2/3D-QSAR, molecular docking and MD simulation studies of FtsZ protein targeting benzimidazoles derivatives

Discovery of novel cholesteryl ester transfer protein (CETP) inhibitors by a multi-stage virtual screening

Cholesteryl ester transfer protein (CETP) is a promising therapeutic target for cardiovascular diseases. It effectively lowers the low-density lipoprotein cholesterol levels and increases the high-density lipoprotein cholesterol levels in the human plasma. This study identified novel and highly potent CETP inhibitors using virtual screening techniques. Molecular docking and molecular dynamics (MD) simulations revealed the binding patterns of these inhibitors, with the top 50 compounds selected according to their predicted binding affinity. Protein-ligand interaction analyses were performed, leading to the selection of 26 compounds for further evaluation. A CETP inhibition assay confirmed the inhibitory activities of the selected compounds. The results of the MD simulations revealed the structural stability of the protein-ligand complexes, with the binding site remaining significantly unchanged, indicating that the five compounds (AK-968/40709303, AG-690/11820117, AO-081/41378586, AK-968/12713193, and AN-465/14952302) identified have the potential as active CETP inhibitors and are promising leads for drug development.

In-silico molecular modelling studies of some camphor imine based compounds as anti-influenza A (H1N1) pdm09 virus agents

The advent of influenza A (H1N1) drug-resistant strains led to the search quest for more potent inhibitors of the influenza A virus, especially in this devastating COVID-19 pandemic era. Hence, the present research utilized some molecular modelling strategies to unveil new camphor imine-based compounds as anti-influenza A (H1N1) pdm09 agents. The 2D-QSAR results revealed GFA-MLR (R2train = 0.9158, Q2=0.8475) and GFA-ANN (R2train = 0.9264, Q2=0.9238) models for the anti-influenza A (H1N1) pdm09 activity prediction which have passed the QSAR model acceptability thresholds. The results from the 3D-QSAR studies also revealed CoMFA (R2train =0.977, Q2=0.509) and CoMSIA_S (R2train =0.976, Q2=0.527) models for activity predictions. Based on the notable information derived from the 2D-QSAR, 3D-QSAR, and docking analysis, ten (10) new camphor imine-based compounds (22a-22j) were designed using the most active compound 22 as the template. Furthermore, the high predicted activity and binding scores of compound 22j were further justified by the high reactive sites shown in the electrostatic potential maps and other quantum chemical calculations. The MD simulation of 22j in the active site of the influenza hemagglutinin (HA) receptor confirmed the dynamic stability of the complex. Moreover, the appraisals of drug-likeness and ADMET properties of the proposed compounds showed zero violation of Lipinski's criteria with good pharmacokinetic profiles. Hence, the outcomes in this work recommend further in-depth in vivo and in-vitro investigations to validate these theoretical findings.Communicated by Ramaswamy H. Sarma.

Synthesis, anticancer activity, molecular docking and molecular dynamics studies of some pyrazole-chalcone hybrids

Four new hybrid compounds (H1-H4) bearing pyrazole (S1 and S2) and chalcone (P1 and P2) fragments were synthesized and characterized. Compounds were assayed for their ability to inhibit the proliferation of human lung (A549) and colon (Caco-2) cancer cell lines. Besides, toxicity against normal cells was determined using the human umbilical vein endothelial cells (HUVEC). In silico molecular docking, molecular dynamics (MD) simulation and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were carried out to predict the binding modes, protein stability, drug-likeness and toxicity of the reported compounds. The in vitro anticancer activity of the tested compounds revealed dose-dependent cell-specific cytotoxicity. In silico studies revealed that the compounds have a good binding affinity, possess appropriate drug-likeness properties and have low toxicity profiles.Communicated by Ramaswamy H. Sarma.

Design, synthesis, and pharmacological evaluation of indazole carboxamides of N-substituted pyrrole derivatives as soybean lipoxygenase inhibitors

In this paper, we attempted to develop a novel class of compounds against lipoxygenase, a key enzyme in the biosynthesis of leukotrienes implicated in a series of inflammatory diseases. Given the absence of appropriate human 5-lipoxygenase crystallographic data, solved soybean lipoxygenase-1 and -3 structures were used as a template to generate an accurate pharmacophore model which was further used for virtual screening purposes. Eight compounds (1-8) have been derived from the in-house library consisting of N-substituted pyrroles conjugated with 5- or 6-indazole moieties through a carboxamide linker. This study led to the discovery of hit molecule 8 bearing a naphthyl group with the IC50 value of 22 μM according to soybean lipoxygenase in vitro assay. Isosteric replacement of naphthyl ring with quinoline moieties and reduction of carbonyl carboxamide group resulted in compounds 9-12 and 13, respectively. Compound 12 demonstrated the most promising enzyme inhibition. In addition, compounds 8 and 12 were found to reduce the carrageenan-induced paw edema in vivo by 52.6 and 49.8%, respectively. In view of the encouraging outcomes concerning their notable in vitro and in vivo anti-inflammatory activities, compounds 8 and 12 could be further optimized for the discovery of novel 5-lipoxygenase inhibitors in future. A structure-based 3D pharmacophore model was used in the virtual screening of in-house library to discover novel potential 5-lipoxygenase inhibitors.

