What place does molecular topology have in today’s drug discovery?

Targeting bacterial growth in biofilm conditions: rational design of novel inhibitors to mitigate clinical and food contamination using QSAR

Antimicrobial resistance (AMR) is a pressing global issue exacerbated by the abuse of antibiotics and the formation of bacterial biofilms, which cause up to 80% of human bacterial infections. This study presents a computational strategy to address AMR by developing three novel quantitative structure-activity relationship (QSAR) models based on molecular topology to identify potential anti-biofilm and antibacterial agents. The models aim to determine the chemo-topological pattern of Gram (+) antibacterial, Gram (-) antibacterial, and biofilm formation inhibition activity. The models were applied to the virtual screening of a commercial chemical database, resulting in the selection of 58 compounds. Subsequent in vitro assays showed that three of these compounds exhibited the most promising antibacterial activity, with potential applications in enhancing food and medical device safety.

The molecular structure, biological roles, and inhibition of plant pathogenic fungal chitin deacetylases

Chitin/polysaccharide deacetylases belong to the carbohydrate esterases family 4 (CE4 enzymes). They play a crucial role in modifying the physiochemical characteristics of structural polysaccharides and are also involved in a wide range of biological processes such as fungal autolysis, spore formation, cell wall formation and integrity, and germling adhesion. These enzymes are mostly common in fungi, marine bacteria, and a limited number of insects. They facilitate the deacetylation of chitin which is a structural biopolymer that is abundantly found in fungal cell walls and spores and also in the cuticle and peritrophic matrices of insects. The deacetylases exhibit specificity towards a substrate containing a sequence of four GlcNAc units, with one of these units being subjected to deacetylation. Chitin deacetylation results in the formation of chitosan, which is a poor substrate for host plant chitinases, therefore it can suppress the host immune response triggered by fungal pathogens and enhance pathogen virulence and colonization. This review discusses plant pathogenic fungal chitin/polysaccharide deacetylases including their structure, substrate specificity, biological roles and some recently discovered chitin deacetylase inhibitors that can help to mitigate plant fungal diseases. This review provides fundamental knowledge that will undoubtedly lead to the rational design of novel inhibitors that target pathogenic fungal chitin deacetylases, which will also aid in the management of plant diseases, thereby safeguarding global food security.

5,6-Dihydrotetrazolo[1,5-c]quinazolines: Toxicity prediction, synthesis, antimicrobial activity, molecular docking, and perspectives

Antimicrobial resistance is a never-ending challenge, which should be considered seriously, especially when using unprescribed "over-the-counter" drugs. The synthesis and investigation of novel biologically active substances is among the directions to overcome this problem. Hence, 18 novel 5,6-dihydrotetrazolo[1,5-c]quinazolines were synthesized, their identity, purity, and structure were elucidated by elemental analysis, IR, LC-MS, ¹ Н, and ¹³ C NMR spectra. According to the computational estimation, 15 substances were found to be of toxicity Class V, two of Class IV, and only one of Class II. The in vitro serial dilution method of antimicrobial screening against Escherichia coli, Staphylococcus aureus, Klebsiella aerogenes, Pseudomonas aeruginosa, and Candida albicans determined b3, c1, c6, and c10 as the "lead-compounds" for further modifications to increase the level of activity. Substance b3 demonstrated antibacterial activity that can be related to the calculated high affinity toward all studied proteins: 50S ribosomal protein L19 (PDB ID: 6WQN), sterol 14-alpha demethylase (PDB ID: 5TZ1), and ras-related protein Rab-9A (PDB ID: 1WMS). The structure-activity and structure-target affinity relationships are discussed. The targets for further investigations and the anatomical therapeutic chemical codes of drug similarity are predicted.

