GPCR molecular research
Membrane proteins
in particular G protein-coupled receptors (GPCRs), are the most important drug targets. As an example, about 40% of the clinically used drugs are targeting GPCRs.
In some pharmaceutical companies, this figure can be even as high as 70-80%. Therefore, the understanding of membrane protein functions is of fundamental importance for modern drug discovery.
AlphaMol
Our team members have made important contributions to understand receptor mediated signalling at the molecular level. They have published many innovative works in top journals including Cell, Nature,
Nature Communications, Chemical Science, Trends in Biochemical Sciences, Angewandte Chemie and others.
Publication
Time
Dissertation
Periodical
Link
2024
The structure and function of olfactory receptors
Trends in Pharm Sci
https://doi.org/10.1016/j.tips.2024.01.004
2023
Molecular basis of ligand selectivity for melatonin receptors
RSC Adv
https://doi.org/10.1039/D2RA06693A
2021
The role of metal ions in GPCR signaling and drug discovery
Computational Molecular Science
https://doi.org/10.1002/WCMS.1565
2020
Structural basis of CXC chemokine receptor 2 activation and signalling
Nature
https://doi.org/10.1038/s41586-020-2492-5
2020
Activation and Signaling Mechanism Revealed by Cannabinoid Receptor-Gi Complex Structures
Cell
https://doi.org/10.1016/j.cell.2020.01.008
2020
Enhancing the Signaling of GPCRs via Orthosteric Ions
ACS Central Science
https://doi.org/10.1021/acscentsci.9b01247
2019
New binding sites, new opportunities for GPCR drug discovery
Trends in Biochemical Sciences
https://doi.org/10.1016/j.tibs.2018.11.011
2018
Exploring a new ligand binding site of G protein-coupled receptors
Chemical Science
https://doi.org/10.1039/C8SC01680A
2019
New binding sites, new opportunities for GPCR drug discovery
Trends in Biochemical Sciences
https://doi.org/10.1016/j.tibs.2018.11.011
2018
5-HT2C Receptor Structures Reveal the Structural Basis of GPCR Polypharmacology
Cell
https://doi.org/10.1016/j.cell.2018.01.001
2017
Designing Safer Analgesics via µ-Opioid Receptor Pathways
Trends in Pharmacological Sciences
https://doi.org/10.1016/j.tips.2017.08.004
2016
Mechanistic Studies on the Stereoselectivity of the Serotonin 5-HT1A Receptor
Angewandte Chemie Int Ed Engl
https://doi.org/10.1002/anie.201603766
2016
The Molecular Mechanism of P2Y1 Receptor Activation
Angewandte Chemie Int Ed Engl
https://doi.org/10.1002/anie.201605147
2015
The Mechanism of Ligand-Induced Activation or Inhibition of mu- and kappa-Opioid Receptors
Angewandte Chemie Int Ed Engl
https://doi.org/10.1002/anie.201501742
2014
W246 Opens a Gate for a Continuous Intrinsic Water Pathway during Activation of the Adenosine A Receptor
Angewandte Chemie Int Ed Engl
https://doi.org/10.1002/anie.201409679
2014
Activation of G-protein-coupled receptors correlates with the formation of a continuous internal water pathway
Nature Communications
https://doi.org/10.1038/ncomms5733
2014
Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges
Structure
https://doi.org/10.1016/j.str.2014.06.012
Innovative GPCR biotesting
G protein-coupled receptors
G protein-coupled receptors (GPCRs) are the most important drug targets, of which about 40% of the marketed drugs are targeting GPCRs.
As a membrane protein, the biological activity testing for GPCR drug discovery is still a challenging task. Many difficulties remain to be resolved including: (1) testing drug activity without labeling (2) measuring GPCR/G-protein interaction directly instead of determining that of cAMP or Ca2+ signaling in an indirect way (3) measuring kinetic properties of GPCR drug molecules and (4) differentiating G protein types inside cells.
