Two- and three-dimensional QSAR studies on a set of antimycobacterial pyrroles: CoMFA, Topomer CoMFA, and HQSAR

In silico research on new sulfonamide derivatives as BRD4 inhibitors targeting acute myeloid leukemia using various computational techniques including 3D-QSAR, HQSAR, molecular docking, ADME/Tox, and molecular dynamics

Acute myeloid leukemia, a serious condition affecting stem cells, drives uncontrollable myeloblast proliferation, leading to accumulation. Extensive research seeks rapid, effective chemotherapeutics. A potential option is a BRD4 inhibitor, known for suppressing cell proliferation. Sulfonamide derivatives probed essential structural elements for potent BRD4 inhibitors. To achieve this goal, we employed 3D-QSAR molecular modeling techniques, including CoMFA, CoMSIA, and HQSAR models, along with molecular docking and molecular dynamics simulations. The validation of the 2D/3D QSAR models, both internally and externally, underscores their robustness and reliability. The contour plots derived from CoMFA, CoMSIA, and HQSAR analyses played a pivotal role in shaping the design of effective BRD4 inhibitors. Importantly, our findings highlight the advantageous impact of incorporating bulkier substituents on the pyridinone ring and hydrophobic/electrostatic substituents on the methoxy-substituted phenyl ring, enhancing interactions with the BRD4 target. The interaction mode of the new compounds with the BRD4 receptor (PDB ID: 4BJX) was investigated using molecular docking simulations, revealing favorable binding energies, supported by the formation of hydrogen and hydrophobic bonds with key protein residues. Moreover, these novel inhibitors exhibited good oral bioavailability and demonstrated non-toxic properties based on ADMET analysis. Furthermore, the newly designed compounds along with the most active one from series 58, underwent a molecular dynamics simulation to analyze their behavior. The simulation provided additional evidence to support the molecular docking results, confirming the sustained stability of the analyzed molecules over the trajectory. This outcome could serve as a valuable reference for designing and developing novel and effective BRD4 inhibitors.Communicated by Ramaswamy H. Sarma.

Pyrrole: A Decisive Scaffold for the Development of Therapeutic Agents and Structure-Activity Relationship

An overview of pyrroles as distinct scaffolds with therapeutic potential and the significance of pyrrole derivatives for drug development are provided in this article. It lists instances of naturally occurring pyrrole-containing compounds and describes the sources of pyrroles in nature, including plants and microbes. It also explains the many conventional and modern synthetic methods used to produce pyrroles. The key topics are the biological characteristics, pharmacological behavior, and functional alterations displayed by pyrrole derivatives. It also details how pyrroles are used to treat infectious diseases. It describes infectious disorders resistant to standard treatments and discusses the function of compounds containing pyrroles in combating infectious diseases. Furthermore, the review covers the uses of pyrrole derivatives in treating non-infectious diseases and resistance mechanisms in non-infectious illnesses like cancer, diabetes, and Alzheimer's and Parkinson's diseases. The important discoveries and probable avenues for pyrrole research are finally summarized, along with their significance for medicinal chemists and drug development. A reference from the last two decades is included in this review.

Profiling the Structural determinants of pyrrolidine derivative as gelatinases (MMP-2 and MMP-9) inhibitors using in silico approaches

Quantitative structure activity relationship (QSAR) studies on pyrrolidine derivatives have been established using CoMFA, CoMSIA, and Hologram QSAR analysis to estimate the values (pIC₅₀) of gelatinase inhibitors. When the CoMFA cross-validation value, Q², was 0.625, the training set coefficient of determination, R² was 0.981. In CoMSIA, Q² was 0.749 and R² was 0.988. In the HQSAR, Q² was 0.84 and R² was 0.946. Visualization of these models was performed by contour maps showing favorable and unfavorable regions for activity, while visualization of HQSAR model was performed by a colored atomic contribution graph. Based on the results obtained of external validation, the CoMSIA model was statistically more significant and robust and was selected as the best model to predict new, more active inhibitors. To study the modes of interactions of the predicted compounds in the active site of MMP-2 and MMP-9, a simulation of molecular docking was realized. A combined study of MD simulations and calculation of free binding energy, were also carried out to validate the results obtained on the best predicted and most active compound in dataset and the compound NNGH as control compound. The results confirm the molecular docking results and indicate that the predicted ligands were stable in the binding site of MMP-2 and MMP-9.

