In a recent study, we have identified BPH03 as a promising scaffold for the development of compounds aimed at modulating the interaction between PED/PEA15 (Phosphoprotein Enriched in ...Diabetes/Phosphoprotein Enriched in Astrocytes 15) and PLD1 (phospholipase D1), with potential applications in type II diabetes therapy. PED/PEA15 is known to be overexpressed in certain forms of diabetes, where it binds to PLD1, thereby reducing insulin-stimulated glucose transport. The inhibition of this interaction reestablishes basal glucose transport, indicating PED as a potential target of ligands capable to recover glucose tolerance and insulin sensitivity. In this study, we employ computational methods to provide a detailed description of BPH03 interaction with PED, evidencing the presence of a hidden druggable pocket within its PLD1 binding surface. We also elucidate the conformational changes that occur during PED interaction with BPH03. Moreover, we report new NMR data supporting the in-silico findings and indicating that BPH03 disrupts the PED/PLD1 interface displacing PLD1 from its interaction with PED. Our study represents a significant advancement toward the development of potential therapeutics for the treatment of type II diabetes.
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Neuromyelitis optica (NMO) is characterized by the presence of pathogenic autoantibodies (NMO-IgGs) against supra-molecular assemblies of aquaporin-4 (AQP4), known as orthogonal array of particles ...(OAPs). NMO-IgGs have a polyclonal origin and recognize different conformational epitopes involving extracellular AQP4 loops A, C, and E. Here we hypothesize a pivotal role for AQP4 transmembrane regions (TMs) in epitope assembly. On the basis of multialignment analysis, mutagenesis, NMO-IgG binding, and cytotoxicity assay, we have disclosed the key role of aspartate 69 (Asp69) of TM2 for NMO-IgG epitope assembly. Mutation of Asp69 to histidine severely impairs NMO-IgG binding for 85.7% of the NMO patient sera analyzed here. Although Blue Native-PAGE, total internal reflection fluorescence microscopy, and water transport assays indicate that the OAP Asp69 mutant is similar in structure and function to the wild type, molecular dynamic simulations have revealed that the D69H mutation has the effect of altering the structural rearrangements of extracellular loop A. In conclusion, Asp69 is crucial for the spatial control of loop A, the particular molecular conformation of which enables the assembly of NMO-IgG epitopes. These findings provide additional clues for new strategies for NMO treatment and a wealth of information to better approach NMO pathogenesis.
Thiolated self-assembled monolayers (SAMs) are typically used to anchor on a gold surface biomolecules serving as recognition elements for biosensor applications. Here, the design and synthesis of ...N-(2-hydroxyethyl)-3-mercaptopropanamide (NMPA) in biotinylated mixed SAMs is proposed as an alternative strategy with respect to on-site multistep functionalization of SAMs prepared from solutions of commercially available thiols. In this study, the mixed SAM deposited from a 10:1 solution of 3-mercaptopropionic acid (3MPA) and 11-mercaptoundecanoic acid (11MUA) is compared to that resulting from a 10:1 solution of NMPA:11MUA. To this end, surface plasmon resonance (SPR) and attenuated total reflectance infrared (ATR-IR) experiments have been carried out on both mixed SAMs after biotinylation. The study demonstrated how the fine tuning of the SAM features impacts directly on both the biofunctionalization steps, i.e., the biotin anchoring, and the biorecognition properties evaluated upon exposure to streptavidin analyte. Higher affinity for the target analyte with reduced nonspecific binding and lower detection limit has been demonstrated when NMPA is chosen as the more abundant starting thiol. Molecular dynamics simulations complemented the experimental findings providing a molecular rationale behind the performance of the biotinylated mixed SAMs. The present study confirms the importance of the functionalization design for the development of a highly performing biosensor.
The endocannabinoid system (ECS) plays a very important role in numerous physiological and pharmacological processes, such as those related to the central nervous system (CNS), including learning, ...memory, emotional processing, as well pain control, inflammatory and immune response, and as a biomarker in certain psychiatric disorders. Unfortunately, the half-life of the natural ligands responsible for these effects is very short. This perspective describes the potential role of the inhibitors of the enzymes fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MGL), which are mainly responsible for the degradation of endogenous ligands in psychic disorders and related pathologies. The examination was carried out considering both the impact that the classical exogenous ligands such as Δ
-tetrahydrocannabinol (THC) and (-)-trans-cannabidiol (CBD) have on the ECS and through an analysis focused on the possibility of predicting the potential toxicity of the inhibitors before they are subjected to clinical studies. In particular, cardiotoxicity (hERG liability), probably the worst early adverse reaction studied during clinical studies focused on acute toxicity, was predicted, and some of the most used and robust metrics available were considered to select which of the analyzed compounds could be repositioned as possible oral antipsychotics.
Ligand efficiency metrics are almost universally accepted as a valuable indicator of compound quality and an aid to reduce attrition. Areas covered: In this review, the authors describe ligand ...efficiency metrics giving a balanced overview on their merits and points of weakness in order to enable the readers to gain an informed opinion. Relevant theoretical breakthroughs and drug-like properties are also illustrated. Several recent exemplary case studies are discussed in order to illustrate the main fields of application of ligand efficiency metrics. Expert opinion: As a medicinal chemist guide, ligand efficiency metrics perform in a context- and chemotype-dependent manner; thus, they should not be used as a magic box. Since the 'big bang' of efficiency metrics occurred more or less ten years ago and the average time to develop a new drug is over the same period, the next few years will give a clearer outlook on the increased rate of success, if any, gained by means of these new intriguing tools.
