Homology modeling a fast tool for drug discovery: current perspectives

Elucidation of 7,8-dihydroxy flavone in complexing with the oxidative stress-inducing enzymes, its impact on radical quenching and DNA damage: an in silico and in vitro approach

Oxidative stress (OS) has been attributed to the progression of various disorders, including cancer, diabetes, and cardiovascular diseases. Several antioxidant compounds and free radical quenchers have been shown to mitigate oxidative stress. However, large-scale randomized controlled trials of such compounds on chronic disease aversion have yielded paradoxical and disappointing results due to the constrained cognizance of their oxidative mechanisms and therapeutic targets. The current study sought to identify the potential therapeutic targets of 7,8-Dihydroxyflavone (7,8-DHF) by analyzing its interactions with the enzymes implicated in oxidative stress and also to explore its radicle quenching potential and prophylactic impact on the H2O2-induced DNA damage. Through the in silco approach, we investigated the antioxidant potential of 7,8-DHF by evaluating its interactions with the human oxidative stress-inducing enzymes such as myeloperoxidase (MPO), NADPH oxidase (NOX), nitric oxide synthase (NOS), and xanthine oxidase (XO) and a comparative analysis of those interactions with known antioxidants (Ascorbic acid, Melatonin, Tocopherol) used as controls. The best-scoring complex was adopted for the simulation analysis in investigating protein-ligand conformational dynamics. The in vitro radicle quenching potential was evaluated by performing a spectrum of antioxidant assays, and radical quenching was observed in a dose-dependent fashion with IC50 values of < 60 µM/mL. Further, we probed its anti-hemolytic potential and prophylactic impact in avian erythrocytes subjected to H2O2-induced hemolysis and DNA damage by implementing hemolysis and comet assays. The protective effect was more pronounced at higher concentrations of the drug.Communicated by Ramaswamy H. Sarma.

Synthesis and biological activity of imidazole phenazine derivatives as potential inhibitors for NS2B-NS3 dengue protease

A series of new imidazole-phenazine derivatives were synthesized via a two-step process. The condensation of 2,3-diaminophenazine and benzaldehyde derivatives proceeds with intermediate formation of an aniline Schiff base, which undergoes subsequent cyclodehydrogenation in situ. The structures of the synthesized compounds were characterized by 1D and 2D NMR, FTIR and HRMS. A total of thirteen imidazole phenazine derivatives were synthesized and validated for their inhibitory activity as anti-dengue agents by an in vitro DENV2 NS2B-NS3 protease assay using a fluorogenic Boc-Gly-Arg-Arg-AMC substrate. Two para-substituted imidazole phenazines, 3e and 3k, were found to be promising lead molecules for novel NS2B-NS3 protease inhibitors with IC50 of 54.8 μM and 71.9 μM, respectively, compared to quercetin as a control (IC50 104.8 μM). The in silico study was performed using AutoDock Vina to identify the binding energy and conformation of 3e and 3k with the active site of the DENV2 NS2B-NS3 protease Wichapong model. The results indicate better binding properties of 3e and 3k with calculated binding energies of -8.5 and -8.4 kcal mol-1, respectively, compared to the binding energy of quercetin of -7.2 kcal mol-1, which corroborates well with the experimental observations.

Drug Repositioning Using Computer-aided Drug Design (CADD)

Drug repositioning is a method of using authorized drugs for other unusually complex diseases. Compared to new drug development, this method is fast, low in cost, and effective. Through the use of outstanding bioinformatics tools, such as computer-aided drug design (CADD), computer strategies play a vital role in the re-transformation of drugs. The use of CADD's special strategy for target-based drug reuse is the most promising method, and its realization rate is high. In this review article, we have particularly focused on understanding the various technologies of CADD and the use of computer-aided drug design for target-based drug reuse, taking COVID-19 and cancer as examples. Finally, it is concluded that CADD technology is accelerating the development of repurposed drugs due to its many advantages, and there are many facts to prove that the new ligand-targeting strategy is a beneficial method and that it will gain momentum with the development of technology.

Development of Alpha-Synuclein protein model against therapeutic aspects of Parkinson's disease

JOURNAL/ijpha/04.03/01363791-202456010-00007/figure1/v/2024-03-07T095025Z/r/image-tiff Parkinson's disease (PD) is the most common neurodegenerative disease caused by the steady depletion of dopamine in the striatum due to the loss of dopaminergic neurons. Most of the current therapeutics work on rebuilding the striatal dopamine level through oral administration of levodopa which stops the symptoms of PD. But there is a long-term motor complication with these dopamine precursors. Moreover, no preventive treatment is available for PD. Thus, before finding a therapeutic treatment for PD, it is necessary to first understand the basic cause of PD. Moreover, alpha-synuclein oligomerization can be the major factor in PD. From the UniProt database, protein information was extracted, and the model was designed by homology modeling technique and validated by the model validation server. Hence, the designed model has 96.5% most favored region and 0% disallowed region. Therefore, the model is stable based on RC plot parameters.

De novo TRPM3 missense variant associated with neurodevelopmental delay and manifestations of cerebral palsy

We identified a de novo heterozygous transient receptor potential cation channel subfamily M (melastatin) member 3 (TRPM3) missense variant, p.(Asn1126Asp), in a patient with developmental delay and manifestations of cerebral palsy (CP) using phenotype-driven prioritization analysis of whole-genome sequencing data with Exomiser. The variant is localized in the functionally important ion transport domain of the TRPM3 protein and predicted to impact the protein structure. Our report adds TRPM3 to the list of Mendelian disease-associated genes that can be associated with CP and provides further evidence for the pathogenicity of the variant p.(Asn1126Asp).

