A structure-oriented kinetics dataset of enzyme-substrate interactions.

Enzymes are essential biological catalysts that drive nearly all biochemical reactions. Understanding their efficiency and specificity involves studying enzyme kinetics, particularly the parameters k and K. However, there is limited data linking these kinetic parameters with the three-dimensional (3D) structures of enzyme-substrate complexes.

Diet-induced obesity in mice increases carotid body chemosensitivity via the leptin-TRPM7 pathway.

Diet-induced obesity (DIO) is associated with increased circulating level of the hormone leptin. We have previously shown that leptin augments hypoxic ventilatory response in mice, and the response is abolished by carotid body (CB) denervation, and that leptin induces hypertension in DIO acting on transient receptor potential melastatin 7 (Trpm7) channels in CB. However CB chemosensory responses in DIO have not been sufficiently elucidated.

Preparation and characterization of HfOC/SiOC composite powders and fibermats the polymer pyrolysis route.

We report on the synthesis and characterization of HfOC/SiOC ceramic composite powders and electrospun fibermats, which integrate the high-temperature resilience of HfOC with the oxidation resistance of silicon oxycarbide (SiOC). The composites were fabricated through a polymer-pyrolysis route by integrating 1,3,5,7-tetramethyl, 1,3,5,7-tetravinyl cyclotetrasiloxane (4-TTCS), a precursor source for SiOC, and a commercial HfC precursor in a 1 : 1 ratio by mass. First, the HfC precursor was heated to 70 °C to drive off water molecules, followed by its blending with the liquid phase 4-TTCS and cross-linking at a moderate temperature (160-400 °C).

Bulk synthesis of mixed transition metal dichalcogenide and performance as working electrode in Li, Na, and K-ion half cells.

Nanosheets of mixed or cation-substituted Transition metal dichalcogenide (TMD) are promising materials for a range of applications, including electrodes for electrochemical energy storage devices. Yet such materials are expensive to produce in large quantities (gram levels or higher). Here, we report on a two-step process, which involves precursor pyrolysis and sulfur annealing for the preparation of bulk powders of MoWS.

Instantaneous formation of interstellar minerals and mineral quantum dots.

Our understanding of the formation pathways of interstellar mineral dust is still evolving. This study investigated the formation of astrophysical mineral dust, such as olivine, by shock processing. Low-velocity (∼1.

DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning.

Ribonucleic Acid (RNA) is the central conduit for information transfer in the cell. Identifying potential RNA targets in disease conditions is a challenging task, given the vast repertoire of functional non-coding RNAs in a human cell. A potential druggable target must satisfy several criteria, including disease association, cellular accessibility, binding pockets for drug-like molecules, and minimal cross-reactivity.

Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature.

With the advent of artificial intelligence (AI), it is now possible to design diverse and novel molecules from previously unexplored chemical space. However, a challenge for chemists is the synthesis of such molecules. Recently, there have been attempts to develop AI models for retrosynthesis prediction, which rely on the availability of a high-quality training dataset.

C Fullerene-Reinforced Silicon Oxycarbide Composite Fiber Mats: Performance as Li-Ion Battery Electrodes.

Precursor-derived silicon oxycarbide (SiOC) has emerged as a potential high-capacity anode material for rechargeable Li-ion batteries. The polymer processing and pyrolysis route, a hallmark of polymer-derived ceramics, allows chemical interfacing with a variety of nanoprecursors and nanofiller phases to produce composites with low-dimensional structures such as fibers and coatings not readily attained in traditional sintered ceramics. Here, buckminsterfullerene or C was introduced as a filler phase in a hybrid precursor of 1,3,5,7-tetramethyl-1,3,5,7-tetravinyl-cyclotetrasiloxane (TTCS) along with polyvinylpyrrolidone or PVP as a spinning agent to fabricate electrospun fiber mats, which upon a high-heat treatment transformed to a C-reinforced SiOC ceramic composite.

