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	<title>drug discovery &#8211; BIOENGINEER.ORG</title>
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	<title>drug discovery &#8211; BIOENGINEER.ORG</title>
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		<title>New Route to Strychnos Alkaloids via Thiophene Cycloadditions</title>
		<link>https://bioengineer.org/new-route-to-strychnos-alkaloids-via-thiophene-cycloadditions/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 23 Jan 2026 14:03:45 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[chiral catalysis]]></category>
		<category><![CDATA[Collective asymmetric synthesis]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[S-dioxide cycloadditions]]></category>
		<category><![CDATA[stereoselective synthesis]]></category>
		<category><![CDATA[Strychnos alkaloids]]></category>
		<category><![CDATA[Synthetic chemistry breakthrough]]></category>
		<category><![CDATA[Thiophene cycloadditions]]></category>
		<category><![CDATA[Thiophene S]]></category>
		<guid isPermaLink="false">https://bioengineer.org/new-route-to-strychnos-alkaloids-via-thiophene-cycloadditions/</guid>

					<description><![CDATA[In a groundbreaking advance that reverberates through the realms of synthetic chemistry and natural product synthesis, a team led by K.H. Park, J. Park, and N. Frank has unveiled a novel collective asymmetric synthetic route harnessing thiophene S,S-dioxide cycloadditions to access the complex Strychnos alkaloids. This landmark work, reported in Nature Chemistry, promises to redefine [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">319838</post-id>	</item>
		<item>
		<title>Machine Learning Unveils PRMT5 Inhibitors’ Diversity and Stability</title>
		<link>https://bioengineer.org/machine-learning-unveils-prmt5-inhibitors-diversity-and-stability/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 16 Jan 2026 02:01:28 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Dynamic stability** **Açıklama:** 1. **PRMT5 inhibitors:** Makalenin temel araştırma konusu. 2. **Machine learning:** Çalışmada kullanılan ana metodolojik yaklaşım. 3]]></category>
		<category><![CDATA[İlaç keşfi]]></category>
		<category><![CDATA[İşte bu içerik için uygun 5 Türkçe etiket: **Makine öğrenmesi]]></category>
		<category><![CDATA[Kanser Tedavisi]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Makalenin içeriğine ve anahtar kelimelerine göre en uygun 5 etiket: **PRMT5 inhibitors]]></category>
		<category><![CDATA[Molecular modeling]]></category>
		<category><![CDATA[Moleküler modelleme** **Açıklama:** 1. **Makine öğrenmesi:** Çalışmanın temel metodolojisini vurgular. 2. **İlaç ke]]></category>
		<category><![CDATA[PRMT5 inhibitörleri]]></category>
		<guid isPermaLink="false">https://bioengineer.org/machine-learning-unveils-prmt5-inhibitors-diversity-and-stability/</guid>

					<description><![CDATA[In a groundbreaking research effort, Dr. A. Khan has delved into the intricate world of protein arginine methyltransferase 5 (PRMT5) inhibitors, utilizing advanced machine learning techniques and molecular modeling methodologies. The study, set to appear in the esteemed journal Molecular Diversity, explores not only the structural diversity of these small molecules but also their dynamic [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">317369</post-id>	</item>
		<item>
		<title>Chlocarbazomycins: Promising Adenosine A1 Receptor Antagonists</title>
		<link>https://bioengineer.org/chlocarbazomycins-promising-adenosine-a1-receptor-antagonists/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Thu, 15 Jan 2026 05:59:25 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Adenosine A1 receptor]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Natural chlocarbazomycins]]></category>
		<category><![CDATA[Neuropharmacology]]></category>
		<category><![CDATA[Receptor antagonists]]></category>
		<guid isPermaLink="false">https://bioengineer.org/chlocarbazomycins-promising-adenosine-a1-receptor-antagonists/</guid>