Advancements in small molecule drug design: A structural perspective

In this review, we outline recent advancements in small molecule drug design from a structural perspective. We compare protein structure prediction methods and explore the role of the ligand binding pocket in structure-based drug design. We examine various structural features used to optimize drug candidates, including functional groups, stereochemistry, and molecular weight. Computational tools such as molecular docking and virtual screening are discussed for predicting and optimizing drug candidate structures. We present examples of drug candidates designed based on their molecular structure and discuss future directions in the field. By effectively integrating structural information with other valuable data sources, we can improve the drug discovery process, leading to the identification of novel therapeutics with improved efficacy, specificity, and safety profiles.

Antibiofilm potential of gallic acid against Klebsiella pneumoniae and Enterobacter hormaechei: in-vitro and in-silico analysis

Biofilm refers to a community of microorganisms that adhere to a substrate and play a crucial role in microbial pathogenesis and developing infections associated with medical devices. Enterobacter hormaechei and Klebsiella pneumoniae are classified as significant nosocomial pathogens within the ESKAPE category and cause diverse infections. In addition to their reputation as prolific biofilm formers, these pathogens are increasingly becoming drug-resistant and pose a substantial threat to the healthcare setting. Due to the inherent resistance of biofilms to conventional therapies, novel strategies are imperative for effectively controlling E. hormaechei and K. pneumoniae biofilms. This study aimed to assess the anti-biofilm activity of gallic acid (GA) against E. hormaechei and K. pneumoniae. The results of biofilm quantification assays demonstrated that GA exhibited significant antibiofilm activity against E. hormaechei and K. pneumoniae at concentrations of 4 mg mL-1, 2 mg mL-1, 1 mg mL-1, and 0.5 mg mL-1. Similarly, GA exhibited a dose-dependent reduction in violacein production, a QS-regulated purple pigment, indicating its ability to suppress violacein production and disrupt QS mechanisms in Chromobacterium violaceum. Additionally, computational tools were utilized to identify the potential target involved in the biofilm formation pathway. The computational analysis further indicated the strong binding affinity of GA to essential biofilm regulators, MrkH and LuxS, suggesting its potential in targeting the c-di-GMP and quorum sensing (QS) pathways to hinder biofilm formation in K. pneumoniae. These compelling findings strongly advocate GA as a promising drug candidate against biofilm-associated infections caused by E. hormaechei and K. pneumoniae.

Network pharmacology based anti-diabetic attributes of bioactive compounds from Ocimum gratissimum L. through computational approach

The present research was framed to determine the key compounds present in the plant Ocimum gratissimum L. targeting protein molecules of Diabetes Mellitus (DM) by employing In-silico approaches. Phytochemicals previously reported to be present in this herb were collated through literature survey and public phytochemical databases, and their probable targets were anticipated using BindingDB (p ≥ 0.7). STRING and KEGG pathway databases were employed for pathway enrichment analysis. Homology modelling was executed to elucidate the structures of therapeutic targets. Further, Phytocompounds from O. gratissimum were subjected for docking with four therapeutic targets of DM by using AutoDock vina through POAP pipeline implementation. 30 compounds were predicted to target 136 protein molecules including aldose reductase, DPP4, alpha-amylase, and alpha-glucosidase. Neuroactive ligand-receptor interaction, MAPK, PI3K-Akt, starch and insulin resistance were predicted to have potentially modulation by phytocompounds. Based on the phytocompound's binding score with the four targets of DM, Rutin scored the lowest binding energy (-11 kcal/mol) with Aldose reductase by forming 17 intermolecular interactions. In conclusion, based on the network and binding score, phytocompounds from O. gratissimum have a synergistic and considerable effect in the management of DM via multi-compound, multi-target, and multi-pathway mechanisms.

Juno and CD9 protein network organization in oolemma of mouse oocyte

Juno and CD9 protein, expressed in oolemma, are known to be essential for sperm-oocyte binding and fusion. Although evidence exists that these two proteins cooperate, their interaction has not yet been demonstrated. Here in, we present Juno and CD9 mutual localization over the surface of mouse metaphase II oocytes captured using the 3D STED super-resolution technique. The precise localization of examined proteins was identified in different compartments of oolemma such as the microvillar membrane, planar membrane between individual microvilli, and the membrane of microvilli-free region. Observed variance in localization of Juno and CD9 was confirmed by analysis of transmission and scanning electron microscopy images, which showed a significant difference in the presence of proteins between selected membrane compartments. Colocalization analysis of super-resolution images based on Pearson's correlation coefficient supported evidence of Juno and CD9 mutual position in the oolemma, which was identified by proximity ligation assay. Importantly, the interaction between Juno and CD9 was detected by co-immunoprecipitation and mass spectrometry in HEK293T/17 transfected cell line. For better understanding of experimental data, mouse Juno and CD9 3D structure were prepared by comparative homology modelling and several protein-protein flexible sidechain dockings were performed using the ClusPro server. The dynamic state of the proteins was studied in real-time at atomic level by molecular dynamics (MD) simulation. Docking and MD simulation predicted Juno-CD9 interactions and stability also suggesting an interactive mechanism. Using the multiscale approach, we detected close proximity of Juno and CD9 within microvillar oolemma however, not in the planar membrane or microvilli-free region. Our findings show yet unidentified Juno and CD9 interaction within the mouse oolemma protein network prior to sperm attachment. These results suggest that a Juno and CD9 interactive network could assist in primary Juno binding to sperm Izumo1 as a prerequisite to subsequent gamete membrane fusion.