Mycobacterial FtsZ and inhibitors: a promising target for the anti-tubercular drug development

The emergence of multidrug-resistant tuberculosis (MDR-TB) strains has rendered many anti-TB drugs ineffective. Consequently, there is an urgent need to identify new drug targets against Mycobacterium tuberculosis (Mtb). Filament Forming Temperature Sensitive Gene Z (FtsZ), a member of the cytoskeletal protein family, plays a vital role in cell division by forming a cytokinetic ring at the cell's center and coordinating the division machinery. When FtsZ is depleted, cells are unable to divide and instead elongate into filamentous structures that eventually undergo lysis. Since the inactivation of FtsZ or alterations in its assembly impede the formation of the Z-ring and septum, FtsZ shows promise as a target for the development of anti-mycobacterial drugs. This review not only discusses the potential role of FtsZ as a promising pharmacological target for anti-tuberculosis therapies but also explores the structural and functional aspects of the mycobacterial protein FtsZ in cell division. Additionally, it reviews various inhibitors of Mtb FtsZ. By understanding the importance of FtsZ in cell division, researchers can explore strategies to disrupt its function, impeding the growth and proliferation of Mtb. Furthermore, the investigation of different inhibitors that target Mtb FtsZ expands the potential for developing effective treatments against tuberculosis.

Molecular modelling studies of substituted indole derivatives as novel influenza a virus inhibitors

The emergence of drug-resistant strains motivate researchers to find new innovative anti-IAV candidates with a different mode of action. In this work, molecular modelling strategies, such as 2D-QSAR, 3D-QSAR, molecular docking, molecular dynamics, FMOs, and ADMET were applied to some substituted indoles as IAV inhibitors. The best-developed 2D-QSAR models, MLR (Q2 = 0.7634, R2train = 0.8666) and ANN[4-3-1] (Q2 = 0.8699, R2train = 0.8705) revealed good statistical validation for the inhibitory response predictions. The 3D-QSAR models, CoMFA (Q2 = 0.504, R2train = 0.805) and CoMSIA/SEDHA (Q2 = 0.619, R2train = 0.813) are selected as the best 3D models following the global thresholds. In addition, the contour maps generated from the CoMFA and CoMSIA models illustrate the relationship between the molecular fields and the inhibitory effects of the studied molecules. The results of the studies led to the design of five new molecules (24a-e) with enhanced anti-IAV activities and binding potentials using the most active molecule (24) as the template scaffold. The conformational stability of the best-designed molecules with the NA protein showed hydrophobic and H-bonds with the key residues from the molecular dynamics simulations of 100 ns. Furthermore, the global reactivity indices from the DFT calculations portrayed the relevance of 24c in view of its smaller band gap as also justified by our QSAR and molecular simulation studies.Communicated by Ramaswamy H. Sarma.

Revelation of potential drug targets of luteolin in Plasmodium falciparum through multi-target molecular dynamics simulation studies

In-silico techniques offer a fast, accurate, reliable, and economical approach to studying the molecular interactions between compounds and proteins. In this study, our main aim is to use in-silico techniques as a rational approach for the prediction of the molecular drug targets for luteolin against Plasmodium falciparum. Multi-target molecular docking, 100 nanoseconds (ns) molecular dynamics (MD) simulations, and Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) binding free energy calculations were carried out for luteolin against dihydrofolate reductase thymidylate synthase (PfDHFR-TS), dihydroorotate dehydrogenase (PfDHODH), and falcipain-2. The native ligands of each protein were used as a reference to evaluate the performance of luteolin. Luteolin outperformed the native ligands of all proteins at molecular docking and MD simulations studies. However, in the MM-GBSA calculations, luteolin outperformed the native ligand of only PfDHFR-TS but not PfDHODH and falcipain-2. Among the studied proteins, the in-silico approach predicted PfDHFR-TS as the most favorable drug target for luteolin.Communicated by Ramaswamy H. Sarma.

Data mining and molecular dynamics analysis to detect HIV-1 reverse transcriptase RNase H activity inhibitor

HIV-1 is a deadly virus that affects millions of people worldwide. In this study, we aimed to inhibit viral replication by targeting one of the HIV-1 proteins and identifying a new drug candidate. We used data mining and molecular dynamics methods on HIV-1 genomes. Based on MAUVE analysis, we selected the RNase H activity of the reverse transcriptase (R.T) enzyme as a potential target due to its low mutation rate and high conservation level. We screened about 94,000 small molecule inhibitors by virtual screening. We validated the hit compounds' stability and binding free energy through molecular dynamics simulations and MM/PBSA. Phomoarcherin B, known for its anticancer properties, emerged as the best candidate and showed potential as an HIV-1 reverse transcriptase RNase H activity inhibitor. This study presents a new target and drug candidate for HIV-1 treatment. However, in vitro and in vivo tests are required. Also, the effect of RNase H activity on viral replication and the interaction of Phomoarcherin B with other HIV-1 proteins should be investigated.

