Articles tagged with Drug Discovery
Researchers developed Epitope Binning-seq to analyze epitopes in monoclonal antibodies. The method accurately classified antibodies into distinct epitope bins, providing valuable insights into their binding patterns and streamlining early antibody drug development.
Researchers have developed a route to modify peptides to target disease diagnostics and drug discovery, focusing on protein-protein interactions (PPIs). By modifying a small peptide sequence, the team showed it binds more quickly and strongly to specific PPI targets.
A study led by Washington State University scientists found that inhibiting CDK7 could help prevent heart damage associated with doxorubicin, a commonly used cancer chemotherapy medication. The researchers also discovered that CDK7 inhibition enhances the medication's cancer-killing capability.
Researchers at Texas A&M University developed vessel-chip technology to create a platform for preclinical drug discovery, reducing the need for animal testing. The system mimics human circulatory systems using tissue-engineered microfluidic devices.
Researchers at Okayama University developed a novel AAK1 inhibitor using Kinobeads technology, shedding light on its inhibitory mechanism and targeting various neurological disorders and viral infections. This breakthrough paves the way for rapid and cost-effective enzyme inhibitors with clinical applications.
The latest SLAS Technology issue highlights recent breakthroughs in skin cutaneous melanoma, glycan-bead coupling, and acoustic ejection mass spectrometry. Researchers adapt technological advancements for life sciences exploration and experimentation in biomedical research and development.
Researchers develop an in vitro model to study tau aggregation, a process linked to neurodegenerative diseases like Alzheimer's and frontotemporal dementia. The approach offers a short timeline for generating data and facilitates the study of potential therapeutic interventions.
Dr. George Bray's paper tracks the development of obesity research over 100 years, from early explorations to modern medication interventions. The study highlights the chronic and relapsing nature of obesity as a disease process.
Nach0 was trained on diverse tasks, including natural language understanding, synthetic route prediction, and molecular generation. The model performed well on molecular tasks using molecular data and outperformed ChatGPT, making it a significant step toward unlocking the full potential of LLMs for drug discovery.
A recent study by Bryan Roth and colleagues validated the accuracy of AlphaFold2 in modeling ligand binding sites, leading to promising results for drug discovery. The researchers found that up to 54% of potential compounds interacted successfully with the target proteins, paving the way for new treatments.
Insilico Medicine's lead compound demonstrates strong enzymatic activity, selectivity, and favorable ADME properties, as well as antitumor activity in various animal models. The company's generative AI-powered platform generated over 3,600 candidate molecules before identifying the promising lead compound.
Researchers at UC San Diego developed a machine learning algorithm to simulate chemistry in drug discovery, synthesizing 32 potential multi-target cancer drugs. The new AI platform, POLYGON, can identify molecules with multiple targets, potentially delivering more effective treatments with fewer side effects.
Researchers at Insilico Medicine developed COSMIC, a new framework for molecular conformation space modeling that provides accurate insights into molecule positioning and activity. This enables faster and more efficient drug design decisions.
Researchers at CeMM and Pfizer have developed a novel method to measure the binding activity of hundreds of small molecules against thousands of human proteins. The study revealed tens of thousands of ligand-protein interactions that can now be explored for drug development.
Researchers at CeMM Research Center create 'vpCells' method for simultaneous fluorescent labelling of many proteins, enabling precise tracking and exploration of protein function. The approach opens up new applications in fundamental cell biology and drug discovery.
The University of Birmingham's Drug Discovery Hub has developed a novel approach to drug discovery, enabling projects to overcome the funding gap between original research and commercial investment. The hub has attracted over £4m in industry funding, grants, and awards, with a successful portfolio of projects.
Researchers at Insilico Medicine have identified a new class of Polθ inhibitors featuring central scaffolding rings, designed using Chemistry42, with significant enzymatic and cellular potency. The discovery showcases the potential of AI in medicinal chemistry for precise molecular modifications.
A new statistical-modeling workflow can quickly identify molecular structures of products formed by chemical reactions, accelerating drug discovery and synthetic chemistry. The workflow also enables the analysis of unpurified reaction mixtures, reducing time spent on purification and characterization.
The KEDD framework integrates structured and unstructured knowledge to enhance predictive accuracy in AI-driven drug discovery. It outperforms existing models in critical tasks, including the 'missing modality problem', by leveraging sparse attention and modality masking techniques.
Researchers develop AI-powered method to rapidly predict multiple protein configurations, understanding protein dynamics and functions. This breakthrough has the potential to revolutionize drug discovery by uncovering more targets for new treatments.
