Matched pairs demonstrate robustness against inter-assay variability.

Machine learning models for chemistry require large datasets, often compiled by combining data from multiple assays. However, combining data without careful curation can introduce significant noise. While absolute values from different assays are rarely comparable, trends or differences between compounds are often assumed to be consistent.

Discovery of non-retinoid compounds that suppress the pathogenic effects of misfolded rhodopsin in a mouse model of retinitis pigmentosa.

Pathogenic mutations that cause rhodopsin misfolding lead to a spectrum of currently untreatable blinding diseases collectively termed retinitis pigmentosa. Small molecules to correct rhodopsin misfolding are therefore urgently needed. In this study, we utilized virtual screening to search for drug-like molecules that bind to the orthosteric site of rod opsin and improve its folding and trafficking.

Exploring the druggability of the UEV domain of human TSG101 in search for broad-spectrum antivirals.

The ubiquitin E2 variant domain of TSG101 (TSG101-UEV) plays a pivotal role in protein sorting and virus budding by recognizing PTAP motifs within ubiquitinated proteins. Disruption of TSG101-UEV/PTAP interactions has emerged as a promising strategy for the development of host-oriented broad-spectrum antivirals with low susceptibility to resistance. TSG101 is a challenging target characterized by an extended and flat binding interface, low affinity for PTAP ligands, and complex binding energetics.

Effect of Silibinin on Human Pancreatic Lipase Inhibition and Gut Microbiota in Healthy Volunteers: A Randomized Controlled Trial.

Thistle () has been traditionally employed for liver protection. However, we recently identified silibinin, the main bioactive compound of thistle extract, as an in vitro pancreatic lipase inhibitor, which suggested a potential role as an anti-obesity agent. This study aimed to assess, in vivo, the efficacy, safety, and effects of silibinin on human lipase.

TOLEDO: enhancing Maestro GUI for non-expert users to perform massive MD simulations.

Classical Molecular Dynamics (MD) simulates the dynamical evolution of biological systems at the atomic level. Using MD in conjunction with high-performance computing (HPC) architectures, we can evaluate the possible interactions between a ligand library against one protein target to find a drug that can influence a protein target to cure a disease. Simultaneously, we can also obtain information about their dynamic evolution.

Assessment of the Interaction of Acetylcholinesterase Binding with Bioactive Compounds from Coffee and Coffee Fractions Digested in the Gastrointestinal Tract.

The aim of the study was to evaluate the degree of acetylcholinesterase (AChE) inhibition by green and light- and dark-roasted coffee extracts and their fractions after digestion in a simulated gastrointestinal tract. The analysis was carried out using isothermal titration calorimetry, molecular docking, and dynamics simulations. The results showed that 3--caffeoylquinic acid binds strongly to AChE through hydrogen interactions with the amino acids ARG289A, HIS440A, and PHE288A and hydrophobic interactions with TYR121A in the active site of the enzyme.

Analysis of AlphaFold and molecular dynamics structure predictions of mutations in serpins.

Serine protease inhibitors (serpins) include thousands of structurally conserved proteins playing key roles in many organisms. Mutations affecting serpins may disturb their conformation, leading to inactive forms. Unfortunately, conformational consequences of serpin mutations are difficult to predict.

Phage display identification of high-affinity ligands for human TSG101-UEV: A structural and thermodynamic study of PTAP recognition.

The ubiquitin E2 variant domain of TSG101 (TSG101-UEV) plays a pivotal role in protein sorting and virus budding by recognizing PTAP motifs within ubiquitinated proteins. Disrupting TSG101-UEV/PTAP interactions has emerged as a promising strategy for the development of novel host-oriented antivirals with a broad spectrum of action. Nonetheless, finding inhibitors with good properties as therapeutic agents remains a challenge since the key determinants of binding affinity and specificity are still poorly understood.

Research into how carvacrol and metformin affect several human proteins in a hyperglycemic condition: A comparative study in silico and in vitro.

