Acta Materia Medica retweeted
This review examines how androgen receptor alterations contribute to CRPC and discusses PROTACs as tools for degrading proteins that sustain disease progression and therapeutic resistance. #CancerBiology #ProstateCancer @harvardmed
#AMM #OpenAccess: doi.org/10.15212/AMM-2024-00…
Acta Materia Medica retweeted
A randomized trial found that Cs4 improved symptom severity, fatigue, insomnia, respiratory symptoms, and quality of life over 12 weeks in patients with long COVID. #ClinicalTrials #CordycepsSinensis @HKUniversity
#AMM #OpenAccess: doi.org/10.15212/AMM-2024-00…
Acta Materia Medica retweeted
💊 Not every disease-associated molecular change is a promising drug target.
In @DrugTargetRev , our Dr Shi-qi An explores how multiomics, single-cell and spatial technologies can strengthen drug target discovery.
🔗 drugtargetreview.com/home/ho…
Acta Materia Medica retweeted
Be Part of the Future of Pharmacology
Join PHARMAUE 2026 – 18th International Conference & Exhibition on Pharmacology, Drug Discovery & Pharmacotherapy.
Date: 8–9 December 2026
Venue: Kuala Lumpur, Malaysia & Virtual
Register Now: pharmacy.ucgconferences.com/…
Acta Materia Medica retweeted
Join us at these upcoming conferences:
- Drug Discovery Chemistry Europe, November 10-12, Barcelona, Spain
drugdiscoverychemistry.com/e…
- The 43rd Medicinal Chemistry Symposium, November 11-13, Kyoto, Japan
k-gakkai.jp/mcs2026/en/en_in…
We will be happy to meet you, discuss the latest developments in Drug Discovery, and explore new opportunities for collaboration.
Acta Materia Medica retweeted
🇳🇱 Leiden University — PhD in AI-Driven Drug Discovery
🔥 URGENT | MSCA-Funded | Deadline: November 12, 2026
🏫 University: Leiden University
🔬 Laboratory: Leiden Academic Centre for Drug Research (LACDR) — Computational Drug Discovery Group
📍 Location: Leiden, Netherlands
🆕 Published: October 15, 2026
📖 Research Project:
ANA-KIN DC10 — Deep Learning for Kinase Drug Discovery
This PhD focuses on developing artificial intelligence models to discover new cancer therapeutics targeting protein kinases.
Unlike conventional kinase inhibitors, which primarily target ATP-binding sites, the project investigates alternative regulatory interfaces to improve drug selectivity and overcome resistance.
Research Activities:
•Develop deep-learning models for kinase inhibitor discovery.
•Integrate chemical, structural, and biophysical datasets.
•Predict molecular binding and drug-resistance mechanisms.
•Design computational approaches for peptide-based therapeutics.
•Apply AI models to experimental drug-discovery workflows.
•Develop open-source computational tools.
The position includes research secondments at two Belgian partner organizations.
💰 Funding Details:
✅ Fully funded through the Horizon Europe MSCA Doctoral Network ANA-KIN.
✅ Four-year salaried PhD position.
✅ Gross monthly salary: €3,204–€4,051.
✅ Additional 8% holiday allowance.
✅ Additional 8.3% year-end allowance.
✅ University pension and employment benefits.
✅ International research secondments and specialist training.
Contract Structure: Initial one-year appointment, extendable for the remaining three years after a positive evaluation.
🔍 Application Requirements:
•Master’s degree in Computer Science, AI, Computational Chemistry, Bioinformatics, or a related field.
•Experience with machine learning and deep learning, preferably PyTorch.
•Knowledge of cheminformatics or computational chemistry.
•Excellent Python programming skills.
•Strong academic English.
•Interest in pharmaceutical research.
MSCA Eligibility:
•Applicants must not already hold a doctoral degree.
•Applicants must not have lived, worked, or studied in the Netherlands for more than 12 months during the preceding 36 months, subject to MSCA exceptions.
Required Documents:
•Motivation letter confirming MSCA eligibility.
•Academic CV.
•Academic grade list.
•Contact details of two referees.
🕒 Application Deadline: November 12, 2026.
⏳ Time Remaining: 4 Days!
⭐ Why Apply?
This is an excellent opportunity to combine artificial intelligence with pharmaceutical research.
The project offers a competitive Dutch salary, international research experience, and collaboration with academic and industrial partners.
