Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information.

In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty of this work is a deep model Predictor that can establish the relationship between chemical structures and their corresponding [Formula: see text] values. We thoroughly study the effect of different molecular descriptors such as ECFP4, ECFP6, SMILES and RDKFingerprint. Also, we demonstrated the importance of attention mechanisms to capture long-range dependencies in molecular sequences. Due to the importance of stereochemical information for the binding mechanism, this information was employed both in the prediction and generation processes. To identify the most promising hits, we apply the self-adaptive multi-objective optimization strategy. Moreover, to ensure the existence of stereochemical information, we consider all the possible enumerated stereoisomers to provide the most appropriate 3D structures. We evaluated this approach against the Ubiquitin-Specific Protease 7 (USP7) by generating putative inhibitors for this target. The predictor with SMILES notations as descriptor plus bidirectional recurrent neural network using attention mechanism has the best performance. Additionally, our methodology identify the regions of the generated molecules that are important for the interaction with the receptor's active site. Also, the obtained results demonstrate that it is possible to discover synthesizable molecules with high biological affinity for the target, containing the indication of their optimal stereochemical conformation.

New Scaffolds of Proteasome Inhibitors: Boosting Anticancer Potential by Exploiting the Synergy of In Silico and In Vitro Methodologies.

Cancer is a complex multifactorial disease whose pathophysiology involves multiple metabolic pathways, including the ubiquitin-proteasome system, for which several proteasome inhibitors have already been approved for clinical use. However, the resistance to existing therapies and the occurrence of severe adverse effects is still a concern. The purpose of this study was the discovery of novel scaffolds of proteasome inhibitors with anticancer activity, aiming to overcome the limitations of the existing proteasome inhibitors. Thus, a structure-based virtual screening protocol was developed using the structure of the human 20S proteasome, and 246 compounds from virtual databases were selected for in vitro evaluation, namely proteasome inhibition assays and cell viability assays. Compound 4 (JHG58) was shortlisted as the best hit compound based on its potential in terms of proteasome inhibitory activity and its ability to induce cell death (both with IC50 values in the low micromolar range). Molecular docking studies revealed that compound 4 interacts with key residues, namely with the catalytic Thr1, Ala20, Thr21, Lys33, and Asp125 at the chymotrypsin-like catalytic active site. The hit compound is a good candidate for additional optimization through a hit-to-lead campaign.

Decoding the secrets: how conformational and structural regulators inhibit the human 20S proteasome.

Acquired resistance to drugs that modulate specific protein functions, such as the human proteasome, presents a significant challenge in targeted therapies. This underscores the importance of devising new methodologies to predict drug binding and potential resistance due to specific protein mutations. In this work, we conducted an extensive computational analysis to ascertain the effects of selected mutations (Ala49Thr, Ala50Val, and Cys52Phe) within the active site of the human proteasome. Specifically, we sought to understand how these mutations might disrupt protein function either by altering protein stability or by impeding interactions with a clinical administered drug. Leveraging molecular dynamics simulations and molecular docking calculations, we assessed the effect of these mutations on protein stability and ligand affinity. Notably, our results indicate that the Cys52Phe mutation critically impacts protein-ligand binding, providing valuable insights into potential proteasome inhibitor resistance.

Bromoditerpenes from the Red Seaweed Sphaerococcus coronopifolius as Potential Cytotoxic Agents and Proteasome Inhibitors and Related Mechanisms of Action.

Seaweeds are a great source of compounds with cytotoxic properties with the potential to be used as anticancer agents. This study evaluated the cytotoxic and proteasome inhibitory activities of 12R-hydroxy-bromosphaerol, 12S-hydroxy-bromosphaerol, and bromosphaerol isolated from Sphaerococcus coronopifolius. The cytotoxicity was evaluated on malignant cell lines (A549, CACO-2, HCT-15, MCF-7, NCI-H226, PC-3, SH-SY5Y, and SK-MEL-28) using the MTT and LDH assays. The ability of compounds to stimulate the production of hydrogen peroxide (H2O2) and to induce mitochondrial dysfunction, the externalization of phosphatidylserine, Caspase-9 activity, and changes in nuclear morphology was also studied on MCF-7 cells. The ability to induce DNA damage was also studied on L929 fibroblasts. The proteasome inhibitory activity was estimated through molecular docking studies. The compounds exhibited IC50 values between 15.35 and 53.34 µM. 12R-hydroxy-bromosphaerol and 12S-hydroxy-bromosphaerol increased the H2O2 levels on MCF-7 cells, and bromosphaerol induced DNA damage on fibroblasts. All compounds promoted a depolarization of mitochondrial membrane potential, Caspase-9 activity, and nuclear condensation and fragmentation. The compounds have been shown to interact with the chymotrypsin-like catalytic site through molecular docking studies; however, only 12S-hydroxy-bromosphaerol evidenced interaction with ALA20 and SER169, key residues of the proteasome catalytic mechanism. Further studies should be outlined to deeply characterize and understand the potential of those bromoditerpenes for anticancer therapeutics.

