HessFit: A Toolkit to Derive Automated Force Fields from Quantum Mechanical Information.

In this study, we introduce a novel approach to enhance the accuracy of molecular dynamics simulations by refining the force fields (FFs) through a combination of transferable parameters and molecule-specific characteristics derived from quantum mechanical (QM) calculations. Traditional FFs often prioritize generality over precision, leading to limitations in the accuracy of accurately capturing intra- and intermolecular interactions. To address this, we present an open-source toolkit, called HessFit, designed to integrate QM-derived bonded parameters and atomic charges into existing FFs. In combination with bond, angle, torsional, and nonbonded parameters derivation, HessFit can easily extract multiple barrier terms of dihedrals from QM Hessian and gradient or return all terms through a fitting procedure scheme of QM potential energy surface. We showcase the effectiveness of HessFit through comprehensive evaluations of vibrational properties across a diverse set of small molecules and demonstrate that experimental results support its ability in predicting thermodynamic properties of organic molecules compared to previous state-of-the-art approaches. We further explore its application to Zn2+ metalloprotein models, which are hard systems to treat with automatic approaches. Our results demonstrate that HessFit parameters compete with GAFF2 and OPLS parameters to describing small organic molecules, and its feasibility is also comparable to current FFs used to modeling nonstandard residues in Zn proteins for molecular dynamics simulations. The effectiveness of the HessFit protocol makes it a valuable tool for deriving or extending force field parameters for novel compounds in several molecular modeling applications.

Synthesis and in vitro cytotoxicity of benzoxazole-based PPARα/γ antagonists in colorectal cancer cell lines.

A series of benzoxazole-based amides and sulfonamides were synthesized and evaluated for their human peroxisome proliferator-activated receptor (PPAR)α and PPARγ activity. All tested compounds showed a dual antagonist profile on both PPAR subtypes; based on transactivation results, seven compounds were selected to test their in vitro antiproliferative activity in a panel of eight cancer cell lines with different expression rates of PPARα and PPARγ. 3f was identified as the most cytotoxic compound, with higher potency in the colorectal cancer cell lines HT-29 and HCT116. Compound 3f induced a concentration-dependent activation of caspases and cell-cycle arrest in both colorectal cancer models. Docking experiments were also performed to shed light on the putative binding mode of this novel class of dual PPARα/γ antagonists.

The Crosstalk between N-Formyl Peptide Receptors and uPAR in Systemic Sclerosis: Molecular Mechanisms, Pathogenetic Role and Therapeutic Opportunities.

Systemic Sclerosis (SSc) is a heterogeneous autoimmune disease characterized by widespread vasculopathy, the presence of autoantibodies and the progressive fibrosis of skin and visceral organs. There are still many questions about its pathogenesis, particularly related to the complex regulation of the fibrotic process, and to the factors that trigger its onset. Our recent studies supported a key role of N-formyl peptide receptors (FPRs) and their crosstalk with uPAR in the fibrotic phase of the disease. Here, we found that dermal fibroblasts acquire a proliferative phenotype after the activation of FPRs and their interaction with uPAR, leading to both Rac1 and ERK activation, c-Myc phosphorylation and Cyclin D1 upregulation which drive cell cycle progression. The comparison between normal and SSc fibroblasts reveals that SSc fibroblasts exhibit a higher proliferative rate than healthy control, suggesting that an altered fibroblast proliferation could contribute to the initiation and progression of the fibrotic process. Finally, a synthetic compound targeting the FPRs/uPAR interaction significantly inhibits SSc fibroblast proliferation, paving the way for the development of new targeted therapies in fibrotic diseases.

Impairment of Nucleolin Activity and Phosphorylation by a Trachylobane Diterpene from Psiadia punctulata in Cancer Cells.

