GPCR Conformations: Implications for Rational Drug Design
Ontology highlight
ABSTRACT:
SUBMITTER: Parrill A
PROVIDER: S-EPMC4052540 | biostudies-literature | 2010 Dec
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The purinergic signaling system includes membrane-bound receptors for extracellular purines and pyrimidines, and enzymes/transporters that regulate receptor activation by endogenous agonists. Receptors include: adenosine (A1 , A2A , A2B, and A3 ) and P2Y (P2Y1 , P2Y2 , P2Y4 , P2Y6 , P2Y11 , P2Y12 , P2Y13 , and P2Y14 ) receptors (all GPCRs), as well as P2X receptors (ion channels). Receptor activation, especially accompanying physiological stress or damage, creates a temporal sequence of signaling to counteract this stress and either mobilize (P2Rs) or suppress (ARs) immune responses. Thus, modulation of this large signaling family has broad potential for treating chronic diseases. Experimentally determined structures represent each of the three receptor families. We focus on selective purinergic agonists (A1 , A3 ), antagonists (A3 , P2Y14 ), and allosteric modulators (P2Y1 , A3 ). Examples of applying structure-based design, including the rational modification of known ligands, are presented for antithrombotic P2Y1 R antagonists and anti-inflammatory P2Y14 R antagonists and A3 AR agonists. A3 AR agonists are a potential, nonaddictive treatment for chronic neuropathic pain.
| S-EPMC8276773 | biostudies-literature
Project description:BACKGROUND: HIV-1 replication can be successfully blocked by targeting gag gene products, offering a promising strategy for new drug classes that complement current HIV-1 treatment options. However, naturally occurring polymorphisms at drug binding sites can severely compromise HIV-1 susceptibility to gag inhibitors in clinical and experimental studies. Therefore, a comprehensive understanding of gag natural diversity is needed. FINDINGS: We analyzed the degree of functional conservation in 10862 full-length gag sequences across 8 major HIV-1 subtypes and identified the impact of natural variation on known drug binding positions targeted by more than 20 gag inhibitors published to date. Complete conservation across all subtypes was detected in 147 (29%) out of 500 gag positions, with the highest level of conservation observed in capsid protein. Almost half (41%) of the 136 known drug binding positions were completely conserved, but all inhibitors were confronted with naturally occurring polymorphisms in their binding sites, some of which correlated with HIV-1 subtype. Integration of sequence and structural information revealed one drug binding pocket with minimal genetic variability, which is situated at the N-terminal domain of the capsid protein. CONCLUSIONS: This first large-scale analysis of full-length HIV-1 gag provided a detailed mapping of natural diversity across major subtypes and highlighted the considerable variation in current drug binding sites. Our results contribute to the optimization of gag inhibitors in rational drug design, given that drug binding sites should ideally be conserved across all HIV-1 subtypes.
| S-EPMC4228425 | biostudies-literature
Project description:Paradigms in drug design and discovery are changing at a significant pace. Concomitant to the sequencing of over 180 several genomes, the high-throughput miniaturization of chemical synthesis and biological evaluation of a multiple compounds on gene/protein expression and function opens the way to global drug-discovery approaches, no more focused on a single target but on an entire family of related proteins or on a full metabolic pathway. Chemogenomics is this emerging research field aimed at systematically studying the biological effect of a wide array of small molecular-weight ligands on a wide array of macromolecular targets. Since the quantity of existing data (compounds, targets and assays) and of produced information (gene/protein expression levels and binding constants) are too large for manual manipulation, information technologies play a crucial role in planning, analysing and predicting chemogenomic data. The present review will focus on predictive in silico chemogenomic approaches to foster rational drug design and derive information from the simultaneous biological evaluation of multiple compounds on multiple targets. State-of-the-art methods for navigating in either ligand or target space will be presented and concrete drug design applications will be mentioned.
| S-EPMC1978269 | biostudies-other
Project description:Due to the synergic relationship between medical chemistry, bioinformatics and molecular simulation, the development of new accurate computational tools for small molecules drug design has been rising over the last years. The main result is the increased number of publications where computational techniques such as molecular docking, de novo design as well as virtual screening have been used to estimate the binding mode, site and energy of novel small molecules. In this work I review some tools, which enable the study of biological systems at the atomistic level, providing relevant information and thereby, enhancing the process of rational drug design.
