Unbiased De Novo Generation of Organic Molecular Materials - Thomas Cauchy

Unbiased De Novo Generation of Organic Molecular Materials - Thomas Cauchy

If you enjoyed this talk, consider joining the Molecular Modeling and Drug Discovery (M2D2) talks live: https://valence-discovery.github.io/M...

Also consider joining the M2D2 Slack: https://join.slack.com/t/m2d2group/shared_invite/zt-16i9r9jir-ioE0TJVHEO~bAyZxu17neg

Abstract: Beyond the active search for new drugs, de novo generation methods are also a great opportunity for the discovery of molecular materials. However, the chemical space of these materials differs from that of bioactive molecules. This conference will present the challenges inherent to this kind of problems. For most molecular materials, new targets must have specific electronic properties. This normally means a very costly evaluation by quantum mechanical calculations. Furthermore this evaluation requires a knowledge of the atomic positions in three dimensions. All these specific constraints have led us to propose our own generation method based on EvoMol, an efficient evolutionary algorithm. Free to travel the whole chemical space, the methods that limit the solutions to realistic molecules will be presented.

Speaker: Thomas Cauchy - https://twitter.com/ThomasCauchyQC

Twitter Prudencio: https://twitter.com/tossouprudencio

Twitter Therence: https://twitter.com/Therence_mtl

Twitter Cas: https://twitter.com/cas_wognum

Twitter Valence Discovery: https://twitter.com/valence_ai

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(60)

Structure-Independent Peptide Binder Design via Generative Language Models | Pranam Chatterjee

Structure-Independent Peptide Binder Design via Generative Language Models | Pranam Chatterjee

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifie...

20 Kesä 20231h

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | Albert Musaelian

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | Albert Musaelian

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplif...

13 Kesä 20231h 9min

Multimodal Deep Learning for Protein Engineering | Kevin K. Yang

Multimodal Deep Learning for Protein Engineering | Kevin K. Yang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifie...

7 Kesä 20231h 2min

Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele

Systematic Analysis of Biomolecular Conformational Ensembles with PENSA | Martin Vögele

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies ...

30 Touko 202350min

Training Neural Network Potentials: Bayesian and Simulation-based Approaches | Stephan Thaler

Training Neural Network Potentials: Bayesian and Simulation-based Approaches | Stephan Thaler

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mo...

16 Touko 20231h 3min

Accelerating Cryptic Pocket Discovery Using Alphafold and Markov State Modelling | Soumendranath Bhakat

Accelerating Cryptic Pocket Discovery Using Alphafold and Markov State Modelling | Soumendranath Bhakat

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mole...

9 Touko 202331min

Machine Learning Molecules | Gianni De Fabritiis

Machine Learning Molecules | Gianni De Fabritiis

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies mole...

25 Huhti 202357min

Protein Representation Learning by Geometric Structure Pretraining | Zuobai Zhang

Protein Representation Learning by Geometric Structure Pretraining | Zuobai Zhang

[DISCLAIMER] - For the full visual experience, we recommend you tune in through our ⁠⁠⁠⁠YouTube channel ⁠⁠⁠⁠to see the presented slides. Try datamol.io - the open source toolkit that simplifies molecu...

19 Huhti 202353min

Suosittua kategoriassa Tiede

rss-mita-tulisi-tietaa
rss-hereilla
rss-duodecim-lehti
rss-poliisin-mieli
tiedekulma-podcast
rss-ilmasto-kriisissa
docemilia
hippokrateen-vastaanotolla
sotataidon-ytimessa
filocast-filosofian-perusteet
rss-radplus
rss-tiedetta-vai-tarinaa
rss-opeklubi
rss-kasvikutsut
rss-totuuden-liepeilla