In the last few decades, virtual screening has proved to be able to guide the selection of new hit compounds with predefined biological activity. However, the usage of these computational techniques ...is often associated with resource- and time-consuming preparation protocols. In this work we present Commercial Compound Collection (CoCoCo), a suite of free and ready-to-use chemical databases to help setting up in silico screening projects. CoCoCo collects molecular structural information of commercial compounds from various chemical vendors by merging them in a unique, non-redundant format. CoCoCo databases are prepared with transparent and straightforward routines based on state-of-the-art computational tools that introduce comprehensive structural information about tautomers, stereoisomers and conformational states of each compound. CoCoCo suite is especially conceived as a set of valuable tools that may help a wide range of researchers who wish to initiate their own project in the field of computational drug design. CoCoCo suite is available free of charge at the website .
This study introduces a new de novo design algorithm called GENERA that combines the capabilities of a deep-learning algorithm for automated drug-like analogue design, called DeLA-Drug, with a ...genetic algorithm for generating molecules with desired target-oriented properties. Specifically, GENERA was applied to the angiotensin-converting enzyme 2 (ACE2) target, which is implicated in many pathological conditions, including COVID-19. The ability of GENERA to de novo design promising candidates for a specific target was assessed using two docking programs, PLANTS and GLIDE. A fitness function based on the Pareto dominance resulting from computed PLANTS and GLIDE scores was applied to demonstrate the algorithm’s ability to perform multiobjective optimizations effectively. GENERA can quickly generate focused libraries that produce better scores compared to a starting set of known ACE-2 binders. This study is the first to utilize a DL-based algorithm designed for analogue generation as a mutational operator within a GA framework, representing an innovative approach to target-oriented de novo design.
In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers ...and conceived for data-driven generation of similar-to-bioactive compounds. DeLA-Drug captures the syntax of SMILES strings of more than 1 million compounds belonging to the ChEMBL28 database and, by employing a new strategy called sampling with substitutions (SWS), generates molecules starting from a single user-defined query compound. Remarkably, the algorithm preserves druglikeness and synthetic accessibility of the known bioactive compounds present in the ChEMBL28 repository. The absence of any time-demanding fine-tuning procedure enables DeLA-Drug to perform a fast generation of focused libraries for further high-throughput screening and makes it a suitable tool for performing de novo design even in low-data regimes. To provide a concrete idea of its applicability, DeLA-Drug was applied to the cannabinoid receptor subtype 2 (CB2R), a known target involved in different pathological conditions such as cancer and neurodegeneration. DeLA-Drug, available as a free web platform (http://www.ba.ic.cnr.it/softwareic/deladrugportal/), can help medicinal chemists interested in generating analogues of compounds already available in their laboratories and, for this reason, good candidates for an easy and low-cost synthesis.
Abstract
The implementation of nonanimal approaches is of particular importance to regulatory agencies for the prediction of potential hazards associated with acute exposures to chemicals. This work ...was carried out in the framework of an international modeling initiative organized by the Acute Toxicity Workgroup (ATWG) of the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) with the participation of 32 international groups across government, industry, and academia. Our contribution was to develop a multifingerprints similarity approach for predicting five relevant toxicology endpoints related to the acute oral systemic toxicity that are: the median lethal dose (LD50) point prediction, the “nontoxic” (LD50 > 2000 mg/kg) and “very toxic” (LD50<50 mg/kg) binary classification, and the multiclass categorization of chemicals based on the United States Environmental Protection Agency and Globally Harmonized System of Classification and Labeling of Chemicals schemes. Provided by the ICCVAM’s ATWG, the training set used to develop the models consisted of 8944 chemicals having high-quality rat acute oral lethality data. The proposed approach integrates the results coming from a similarity search based on 19 different fingerprint definitions to return a consensus prediction value. Moreover, the herein described algorithm is tailored to properly tackling the so-called toxicity cliffs alerting that a large gap in LD50 values exists despite a high structural similarity for a given molecular pair. An external validation set made available by ICCVAM and consisting in 2896 chemicals was employed to further evaluate the selected models. This work returned high-accuracy predictions based on the evaluations conducted by ICCVAM’s ATWG.
Organic thin film transistors (OTFT) are metal–insulator–semiconductor field-effect transistors in which the semiconductor is a conjugated organic material. They are the subject of intense industrial ...research because their fabrication process is less expensive when compared with inorganic TFTs. Among the others, the organic material mostly employed in their construction consists of two semiconductor polymers, namely poly(3-hexylthiophene) (P3HT) and poly(2,5-bis(3-alkylthiophen-2-yl)thieno3,2-bthiophene) (PBTTT). Despite the large amount of experimental efforts in the characterization of the electronic properties of these devices, several questions regarding their morphological arrangement in bulk and at interfaces remain wide open. Here, we report results obtained by classical molecular dynamics simulations of P3HT and PBTTT inspired by OTFT fabrication techniques. In particular, we investigate how the annealing fabrication process and the presence of residual solvent molecules left over after spin coating might modify the morphology and the dynamics of the amorphous phase of these two polymers. Simulations of both polymer deposits at 300 K after annealing show an increase in the number of interdigitation events between the alkyl chains of two polymeric macromolecules; moreover, we find that the increased stability of the π–π stacking is caused by an improved layering of the films, which may account for the better charge transport properties reported in experiments. Our results strongly suggest that thin semiconductor films are required to boost the performances of the devices and that a minimal presence of residual solvent does not alter dramatically the microscopic structure and stability of the polymeric films.
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