Molecular insights into the structural and dynamical changes of calcium channel TRPV6 induced by its interaction with phosphatidylinositol 4,5-bisphosphate

Transient receptor potential vanilloid subfamily member 6 (TRPV6) is an epithelial calcium channel that regulates the initial step of the transcellular calcium transport pathway. TRPV6 is expressed in the kidney, intestine, placenta, and other tissues, and the dysregulation of the channel is implicated in several human cancers. It has been reported that phosphatidylinositol 4,5-bisphosphate (PIP2) activates TRPV6 and its close homologue TRPV5; however, the underlying molecular mechanism is less clear. Recently, a structure of rabbit TRPV5 in complex with dioctanoyl (diC8) PIP2, a soluble form of PIP2, was determined by cryo-electron microscopy. Based on this structure, the structural model of human TRPV6 with PIP2 was set up, and then molecular dynamics simulations were performed for TRPV6 with and without PIP2. Simulation results show that the positively charged residues responsible for TRPV5 binding of diC8 PIP2 are conserved in the interactions between TRPV6 and PIP2. The binding of PIP2 to TRPV6 increases the distance between the diagonally opposed residues D542 in the selectivity filter and that between the diagonally opposed M578 residues in the lower gate of TRPV6. A secondary structural analysis reveals that residues M578 in TRPV6 undergo structural and position changes during the binding of PIP2 with TRPV6. In addition, principal component analysis indicates that the binding of PIP2 increases the dynamical motions of both the selectivity filter and the lower gate of TRPV6. These changes induced by PIP2 favor the channel opening. Thus, this study provides a basis for understanding the mechanism underlying the PIP2-induced TRPV6 channel activation.Communicated by Ramaswamy H. Sarma.

Lead optimization, pharmacophore development and scaffold design of protein kinase CK2 inhibitors as potential COVID-19 therapeutics

Therapeutic agents being designed against COVID-19 have targeted either the virus directly or the host cellular machinery. A particularly attractive host target is the ubiquitous and constitutively active serine-threonine kinase, Protein kinase CK2 (CK2). CK2 enhances viral protein synthesis by inhibiting the sequestration of host translational machinery as stress granules and assists in viral egression via association with the N-protein at filopodial protrusions of the infected cell. CK2 inhibitors such as Silmitasertib have been proposed as possible therapeutic candidates in COVID-19 infections. The present study aims to optimize Silmitasertib, develop pharmacophore models and design unique scaffolds to modulate CK2. The lead optimization phase involved the generation of compounds structurally similar to Silmitasertib via bioisostere replacement followed by a multi-stage docking approach to identify drug-like candidates. Molecular dynamics (MD) simulations were performed for two promising candidates (ZINC-43206125 and PC-57664175) to estimate their binding stability and interaction. Top scoring candidates from the lead optimization phase were utilized to build ligand-based pharmacophore models. These models were then merged with structure-based pharmacophores (e-pharmacophores) to build a hybrid hypothesis. This hybrid hypothesis was validated against a decoy set and used to screen a diverse kinase inhibitors library to identify favored chemical features in the retrieved actives. These chemical features include; an anion, an aromatic ring and an H-bond acceptor. Based on the knowledge of these features; de-novo scaffold design was carried out which identified phenindiones, carboxylated steroids, macrocycles and peptides as novel scaffolds with the potential to modulate CK2.Communicated by Ramaswamy H. Sarma.

Molecular Design and In-Silico Analysis of Trisubstituted Benzimidazole Derivatives as Ftsz Inhibitor