					<description><![CDATA[Recent advancements in the realm of neuropharmacology have garnered attention as researchers have begun to delve into the intricate interactions of natural compounds with brain receptors. One such promising avenue of study is the exploration of natural chlocarbazomycins as potential antagonists of the adenosine A1 receptor. This research exemplifies an innovative fusion of ligand-based and [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">317081</post-id>	</item>
		<item>
		<title>Revolutionizing Molecular Design with FRAIL Technology</title>
		<link>https://bioengineer.org/revolutionizing-molecular-design-with-frail-technology/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sat, 10 Jan 2026 00:17:29 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Computational chemistry]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[FAAH-1 Inhibitors]]></category>
		<category><![CDATA[Fragment-based reinforcement learning]]></category>
		<category><![CDATA[FRAIL Technology]]></category>
		<category><![CDATA[Reinforcement Learning]]></category>
		<guid isPermaLink="false">https://bioengineer.org/revolutionizing-molecular-design-with-frail-technology/</guid>

					<description><![CDATA[In an era marked by rapid advancements in artificial intelligence and computational sciences, researchers have made significant strides in the integration of these fields with molecular design and drug discovery. One groundbreaking approach, recognized for its innovative use of technology in accelerating molecular optimization, is known as FRAIL—an acronym for Fragment-based Reinforcement Learning. This method, [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">315481</post-id>	</item>
		<item>
		<title>Triazolopyridines: Advances in Synthesis and Applications</title>
		<link>https://bioengineer.org/triazolopyridines-advances-in-synthesis-and-applications/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Tue, 23 Dec 2025 14:16:34 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Heterocyclic Compounds]]></category>
		<category><![CDATA[Medicinal Chemistry]]></category>
		<category><![CDATA[Pharmaceutical Applications]]></category>
		<category><![CDATA[Triazolopyridine Synthesis]]></category>
		<guid isPermaLink="false">https://bioengineer.org/triazolopyridines-advances-in-synthesis-and-applications/</guid>

					<description><![CDATA[In the ever-evolving landscape of synthetic chemistry, triazolopyridines have emerged as a unique and versatile class of compounds. These compounds have garnered significant attention due to their diverse biological activities and potential applications in medicinal chemistry. The research article by Zhao, Geng, Xu, and their collaborators delves into the comprehensive analysis of triazolopyridines, illuminating their [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">310594</post-id>	</item>
		<item>
		<title>Antifungal Indole Derivatives: Design, Synthesis, Evaluations</title>
		<link>https://bioengineer.org/antifungal-indole-derivatives-design-synthesis-evaluations/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 22 Dec 2025 03:31:11 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Antifungal agents]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Indole derivatives]]></category>
		<category><![CDATA[molecular docking]]></category>
		<category><![CDATA[Synthetic methods]]></category>
		<guid isPermaLink="false">https://bioengineer.org/antifungal-indole-derivatives-design-synthesis-evaluations/</guid>

					<description><![CDATA[Research has consistently shown that indole derivatives are a treasure trove of biological activities, exhibiting a wide range of beneficial properties. These include antifungal, antibacterial, anticancer, antioxidant, antimalarial, antidiabetic, antitubercular, and anticholinesterase effects. The multifaceted roles of these compounds make them essential candidates for pharmacological studies. In the burgeoning field of medicinal chemistry, indole derivatives [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">310146</post-id>	</item>
		<item>
		<title>New Small-Molecule Inhibitor Discovered for GMP Synthetase</title>
		<link>https://bioengineer.org/new-small-molecule-inhibitor-discovered-for-gmp-synthetase/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 19 Dec 2025 14:34:03 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Antiviral therapy]]></category>
		<category><![CDATA[cancer therapy]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[keşfedilen inhibitörün doğrudan hedefi. 2. **Cancer therapy:** İnhibitörün]]></category>
		<category><![CDATA[Makalenin içeriğine ve anahtar kelimelerine göre en uygun 5 etiket: **GMP synthetase inhibitor]]></category>
		<category><![CDATA[Purine biosynthesis** **Açıklama:** 1. **GMP synthetase inhibitor:** Makalenin ana konusu]]></category>
		<guid isPermaLink="false">https://bioengineer.org/new-small-molecule-inhibitor-discovered-for-gmp-synthetase/</guid>

