Current Medicinal Chemistry - Volume 29, Issue 14, 2022

Chronic obstructive pulmonary disease (COPD) is an increasing cause of global morbidity and mortality, with poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations, with different phenotypes being identified even among patients with comparable degrees of airflow limitation. Considering the burden of COPD in terms of social and economic costs, in recent years growing attention has been given to the need for more personalized approaches and patienttailored rehabilitation programs. In this regard, the systematic analysis of metabolites in biological matrices, namely metabolomics, may become an essential tool in phenotyping diseases. Through the identification and quantification of the small molecules produced during biological processes, metabolomic profiling of biological samples has thus been proposed as an opportunity to identify novel biomarkers of disease outcome and treatment response. Exhaled breath condensate (EBC) and plasma/serum are fluid pools, which can be easily extracted and analyzed. In this review, we discuss the potential clinical applications of the metabolomic profiling of EBC and plasma/serum in COPD.

Epigenetic regulations play a crucial role in the expression of various genes that are important in the normal cell function. Any alteration in these epigenetic mechanisms can lead to the modification of histone and DNA, resulting in the silencing or enhanced expression of some genes causing various diseases. Acetylation, methylation, ribosylation, or phosphorylation of histone proteins modifies its interaction with the DNA, consequently changing the ratio of heterochromatin and euchromatin. Terminal lysine residues of histone proteins serve as potential targets of such epigenetic modifications. The current review focuses on the histone modifications, and their contributing factors; the role of these modifications on metabolism leads to cancer, and methylation of histone in cancer affects the DNA repair mechanisms.

Several neurotransmitters and neuropeptides were reported to join in or cooperate with different cells of the immune system, bone marrow, and peripheral cells. Numerous data support that neuroactive molecules might control immune system activity and hemopoiesis operating on lymphoid organs and the primary hematopoietic unit, the hematopoietic niche. Furthermore, many compounds seem to be able to take part in the leukemogenesis and lymphomagenesis process and in the onset of multiple myeloma. In this review, we will assess the possibility that neurotransmitters and neuropeptides may have a role in the onset of haematological neoplasms, may affect the response to treatment, or may represent a useful starting point for a new therapeutic approach. More in vivo investigations are needed to evaluate neuropeptide’s role in haematological malignancies and their possible utilization as an antitumor therapeutic target. Comprehending the effect of the pharmacological administration of neuropeptide modulators on hematologic malignancies opens up new possibilities in curing clonal hematologic diseases to achieve more satisfactory outcomes.

Background: CDK2 participates in the control of eukaryotic cell-cycle progression. Due to the great interest in CDK2 for drug development and the relative easiness in crystallizing this enzyme, we have over 400 structural studies focused on this protein target. This structural data is the basis for the development of computational models to estimate CDK2-ligand binding affinity. Objective: This work focuses on the recent developments in the application of supervised machine learning modeling to develop scoring functions to predict the binding affinity of CDK2. Method: We employed the structures available at the protein data bank and the ligand information accessed from the BindingDB, Binding MOAD, and PDBbind to evaluate the predictive performance of machine learning techniques combined with physical modeling used to calculate binding affinity. We compared this hybrid methodology with classical scoring functions available in docking programs. Results: Our comparative analysis of previously published models indicated that a model created using a combination of a mass-spring system and cross-validated Elastic Net to predict the binding affinity of CDK2-inhibitor complexes outperformed classical scoring functions available in AutoDock4 and AutoDock Vina. Conclusion: All studies reviewed here suggest that targeted machine learning models are superior to classical scoring functions to calculate binding affinities. Specifically for CDK2, we see that the combination of physical modeling with supervised machine learning techniques exhibits improved predictive performance to calculate the protein-ligand binding affinity. These results find theoretical support in the application of the concept of scoring function space.

Background: The fusion and rearrangement of the ALK gene of anaplastic lymphoma kinase is an important cause of a variety of cancers, including non-small cell lung cancer (NSCLC) and anaplastic large cell lymphoma (ALCL). Since crizotinib first came out, many ALK inhibitors have come out one after another, but the fatal flaw in each generation of ALK inhibitors is the body's resistance to drugs. Therefore, how to solve the problem of drug resistance has become an important bottleneck in the application and development of ALK inhibitors. This article briefly introduces the drug resistance of ALK inhibitors and the modified forms of ALK inhibitors, which provide a theoretical basis for solving the drug resistance of ALK inhibitors and the development of a new generation of ALK kinase inhibitors. Methods: We use relevant databases to query relevant literature, and then screen and select based on the relevance and cutting edge of the content. We then summarize and analyze appropriate articles, integrate and classify relevant studies, and finally write articles based on topics. Results: This article starts with the problem of ALK resistance, first introduces the composition of ALK kinase, and then introduces the problem of resistance of ALK kinase inhibitors. Later, the structural modification to overcome ALK resistance was introduced, and finally, the method to overcome ALK resistance was introduced. Conclusion: This article summarizes the resistance pathways of ALK kinase inhibitors, and integrates the efforts made to overcome the structural modification of ALK resistance problems, and hopes to provide some inspiration for the development of the next generation of ALK kinase inhibitors.