Tuberculosis (TB) is the fastest spreading infectious disease and one of the top ten diseases that kill millions of people annually. The rapid spread of a multidrug-resistant strain of Mycobacterium tuberculosis leads to multidrug-resistance tuberculosis (MDR-TB), which is very difficult to treat. Filament temperature-sensitive protein ring-Z (Ftsz) protein could be the best target to inhibit bacterial cytokinesis. This research is conducted to predict the antitubercular activity of trisubstituted benzimidazole derivatives targeting FtsZ protein by an in-silico approach (molecular docking, pharmacokinetic parameter, drug likeliness, toxicity prediction, and biological activity prediction). Amine and aldehyde substitutions are used as primary scaffolds to design 20 trisubstituted benzimidazole derivatives for molecular docking. AutoDock vina v.1.2.0 software was used to predict the binding interaction between ligand and receptor (FtsZ, PDB ID : 1RQ7). The drug-likeliness properties and toxicity of ligands were predicted from SwissADMET and ToxiM web servers, respectively. Compound A15 (2,3,5,6-tetrafluoro-N1-{6-fluoro-5-[4-(1H-imidazole-1-yl) phenoxy]-1H-1,3-benzodiazol-2-yl} benzene-1,4-diamine) showed the best binding energy (ΔG = −10.2 kcal/mol/) along with four hydrogen bond interactions (GLY107, PHE180, ASP 184). Similarly, compounds A19 and A20 have the best binding score of −9.8 kcal/mol, with excellent pharmacokinetic parameters. It is found that the binding energy of all ligands (ΔG = −8.0 to −10.2 kcal/mol) is better than the reference compound Moxifloxacin (ΔG = −7.7 kcal/mol). None of the ligands violate Lipinski’s rule, but all ligands’ toxicity is slightly high (>0.8 score). It is reported that the amine-substituted benzimidazole derivatives have better binding energy than the aldehyde substitution. Therefore, it is concluded that compounds A19 and A20 can be the best candidate as Ftsz protein inhibitors but an in-vitro animal study and toxicity study are necessary to validate these data.

Designing of new tetrahydro-β-carboline-based ABCG2 inhibitors using 3D-QSAR, molecular docking, and DFT tools

Human ATP-binding cassette superfamily G member 2 (ABCG2) protein is a member of the ABC transporter family, which is responsible for multidrug resistance (MDR) in cancerous cells. MDR reduces the effectiveness of chemotherapy in breast cancer, which is one of the leading causes of death in women globally. MDR in cancer cells is one of the immediate signs of progression of resistance; thus, various anticancer drugs can be designed. To reduce MDR, we utilized the tetrahydro-β-carboline (THβC) compound library. We accomplished a three-dimensional quantitative structure-activity relationship (3D-QSAR), scaffold hopping to design a new library of compounds of THβC, and further molecular docking, induced-fit docking (IFD), molecular mechanics energies combined with generalized born and surface area continuum solvation (MM-GBSA), drug-like features, ADMET properties, and density functional theory (DFT) studies were performed. From these studies, the best 3D-QSAR model (r2 = 0.99, q2 = 0.92) was found, and the necessity of electrostatic, steric, and hydrophobic field effects were determined that could modulate bioactivity. Moreover, based on electrostatic, steric, and hydrophobic field notations, new THβC derivatives (3409) were designed. These findings might provide new insight for researchers to perform in vitro and in vivo studies for better antagonists against MDR in treating breast cancer.Communicated by Ramaswamy H. Sarma.

Chemical, biological and in silico assessment of date (P. dactylifera L.) fruits grown in Ha'il region

Background: Dates palm (Phoenix dactylifera L.) fruits are among the most widely used fruits in the Middle East and African nations. Numerous researchers confirmed the presence of phytochemicals in P. dactylifera L. fruit and its by-products with broad-ranging biological activities. Objectives: In the present work, phytochemical and biological assessments of two different cultivars of date fruit (Shishi M1 and Majdool M2 grown in the Ha'il region of Saudi Arabia) have been carried out. Methods: Date fruits were extracted and analyzed by gas chromatography-mass spectrometry (GS-MS),liquid chromatography-mass spectrometry (LC-MS) and Fourier-transform infrared spectroscopy (FT-IR)techniques. The lyophilized methanolic extracts were analyzed for their in-vitro antiproliferative andcytotoxicity against colon cancer (HCT116) cell line. To identify the possible constituents responsible for the bioactivity, in-silico molecular docking and molecular dynamics (MD) simulation studies were carried out. Results: Both cultivars exhibited in-vitro anticancer activity (IC₅₀ = 591.3 μg/mL and 449.9 μg/mL for M1 and M2, respectively) against colon cancer HCT-116 cells. The computational analysis results indicated procyanidin B2 and luteolin-7-O-rutinoside as the active constituents. Conclusion: Based on these results, we conclude that these cultivars could be a valuable source for developing health promoter phytochemicals, leading to the development of the Ha'il region, Saudi Arabia.

Design and evaluation of pyrimidine derivatives as potent inhibitors of ABCG2, a breast cancer resistance protein

The protein ATP-binding cassette subfamily G member 2 (ABCG2) is one of the major factors behind multidrug resistance (MDR) in breast cancer. We performed three-dimensional quantitative structure-activity relationship (3D-QSAR) modelling, docking, and molecular dynamics (MD) simulation to design pyrimidine-based ABCG2 antagonists. The developed QSAR model (r 2 = 0.92, q 2 = 0.82, and good cross-validated r 2 = 0.73) dictate requirement of electrostatic, and hydrophobic fields for modulating bioactivity. Based on this rationale, we designed and screened 1010 new compounds, among them 2 (ND-510 and ND-500) exhibit excellent drug-like features. Comparative molecular docking, MM/GBSA and ADMET profiles were determined to understand the interactive poses, affinity, and drug-likeness of the designed compounds. Furthermore, MD simulations were performed with the ABCG2 receptor, and the results were compared with the two earlier synthesized active compounds. The outcomes of the study will help researchers to develop new antagonists for treatment of MDR breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03231-1.

Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

Background

Influenza virus disease remains one of the most contagious diseases that aided the deaths of many patients, especially in this COVID-19 pandemic era. Recent discoveries have shown that the high prevalence of influenza and SARS-CoV-2 coinfection can rapidly increase the death rate of patients. Hence, it became necessary to search for more potent inhibitors for influenza disease therapy. The present study utilized some computational modeling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions of some 1,3-thiazine derivatives as inhibitors of influenza neuraminidase (NA).

Results

The 2D-QSAR modeling results showed GFA-MLR ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9192, Q2 = 0.8767, R2adj = 0.8991, RMSE = 0.0959, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8943, $$R_{{{\text{pred}}}}^{2}$$ R pred 2  = 0.7745) and GFA-ANN ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9227, Q2 = 0.9212, RMSE = 0.0940, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.8831, $$R_{{{\text{pred}}}}^{2}$$ R pred 2  = 0.7763) models with the computed descriptors as ATS7s, SpMax5_Bhv, nHBint6, and TDB9m for predicting the NA inhibitory activities of compounds which have passed the global criteria of accepting QSAR model. The 3D-QSAR modeling was carried out based on the comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA). The CoMFA_ES ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.9620, Q2 = 0.643) and CoMSIA_SED ($$R_{{\text{train }}}^{2}$$ R train 2  = 0.8770, Q2 = 0.702) models were found to also have good and reliable predicting ability. The compounds were also virtually screened based on their binding scores via molecular docking simulations with the active site of the NA (H1N1) target receptor which also confirms their resilient potency. Four potential lead compounds (4, 7, 14, and 15) with the relatively high inhibitory rate (> 50%) and docking (> − 6.3 kcal/mol) scores were identified as the possible lead candidates for in silico exploration of improved anti-influenza agents.

Conclusion

The drug-likeness and ADMET predictions of the lead compounds revealed non-violation of Lipinski’s rule and good pharmacokinetic profiles as important guidelines for rational drug design. Hence, the outcome of this research set a course for the in silico design and exploration of novel NA inhibitors with improved potency.

Identification of PARP12 Inhibitors By Virtual Screening and Molecular Dynamics Simulations

Poly [adenosine diphosphate (ADP)-ribose] polymerases (PARPs) are members of a family of 17 enzymes that performs several fundamental cellular processes. Aberrant activity (mutation) in PARP12 has been linked to various diseases including inflammation, cardiovascular disease, and cancer. Herein, a large library of compounds (ZINC-FDA database) has been screened virtually to identify potential PARP12 inhibitor(s). The best compounds were selected on the basis of binding affinity scores and poses. Molecular dynamics (MD) simulation and binding free energy calculation (MMGBSA) were carried out to delineate the stability and dynamics of the resulting complexes. To this end, root means deviations, relative fluctuation, atomic gyration, compactness, covariance, residue-residue contact map, and free energy landscapes were studied. These studies have revealed that compounds ZINC03830332, ZINC03830554, and ZINC03831186 are promising agents against mutated PARP12.

In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions

Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR (R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN (R train ​ 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES (R train ​ 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA (R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.

AB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials

Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.

Structure-based virtual screening and biological evaluation of novel inhibitors of mycobacterium Z-ring formation

The major part of commercial prodrugs against Mycobacterium tuberculosis (Mtb) demonstrated a significant inhibitory effect on cell division and inhibition of bacterial growth in vitro. However, further implementation often failed to overcome the compensatory system of interchangeable cascades. This is the most common situation for the compounds, which hit the key enzymes activities involved in all basic stages of the cell cycle. We decided to find more compounds, which could affect a cytoskeleton complex playing important role in sensing the external signals, intracellular transport, and cell division. In general, the bacterial cytoskeleton is crucial for response to the environment and participates in cell-to-cell communication. In turn, filamentous temperature-sensitive Z (FtsZ) protein, a mycobacterial tubulin homolog, is essential for Z-ring formation and further bacteria cell division. We predicted the most preferable binding-sites and conducted a high-throughput virtual screening. Modeling results suggest that some compounds bind in a specific region on the surface Mtb FtsZ, which is absent in human, and other could hit GTPase activity of the FtsZ. Further in vitro studies confirmed that these novel molecules can efficiently bind to these pockets, demonstrating an effect on the polymerization state and kinetics mechanisms. The rescaling of the experiment on the cell line revealed that reported compounds are able to alter the polymerization level of the filamentous and, therefore, prevent mycobacteria reproduction.