Molecular Modeling Unveils the Effective Interaction of B-RAF Inhibitors with Rare B-RAF Insertion Variants

The Food and Drug Administration (FDA) has approved MAPK inhibitors as a treatment for melanoma patients carrying a mutation in codon V600 of the BRAF gene exclusively. However, BRAF mutations outside the V600 codon may occur in a small percentage of melanomas. Although these rare variants may cause B-RAF activation, their predictive response to B-RAF inhibitor treatments is still poorly understood. We exploited an integrated approach for mutation detection, tumor evolution tracking, and assessment of response to treatment in a metastatic melanoma patient carrying the rare p.T599dup B-RAF mutation. He was addressed to Dabrafenib/Trametinib targeted therapy, showing an initial dramatic response. In parallel, in-silico ligand-based homology modeling was set up and performed on this and an additional B-RAF rare variant (p.A598_T599insV) to unveil and justify the success of the B-RAF inhibitory activity of Dabrafenib, showing that it could adeptly bind both these variants in a similar manner to how it binds and inhibits the V600E mutant. These findings open up the possibility of broadening the spectrum of BRAF inhibitor-sensitive mutations beyond mutations at codon V600, suggesting that B-RAF V600 WT melanomas should undergo more specific investigations before ruling out the possibility of targeted therapy.

Squalene hopene cyclases and oxido squalene cyclases: potential targets for regulating cyclisation reactions

Squalene hopene cyclases (SHC) convert squalene, the linear triterpene to fused ring product hopanoid by the cationic cyclization mechanism. The main function of hopanoids, a class of pentacyclic triterpenoids in bacteria involves the maintenance of membrane fluidity and stability. 2, 3-oxido squalene cyclases are functional analogues of SHC in eukaryotes and both these enzymes have fascinated researchers for the high stereo selectivity, complexity, and efficiency they possess. The peculiar property of the enzyme squalene hopene cyclase to accommodate substrates other than its natural substrate can be exploited for the use of these enzymes in an industrial perspective. Here, we present an extensive overview of the enzyme squalene hopene cyclase with emphasis on the cloning and overexpression strategies. An attempt has been made to explore recent research trends around squalene cyclase mediated cyclization reactions of flavour and pharmaceutical significance by using non-natural molecules as substrates.

Molecular modelling and biological evaluation of phyto-molecules as potential activators of gluconolactone oxidase (GULO)

Diabetes, the cause of colossal economic and disease burden, is a key area of research in drug discovery programs. Elevated blood glucose levels in diabetes lead to several adverse consequences due to the formation of advanced glycation end products and free radicals. Vitamin C, a potent antioxidant, protects the body's cells and tissues from oxidative damage and dysfunctions. Glucose is the precursor of Vitamin C synthesis in plants and some mammals. L-gulono lactone oxidase (GULO) is the rate-limiting enzyme in producing Vitamin C. However, it is not synthesized in bats, primates, humans, and guinea pigs because of the pseudogene. Several phytomolecules having antioxidant properties are hypothesized to be promising and selective activators of GULO. Therefore, the present study focused on screening agonists of GULO from phytomolecules as an effective augmentor for Vitamin C synthesis, thereby suppressing the sequela of diabetic events. The 3D structure of GULO was generated by the ab-initio method. Subsequently, molecular docking explored the possible binding patterns of GULO protein with different plant phenolic compounds, followed by supplementation of the potent phytomolecules to diabetic guinea pigs. It is noteworthy that Resveratrol and Hydroxytyrosol showed better binding affinity. The molecular simulation also confirmed that Resveratrol is an activator of the GULO enzyme. Interestingly, it was also established that Vitamin C levels were improved in diabetic guinea pigs supplemented with the phytomolecules and comparatively Resveratrol modulates the concentration of glucose and Vitamin C levels substantially, thereby alleviating hyperglycemia. However, further studies are warranted to study the mechanisms.Communicated by Ramaswamy H. Sarma.

Ligand-based virtual screening, molecular dynamics, and biological evaluation of repurposed drugs as inhibitors of Trypanosoma cruzi proteasome

Chagas disease is a well-known Neglected Tropical Disease, mostly endemic in continental Latin America, but that has spread to North America and Europe. Unfortunately, current treatments against such disease are ineffective and produce known and undesirable side effects. To find novel effective drug candidates to treat Chagas disease, we uniquely explore the Trypanosoma cruzi proteasome as a recent biological target and, also, apply drug repurposing through different computational methodologies. For this, we initially applied protein homology modeling to build a robust model of proteasome β4/β5 subunits, since there is no crystallographic structure of this target. Then, we used it on a drug repurposing via a virtual screening campaign starting with more than 8,000 drugs and including the methodologies: ligand-based similarity, toxicity predictions, and molecular docking. Three drugs were selected concerning their favorable interactions at the protein binding site and subsequently submitted to molecular dynamics simulations, which allowed us to elucidate their behavior and compare such theoretical results with experimental ones, obtained in biological assays also described in this paper.Communicated by Ramaswamy H. Sarma.

Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development

The use of computer-aided drug design (CADD) for the identification of lead compounds in radiotracer development is steadily increasing. Traditional CADD methods, such as structure-based and ligand-based virtual screening and optimization, have been successfully utilized in many drug discovery programs and are highlighted throughout this review. First, we discuss the use of virtual screening for hit identification at the beginning of drug discovery programs. This is followed by an analysis of how the hits derived from virtual screening can be filtered and culled to highly probable candidates to test in in vitro assays. We then illustrate how CADD can be used to optimize the potency of experimentally validated hit compounds from virtual screening for use in positron emission tomography (PET). Finally, we conclude with a survey of the newest techniques in CADD employing machine learning (ML).

CADD, AI and ML in drug discovery: A comprehensive review

Computer-aided drug design (CADD) is an emerging field that has drawn a lot of interest because of its potential to expedite and lower the cost of the drug development process. Drug discovery research is expensive and time-consuming, and it frequently took 10-15 years for a drug to be commercially available. CADD has significantly impacted this area of research. Further, the combination of CADD with Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies to handle enormous amounts of biological data has reduced the time and cost associated with the drug development process. This review will discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process. It will also provide a detailed overview of the different in silico tools used and how these approaches interact.