Researchers have developed a new, synthetic lung surfactant that mimics the functionality of animal-derived formulations. The surfactant has shown promise in reducing surface tension and may offer a cheaper alternative to Infasurf.
A newly developed compound is showing promise as a more effective treatment for human schistosomiasis, an understudied tropical disease caused by parasitic worms. The compound overcomes the limitations of current treatment praziquantel by being effective against the larval stage and resistant strains.
Researchers at the University of Toronto and Sinai Health have created a new platform to identify proteins that can be co-opted to control the stability of other proteins. The study identified over 600 new effector proteins that could be used therapeutically, including those that can efficiently degrade or stabilize target proteins.
Researchers at Xi'an Jiaotong-Liverpool University developed a new method that enables the efficient production of cysteine-rich peptides and microproteins in their naturally folded 3D structure. The approach uses organic solvents to mimic nature's oxidative folding process, resulting in speeds of over 100,000 times faster than aqueous...
Researchers have identified a potential path to eliminate the viral reservoir that prevents people from being completely cured of HIV. A new drug candidate, called a proteolysis targeting chimeras (PROTAC) molecule, triggers the degradation of the Nef protein, which suppresses HIV replication and restores immune system detection. This ...
Researchers have discovered compounds that can activate estrogen-related receptors (ERRs), similar to the effects of exercise on metabolism and muscle growth. The new compounds may offer a substitute for exercise in people with medical conditions, such as heart failure and neurodegenerative disease.
Researchers have identified a subset of T-cells that acts like stem cells and continuously generates effector T-cells that attack transplanted organs. Targeting the transcription factor IRF4 may lead to innovative therapies for patients with chronic infections, cancers, autoimmune diseases and transplanted organs.
A new study suggests that mushroom extract containing psilocybin demonstrates superior efficacy in stimulating neuroplasticity and promoting new connections between nerve cells. The research found that the extract had a more potent and prolonged impact on synaptic plasticity compared to chemically synthesized psilocybin.
Researchers used generative AI to design a lead molecule for treating fibrosis, a biological process associated with aging. The compound, INS018_055, demonstrated significant efficacy in preclinical studies and showed promising results in clinical trials, accelerating drug discovery and providing new therapeutic options.
A network of African scientists has secured funding to develop new drugs for malaria and TB, two major diseases affecting the continent. The Grand Challenges Africa Drug Discovery Accelerator Programme will support leading research efforts on these diseases.
Researchers at University at Buffalo propose a new approach to developing cancer drugs by determining the optimal placement of molecular linkers earlier in the process, reducing trial and error and increasing potency, according to a study published in Communications Chemistry.
Researchers at City of Hope have developed a new approach to target and destroy hard-to-kill leukemia stem cells. The therapy method uses Type II interferon to disrupt the cancer cells' ability to divide, and a T cell engager antibody to create a bridge between the immune system and the leukemia stem cells.
PandaOmics uses advanced AI algorithms to process vast quantities of diverse data, performing gene and pathway analysis and target predictions. The platform has been extensively validated in multiple therapeutic areas, including oncology, inflammation, and immunology.
Scientists from IOCB Prague have developed a universal and accurate new computational method to predict how proteins interact with drugs. The SQM2.20 scoring function yields DFT-quality predictions in minutes, significantly accelerating drug discovery.
Researchers at North Carolina State University are developing a suite of performance metrics to standardize the evaluation of self-driving labs in chemistry and materials science. These metrics aim to compare different lab technologies and identify areas for improvement, ultimately advancing the field and accelerating discovery.
A new AI tool, DeepGO-SE, successfully predicts the molecular functions of unknown proteins with high accuracy. This breakthrough enables researchers to analyze uncharacterized proteins, facilitating tasks such as drug discovery, metabolic pathway analysis, and disease associations.
A recent study has identified a promising solution to combat resistance to protein degraders, which are a novel approach in drug discovery. The researchers found that the drug RBS-10 selectively removes resistant cells by targeting the enzyme NQO1, which is overexpressed in these cells.
Insilico Medicine has discovered a novel PHD inhibitor for treating anemia using its AI-powered generative chemistry platform Chemistry42. The compound demonstrated favorable ADMET and PK profiles in animal models, showing promise for further investigations.
Researchers at Insilico Medicine have identified MYT1 as a promising therapeutic target for breast and gynecological cancers. A series of novel, potent, and highly selective inhibitors specifically targeting MYT1 were discovered using AI-driven generative biology and chemistry engine.
The CACHE Challenge series has identified seven promising molecules with potential for new, more effective drugs for familial Parkinson's disease. The open science competition, funded by The Michael J. Fox Foundation and Conscience, used AI to predict hits and validated experimental results.
