November 2021: A mini-series of webinars on structure-based drug discovery.
Prof. Durrant's research covers a variety of interests in computational biology. In this session, he will focus on freely available tools applicable to the earliest steps in structure-based computer-aided drug discovery, including small-molecule database preparation, virtual screening via computer docking, ligand optimization, and molecular visualization.
Prof. Koes is renowned for his support for open source tools and software. Today he will focus on methods you can freely access to carry out structure-based virtual screening. As well as describing ‘how’ to use these methods he will provide guidance on when they are most appropriate, and discuss interpretation of the results. Prof. Koes will discuss both docking and pharmacophore methods.
ChimeraX is a powerful tool in the visualisation of molecules – see for example “UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Pettersen EF, Goddard TD, Huang CC, Meng EC, Couch GS, Croll TI, Morris JH, Ferrin TE. Protein Sci. 2021 Jan;30(1):70-82”. Dr. Mark Gardner & Dr Alexander Alex will show some of the features of ChimeraX with a focus on protein ligand interactions & analysis of docking results. We will also discuss our experience of small molecule docking & screening.
This series of webinars on compound design aims to share experiences of compound design in global health projects (malaria, TB, NTD), covering a range of topics including the use of freely available design tools, quality criteria such as target candidate profiles, screen sequences and case histories. If you are interested in making a presentation, please contact mark.gardner [at] amgconsultants.co.uk.
Links to recordings of previous webinars
Martine Keenan (Epichem) discusses CYP51, as a drug target for Chagas disease. This was a great hope to the field over a decade ago, but whilst research programs targeting this mechanism have not delivered a new chemical entity to the clinic, many useful lessons have been learnt along the way to advance the field. Research and learnings from T. cruzi medicinal chemistry programs undertaken by DNDi’s Chagas disease Consortium shape our approach to drug discovery efforts today, influencing the ideal profile of screening hits, identifying T. cruzi CYP51 pharmacophores, and a screening cascade for compound triage.
Neil Berry (University of Liverpool) uses a combination of machine learning and cheminformatics to discover potential drugs. He illustrates this approach in two areas:
1. Antimalarials: Exploring the MEP Pathway identified the 1,2-benzoisothiazolone (BITZ) chemotype as a promising Plasmodium IspD inhibitor.
2. Anti-Wolbachia (A-WOL) Drug Discovery: Machine learning approaches were used to select successive generations of compounds for screening, combining results from HTS and ligand based virtual screening. This approach gave i) an increased hit rate, ii) expansion of SAR around hits, iii) discovery of novel hit chemotypes, and iv) probed new areas of chemical space. Neil highlighted AWZ1066S which is now in preclinical development and expected to enter clinical trial in ~12 months.
Tom von Geldern (AbbVie, Franciscan Institute for World Health) presents a novel macrofilaricidal agent, Tylosin A, which acts by targeting the worm-symbiont Wolbachia bacterium. Chemical modification improved anti-Wolbachia activity and oral pharmacokinetic properties; an optimized analog (ABBV-4083) has been selected for clinical evaluation. Tom describes the medicinal chemistry optimization program, and gives a snapshot of the preclinical characterization of the candidate, including in vivo profiling.
European Bioinformatics Institute is launching a website, with support from MMV, to predict blood stage malaria activity. The model has been trained on over 5 million data points on screening collections from Novartis, GSK, St Jude Children's Research Hospital, AstraZeneca and MMV.
James Duffy (MMV) and Nicolas Bosc (EBI) explain the why and the what of the model and how you can apply it to your compound collection.
In-Silico Drug Design - What to do, What not to do
"We’re all victims of our own history…” - Dr Al Dossetter (Medchemica) will go through a brief tour of lesson learnt from >20 years of drug discovery using in-silico techniques. The talk will feature two lead optimisation project case studies as examples, both of which used 2D cheminfomatics and 3D structure based design.
PKTool v3.0 - update of popular free tool for dose prediction and pharmacokinetic modelling
Mark Gardner covers new features in the new version of the BMGF PK Tool for human dose prediction. These include handling single dose compounds, using Cav (or AUC) as well as Cmin for dose prediction, estimating bioavailability, and new usability features such as annotation. After a brief run-through for experienced users, Gardner provides an overview explaining the use of the PK Tool for dose prediction, comparing allometric scaling with in vitro clearance estimates and how to use the tool to ask 'what if' questions.
In early 2022, the source code was developed to add options to help analyse situations where long-acting or extended-release formulations. Explanatory notes, source code & test data are all available.
Modelling pharmacokinetics with PKTool v2.0 - improvements to BMGF’s free tool
BMGF’s free PKTool has been updated to address feedback from the Global Health community. Mark Gardner from AMG Consultants took us through the improved tool and demonstrated how to predict human dosing from experimental data.
Advanced features of DataWarrior - creating workflows with macros
DataWarrior has become an invaluable free tool for visualising drug discovery data. Isabelle Giraud, from Idorsia (formerly Actelion), demonstrated some of its more advanced features that allow you to streamline your workflows and make the most of your data.