Molecular modeling, simulation and docking of Rv1250 protein from Mycobacterium tuberculosis

Computational prediction and protein structure modeling have come to the aid of various biological problems in determining the structure of proteins. These technologies have revolutionized the biological world of research, allowing scientists and researchers to gain insights into their biological questions and design experimental research much more efficiently. Pathogenic Mycobacterium spp. is known to stay alive within the macrophages of its host. Mycobacterium tuberculosis is an acid-fast bacterium that is the most common cause of tuberculosis and is considered to be the main cause of resistance of tuberculosis as a leading health issue. The genome of Mycobacterium tuberculosis contains more than 4,000 genes, of which the majority are of unknown function. An attempt has been made to computationally model and dock one of its proteins, Rv1250 (MTV006.22), which is considered as an apparent drug-transporter, integral membrane protein, and member of major facilitator superfamily (MFS). The most widely used techniques, i.e., homology modeling, molecular docking, and molecular dynamics (MD) simulation in the field of structural bioinformatics, have been used in the present work to study the behavior of Rv1250 protein from M. tuberculosis. The structure of unknown TB protein, i.e., Rv1250 was retrived using homology modeling with the help of I-TASSER server. Further, one of the sites responsible for infection was identified and docking was done by using the specific Isoniazid ligand which is an inhibitor of this protein. Finally, the stability of protein model and analysis of stable and static interaction between protein and ligand molecular dynamic simulation was performed at 100 ns The designing of novel Rv1250 enzyme inhibitors is likely achievable with the use of proposed predicted model, which could be helpful in preventing the pathogenesis caused by M. tuberculosis. Finally, the MD simulation was done to evaluate the stability of the ligand for the specific protein.

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma.

The Anti-Candida Activity of Tephrosia apollinea Is More Superiorly Attributed to a Novel Steroidal Compound with Selective Targeting

Tephrosia is widely distributed throughout tropical, subtropical, and arid regions. This genus is known for several biological activities, including its anti-Candida activity, which is mainly attributed to prenylated flavonoids. The biological activities of most Tephrosia species have been studied, except T. apollinea. This study was conducted to investigate the underlying anti-Candida activity of T. apollinea, wildly grown in the United Arab Emirates (UAE). The T. apollinea plant was collected, dried, and the leaves were separated. The leaves were ground and extracted. The dried extract was subjected to successive chromatography to identify unique phytochemicals with a special pharmacological activity. The activity of the compound was validated by homology modeling and molecular docking studies. A novel steroidal compound (ergosta-6, 8(14), 22, 24(28)-tetraen-3-one) was isolated and named TNS. In silico target identification of TNS revealed a high structural similarity with the Candida 14-α-demethylase enzyme substrate. The compound exhibited a significant anti-Candida activity, specifically against the multi-drug-resistant Candida auris at MIC₅₀, 16 times less than the previously reported prenylated flavonoids and 5 times less than the methanol extract of the plant. These findings were supported by homology modeling and molecular docking studies. TNS may represent a new class of Candida 14-α-demethylase inhibitors.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Carvacrol inhibits Streptococcus pyogenes biofilms by suppressing the expression of genes associated with quorum-sensing and reducing cell surface hydrophobicity

Streptococcus pyogenes is a leading cause of chronic and acute infections, including streptococcus pharyngitis. Biofilm formation by S. pyogenes can cause tolerance against antibiotics. Although penicillin remains the first choice of antibiotic for S. pyogenes, alternative approaches have gained interest due to treatment failures and hypersensitive individuals. Carvacrol is a monoterpenoid from herbal plants with selective biocidal activity on S. pyogenes. Therefore, the present study reveals the efficacy of carvacrol in inhibiting and eradicating S. pyogenes biofilm. The antibiofilm activities were investigated using colorimetric assays, microscopy, cell surface hydrophobicity, gene expression analysis, and in-silico analysis. Carvacrol also showed a minimum biofilm inhibitory concentration (MBIC) against S. pyogenes of 125 μg/mL. The electron microscopic and confocal microscopic analyses revealed a dose-dependent suppression of biofilm formation and a reduction in the biofilm thickness by carvacrol. Carvacrol also inhibited the biofilm-associated virulence factors such as cell surface hydrophobicity. Quantitative real-time polymerase chain reaction analysis showed the downregulation of speB, srtB, luxS, covS, dltA, ciaH, and hasA genes involved in biofilm formation. The results suggested the therapeutic potential of carvacrol against biofilm-associated streptococcal infections.

An Overview of Antiviral Peptides and Rational Biodesign Considerations

Viral diseases have contributed significantly to worldwide morbidity and mortality throughout history. Despite the existence of therapeutic treatments for many viral infections, antiviral resistance and the threat posed by novel viruses highlight the need for an increased number of effective therapeutics. In addition to small molecule drugs and biologics, antimicrobial peptides (AMPs) represent an emerging class of potential antiviral therapeutics. While AMPs have traditionally been regarded in the context of their antibacterial activities, many AMPs are now known to be antiviral. These antiviral peptides (AVPs) have been shown to target and perturb viral membrane envelopes and inhibit various stages of the viral life cycle, from preattachment inhibition through viral release from infected host cells. Rational design of AMPs has also proven effective in identifying highly active and specific peptides and can aid in the discovery of lead peptides with high therapeutic selectivity. In this review, we highlight AVPs with strong antiviral activity largely curated from a publicly available AMP database. We then compile the sequences present in our AVP database to generate structural predictions of generic AVP motifs. Finally, we cover the rational design approaches available for AVPs taking into account approaches currently used for the rational design of AMPs.

Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

The global expansion of COVID-19 and the mutations of severe acute respiratory syndrome coronavirus necessitate quick development of treatment and vaccination. Because the androgen-responsive serine protease TMPRSS2 is involved in cleaving the SARS-CoV-2 spike protein allowing the virus to enter the cell, therefore, direct TMPRSS2 inhibition will inhibit virus activation and disease progression which make it an important target for drug discovery. In this study, a homology model of TMPRSS2 protein was initially developed. Then, we used the fragment-based drug design (FBDD) technique to develop effective TMPRSS2 inhibitors. Over a half-million fragments from the enamine database were screened for their binding ability to target protein, and then best-scoring fragments were linked to building new molecules with a good binding affinity. XP docking and MM-GBSA studies revealed 10 new formed molecules with docking score ≤ -14.982 kcal/mol compared to ambroxol (control) with a docking score of -6.464 kcal/mol. Finally, molecular dynamics (MD) and density functional theory (DFT) were calculated for the top 3 molecules.

Modelling and targeting mitochondrial protein tyrosine phosphatase 1: a computational approach

The present research scintillates on the homology modelling of rat mitochondrial protein tyrosine phosphatase 1 (PTPMT1) and targeting its activity using flavonoids through a computational docking approach. PTPMT1 is a dual-specificity phosphatase responsible for protein phosphorylation and plays a vital role in the metabolism of cardiolipin biosynthesis, insulin regulation, etc. The inhibition of PTPMT1 has also shown enhanced insulin levels. The three-dimensional structure of the protein is not yet known. The homology modelling was performed using SWISS-MODEL and Geno3D webservers to compare the efficiencies. The PROCHECK for protein modelled using SWISS-MODEL showed 91.6% of amino acids in the most favoured region, 0.7% residues in the disallowed region that was found to be significant compared to the model built using Geno3D. 210 common flavonoids were docked in the modelled protein using the AutoDock 4.2.6 along with a control drug alexidine dihydrochloride. Our results show promising candidates that bind protein tyrosine phosphatase 1, including, prunin (- 8.66 kcal/mol); oroxindin (- 8.56 kcal/mol); luteolin 7-rutinoside (- 8.47 kcal/mol); 3(2H)-isoflavenes (- 8.36 kcal/mol); nicotiflorin (- 8.29 kcal/mol), ranked top in the docking experiments. We predicted the pharmacokinetic and Lipinski properties of the top ten compounds with the lowest binding energies. To further validate the stability of the modelled protein and docked complexes molecular dynamics simulations were performed using Desmond, Schrodinger for 150 ns in conjunction with MM-GBSA. Thus, flavonoids could act as potential inhibitors of PTPMT1, and further, in-vitro and in-vivo studies are essential to complete the drug development process.

The design of TOPK inhibitors using structure-based pharmacophore modeling and molecular docking based on an MD-refined homology model

The TOPK enzyme (also known as PBK) is a serine-threonine protein kinase that is rarely detected in normal tissues yet is found to be overexpressed and activated in a variety of cancers such as lung, colorectal, breast, and esophageal cancer. Its prevalence in cancerous cells is associated with their poor prognosis and responsiveness to treatment. This enzyme plays a vital role in cell division, specifically in regulating cytokinesis. Unlike drugs targeting early phases in mitosis, inhibition of cytokinesis by targeting biomolecules that are unique to multiplying cells poses no threat to the normal function of non-multiplying cells. Studies have shown that inhibition of cytokinesis is promising in suppressing the growth of proliferating cancerous cells as exemplified by the complete tumor regression seen with the suppression of TOPK. Herein, we report the identification of potent TOPK inhibitors with anticancer potential using a structure-based drug design approach. The only available crystal structure of TOPK corresponds to a double mutant (T9E and T198E) dimer with a distorted N-lobe conformation, thus 3D homology modeling was implemented to rebuild the enzyme's native conformation. The resulting refined model was used to generate 3D pharmacophore models for the virtual screening of small molecules databases. Retrieved hits were filtered, docked into the ATP binding site of the enzyme, rescored, and the binding free energies for the top consensually scoring hits were calculated. Consequently, 45 compounds were selected and their in vitro inhibitory activity against TOPK was tested revealing four potential hits with the most active compound having an IC₅₀ of 3.85 µM. This compound will be chosen as a lead compound to synthesize analogs aiming to enhance potency and drug-like properties and to enrich the SAR data.

Indole-Containing Pyrazino[2,1-b]quinazoline-3,6-diones Active against Plasmodium and Trypanosomatids

Malaria, leishmaniasis, and sleeping sickness are potentially fatal diseases that represent a real health risk for more than 3,5 billion people. New antiparasitic compounds are urgent leading to a constant search for novel scaffolds. Herein, pyrazino[2,1-b]quinazoline-3,6-diones containing indole alkaloids were explored for their antiparasitic potential against Plasmodium falciparum, Trypanosoma brucei, and Leishmania infantum. The synthetic libraries furnished promising hit compounds that are species specific (7, 12) or with broad antiparasitic activity (8). Structure-activity relationships were more evident for Plasmodium with anti-isomers (1S,4R) possessing excellent antimalarial activity, while the presence of a substituent on the anthranilic acid moiety had a negative effect on the activity. Hit compounds against malaria did not inhibit β-hematin, and in silico studies predicted these molecules as possible inhibitors for prolyl-tRNA synthetase both from Plasmodium and Leishmania. These results disclosed a potential new chemotype for further optimization toward novel and affordable antiparasitic drugs.