Insights into the structural and dynamical changes of spike glycoprotein mutations associated with SARS-CoV-2 host receptor binding

Novel Coronavirus or SARS-CoV-2 has received worldwide attention due to the COVID-19 pandemic, which originated in Wuhan, China leading to thousands of deaths to date. The SARS-CoV-2 Spike glycoprotein protein is one of the main focus of COVID-19 related research as it is a structural protein that facilitates its attachment, entry, and infection to the host cells. We have focused our work on mutations in two of the several functional domains in the virus spike glycoprotein, namely, receptor-binding domain (RBD) and heptad repeat 1 (HR1) domain. These domains are majorly responsible for the stability of spike glycoprotein and play a key role in the host cell attachment and infection. In our study, several mutations like R408I, L455Y, F486L, Q493N, Q498Y, N501T of RBD (319-591), and A930V, D936Y of HR1 (912-984) have been studied to examine its role on the spike glycoprotein native structure. Comparisons of MD simulations in the WT and mutants revealed a significant de-stabilization effect of the mutations on RBD and HR1 domains. We have investigated the impact of mapped mutations on the stability of the spike glycoprotein, before binding to the receptor, which may be consequential to its binding properties to the receptor and other ligands.Communicated by Ramaswamy H. Sarma.

The structural, functional, and dynamic effect of Tau tubulin kinase1 upon a mutation: A neuro-degenerative hotspot

Alzheimer's disease (AD) is a progressive disorder that causes brain cells to degenerate and die. AD is one of the common causes of dementia that leads to a decline in thinking, behavioral and social skills that disrupts a person's ability to function independently. Tau-tubulin kinase1 (TTBK1) is a crucial disease regulating AD protein, which is majorly responsible for the phosphorylation and accumulation of tau protein at specific Serine/Threonine residues found in paired helical filaments, suggesting its role in tauopathy. TTBK1 involvement in many diseases and the restricted expression of TTBK1 to the central nervous system (CNS) makes TTBK1 an attractive therapeutic target for tauopathies. The genetic variations in TTBK1 are primarily involved in the TTBK1 pathogenesis. This study highlighted the destabilizing, damaging and deleterious effect of the mutation R142Q on TTBK1 structure through computational predictions and molecular dynamics simulations. The protein deviation, fluctuations, conformational dynamics, solvent accessibility, hydrogen bonding, and the residue-residue mapping confirmed the mutant effect to cause structural aberrations, suggesting overall destabilization due to the protein mutation. The presence of well-defined free energy minima was observed in TTBK1-wild type, as opposed to that in the R142Q mutant, reflecting structural deterioration. The overall findings from the study reveal that the presence of R142Q mutation on TTBK1 is responsible for the structural instability, leading to disruption of its biological functions. The mutation could be used as future diagnostic markers in treating AD.

Atomic Resolution Homology Models and Molecular Dynamics Simulations of Plasmodium falciparum Tubulins

Microtubules are tubulin polymers present in the eukaryotic cytoskeleton essential for structural stability and cell division that are also roadways for intracellular transport of vesicles and organelles. In the human malaria parasite Plasmodium falciparum, apart from providing structural stability and cell division, microtubules also facilitate important biological activities crucial for parasite survival in hosts, such as egression and motility. Hence, parasite structures and processes involving microtubules are among the most important drug targets for discovering much-needed novel Plasmodium inhibitors. The current study aims to construct reliable and high-quality 3D models of α-, β-, and γ-tubulins using various modeling techniques. We identified a common binding pocket specific to Plasmodium α-, β-, and γ-tubulins. Molecular dynamics simulations confirmed the stability of the Plasmodium tubulin 3D structures. The models generated in the present study may be used for protein-protein and protein-drug interaction investigations targeted toward designing malaria parasite tubulin-specific inhibitors.

Structural stability predictions and molecular dynamics simulations of RBD and HR1 mutations associated with SARS-CoV-2 spike glycoprotein

The COVID-19 pandemic is caused by human transmission and infection of Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2). There is no trusted drug against the virus; hence, efforts are on discovering novel inhibitors for the virus. The entry of a SARS-CoV-2 virus particle into a host cell is initiated by its spike glycoprotein and host Angiotensin-Converting Enzyme 2 (ACE2) receptor interaction. Spike glycoprotein domains, namely, the Receptor Binding Domain (RBD) and Heptad Repeat (HR) domains, are essential for this activity. We have studied the impact of mutations such as A348T, N354D, D364Y, G476S, V483A, S494D in the RBD (319-591), and S939F, S940T, T941A, S943P (912-984) in the HR1 domains of spike glycoprotein. Summarily, we utilized the computational screening algorithms to rank the deleterious, damaging and disease-associated spike glycoprotein mutations. Subsequently, to understand the changes in conformation, flexibility and function of the spike glycoprotein mutants, Molecular Dynamics (MD) simulations were performed. The computational predictions and analysis of the MD trajectories suggest that the RBD and HR1 mutations induce significant phenotypic effects on the pre-binding spike glycoprotein structure, which are presumably consequential to its binding to the receptor and provides lead to design inhibitors against the binding.Communicated by Ramaswamy H. Sarma.