Given the crucial association of hydrogen peroxide with a wide range of human diseases, this compound has currently earned the reputation of being a popular biomolecular target. Although various analytical methods have attracted our attention, fluorescent probes have been used as prominent tools to determine H2O2 to reflect the physiological and pathological conditions of biological systems. The sensitive responsive part of these probes is the boronate ester and boronic acid groups, which are important reporters for H2O2 recognition. In this review, we summarize boronate ester/boronic acid group-based fluorescent probes for H2O2 reported from 2012 to 2020, and we have generally classified the fluorophores into six categories to exhaustively elaborate the design strategy and comprehensive systematic performance. We hope that this review will inspire the exploration of new fluorescent probes based on boronate ester/boronic acid groups for the detection of H2O2 and other relevant analytes.

The evolution in research and clinical settings of targeted therapies has been inspired by the progress of cancer chemotherapy to use small molecules and monoclonal antibodies for targeting specific disease-associated genes and proteins for noninfectious chronic diseases. In addition to conventional protein inhibition and activation strategies as drug discovery modalities, new methods of targeted protein degradation and regulation using molecular glues have become an attractive approach for drug discovery. Mechanistically, molecular glues trigger interactions between the proteins that originally did not interact by forming ternary complexes as protein-protein interaction (PPI) modulators. New molecular glues and their mechanisms of action have been actively investigated in the past decades. An immunomodulatory imide drug, thalidomide, and its derivatives have been used in the clinic and are a class of molecular glue that induces degradation of several neo-substrates. In this review, we summarize the development of molecular glues and share our opinions on the identification of novel molecular glues in an attempt to promote the concept and inspire further investigations.

Background: Parasitic diseases caused by protozoa, such as Chagas disease, leishmaniasis, malaria, African trypanosomiasis, amoebiasis, trichomoniasis, and giardiasis, are considered serious public health problems in developing countries. Drug resistance among parasites justifies the search for new therapeutic drugs, and the identification of new targets becomes a valuable approach. In this scenario, the glycolysis pathway, which converts glucose into pyruvate, plays an important role in the protozoa energy supply, and it is therefore considered a promising target. In this pathway, triose phosphate isomerase (TIM) plays an essential role in efficient energy production. Furthermore, protozoa TIM shows structural differences with human enzyme counterparts, suggesting the possibility of obtaining selective inhibitors. Therefore, TIM is considered a valid approach to develop new antiprotozoal agents, inhibiting the glycolysis in the parasite. Objective: In this review, we discuss the drug design strategies, structure-activity relationship, and binding modes of outstanding TIM inhibitors against Trypanosoma cruzi, Trypanosoma brucei, Plasmodium falciparum, Giardia lamblia, Leishmania mexicana, Trichomonas vaginalis, and Entamoeba histolytica. Results: TIM inhibitors have mainly shown aromatic systems and symmetrical structure, where the size and type of heteroatom are important for enzyme inhibition. This inhibition is mainly based on the interaction with i) the interfacial region of TIM inducing changes on the quaternary and tertiary structure or ii) with the TIM catalytic region, the main pathways that disable the catalytic activity of the enzyme. Conclusion: Benzothiazole, benzoxazole, benzimidazole, and sulfhydryl derivatives stand out as TIM inhibitors. In silico and in vitro studies have demonstrated that the inhibitors bind mainly at the TIM dimer interface. In this review, the development of new TIM inhibitors as antiprotozoal drugs is demonstrated as an important pharmaceutical strategy that may lead to new therapies for these ancient parasitic diseases.

Background: COVID-19 is still causing long-term health consequences, mass deaths, and collapsing healthcare systems around the world. There are no efficient drugs for its treatment. However, previous studies revealed that SARS-CoV-2 and SARS-CoV have 96% and 86.5% similarities in cysteine proteases (3CL^pro) and papain-like protease (PL^pro) sequences, respectively. This resemblance could be important in the search for drug candidates with antiviral effects against SARS-CoV-2. Objective: This paper is a compilation of natural products that inhibit SARS-CoV 3CL^pro and PL^pro and, concomitantly, reduce inflammation and/or modulate the immune system as a perspective strategy for COVID-19 drug discovery. It also presents in silico studies performed on these selected natural products using SARS-CoV-2 3CL^pro and PL^pro as targets to propose a list of hit compounds. Methods: The plant metabolites were selected in the literature based on their biological activities on SARS-CoV proteins, inflammatory mediators, and immune response. The consensus docking analysis was performed using four different packages. Results: Seventy-nine compounds reported in the literature with inhibitory effects on SARS-CoV proteins were reported as anti-inflammatory agents. Fourteen of them showed immunomodulatory effects in previous studies. Five and six of these compounds showed significant in silico consensus as drug candidates that can inhibit PL^pro and 3CL^pro, respectively. Our findings corroborated recent results reported on anti-SARS-CoV-2 in the literature. Conclusion: This study revealed that amentoflavone, rubranoside B, savinin, psoralidin, hirsutenone, and papyriflavonol A are good drug candidates for the search of antibiotics against COVID-19.