Outputs (58)

Artificial intelligence for small molecule anticancer drug discovery (2024)
Journal Article

Introduction: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has several advantages. Despit... Read More about Artificial intelligence for small molecule anticancer drug discovery.

Solvent flashcards: a visualisation tool for sustainable chemistry. (2024)
Journal Article

Selecting greener solvents during experiment design is imperative for greener chemistry. While many solvent selection guides are currently used in the pharmaceutical industry, these are often paper-based guides which can make it difficult to identify... Read More about Solvent flashcards: a visualisation tool for sustainable chemistry..

Machine learning insights into predicting biogas separation in metal-organic frameworks (2024)
Journal Article

Breakthroughs in efficient use of biogas fuel depend on successful separation of carbon dioxide/methane streams and identification of appropriate separation materials. In this work, machine learning models are trained to predict biogas separation pro... Read More about Machine learning insights into predicting biogas separation in metal-organic frameworks.

Discovery of novel SOS1 inhibitors using machine learning (2024)
Journal Article

Overactivation of the rat sarcoma virus (RAS) signaling is responsible for 30% of all human malignancies. Son of sevenless 1 (SOS1), a crucial node in the RAS signaling pathway, could modulate RAS activation, offering a promising therapeutic strategy... Read More about Discovery of novel SOS1 inhibitors using machine learning.

Applications of Quantum Chemistry in Biomimetic Syntheses of Polycyclic Furanocembrane Derivatives (2024)
Journal Article

This paper summarizes the guidance provided by quantum chemical calculations to the biomimetic syntheses of polycyclic marine furanocembrane derivatives. Polycyclic furanocembrane derivatives are a group of structurally complex and biologically impor... Read More about Applications of Quantum Chemistry in Biomimetic Syntheses of Polycyclic Furanocembrane Derivatives.

Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations (2023)
Journal Article

Excipients are included within protein biotherapeutic solution formulations to improve colloidal and conformational stability but are generally not designed for the specific purpose of preventing aggregation and improving cryoprotection in solution.... Read More about Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations.

Electrocatalytic CO2 reduction to C2H4: From lab to fab (2023)
Journal Article

The global concerns of energy crisis and climate change, primarily caused by carbon dioxide (CO2), are of utmost importance. Recently, the electrocatalytic CO2 reduction reaction (CO2RR) to high value-added multi-carbon (C2+) products driven by renew... Read More about Electrocatalytic CO2 reduction to C2H4: From lab to fab.

Theoretical analysis of divalent cation effects on aptamer recognition of neurotransmitter targets (2023)
Journal Article

Aptamer-based sensing of small molecules such as dopamine and serotonin in the brain, requires characterization of the specific aptamer sequences in solutions mimicking the in vivo environment with physiological ionic concentrations. In particular, d... Read More about Theoretical analysis of divalent cation effects on aptamer recognition of neurotransmitter targets.

Synergistic engineering of heteronuclear Ni-Ag dual-atom catalysts for high-efficiency CO2 electroreduction with nearly 100% CO selectivity (2023)
Journal Article

Single-atom catalysts (SACs) have emerged as attractive materials for the electrocatalytic carbon dioxide reduction (ECO2R). Dual-atom catalysts (DACs), an extension of SACs, exhibit more compelling functionalities due to the synergistic effects betw... Read More about Synergistic engineering of heteronuclear Ni-Ag dual-atom catalysts for high-efficiency CO2 electroreduction with nearly 100% CO selectivity.

ML meets MLn: machine learning in ligand promoted homogeneous catalysis (2023)
Journal Article

The benefits of using machine learning approaches in the design, optimisation and understanding of homogeneous catalytic processes are being increasingly realised. We focus on the understanding and implementation of key concepts, which serve as condu... Read More about ML meets MLn: machine learning in ligand promoted homogeneous catalysis.