Curvilinear regression analysis of benzenoid hydrocarbons and computation of some reduced reverse degree based topological indices for hyaluronic acid-paclitaxel conjugates

Graph theoretical molecular descriptors alias topological indices are a convenient means for expressing in numerical form the chemical structure encoded in a molecular graph. The structure descriptors derived from molecular graphs are widely used in quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies. The reason for introducing new indices is to obtain predictions of target properties of considered molecules that are better than the predictions obtained using already known indices. In this paper, we apply the reduced reverse degree based indices introduced in 2021 by Vignesh et al. In the QSPR analysis, we first compute the reduced reverse degree based indices for a family of benzenoid hydrocarbon molecules and then we obtain the correlation with the Physico-chemical properties of the considered molecules. We show that all the properties taken into consideration for the benzenoid hydrocarbons can be very effectively predicted by the reduced reverse degree based indices. Also, we have compared the predictive capability of reduced reverse degree based topological descriptors against 16 existing degree based indices. Further, we compute the defined reduced reverse degree based topological indices for Hyaluronic Acid-Paclitaxel Conjugates [Formula: see text], [Formula: see text].

Combined Application of Tacrolimus with Cyproconazole, Hymexazol and Novel {2-(3-R-1H-1,2,4-triazol-5-yl)phenyl}amines as Antifungals: In Vitro Growth Inhibition and In Silico Molecular Docking Analysis to Fungal Chitin Deacetylase

Agents with antifungal activity play a vital role as therapeutics in health care, as do fungicides in agriculture. Effectiveness, toxicological profile, and eco-friendliness are among the properties used to select suitable substances. Furthermore, a steady supply of new agents with different modes of action is required to counter the well-known potential of human and phyto-pathogenic fungi to develop resistance against established antifungals. Here, we use an in vitro growth assay to investigate the activity of the calcineurin inhibitor tacrolimus in combination with the commercial fungicides cyproconazole and hymexazol, as well as with two earlier reported novel {2-(3-R-1H-1,2,4-triazol-5-yl)phenyl}amines, against the fungi Aspergillus niger, Colletotrichum higginsianum, Fusarium oxysporum and the oomycete Phytophthora infestans, which are notoriously harmful in agriculture. When tacrolimus was added in a concentration range from 0.25 to 25 mg/L to the tested antifungals (at a fixed concentration of 25 or 50 mg/L), the inhibitory activities were distinctly enhanced. Molecular docking calculations revealed triazole derivative 5, (2-(3-adamantan-1-yl)-1H-1,2,4-triazol-5-yl)-4-chloroaniline), as a potent inhibitor of chitin deacetylases (CDA) of Aspergillus nidulans and A. niger (AnCDA and AngCDA, respectively), which was stronger than the previously reported polyoxorin D, J075-4187, and chitotriose. The results are discussed in the context of potential synergism and molecular mode of action.

QSAR Studies, Molecular Docking, Molecular Dynamics, Synthesis, and Biological Evaluation of Novel Quinolinone-Based Thiosemicarbazones against Mycobacterium tuberculosis

In this study, a series of novel quinolinone-based thiosemicarbazones were designed in silico and their activities tested in vitro against Mycobacterium tuberculosis (M. tuberculosis). Quantitative structure-activity relationship (QSAR) studies were performed using quinolinone and thiosemicarbazide as pharmacophoric nuclei; the best model showed statistical parameters of R² = 0.83; F = 47.96; s = 0.31, and was validated by several different methods. The van der Waals volume, electron density, and electronegativity model results suggested a pivotal role in antituberculosis (anti-TB) activity. Subsequently, from this model a new series of quinolinone-thiosemicarbazone 11a-e was designed and docked against two tuberculosis protein targets: enoyl-acyl carrier protein reductase (InhA) and decaprenylphosphoryl-β-D-ribose-2'-oxidase (DprE1). Molecular dynamics simulation over 200 ns showed a binding energy of -71.3 to -12.7 Kcal/mol, suggesting likely inhibition. In vitro antimycobacterial activity of quinolinone-thiosemicarbazone for 11a-e was evaluated against M. bovis, M. tuberculosis H37Rv, and six different strains of drug-resistant M. tuberculosis. All compounds exhibited good to excellent activity against all the families of M. tuberculosis. Several of the here synthesized compounds were more effective than the standard drugs (isoniazid, oxafloxacin), 11d and 11e being the most active products. The results suggest that these compounds may contribute as lead compounds in the research of new potential antimycobacterial agents.

