Identification of anti-mycobacterial agents against mmpL3: Virtual screening, ADMET analysis and MD simulations

Synthetic account on indoles and their analogues as potential anti-plasmodial agents

Malaria caused by P. falciparum, has been recognized as one of the major infectious diseases causing the death of several patients as per the reports from the World Health Organization. In search of effective therapeutic agents against malaria, several research groups have started working on the design and development of novel heterocycles as anti-malarial agents. Heterocycles have been recognized as the pharmacophoric features for the different types of medicinally important activities. Among all these heterocycles, nitrogen containing aza-heterocycles should not be underestimated owing to their wide therapeutic window. Amongst the aza-heterocycles, indoles and fused indoles such as marinoquinolines, isocryptolepines and their regioisomers, manzamines, neocryptolenines, and indolones have been recognized as anti-malarial agents active against P. falciparum. The present work unleashes the synthetic attempts of anti-malarial indoles and fused indoles through cyclocondensation, Fischer-indole synthesis, etc. along with the brief discussions on structure-activity relationships, in vitro or in vivo studies for the broader interest of these medicinal chemists, working on their design and development as potential anti-malarial agents.

Synthesis, biological evaluation and molecular docking study of pyrimidine linked thiazolidinedione derivatives as potential antimicrobial and antitubercular agents

The design and development of novel antimicrobial agents are highly desired to combat the emergence of medication resistance against microorganisms that cause infections. A series of new pyrimidine-linked thiazolidinedione derivatives (5a-j) were synthesized, characterized, and their antimicrobial properties assessed in the current investigation. Here, novel pyrimidine-linked thiazolidinedione compounds were designed using the molecular hybridization approach. Elemental and spectral techniques were used to determine the structures of the synthesized hybrids. The majority of compounds showed encouraging antibacterial properties. Among the active compounds, 5g, 5i, and 5j showed 1.85, 1.15, and 1.38 times the activity of streptomycin against S. aureus, respectively, with MIC values of 6.4, 10.3, and 8.6 µM. With MIC values of 10.8, 21.9, and 15.4 µM, respectively, the compounds 5g, 5i, and 5j showed 2.14, 1.05, and 1.50 times the activity of linezolid against the methicillin-resistant S. aureus (MRSA) strain. Furthermore, when compared to the reference medications, compounds 5g, 5i, and 5j demonstrated broad-range antimicrobial efficacy against all tested strains of bacteria and fungus. Out of all the compounds that were investigated, compounds 5g, 5i, and 5j showed noteworthy anti-tubercular activity. 5g is the most effective, 1.59 times more effective than reference drug isoniazid. To anticipate the binding manner, the synthesized potent compounds were subjected to molecular docking into the active binding site of MRSA and the mycobacterial membrane protein large 3 (MmpL3) protein. The compounds 5g, 5i, and 5j may eventually serve as lead compounds in the search for antimicrobial and anti-TB therapeutic agents.

Novel Inhibitors to MmpL3 Transporter of Mycobacterium tuberculosis by Structure-Based High-Throughput Virtual Screening and Molecular Dynamics Simulations

Tuberculosis (TB)-causing bacterium Mycobacterium tuberculosis (Mtb) utilizes mycolic acids for building the mycobacterial cell wall, which is critical in providing defense against external factors and resisting antibiotic action. MmpL3 is a secondary resistance nodulation division transporter that facilitates the coupled transport of mycolic acid precursor into the periplasm using the proton motive force, thus making it an attractive drug target for TB infection. In 2019, X-ray crystal structures of MmpL3 from M. smegmatis were solved with a promising inhibitor SQ109, which showed promise against drug-resistant TB in Phase II clinical trials. Still, there is a pressing need to discover more effective MmpL3 inhibitors to counteract rising antibiotic resistance. In this study, structure-based high-throughput virtual screening combined with molecular dynamics (MD) simulations identified potential novel MmpL3 inhibitors. Approximately 17 million compounds from the ZINC15 database were screened against the SQ109 binding site on the MmpL3 protein using drug property filters and glide XP docking scores. From this, the top nine compounds and the MmpL3-SQ109 crystal complex structure each underwent 2 × 200 ns MD simulations to probe the inhibitor binding energetics to MmpL3. Four of the nine compounds exhibited stable binding properties and favorable drug properties, suggesting these four compounds could be potential novel inhibitors of MmpL3 for M. tuberculosis.