Structural Insights on Hyp-Gly-Containing Peptides as Antiplatelet Compounds through Topomer CoMFA and CoMSIA Analysis

Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q² value of 0.710, an r² value of 0.826, an r²_pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q² value of 0.461, an r² value of 0.999, and an r²_pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 μmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases.

Molecular engineering and activity improvement of acetylcholinesterase inhibitors: Insights from 3D-QSAR, docking, and molecular dynamics simulation studies

The carbamate molecule rivastigmine was found to possess promising anti-acetylcholinesterase activity, enabling to target and occupy choline binding sites, and as a result, widely used to improve the treatment of Alzheimer's disease (AD). Higher dose of rivastigmine indicates rapid onset but more adverse effects, such as the large fluctuations in plasma concentration level and frequent incidence of gastrointestinal side effect. To solve the dilemma, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR), docking and molecular dynamics (MD) simulation strategy to construct a dismountable nanoplatform of inhibitor engineering, verification and application for improving the inhibitory activity per unit concentration. With the aid of 3D-QSAR method, we constructed a model by using 25 molecules reported, and verified well the rationality of these QSAR models by non-cross validation coefficient (r² = 0.902). Docking and MD results show that rivastigmine, as a control, does target exactly the binding sites of acetylcholinesterase, those already observed experimentally, in turn, confirming the reliability of the present 3D-QSAR results. The method suggests that groups with electron-donating chemical property can improve the inhibitory activity, and screens out two novel inhibitors L-1 and L-2 with more activity from database (about 8000 compounds). Moreover, L-1 and L-2 not only target exactly the same binding sites of acetylcholinesterase as the rivastigmine does, but also hold stronger binding energy, showing a more powerful inhibitory ability. More broadly, this work showcases an approach in the engineering of carbamate inhibitors to enhance their inhibitory activity using electron-donating groups, which simplifies the design process of complex bioactive molecules.

Discovery of MAO-B Inhibitor with Machine Learning, Topomer CoMFA, Molecular Docking and Multi-Spectroscopy Approaches

Alzheimer’s disease (AD) is the most common type of dementia and is a serious disruption to normal life. Monoamine oxidase-B (MAO-B) is an important target for the treatment of AD. In this study, machine learning approaches were applied to investigate the identification model of MAO-B inhibitors. The results showed that the identification model for MAO-B inhibitors with　K-nearest neighbor(KNN) algorithm had a prediction accuracy of 94.1% and 88.0% for the 10-fold cross-validation test and the independent test set, respectively. Secondly, a quantitative activity prediction model for MAO-B was investigated with the Topomer CoMFA model. Two separate cutting mode approaches were used to predict the activity of MAO-B inhibitors. The results showed that the cut model with q² = 0.612 (cross-validated correlation coefficient) and r² = 0.824 (non-cross-validated correlation coefficient) were determined for the training and test sets, respectively. In addition, molecular docking was employed to analyze the interaction between MAO-B and inhibitors. Finally, based on our proposed prediction model, 1-(4-hydroxyphenyl)-3-(2,4,6-trimethoxyphenyl)propan-1-one (LB) was predicted as a potential MAO-B inhibitor and was validated by a multi-spectroscopic approach including fluorescence spectra and ultraviolet spectrophotometry.

Using computers to ESKAPE the antibiotic resistance crisis

Since the discovery of penicillin, the development and use of antibiotics have promoted safe and effective control of bacterial infections. However, the number of antibiotic-resistance cases has been ever increasing over time. Thus, the drug discovery process demands fast, efficient and cost-effective alternative approaches for developing lead candidates with outstanding performance. Computational approaches are appealing techniques to develop lead candidates in an in silico fashion. In this review, we provide an overview of the implementation of current in silico state-of-the-art techniques, including machine learning (ML) and deep learning (DL), in drug discovery. We also discuss the development of quantum computing and its potential benefits for antibiotics research and current bottlenecks that limit computational drug discovery advancement.