Human nucleolin (hNcl) is a multifunctional protein involved in the progression of various cancers and plays a key role in other pathologies. Therefore, there is still unsatisfied demand for hNcl modulators. Recently, we demonstrated that the plant ent-kaurane diterpene oridonin inhibits hNcl but, unfortunately, this compound is quite toxic for healthy cells. Trachylobane diterpene 6,19-dihydroxy-ent-trachiloban-17-oic acid (compound 12) extracted from Psiadia punctulata (DC.) Vatke (Asteraceae) emerged as a ligand of hNcl from a cellular thermal shift assay (CETSA)-based screening of a small library of diterpenes. Effective interaction between this compound and the protein was demonstrated to occur both in vitro and inside two different types of cancer cells. Based on the experimental and computational data, a model of the hNcl/compound 12 complex was built. Because of this binding, hNcl mRNA chaperone activity was significantly reduced, and the level of phosphorylation of the protein was affected. At the biological level, cancer cell incubation with compound 12 produced a cell cycle block in the subG0/G1 phase and induced early apoptosis, whereas no cytotoxicity towards healthy cells was observed. Overall, these results suggested that 6,19-dihydroxy-ent-trachiloban-17-oic could represent a selective antitumoral agent and a promising lead for designing innovative hNcl inhibitors also usable for therapeutic purposes.

Pharmacophore hybridization approach to discover novel pyrazoline-based hydantoin analogs with anti-tumor efficacy.

In search for new and safer anti-cancer agents, a structurally guided pharmacophore hybridization strategy of two privileged scaffolds, namely diaryl pyrazolines and imidazolidine-2,4-dione (hydantoin), was adopted resulting in a newfangled series of compounds (H1-H22). Herein, a bio-isosteric replacement of "pyrrolidine-2,5-dione" moiety of our recently reported antitumor hybrid incorporating diaryl pyrazoline and pyrrolidine-2,5-dione scaffolds with "imidazoline-2,4-dione" moiety has been incorporated. Complete biological studies revealed the most potent analog among all i.e. compound H13, which was at-least 10-fold more potent compared to the corresponding pyrrolidine-2,5-dione, in colon and breast cancer cells. In-vitro studies showed activation of caspases, arrest of G0/G1 phase of cell cycle, decrease in the expression of anti-apoptotic protein (Bcl-2) and increased DNA damage. In-vivo assay on HT-29 (human colorectal adenocarcinoma) animal xenograft model unveiled the significant anti-tumor efficacy along with oral bioavailability with maximum TGI 36% (i.p.) and 44% (per os) at 50 mg/kg dose. These findings confirm the suitability of hybridized pyrazoline and imidazolidine-2,4-dione analog H13 for its anti-cancer potential and starting-point for the development of more efficacious analogs.

Antagonizing S1P3 Receptor with Cell-Penetrating Pepducins in Skeletal Muscle Fibrosis.

S1P is the final product of sphingolipid metabolism, which interacts with five widely expressed GPCRs (S1P1-5). Increasing numbers of studies have indicated the importance of S1P3 in various pathophysiological processes. Recently, we have identified a pepducin (compound KRX-725-II) acting as an S1P3 receptor antagonist. Here, aiming to optimize the activity and selectivity profile of the described compound, we have synthesized a series of derivatives in which Tyr, in position 4, has been substituted with several natural aromatic and unnatural aromatic and non-aromatic amino acids. All the compounds were evaluated for their ability to inhibit vascular relaxation induced by KRX-725 (as S1P3 selective pepducin agonist) and KRX-722 (an S1P1-selective pepducin agonist). Those selective towards S1P3 (compounds V and VII) were also evaluated for their ability to inhibit skeletal muscle fibrosis. Finally, molecular dynamics simulations were performed to derive information on the preferred conformations of selective and unselective antagonists.

Inhibition mechanism of naphthylphenylamine derivatives acting on the CDC25B dual phosphatase and analysis of the molecular processes involved in the high cytotoxicity exerted by one selected derivative in melanoma cells.

