Accelerating molecular discovery using an in silico design platform

Accelerating molecular discovery using an in silico design platform

Accelerating molecular discovery using an in silico design platform

By Parc Científic de Barcelona - Schrödinger

Date and time

Tuesday, July 8 · 9:30am - 3pm CEST

Location

Parc Científic de Barcelona - Sala Dolors Aleu - Edifici Clúster II

Baldiri Reixac, 4-10 08028 Barcelona Spain

About this event

  • Event lasts 5 hours 30 minutes

Take a break from your other obligations and let’s talk! Schrödinger together with Parc Científic de Barcelona invite you to join us on Tuesday, July 8th at PCB's Sala Dolors Aleu for an extended version of Schrödinger's Lunch and Learn series where we will introduce the diverse capabilities of Schrödinger’s molecular design platform. Schrödinger scientists will present how modern physics-based simulation methods as well as machine learning can help to create better molecules faster and answer your questions around computer-driven molecular design.

Event programme

09:30-09:35 Welcome and opening, Grisha Domakowski, Parc Cientific de Barcelona Commercialization & Communication Director.

09:35 - 11:30

Accelerating biologics design through computational modelling and collaborative enterprise informatics

Dan Cannon, Principal Scientist II, Applications Sciences

This Schrödinger workshop will explore how to use physics-based computational methods (BioLuminate, FEP+) and collaborative enterprise informatics (LiveDesign) to accelerate biologics design. We will present case studies on large scale mutagenesis for affinity, analysing and correcting developability issues, variant selection based on cross-reactivity, multi-parameter ideation and more. Whether you're new to computational tools or looking for a deeper dive into advanced methods, this session is designed to provide valuable insights for all experience levels.


11.30-12:00 Coffee break


12:00 - 14:00

Accelerating small-molecule drug discovery combining physics-based methods, machine learning techniques and digital chemistry

David Rinaldo, Senior Principal Scientist, Applications Science

Drug Design is a highly complex task literally consisting in finding a molecule with defined properties in the ocean of all possible molecules. In the past 10 years the field has experienced dramatic changes including an explosion in the size of commercial chemical libraries, a significant increase in available computing power (GPU, cloud computing), and significant advances in machine learning techniques (the so-called AI revolution). In this workshop we will see how Schrödinger has been leveraging those technological revolutions to accelerate the small-molecule drug discovery process.

In the first part of this workshop, we will present a few physics-based methods Schrödinger has been recently developing and then we will see how those techniques can efficiently be combined to efficiently and collaboratively find new drug candidates.

14:00 -15:00 Lunch

Register today to secure your seat!

The workshop is free to attend but pre-registration is required as seats are limited. Previous-experience with the Schrödinger suite is not required.

Speakers BIO

Dan Cannon

Principal Scientist II, Applications Science. Schrödinger

Dan Cannon is a Principal Applications Scientist at Schrödinger and the EU lead for biologics services. Prior to joining Schrödinger, Dan received his Ph.D. from the University of Strathclyde in Glasgow, UK, under the supervision of Prof. Tell Tuttle. In 2016, he began working at MedImmune in Cambridge, UK, using computational approaches for therapeutic protein design before joining Schrödinger in August of 2018 In his role as Applications Scientist he uses his expertise in biologics towards developing novel computational protein design and analysis workflows and enables customers to leverage protein structures towards rational design.

David Rinaldo

Senior Principal Scientist, Applications Science. Schrödinger

In 2003, David Rinaldo received his PhD from the Université Joseph Fourier working on metalloproteins under the supervision of Martin J. Field at the Institut de Biologie Structurale in Grenoble. For his post-doc, he then moved to Columbia University where he was studying metalloenzymes mechanisms using QM and QM/MM methods in Richard Friesner’s laboratory. Following his post-doc, he joined Schrodinger in 2007 as Applications Scientist where he has been supporting customers in Europe. He is now Senior Principal Scientist at Schrodinger and is advising customers on using the Schrodinger’s small molecule drug discovery Suite.

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