Chemoinformatics

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25 New Compounds: How Scripps Research Uses Computer Modeling to Transform Drug Discovery
ByAnchal Negi January 15, 2025October 22, 2026

In an extraordinary feat of chemical synthesis, chemists from Scripps Research have produced 25 picrotoxane molecules. This groundbreaking work combines cutting-edge computational modeling and innovative laboratory techniques to navigate the complex pathways of these functionally dense molecules. Their findings, published in Nature, not only shed light on picrotoxane chemistry but also push the boundaries of…

Read More 25 New Compounds: How Scripps Research Uses Computer Modeling to Transform Drug Discovery
AI | Bioinformatics | Chemoinformatics | Drug Discovery | LLM | News | Paper Summary | Tools | Trending

Unlocking New Possibilities in Drug Design: DrugLLM’s Novel Approach to Few-Shot Molecule Generation Using Open Large Language Models
ByDeotima Chakraborty May 16, 2024October 22, 2026

The languages of biology and chemistry are difficult for language processing and computer vision systems to grasp, notwithstanding their advances in language processing. Although LLMs can improve few-shot learning, they are not very good at capturing the connection between pharmacochemical characteristics and molecular structure, which makes small-molecule drug modification less effective in few-shot learning. Researchers…

Read More Unlocking New Possibilities in Drug Design: DrugLLM’s Novel Approach to Few-Shot Molecule Generation Using Open Large Language Models
Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | News | Paper Summary | Protein Design | Structural Biology | Tools | Trending

Unlocking New Drug Targets: Researchers Develop Computational Method to Target Proteins Inside Cell Membranes
ByAnchal Negi March 28, 2024October 22, 2026

Can you imagine that you can design proteins that have a particular function, and they are like small robots working inside our cells? This may be the reality pretty soon. Researchers from the University of California and Yale University came up with an innovative way of creating transmembrane proteins from scratch, thus leading to targeted…

Read More Unlocking New Drug Targets: Researchers Develop Computational Method to Target Proteins Inside Cell Membranes
AI | Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | News | Paper Summary | Structural Biology | Trending

Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
ByAnchal Negi March 7, 2024October 22, 2026

Molecular geometry modeling, which involves building models that show the spatial arrangement of atoms in a molecule, usually helps with this understanding. The field of molecular modeling has been transformed by geometric deep learning. However, due to molecules’ inherent 3D shape and the intricate interactions between their constituent atoms, standard deep learning algorithms need help…

Read More Microsoft Reveals ViSNet: A Cutting-Edge Framework for Molecular Property Prediction and Simulating Molecular Dynamics
AI | Bioinformatics | Chemoinformatics | Computational Models | Drug Discovery | LLM | News | Paper Summary | Trending

Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction
ByDeotima Chakraborty February 21, 2024October 22, 2026

Compound-protein interaction (CPI) prediction accuracy is crucial for drug discovery. Creating deep learning models that can be applied broadly requires expanding the CPI data through experimental validation. With their strong generalization performance in a range of tasks involving substances and proteins, large language models (LLMs) such as chemical and protein language models have become foundational…

Read More Revolutionizing Drug Discovery with ChemGLaM: Chemical-Genomics Language Models for Compound-Protein Interaction Prediction
AI | Chemoinformatics | Drug Discovery | LLM | News | Trending

A GPT-driven Robot Chemist Designs, Plans, and Performs Complex Experiments – All by Itself!
ByDr. Tamanna Anwar December 21, 2023October 22, 2026

Scientists at Carnegie Mellon University have unveiled a breakthrough artificial intelligence system called Coscientist that can independently design and execute complex chemistry experiments at the touch of a button. The system aims to accelerate discoveries across scientific domains by leveraging the raw reasoning power of models like GPT-4. Coscientist combines natural language processing prowess with tools enabling…

Read More A GPT-driven Robot Chemist Designs, Plans, and Performs Complex Experiments – All by Itself!
AI | Bioinformatics | Chemoinformatics | Drug Discovery | News | Paper Summary | Structural Biology | Tools | Trending

DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
BySonal Keni November 10, 2023November 28, 2023

As computationally generated molecules become more popular in the fields of drug development and biotechnology, ease of synthesis becomes a common problem. Often, the molecules generated by machine learning models may be challenging to synthesize and may require many steps, making it too expensive for production. A new deep learning model DeepSA, developed by researchers…

Read More DeepSA: A Cutting-edge Chemical Language Model for Compound Synthesis Accessibility Prediction
Bioinformatics | Chemoinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Trending

Virtual Drug Screening with Less Data: Boosting Predictions with Transfer Learning and Kernel Methods
BySwasti Tyagi September 16, 2023October 22, 2026

A team of researchers at the Eric and Wendy Schmidt Centre at the Broad Institute of MIT and Harvard developed a model that uses kernel methods to facilitate transfer learning. Kernel methods are simple machine learning algorithms that are used to train models on data that has been transformed beforehand. Transfer learning is a technique…

Read More Virtual Drug Screening with Less Data: Boosting Predictions with Transfer Learning and Kernel Methods
AI | Bioengineering | Bioinformatics | Chemoinformatics | News | Paper Summary | Proteomics | Trending

AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein Generation
ByAditi Sarkar August 24, 2023August 24, 2023

The University of Toronto researchers have explored the potential of Chemical Language Models (CLMs) to thrive as Biological Learning Models. In contrast to popular Protein Language Models that learn from protein sequences, CLMs can learn atomic-level representations of proteins and also learn protein backbones and natural amino acid structures, as well as the primary sequence…

