ATP-Binding Cassette and Solute Carrier Transporters: Understanding Their Mechanisms and Drug Modulation Through Structural and Modeling Approaches.

The ATP-binding cassette (ABC) and solute carrier (SLC) transporters play pivotal roles in cellular transport mechanisms, influencing a wide range of physiological processes and impacting various medical conditions. Recent advancements in structural biology and computational modeling have provided significant insights into their function and regulation. This review provides an overview of the current knowledge of human ABC and SLC transporters, emphasizing their structural and functional relationships, transport mechanisms, and the contribution of computational approaches to their understanding.

Recent Applications of Artificial Intelligence in Discovery of New Antibacterial Agents.

Antimicrobial resistance (AMR) represents today a major challenge for global public health, compromising the effectiveness of treatments against a multitude of bacterial infections. In recent decades, artificial intelligence (AI) has emerged as a promising technology for the identification and development of new antibacterial agents. This review focuses on AI methodologies applied to discover new antibacterial candidates.

Machine Learning and Deep Learning Models for Predicting Noncovalent Inhibitors of AmpC β-Lactamase.

Continuous use of antibiotics leads to the ability of bacteria to adapt by developing complex antibiotic resistance (AR) mechanisms. The synthesis of β-lactamases is a widely observed AR mechanism. The class C β-lactamase (AmpC) causes significant resistance toward β-lactam antibiotics, and new treatments are urgently needed.

Mechanistic insights into P-glycoprotein ligand transport and inhibition revealed by enhanced molecular dynamics simulations.

P-glycoprotein (P-gp) plays a crucial role in cellular detoxification and drug efflux processes, transitioning between inward-facing (IF) open, occluded, and outward-facing (OF) states to facilitate substrate transport. Its role is critical in cancer therapy, where P-gp contributes to the multidrug resistance phenotype. In our study, classical and enhanced molecular dynamics (MD) simulations were conducted to dissect the structural and functional features of the P-gp conformational states.

Computational and artificial intelligence-based approaches for drug metabolism and transport prediction.

Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are critical in the early stages of drug development to reduce the rate of drug candidate failure. A variety of experimental and computational technologies have been developed to predict DDIs and ADRs.

Role of Conformational Dynamics of Sulfotransferases SULT1A1 and SULT1A3 in Substrate Specificity.

Sulfotransferases (SULTs) are phase II metabolizing enzymes catalyzing the sulfoconjugation from the co-factor 3'-Phosphoadenosine 5'-Phosphosulfate (PAPS) to a wide variety of endogenous compounds, drugs and natural products. Although SULT1A1 and SULT1A3 share 93% identity, SULT1A1, the most abundant SULT isoform in humans, exhibits a broad substrate range with specificity for small phenolic compounds, while SULT1A3 displays a high affinity toward monoamine neurotransmitters like dopamine. To elucidate the factors determining the substrate specificity of the SULT1 isoenzymes, we studied the dynamic behavior and structural specificities of SULT1A1 and SULT1A3 by using molecular dynamics (MD) simulations and ensemble docking of common and specific substrates of the two isoforms.

Insights into the molecular basis and mechanism of heme-triggered TLR4 signalling: The role of heme-binding motifs in TLR4 and MD2.

Haemolytic disorders, such as sickle cell disease, are accompanied by the release of high amounts of labile heme into the intravascular compartment resulting in the induction of proinflammatory and prothrombotic complications in affected patients. In addition to the relevance of heme-regulated proteins from the complement and blood coagulation systems, activation of the TLR4 signalling pathway by heme was ascribed a crucial role in the progression of these pathological processes. Heme binding to the TLR4-MD2 complex has been proposed recently, however, essential mechanistic information of the processes at the molecular level, such as heme-binding kinetics, the heme-binding capacity and the respective heme-binding sites (HBMs) is still missing.

Serum levels of leptin and adiponectin in patients with autoimmune Hashimoto's thyroiditis.

Introduction: Adipose tissue is immunologically and hormonally active, and these effects are mediated largely by adipocytokines. Thyroid hormones regulate metabolism and organ function, and Hashimoto's thyroiditis (HT) is the most common autoimmune disease affecting thyroid function.

Aim: To evaluate the levels of the adipocytokines leptin and adiponectin in patients with autoimmune HT, and to perform a comparative intragroup analysis in patients with different stages of gland functional activity, and in a control group.

Complement C3a treatment accelerates recovery after stroke via modulation of astrocyte reactivity and cortical connectivity.

Despite advances in acute care, ischemic stroke remains a major cause of long-term disability. Approaches targeting both neuronal and glial responses are needed to enhance recovery and improve long-term outcome. The complement C3a receptor (C3aR) is a regulator of inflammation with roles in neurodevelopment, neural plasticity, and neurodegeneration.

Ruthenium-Catalyzed Cycloaddition for Introducing Chemical Diversity in Second-Generation β-Lactamase Inhibitors.

Ruthenium(II) alkyne azide cycloaddition (RuAAC) is an attractive reaction to access 1,5-triazole derivatives and is applicable to internal alkynes. Here, we explore RuAAC to introduce molecular diversity on the diazabicyclooctane (DBO) scaffold of β-lactamase inhibitors. The methodology presented is fully regioselective and enabled synthesis of a series of 1,5-triazole DBOs and trisubstituted analogues.

Machine learning and structure-based modeling for the prediction of UDP-glucuronosyltransferase inhibition.

