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“DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space map**, development and structural interpretation of machine learning models, and indexing of large databases
The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the...
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Iterative machine learning-based chemical similarity search to identify novel chemical inhibitors
Machine learning-based chemical screening has made substantial progress in recent years. However, these predictions often have low accuracy and high...
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TransExION: a transformer based explainable similarity metric for comparing IONS in tandem mass spectrometry
AbstractSmall molecule identification is a crucial task in analytical chemistry and life sciences. One of the most commonly used technologies to...
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Constructing a Complete Set of Homodesmic Reactions Using the Depth-First Search Procedure
AbstractA graph-theoretical algorithm based on the depth-first search (DFS) procedure of graph analysis is proposed for determining a complete set of...
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VSFlow: an open-source ligand-based virtual screening tool
Ligand-based virtual screening is a widespread method in modern drug design. It allows for a rapid screening of large compound databases in order to...
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One chiral fingerprint to find them all
AbstractMolecular fingerprints are indispensable tools in cheminformatics. However, stereochemistry is generally not considered, which is problematic...
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GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES
Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common...
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Sachem: a chemical cartridge for high-performance substructure search
BackgroundStructure search is one of the valuable capabilities of small-molecule databases. Fingerprint-based screening methods are usually employed...
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Interoperable chemical structure search service
MotivationThe existing connections between large databases of chemicals, proteins, metabolites and assays offer valuable resources for research in...
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PIKAChU: a Python-based informatics kit for analysing chemical units
As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of in silico...
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Simplified, interpretable graph convolutional neural networks for small molecule activity prediction
We here present a streamlined, explainable graph convolutional neural network (gCNN) architecture for small molecule activity prediction. We first...
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An algorithm to classify homologous series within compound datasets
Homologous series are groups of related compounds that share the same core structure attached to a motif that repeats to different degrees. Compounds...
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BioisoIdentifier: an online free tool to investigate local structural replacements from PDB
Within the realm of contemporary medicinal chemistry, bioisosteres are empirically used to enhance potency and selectivity, improve adsorption,...
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Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations
Identifying bioactive conformations of small molecules is an essential process for virtual screening applications relying on three-dimensional...
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Prediction of molecular interactions and physicochemical properties relevant for vasopressin V2 receptor antagonism
We have developed two ligand- and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity...
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Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design
Systematic optimization of large macrocyclic peptide ligands is a serious challenge. Here, we describe an approach for lead-optimization using the...
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One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome
BackgroundMolecular fingerprints are essential cheminformatics tools for virtual screening and map** chemical space. Among the different types of...
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Llamol: a dynamic multi-conditional generative transformer for de novo molecular design
AbstractGenerative models have demonstrated substantial promise in Natural Language Processing (NLP) and have found application in designing...
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Systemic evolutionary chemical space exploration for drug discovery
Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening...
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FP-ADMET: a compendium of fingerprint-based ADMET prediction models
MotivationThe absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs plays a key role in determining which among the...