Carvacrol (CV) is an organic compound found in the essential oils of many aromatic herbs. It is nearly unfeasible to analyze all the current human proteins for a query ligand using in vitro and in vivo methods. This study aimed to clarify whether CV possesses an anti-diabetic feature via Docking-based inverse docking and molecular dynamic (MD) simulation and in vitro characterization against a set of novel human protein targets.

Monastrol suppresses invasion and metastasis in human colorectal cancer cells by targeting fascin independent of kinesin-Eg5 pathway.

Rearrangement of the actin cytoskeleton is a prerequisite for carcinoma cells to develop cellular protrusions, which are required for migration, invasion, and metastasis. Fascin is a key protein involved in actin bundling and is expressed in aggressive and invasive carcinomas. Additionally, fascin appears to be involved in tubulin-binding and microtubule rearrangement.

Geometric deep learning methods and applications in 3D structure-based drug design.

3D structure-based drug design (SBDD) is considered a challenging and rational way for innovative drug discovery. Geometric deep learning is a promising approach that solves the accurate model training of 3D SBDD through building neural network models to learn non-Euclidean data, such as 3D molecular graphs and manifold data. Here, we summarize geometric deep learning methods and applications that contain 3D molecular representations, equivariant graph neural networks (EGNNs), and six generative model methods [diffusion model, flow-based model, generative adversarial networks (GANs), variational autoencoder (VAE), autoregressive models, and energy-based models].

Enhancing MD simulations: ASGARD's automated analysis for GROMACS.

Molecular Dynamics (MD) simulations are essential in analyzing the physical movement of molecules, with GROMACS being a widely recognized open-source package for this purpose. However, conducting analyses individually in GROMACS can take excessive time and effort. Addressing this challenge, we introduce ASGARD, an innovative workflow designed to streamline and automate the analysis of MD simulation of protein or protein-ligand complex.

Identification of potent inhibitors of kynurenine-3-monooxygenase from natural products: approaches.

Existing inhibitors of kynurenine-3-monooxygenase (KMO) have side effects and poorly cross the blood-brain barrier. Therefore, the discovery of new molecules targeting KMO isnecessary.This study aims to develop a novel therapeutic drug targeting KMO using computational methods and experimental validation of natural compounds.

An Interpretable Machine Learning Approach to Predict Sensory Processing Sensitivity Trait in Nursing Students.

Sensory processing sensitivity (SPS) is a personality trait that makes certain individuals excessively sensitive to stimuli. People carrying this trait are defined as Highly Sensitive People (HSP). The SPS trait is notably prevalent among nursing students and nurse staff.

Comparative assessment of different anti-CD147/Basigin 2 antibodies as a potential therapeutic anticancer target by molecular modeling and dynamic simulation.

Cluster of differentiation 147 (CD147) is an attractive target for anticancer therapy since it is pivotal in developing and progressing several of malignant tumors in the context of its high expression levels. Although anti-CD147 antibodies by different laboratories are designed for the Ig-like domains of CD147, there is a demand to provide priority among these anti-CD147 antibodies for developing of therapeutic anti-CD147 antibody before experimental validations. This study uses molecular docking and dynamic simulation techniques to compare the binding modes and affinities of nine antibody models against the Ig-like domains of CD147.

Vitamin-C-dependent downregulation of the citrate metabolism pathway potentiates pancreatic ductal adenocarcinoma growth arrest.

In pancreatic ductal adenocarcinoma (PDAC), metabolic rewiring and resistance to standard therapy are closely associated. PDAC cells show enormous requirements for glucose-derived citrate, the first rate-limiting metabolite in the synthesis of new lipids. Both the expression and activity of citrate synthase (CS) are extraordinarily upregulated in PDAC.

ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery.

