A Nano-QSTR model to predict nano-cytotoxicity: an approach using human lung cells data.

Background: The widespread use of new engineered nanomaterials (ENMs) in industries such as cosmetics, electronics, and diagnostic nanodevices, has been revolutionizing our society. However, emerging studies suggest that ENMs present potentially toxic effects on the human lung. In this regard, we developed a machine learning (ML) nano-quantitative-structure-toxicity relationship (QSTR) model to predict the potential human lung nano-cytotoxicity induced by exposure to ENMs based on metal oxide nanoparticles.

A novel machine learning-based screening identifies statins as inhibitors of the calcium pump SERCA.

We report a novel small-molecule screening approach that combines data augmentation and machine learning to identify Food and Drug Administration (FDA)-approved drugs interacting with the calcium pump (Sarcoplasmic reticulum Ca-ATPase, SERCA) from skeletal (SERCA1a) and cardiac (SERCA2a) muscle. This approach uses information about small-molecule effectors to map and probe the chemical space of pharmacological targets, thus allowing to screen with high precision large databases of small molecules, including approved and investigational drugs. We chose SERCA because it plays a major role in the excitation-contraction-relaxation cycle in muscle and it represents a major target in both skeletal and cardiac muscle.

Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds.

We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries.

Nanosafety: An Evolving Concept to Bring the Safest Possible Nanomaterials to Society and Environment.

The use of nanomaterials has been increasing in recent times, and they are widely used in industries such as cosmetics, drugs, food, water treatment, and agriculture. The rapid development of new nanomaterials demands a set of approaches to evaluate the potential toxicity and risks related to them. In this regard, nanosafety has been using and adapting already existing methods (toxicological approach), but the unique characteristics of nanomaterials demand new approaches (nanotoxicology) to fully understand the potential toxicity, immunotoxicity, and (epi)genotoxicity.

Yes SIR! On the structure-inactivity relationships in drug discovery.

In analogy with structure-activity relationships (SARs), which are at the core of medicinal chemistry, studying structure-inactivity relationships (SIRs) is essential to understanding and predicting biological activity. Current computational methods should predict or distinguish 'activity' and 'inactivity' with the same confidence because both concepts are complementary. However, the lack of inactivity data, in particular in the public domain, limits the development of predictive models and its broad application.

An pipeline for the discovery of multitarget ligands: A case study for epi-polypharmacology based on DNMT1/HDAC2 inhibition.

The search for novel therapeutic compounds remains an overwhelming task owing to the time-consuming and expensive nature of the drug development process and low success rates. Traditional methodologies that rely on the one drug-one target paradigm have proven insufficient for the treatment of multifactorial diseases, leading to a shift to multitarget approaches. In this emerging paradigm, molecules with off-target and promiscuous interactions may result in preferred therapies.

Nanomaterial Exposure, Extracellular Vesicle Biogenesis and Adverse Cellular Outcomes: A Scoping Review.

The progressively increasing use of nanomaterials (NMs) has awakened issues related to nanosafety and its potential toxic effects on human health. Emerging studies suggest that NMs alter cell communication by reshaping and altering the secretion of extracellular vesicles (EVs), leading to dysfunction in recipient cells. However, there is limited understanding of how the physicochemical characteristics of NMs alter the EV content and their consequent physiological functions.

Rationality over fashion and hype in drug design.

The current hype associated with machine learning and artificial intelligence often confuses scientists and students and may lead to uncritical or inappropriate applications of computational approaches. Even the field of computer-aided drug design (CADD) is not an exception. The situation is ambivalent.

Conserved Luminal C-Terminal Domain Dynamically Controls Interdomain Communication in Sarcolipin.

Sarcolipin (SLN) mediates Ca transport and metabolism in muscle by regulating the activity of the Ca pump SERCA. SLN has a conserved luminal C-terminal domain that contributes to its functional divergence among homologous SERCA regulators, but the precise mechanistic role of this domain remains poorly understood. We used all-atom molecular dynamics (MD) simulations of SLN totaling 77.