Researchers developed a platform combining automated experiments with AI to predict chemical reactivity, greatly accelerating the design process for new drugs. A machine learning model predicts where molecules will react and how reaction sites vary under different conditions, enabling precise tweaks to complex molecules.
A new catalyst developed by researchers at Nagoya University successfully synthesized a key intermediate for the incontinence drug oxybutynin in 5-30 minutes, significantly faster than existing methods. The discovery represents a major advance in chiral drug synthesis and holds great promise for future drug discovery efforts.
A global study has identified over 200 genes linked to depression, including 50 new genetic loci and 205 novel genes. The research also suggests potential for drug repurposing and highlights the need for more diverse genetic datasets to develop effective treatments.
The University of Rochester is establishing a new NIH-funded center focused on developing FDA-qualified drug development tools related to barrier functions in disease. Researchers will create microphysiological systems with ultrathin membranes of human cells, aiming to reduce animal trials and improve drug efficacy.
The Colorado Center for Personalized Medicine has hit a major milestone of returning clinical genetic results to over 30,000 patients, making it a leader in providing personalized patient care. The center is also studying pharmacogenomics and providing results to guide drug selection and dosing.
Researchers discovered new antibiotic molecules targeting Mycobacterium tuberculosis, reducing its pathogenicity. These substances also enhance the activity of conventional antibiotics like ethionamide, offering a renewed treatment approach.
Researchers have found a way to control MYC's hyperactivity using a peptide compound with sub-micro-molar affinity. This breakthrough offers hope for more effective treatments for cancer patients.
A new synthetic antibiotic teixobactin has been shown to be highly effective against 'superbugs' such as MRSA and bacterial biofilms, which are associated with serious chronic infections. The study's findings provide promising hope for the development of new treatments against multidrug-resistant bacteria and biofilm-related infections.
Researchers have developed a new method to generate cyclic peptides that can target diseases and be administered orally, overcoming challenges in protein binding. The approach enables high-throughput screening and has shown substantial bioavailability in rats, opening possibilities for treating various diseases.
Researchers develop a novel protein killer and discover a new ligase for PROTACs, which can specifically target and degrade pathological proteins in specific tissues. This breakthrough could enable the targeted degradation of proteins in tumors.
Researchers at the University of Bath have created a novel bacterial system to mass-produce cyclic proteins and peptides, addressing a significant bottleneck in the development of new therapeutic treatments. By harnessing the natural cyclization process from the Oldenlandia flower, they improved heat and chemical stability, as well as ...
A Phase II clinical trial has demonstrated that fosravuconazole is effective in treating mycetoma, a chronic disabling disease. The new oral treatment has been shown to have significant advantages over existing treatments, including a lower pill burden and minimal interactions with other medications.
This special collection in SLAS Discovery highlights the significant impact of high-content imaging in basic and translational research. Researchers have made advancements in cell painting and phenotypic profiling, offering new therapeutic approaches for diseases such as Gaucher's.
A small molecule called YM022 has been discovered to block aversive memory formation in mice, offering a new direction for developing anti-depressants. The study found that YM022 suppressed neuroplasticity-caused aversive memory formation and reduced depressive behaviors in mice.
Researchers have discovered two new cofactorless oxygenases, TnmJ and TnmK2, which enable bacteria to produce compounds for targeting and breaking up DNA. This breakthrough offers a potentially easier way to study and manufacture complex natural chemicals, including those that could become medicines.
Researchers have identified a crucial biological trigger of Huntington's disease, finding that methylation converts an important protein into waste. By targeting this process, they may develop effective therapies for other neurodegenerative diseases.
Researchers developed a waterproof device that captures and enriches dissolved compounds in seawater, revealing diverse elemental compositions and unknown molecular structures, with potential applications for drug discovery and ecosystem health monitoring.
Scientists at Nagoya University developed a new gastric acid inhibitor with a binding affinity nearly 10 times higher than existing drugs. The AI-driven approach led to the creation of compound DQ-18, which exhibits stronger binding to the gastric proton pump.
New study reveals that microtubule poisons effectively treat cancer by causing abnormal cell division, leading to tumor cell death. The findings contradict decades-long assumptions about the mechanism of action of these drugs.
Cleveland Clinic is selected by Wellcome Leap to lead two quantum computing research projects in collaboration with IBM Quantum and Algorithmiq. The projects aim to accelerate the development of quantum computing applications for healthcare, with a focus on protein structure prediction and photon-drug interactions in cancer treatment.