Unravelling high-affinity binding compounds towards transmembrane protease serine 2 enzyme in treating SARS-CoV-2 infection using molecular modelling and docking studies

The coronavirus disease-19 (COVID-19) outbreak that is caused by a highly contagious severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become a zoonotic pandemic, with approximately 24.5 million positive cases and 8.3 lakhs deaths globally. The lack of effective drugs or vaccine provoked the research for drug candidates that can disrupt the spread and progression of the virus. The identification of drug molecules through experimental studies is time-consuming and expensive, so there is a need for developing alternative strategies like in silico approaches which can yield better outcomes in less time. Herein, we selected transmembrane protease serine 2 (TMPRSS2) enzyme, a potential pharmacological target against SARS-CoV-2, involved in the spread and pathogenesis of the virus. Since 3D structure is not available for this protein, the present study aims at homology modelling and validation of TMPRSS2 using Swiss-model server. Validation of the modelled TMPRSS2 using various online tools confirmed model accuracy, topology and stereochemical plausibility. The catalytic triad consisting of Serine-441, Histidine-296 and Aspartic acid-345 was identified as active binding site of TMPRSS2 using existing ligands. Molecular docking studies of various drugs and phytochemicals against the modelled TMPRSS2 were performed using camostat as a standard drug. The results revealed eight potential drug candidates, namely nafamostat, meloxicam, ganodermanontriol, columbin, myricetin, proanthocyanidin A2, jatrorrhizine and baicalein, which were further studied for ADME/T properties. In conclusion, the study unravelled eight high affinity binding compounds, which may serve as potent antagonists against TMPRSS2 to impact COVID-19 drug therapy.

A molecular journey to check the conformational dynamics of tau tubulin kinase 2 mutations associated with Alzheimer's disease

Proteins are one of the most vital components of biological functions. Proteins have evolutionarily conserved structures as the shape and folding pattern predominantly determine their function. Considerable research efforts have been made to study the protein folding mechanism. The misfolding of protein intermediates of large groups form polymers with unwanted aggregates that may initiate various diseases. Amongst the diseases caused by misfolding of proteins, Alzheimer's disease (AD) is one of the most prevalent neuro-disorders which has a worldwide impact on human health. The disease is associated with several vital proteins and single amino acid mutations. Tau tubulin kinase 2 (TTBK2) is one of the kinases which is known to phosphorylate tau and tubulin. The literature strongly supports that the mutations-K50E, D163A, R181E, A184E and K143E are associated with multiple important cellular processes of TTBK2. In this study, to understand the molecular basis of the functional effects of the mutations, we have performed structural modeling for TTBK2 and its mutations, using computational prediction algorithms and Molecular Dynamics (MD) simulations. The MD simulations highlighted the impact of the mutations on the Wild Type (WT) by the conformational dynamics, Free Energy Landscape (FEL) and internal molecular motions, indicating the structural de-stabilization which may lead to the disruption of its biological functions. The destabilizing effect of TTBK2 upon mutations provided valuable information about individuals carrying this mutant which could be used as a diagnostic marker in AD.

Screening Malaria-box compounds to identify potential inhibitors against SARS-CoV-2 Mpro, using molecular docking and dynamics simulation studies

Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) Main protease (M^pro) is one of the vital drug targets amongst all the coronaviruses, as the protein is indispensable for virus replication. The study aimed to identify promising lead molecules against M^pro enzyme through virtual screening of Malaria Venture (MMV) Malaria Box (MB) comprising of 400 experimentally proven compounds. The binding affinities were studied using virtual screening based molecular docking, which revealed five molecules having the highest affinity scores compared to the reference molecules. Utilizing the established 3D structure of M^pro the binding affinity conformations of the docked complexes were studied by Molecular Dynamics (MD) simulations. The MD simulation trajectories were analysed to monitor protein deviation, relative fluctuation, atomic gyration, compactness covariance, residue-residue map and free energy landscapes. Based on the present study outcome, we propose three Malaria_box (MB) compounds, namely, MB_241, MB_250 and MB_266 to be the best lead compounds against M^pro activity. The compounds may be evaluated for their inhibitory activities using experimental techniques.

Molecule Property Analyses of Active Compounds for Mycobacterium tuberculosis

Tuberculosis (TB) continues to claim the lives of around 1.7 million people per year. Most concerning are the reports of multidrug drug resistance. Paradoxically, this global health pandemic is demanding new therapies when resources and interest are waning. However, continued tuberculosis drug discovery is critical to address the global health need and burgeoning multidrug resistance. Many diverse classes of antitubercular compounds have been identified with activity in vitro and in vivo. Our analyses of over 100 active leads are representative of thousands of active compounds generated over the past decade, suggests that they come from few chemical classes or natural product sources. We are therefore repeatedly identifying compounds that are similar to those that preceded them. Our molecule-centered cheminformatics analyses point to the need to dramatically increase the diversity of chemical libraries tested and get outside of the historic Mtb property space if we are to generate novel improved antitubercular leads.