Highlights in USP7 inhibitors for cancer treatment.

Ubiquitin-specific protease 7 (USP7) is a member of one of the most largely studied families of deubiquitylating enzymes. It plays a key role modulating the levels of multiple proteins, including tumor suppressors, transcription factors, epigenetic modulators, DNA repair proteins, and regulators of the immune response. The abnormal expression of USP7 is found in various malignant tumors and a high expression signature generally indicates poor tumor prognosis. This suggests USP7 as a promising prognostic and druggable target for cancer therapy. Nonetheless, no approved drugs targeting USP7 have already entered clinical trials. Therefore, the development of potent and selective USP7 inhibitors still requires intensive research and development efforts before the pre-clinical benefits translate into the clinic. This mini review systematically summarizes the role of USP7 as a drug target for cancer therapeutics, as well as the scaffolds, activities, and binding modes of some of the most representative small molecule USP7 inhibitors reported in the scientific literature. To wind up, development challenges and potential combination therapies using USP7 inhibitors for less tractable tumors are also disclosed.

Deep generative model for therapeutic targets using transcriptomic disease-associated data-USP7 case study.

The generation of candidate hit molecules with the potential to be used in cancer treatment is a challenging task. In this context, computational methods based on deep learning have been employed to improve in silico drug design methodologies. Nonetheless, the applied strategies have focused solely on the chemical aspect of the generation of compounds, disregarding the likely biological consequences for the organism's dynamics. Herein, we propose a method to implement targeted molecular generation that employs biological information, namely, disease-associated gene expression data, to conduct the process of identifying interesting hits. When applied to the generation of USP7 putative inhibitors, the framework managed to generate promising compounds, with more than 90% of them containing drug-like properties and essential active groups for the interaction with the target. Hence, this work provides a novel and reliable method for generating new promising compounds focused on the biological context of the disease.

Disclosing the antitumour potential of the marine bromoditerpene sphaerococcenol A on distinct cancer cellular models.

Nature has revealed to be a key source of innovative anticancer drugs. This study evaluated the antitumour potential of the marine bromoditerpene sphaerococcenol A on different cancer cellular models. Dose-response analyses (0.1-100 µM; 24 h) were accomplished in eight different tumour cell lines (A549, CACO-2, HCT-15, MCF-7, NCI-H226, PC-3, SH-SY5Y, SK-MEL-28). Deeper studies were conducted on MFC-7 cells, namely, determination of hydrogen peroxide (H2O2) levels and evaluation of apoptosis biomarkers (phosphatidylserine membrane translocation, mitochondrial dysfunction, Caspase-9 activity, and DNA changes). The ability of the compound to induce genotoxicity was verified in L929 fibroblasts. Sphaerococcenol A capacity to impact colorectal-cancer stem cells (CSCs) tumourspheres (HT29, HCT116, SW620) was evaluated by determining tumourspheres viability, number, and area, as well as the proteasome inhibitory activity. Sphaerococcenol A hepatoxicity was studied in AML12 hepatocytes. The compound exhibited cytotoxicity in all malignant cell lines (IC50 ranging from 4.5 to 16.6 µM). MCF-7 cells viability loss was accompanied by H2O2 generation, mitochondrial dysfunction, Caspase-9 activation and DNA nuclear morphology changes. Furthermore, the compound displayed the lowest IC50 on HT29-derived tumourspheres (0.70 µM), followed by HCT116 (1.77 µM) and SW620 (2.74 µM), impacting the HT29 tumoursphere formation by reducing their number and area. Finally, the compound displayed low cytotoxicity on AML12 hepatocytes without genotoxicity. Overall, sphaerococcenol A exhibits broad cytotoxic effects on different tumour cells, increasing H2O2 production and apoptosis. It also affects colorectal CSCs-enriched tumoursphere development. These data highlight the relevance to include sphaerococcenol A in further pharmacological studies aiming cancer treatments.

Revisiting Proteasome Inhibitors: Molecular Underpinnings of Their Development, Mechanisms of Resistance and Strategies to Overcome Anti-Cancer Drug Resistance.