The dual phosphatases CDC25 are involved in cell cycle regulation and overexpressed in many tumours, including melanoma. CDC25 is a promising target for discovering anticancer drugs, and several studies focussed on characterisation of quinonoid CDC25 inhibitors, frequently causing undesired side toxic effects. Previous work described an optimisation of the inhibition properties by naphthylphenylamine (NPA) derivatives of NSC28620, a nonquinonoid CDC25 inhibitor. Now, the CDC25B•inhibitor interaction was investigated through fluorescence studies, shedding light on the different inhibition mechanism exerted by NPA derivatives. Among the molecular processes, mediating the specific and high cytotoxicity of one NPA derivative in melanoma cells, we observed decrease of phosphoAkt, increase of p53, reduction of CDC25 forms, cytochrome c cytosolic translocation and increase of caspase activity, that lead to the activation of an apoptotic programme. A basic knowledge on CDC25 inhibitors is relevant for discovering potent bioactive molecules, to be used as anticancer agents against the highly aggressive melanoma.

APP Maturation and Intracellular Localization Are Controlled by a Specific Inhibitor of 37/67 kDa Laminin-1 Receptor in Neuronal Cells.

Amyloid precursor protein (APP) is processed along both the nonamyloidogenic pathway preventing amyloid beta peptide (Aß) production and the amyloidogenic pathway, generating Aß, whose accumulation characterizes Alzheimer's disease. Items of evidence report that the intracellular trafficking plays a key role in the generation of Aß and that the 37/67 kDa LR (laminin receptor), acting as a receptor for Aß, may mediate Aß-pathogenicity. Moreover, findings indicating interaction between the receptor and the key enzymes involved in the amyloidogenic pathway suggest a strong link between 37/67 kDa LR and APP processing. We show herein that the specific 37/67 kDa LR inhibitor, NSC48478, is able to reversibly affect the maturation of APP in a pH-dependent manner, resulting in the partial accumulation of the immature APP isoforms (unglycosylated/acetylated forms) in the endoplasmic reticulum (ER) and in transferrin-positive recycling endosomes, indicating alteration of the APP intracellular trafficking. These effects reveal NSC48478 inhibitor as a novel small molecule to be tested in disease conditions, mediated by the 37/67 kDa LR and accompanied by inactivation of ERK1/2 (extracellular signal-regulated kinases) signalling and activation of Akt (serine/threonine protein kinase) with consequent inhibition of GSK3ß.

CDC25 Inhibition in Acute Myeloid Leukemia-A Study of Patient Heterogeneity and the Effects of Different Inhibitors.

Cell division cycle 25 (CDC25) protein phosphatases regulate cell cycle progression through the activation of cyclin-dependent kinases (CDKs), but they are also involved in chromatin modulation and transcriptional regulation. CDC25 inhibition is regarded as a possible therapeutic strategy for the treatment of human malignancies, including acute myeloid leukemia (AML). We investigated the in vitro effects of CDC25 inhibitors on primary human AML cells derived from 79 unselected patients in suspension cultures. Both the previously well-characterized CDC25 inhibitor NSC95397, as well as five other inhibitors (BN82002 and the novel small molecular compounds ALX1, ALX2, ALX3, and ALX4), only exhibited antiproliferative effects for a subset of patients when tested alone. These antiproliferative effects showed associations with differences in genetic abnormalities and/or AML cell differentiation. However, the responders to CDC25 inhibition could be identified by analysis of global gene expression profiles. The differentially expressed genes were associated with the cytoskeleton, microtubules, and cell signaling. The constitutive release of 28 soluble mediators showed a wide variation among patients and this variation was maintained in the presence of CDC25 inhibition. Finally, NSC95397 had no or only minimal effects on AML cell viability. In conclusion, CDC25 inhibition has antiproliferative effects on primary human AML cells for a subset of patients, and these patients can be identified by gene expression profiling.

LT175 is a novel PPARα/γ ligand with potent insulin-sensitizing effects and reduced adipogenic properties.

