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AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor.

Authors :
Ren F
Ding X
Zheng M
Korzinkin M
Cai X
Zhu W
Mantsyzov A
Aliper A
Aladinskiy V
Cao Z
Kong S
Long X
Man Liu BH
Liu Y
Naumov V
Shneyderman A
Ozerov IV
Wang J
Pun FW
Polykovskiy DA
Sun C
Levitt M
Aspuru-Guzik A
Zhavoronkov A
Source :
Chemical science [Chem Sci] 2023 Jan 10; Vol. 14 (6), pp. 1443-1452. Date of Electronic Publication: 2023 Jan 10 (Print Publication: 2023).
Publication Year :
2023

Abstract

The application of artificial intelligence (AI) has been considered a revolutionary change in drug discovery and development. In 2020, the AlphaFold computer program predicted protein structures for the whole human genome, which has been considered a remarkable breakthrough in both AI applications and structural biology. Despite the varying confidence levels, these predicted structures could still significantly contribute to structure-based drug design of novel targets, especially the ones with no or limited structural information. In this work, we successfully applied AlphaFold to our end-to-end AI-powered drug discovery engines, including a biocomputational platform PandaOmics and a generative chemistry platform Chemistry42. A novel hit molecule against a novel target without an experimental structure was identified, starting from target selection towards hit identification, in a cost- and time-efficient manner. PandaOmics provided the protein of interest for the treatment of hepatocellular carcinoma (HCC) and Chemistry42 generated the molecules based on the structure predicted by AlphaFold, and the selected molecules were synthesized and tested in biological assays. Through this approach, we identified a small molecule hit compound for cyclin-dependent kinase 20 (CDK20) with a binding constant Kd value of 9.2 ± 0.5 μM ( n = 3) within 30 days from target selection and after only synthesizing 7 compounds. Based on the available data, a second round of AI-powered compound generation was conducted and through this, a more potent hit molecule, ISM042-2-048, was discovered with an average Kd value of 566.7 ± 256.2 nM ( n = 3). Compound ISM042-2-048 also showed good CDK20 inhibitory activity with an IC <subscript>50</subscript> value of 33.4 ± 22.6 nM ( n = 3). In addition, ISM042-2-048 demonstrated selective anti-proliferation activity in an HCC cell line with CDK20 overexpression, Huh7, with an IC <subscript>50</subscript> of 208.7 ± 3.3 nM, compared to a counter screen cell line HEK293 (IC <subscript>50</subscript> = 1706.7 ± 670.0 nM). This work is the first demonstration of applying AlphaFold to the hit identification process in drug discovery.<br />Competing Interests: Insilico Medicine is a company developing an AI-based end-to-end integrated pipeline for drug discovery and development and engaged in aging and cancer research. Alán Aspuru-Guzik is co-founder and Chief Vision officer of Kebotix, an AI-powered materials and molecular discovery company and co-founder and Chief Scientific Officer of Zapata Computing, a quantum software computing company. Alán Aspuru-Guzik is a scientific advisor to Insilico Medicine. Michael Levitt is an advisor to Insilico Medicine.<br /> (This journal is © The Royal Society of Chemistry.)

Details

Language :
English
ISSN :
2041-6520
Volume :
14
Issue :
6
Database :
MEDLINE
Journal :
Chemical science
Publication Type :
Academic Journal
Accession number :
36794205
Full Text :
https://doi.org/10.1039/d2sc05709c