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#proteinscience

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CSBJ<p>This study introduces plmCP, an innovative method for detecting circular permutations (CPs) in proteins using Protein Language Models (PLMs)—paving the way for deeper insights into protein evolution, engineering, and synthetic biology.</p><p>🔗 Detection of circular permutations by Protein Language Models. Computational and Structural Biotech Journal, DOI: <a href="https://doi.org/10.1016/j.csbj.2024.12.029" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1016/j.csbj.2024.12</span><span class="invisible">.029</span></a></p><p>📚 CSBJ: <a href="https://www.csbj.org/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">csbj.org/</span><span class="invisible"></span></a></p><p><a href="https://mastodon.social/tags/ProteinScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ProteinScience</span></a> <a href="https://mastodon.social/tags/AIinBiotech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AIinBiotech</span></a> <a href="https://mastodon.social/tags/SyntheticBiology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SyntheticBiology</span></a> <a href="https://mastodon.social/tags/Bioinformatics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bioinformatics</span></a> <a href="https://mastodon.social/tags/ProteinEngineering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ProteinEngineering</span></a></p>
Hari Tulsidas<p>Scientists have cracked the code behind proteins’ extraordinary structures, unravelling how these molecular machines fold into shapes critical for life. This breakthrough deepens our understanding of biology and opens the door to designing custom proteins for medicine, energy, and materials. Could this reshape how we engineer solutions at the molecular level? <a href="https://masto.ai/tags/ProteinScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ProteinScience</span></a> <a href="https://masto.ai/tags/Biotechnology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Biotechnology</span></a> <a href="https://masto.ai/tags/Innovation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Innovation</span></a><br><a href="https://www.nobelprize.org/prizes/chemistry/2024/press-release/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">nobelprize.org/prizes/chemistr</span><span class="invisible">y/2024/press-release/</span></a></p>
Hari Tulsidas<p>AI has transformed protein science, predicting structures with unprecedented speed and accuracy. Yet, while tools like AlphaFold have revolutionized the field, the work is far from over. Understanding protein dynamics, interactions, and functions requires experimental and theoretical advances. AI is a powerful ally in decoding life’s molecular machinery. <a href="https://masto.ai/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://masto.ai/tags/ProteinScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ProteinScience</span></a> <a href="https://masto.ai/tags/Biotechnology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Biotechnology</span></a><br><a href="https://www.quantamagazine.org/how-ai-revolutionized-protein-science-but-didnt-end-it-20240626/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">quantamagazine.org/how-ai-revo</span><span class="invisible">lutionized-protein-science-but-didnt-end-it-20240626/</span></a></p>
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