Virtual Screening Approach to Identify High-Affinity Inhibitors of Serum and Glucocorticoid-Regulated Kinase 1 among Bioactive Natural Products: Combined Molecular Docking and Simulation Studies

Serum and glucocorticoid-regulated kinase 1 (SGK1) is a serine/threonine kinase that works under acute transcriptional control by several stimuli, including serum and glucocorticoids. It plays a significant role in the cancer progression and metastasis, as it regulates inflammation, apoptosis, hormone release, neuro-excitability, and cell proliferation. SGK1 has recently been considered as a potential drug target for cancer, diabetes, and neurodegenerative diseases. In the present study, we have performed structure-based virtual high-throughput screening of natural compounds from the ZINC database to find potential inhibitors of SGK1. Initially, hits were selected based on their physicochemical, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and other drug-like properties. Afterwards, PAINS filter, binding affinities estimation, and interaction analysis were performed to find safe and effective hits. We found four compounds bearing appreciable binding affinity and specificity towards the binding pocket of SGK1. The docking results were complemented by all-atom molecular dynamics simulation for 100 ns, followed by MM/PBSA, and principal component analysis to investigate the conformational changes, stability, and interaction mechanism of SGK1 in-complex with the selected compound ZINC00319000. Molecular dynamics simulation results suggested that the binding of ZINC00319000 stabilizes the SGK1 structure, and it leads to fewer conformational changes. In conclusion, the identified compound ZINC00319000 might be further exploited as a scaffold to develop promising inhibitors of SGK1 for the therapeutic management of associated diseases, including cancer.

FtsA-FtsZ interaction in Vibrio cholerae causes conformational change of FtsA resulting in inhibition of ATP hydrolysis and polymerization

Proper interaction between the divisome proteins FtsA and FtsZ is important for the bacterial cell division which is not well characterized till date. In this study, the objective was to understand the mechanism of FtsA-FtsZ interaction using full-length recombinant proteins. We cloned, over-expressed, purified and subsequently characterized FtsA of Vibrio cholerae (VcFtsA). We found that VcFtsA polymerization assembly was dependent on Ca²⁺ ions, which is unique among FtsA proteins reported until now. VcFtsA also showed ATPase activity and its assembly was ATP dependent. Binding parameters of the interaction between the two full-length proteins, VcFtsA, and VcFtsZ determined by fluorescence spectrophotometry yielded a K_d value of around 38 μM. The K_d value of the interaction was 3 μM when VcFtsA was in ATP bound state. We found that VcFtsZ after interacting with VcFtsA causes a change of secondary structure in the later one leading to loss of its ability to hydrolyze ATP, subsequently halting the VcFtsA polymerization. On the other hand, a double-mutant of VcFtsA (VcFtsA-D242E,R300E), that does not bind to VcFtsZ, polymerized in the presence of VcFtsZ. Though FtsA proteins among different organisms show 70-80% homology in their sequences, assembly of VcFtsA showed a difference in its regulatory processes.

Virtual identification of novel peroxisome proliferator-activated receptor (PPAR) α/δ dual antagonist by 3D-QSAR, molecule docking, and molecule dynamics simulation

The therapeutic potential of PPARs antagonists extends beyond diabetes. PPARs antagonists represent a new drug class that holds promise as a broadly applicable therapeutic approach for cancer treatment. Thus, there is a strong need to develop a rational design strategy for creating PPARs antagonists. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) models of PPARα receptor (CoMFA-1, q ² = 0.636, r ² = 0.953; CoMSIA-1, q ² = 0.779, r ² = 0.999) and PPARδ receptor (CoMFA-2, q ² = 0.624, r ² = 0.906; CoMSIA-2, q ² = 0.627, r ² = 0.959) were successfully constructed using 35 triazolone ring derivatives. Contour map analysis revealed that the electrostatic and hydrophobic fields played vital roles in the bioactivity of dual antagonists. Molecular docking studies suggested that the hydrogen bonding, electrostatic and hydrophobic interactions all influenced the binding of receptor-ligand complex. Based on the information obtained above, we designed a series of compounds. The docking results were mutually validated with 3D-QSAR results. Three-dimensional-QSAR and absorption, distribution, metabolism, excretion and toxicity (ADMET) predictions indicated that 19 newly designed compounds possessed excellent biological activity and physicochemical properties. In summary, this research could provide theoretical guidance for the structural optimization of novel PPARα and δ dual antagonists. Communicated by Ramaswamy H. Sarma.