نموذج كلود التابع لشركة أنثروبيك يكتشف منظومة إنزيمية جديدة تشبه تقنية كريسبر لتعديل الجينات

Claude discovers CRISPR-like enzyme system

Written by

Picture of فريقنا

فريقنا

Communications Consultant

Anthropic has announced the launch of a new life sciences lab and research group, revealing that its Claude AI model has achieved an unprecedented biological discovery by independently uncovering an entirely new enzyme system with structural similarities to the revolutionary CRISPR gene-editing technology.

Anthropic has announced the launch of a new life sciences lab and research group, revealing that its Claude AI model has achieved an unprecedented biological discovery by independently uncovering an entirely new enzyme system with structural similarities to the revolutionary CRISPR gene-editing technology.

Article Index:

Anthropic’s announcement and launch of the new life sciences lab

American artificial intelligence research company Anthropic announced on Wednesday the establishment of an advanced laboratory and research group dedicated to life sciences and molecular biology, revealing at the same time that its Claude AI model has discovered a previously unknown enzyme system that shares structural characteristics with the CRISPR gene-editing technology.

This announcement represents an early practical and historical test of the ability of general artificial intelligence models to independently lead complex biological discovery research, coinciding with the company’s preparations for what is set to be the technology sector’s largest initial public offering.

Research methodology and deployment of 950 genome-processing agents

The discovered enzyme system has been named “array-associated reverse transcriptases” (ART), and its identification came after Anthropic scientists tasked the model with searching a giant genetic sequence database independently to discover new examples of reverse transcriptase enzymes, which are responsible for converting RNA into DNA.

To accomplish this massive computational task, the company deployed approximately 950 intelligent agents from the Claude family, which worked in parallel for 21 consecutive hours to process more than 210 million biological tokens. The systems successfully gathered 200,000 enzymes, identified 3,500 promising systems, and narrowed them down to 20 final systems for laboratory analysis.

The AI agent’s observation of repetitive patterns and operation logs

The internal operation logs of one of Claude’s agents revealed the exceptional moment of discovery when the AI agent detected an unusual repetitive pattern in the DNA sequences adjacent to the reverse transcriptase enzyme gene, noting in its automated report: “The adjacent DNA is quite striking; I can see with the naked eye a tandem repetitive array resembling CRISPR arrays!”

The agent automatically counted the repeats, measured the distances between them, and scanned all previous scientific literature and research to ensure no prior study had documented this configuration, before drafting a comprehensive report and sending it to the human team for laboratory review, leaving the scientists’ role to experimental verification in test tubes.

Structural components of the reverse transcriptase system and comparison with CRISPR

The new ART system consists of three main integrated elements including: a reverse transcriptase enzyme, a partner gene, and an orderly array of DNA sequences that repeat and are spaced with geometric precision mimicking the famous CRISPR arrays.

Although similar reverse transcriptase enzymes have been observed in previous studies of giant bacteriophages, Anthropic emphasized that Claude is the first entity to observe the distinct structural features of the system, including the non-coding DNA array and associated helper proteins that open new horizons for understanding viral defense mechanisms in micro-organisms.

Evaluation by Professor Feng Zhang of the Broad Institute of MIT

The discovery received widespread attention and praise from top global genomics scientists. Professor Feng Zhang, a pioneer of CRISPR gene-editing technologies and a professor at the Massachusetts Institute of Technology and the Broad Institute, reviewed the study’s scientific draft and technical report and praised the methodology used.

Zhang said in an official statement: “This is an inspiring and exciting model of how AI agents can drive biological discoveries; observing RNA repeat arrays associated with reverse transcriptases is truly interesting and deserves further in-depth laboratory investigations to understand its vital functions.”

Future prospects for gene editing and initial public offering preparations

Anthropic confirmed that the fundamental biological function of the system remains unknown, and that it is premature to conclude that it possesses immediate therapeutic applications as a gene-editing tool like CRISPR, noting that initial experiments showed the system producing short, distinct RNA molecules while testing continues in its certified biosafety-level laboratory.

This achievement enhances Anthropic’s market value and proves that its latest AI models have moved beyond text processing and article summarization to become true partners driving scientific discoveries in medicine and the fight against intractable diseases ahead of its anticipated IPO.

Frequently asked questions

Question: What is the new enzyme system discovered by the Claude model?
Answer: It discovered the array-associated reverse transcriptase system called ART, which resembles CRISPR.

Question: How many agents and how much time were required to reach this biological discovery?
Answer: Anthropic deployed 950 agents working for 21 consecutive hours to process 210 million genetic tokens.

Question: Who is the leading scientist who praised Claude’s discovery of the enzymes?
Answer: It was praised by Professor Feng Zhang, the pioneer of CRISPR gene editing at the Massachusetts Institute of Technology.

شارك هذا الموضوع:

شارك هذا الموضوع:

اترك رد

الفئات

المنشورات الأخيرة

Discover more from Buzzinga

Subscribe now to keep reading and get access to the full archive.

Continue reading