Drug development is a complex, costly, and time-consuming endeavor. While high-throughput screening (HTS) plays a critical role in the discovery stage, it is one of many factors contributing to these challenges. In certain contexts, virtual screening can complement the HTS, potentially offering a more streamlined approach in the initial stages of drug discovery.

Identification of new potential candidates to inhibit EGF via machine learning algorithm.

One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerate the drug discovery process. Hence, an ensemble computational-experimental approach, consisting of three steps, a machine learning model, simulation of drug-target interaction and experimental characterization, was developed.

Suramin, a drug for the treatment of trypanosomiasis, reduces the prothrombotic and metastatic phenotypes of colorectal cancer cells by inhibiting hepsin.

Unlabelled: Recently, our group identified serine-protease hepsin from primary tumor as a biomarker of metastasis and thrombosis in patients with localized colorectal cancer. We described hepsin promotes invasion and thrombin generation of colorectal cancer cells in vitro and in vivo and identified venetoclax as a hepsin inhibitor that suppresses these effects. Now, we aspire to identify additional hepsin inhibitors, aiming to broaden the therapeutic choices for targeted intervention in colorectal cancer.

Antcin-B, a phytosterol-like compound from Taiwanofungus camphoratus inhibits SARS-CoV-2 3-chymotrypsin-like protease (3CL) activity in silico and in vitro.

Despite the remarkable development of highly effective vaccines, including mRNA-based vaccines, within a limited timeframe, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not been entirely eradicated. Thus, it is crucial to identify new effective anti-3CL compounds, pivotal for the replication of SARS-CoV-2. Here, we identified an antcin-B phytosterol-like compound from Taiwanofungus camphoratus that targets 3CL activity.

Exploring the Antioxidant Properties of Caffeoylquinic and Feruloylquinic Acids: A Computational Study on Hydroperoxyl Radical Scavenging and Xanthine Oxidase Inhibition.

Caffeoylquinic (5-CQA) and feruloylquinic (5-FQA) acids, found in coffee and other plant sources, are known to exhibit diverse biological activities, including potential antioxidant effects. However, the underlying mechanisms of these phenolic compounds remain elusive. This paper investigates the capacity and mode of action of 5-CQA and 5-FQA as natural antioxidants acting as hydroperoxyl radical scavengers and xanthine oxidase (XO) inhibitors.

Effects of In Vitro Digestion of Polyphenols from Coffee on Binding Parameters to Human Topoisomerase II α.

Type II topoisomerase (TOPII) is an enzyme that influences the topology of DNA. DNA breaks generated by TOPII may result in mutagenic or cytotoxic changes in cancer cells. In this study, we characterized interactions of TOPIIα with coffee extracts and individual chlorogenic acids (CHAs) from the extracts by performing isothermal titration calorimetry (ITC) and molecular docking (MD) simulations.

Venetoclax is a potent hepsin inhibitor that reduces the metastatic and prothrombotic phenotypes of hepsin-expressing colorectal cancer cells.

Hepsin is a type II transmembrane serine protease and its expression has been linked to greater tumorigenicity and worse prognosis in different tumors. Recently, our group demonstrated that high hepsin levels from primary tumor were associated with a higher risk of metastasis and thrombosis in localized colorectal cancer patients. This study aims to explore the molecular role of hepsin in colorectal cancer.

Effect of Inhibiting Butyrylcholinesterase Activity Using Fractionated Coffee Extracts Digested In Vitro in Gastrointestinal Tract: Docking Simulation and Calorimetric and Studies.

Butyrylcholinesterase (BChE) is a major enzyme from the alpha-glycoprotein family that catalyzes the hydrolysis of neurotransmitter acetylcholine (ACh), lowering the concentration of ACh in the nervous system, which could cause aggravation of Alzheimer's disease (AD). In select pathological conditions, it is beneficial to reduce the activity of this enzyme. The aim of this study was to evaluate the degree of BChE inhibition by coffee extracts fractionated into mono- and diesters of caffeic acid/caffeine, digested in vitro in the gastrointestinal tract.