In this regard, the team member of AlphaMol developed a series of innovative biochip technologies to overcome the hurdle in GPCR drug discovery in the past 20 years. Such breakthrough facilitates the process of GPCR drug discovery in a much more accurate and efficient way.
Publication
Time
Dissertation
Periodical
Link
2018
Single-vesicle assays using liposomes and cell-derived vesicles: from modeling complex membrane processes to synthetic biology and biomedical applications
Chemical reviews
https://doi.org/10.1021/acs.chemrev.7b00777
2011
Activation of G-protein-coupled receptors in cell-derived plasma membranes supported on porous beads
JACS
https://doi.org/10.1021/ja205302g
1999
Micropatterned immobilization of a G protein–coupled receptor and direct detection of G protein activation
Nature Biotechnology
https://doi.org/10.1038/15090
1998
Incorporation of Rhodopsin in Laterally Structured Supported Membranes:  Observation of Transducin Activation with Spatially and Time-Resolved Surface Plasmon Resonance†
Biochemistry
https://doi.org/10.1021/bi971564r
New drug discovery
AlphaMol
Modern drug discovery and development is a complicated process, which costs about $2-3 billion and lasts for 12 years on average. How to decrease the costs and speed up the process is the challenge. Computational biology and Artificial Intelligence, combined with new technologies in experimental drug screening, are expected to make the hunt for new drugs quicker, cheaper and more efficient.
Our team has established a sophisticated computer-aided drug discovery platform, which combines Artificial Intelligence, WebGL, cloud computing and big data. It can perform a wide range of drug discovery tasks such as molecular generation, virtual screening, lead optimization, drug property optimization, molecular dynamics simulation, accurate binding energy prediction and others. We have applied our tools successfully to discover and design potent drug candidates for various targets.
Members of our team have the experience of advancing designed molecules into clinical trials. More recently, we discovered a series of potent compounds for different orphan receptors. These compounds could result in "me-only" drug candidates.
Publication
Time
Dissertation
Periodical
Link
2024
Computational drug development for membrane protein targets
Nature Biotechnology
https://doi.org/10.1038/s41587-023-01987-2
2023
Will the hype of automated drug discovery finally be realized?
Expert Opinion on Drug Discovery
https://doi.org/10.1080/17460441.2023.2293157
2023
Celastrol Combats Methicillin-Resistant Staphylococcus aureus by Targeting Δ1-Pyrroline-5-Carboxylate Dehydrogenase
Advanced Science
https://doi.org/10.1002/advs.202302459
2021
MolADI: A Web Server for Automatic Analysis of Protein–Small Molecule Dynamic Interactions
Molecules
https://doi.org/10.3390/molecules26154625
2021
Rutin, a Natural Inhibitor of IGPD Protein, Inhibits the Formation of Biofilm in Staphylococcus xylosus ATCC700404 in vitro and in vivo
Frontiers in Pharmacology
https://doi.org/10.3389/fphar.2021.728354
2020
Clinical HDAC Inhibitors are Effective Drugs to Prevent the Entry of SARS-CoV2
ACS Pharmacology & Translational Science
https://doi.org/10.1021/acsptsci.0c00163
2020
Enhancing the Signaling of GPCRs via Orthosteric Ions
ACS Central Science
https://doi.org/10.1021/acscentsci.9b01247
2019
Advancing Drug Discovery via Artificial Intelligence
Trends in Pharmacological Sciences
https://doi.org/10.1016/j.tips.2019.06.004
2019
New binding sites, new opportunities for GPCR drug discovery
Trends in Biochemical Sciences
https://doi.org/10.1016/j.tibs.2018.11.011
2019
Computational modeling of the olfactory receptor Olfr73 suggests a molecular basis for low potency of olfactory receptor-activating compounds
Communications Biology
https://doi.org/10.1038/s42003-019-0384-8
2018
Exploring a new ligand binding site of G protein-coupled receptors
Chemical Science
https://doi.org/10.1039/C8SC01680A
2017
Implementing WebGL and HTML5 in Macromolecular Visualization and Modern Computer-Aided Drug Design
Trends in Biotechnology
https://doi.org/10.1016/j.tibtech.2017.03.009
2017
Using PyMOL as a platform for computational drug design
Computational Molecular Science
https://doi.org/10.1002/wcms.1303
Resolving membrane protein structures in real lipids
Membrane proteins
Membrane proteins are important drug targets which include G protein-coupled receptors (GPCRs), ion channels, transporters and others. Our team has close collaborations with leading scientist in the area of structural biology. However, most of current membrane protein structures were resolved at detergent or artificial lipid environments which are totally different from their physiological conditions. This in return result in losing the physiological functions of target membrane protein. Such structures will increase the cost the of structure-based drug discovery noticeably.