Drug Discovery Data Insights
CDD hosted a discussion between Andrew Leach (ChEMBL), Evan Bolton (PubChem), and Ashley Farley (BMGF) on how SAR Data from the freely available ChEMBL and PubChem resources is transforming the Drug Discovery Informatics landscape. The discussion considered the challenges of creating large-scale community resource from heterogeneous biological data.
Searching and Analysing 3D Protein-ligand structures using PDBe web services
Abhik Mukhopadhyay, EBI UK showed how to search and analyse 3D protein-ligand structures using Protein Data bank in Europe (PDBe) websites and services (www.pdbe.org). He also demonstrated some PDBe web services that medicinal and computational chemist will find useful in understanding how small molecules interact with proteins.
→ Abhik's slides
PK Solver - a free tool to analyse pharmacokinetic data and derive PK parameters for modelling
PK Solver is a Microsoft Excel add-in which complements the free BMGF-funded PK Tool for pharmacokinetic analysis and prediction. It takes raw data and calculates parameters such as half-life, volume, AUC. Mark Gardner (AMG Consultants) described how to set PK Solver up and how to use it. Mark also gave an update on plans to update the PK Tool to make it more user-friendly and add in some additional capabilities.
→ Mark's slides
Hit triaging and advancement to anti-wolbachial lead compounds
Continuing the theme of capitalising on HTS results, Mike Petrassi presented on developing anti-wolbachial lead compounds at CALIBR.
Processing malaria HTS results using KNIME
Greg Landrum, Knime, gave a tutorial on workflows developed for ligand-based virtual screening, based on results of a phenotypic HTS against malaria.
→ Workflows and data from Greg's presentation (instructions together with a copy of the slides)
→ Greg's slides
A free web-based environment for docking, virtual screening, target prediction and more design tools; Vincent Zoete and Antoine Daina, Swiss Institute of Bioinformatics
Picking the best of the free drug discovery ADMET prediction models
Mark Gardner, AMG Consultants
→ Mark's slides
SwissADME: a web tool to support pharmacokinetic optimization for drug discovery
Vincent Zoete and Antoine Daina, Swiss Institute of Bioinformatics
Heterocyclic Quinolones – privileged pharmacophore targeting both Mycobacterium tuberculosis and malaria
Gemma Nixon, University of Liverpool
Using Jupyter as an electronic notebook to store and share computational chemistry
Chris Swain, Cambridge MedChem Consulting
→ Chris' slides
Transforming ‘hits’ into ‘leads’ - Two malaria drug discovery case studies
Claire Le Manach and Tanya Paquet, University of Cape Town
- An introduction to the free BMGF PK tool, Mark Gardner, AMG consultants (Start - 44:00)
- Using the PK tool in human dose prediction, Gavin Whitlock, Sandexis (44:00 - End)
- Predicting physicochemical properties with OCHEM and using chemistry in patents, Igor Tetko, Helmholtz Zentrum Munchen and BigChem GmbH
- 20 million public patent-extracted chemical structures: a look at the gift horse, Christopher Southan, GtoPDB and Centre for Integrative Physiology, University of Edinburgh
→ Chris' slides
- Solubility prediction: Outcomes & insights from the "Solubility Challenge" competition, Jonathan Goodman, University of Cambridge
- How Confident can we be in ADME Predictions? Matt Segall, Optibrium
- Freely available databases with applications in Drug Design, Caroline Low
→ Caroline's slides
- A simple KNIME script to compare compound collections, Mark Gardner
→ Mark's slides
- Tips on R group analysis in DataWarrior, Mark Gardner
→ Mark's slides
The ChEMBL Database for Drug Discover and Design, Anna Gaulton, EMBL-EBI
Two ChEMBL use cases: (1) Using ChEMBL data to produce a Quantitative Estimate of Drug-likeness; (2) Using ChEMBL data to derive transformations and models for de novo design, Jérémy Besnard, ExScientia
- Open source malaria project, Mat Todd, University of Sydney
- An introduction to the open-source workflow tool KNIME and applications in drug discovery, Greg Landrum, KNIME
- KNIME use case: Property calculation and chemical space diagrams in DNDi's Drug Booster project, Ben Perry, DNDi
→ Ben's workflow & guide
- KNIME use case: ‘Know Your Molecule’ searching ChEMBL with KNIME & interpreting the data, Mark Gardner, AMG
→ Mark's guide & workflow
- DataWarrior advanced data analysis, Isabelle Giraud, Actelion
- Using the RSC Medicinal Chemistry Toolkit in Drug Discovery Projects, Andy Davis, AZ
Visceral leishmaniasis Target Candidate Profile & screen sequence, Charlie Mowbrary, DNDi
→ Charlie's slides
Malaria Target Candidate Profiles, stage gates and implications for successful malaria drug discovery, Paul Willis, MMV
- Application of PK Tools in the optimisation of a series for the treatment of leishmaniasis, Gavin Whitlock, Sandexis
- Hints and tips to working with DataWarrior, Isabelle Giraud, Actelion
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We have to add the chemical structures as a pic – Danielle not sure about link