Structural model of human PORCN illuminates disease-associated variants and drug-binding sites

Wnt signaling is essential for normal development and is a therapeutic target in cancer. The enzyme PORCN, or porcupine, is a membrane-bound O-acyltransferase (MBOAT) that is required for the post-translational modification of all Wnts, adding an essential mono-unsaturated palmitoleic acid to a serine on the tip of Wnt hairpin 2. Inherited mutations in PORCN cause focal dermal hypoplasia, and therapeutic inhibition of PORCN slows the growth of Wnt-dependent cancers. Based on homology to mammalian MBOAT proteins, we developed and validated a structural model of human PORCN. The model accommodates palmitoleoyl-CoA and Wnt hairpin 2 in two tunnels in the conserved catalytic core, shedding light on the catalytic mechanism. The model predicts how previously uncharacterized human variants of uncertain significance can alter PORCN function. Drugs including ETC-159, IWP-L6 and LGK-974 dock in the PORCN catalytic site, providing insights into PORCN pharmacologic inhibition. This structural model enhances our mechanistic understanding of PORCN substrate recognition and catalysis, as well as the inhibition of its enzymatic activity, and can facilitate the development of improved inhibitors and the understanding of disease-relevant PORCN mutants. This article has an associated First Person interview with the joint first authors of the paper.

Emerging Roles of Pleckstrin-2 Beyond Cell Spreading

Pleckstrin-2 is a member of pleckstrin family with well-defined structural features that was first identified in 1999. Over the past 20 years, our understanding of PLEK2 biology has been limited to cell spreading. Recently, increasing evidences support that PLEK2 plays important roles in other cellular events beyond cell spreading, such as erythropoiesis, tumorigenesis and metastasis. It serves as a potential diagnostic and prognostic biomarker as well as an attractive target for the treatment of cancers. Herein, we summary the protein structure and molecular interactions of pleckstrin-2, with an emphasis on its regulatory roles in tumorigenesis.

Bacterial Quorum-Sensing Molecules as Promising Natural Inhibitors of Candida albicans Virulence Dimorphism: An In Silico and In Vitro Study

Farnesol, a self-secreted quorum-sensing molecule (QSM) of Candida albicans, has been known to limit yeast-to-hyphal transition by blocking the RAS1-cAMP-PKA pathway. In a similar fashion, certain bacterial QSMs have also been reported to be successful in attenuating C. albicans biofilm and hyphal formation at relatively high cell density. This prompted us to investigate the antihyphal efficacy of certain bacterial QSMs through virtual docking against seminal drug targets, viz., CYCc and RAS1, that have been reported to be the hallmark players in C. albicans dimorphic virulence cascade. Against this backdrop, 64 QSMs belonging to five different bacterial QS signaling systems were subjected to initial virtual screening with farnesol as reference. Data of the virtual screening unveiled QSMs belonging to diketopiperazines (DKPs), i.e., 3-benzyl-6-isobutylidene-2,5-piperazinedione (QSSM 1157) and cyclo(l-Pro-l-Leu) (QSSM 1112), as potential inhibitors of CYCc and RAS1 with binding energies of -8.2 and -7.3 kcal mol-1, respectively. Further, the molecular dynamics simulations (for 50 ns) of CYCc-QSSM 1157 and RAS1-QSSM 1112 complexes revealed the mean ligand root mean square deviation (RMSD) values of 0.35 and 0.27 Å, respectively, which endorsed the rigid nature, less fluctuation in binding stiffness, and conformation of binding complexes. Furthermore, the identified two QSMs were found to be good in solubility, absorption, and permeation and less toxic in nature, as revealed by pharmacokinetics and toxicity analyses. In addition, the in vitro antihyphal assays using liquid and solid media, germ-tube experiment, and microscopic analysis strongly validated DKP-QSSM 1112 as a promising inhibitor of hyphal transition. Taken together, the present study unequivocally proves that DKPs can be used as potent inhibitors of C. albicans virulence dimorphism.

Identification of novel TMPRSS2 inhibitors for COVID-19 using e-pharmacophore modelling, molecular docking, molecular dynamics and quantum mechanics studies

SARS coronavirus 2 (SARS-CoV-2) has spread rapidly around the world and continues to have a massive global health effect, contributing to an infectious respiratory illness called coronavirus infection-19 (COVID-19). TMPRSS2 is an emerging molecular target that plays a role in the early stages of SARS-CoV-2 infection; hence, inhibiting its activity might be a target for COVID-19. This study aims to use many computational approaches to provide compounds that could be optimized into clinical candidates. As there is no experimentally derived protein information, initially we develop the TMPRSS2 model. Then, we generate a pharmacophore model from TMPRSS2 active site consequently, and the developed models were employed for the screening of one million molecules from the Enamine database. The created model was then screened using e-pharmacophore-based screening, molecular docking, free energy estimation and molecular dynamic simulation. Also, ADMET prediction and density functional theory calculations were performed. Three potential molecules (Z126202570, Z46489368, and Z422255982) exhibited promising stable binding interactions with the target. In conclusion, these findings empower further in vitro and clinical assessment for these compounds as novel anti-COVID19 agents.

Serum Albumin in Health and Disease: Esterase, Antioxidant, Transporting and Signaling Properties

Being one of the main proteins in the human body and many animal species, albumin plays a decisive role in the transport of various ions-electrically neutral and charged molecules-and in maintaining the colloidal osmotic pressure of the blood. Albumin is able to bind to almost all known drugs, as well as many nutraceuticals and toxic substances, largely determining their pharmaco- and toxicokinetics. Albumin of humans and respective representatives in cattle and rodents have their own structural features that determine species differences in functional properties. However, albumin is not only passive, but also an active participant of pharmacokinetic and toxicokinetic processes, possessing a number of enzymatic activities. Numerous experiments have shown esterase or pseudoesterase activity of albumin towards a number of endogeneous and exogeneous esters. Due to the free thiol group of Cys34, albumin can serve as a trap for reactive oxygen and nitrogen species, thus participating in redox processes. Glycated albumin makes a significant contribution to the pathogenesis of diabetes and other diseases. The interaction of albumin with blood cells, blood vessels and tissue cells outside the vascular bed is of great importance. Interactions with endothelial glycocalyx and vascular endothelial cells largely determine the integrative role of albumin. This review considers the esterase, antioxidant, transporting and signaling properties of albumin, as well as its structural and functional modifications and their significance in the pathogenesis of certain diseases.

Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors

BACKGROUND

Molecular docking is in regular practice to assess ligand affinity on a target protein crystal structure. In the absence of protein crystal structure, the homology modeling or comparative modeling is the best alternative to elucidate the relationship details between a ligand and protein at the molecular level. The development of accurate homology modeling (HM) and its integration with molecular docking (MD) is essential for successful, rational drug discovery.

OBJECTIVE

The G-protein coupled receptors (GPCRs) are attractive therapeutic targets due to their immense role in human pharmacology. The GPCRs are membrane-bound proteins with the complex constitution, and the understanding of their activation and inactivation mechanisms is quite challenging. Over the past decade, there has been a rapid expansion in the number of solved G-protein-coupled receptor (GPCR) crystal structures; however, the majority of the GPCR structures remain unsolved. In this context, HM guided MD has been widely used for structure-based drug design (SBDD) of GPCRs.

METHODS

The focus of this review is on the recent (i) developments on HM supported GPCR drug discovery in the absence of GPCR crystal structures and (ii) application of HM in understanding the ligand interactions at the binding site, virtual screening, determining receptor subtype selectivity and receptor behaviour in comparison with GPCR crystal structures.

RESULTS

The HM in GPCRs has been extremely challenging due to the scarcity in template structures. In such a scenario, it is difficult to get accurate HM that can facilitate understanding of the ligand-receptor interactions. This problem has been alleviated to some extent by developing refined HM based on incorporating active /inactive ligand information and inducing protein flexibility. In some cases, HM proteins were found to outscore crystal structures.

CONCLUSION

The developments in HM have been highly operative to gain insights about the ligand interaction at the binding site and receptor functioning at the molecular level. Thus, HM guided molecular docking may be useful for rational drug discovery for the GPCRs mediated diseases.

An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19

The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved in structure-based drug design are molecular docking and molecular dynamic simulation, whereas ligand-based drug design includes pharmacophore modeling, quantitative structure-activity relationship (QSARs), and artificial intelligence (AI). We have briefly discussed the significance of computer-aided drug design in the context of COVID-19 and how the researchers continue to rely on these computational techniques in the rapid identification of promising drug candidate molecules against various drug targets implicated in the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The structural elucidation of pharmacological drug targets and the discovery of preclinical drug candidate molecules have accelerated both structure-based as well as ligand-based drug design. This review article will help the clinicians and researchers to exploit the immense potential of computer-aided drug design in designing and identification of drug molecules and thereby helping in the management of fatal disease.

Absolute Configuration, Enantioselective Bioactivity, and Degradation of the Novel Chiral Triazole Fungicide Mefentrifluconazole

Mefentrifluconazole is a new chiral triazole fungicide with a pair of enantiomers. However, the enantioselective differences in the biological effects and environmental behaviors of mefentrifluconazole are unclear. In the present work, a new simultaneous determination method of mefentrifluconazole enantiomers was established using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The absolute configuration of the two mefentrifluconazole enantiomers was confirmed by comparing the experimental and calculated ECD spectra. The enantioselective bioactivity to target fungi and degradation in cucumber samples were also assessed. The absolute configurations of the two enantiomers eluted on the Superchiral IG-3 column were confirmed as R-(-)-mefentrifluconazole and S-(+)-mefentrifluconazole. The R-(-)-mefentrifluconazole possessed 5-473 times higher bioactivity than S-(+)-mefentrifluconazole toward six kinds of target pathogenic fungi. In addition, R-(-)-mefentrifluconazole exhibited stronger efficacy of suppression of ergosterol biosynthesis. The molecular docking results indicated that R-(-)-mefentrifluconazole had shorter binding distances and lower energies with the target protein than S-(+)-mefentrifluconazole, which may result in the enantioselective bioactivity. The high-efficiency enantiomer of R-(-)-mefentrifluconazole has longer duration in cucumber samples due to the relatively long half-life of 4.0 days. This research has clarified the bioactivity differences and mechanism between mefentrifluconazole enantiomers against target fungi and laid the foundation for an in-depth study of mefentrifluconazole at the chiral level.

Dasatinib-SIK2 Binding Elucidated by Homology Modeling, Molecular Docking, and Dynamics Simulations

Salt-inducible kinases (SIKs) are calcium/calmodulin-dependent protein kinase (CAMK)-like (CAMKL) family members implicated in insulin signal transduction, metabolic regulation, inflammatory response, and other processes. Here, we focused on SIK2, which is a target of the Food and Drug Administration (FDA)-approved pan inhibitor N-(2-chloro-6-methylphenyl)-2-(6-(4-(2-hydroxyethyl)piperazin-1-yl)-2-methylpyrimidin-4-ylamino)thiazole-5-carboxamide (dasatinib), and constructed four representative SIK2 structures by homology modeling. We investigated the interactions between dasatinib and SIK2 via molecular docking, molecular dynamics simulation, and binding free energy calculation and found that dasatinib showed strong binding affinity for SIK2. Binding free energy calculations suggested that the modification of various dasatinib regions may provide useful information for drug design and to guide the discovery of novel dasatinib-based SIK2 inhibitors.