Read More AI’s Quantum Leap into Bioengineering: Unleashing Language Models in Atom-by-Atom Protein Generation
AI | Bioinformatics | Chemoinformatics | Deep Learning | Drug Discovery | News | Structural Biology | Tools | Trending

Advancing Drug Discovery with DrugEx: An Open-source Software Package for Exploring the Depths of Drug-like Chemical Space using Deep Learning Models and Tools
ByDr. Tamanna Anwar June 9, 2023October 22, 2026

The discovery of novel molecules with desired properties is a long-standing challenge in medicinal chemistry. On the other hand, de novo drug design tools have been developed as a result of recent developments in machine learning. In spite of the increasing popularity of these technologies, user-friendly and adaptable resources are not available. Scientists from Leiden…

Read More Advancing Drug Discovery with DrugEx: An Open-source Software Package for Exploring the Depths of Drug-like Chemical Space using Deep Learning Models and Tools
AI | Bioinformatics | Chemoinformatics | Machine Learning | News | Paper Summary

Transcriptome-Wide Prediction of Chemical Messenger RNA Modifications: A Novel Approach Using Machine Learning
ByBanhita Maitra May 9, 2023May 21, 2023

Machine learning-based methods have played a significant role in detecting RNA modifications. The advent of new high-throughput experimental and computational techniques has propelled the discovery of RNA modifications. The epitranscriptome refers to the biochemical modifications of the RNA (transcriptome) within a cell. Such modifications significantly impact several biological processes. The authors of the paper published…

Read More Transcriptome-Wide Prediction of Chemical Messenger RNA Modifications: A Novel Approach Using Machine Learning
Bioinformatics | Chemoinformatics | Drug Discovery | News | Paper Summary | Trending

Revolutionizing Fragment-based Drug Discovery: An Automated, Open-Source Workflow for Generating 3D Fragment Libraries
ByBanhita Maitra May 6, 2023October 22, 2026

Scientists from Amsterdam, Netherlands, have developed an automated and open-source workflow for the design of 3D fragment libraries in the KNIME software. Fragment-based drug discovery (FBDD) has proven successful in producing a growing list of clinical candidates, with six approved drugs as of 2022. Fragments, or smaller molecules, are used as screening compounds as opposed…

Read More Revolutionizing Fragment-based Drug Discovery: An Automated, Open-Source Workflow for Generating 3D Fragment Libraries
Cancer Research | Chemoinformatics | Drug Discovery | Machine Learning | News | Paper Summary | Trending

Bridging the Gap between Cheminformatics and Machine Learning to Investigate Androgen Receptor Antagonists in the Fight Against Prostate Cancer
ByBanhita Maitra March 14, 2023October 22, 2026

Researchers from Thailand perform a systematic cheminformatics analysis and machine learning modeling to study how human Androgen Receptors (AR) antagonists combat Prostate cancer, one of the leading causes of death in male cancer patients. Androgen receptor signaling drives the growth and prostate cancer progression. The authors perform the study on human AR antagonists from the…

Read More Bridging the Gap between Cheminformatics and Machine Learning to Investigate Androgen Receptor Antagonists in the Fight Against Prostate Cancer
AI | Bioinformatics | Cancer Research | Chemoinformatics | Chronic Diseases | Computational Models | COVID-19 | Covid-19 News | Drug Discovery | Machine Learning | News | Trending

Speeding Up Drug Formulation Development: Harnessing the Power of Machine Learning
ByDr. Tamanna Anwar January 11, 2023October 22, 2026

Scientists at the University of Toronto advanced drug formulation development by utilizing machine learning techniques to predict and guide the design of long-acting injectable drugs. Through the use of these algorithms, the scientists were able to predict the release of drugs from advanced delivery systems and use this information to inform the design of new…

Read More Speeding Up Drug Formulation Development: Harnessing the Power of Machine Learning
Bioinformatics | Cancer Research | Chemoinformatics | Machine Learning | News | Structural Biology

A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance
ByDr. Tamanna Anwar June 5, 2022June 18, 2022

A team led by the University of Maryland utilizes machine learning to explain why a “wonder drug” may not work in all patients. Understanding how mutations cause a medicine to become ineffective is a huge issue. The mechanism by which mutations produce drug resistance is frequently discussed solely in terms of thermodynamics. The case where…

Read More A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance
AI | Algorithm | AMR Alert | Chemoinformatics | Drug Discovery | Health | News

Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs
ByDr. Tamanna Anwar May 7, 2022October 22, 2026

The widespread use of computational waste-to-value algorithms can speed up the productive reuse of chemicals that would otherwise incur storage or disposal expenses or even pose environmental risks. Scientists from the Ulsan Institute of Science and Technology, Republic of Korea, have developed an innovative strategy to repurpose waste chemicals into usable products using artificial intelligence…

Read More Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs

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Chemoinformatics

25 New Compounds: How Scripps Research Uses Computer Modeling to Transform Drug Discovery

Transcriptome-Wide Prediction of Chemical Messenger RNA Modifications: A Novel Approach Using Machine Learning

A New Computer Simulation Coupled with Machine Learning Cracked the Mechanism of Cancer Drug Resistance

Artificial Intelligence Based ‘Waste-to-Valuable’ Algorithm for Repurposing Chemical Wastes into Useful Drugs

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