					<description><![CDATA[In the ever-evolving landscape of biomedical research, the discovery and development of small-molecule inhibitors represent a critical avenue for advancing therapeutic strategies, particularly against challenging diseases. A groundbreaking study led by researchers, including Wang, Z., Sundarraj, R., and Mao, B., has unveiled a novel small-molecule inhibitor specifically targeting human GMP synthetase, an enzyme pivotal in [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">309548</post-id>	</item>
		<item>
		<title>Enantioselective Protein Affinity Mass Spectrometry Advances</title>
		<link>https://bioengineer.org/enantioselective-protein-affinity-mass-spectrometry-advances/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Wed, 17 Dec 2025 22:03:00 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[başlıkta ve içerikte sürekli vurgulanıyor. 2. **Protein]]></category>
		<category><![CDATA[biomolecular analysis]]></category>
		<category><![CDATA[Biomolecular interactions** **Kısa açıklama:** 1. **Enantioselective mass spectrometry:** Ana teknik]]></category>
		<category><![CDATA[Chiral drug discovery]]></category>
		<category><![CDATA[chiral molecule analysis]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Enantioselective protein affinity mass spectrometry]]></category>
		<category><![CDATA[İşte içerik için uygun 5 etiket (virgülle ayrılmış): **Enantioselective mass spectrometry]]></category>
		<category><![CDATA[Protein affinity selection]]></category>
		<category><![CDATA[protein-ligand interactions]]></category>
		<category><![CDATA[Stereochemical analysis]]></category>
		<guid isPermaLink="false">https://bioengineer.org/enantioselective-protein-affinity-mass-spectrometry-advances/</guid>

					<description><![CDATA[In the relentless pursuit of precision in molecular biology and pharmaceutical science, an innovative method has emerged that promises to revolutionize the way researchers identify and analyze chiral molecules binding to proteins. The groundbreaking technique, known as Enantioselective Protein Affinity Selection Mass Spectrometry (E-ASMS), has been developed by Wang, Sun, Ahmad, and colleagues, and is [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">308949</post-id>	</item>
		<item>
		<title>Innovative Technique Enables Rapid and Comprehensive Detection of Protein-Ligand Interactions</title>
		<link>https://bioengineer.org/innovative-technique-enables-rapid-and-comprehensive-detection-of-protein-ligand-interactions/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Tue, 11 Nov 2025 17:39:49 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[high-throughput proteomics]]></category>
		<category><![CDATA[HT-PELSA]]></category>
		<category><![CDATA[membrane proteins]]></category>
		<category><![CDATA[protein-ligand interactions]]></category>
		<guid isPermaLink="false">https://bioengineer.org/innovative-technique-enables-rapid-and-comprehensive-detection-of-protein-ligand-interactions/</guid>

					<description><![CDATA[Proteins sit at the very heart of life’s machinery, orchestrating almost every biological function necessary for cells and organisms to thrive. The concept of proteins, first coined by Swedish chemist Jöns Jacob Berzelius in the early 19th century, derived from the Greek proteios, meaning “primary” or “of first importance,” aptly highlights their foundational role. Despite [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">294955</post-id>	</item>
		<item>
		<title>AI Revolutionizes Biology and Medicine</title>
		<link>https://bioengineer.org/ai-revolutionizes-biology-and-medicine/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 17 Oct 2025 17:55:39 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[AI Ethics in Medicine]]></category>
		<category><![CDATA[artificial intelligence in healthcare]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Interdisciplinary Collaboration]]></category>
		<category><![CDATA[personalized medicine]]></category>
		<guid isPermaLink="false">https://bioengineer.org/ai-revolutionizes-biology-and-medicine/</guid>

					<description><![CDATA[Artificial intelligence (AI) has rapidly emerged as one of the most transformative technologies of the 21st century, influencing a multitude of sectors, including biology and medicine. The integration of AI into these fields is not merely a trend; it represents a monumental shift in how researchers and practitioners approach fundamental problems, paving the way for [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">282990</post-id>	</item>
		<item>
		<title>New Pipeline Advances Molecular Design Validation in Practice</title>
		<link>https://bioengineer.org/new-pipeline-advances-molecular-design-validation-in-practice/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sat, 11 Oct 2025 02:01:55 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Computational chemistry]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[material science]]></category>
		<category><![CDATA[Molecular design validation]]></category>
		<category><![CDATA[Structure-aware pipeline]]></category>
		<guid isPermaLink="false">https://bioengineer.org/new-pipeline-advances-molecular-design-validation-in-practice/</guid>