Rational Design of Chitin Deacetylase Inhibitors for Sustainable Agricultural Use Based on Molecular Topology

Fungicide resistance is a major concern in modern agriculture; therefore, there is a pressing demand to develop new, greener chemicals. Chitin is a major component of the fungal cell wall and a well-known elicitor of plant immunity. To overcome chitin recognition, fungal pathogens developed different strategies, with chitin deacetylase (CDA) activity being the most conserved. This enzyme is responsible for hydrolyzing the N-acetamido group in N-acetylglucosamine units of chitin to convert it to chitosan, a compound that can no longer be recognized by the plant. In previous works, we observed that treatments with CDA inhibitors, such as carboxylic acids, reduced the symptoms of cucurbit powdery mildew and induced rapid activation of chitin-triggered immunity, indicating that CDA could be an interesting target for fungicide development. In this work, we developed an in silico strategy based on QSAR (quantitative structure-activity relationship) and molecular topology (MT) to discover new, specific, and potent CAD inhibitors. Starting with the chemical structures of few carboxylic acids, with and without disease control activity, three predictive equations based on the MT paradigm were developed to identify a group of potential molecules. Their fungicidal activity was experimentally tested, and their specificity as CDA inhibitors was studied for the three best candidates by molecular docking simulations. To our knowledge, this is the first time that MT has been used for the identification of potential CDA inhibitors to be used against resistant powdery mildew strains. In this sense, we consider of special interest the discovery of molecules capable of stimulating the immune system of plants by triggering a defensive response against fungal species that are highly resistant to fungicides such as powdery mildew.

COVID-19 and the Importance of Being Prepared: A Multidisciplinary Strategy for the Discovery of Antivirals to Combat Pandemics

During an emergency, such as a pandemic in which time and resources are extremely scarce, it is important to find effective and rapid solutions when searching for possible treatments. One possibility in this regard is the repurposing of available “on the market” drugs. This is a proof of the concept study showing the potential of a collaboration between two research groups, engaged in computer-aided drug design and control of viral infections, for the development of early strategies to combat future pandemics. We describe a QSAR (quantitative structure activity relationship) based repurposing study on molecular topology and molecular docking for identifying inhibitors of the main protease (Mpro) of SARS-CoV-2, the causative agent of COVID-19. The aim of this computational strategy was to create an agile, rapid, and efficient way to enable the selection of molecules capable of inhibiting SARS-CoV-2 protease. Molecules selected through in silico method were tested in vitro using human coronavirus 229E as a surrogate for SARS-CoV-2. Three strategies were used to screen the antiviral activity of these molecules against human coronavirus 229E in cell cultures, e.g., pre-treatment, co-treatment, and post-treatment. We found >99% of virus inhibition during pre-treatment and co-treatment and 90−99% inhibition when the molecules were applied post-treatment (after infection with the virus). From all tested compounds, Molport-046-067-769 and Molport-046-568-802 are here reported for the first time as potential anti-SARS-CoV-2 compounds.

How Molecular Topology Can Help in Amyotrophic Lateral Sclerosis (ALS) Drug Development: A Revolutionary Paradigm for a Merciless Disease

Even if amyotrophic lateral sclerosis is still considered an orphan disease to date, its prevalence among the population is growing fast. Despite the efforts made by researchers and pharmaceutical companies, the cryptic information related to the biological and physiological onset mechanisms, as well as the complexity in identifying specific pharmacological targets, make it almost impossible to find effective treatments. Furthermore, because of complex ethical and economic aspects, it is usually hard to find all the necessary resources when searching for drugs for new orphan diseases. In this context, computational methods, based either on receptors or ligands, share the capability to improve the success rate when searching and selecting potential candidates for further experimentation and, consequently, reduce the number of resources and time taken when delivering a new drug to the market. In the present work, a computational strategy based on Molecular Topology, a mathematical paradigm capable of relating the chemical structure of a molecule to a specific biological or pharmacological property by means of numbers, is presented. The result was the creation of a reliable and accessible tool to help during the early in silico stages in the identification and repositioning of potential hits for ALS treatment, which can also apply to other orphan diseases. Considering that further computational and experimental results will be required for the final identification of viable hits, three linear discriminant equations combined with molecular docking simulations on specific proteins involved in ALS are reported, along with virtual screening of the Drugbank database as a practical example. In this particular case, as reported, a clinical trial has been already started for one of the drugs proposed in the present study.