Synthesis, biological assessment, and computational investigations of nifedipine and monastrol analogues as anti-leishmanial major and anti-microbial agents

Leishmaniasis includes a range of parasitic diseases caused by numerous types of the protozoan kinetoplastid parasite. Fungal and bacterial pathogens have led to infectious illnesses causing some main public health problem in current years. A series of dihydropyridine and tetrahydropyrimidine derivatives having fluoro, bromo, and nitro substituents at para-phenyl ring on C4 of dihydropyridine and tetrahydropyrimidine rings were synthesized. Then, anti-leishmanial and antimicrobial potencies of compounds were assessed. All compounds were synthesized via Hantzsch and Biginelli reactions. All derivatives were evaluated for their anti-leishmanial and antimicrobial activities. Moreover, docking and molecular dynamics simulation calculations of the compounds in PRT1 binding site were performed to report the results of anti-leishmanial and antimicrobial activities. Compounds 4a and 4b showed the highest anti-amastigote and anti-promastigote activities. Compound 4a revealed the highest antimicrobial activity against E. coli, P. aeruginosa, and C. albicans strains. In addition, compound 4c showed the highest activity against S. aureus. The fluoro, bromo, and nitro substituents in para-position of phenyl group at C4 of dihydropyridine and tetrahydropyrimidine moieties as well as the bulk and length of the chain linking to the ester moieties are essential for anti-leishmanial and anti-microbial activities of these derivatives. Low cytotoxicity was shown by most of derivatives against macrophages. The molecular docking studies were in agreement with in vitro assay. Moreover, hydrogen binds, RMSF, RMSD, and Rg, strongly showed the steady binding of 4a and 4b compounds in PRT1 active site.

In silico screening, ADMET analysis and MD simulations of phytochemicals of Onosma bracteata Wall. as SARS CoV-2 inhibitors

Being attracted with their cardiotonic, antidiabetic, cough relieving activity, treatment of fever, absorbent, anti-asthmatic, etc. activities reported in ancient Ayurvedic literature, phytochemicals of Onosma bracteata wall should be evaluated for their activity against SARS-CoV-2 virus. The main objective of this study is to identify a hit molecule for the inhibition of entry, replication, and protein synthesis of SARS CoV-2 virus into the host. To achieve given objective, computational virtual screening of phytochemicals of Onosma bracteata wall has been performed against three main viral targets: spike, RdRp, and M^pro. Further, the analysis of Lipinski's Ro5 and their estimation of ADMET profiles were performed using computational tools. The MD simulations studies of top hits against each viral target have also been performed for 20 ns to ensure their stability. The analysis of results revealed that Pulmonarioside C (9) and other plant compounds showed better binding affinity towards targets than existing antiviral compounds, making them probable lead compounds against SARS-CoV-2. Structural modifications and studies through in silico analysis provided the founding stone for the establishment of SARS CoV-2 inhibitory potential of phytoconstitutents of Onosma bracteata wall.

Computational design of MmpL3 inhibitors for tuberculosis therapy

Tuberculosis is a chronic communicable disease caused by Mycobacterium tuberculosis (Mtb) and spreads from lungs to lymphatic system. The cell wall of mycobacterium plays a prominent role in maintaining the virulence and pathogenicity and also acts as prime target for drug discovery. Hence, this study has put into emphasis with target MmpLs (Mycobacterial membrane proteins Large) which are significant for the growth and survival of Mycobacterium tuberculosis. MmpLs belongs to the resistance, nodulation and division (RND) protein superfamily. MmpL3 is the only MmpL deemed essential for the replication and viability of mycobacterial cells. For the study, we have selected SQ109 derivatives as Mmpl3 inhibitor, which holds non-covalent property. Structure-based pharmacophore model of MmpL3 target protein with SQ109 as co-crystallized ligand (PDB: 6AJG) was generated to screen the ligand database. Compounds with decent fitness score and pharmacophoric features were compared with standard drug and taken for molecular docking studies. Further prime molecular mechanics-Poisson-Boltzmann surface area (MM-GBSA) and induced fit calculations identified potential molecules for further drug-likeness screening. Overall computational calculations identified ZINC000000016638 and ZINC000000003594 as potential in silico MmpL3 inhibitors. Molecular dynamics simulations integrated with MM-PBSA free energy calculations identified that MmpL3-ZINC000000016638 complex was more stable. Study can be further extended for synthesis and biological evaluation, derivatization of active compound to identify potential and safe lead compounds for effective tuberculosis therapy.

Optimal Modeling of Anti-Breast Cancer Candidate Drugs Based on Graph Model Feature Selection

Breast cancer is one of the most widespread and fatal cancers in women. At present, anticancer drug-inhibiting estrogen receptor α subtype (ERα) can greatly improve the cure rate for breast cancer patients, so the research and development of this kind of drugs are very urgent. In this paper, the problem of how to screen excellent anticancer drugs is abstracted as an optimization problem. Firstly, the graph model is used to extract low-dimensional features with strong distinguishing and describing ability according to various attributes of candidate compounds, and then, kernel functions are used to map these features to high-dimensional space. Then, the quantitative analysis model of ERα biological activity and the classification model based on ADMET properties of the support vector machine are constructed. Finally, sequential least square programming (SLSQP) is utilized to solve the ERα biological activity model. The experimental results show that for anticancer data sets, compared with principal component analysis (PCA), the error rate of the graph model constructed in this paper is reduced by 6.4%, 15%, and 7.8% on mean absolute error (MAE), mean squared error (MSE), and root mean square error (RMSE), respectively. In terms of classification prediction, compared with principal component analysis (PCA), the recall and precision rates of this method are enhanced by 19.5% and 12.41%, respectively. Finally, the optimal biological activity value (IC50_nM) 34.6 and inhibitory biological activity value (pIC50) 7.46 were obtained.

