ChemDiv, Inc.

ChemDiv Presents: Antiobesity library The primary objective of creating this library was to identify novel potential anti-obesity compounds that operate through mechanisms distinct from GLP1R agonism. This approach aims to address the growing obesity epidemic by exploring alternative molecular targets and pathways involved in weight regulation. https://lnkd.in/eKyipNsN #Antiobesity

GPCR libraries available from Chemdiv Chemdiv GPCR discovery screening platform includes over 200 000 compounds in 9 focused, annotated and active fragments GPCR libraries, and 80 assays in 74 GPCR classes (C оrphans, Adhesion GPCRs, Adreno receptors, Chemokine receptors, Dopamine receptors, Histamine receptors, Opioid receptors, Serotonin receptors. Start screening project with Chemdiv! You will save your time, funds and efforts to find hits of novel chemotypes, SAR series and obtain brillant medicinal chemictry expertise. A library of small molecule compounds specifically targeting GPCRs can serve as a powerful tool in drug discovery, providing a crucial resource for identifying novel therapeutic agents. GPCRs, due to their involvement in a wide array of physiological processes and diseases, represent a significant proportion of current drug targets. A well-curated library offers researchers a diverse range of small molecules that can selectively interact with various GPCRs, enabling the exploration of their therapeutic potential in a systematic and efficient manner. Our library allows for high-throughput screening to rapidly identify compounds with promising biological activity against specific GPCRs. This approach is particularly beneficial in the early stages of drug development, where it can significantly accelerate the process of lead identification and optimization. https://lnkd.in/gvsagzus #GPCR

ChemDiv Presents: ChemData: Premium Data sets for AI-Powered Drug Discovery. Public Datasets Challenges Data Quality and Verification: - Literature-derived datasets lack standardized verification, with missing experimental details and quality controls. - Al models built on this unverified data may perform well in cross-validation but fail dramatically when applied to novel compounds in real experimental settings. Negative Data Samples: - Public databases overwhelmingly contain active compounds while unsuccessful experiments remain unpublished. - This imbalance leads Al models to overpredict activity and produce high false-positive rates, as they've rarely been trained on truly inactive compounds. Consistent Experimental Conditions: - Bioactivity and ADMET data comes from experiments with varying protocols, reagents, and conditions. - What appears as a single property (like "solubility" or "IC50") can represent fundamentally different measurements depending on experimental setup, causing models to learn artifacts rather than intrinsic molecular properties. Chemical Space Coverage: - Public datasets have significant gaps, focusing heavily on popular scaffolds and "drug-like" compounds. - Most molecules are tested against only a fraction of possible targets, creating an incomplete activity matrix that limits model performance when encountering novel chemical structures or target families. #Datasets #AI_Powered https://lnkd.in/evMsmjYi

🌟 Happy International Day of Women and Girls in Science! 🌟 Today, we celebrate the brilliance, resilience, and contributions of women in STEM fields worldwide. From groundbreaking discoveries to pioneering innovations, women continue to shape the future of science, technology, and medicine. 🚀 Did you know? Despite progress, women still make up only 30% of researchers globally. By fostering mentorship, equal opportunities, and representation, we can empower the next generation of female scientists and innovators. 🔬 To all the incredible women and girls in science—your curiosity, dedication, and passion inspire change. Let’s continue to support and uplift each other in building a more inclusive and diverse scientific community. 💡 Tag a woman in science who inspires you! Let’s celebrate their achievements and amplify their voices. #WomenInScience #GirlsInSTEM #InternationalDayOfWomenAndGirlsInScience #STEMLeadership #WomenInSTEM

Just wrapped up an incredible experience at #SLAS2025! It was a fantastic show filled with innovative exhibitors, insightful posters, and great networking opportunities. I truly enjoyed connecting with industry experts, exploring cutting-edge technologies, and discussing the future of life sciences. Looking forward to continuing the conversations and collaborations sparked at the event. Feel free to reach out—let’s keep the momentum going! 

Plan to attend SLAS 2025? Scheduled a meeting with Aleksandra Khotimchenko to learn more about our Small Molecule Diverse Collection for Screening!

ChemDiv, Inc. CEO, Bill Farley, will be attending the J.P. Morgan Healthcare Conference in San Francisco, CA, January 13–16, 2025. This event serves as a premier gathering of industry leaders, offering an unparalleled opportunity to engage in meaningful discussions, explore innovative strategies, and foster impactful collaborations. 💥 If you are also attending, we invite you to connect with Bill Farley to discuss potential synergies and partnership opportunities. 🤝 To arrange a meeting, please reach out directly to Bill Farley.

This Veterans Day we honor the courage, sacrifice, and unwavering dedication of the men and women who have served in our military. We are deeply grateful to our veterans and their families for their commitment and service, which continue to inspire us every day. 💫 Thank you for your sacrifice and bravery 👏

ChemDiv released new update of our screening collection. You can download database that includes over 1.6 million HTS compounds, 70,000 building blocks, 45,000 inhibitors and drugs. With unigue structural diversity, smart design, fresh updates and varios formats available, we keep over 30Y market leadership. ChemDiv ensures resupply, resynthesis, immediate analogs selection, medchem FTE support for H2L. https://lnkd.in/exgt57S7 #screening_collection

ChemDiv introduces a new DarkKinome library of screening compounds. DarkKinome refers to a subset of protein kinases that are less well-studied than their better-known counterparts. These kinases, including BRSK2, CDK10, CDK12, CDK13, DYRK1B, PIP4K2C, PKMYT1, STK17B, TLK2, and WEE2, are characterized by limited structural and functional knowledge, posing challenges for drug discovery. Despite this, they are considered drug targets due to their roles in various signaling pathways and potential implications for diseases such as cancer and neurodegeneration. Target kinases: 1. BRSK2: involved in the regulation of neuronal function. 2. CDK10: plays a role in cell cycle regulation and transcription. 3. CDK12: important for the regulation of RNA polymerase II transcription. 4. CDK13: functions similarly to CDK12 in transcriptional control. 5. DYRK1B: associated with neurodevelopmental disorders and cancer. 6. PIP4K2C: involved in phosphoinositide metabolism. 7. PKMYT1: regulates cell cycle progression. 8. STK17B: involved in stress response pathways. 9. TLK2: associated with DNA damage response. 10. WEE2: critical regulator of the cell cycle. To improve the understanding and therapeutic targeting of these dark kinases, we created a customized chemical library containing potentially active 8436 molecules targeting these targets. The development of this library utilizes machine learning algorithms combined with extensive knowledge obtained from both open and commercial databases including: PubChem, ChEMBL, Google Patents, SciFinder, and others. Using these resources, we selected small molecules with potentially high affinity and selectivity for dark kinome targets. The integration of machine learning enabled prediction of the potency and safety profiles of compounds, improving the efficiency of the drug discovery process. For each of the 10 kinases, we provide a list of compounds. https://lnkd.in/evmNtu3a #DarkKinome