modeling
The most recent version of the Cahn-Ingold-Prelog rules for the determination of stereodescriptors as described in Nomenclature of Organic Chemistry: IUPAC Recommendations and Preferred Names 2013 (the "Blue Book"; Favre and Powell. Royal Society of ...

Insight Analysis of Promiscuous Estrogen Receptor α-Ligand Binding by a Novel Machine Learning Scheme.

Chemical research in toxicology
Estrogen receptor α (ERα) plays a significant role in occurrence of breast cancer and may cause various adverse side-effects when ERα is an off-target protein. A theoretical model was derived to predict the binding affinity of ERα using the pharmacop...