J Chem Inf Model July 2022 PMID 35727311

AI-Based Protein Structure Prediction in Drug Discovery: Impacts and Challenges.

Michael Schauperl, Rajiah Aldrin Denny

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Mentions

Peak: 14 in Jun 2022

across 4 sources since Jun 2022

Extended reach

73,461

potential audience

Total likes

191

Video views

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Mentions per month

Jun 2022 – Jul 2025

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AI synopsis

What people are saying

The group shows strong support for the article’s positive assessment of AI-driven methods like AlphaFold2, with phrases such as 'help make drug design more efficient' and 'factors that influence predictions.' The tone reflects enthusiasm and recognition of ongoing challenges, contributing to a picture of a field with high potential and active discussion about improvements and future implications.

AgreementModerate agreement

Most discussions acknowledge the positive impact of AI tools like AlphaFold2 on drug discovery, showing general support for the publication's findings.

InterestHigh interest

The posts demonstrate high interest through repeated references to advancements, challenges, and the importance of the topic in current research.

EngagementModerate engagement

Some comments delve into specific factors influencing prediction accuracy and potential improvements, indicating thoughtful engagement.

ImpactHigh impact

Many posts highlight the transformative potential of AI in accelerating drug development and understanding protein structures, emphasizing its significant impact.

Abstract in brief

Proteins are essential for human biology and are key targets in drug discovery because their structure determines their biological function, but many protein structures have not been experimentally determined yet.
Recent advances like AlphaFold2, a machine learning tool, have significantly improved our ability to predict protein structures with high accuracy, aiding drug design efforts.
Despite these advancements, challenges remain in predicting complex protein features such as conformational states, domain interactions, posttranslational modifications, and changes caused by binding partners, which are crucial for developing effective drugs in the pharmaceutical industry.]

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All mentions

AI-Powered Protein Structure Prediction and Its Impact on Drug Discovery

Proteins are vital in biology and drug discovery, with structure defining function. Advances like AlphaFold2 greatly enhance our ability to predict protein shapes, aiding pharma efforts, but challenges remain in complex…

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José G. Parra

@JosGParra1 · X

RT @ACSSynBio: "In this Perspective, we explore how AlphaFold2 and related methods help make drug design more efficient. " Schauperl and D…

Oct 1, 2022 · 3 shares · 607 followers View post →

Leonardo Rios

@DrLeoRios · X

RT @ACSSynBio: "In this Perspective, we explore how AlphaFold2 and related methods help make drug design more efficient. " Schauperl and D…

Sep 30, 2022 · 3 shares · 9,328 followers View post →

JCIM & JCTC Journals

@JCIM_JCTC · X

RT @ACSSynBio: "In this Perspective, we explore how AlphaFold2 and related methods help make drug design more efficient. " Schauperl and D…

Sep 30, 2022 · 3 shares · 10,118 followers View post →

ACS Synthetic Bio

@ACSSynBio · X

Sep 29, 2022 · 6 likes · 3 shares · 11,047 followers View post →

SJ Fan

@SJFan48552412 · X

RT @JCIM_JCTC: AI-Based Protein Structure Prediction in #DrugDiscovery: Impacts and Challenges #ArtificialIntelligence https://t.co/Osbh5o…

Jul 24, 2022 · 2 shares · 56 followers View post →

CompChemBio Bot

@CompChemBioBot · X

RT @JCIM_JCTC: AI-Based Protein Structure Prediction in #DrugDiscovery: Impacts and Challenges #ArtificialIntelligence https://t.co/Osbh5o…

Jul 14, 2022 · 2 shares · 2,735 followers View post →

JCIM & JCTC Journals

@JCIM_JCTC · X

AI-Based Protein Structure Prediction in #DrugDiscovery: Impacts and Challenges #ArtificialIntelligence https://t.co/Osbh5oN9uX @SchauperlM #current_issue #JCIM #Perspectives https://t.co/kmJ7UxSXvs

Jul 14, 2022 · 8 likes · 2 shares · 10,118 followers View post →