Synthesis and In Vitro Antimycobacterial Activity of Novel N-Arylpiperazines Containing an Ethane-1,2-diyl Connecting Chain

Novel 1-(2-{3-/4-[(alkoxycarbonyl)amino]phenyl}-2-hydroxyethyl)-4-(2-fluorophenyl)-piperazin-1-ium chlorides (alkoxy = methoxy to butoxy; 8a-h) have been designed and synthesized through multistep reactions as a part of on-going research programme focused on finding new antimycobacterials. Lipophilic properties of these compounds were estimated by RP-HPLC using methanol/water mobile phases with a various volume fraction of the organic modifier. The log k_w values, which were extrapolated from intercepts of a linear relationship between the logarithm of a retention factor k (log k) and volume fraction of a mobile phase modifier (ϕ_M), varied from 2.113 (compound 8e) to 2.930 (compound 8h) and indicated relatively high lipophilicity of these salts. Electronic properties of the molecules 8a-h were investigated by evaluation of their UV/Vis spectra. In a next phase of the research, the compounds 8a-h were in vitro screened against M. tuberculosis CNCTC My 331/88 (identical with H₃₇R_v and ATCC 2794), M. kansasii CNCTC My 235/80 (identical with ATCC 12478), a M. kansasii 6 509/96 clinical isolate, M. avium CNCTC My 330/80 (identical with ATCC 25291) and M. avium intracellulare ATCC 13950, respectively, as well as against M. kansasii CIT11/06, M. avium subsp. paratuberculosis CIT03 and M. avium hominissuis CIT10/08 clinical isolates using isoniazid, ethambutol, ofloxacin, ciprofloxacin or pyrazinamide as reference drugs. The tested compounds 8a-h were found to be the most promising against M. tuberculosis; a MIC = 8 μM was observed for the most effective 1-(2-{4-[(butoxycarbonyl)amino]phen-ylphenyl}-2-hydroxyethyl)-4-(2-fluorophenyl)piperazin-1-ium chloride (8h). In addition, all of them showed low (insignificant) in vitro toxicity against a human monocytic leukemia THP-1 cell line, as observed LD₅₀ values > 30 μM indicated. The structure-antimycobacterial activity relationships of the analyzed 8a-h series are also discussed.

QSAR-driven design, synthesis and discovery of potent chalcone derivatives with antitubercular activity

New anti-tuberculosis (anti-TB) drugs are urgently needed to battle drug-resistant Mycobacterium tuberculosis strains and to shorten the current 6-12-month treatment regimen. In this work, we have continued the efforts to develop chalcone-based anti-TB compounds by using an in silico design and QSAR-driven approach. Initially, we developed SAR rules and binary QSAR models using literature data for targeted design of new heteroaryl chalcone compounds with anti-TB activity. Using these models, we prioritized 33 compounds for synthesis and biological evaluation. As a result, 10 heteroaryl chalcone compounds (4, 8, 9, 11, 13, 17-20, and 23) were found to exhibit nanomolar activity against replicating mycobacteria, low micromolar activity against nonreplicating bacteria, and nanomolar and micromolar against rifampin (RMP) and isoniazid (INH) monoresistant strains (rRMP and rINH) (<1 μM and <10 μM, respectively). The series also show low activity against commensal bacteria and generally show good selectivity toward M. tuberculosis, with very low cytotoxicity against Vero cells (SI = 11-545). Our results suggest that our designed heteroaryl chalcone compounds, due to their high potency and selectivity, are promising anti-TB agents.

Synthesis, antimycobacterial screening and ligand-based molecular docking studies on novel pyrrole derivatives bearing pyrazoline, isoxazole and phenyl thiourea moieties

We report here the synthesis, antibacterial and antitubercular evaluation of 61 novel pyrrolyl derivatives bearing pyrazoline, isoxazole and phenyl thiourea moieties. Molecular docking was carried out on enoyl ACP reductase from Mycobacterium tuberculsosis using Surflex-Dock, which is one of the key enzymes involved in type II fatty acid biosynthetic pathway of Mycobacterium tuberculosis, an attractive target for designing novel antitubercular agents. Docking analysis of the crystal structure of ENR performed using Surflex-Dock in Sybyl-X 2.0 software indicates the occupation of substituted pyrrolyl derivatives into hydrophobic pocket of InhA enzyme. Compounds 9b and 9d exhibited the highest antitubercular activity almost close to isoniazid (0.4 μg/mL) with a MIC value of 0.8 μg/mL. All other compounds showed the good activity with a MIC value of 6.25-100 μg/mL. The compounds were further tested for mammalian cell toxicity using human lung cancer cell-line (A549) and were nontoxic. Some compounds exhibited inhibition activities against InhA.