scholarly journals Exploring amino-acid radical chemistry: protein engineering and de novo design

2005 ◽  
Vol 1707 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Kristina Westerlund ◽  
Bruce W. Berry ◽  
Heidi K. Privett ◽  
Cecilia Tommos
Keyword(s):  
Amino Acid ◽  
Protein Engineering ◽  
De Novo ◽  
De Novo Design ◽  
Radical Chemistry ◽  
Acid Radical

scholarly journals A defined structural unit enables de novo design of small-molecule–binding proteins

Science ◽  
2020 ◽  
Vol 369 (6508) ◽  
pp. 1227-1233 ◽  
Author(s):  
Nicholas F. Polizzi ◽  
William F. DeGrado
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Small Molecules ◽  
Structural Unit ◽  
De Novo ◽  
Computational Design ◽  
De Novo Design ◽  
X Ray ◽  
X Ray Crystallography ◽  
Chemical Groups

The de novo design of proteins that bind highly functionalized small molecules represents a great challenge. To enable computational design of binders, we developed a unit of protein structure—a van der Mer (vdM)—that maps the backbone of each amino acid to statistically preferred positions of interacting chemical groups. Using vdMs, we designed six de novo proteins to bind the drug apixaban; two bound with low and submicromolar affinity. X-ray crystallography and mutagenesis confirmed a structure with a precisely designed cavity that forms favorable interactions in the drug–protein complex. vdMs may enable design of functional proteins for applications in sensing, medicine, and catalysis.

scholarly journals AutoDesigner, a De Novo Design Algorithm for Rapidly Exploring Large Chemical Space for Lead Optimization: Application to the Design and Synthesis of D-Amino Acid Oxidase Inhibitors

2021 ◽  
Author(s):  
Pieter H Bos ◽  
Evelyne M. Houang ◽  
Fabio Ranalli ◽  
Abba E. Leffler ◽  
Nicholas A. Boyles ◽  
...  
Keyword(s):  
Amino Acid ◽  
Drug Discovery ◽  
De Novo ◽  
Chemical Space ◽  
De Novo Design ◽  
Lead Optimization ◽  
Acid Oxidase ◽  
Amino Acid Oxidase ◽  
Design Algorithm ◽  
Starting Point

The lead optimization stage of a drug discovery program generally involves the design, synthesis and assaying of hundreds to thousands of compounds. The design phase is usually carried out via traditional medicinal chemistry approaches and/or structure based drug design (SBDD) when suitable structural information is available. Two of the major limitations of this approach are (1) difficulty in rapidly designing potent molecules that adhere to myriad project criteria, or the multiparameter optimization (MPO) problem, and (2) the relatively small number of molecules explored compared to the vast size of chemical space. To address these limitations we have developed AutoDesigner, a de novo design algorithm. AutoDesigner employs a cloud-native, multi-stage search algorithm to carry out successive rounds of chemical space exploration and filtering. Millions to billions of virtual molecules are explored and optimized while adhering to a customizable set of project criteria such as physicochemical properties and potency. Additionally, the algorithm only requires a single ligand with measurable affinity and a putative binding model as a starting point, making it amenable to the early stages of a SBDD project where limited data is available. To assess the effectiveness of AutoDesigner, we applied it to the design of novel inhibitors of D-amino acid oxidase (DAO), a target for the treatment of schizophrenia. AutoDesigner was able to generate and efficiently explore over 1 billion molecules to successfully address a variety of project goals. The compounds generated by AutoDesigner that were synthesized and assayed (1) simultaneously met not only physicochemical criteria, clearance and central nervous system (CNS) penetration (Kp,uu) cutoffs, but also potency thresholds; (2) fully utilize structural data to discover and explore novel interactions and a previously unexplored subpocket in the DAO active site. The reported data demonstrate that AutoDesigner can play a key role in accelerating the discovery of novel, potent chemical matter within the constraints of a given drug discovery lead optimization campaign.

Amino Acid Pairing for De Novo Design of Self-Assembling Peptides and Their Drug Delivery Potential

2011 ◽  
Vol 21 (13) ◽  
pp. 2456-2464 ◽  
Author(s):  
Shan-Yu Fung ◽  
Hong Yang ◽  
Parisa Sadatmousavi ◽  
Yuebiao Sheng ◽  
Tewodros Mamo ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Amino Acid ◽  
De Novo ◽  
De Novo Design ◽  
Self Assembling
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