Recurrent neural network (RNN) model accelerates the development of antibacterial metronidazole derivatives

Metronidazole is a specific drug against trichomonas and anaerobic bacteria, and is widely used in the clinic. However, extensive clinical application is often accompanied by extensive side effects, so it is still of great significance to develop metronidazole derivatives with a new skeleton. Compared with other traditional receptor-based drug design methods, the computational model based on a neural network has higher accuracy and reliability. In this work, a Recurrent Neural Network (RNN) model is applied to the discovery of metronidazole drugs with a new skeleton. Firstly, the generation model based on a Gated Recurrent Unit (GRU) is trained to generate an effective Simplified Molecular-Input Line-Entry System (SMILES) string library with high precision. Then, transfer learning is introduced to fine-tune the GRU model, and many molecules with structures similar to known active drugs are generated. After cluster analysis of the structures of the new compounds, 20 small molecular compounds with metronidazole structures of all different categories were selected, of which 19 may not belong to any published patents or applications. Through prediction and personal experience, the difficulty of synthesizing these 20 new structures was analyzed, and compound 0001 was chosen as our synthetic target, and a series of structures (8a–l) similar to compound 0001 were synthesized. Finally, the inhibitory activities of these compounds against bacteria E. coli, P. aeruginosa, B. subtilis and S. aureus were determined. The results showed that compound 8a–l had obvious inhibitory activity against these four bacteria, which proved the accuracy of our compound generation model.

Generating antibacterial metronidazole derivatives using a recurrent neural network model.

Chitin Deacetylase, a Novel Target for the Design of Agricultural Fungicides

Fungicide resistance is a serious problem for agriculture. This is particularly apparent in the case of powdery mildew fungi. Therefore, there is an urgent need to develop new agrochemicals. Chitin is a well-known elicitor of plant immunity, and fungal pathogens have evolved strategies to overcome its detection. Among these strategies, chitin deacetylase (CDA) is responsible for modifying immunogenic chitooligomers and hydrolysing the acetamido group in the N-acetylglucosamine units to avoid recognition. In this work, we tested the hypothesis that CDA can be an appropriate target for antifungals using the cucurbit powdery mildew pathogen Podosphaera xanthii. According to our hypothesis, RNAi silencing of PxCDA resulted in a dramatic reduction in fungal growth that was linked to a rapid elicitation of chitin-triggered immunity. Similar results were obtained with treatments with carboxylic acids such as EDTA, a well-known CDA inhibitor. The disease-suppression activity of EDTA was not associated with its chelating activity since other chelating agents did not suppress disease. The binding of EDTA to CDA was confirmed by molecular docking studies. Furthermore, EDTA also suppressed green and grey mould-causing pathogens applied to oranges and strawberries, respectively. Our results conclusively show that CDA is a promising target for control of phytopathogenic fungi and that EDTA could be a starting point for fungicide design.

Targeting the JAK/STAT Pathway: A Combined Ligand- and Target-Based Approach

Janus kinases (JAKs) are a family of proinflammatory enzymes able to mediate the immune responses and the inflammatory cascade by modulating multiple cytokine expressions as well as various growth factors. In the present study, the inhibition of the JAK-signal transducer and activator of transcription (STAT) signaling pathway is explored as a potential strategy for treating autoimmune and inflammatory disorders. A computationally driven approach aimed at identifying novel JAK inhibitors based on molecular topology, docking, and molecular dynamics simulations was carried out. For the best candidates selected, the inhibitory activity against JAK2 was evaluated in vitro. Two hit compounds with a novel chemical scaffold, 4 (IC₅₀ = 0.81 μM) and 7 (IC₅₀ = 0.64 μM), showed promising results when compared with the reference drug Tofacitinib (IC₅₀ = 0.031 μM).

Difluorocarbene-Mediated Cascade Cyclization: The Multifunctional Role of Ruppert-Prakash Reagent

A difluorocarbene-mediated cascade cyclization reaction for rapid access to gem-difluorinated 3-coumaranone derivatives was developed. The difluorocarbene acts as a bipolar CF₂ building block, which enables a homologation cyclization process via sequentially reacting with the phenolate and the ester group on the same substrate. The potential application of this synthetic approach is demonstrated by a late-stage modification of diethylstilbestrol. Mechanistic studies revealed the multiple crucial roles played by the Ruppert-Prakash reagent.