A5014283781- Computational Drug Discovery Methods
- Metabolomics and Mass Spectrometry Studies
- Analytical Chemistry and Chromatography
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Apelin-related biomedical research
- Crystallization and Solubility Studies
- Historical Economic and Social Studies
- Receptor Mechanisms and Signaling
- Genetics, Bioinformatics, and Biomedical Research
- Cardiovascular, Neuropeptides, and Oxidative Stress Research
- Molecular spectroscopy and chirality
- American Constitutional Law and Politics
- Microbial Metabolic Engineering and Bioproduction
- Chemical Synthesis and Analysis
- Spectroscopy and Chemometric Analyses
- Gut microbiota and health
- Machine Learning in Bioinformatics
- Nuclear Receptors and Signaling
- Machine Learning in Materials Science
- Gene expression and cancer classification
- Pharmacogenetics and Drug Metabolism
- X-ray Diffraction in Crystallography
- Microbial Natural Products and Biosynthesis
- Mass Spectrometry Techniques and Applications
University of Cambridge
2015-2024
Imperial College London
2015-2024
Shiraz University
2023-2024
Kyoto Pharmaceutical University
2022
University of Ljubljana
2022
The London College
2022
Addenbrooke's Hospital
2015-2019
Transnational Press London
2017
Papworth Hospital
2017
Unilever (United Kingdom)
2007-2016
Gut microbiota composition and function are symbiotically linked with host health altered in metabolic, inflammatory neurodegenerative disorders. Three recognised mechanisms exist by which the microbiome influences gut-brain axis: modification of autonomic/sensorimotor connections, immune activation, neuroendocrine pathway regulation. We hypothesised interactions between circulating gut-derived microbial metabolites, blood-brain barrier (BBB) also contribute to axis. Propionate, produced...
Random Forest regression (RF), Partial-Least-Squares (PLS) regression, Support Vector Machines (SVM), and Artificial Neural Networks (ANN) were used to develop QSPR models for the prediction of aqueous solubility, based on experimental data 988 organic molecules. The model predicted solubility more accurately than those created by PLS, SVM, ANN offered methods automatic descriptor selection, an assessment importance, in-parallel measure predictive ability, all which serve recommend its use....
Elabela/toddler (ELA) is a critical cardiac developmental peptide that acts through the G-protein-coupled apelin receptor, despite lack of sequence similarity to established ligand apelin. Our aim was investigate receptor pharmacology, expression pattern, and in vivo function ELA peptides adult cardiovascular system, seek evidence for alteration pulmonary arterial hypertension (PAH) which signaling downregulated, demonstrate attenuation PAH severity with exogenous administration rat model.In...
Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells associated with increased tubule-interstitial fibrosis in patient autopsy samples. To study effects virus on independent systemic infected human-induced pluripotent stem-cell-derived organoids SARS-CoV-2. Single-cell RNA sequencing indicated injury dedifferentiation activation profibrotic signaling...
Communication between the gut microbiota and brain is primarily mediated via soluble microbe-derived metabolites, but details of this pathway remain poorly defined. Methylamines produced by microbial metabolism dietary choline L-carnitine have received attention due to their proposed association with vascular disease, effects upon cerebrovascular circulation hitherto not been studied.
We report the results of COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. discovered noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, high-throughput structural biology chemistry. generated...
A molecular similarity searching technique based on atom environments, information-gain-based feature selection, and the naive Bayesian classifier has been applied to a series of diverse datasets its performance compared those alternative methods. Atom environments are count vectors heavy atoms present at topological distance from each structure. In this application, using recently published dataset more than 100000 molecules MDL Drug Data Report database, environment approach appears...
A novel technique for similarity searching is introduced. Molecules are represented by atom environments, which fed into an information-gain-based feature selection. naïve Bayesian classifier then employed compound classification. The new method tested its ability to retrieve five sets of active molecules seeded in the MDL Drug Data Report (MDDR). In comparison experiments, algorithm outperforms all current retrieval methods assessed here using two- and three-dimensional descriptors offers...
We have produced an open source, freely available, algorithm (Open Parser for Systematic IUPAC Nomenclature, OPSIN) that interprets the majority of organic chemical nomenclature in a fast and precise manner. This has been achieved using approach based on regular grammar. grammar is used to guide tokenization, potentially difficult problem names. From parsed name, XML parse tree constructed operated stepwise manner until structure reconstructed from name. Results OPSIN various computer...
Solubility is a key physicochemical property of molecules. Serious deficiencies exist in the consistency and reliability solubility data literature. The accurate prediction would be very useful. However, systematic errors lack metadata associated with measurements greatly reduce confidence current models. To address this, we are accurately measuring intrinsic values, here report results for diverse set 100 druglike molecules at 25 °C an ionic strength 0.15 M using CheqSol approach. This...
We have performed virtual screening using some very simple features, by employing the number of atoms per element as molecular descriptors but without regard to any structural information whatsoever. Surprisingly, these atom counts are able outperform virtual-affinity-based fingerprints and Unity in activity classes. Although weight other biases were known target-based settings (docking), we report effect for ligand-based screening, clearly defined biological targets a large data set (>100...
In this study, two probabilistic machine-learning algorithms were compared for in silico target prediction of bioactive molecules, namely the well-established Laplacian-modified Naïve Bayes classifier (NB) and more recently introduced (to Cheminformatics) Parzen-Rosenblatt Window. Both classifiers trained conjunction with circular fingerprints on a large data set compounds extracted from ChEMBL, covering 894 human protein targets than 155,000 ligand-protein pairs. This is also provided as...
[Pyr(1)]apelin-13 is an endogenous vasodilator and inotrope but downregulated in pulmonary hypertension heart failure, making the apelin receptor attractive therapeutic target. Agonists acting at same G-protein-coupled can be engineered to stabilize different conformational states function as biased ligands, selectively stimulating either G-protein or β-arrestin pathways. We used molecular dynamics simulations of apelin/receptor interactions design cyclic analogues identified MM07 a agonist....
Metabolomics is the comprehensive study of a multitude small molecules to gain insight into an organism's metabolism. The research field dynamic and expanding with applications across biomedical, biotechnological, many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, repositories, analysis tools. However, rapid progress resulted in mosaic independent, sometimes incompatible, methods that are difficult connect useful...
Imaging using 3-D DESI mass spectral data combined with deep learning reveals the topology and heterogeneity of colorectal cancer.
Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making largely unknown. Using the iKnife to sample aerosol of cauterized specimens, we demonstrate a new mode real-time diagnosis, coupling metabolic phenotype mutant PIK3CA genotype. results an increase arachidonic acid and concomitant overproduction eicosanoids, acting promote cell proliferation beyond...