AlphaMol
Our team has developed a new pipeline which can resolve the membrane protein structures at real lipid environments. With such functional structures, we can design drug molecules in a more accurate way. Moreover, excellent cryoEM facilities are accessible in both China and Switzerland.
Publication
Time
Dissertation
Periodical
Link
2023
Cryo-EM structures of ClC-2 chloride channel reveal the blocking mechanism of its specific inhibitor AK-42
Nat Commun
https://doi.org/10.1038/s41467-023-39218-6
2023
Cryo-EM structure of human heptameric pannexin 2 channel
Nature Communications
https://doi.org/10.1038/s41467-023-36861-x
2021
Asymmetric opening of the homopentameric 5-HT3A serotonin receptor in lipid bilayers
Nature Communications
https://doi.org/10.1038/s41467-021-21016-7
2016
A Gating Mechanism of the Serotonin 5-HT3 Receptor
Structure
https://doi.org/10.1016/j.str.2016.03.019
2015
The Structure of the Mouse Serotonin 5-HT3 Receptor in Lipid Vesicles
Structure
https://doi.org/10.1016/j.str.2015.11.004
2014
X-ray structure of the mouse serotonin 5-HT3 receptor
Nature
https://doi.org/10.1038/nature13552
2014
Molecular and dimensional profiling of highly purified extracellular vesicles by fluorescence fluctuation spectroscopy
Analytical Chemistry
https://doi.org/10.1021/ac501801m
2011
Overcoming barriers to membrane protein structure determination
Nature Biotechnology
https://doi.org/10.1038/nbt.1833
New computational algorithm development
AlphaMol
Our team has developed an absolute binding energy prediction tool, which is known as AlphaE. With the new algorithm of AlphaE, we can predict accurately the binding activity of a compound. The RMSE (root-mean-square-energy) is as low as 1 kcal/mol in comparison with experimental data. AlphaE also overcomes many difficulties in currently available tools such as: (1) predictions are not reliable when the molecule changes too much; (2) calculations cannot be performed if molecules bind to different pockets; (3) predictions need large amount of CPU and GPU resources.
Furthermore, AlphaMol also developed many new computational algorithm and tools to predict the physical properties and drug-likeness of molecules. These tools demonstrated perfect correlations with experimental data, of which the R2 is up to 0.99.
Publication
Time
Dissertation
Periodical
Link
2024
Machine learning deciphered molecular mechanistics with accurate kinetic and thermodynamic prediction
Journal of Chemical Theory and Computation
https://doi.org/10.1021/acs.jctc.3c01412
2022
Accurate Physical Property Predictions via Deep Learning
Molecules
https://doi.org/10.3390/molecules27051668
2021
MolADI: A Web Server for Automatic Analysis of Protein–Small Molecule Dynamic Interactions
Molecules
https://doi.org/10.3390/molecules26154625
2019
Advancing Drug Discovery via Artificial Intelligence
Trends in Pharmacological Sciences
https://doi.org/10.1016/j.tips.2019.06.004
2017
Implementing WebGL and HTML5 in macromolecular visualization and modern computer-aided drug design
Trends in Biotechnology
https://doi.org/10.1016/j.tibtech.2017.03.009
2017
Using PyMOL as a platform for computational drug design
Computational Molecular Science
https://doi.org/10.1002/wcms.1303