Peroxisome proliferator-activated receptors (PPARs) are ligand-dependent transcription factors regulating lipid and glucose metabolism. Ongoing drug discovery programs aim to develop dual PPARα/γ agonists devoid of the side effects of the marketed antidiabetic agents thiazolidinediones and the dual agonists glitazars. Recently, we described a new dual PPARα/γ ligand, LT175, with a partial agonist profile against PPARγ and interacting with a newly identified region of the PPARγ-ligand binding domain (1). Here we show that LT175 differentially activated PPARγ target genes involved in fatty acid esterification and storage in 3T3-L1-derived adipocytes. This resulted in a less severe lipid accumulation compared with that triggered by rosiglitazone, suggesting that LT175 may have a lower adipogenic activity. Consistent with this hypothesis, in vivo administration of LT175 to mice fed a high-fat diet decreased body weight, adipocyte size, and white adipose tissue mass, as assessed by magnetic resonance imaging. Furthermore, LT175 significantly reduced plasma glucose, insulin, non-esterified fatty acids, triglycerides, and cholesterol and increased circulating adiponectin and fibroblast growth factor 21 levels. Oral glucose and insulin tolerance tests showed that the compound improves glucose homeostasis and insulin sensitivity. Moreover, we demonstrate that the peculiar interaction of LT175 with PPARγ affected the recruitment of the coregulators cyclic-AMP response element-binding protein-binding protein and nuclear corepressor 1 (NCoR1), fundamentals for the PPARγ-mediated adipogenic program. In conclusion, our results describe a new PPAR ligand, modulating lipid and glucose metabolism with reduced adipogenic activity, that may be used as a model for a series of novel molecules with an improved pharmacological profile for the treatment of dyslipidemia and type 2 diabetes.

Therapeutic targeting the cell division cycle 25 (CDC25) phosphatases in human acute myeloid leukemia--the possibility to target several kinases through inhibition of the various CDC25 isoforms.

The cell division cycle 25 (CDC25) phosphatases include CDC25A, CDC25B and CDC25C. These three molecules are important regulators of several steps in the cell cycle, including the activation of various cyclin-dependent kinases (CDKs). CDC25s seem to have a role in the development of several human malignancies, including acute myeloid leukemia (AML); and CDC25 inhibition is therefore considered as a possible anticancer strategy. Firstly, upregulation of CDC25A can enhance cell proliferation and the expression seems to be controlled through PI3K-Akt-mTOR signaling, a pathway possibly mediating chemoresistance in human AML. Loss of CDC25A is also important for the cell cycle arrest caused by differentiation induction of malignant hematopoietic cells. Secondly, high CDC25B expression is associated with resistance against the antiproliferative effect of PI3K-Akt-mTOR inhibitors in primary human AML cells, and inhibition of this isoform seems to reduce AML cell line proliferation through effects on NFκB and p300. Finally, CDC25C seems important for the phenotype of AML cells at least for a subset of patients. Many of the identified CDC25 inhibitors show cross-reactivity among the three CDC25 isoforms. Thus, by using such cross-reactive inhibitors it may become possible to inhibit several molecular events in the regulation of cell cycle progression and even cytoplasmic signaling, including activation of several CDKs, through the use of a single drug. Such combined strategies will probably be an advantage in human cancer treatment.

Advancing drug discovery with deep attention neural networks.

In the dynamic field of drug discovery, deep attention neural networks are revolutionizing our approach to complex data. This review explores the attention mechanism and its extended architectures, including graph attention networks (GATs), transformers, bidirectional encoder representations from transformers (BERT), generative pre-trained transformers (GPTs) and bidirectional and auto-regressive transformers (BART). Delving into their core principles and multifaceted applications, we uncover their pivotal roles in catalyzing de novo drug design, predicting intricate molecular properties and deciphering elusive drug-target interactions. Despite challenges, these attention-based architectures hold unparalleled promise to drive transformative breakthroughs and accelerate progress in pharmaceutical research.

Navigating the frontier of drug-like chemical space with cutting-edge generative AI models.

Deep generative models (GMs) have transformed the exploration of drug-like chemical space (CS) by generating novel molecules through complex, nontransparent processes, bypassing direct structural similarity. This review examines five key architectures for CS exploration: recurrent neural networks (RNNs), variational autoencoders (VAEs), generative adversarial networks (GANs), normalizing flows (NF), and Transformers. It discusses molecular representation choices, training strategies for focused CS exploration, evaluation criteria for CS coverage, and related challenges. Future directions include refining models, exploring new notations, improving benchmarks, and enhancing interpretability to better understand biologically relevant molecular properties.

