Molecular Discovery Ltd is a software company working in the area of drug discovery.Founded in 1984 by Peter Goodford, its aim was to provide the GRID software to scientists working in the field of Drug Design, and enabled one of the first examples of rational drug design with the discovery of Zanamivir in 1989. In combination with statistical methods such as GOLPE, GRID's method of modeling molecular interaction (known as a "forcefield") can also be used to perform 3D-QSAR.In the last decade, the GRID forcefield has been applied to other areas of drug discovery, including virtual screening, scaffold-hopping, ADME and pharmacokinetic modelling, optimisation of metabolic stability and metabolite prediction, as well as pKa and tautomer modelling.Molecular Discovery manages a Cytochrome P450 Consortium aimed at generating a large set of homogeneous experimental data for human metabolism, allowing the development of predictive in silico models..
Dataset used to develop Deep GRID model
The publisher regrets that in the November 2021 issue, Mathew S. Margolis, a co-author of the above article, was incorrectly excluded from the authorship listings due to a transcription error in production. The corrected authorship listing should appear as below. The publisher would like to apologise for any inconvenience caused. Tammy Than, Christina E. Morettin, Jennifer S. Harthan, Andrew T.E. Hartwick, Julia B. Huecker, Spencer D. Johnson, Mary K. Migneco, Ellen Shorter, Meredith Whiteside, Mathew S. Margolis, Christian K. Olson, Christopher S. Alferez, Tavé van Zyl, Bojana Rodic-Polic, Gregory A. Storch, Mae O. Gordon Efficacy of a Single Administration of 5% Povidone-Iodine in the Treatment of Adenoviral ConjunctivitisAmerican Journal of OphthalmologyVol. 231PreviewHuman adenoviruses are estimated to account for approximately 65%-90% of the viral conjunctivitis cases.1 Adenoviral conjunctivitis (Ad-Cs) is typically associated with significant discomfort, tearing, discharge, lid swelling, and photophobia. More rarely, there can be permanent corneal scarring owing to inflammation. Ad-Cs is highly contagious, as the virus is resistant to standard disinfectants, including 70% isopropyl alcohol and 3% hydrogen peroxide, and can persist on fomites at room temperature for 5-7 weeks. Full-Text PDF
Leishmaniasis is a parasite disease prevalent in 88 nations worldwide, causing high morbidity and mortality in most developing countries. Since no vaccine or pharmaceutical treatment with the best therapeutic window is available, the World Health Organization has listed Leishmaniasis as a priority disease. The enzyme heat shock protein 83 (Hsp83), which is frequently found in cells, catalyzes cellular biological pathways to carry out tasks such as protein folding, intracellular protein trafficking, acquired thermotolerance, differentiation, adaptability, pathogenicity, persistence in the host cell and preventing proteins from being damaged by heat and other stresses. Therefore, HSP actively rewires cellular functions and signalling pathways, which is crucial for cell survival. Inhibition of HSP may interfere with pathogenesis and virulence by impairing several processes. Therefore, L. donovani heat shock protein 83 (LdHsp83) has been suggested as a potential leishmaniasis therapeutic target. Thus, in this study, we built the structure of HSP83 by homology modelling. We used Leishmania primary HSP90 crystal structure (PDB ID 3HJCA) as a template for constructing 3D models of LdHSP83 by comparative modelling approach using SWISS-MODEL, Phyre, GENO 3D program server and Prime 2.1 (Maestro 9.1, Schrodinger 2010) program tool. Based on overall stereochemical quality (PROCHECK, DOPE, Verify 3D), the best model was selected and further used for structural analysis. The energy-minimized, refined and characterized model was further investigated for antileishmanial activity with currently available antileishmanial drugs and enumerated virtual library of chemical compounds through a docking approach. A few combinations, including oxmetidine, had an excellent binding affinity with the Hsp83, as indicated by Glide Score (G Score) and Gold Fitness Score. These potential inhibitors were further studied for SAR and ADMET properties, respectively, by TSAR 3.3 and Qikprop 2.3, indicating the safety and efficacy of these compounds. Once preclinically and clinically examined, these compounds may further be implemented in leishmaniasis therapy.
RATIONALE:Cytochrome P450 (CYP450) reaction phenotyping (CRP) and kinetic studies are essential in early drug discovery to determine which metabolic enzymes react with new drug entities. A new semi-automated computer-assisted workflow for CRP is introduced in this work. This workflow provides not only information regarding parent disappearance, but also metabolite identification and relative metabolite formation rates for kinetic analysis.METHODS:Time-course experiments based on incubating six probe substrates (dextromethorphan, imipramine, buspirone, midazolam, ethoxyresorufin and diclofenac) with recombinant human enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) and human liver microsomes (HLM) were performed. Liquid chromatography/high-resolution mass spectrometry (LC/HRMS) analysis was conducted with an internal standard to obtain high-resolution full-scan and MS/MS data. Data were analyzed using Mass-MetaSite software. A server application (WebMetabase) was used for data visualization and review.RESULTS:CRP experiments were performed, and the data were analyzed using a software-aided approach. This automated-evaluation approach led to (1) the detection of the CYP450 enzymes responsible for both substrate depletion and metabolite formation, (2) the identification of specific biotransformations, (3) the elucidation of metabolite structures based on MS/MS fragment analysis, and (4) the determination of the initial relative formation rates of major metabolites by CYP450 enzymes.CONCLUSIONS:This largely automated workflow enabled the efficient analysis of HRMS data, allowing rapid evaluation of the involvement of the main CYP450 enzymes in the metabolism of new molecules during drug discovery.
One of the key factors in drug discovery is related to the metabolic properties of the lead compound, which may influence the bioavailability of the drug, its therapeutic window, and unwanted side-effects of its metabolites. Therefore, it is of critical importance to enable the fast translation of the experimentally determined metabolic information into design knowledge. The elucidation of the metabolite structure is the most structurally rich and informative end-point in the available range of metabolic assays. A methodology is presented to partially automate the analysis of this experimental information, making the process more efficient. The computer assisted method helps in the chromatographic peak selection and the metabolite structure assignment, enabling automatic data comparison for qualitative applications (kinetic analysis, cross species comparison).