MoS, WS, and MoWS Flakes as Reversible Host Materials for Sodium-Ion and Potassium-Ion Batteries.

Transition-metal dichalcogenides (TMDs) and their alloys are vital for the development of sustainable and economical energy storage alternatives due to their large interlayer spacing and hosting ability for alkali-metal ions. Although the Li-ion chemically correlates with the Na-ion and K-ion, research on batteries with TMD anodes for K is still in its infancy. This research explores TMDs such as molybdenum disulfide (MoS) and tungsten disulfide (WS) and TMD alloys such as molybdenum tungsten disulfide (MoWS) for both sodium-ion batteries (NIBs) and potassium-ion batteries (KIBs).

Addressing Irreversibility and Structural Distortion in WS Inorganic Fullerene-Like Nanoparticles: Effects of Voltage Cutoff Experiments in Beyond Li-Ion Storage Applications.

Large interlayer spacing beneficially allows Na- and K-ion storage in transition-metal dichalcogenide (TMD)-based electrodes, but side reactions and volume change, which pulverize the TMD crystalline structure, are persistent challenges for the utilization of these materials in next-generation devices. This study first determines whether irreversibility due to structural distortion, which results in poor cycling stability, is also apparent in the case of inorganic fullerene-like (IF) tungsten disulfide (WS) nanocages (WSIF). To address these problems, this study proposes upper and lower voltage cutoff experiments to limit specific reactions in Na/WSIF and K/WSIF half-cells.

Green synthesis of copper nanoparticles by using pineapple peel waste: in vitro characterizations and antibacterial potential.

A considerable amount of fruit waste is being produced every day worldwide. The green synthesis of metal nanoparticles from fruit peel waste can be an innovative, cost-effective, and eco-friendly alternative to traditional methods. Copper nanoparticles (CuNPs) were synthesized by a green method using the pineapple peels extract (PLX) and copper sulfate pentahydrate.

Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process.

Application of Artificial intelligence (AI) in drug discovery has led to several success stories in recent times. While traditional methods mostly relied upon screening large chemical libraries for early-stage drug-design, de novo design can help identify novel target-specific molecules by sampling from a much larger chemical space. Although this has increased the possibility of finding diverse and novel molecules from previously unexplored chemical space, this has also posed a great challenge for medicinal chemists to synthesize at least some of the de novo designed novel molecules for experimental validation.

Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning.

Ribonucleic acids (RNAs) play important roles in cellular regulation. Consequently, dysregulation of both coding and non-coding RNAs has been implicated in several disease conditions in the human body. In this regard, a growing interest has been observed to probe into the potential of RNAs to act as drug targets in disease conditions.

pBRICS: A Novel Fragmentation Method for Explainable Property Prediction of Drug-Like Small Molecules.

Generative artificial intelligence algorithms have shown to be successful in exploring large chemical spaces and designing novel and diverse molecules. There has been considerable interest in developing predictive models using artificial intelligence for drug-like properties, which can potentially reduce the late-stage attrition of drug candidates or predict the properties of novel AI-designed molecules. Concurrently, it is important to understand the contribution of functional groups toward these properties and modify them to obtain property-optimized lead compounds.

Topoisomerase VIB and Spo11 Constitute Functional Type IIB Topoisomerase in Malaria Parasite: Its Possible Role in Mitochondrial DNA Segregation.

The human malaria parasite undergoes a noncanonical cell division, namely, endoreduplication, where several rounds of nuclear, mitochondrial, and apicoplast replication occur without cytoplasmic division. Despite its importance in biology, the topoisomerases essential for decatenation of replicated chromosome during endoreduplication remain elusive. We hypothesize that the topoisomerase VI complex, containing Plasmodium falciparum topiosomerase VIB (PfTopoVIB) and catalytic P.

Gex2SGen: Designing Drug-like Molecules from Desired Gene Expression Signatures.