Unleashing the power of generative AI in drug discovery.

Artificial intelligence (AI) is revolutionizing drug discovery by enhancing precision, reducing timelines and costs, and enabling AI-driven computer-aided drug design. This review focuses on recent advancements in deep generative models (DGMs) for de novo drug design, exploring diverse algorithms and their profound impact. It critically analyses the challenges that are intricately interwoven into these technologies, proposing strategies to unlock their full potential. It features case studies of both successes and failures in advancing drugs to clinical trials with AI assistance. Last, it outlines a forward-looking plan for optimizing DGMs in de novo drug design, thereby fostering faster and more cost-effective drug development.

Identification of selective 5-LOX and FLAP inhibitors as novel anti-inflammatory agents by ligand-based virtual screening.

Inflammation is a multifaceted biological process in which the conversion of arachidonic acid to eicosanoids, including prostaglandins and leukotrienes (LTs), plays a crucial role. 5-Lipoxygenase (5-LOX) is a key enzyme in cellular LT biosynthesis, and it is supported by the accessory protein 5-lipoxygenase-activating protein (FLAP). Pharmacological interventions to modulate LTs aim at either decreasing their biosynthesis or at mitigating their biological effects. Therefore, inhibiting 5-LOX or FLAP represents a useful strategy to reduce inflammation. Herein we present the identification and pharmacological evaluation of novel inhibitors targeting 5-LOX or FLAP. By means of a ligand-based virtual screening approach, we selected 38 compounds for in vitro assays. Among them, ALR-38 exhibits direct 5-LOX inhibition, while ALR-6 and ALR-27 showed potential as FLAP inhibitors. These latter not only reduced LT production but also promoted the generation of specialized pro-resolving mediators in specific human macrophage phenotypes. Interestingly, the identified compounds turned out to be selective for their respective targets, as none of them displayed activity towards microsomal prostaglandin E2 synthase-1 and soluble epoxide hydrolase, which are other proteins involved in eicosanoid biosynthesis. Thus, these compounds are endowed with potential therapeutic utility in mitigating inflammatory responses and might offer a venue for tackling inflammation-based disorders.

Enhancing De Novo Drug Design across Multiple Therapeutic Targets with CVAE Generative Models.

Drug discovery is a costly and time-consuming process, necessitating innovative strategies to enhance efficiency across different stages, from initial hit identification to final market approval. Recent advancement in deep learning (DL), particularly in de novo drug design, show promise. Generative models, a subclass of DL algorithms, have significantly accelerated the de novo drug design process by exploring vast areas of chemical space. Here, we introduce a Conditional Variational Autoencoder (CVAE) generative model tailored for de novo molecular design tasks, utilizing both SMILES and SELFIES as molecular representations. Our computational framework successfully generates molecules with specific property profiles validated though metrics such as uniqueness, validity, novelty, quantitative estimate of drug-likeness (QED), and synthetic accessibility (SA). We evaluated our model's efficacy in generating novel molecules capable of binding to three therapeutic molecular targets: CDK2, PPARγ, and DPP-IV. Comparing with state-of-the-art frameworks demonstrated our model's ability to achieve higher structural diversity while maintaining the molecular properties ranges observed in the training set molecules. This proposed model stands as a valuable resource for advancing de novo molecular design capabilities.

Cladosporols and PPARγ: Same Gun, Same Bullet, More Targets.