A hallmark of phospholamban functional divergence is located in the N-terminal phosphorylation domain.

Sarcoplasmic reticulum Ca pump (SERCA) is a critical component of the Ca transport machinery in myocytes. There is clear evidence for regulation of SERCA activity by PLB, whose activity is modulated by phosphorylation of its N-terminal domain (residues 1-25), but there is less clear evidence for the role of this domain in PLB's functional divergence. It is widely accepted that only sarcolipin (SLN), a protein that shares substantial homology with PLB, uncouples SERCA Ca transport from ATP hydrolysis by inducing a structural change of its energy-transduction domain; yet, experimental evidence shows that the transmembrane domain of PLB (residues 26-52, PLB) partially uncouples SERCA .

Structural Basis for the Limited Response to Oxidative and Thiol-Conjugating Agents by Triosephosphate Isomerase From the Photosynthetic Bacteria .

In plants, the ancestral cyanobacterial triosephosphate isomerase (TPI) was replaced by a duplicated version of the cytosolic TPI. This isoform acquired a transit peptide for chloroplast localization and functions in the Calvin-Benson cycle. To gain insight into the reasons for this gene replacement in plants, we characterized the TPI from the photosynthetic bacteria (SyTPI).

Structural basis for relief of phospholamban-mediated inhibition of the sarcoplasmic reticulum Ca-ATPase at saturating Ca conditions.

Sarcoplasmic reticulum Ca-ATPase (SERCA) is critical for cardiac Ca transport. Reversal of phospholamban (PLB)-mediated SERCA inhibition by saturating Ca conditions operates as a physiological rheostat to reactivate SERCA function in the absence of PLB phosphorylation. Here, we performed extensive atomistic molecular dynamics simulations to probe the structural mechanism of this process.

Preexisting domain motions underlie protonation-dependent structural transitions of the P-type Ca-ATPase.

We have performed microsecond molecular dynamics (MD) simulations to determine the mechanism for protonation-dependent structural transitions of the sarco/endoplasmic reticulum Ca-ATPase (SERCA), one of the most prominent members of the large P-type ATPase superfamily that transports ions across biological membranes. The release of two H from the transport sites activates SERCA by inducing a structural transition between low (E2) and high (E1) Ca-affinity states (E2-to-E1 transition), but the structural mechanism by which transport site deprotonation facilitates this transition is unknown. We performed microsecond all-atom MD simulations to determine the effects of transport site protonation on the structural dynamics of the E2 state in solution.

Database fingerprint (DFP): an approach to represent molecular databases.

Background: Molecular fingerprints are widely used in several areas of chemoinformatics including diversity analysis and similarity searching. The fingerprint-based analysis of chemical libraries, in particular of large collections, usually requires the molecular representation of each compound in the library that may lead to issues of storage space and redundant calculations. In fact, information redundancy is inherent to the data, resulting on binary digit positions in the fingerprint without significant information.

Design and synthesis of N-benzoyl amino acid derivatives as DNA methylation inhibitors.

The inhibition of human DNA Methyl Transferases (DNMT) is a novel promising approach to address the epigenetic dysregulation of gene expression in different diseases. Inspired by the validated virtual screening hit NSC137546, a series of N-benzoyl amino acid analogues was synthesized and obtained compounds were assessed for their ability to inhibit DNMT-dependent DNA methylation in vitro. The biological screening allowed the definition of a set of preliminary structure-activity relationships and the identification of compounds promising for further development.

Developmental DNA methyltransferase inhibitors in the treatment of gynecologic cancers.

Introduction: DNA methylation has become an attractive target for the treatment of cancer. DNA methyltransferase inhibitors have proven useful for the treatment of myelodysplastic syndrome and are being evaluated in gynecological neoplasias.

Areas Covered: We provide an overview of the current knowledge on DNA methylation and cancer and the role of DNA methylation in cervical, ovarian and endometrial carcinomas.