Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites.

The coronavirus disease 2019 (COVID-19) pandemic has spurred a wide range of approaches to control and combat the disease. However, selecting an effective antiviral drug target remains a time-consuming challenge. Computational methods offer a promising solution by efficiently reducing the number of candidates.

Characterization of the mechanism of bile salt hydrolase substrate specificity by experimental and computational analyses.

Bile salt hydrolases (BSHs) are currently being investigated as target enzymes for metabolic regulators in humans and as growth promoters in farm animals. Understanding structural features underlying substrate specificity is necessary for inhibitor design. Here, we used a multidisciplinary workflow including mass spectrometry, mutagenesis, molecular dynamic simulations, machine learning, and crystallography to demonstrate substrate specificity in Lactobacillus salivarius BSH, the most abundant enzyme in human and farm animal intestines.

Intermolecular Interactions in G Protein-Coupled Receptor Allosteric Sites at the Membrane Interface from Molecular Dynamics Simulations and Quantum Chemical Calculations.

Allosteric modulators are called promising candidates in G protein-coupled receptor (GPCR) drug development by displaying subtype selectivity and more specific receptor modulation. Among the allosteric sites known to date, cavities at the receptor-lipid interface represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability, the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze interactions in the allosteric sites of the PAR2, C5aR1, and GCGR receptors in three lipid compositions using molecular dynamics simulations.

Ureas derived from camphor and fenchone reveal enantiomeric preference of human soluble epoxide hydrolase.

The soluble epoxide hydrolase (sEH) is a potential target to treat cardiovascular, renal and neuronal diseases. A series of sEH inhibitors containing naturally occurring lipophilic groups (originating from camphor and fenchone) were developed. Inhibitory potency ranging from 0.

Probe Confined Dynamic Mapping for G Protein-Coupled Receptor Allosteric Site Prediction.

Targeting G protein-coupled receptors (GPCRs) through allosteric sites offers advantages over orthosteric sites in identifying drugs with increased selectivity and potentially reduced side effects. In this study, we developed a probe confined dynamic mapping protocol that allows the prediction of allosteric sites at both the GPCR extracellular and intracellular sides, as well as at the receptor-lipid interface. The applied harmonic wall potential enhanced sampling of probe molecules in a selected area of a GPCR while preventing membrane distortion in molecular dynamics simulations.

A Facile Approach to Bis(isoxazoles), Promising Ligands of the AMPA Receptor.

A convenient synthetic approach to novel functionalized bis(isoxazoles), the promising bivalent ligands of the AMPA receptor, was elaborated. It was based on the heterocyclization reactions of readily available electrophilic alkenes with the tetranitromethane-triethylamine complex. The structural diversity of the synthesized compounds was demonstrated.

Baseline Model for Predicting Protein-Ligand Unbinding Kinetics through Machine Learning.

Derivation of structure-kinetics relationships can help rational design and development of new small-molecule drug candidates with desired residence times. Efforts are now being directed toward the development of efficient computational methods. Currently, there is a lack of solid, high-throughput binding kinetics prediction approaches on bigger datasets.

Bioisosteric substitution of adamantane with bicyclic lipophilic groups improves water solubility of human soluble epoxide hydrolase inhibitors.

A series of inhibitors of the soluble epoxide hydrolase (sEH) containing lipophilic groups of natural origin (camphanyl, norcamphanyl, furan-2-yl) were developed. Inhibitory potency ranging from 0.4 nM to 2.

graphDelta: MPNN Scoring Function for the Affinity Prediction of Protein-Ligand Complexes.

In this work, we present graph-convolutional neural networks for the prediction of binding constants of protein-ligand complexes. We derived the model using multi task learning, where the target variables are the dissociation constant ( ), inhibition constant ( ), and half maximal inhibitory concentration (IC). Being rigorously trained on the PDBbind dataset, the model achieves the Pearson correlation coefficient of 0.

Imidazolidine-2,4,5- and pirimidine-2,4,6-triones - New primary pharmacophore for soluble epoxide hydrolase inhibitors with enhanced water solubility.

A series of inhibitors of the soluble epoxide hydrolase (sEH) containing imidazolidine-2,4,5-trione or pirimidine-2,4,6-trione has been synthesized. Inhibition potency of the described compounds ranges from 8.4 μM to 0.

Bivalent AMPA receptor positive allosteric modulators of the bis(pyrimidine) series.

The first example of a novel class of AMPA receptor positive allosteric modulators of the bis(pyrimidine) series having a hydroquinone linker has been obtained and showed a potency to increase kainate-induced currents at subnanomolar concentrations.

Novel Positive Allosteric Modulators of AMPA Receptors Based on 3,7-Diazabicyclo[3.3.1]nonane Scaffold.

A series of new positive allosteric modulators (PAMs) of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors based on 3,7-diazabicyclo[3.3.1]nonane scaffold have been designed, synthesized, and analyzed.

Computational characterization of the glutamate receptor antagonist perampanel and its close analogs: density functional exploration of conformational space and molecular docking study.

Perampanel approved by FDA in 2012 is a first-in-class antiepileptic drug which inhibits α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor currents. It is markedly more active than many of its close analogs, and the reasons for this activity difference are not quite clear. Recent crystallographic studies allowed the authors to identify the location of its binding site.

Chemical space exploration guided by deep neural networks.

A parametric t-SNE approach based on deep feed-forward neural networks was applied to the chemical space visualization problem. It is able to retain more information than certain dimensionality reduction techniques used for this purpose (principal component analysis (PCA), multidimensional scaling (MDS)). The applicability of this method to some chemical space navigation tasks (activity cliffs and activity landscapes identification) is discussed.

Comparative Study of Multitask Toxicity Modeling on a Broad Chemical Space.

Acute toxicity is one of the most challenging properties to predict purely with computational methods due to its direct relationship to biological interactions. Moreover, toxicity can be represented by different end points: it can be measured for different species using different types of administration, etc., and it is questionable if the knowledge transfer between end points is possible.

Adamantyl thioureas as soluble epoxide hydrolase inhibitors.

A series of inhibitors of the soluble epoxide hydrolase (sEH) containing one or two thiourea groups has been developed. Inhibition potency of the described compounds ranges from 50 μM to 7.2 nM.

Cytokinin activity of N-benzyladenine derivatives assayed by interaction with the receptors in planta, in vitro, and in silico.

Biological effects of hormones in both plants and animals are based on high-affinity interaction with cognate receptors resulting in their activation. The signal of cytokinins, classical plant hormones, is perceived in Arabidopsis by three homologous membrane receptors: AHK2, AHK3, and CRE1/AHK4. To study the cytokinin-receptor interaction, we used 25 derivatives of potent cytokinin N-benzyladenine (BA) with substituents in the purine heterocycle and/or in the side chain.