Several natural compounds have been found to act as PPARγ agonists, thus regulating numerous biological processes, including the metabolism of carbohydrates and lipids, cell proliferation and differentiation, angiogenesis, and inflammation. Recently, Cladosporols, secondary metabolites purified from the fungus Cladosporium tenuissimum, have been demonstrated to display an efficient ability to control cell proliferation in human colorectal and prostate cancer cells through a PPARγ-mediated modulation of gene expression. In addition, Cladosporols exhibited a strong anti-adipogenetic activity in 3T3-L1 murine preadipocytes, preventing their in vitro differentiation into mature adipocytes. These data interestingly point out that the interaction between Cladosporols and PPARγ, in the milieu of different cells or tissues, might generate a wide range of beneficial effects for the entire organism affected by diabetes, obesity, inflammation, and cancer. This review explores the molecular mechanisms by which the Cladosporol/PPARγ complex may simultaneously interfere with a dysregulated lipid metabolism and cancer promotion and progression, highlighting the potential therapeutic benefits of Cladosporols for human health.

A chemical modification of a peroxisome proliferator-activated receptor pan agonist produced a shift to a new dual alpha/gamma partial agonist endowed with mitochondrial pyruvate carrier inhibition and antidiabetic properties.

New analogs of the PPAR pan agonist AL29-26 encompassed ligand (S)-7 showing potent activation of PPARα and -γ subtypes as a partial agonist. In vitro experiments and docking studies in the presence of PPAR antagonists were performed to help interpretation of biological data and investigate the main interactions at the binding sites. Further in vitro experiments showed that (S)-7 induced anti-steatotic effects and enhancement of the glucose uptake. This latter effect could be partially ascribed to a significant inhibition of the mitochondrial pyruvate carrier demonstrating that (S)-7 also acted through insulin-independent mechanisms. In vivo experiments showed that this compound reduced blood glucose and lipid levels in a diabetic mice model displaying no toxicity on bone, kidney, and liver. To our knowledge, this is the first example of dual PPARα/γ partial agonist showing these combined effects representing, therefore, the potential lead of new drugs for treatment of dyslipidemic type 2 diabetes.

New avenues in artificial-intelligence-assisted drug discovery.

Over the past decade, the amount of biomedical data available has grown at unprecedented rates. Increased automation technology and larger data volumes have encouraged the use of machine learning (ML) or artificial intelligence (AI) techniques for mining such data and extracting useful patterns. Because the identification of chemical entities with desired biological activity is a crucial task in drug discovery, AI technologies have the potential to accelerate this process and support decision making. In addition, the advent of deep learning (DL) has shown great promise in addressing diverse problems in drug discovery, such as de novo molecular design. Herein, we will appraise the current state-of-the-art in AI-assisted drug discovery, discussing the recent applications covering generative models for chemical structure generation, scoring functions to improve binding affinity and pose prediction, and molecular dynamics to assist in the parametrization, featurization and generalization tasks. Finally, we will discuss current hurdles and the strategies to overcome them, as well as potential future directions.

Novel Reversible Inhibitors of Xanthine Oxidase Targeting the Active Site of the Enzyme.

Xanthine oxidase (XO) is a flavoprotein catalysing the oxidation of hypoxanthine to xanthine and then to uric acid, while simultaneously producing reactive oxygen species. Altered functions of XO may lead to severe pathological diseases, including gout-causing hyperuricemia and oxidative damage of tissues. These findings prompted research studies aimed at targeting the activity of this crucial enzyme. During the course of a virtual screening study aimed at the discovery of novel inhibitors targeting another oxidoreductase, superoxide dismutase, we identified four compounds with non-purine-like structures, namely ALS-1, -8, -15 and -28, that were capable of causing direct inhibition of XO. The kinetic studies of their inhibition mechanism allowed a definition of these compounds as competitive inhibitors of XO. The most potent molecule was ALS-28 (Ki 2.7 ± 1.5 µM), followed by ALS-8 (Ki 4.5 ± 1.5 µM) and by the less potent ALS-15 (Ki 23 ± 9 µM) and ALS-1 (Ki 41 ± 14 µM). Docking studies shed light on the molecular basis of the inhibitory activity of ALS-28, which hinders the enzyme cavity channel for substrate entry consistently with the competitive mechanism observed in kinetic studies. Moreover, the structural features emerging from the docked poses of ALS-8, -15 and -1 may explain the lower inhibition power with respect to ALS-28. All these structurally unrelated compounds represent valuable candidates for further elaboration into promising lead compounds.