Macs in Chemistry

Insanely Great Science

CCG releases PSILO 2019.02

 

Chemical Computing Group have announced the 2019 release of PSILO, CCG Protein Structure Database System. The PSILO 2019.02 version includes a variety of new features and enhancements for viewing and searching records and for aligning and identifying protein active sites. Additional features in PSILO 2019.02 include streamlined PSILO IT infrastructure which facilitates deployment and performing PSILO searches directly from MOE.

NEW & ENHANCED FEATURES IN PSILO 2019.02

  • Analyze Ligand and Receptor Interaction Patterns using Clustered 3D Environments
  • Perform the Full Range of PSILO Searches from MOE
  • Infer Apo-pockets Using PSILO Family References
  • Include Crystal Contacts in Ligand Interaction Diagrams
  • Streamlined PSILO IT Infrastructure

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In which area is Artificial Intelligence likely to most impact Chemistry, the results are in

 

I ran a poll last week asking "In which area is Artificial Intelligence likely to most impact Chemistry?" And we now have the results.

pollResults

Whilst Molecular Design was the most popular choice it was interesting to see that all options were well supported. This suggests that there are opportunities for artificial intelligence to have an impact in many facets of chemistry. I'm delighted to see this since this was part of the thinking behind the AI in Chemistry meeting and I think the line up of speakers will have something for everyone.

2nd RSC-BMCS / RSC-CICAG, Artificial Intelligence in Chemistry, Monday-Tuesday, 2nd to 3rd September 2019. Fitzwilliam College, Cambridge, UK. #AIChem19

Synopsis
Artificial Intelligence is presently experiencing a renaissance in development of new methods and practical applications to ongoing challenges in Chemistry. Following the success of the inaugural “Artificial Intelligence in Chemistry” meeting in 2018, we are pleased to announce that the Biological & Medicinal Chemistry Sector (BMCS) and Chemical Information & Computer Applications Group (CICAG) of the Royal Society of Chemistry are once again organising a conference to present the current efforts in applying these new methods. The meeting will be held over two days and will combine aspects of artificial intelligence and deep machine learning methods to applications in chemistry.

Programme (draft)

Monday, 2nd September
08.30
Registration, refreshments
09.30
Deep learning applied to ligand-based de novo design: a real-life lead optimization case study
Quentin Perron, IKTOS, France
10.00
A. Turing test for molecular generators
Jacob Bush, GlaxoSmithKline, UK
10.30
Flash poster presentations
11.00
Refreshments, exhibition and posters
11.30
Presentation title to be confirmed
Keynote: Regina Barzilay, Massachusetts Institute of Technology, USA
12.30
Lunch, exhibition and posters
14.00
Artificial intelligence for predicting molecular Electrostatic Potentials (ESPs): a step towards developing ESP-guided knowledge-based scoring functions
Prakash Rathi, Astex Pharmaceuticals, UK
14.30
Molecular transformer for chemical reaction prediction and uncertainty estimation
Alpha Lee, University of Cambridge, UK
15.00
Drug discovery disrupted - quantum physics meets machine learning
Noor Shaker, GTN, UK
15.30
Refreshments, exhibition and posters
16.00
Application of AI in chemistry: where are we in drug design?
Christian Tyrchan, AstraZeneca, Sweden
16.30
Presentation title to be confirmed
Anthony Nicholls, OpenEye Scientific Software, USA
17.30 Close
18.45 Drinks reception
19.15 Conference dinner

Tuesday, 3rd September
08.30
Refreshments
09.00v Deep generative models for 3D compound design from fragment screens
Fergus Imrie, University of Oxford, UK
09.30
DeeplyTough: learning to structurally compare protein binding sites
Joshua Meyers, BenevolentAI, UK
10.00
Discovery of nanoporous materials for energy applications
Maciej Haranczyk, IMDEA Materials Institute, Spain
10.30
Refreshments, exhibition and posters
11.00
Deep learning for drug discovery
Keynote: David Koes, University of Pittsburgh, USA
12.00
Networking lunch, exhibition and posters
14.00
Presentation title to be confirmed
Olexandr Isayev, University of North Carolina at Chapel Hill, USA
14.30
Dreaming functional molecules with generative ML models
Christoph Kreisbeck, Kebotix, USA
15.00
Refreshments, exhibition and posters
15.30
Presentation title to be confirmed
Keynote: Adrian Roitberg, University of Florida, USA
16.30
Close

You can get more information and register here https://www.maggichurchouseevents.co.uk/bmcs/AI-2019.htm.


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RSC Elections

 

Voting for the Royal Society of Chemistry 2019 elections is now open and you should have been notified.

This year, they are holding elections for the following positions:

  • RSC President (one vacancy)
  • Elected Trustees (three vacancies)
  • Elected member of Professional Standards Board (one vacancy)
  • President of Analytical Division (one vacancy)
  • President of Chemistry Biology Interface Division (one vacancy)
  • President of Education Division (one vacancy)
  • President of Environment, Sustainability and Energy Division (one vacancy)
  • Elected member of Analytical Division Council (two vacancies)
  • Elected member of Education Division Council (two vacancies)
  • Elected member of Environment, Sustainability and Energy Division Council (two vacancies)
  • Elected member of Faraday Division Council (two vacancies)
  • Elected member of Materials Chemistry Division Council (two vacancies)
  • Elected member of Organic Division Council (two vacancies)

Voting closes at 17:00 (UK time) on Friday 21 June 2019 so I'd urge you to vote ASAP.

On a personal note.

David Rees is standing for RSC President, I've known David for many years and I can't think of a better person to lead the RSC in these uncertain times. A really top class scientist with an excellent career in Drug Discovery, whilst maintaining contacts with academic research and holding important roles within the RSC.


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SilcsBio Software

 

A recent publication "Optimization and Evaluation of Site-Identification by Ligand Competitive Saturation (SILCS) as a Tool for Target-Based Ligand Optimization" DOI caught my eye. Predicting ligand binding affinities is a very challenging process and whilst free energy perturbation methods have proved useful they are very computationally demanding. SILCS looks to give similar accuracy but with reduced computational demands.

The software is available from SILCSBIO and whilst it requires significant compute resources or access to a virtual cluster using Amazon Web Services, the SilcsBio Graphical User Interface (GUI) enables running SILCS and SSFEP simulations and analysing results through a GUI instead of the command line and is available for Mac OSX and Windows. Visualisation of results uses VMD or PYMOL plugins.


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Samson tutorials

 

I've been keeping an eye on Samson for a while now and whilst we still wait for the version 1 release the current version sports some interesting developments.

SAMSON is the quickly growing platform for molecular modeling. SAMSON's goal is to make it faster for everyone to design drugs, materials and nanosystems.

There are an increasing number of Elements

SAMSON Elements are modules for SAMSON that you add from SAMSON Connect. The first time you start SAMSON, some default SAMSON Elements are automatically installed

And the documentation now includes some tutorials, the GROMACS Wizard Light help you to easily run GROMACS simulations and get results as plots and simulation trajectories.

As I've mentioned before the Samson scripting API allows you to control Samson using Python.


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