Proteasome inhibitors have shown relevant clinical activity in several hematological malignancies, namely in multiple myeloma and mantle cell lymphoma, improving patient outcomes such as survival and quality of life, when compared with other therapies. However, initial response to the therapy is a challenge as most patients show an innate resistance to proteasome inhibitors, and those that respond to the therapy usually develop late relapses suggesting the development of acquired resistance. The mechanisms of resistance to proteasome inhibition are still controversial and scarce in the literature. In this review, we discuss the development of proteasome inhibitors and the mechanisms of innate and acquired resistance to their activity-a major challenge in preclinical and clinical therapeutics. An improved understanding of these mechanisms is crucial to guiding the design of new and more effective drugs to tackle these devastating diseases. In addition, we provide a comprehensive overview of proteasome inhibitors used in combination with other chemotherapeutic agents, as this is a key strategy to combat resistance.

Chemical Patterns of Proteasome Inhibitors: Lessons Learned from Two Decades of Drug Design.

Drug discovery now faces a new challenge, where the availability of experimental data is no longer the limiting step, and instead, making sense of the data has gained a new level of importance, propelled by the extensive incorporation of cheminformatics and bioinformatics methodologies into the drug discovery and development pipeline. These enable, for example, the inference of structure-activity relationships that can be useful in the discovery of new drug candidates. One of the therapeutic applications that could benefit from this type of data mining is proteasome inhibition, given that multiple compounds have been designed and tested for the last 20 years, and this collection of data is yet to be subjected to such type of assessment. This study presents a retrospective overview of two decades of proteasome inhibitors development (680 compounds), in order to gather what could be learned from them and apply this knowledge to any future drug discovery on this subject. Our analysis focused on how different chemical descriptors coupled with statistical tools can be used to extract interesting patterns of activity. Multiple instances of the structure-activity relationship were observed in this dataset, either for isolated molecular descriptors (e.g., molecular refractivity and topological polar surface area) as well as scaffold similarity or chemical space overlap. Building a decision tree allowed the identification of two meaningful decision rules that describe the chemical parameters associated with high activity. Additionally, a characterization of the prevalence of key functional groups gives insight into global patterns followed in drug discovery projects, and highlights some systematically underexplored parts of the chemical space. The various chemical patterns identified provided useful insight that can be applied in future drug discovery projects, and give an overview of what has been done so far.

Computational Approaches for the Discovery of Human Proteasome Inhibitors: An Overview.

Proteasome emerged as an important target in recent pharmacological research due to its pivotal role in degrading proteins in the cytoplasm and nucleus of eukaryotic cells, regulating a wide variety of cellular pathways, including cell growth and proliferation, apoptosis, DNA repair, transcription, immune response, and signaling processes. The last two decades witnessed intensive efforts to discover 20S proteasome inhibitors with significant chemical diversity and efficacy. To date, the US FDA approved to market three proteasome inhibitors: bortezomib, carfilzomib, and ixazomib. However new, safer and more efficient drugs are still required. Computer-aided drug discovery has long being used in drug discovery campaigns targeting the human proteasome. The aim of this review is to illustrate selected in silico methods like homology modeling, molecular docking, pharmacophore modeling, virtual screening, and combined methods that have been used in proteasome inhibitors discovery. Applications of these methods to proteasome inhibitors discovery will also be presented and discussed to raise improvements in this particular field.

3-Hydroxypyrrolidine and (3,4)-dihydroxypyrrolidine derivatives: inhibition of rat intestinal α-glucosidase.

Thirteen pyrrolidine-based iminosugar derivatives have been synthesized and evaluated for inhibition of α-glucosidase from rat intestine. The compounds studied were the non-hydroxy, mono-hydroxy and dihydroxypyrrolidines. All the compounds were N-benzylated apart from one. Four of the compounds had a carbonyl group in the 2,5-position of the pyrrolidine ring. The most promising iminosugar was the trans-3,4-dihydroxypyrrolidine 5 giving an IC50 of 2.97±0.046 and a KI of 1.18 mM. Kinetic studies showed that the inhibition was of the mixed type, but predominantly competitive for all the compounds tested. Toxicological assay results showed that the compounds have low toxicity. Docking studies showed that all the compounds occupy the same region as the DNJ inhibitor on the enzyme binding site with the most active compounds establishing similar interactions with key residues. Our studies suggest that a rotation of ∼90° of some compounds inside the binding pocket is responsible for the complete loss of inhibitory activity. Despite the fact that activity was found only in the mM range, these compounds have served as simple molecular tools for probing the structural features of the enzyme, so that inhibition can be improved in further studies.

Optimization of O3-acyl kojic acid derivatives as potent and selective human neutrophil elastase inhibitors.

Human neutrophil elastase (HNE) is an attractive target for treating chronic and acute inflammatory lung diseases. An optimization campaign of the kojic acid scaffold to develop new potent HNE inhibitors is reported. O3-Pivaloyl derivatives were shown to be the most potent inhibitors with IC5o values down to 80 nM. These compounds presented excellent selectivity and cytotoxicity profiles with suitable ligand efficiency.