UDP-glucuronosyltransferases (UGTs) are responsible for 35% of the phase II drug metabolism. In this study, we focused on UGT1A1, which is a key UGT isoform. Strong inhibition of UGT1A1 may trigger adverse drug/herb-drug interactions, or result in disorders of endobiotic metabolism.

Pharmacogenetics of human sulfotransferases and impact of amino acid exchange on Phase II drug metabolism.

Sulfotransferases (SULTs) are Phase II drug-metabolizing enzymes (DMEs) catalyzing the sulfation of a variety of endogenous compounds, natural products, and drugs. Various drugs, such as nonsteroidal anti-inflammatory drugs (NSAIDS) can inhibit SULTs, affecting drug-drug interactions. Several polymorphisms have been identified for SULTs that might be crucial for interindividual variability in drug response and toxicity or for increased disease risk.

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9.

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug-drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity.

Computational Analysis of Chemical Space of Natural Compounds Interacting with Sulfotransferases.

The aim of this study was to investigate the chemical space and interactions of natural compounds with sulfotransferases (SULTs) using ligand- and structure-based in silico methods. An in-house library of natural ligands (hormones, neurotransmitters, plant-derived compounds and their metabolites) reported to interact with SULTs was created. Their chemical structures and properties were compared to those of compounds of non-natural (synthetic) origin, known to interact with SULTs.

Insights into the substrate binding mechanism of SULT1A1 through molecular dynamics with excited normal modes simulations.

Sulfotransferases (SULTs) are phase II drug-metabolizing enzymes catalyzing the sulfoconjugation from the co-factor 3'-phosphoadenosine 5'-phosphosulfate (PAPS) to a substrate. It has been previously suggested that a considerable shift of SULT structure caused by PAPS binding could control the capability of SULT to bind large substrates. We employed molecular dynamics (MD) simulations and the recently developed approach of MD with excited normal modes (MDeNM) to elucidate molecular mechanisms guiding the recognition of diverse substrates and inhibitors by SULT1A1.

New machine learning and physics-based scoring functions for drug discovery.

Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring functions remains a challenging task. The performance of scoring functions is very heterogeneous across different target classes.

Fr-PPIChem: An Academic Compound Library Dedicated to Protein-Protein Interactions.

Protein-protein interactions (PPIs) mediate nearly every cellular process and represent attractive targets for modulating disease states but are challenging to target with small molecules. Despite this, several PPI inhibitors (iPPIs) have entered clinical trials, and a growing number of PPIs have become validated drug targets. However, high-throughput screening efforts still endure low hit rates mainly because of the use of unsuitable screening libraries.

Anti-Factor B Antibodies and Acute Postinfectious GN in Children.

Background: The pathophysiology of the leading cause of pediatric acute nephritis, acute postinfectious GN, including mechanisms of the pathognomonic transient complement activation, remains uncertain. It shares clinicopathologic features with C3 glomerulopathy, a complement-mediated glomerulopathy that, unlike acute postinfectious GN, has a poor prognosis.

Methods: This retrospective study investigated mechanisms of complement activation in 34 children with acute postinfectious GN and low C3 level at onset.

A Free Web-Based Protocol to Assist Structure-Based Virtual Screening Experiments.

Chemical biology and drug discovery are complex and costly processes. In silico screening approaches play a key role in the identification and optimization of original bioactive molecules and increase the performance of modern chemical biology and drug discovery endeavors. Here, we describe a free web-based protocol dedicated to small-molecule virtual screening that includes three major steps: ADME-Tox filtering (via the web service FAF-Drugs4), docking-based virtual screening (via the web service MTiOpenScreen), and molecular mechanics optimization (via the web service AMMOS2 [Automatic Molecular Mechanics Optimization for in silico Screening]).

Comparative structural and evolutionary analyses predict functional sites in the artemisinin resistance malaria protein K13.

Numerous mutations in the Plasmodium falciparum Kelch13 (K13) protein confer resistance to artemisinin derivatives, the current front-line antimalarial drugs. K13 is an essential protein that contains BTB and Kelch-repeat propeller (KREP) domains usually found in E3 ubiquitin ligase complexes that target substrate protein(s) for ubiquitin-dependent degradation. K13 is thought to bind substrate proteins, but its functional/interaction sites and the structural alterations associated with artemisinin resistance mutations remain unknown.

Analysis of solvent-exposed and buried co-crystallized ligands: a case study to support the design of novel protein-protein interaction inhibitors.

Molecular descriptors have been used to characterize and predict the functions of small molecules, including inhibitors of protein-protein interactions (iPPIs). Such molecules are valuable to investigate disease pathways and as starting points for drug discovery endeavors. iPPIs tend to bind at the surface of macromolecules and the design of such compounds remains challenging.

Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets.

Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery.

Insights into molecular mechanisms of drug metabolism dysfunction of human CYP2C9*30.

Cytochrome P450 2C9 (CYP2C9) metabolizes about 15% of clinically administrated drugs. The allelic variant CYP2C9*30 (A477T) is associated to diminished response to the antihypertensive effects of the prodrug losartan and affected metabolism of other drugs. Here, we investigated molecular mechanisms involved in the functional consequences of this amino-acid substitution.

Structural Dynamics of DPP-4 and Its Influence on the Projection of Bioactive Ligands.

Dipeptidyl peptidase-4 (DPP-4) is a target to treat type II diabetes mellitus. Therefore, it is important to understand the structural aspects of this enzyme and its interaction with drug candidates. This study involved molecular dynamics simulations, normal mode analysis, binding site detection and analysis of molecular interactions to understand the protein dynamics.