Molecular Design of Solvents:  An Efficient Search Algorithm for Branched Molecules

2004 ◽  
Vol 43 (3) ◽  
pp. 784-790 ◽  
Author(s):  
M. Cismondi ◽  
E. A. Brignole
Keyword(s):  
Molecular Design ◽  
Search Algorithm ◽  
Efficient Search

Beam Search Sampling for Molecular Design and Intrinsic Prioritization with Machine Intelligence

2021 ◽  
Author(s):  
Michael Moret ◽  
Moritz Helmstädter ◽  
Francesca Grisoni ◽  
Gisbert Schneider ◽  
Daniel Merk
Keyword(s):  
De Novo ◽  
Molecular Design ◽  
Search Algorithm ◽  
Sampling Technique ◽  
Machine Intelligence ◽  
Language Models ◽  
Scoring Functions ◽  
Beam Search ◽  
De Novo Drug Design ◽  
Chemical Language

Chemical language models enable de novo drug design without the requirement for explicit molecular construction rules. While such models have been applied to generate novel compounds with desired bioactivity, the actual prioritization and selection of the most promising computational designs remains challenging. In this work, we leveraged the probabilities learnt by chemical language models with the beam search algorithm as a model-intrinsic technique for automated molecule design and scoring. Prospective application of this method yielded three novel inverse agonists of retinoic acid receptor-related orphan receptors (RORs). Each design was synthesizable in three reaction steps and presented low-micromolar to nanomolar potency towards RORg. This model-intrinsic sampling technique eliminates the strict need for external compound scoring functions, thereby further extending the applicability of generative artificial intelligence to data-driven drug discovery.<br>

Efficient Search Algorithm for Determining Optimal R=1/2 Systematic Convolutional Self-Doubly Orthogonal Codes

2012 ◽  
Vol 60 (1) ◽  
pp. 3-8 ◽  
Author(s):  
G. Kowarzyk ◽  
N. Belanger ◽  
D. Haccoun ◽  
Y. Savaria
Keyword(s):  
Search Algorithm ◽  
Efficient Search ◽  
Orthogonal Codes
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