Pharmacophore modelling, QSAR study, molecular docking and insilico ADME prediction of 1,2,3-triazole and pyrazolopyridones as DprE1 inhibitor antitubercular agents

Pharmacophore mapping, 3D QSAR, molecular docking, and ADME prediction studies of novel Benzothiazinone derivatives

In the quest to combat tuberculosis, DprE1, a challenging target for novel anti-tubercular agents due to its small size and membrane location, has been a focus of research. DprE1 catalyzes the transformation of DPR into Ketoribose DPX, with Benzothiazinone emerging as a potent pharmacophore for inhibiting DprE1. Clinical trial drugs such as BTZ043, BTZ038, PBTZ169, and TMC-207 have shown promising results as DprE1 inhibitors. This study employed pharmacophore mapping of Pyrazolopyridine, Dinitrobenzamide, and Benzothiazinone derivatives to identify crucial features for eliciting a biological response. Benzothiazinone (Ligand code: 73) emerged as a reference ligand with a fitness score of 3.000. ROC analysis validated the pharmacophore with an excellent score of 0.71. To build a 3D QSAR model, a series of Benzothiazinone congeneric derivatives were explored. The model exhibited strong performance, with a standard deviation of 0.1531, a correlation coefficient for the training set (R2) value of 0.9754, and a correlation coefficient for test set Q2 value of 0.7632, indicating robust predictive capabilities. Contour maps guided the design of novel benzothiazinone derivatives, emphasizing steric, electrostatic, hydrophobic, H-bond acceptor, and H-bond donor groups for structure-activity relationships. Docking studies against PDB ID: 4NCR demonstrated favorable scores, with interactions aligning well with the in-built ligand 26 J. Docking validation via RMSD values supported the reliability of the docking results. This comprehensive approach aids in the design of novel benzothiazinone derivatives with potential anti-tubercular properties, contributing to the development of novel anti-tubercular agents which can be pivotal in the eradication of tuberculosis.

In-silico identification and exploration of small molecule coumarin-1,2,3-triazole hybrids as potential EGFR inhibitors for targeting lung cancer

Globally, lung cancer is a significant public health concern due to its role as the leading cause of cancer-related mortalities. The promising target of EGFR for lung cancer treatment has been identified, providing a potential avenue for more effective therapies. The purpose of the study was to design a library of 1843 coumarin-1,2,3-triazole hybrids and screen them based on a designed pharmacophore to identify potential inhibitors targeting EGFR in lung cancer with minimum or no side effects. Pharmacophore-based screening was carried out and 60 hits were obtained. To gain a better understanding of the binding interactions between the compounds and the targeted receptor, molecular docking was conducted on the 60 screened compounds. In-silico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results indicated that coumarin-1,2,3-triazole hybrids COUM-0849, COUM-0935, COUM-0414, COUM-1335, COUM-0276, and COUM-0484 exhibit dock score of - 10.2, - 10.2, - 10.1, - 10.1, - 10, - 10 while reference molecule - 7.9 kcal/mol for EGFR (PDB ID: 4HJO) respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, we performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of coumarin-1,2,3-triazole hybrids as promising EGFR inhibitors for the management of lung cancer.

In-silico design, pharmacophore-based screening, and molecular docking studies reveal that benzimidazole-1,2,3-triazole hybrids as novel EGFR inhibitors targeting lung cancer

Lung cancer is a complex and heterogeneous disease, which has been associated with various molecular alterations, including the overexpression and mutations of the epidermal growth factor receptor (EGFR). In this study, designed a library of 1843 benzimidazole-1,2,3-triazole hybrids and carried out pharmacophore-based screening to identify potential EGFR inhibitors. The 164 compounds were further evaluated using molecular docking and molecular dynamics simulations to understand the binding interactions between the compounds and the receptor. In-si-lico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results of this study indicate that benzimidazole-1,2,3-triazole hybrids BENZI-0660, BENZI-0125, BENZI-0279, BENZI-0415, BENZI-0437, and BENZI-1110 exhibit dock scores of -9.7, -9.6, -9.6, -9.6, -9.6, -9.6 while referencing molecule -7.9 kcal/mol for EGFR (PDB ID: 4HJO), respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzimidazole-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. This research opens up a new avenue for the discovery and development of potent and selective EGFR inhibitors for the treatment of lung cancer.Communicated by Ramaswamy H. Sarma.

Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study

Mycobacterium tuberculosis is the bacterial strain that causes tuberculosis (TB). However, multidrug-resistant and extensively drug-resistant tuberculosis are significant obstacles to effective treatment. As a result, novel therapies against various strains of M. tuberculosis have been developed. Drug development is a lengthy procedure that includes identifying target protein and isolation, preclinical testing of the drug, and various phases of a clinical trial, etc., can take decades for a molecule to reach the market. Computational approaches such as QSAR, molecular docking techniques, and pharmacophore modeling have aided drug development. In this review article, we have discussed the various techniques in tuberculosis drug discovery by briefly introducing them and their importance. Also, the different databases, methods, approaches, and software used in conducting QSAR, pharmacophore modeling, and molecular docking have been discussed. The other targets targeted by these techniques in tuberculosis drug discovery have also been discussed, with important molecules discovered using these computational approaches. This review article also presents the list of drugs in a clinical trial for tuberculosis found drugs. Finally, we concluded with the challenges and future perspectives of these techniques in drug discovery.

DprE1 Inhibitors: Enduring Aspirations for Future Antituberculosis Drug Discovery

DprE1 is a crucial enzyme involved in the cell wall synthesis of Mycobacterium tuberculosis and a promising target for antituberculosis drug development. However, its unique structural characteristics for ligand binding and association with DprE2 make developing new clinical compounds challenging. This review provides an in-depth analysis of the structural requirements for both covalent and non-covalent inhibitors, their 2D and 3D binding patterns, as well as their biological activity data in vitro and in vivo, including pharmacokinetic information. We also introduce a protein quality score (PQS) and an active-site map of the DprE1 enzyme to help medicinal chemists better understand DprE1 inhibition and develop new and effective anti-TB drugs. Furthermore, we examine the resistance mechanisms associated with DprE1 inhibitors to understand future developments due to resistance emergence. This comprehensive review offers insight into the DprE1 active site, including protein-binding maps, PQS, and graphical representations of known inhibitors, making it a valuable resource for medicinal chemists working on future antitubercular compounds.

In-silico identification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies

Lung cancer is one of the most common and deadly types of cancer worldwide, and the epidermal growth factor receptor (EGFR) has emerged as a promising therapeutic target for the treatment of this disease. In this study, we designed a library of 1840 benzofuran-1,2,3-triazole hybrids and conducted pharmacophore-based screening to identify potential EGFR inhibitors. The 20 identified compounds were further evaluated using molecular docking and molecular dynamics simulations to understand their binding interactions with the EGFR receptor. In-silico ADME and toxicity studies were also performed to assess their drug-likeness and safety profiles. The results of this study showed the benzofuran-1,2,3-triazole hybrids BENZ-0454, BENZ-0143, BENZ-1292, BENZ-0335, BENZ-0332, and BENZ-1070 dock score of - 10.2, - 10, - 9.9, - 9.8, - 9.7, - 9.6, while reference molecule - 7.9 kcal/mol for EGFR (PDB ID: 4HJO) respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of the receptor, indicating their potential as inhibitors. The in-silico ADME and toxicity studies suggested that the compounds had good pharmacokinetic and safety profiles, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzofuran-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. Overall, this study provides a valuable starting point for the development of novel EGFR inhibitors with improved efficacy and safety profiles.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00157-1.

Field and atom-based 3D-QSAR models of chromone (1-benzopyran-4-one) derivatives as MAO inhibitors