In‐silico Computational Investigations of AntiViral Lignan Derivatives as Potent Inhibitors of SARS CoV‐2

Due to alarming outbreak of pandemic COVID‐19 in recent times, there is a strong need to discover and identify new antiviral agents acting against SARS CoV‐2. Among natural products, lignan derivatives have been found effective against several viral strains including SARS CoV‐2. Total of twenty‐seven reported antiviral lignan derivatives of plant origin have been selected for computational studies to identify the potent inhibitors of SARS CoV‐2. Molecular docking study has been carried out in order to predict and describe molecular interaction between active site of enzyme and lignan derivatives. Out of identified hits, clemastatin B and erythro‐strebluslignanol G demonstrated stronger binding and high affinity with all selected proteins. Molecular dynamics simulation studies of clemastin B and savinin against promising targets of SARS CoV‐2 have revealed their inhibitory potential against SARS CoV‐2. In fine, in‐silico computational studies have provided initial breakthrough in design and discovery of potential SARS CoV‐2 inhibitors.

A holistic molecular modelling approach to design novel indole-2-carboxamide derivatives as potential inhibitors of MmpL3

Tuberculosis is an infectious air-borne disease and one of the leading causes of death globally among all infectious diseases. There is an urgent need to develop antitubercular drugs that would be highly efficient and less toxic than the presently available marketed drugs. Mycobacterium membrane protein large 3 (MmpL3) is an emerging drug target in tuberculosis with various classes of molecules that have been known to inhibit it. In this study, a dataset of indole-2-carboxamides showing antitubercular activity by inhibiting MmpL3 was utilized. Initially, a chimera-based homology model was developed and docking was performed with the filtered dataset to analyse the interactions. Thereafter, molecular dynamics simulations were run with representative molecules to gain a better insight on the binding patterns. To attain a more quantitative correlation, an atom-based 3D QSAR model was developed which complemented the results from the previous models. A library of novel indole-2-carboxamides was then generated using core hopping-based ligand enumeration and upon screening on our workflow model it predicted three molecules as potent antitubercular compounds. This work not only helps to gain new insights on the interactions at the MmpL3 binding site but also provides novel indole-2-carboxamides having the potential to become antitubercular drugs in future.

Systematic virtual screening in search of SARS CoV-2 inhibitors against spike glycoprotein: pharmacophore screening, molecular docking, ADMET analysis and MD simulations

In the absence of efficient anti-viral medications, the coronavirus disease 2019 (COVID-19), stemming from severe acute respiratory syndrome coronavirus-2 (SARS CoV-2), has spawned a worldwide catastrophe and global emergency. Amidst several anti-viral targets of COVID-19, spike glycoprotein has been recognized as an essential target for the viral entry into the host cell. In the search of effective SARS CoV-2 inhibitors acting against spike glycoprotein, the virtual screening of 175,851 ligands from the 2020.1 Asinex BioDesign library has been performed using in silico tools like SiteMap analysis, pharmacophore-based screening, molecular docking using different levels of precision, such as high throughput virtual screening, standard precision and extra precision, followed by absorption, distribution, metabolism, excretion and toxicity analysis, and molecular dynamics (MD) simulation. Following a molecular docking study, seventeen molecules (with a docking score of less than - 6.0) were identified having the substantial interactions with the catalytic amino acid and nucleic acid residues of spike glycoprotein at the binding site. In investigations using MD simulations for 10 ns, the hit molecules (1 and 2) showed adequate compactness and uniqueness, as well as satisfactory stability. These computational research findings have offered a key starting point in the field of design and development of novel SARS CoV-2 entry inhibitors with appropriate drug likeliness.

In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis

Severe acute respiratory syndrome has relapsed recently as novel coronavirus causing a life threat to the entire world in the absence of an effective therapy. To hamper the replication of the deadly SARS CoV-2 inside the host cells, systematic in silico virtual screening of total 267,324 ligands from Asinex EliteSynergy and BioDesign libraries has been performed using AutoDock Vina against RdRp. The molecular modeling studies revealed the identification of twenty-one macrocyclic hits (2-22) with better binding energy than remdesivir (1), marketed SARS CoV-2 inhibitor. Further, the analysis using rules for drug-likeness and their ADMET profile revealed the candidature of these hits due to superior oral bioavailability and druggability. Further, the MD simulation studies of top two hits (2 and 3) performed using GROMACS 2020.1 for 10 ns revealed their stability into the docked complexes. These results provide an important breakthrough in the design of macrocyclic hits as SARS CoV-2 RNA replicase inhibitor.