Drug-induced gene expression profiling provides a lot of useful information covering various aspects of drug discovery and development. Most importantly, this knowledge can be used to discover drugs' mechanisms of action. Recently, deep learning-based drug design methods are in the spotlight due to their ability to explore huge chemical space and design property-optimized target-specific drug molecules.

Amentoflavone and methyl hesperidin, novel lead molecules targeting epitranscriptomic modulator in acute myeloid leukemia: in silico drug screening and molecular dynamics simulation approach.

Introduction: MA modification in transcriptome is critical in regulating different cellular processes, including cancer. In human beings, METTL3 is the major mA writer that works in association with METTL14, an accessory protein. Extensive study revealed that cancer progression for acute myeloid leukemia, gastric cancer, colorectal cancer, hepatocellular carcinoma, and lung cancer is directly contributed by irregular expression of METTL3.

R-SIM: A Database of Binding Affinities for RNA-small Molecule Interactions.

Ribonucleic acids (RNAs) are involved in a multitude of crucial cellular functions by acting as a central conduit for information transfer. Due to their essential and versatile functional roles in the cell, RNAs have also been implicated in multiple disease conditions of therapeutic relevance including cancers, bacterial and viral infections and neurodegenerative disorders. Recently, several approaches have emerged to tap into the potentially unexplored regions of the druggable genome, which refers to the genes and gene products that are focused during drug development.

Sonochemical synthesis and biological evaluation of isoquinolin-1(2H)-one/isoindolin-1-one derivatives: Discovery of a positive ago-allosteric modulator (PAAM) of 5HTR.

Efforts have been devoted for the discovery and development of positive allosteric modulators (PAMs) of 5-HTR because of their potential advantages over the orthosteric agonist like Lorcaserin that was withdrawn from the market. On the other hand, pursuing a positive ago-allosteric modulator (PAAM) is considered as beneficial particularly when an agonist is not capable of affecting the potency of the endogenous agonist sufficiently. In search of a suitable PAAM of 5-HTR we adopted an in silico based approach that indicated the potential of the 3-(1-hydroxycycloalkyl) substituted isoquinolin-1-one derivatives against the 5-HTR as majority of these molecules interacted with the site other than that of Lorcaserin with superior docking scores.

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to drug resistance. Thus, there is a critical need for identification of novel anti-tuberculosis agents targeting Mtb-specific proteins. The ceaseless search for novel antimicrobial agents to combat drug-resistant bacteria can be accelerated by the development of advanced deep learning methods, to explore both existing and uncharted regions of the chemical space.

Tissue-specific mitochondrial HIGD1C promotes oxygen sensitivity in carotid body chemoreceptors.

Mammalian carotid body arterial chemoreceptors function as an early warning system for hypoxia, triggering acute life-saving arousal and cardiorespiratory reflexes. To serve this role, carotid body glomus cells are highly sensitive to decreases in oxygen availability. While the mitochondria and plasma membrane signaling proteins have been implicated in oxygen sensing by glomus cells, the mechanism underlying their mitochondrial sensitivity to hypoxia compared to other cells is unknown.

An interpretable machine learning model for selectivity of small-molecules against homologous protein family.

In the early stages of drug discovery, various experimental and computational methods are used to measure the specificity of small molecules against a target protein. The selectivity of small molecules remains a challenge leading to off-target side effects. We have developed a multitask deep learning model for predicting the selectivity on closely related homologs of the target protein.

An Explainable Multiparameter Optimization Approach for Drug Design against Proteins from the Central Nervous System.

The aim of drug design and development is to produce a drug that can inhibit the target protein and possess a balanced physicochemical and toxicity profile. Traditionally, this is a multistep process where different parameters such as activity and physicochemical and pharmacokinetic properties are optimized sequentially, which often leads to high attrition rate during later stages of drug design and development. We have developed a deep learning-based drug design method that can design novel small molecules by optimizing target specificity as well as multiple parameters (including late-stage parameters) in a single step.