					<description><![CDATA[In the dynamic realm of molecular design, recent advancements are paving the way toward innovative methodologies that harness the power of artificial intelligence and computational techniques. A significant stride in this field has emerged from a study led by Dias and Rodrigues, published in Nature Machine Intelligence. The focus lies on the real-world validation of [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">279017</post-id>	</item>
		<item>
		<title>St. Jude Algorithm Harnesses Water Dynamics to Accelerate Drug Discovery</title>
		<link>https://bioengineer.org/st-jude-algorithm-harnesses-water-dynamics-to-accelerate-drug-discovery/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 27 Jun 2025 20:30:34 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[ColdBrew algorithm]]></category>
		<category><![CDATA[computational protein-ligand modeling]]></category>
		<category><![CDATA[cryogenic artifact correction]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[water dynamics in proteins]]></category>
		<guid isPermaLink="false">https://bioengineer.org/st-jude-algorithm-harnesses-water-dynamics-to-accelerate-drug-discovery/</guid>

					<description><![CDATA[In the intricate world of molecular biology, water has long been recognized as a fundamental player influencing the structure and function of proteins — the workhorse molecules of the cell. Despite its crucial role, the behavior and positioning of water molecules within protein environments have remained largely elusive to researchers, especially in the context of [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">250660</post-id>	</item>
		<item>
		<title>Precious2GPT: Multiomics transformer and conditional diffusion for generation of multi-omics multi-species multi-tissue synthetic biological data</title>
		<link>https://bioengineer.org/precious2gpt-multiomics-transformer-and-conditional-diffusion-for-generation-of-multi-omics-multi-species-multi-tissue-synthetic-biological-data/</link>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Tue, 13 Aug 2024 18:10:23 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[aging research]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[multi-omics AI]]></category>
		<category><![CDATA[synthetic biological data]]></category>
		<category><![CDATA[transformer-diffusion models]]></category>
		<guid isPermaLink="false">https://bioengineer.org/precious2gpt-multiomics-transformer-and-conditional-diffusion-for-generation-of-multi-omics-multi-species-multi-tissue-synthetic-biological-data/</guid>

					<description><![CDATA[  PreciousGPT series are pioneering architecture designed to understand the biological mechanisms and the aging process for life from birth to death Precious2GPT diffusion-transformer architecture was published in Nature npj Aging Precious2GPT integrates pretrained transformers with conditional diffusion models for generating multi-omics, multi-species, and multi-tissue data for drug discovery and aging research Precious3GPT is in [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">231448</post-id>	</item>
		<item>
		<title>Autobahn Labs, Cold Spring Harbor Laboratory partner to advance novel science to clinic</title>
		<link>https://bioengineer.org/autobahn-labs-cold-spring-harbor-laboratory-partner-to-advance-novel-science-to-clinic/</link>
					<comments>https://bioengineer.org/autobahn-labs-cold-spring-harbor-laboratory-partner-to-advance-novel-science-to-clinic/#respond</comments>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 07 Jun 2021 16:18:43 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[Academic-Industry Incubator]]></category>
		<category><![CDATA[Biology]]></category>
		<category><![CDATA[Biopharmaceutical Partnerships]]></category>
		<category><![CDATA[Biotechnology]]></category>
		<category><![CDATA[Collaboration]]></category>
		<category><![CDATA[drug discovery]]></category>
		<category><![CDATA[Medicine/Health]]></category>
		<category><![CDATA[Pharmaceutical Chemistry]]></category>
		<category><![CDATA[Pharmaceutical Science]]></category>
		<category><![CDATA[Pharmaceutical Sciences]]></category>
		<category><![CDATA[Preclinical Development]]></category>
		<category><![CDATA[Strategic Collaboration]]></category>
		<guid isPermaLink="false">https://bioengineer.org/autobahn-labs-cold-spring-harbor-laboratory-partner-to-advance-novel-science-to-clinic/</guid>

					<description><![CDATA[Expansion to East Coast validates Autobahn Labs&#8217; novel incubator model PALO ALTO, CA (June 7, 2021) &#8211; Autobahn Labs, an early-stage drug discovery incubator, today announced a new strategic venture collaboration with Cold Spring Harbor Laboratory (CSHL). Together with Autobahn Labs, CSHL will identify promising research programs with therapeutic potential and partner to form promising [&#8230;]]]></description>
		
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