🔗 Official University Application:
careers.universiteitleiden.n…
#phd #PhD #phdopportunity #phdposition
Acta Materia Medica retweeted
POSTDOCTORAL FELLOWSHIPS IN MEDICINAL CHEMISTRY AT UNIVERSITY OF CAPE TOWN
👇👇👇👇👇👇👇👇
@PostdocPhd @PostdocO
Acta Materia Medica retweeted
A response regression model separates viral-load-driven host responses from genuine HTA effects, improving identification of pharmacologically relevant genes. #Virology #Transcriptomics #antiviral
#AMM #OpenAccess: doi.org/10.15212/AMM-2025-00…
Acta Materia Medica retweeted
Does higher selectivity create higher uncertainty for antibody drugs? A new perspective in #CTSjournal explores how context-dependent pharmacology impacts translation, dose selection, & combination therapy in antibody drug development.
Read more: doi.org/10.1111/cts.70556
Acta Materia Medica retweeted
The future of drug discovery isn't just about proving a drug works.
It's about proving why it can outperform the standard of care.
👉 medvolt.ai
#Medvolt #DrugDiscovery #ClinicalTrials #MedGraph #SystemsBiology #AIDrugDiscovery
🤖 Made with AI
Acta Materia Medica retweeted
In a new publishing deal, #Causaly and @Sage_Publishing have announced a partnership to bring full-text scientific peer-reviewed literature into the world of AI-powered drug discovery research.
#publishing #DrugDiscovery #ArtificialIntelligence
hubs.li/Q04r6GZ10
Acta Materia Medica retweeted
📊 A bioRxiv preprint outlines a computational pipeline for targeting the ELMO1/DOCK2 complex, suggesting open-access AI tools and public structural data could reprice early drug…
🔗 atlas360.news/en/news/elmo1-…
📩 Subscribe: atlas360.news/en/bulten
#health #drugdiscovery #openscience
Acta Materia Medica retweeted
This study validates that #Euphorbia humifusa Willd. extract & #Avicularin inhibit #Inflammation & abnormal #Keratinocyte proliferation in #Psoriasis via their modulatory effects on #IL17 signaling, highlighting both therapeutic promise & methodological strength in #NaturalProduct research.
#OpenAccess: amm-journal.org/index.php/20…
Acta Materia Medica retweeted
This review examines the #Molecular hierarchy and roles of #SKP2 in #CellularHomeostasis, and maps current #therapeutic strategies, aiming to build a #Translational atlas that supports future SKP2-directed interventions for #Cancer and other disorders.
@harvardmed
#OpenAccess:amm-journal.org/index.php/20…
Acta Materia Medica retweeted
'Discovery of Biased Dual-Agonists of Glucagon-Like Peptide 1 and Glucagon Receptors through Mutation of a Conserved Aspartate' from ACS Medicinal Chemistry Letters is currently free to read as an #ACSEditorsChoice.
📖 Read the article: go.acs.org/enP
Acta Materia Medica retweeted
Recent advances in the development of covalent inhibitors - now published in RSC Medicinal Chemistry pubs.rsc.org/en/content/arti…………………………… #chemistry #Bioinformatics #ChemicalProbes #MedicinalChemistry
Acta Materia Medica retweeted
Advancing PROTAC therapeutics requires advanced analytics. This Tech Note from @SCIEXnews demonstrates sensitive ARV-110 quantification in rat plasma, critical for pharmacokinetic studies, safety & efficacy evaluation and preclinical development >>> hubs.ly/Q04gMGc10
Acta Materia Medica retweeted
Feeding data to AI to speed up drug discovery phys.org/news/2026-06-ai-dru…
Acta Materia Medica retweeted
Dual-Acting Vitamin B3-Melanostatin Neuropeptide Hybrids as Potent Modulators of the Dopamine D2 Receptors with Neuroprotective Activity | Journal of Medicinal Chemistry pubs.acs.org/doi/full/10.102…
Acta Materia Medica retweeted
💊 New paper: DesignMaster — rational PROTAC design with multi-conditional diffusion
bioRxiv (Jun 15) | Shi et al.
PROTACs degrade proteins instead of just inhibiting them — but designing them is hard. DesignMaster uses diffusion to jointly optimize the linker & warheads under multiple constraints.
📄 biorxiv.org/content/10.64898…
#DrugDiscovery #AIxBiology #PROTAC #DiffusionModel





