| S-EPMC5039900 | biostudies-literature
Project description:Rationally designing drugs that last longer in the face of biological evolution is a critical objective of drug discovery. However, this goal is thwarted by the diversity and stochasticity of evolutionary trajectories that drive uncertainty in the clinic. Although biophysical models can qualitatively predict whether a mutation causes resistance, they cannot quantitatively predict the relative abundance of resistance mutations in patient populations. We present stochastic, first-principle models that are parameterized on a large in vitro dataset and that accurately predict the epidemiological abundance of resistance mutations across multiple leukemia clinical trials. The ability to forecast resistance variants requires an understanding of their underlying mutation biases. Beyond leukemia, a meta-analysis across prostate cancer, breast cancer, and gastrointestinal stromal tumors suggests that resistance evolution in the adjuvant setting is influenced by mutational bias. Our analysis establishes a principle for rational drug design: when evolution favors the most probable mutant, so should drug design.
| S-EPMC8000225 | biostudies-literature
Project description: Not available
| S-EPMC3285144 | biostudies-literature
Project description:In order to efficiently deliver anticancer agents to tumors, biocompatible nanoparticles or bioconjugates, including antibody-drug conjugates (ADCs), have recently been designed, synthesized, and tested, some even in clinical trials. Controlled delivery can be enhanced by changing specific design characteristics of the bioconjugate such as its size, the nature of the payload, and the surface features. The delivery of macromolecular drugs to cancers largely relies on the leaky nature of the tumor vasculature compared with healthy vessels in normal organs. When administered intravenously, macromolecular bioconjugates and nanosized agents tend to circulate for prolonged times, unless they are small enough to be excreted by the kidney or stealthy enough to evade the macrophage phagocytic system (MPS), formerly the reticulo-endothelial system (RES). Therefore, macromolecular bioconjugates and nanosized agents with long circulation times leak preferentially into tumor tissue through permeable tumor vessels and are then retained in the tumor bed due to reduced lymphatic drainage. This process is known as the enhanced permeability and retention (EPR) effect. However, success of cancer drug delivery only relying on the EPR effect is still limited. To cure cancer patients, further improvement of drug delivery is required by both designing superior agents and enhancing EPR effects. In this Review, we describe the basis of macromolecular or nanosized bioconjugate delivery into cancer tissue and discuss current diagnostic methods for evaluating leakiness of the tumor vasculature. Then, we discuss methods to augment conventional "permeability and retention" effects for macromolecular or nanosized bioconjugates in cancer tissue.
| S-EPMC4275162 | biostudies-other
Project description:Using searching techniques based on algorithms derived from graph theory, we have established a similarity between a 3-dimensional cluster of side chains implicated in drug binding in influenza sialidase and side chains involved in isocitrate binding in Escherichia coli isocitrate dehydrogenase. The possible implications of the use of such comparative methods in drug design are discussed.
| S-EPMC2142892 | biostudies-other
Project description:There are over 420 human solute carrier (SLC) transporters from 65 families that are expressed ubiquitously in the body. The SLCs mediate the movement of ions, drugs, and metabolites across membranes and their dysfunction has been associated with a variety of diseases, such as diabetes, cancer, and central nervous system (CNS) disorders. Thus, SLCs are emerging as important targets for therapeutic intervention. Recent technological advances in experimental and computational biology allow better characterization of SLC pharmacology. Here we describe recent approaches to modulate SLC transporter function, with an emphasis on the use of computational approaches and computer-aided drug design (CADD) to study nutrient transporters. Finally, we discuss future perspectives in the rational design of SLC drugs.
| S-EPMC7082830 | biostudies-literature
Project description:LpxC is an essential enzyme in the lipid A biosynthetic pathway in gram-negative bacteria. Several promising antimicrobial lead compounds targeting LpxC have been reported, though they typically display a large variation in potency against different gram-negative pathogens. We report that inhibitors with a diacetylene scaffold effectively overcome the resistance caused by sequence variation in the LpxC substrate-binding passage. Compound binding is captured in complex with representative LpxC orthologs, and structural analysis reveals large conformational differences that mostly reflect inherent molecular features of distinct LpxC orthologs, whereas ligand-induced structural adaptations occur at a smaller scale. These observations highlight the need for a molecular understanding of inherent structural features and conformational plasticity of LpxC enzymes for optimizing LpxC inhibitors as broad-spectrum antibiotics against gram-negative infections.
| S-EPMC3149848 | biostudies-literature