Monoamine oxidases (MAOs) are flavo-enzymes that aid in the oxidative deamination of neurotransmitters like dopamine, serotonin, and epinephrine. MAO inhibitors are antidepressants that work by preventing the breakdown of brain neurotransmitters and regulating mood. MAO inhibitors that use the chromone (1-benzopyran-4-one) structure have been found to be quite effective in studies. The current study involves the creation of pharmacophore models, 3-D QSAR, virtual screening, and docking investigations, all of which are evaluated using various criteria. The investigation included 39 ligands that emerged pharmacophore AHRRR_1, as the best pharmacophore model with a survival score of 5.6485. The 3D QSAR investigation revealed a significant model with the values of R2 = 0.9064 and Q2 = 0.8239. Docking study revealed that compound 18 had the highest docking (-10.402 kcal/mol) score in the series and showed interactions with the essential amino acid TYR398 required for MAO inhibitory activity. ZINC compounds were screened using the created pharmacophore model, which was followed up with a virtual screening study. The ZINC compounds with the best XP docking scores are ZINC03113255, ZINC07777127, ZINC05166353 and ZINC09341502 (with docking scores -10.021, -9.486, -8.031 and -7.792 kcal/mol, respectively). ZINC03113255, which showed the best score, has binding interactions with amino acid residues, TYR326, TYR398 and LYS296 of monoamine oxidase B. The ADME analysis demonstrated the compound's drug-like characteristics. The findings of this study may be used in the development of chromone compounds that target the MAO inhibitor.Communicated by Ramaswamy H. Sarma.

3D-QSAR Studies of 1,2,4-Oxadiazole Derivatives as Sortase A Inhibitors

Sortase A (SrtA) is an enzyme that catalyzes the attachment of proteins to the cell wall of Gram-positive bacterial membrane, preventing the spread of pathogenic bacterial strains. Here, one class of oxadiazole compounds was distinguished as an efficient inhibitor of SrtA via the "S. aureus Sortase A" substrate-based virtual screening. The current study on 3D-QSAR was done by utilizing preparation of the structure in the Schrödinger software suite and an assessment of 120 derivatives with the crystal structure of 1,2,4-oxadiazole which was extracted from the PDB data bank. The docking operation of the best compound in terms of pMIC (pMIC = 2.77) was done to determine the drug likeliness and binding form of 1,2,4-oxadiazole derivatives as antibiotics in the active site. Using the kNN-MFA way, seven models of 3D-QSAR were created and amongst them, and one model was selected as the best. The chosen model based on q 2 (pred_r 2) and R 2 values related to the sixth factor of PLS illustrates better and more acceptable external and internal predictions. Values of crossvalidation (pred_r 2), validation (q 2), and F were observed 0.5479, 0.6319, and 179.0, respectively, for a test group including 24 molecules and the training group including 96 molecules. The external reliability outcomes showed that the acceptable and the selective 3D-QSAR model had a high predictive potential (R 2 = 0.9235) which was confirmed by the Y-randomization test. Besides, the model applicability domain was described successfully to validate the estimation of the model.

Rational in silico drug design of HIV-RT inhibitors through G-QSAR and molecular docking study of 4-arylthio and 4-aryloxy-3-iodopyridine-2(1-H)-one derivative

Background

Human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV). Antiretroviral therapy (ART) against HIV infection offers the promise of controlling disease progression and prolonging the survival of HIV-infected patients. Reverse transcriptase (RT) inhibitors remain the cornerstone of the drug regimen to treat AIDS. In this direction, by using group-based QSAR study (G-QSAR), identification of the structural need for the development of lead structure with reverse transcriptase inhibition on 97 reported structures was carried out. Docking analysis was performed further and suggested the structural properties required for binding affinity with the receptor. The molecules in the data set were fragmented into six (R1, R2, R3, R4, R5, and R6) by applying the fragmentation pattern. Three G-QSAR models were selected based on the statistical significance of the model. The molecular docking study was performed to explain the structural properties required for the design of potent HIV-RT inhibitors.

Results

The statistically validated QSAR models reveal the presence of higher hydrophobic groups containing single-bonded –Br atom, 2 aromatic bonded –NH group with less electronegativity, and entropic interaction fields at R2 essential for better anti-HIV activity. The presence of a lipophilic group at R3, oxygen and sulfur connected with two aromatic bonds at R4, and –CH3 group at R5 was fruitful for reverse transcriptase inhibition. Docking studies of the selected inhibitors with the active site of reverse transcriptase enzyme showed hydrogen bond, Van der Waal’s, charge, aromatic, and π–π interactions with residues present at the active site.

Conclusion

The results of the generated models provide significant site-specific insight into the structural requirements for reverse transcriptase inhibition during the design and development of novel anti-HIV compounds. Molecular docking study revealed the binding interaction between the ligand and the receptor which gave insight towards the structure-based design for the discovery of more potent compounds with better activity against HIV infection.