S-(+)-Pentedrone and R-(+)-methylone as the most oxidative and cytotoxic enantiomers to dopaminergic SH-SY5Y cells: Role of MRP1 and P-gp in cathinones enantioselectivity

Cathinone derivatives are the most representative group within new drugs market, which have been described as neurotoxic. Since cathinones, as pentedrone and methylone, are available as racemates, it is our aim to study the neuronal cytotoxicity induced by each enantiomer. Therefore, a dopaminergic SH-SY5Y cell line was used to evaluate the hypothesis of enantioselectivity of pentedrone and methylone enantiomers on cytotoxicity, oxidative stress, and membrane efflux transport (confirmed by in silico studies). Our study demonstrated enantioselectivity of these cathinones, being the S-(+)-pentedrone and R-(+)-methylone the most oxidative enantiomers and also the most cytotoxic, suggesting the oxidative stress as main cytotoxic mechanism, as previously described in in vitro studies. Additionally, the efflux transporter multidrug resistance associated protein 1 (MRP1) seems to play, together with GSH, a selective protective role against the cytotoxicity induced by R-(-)-pentedrone enantiomer. It was also observed an enantioselectivity in the binding to P-glycoprotein (P-gp), another efflux protein, being the R-(-)-pentedrone and S-(-)-methylone the most transported enantiomeric compounds. These results were confirmed, in silico, by docking studies, revealing that R-(-)-pentedrone is the enantiomer with highest affinity to MRP1 and S-(-)-methylone and R-(-)-pentedrone are the enantiomers with highest affinity to P-gp. In conclusion, our data demonstrated that pentedrone and methylone present enantioselectivity in their cytotoxicity, which seems to involve different oxidative reactivity as well as different affinity to the P-gp and MRP1 that together with GSH play a protective role.

SARS CoV-2 Spike Protein in silico Interaction With ACE2 Receptors From Wild and Domestic Species

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared a pandemic by the World Health Organization (WHO), and since its first report, it has become a major public health concern. SARS-CoV-2 is closely related to SARS-CoV and SARS-related bat coronaviruses, and it has been described to use angiotensin-converting enzyme 2 (ACE2) as a receptor. Natural SARS-CoV-2 infection in domestic and wildlife animals, measured by RT-qPCR, has been confirmed in different countries, especially from the Felidae family. In silico analysis of the interaction between the SARS-CoV-2 spike protein and the cellular receptor ACE2 in various animal species has suggested that wild felids and domestic cats could be susceptible to SARS-CoV-2 based on this interaction. Here, we performed a protein-protein molecular docking analysis of SARS-CoV-2 spike protein with the ACE2 receptor from different animals to elucidate the potential of those species as intermediate hosts or susceptible animals for SARS-CoV-2 infection. Compared to human ACE2, we found that ACE2 receptors from domestic cats and tigers could efficiently interact with RBD of SARS CoV-2 Spike protein. However, dog, ferret, and hamster ACE2 receptor interaction with SARS-CoV-2 S protein RBD was not predicted as favorable, demonstrating a potential differentiated susceptibility in the evaluated species.

SARS-CoV-2 entry inhibitors by dual targeting TMPRSS2 and ACE2: An in silico drug repurposing study

The coronavirus disease (COVID-19) is spreading between human populations mainly through nasal droplets. Currently, the vaccines have great hope, but it takes years for testing its efficacy in human. As there is no specific drug treatment available for COVID-19 pandemic, we explored in silico repurposing of drugs with dual inhibition properties by targeting transmembrane serine protease 2 (TMPRSS2) and human angiotensin-converting enzyme 2 (ACE2) from FDA-approved drugs. The TMPRSS2 and ACE2 dual inhibitors in COVID-19 would be a novel antiviral class of drugs called “entry inhibitors.” For this purpose, approximately 2800 US-FDA approved drugs were docked using a virtual docking tool with the targets TMPRSS2 and ACE2. The best-fit drugs were selected as per docking scores and visual outcomes. Later on, drugs were selected on the basis of molecular dynamics simulations. The drugs alvimopan, arbekacin, dequalinum, fleroxacin, lopinavir, and valrubicin were shortlisted by visual analysis and molecular dynamics simulations. Among these, lopinavir and valrubicin were found to be superior in terms of dual inhibition. Thus, lopinavir and valrubicin have the potential of dual-target inhibition whereby preventing SARS-CoV-2 entry to the host. For repurposing of these drugs, further screening in vitro and in vivo would help in exploring clinically.

Investigation of Alpinia calcarata constituent interactions with molecular targets of rheumatoid arthritis: docking, molecular dynamics, and network approach

Rheumatoid arthritis (RA) is a systemic autoimmune disorder that commonly affects multiple joints of the body. Currently, there is no permanent cure to the disease, but it can be managed with several potent drugs that cause serious side effects on prolonged use. Traditional remedies are considered promising for the treatment of several diseases, particularly chronic conditions, because they have lower side effects compared to synthetic drugs. In folklore, the rhizome of Alpinia calcarata Roscoe (Zingiberaceae) is used as a major ingredient of herbal formulations to treat RA. Phytoconstituents reported in A. calcarata rhizomes are diterpenoids, sesquiterpenoid, flavonoids, phytosterol, and volatile oils. The present study is intended to understand the molecular-level interaction of phytoconstituents present in A. calcarata rhizomes with RA molecular targets using computational approaches. A total of 30 phytoconstituents reported from the plant were used to carry out docking with 36 known targets of RA. Based on the docking results, 4 flavonoids were found to be strongly interacting with the RA targets. Further, molecular dynamics simulation confirmed stable interaction of quercetin with 6 targets (JAK3, SYK, MMP2, TLR8, IRAK1, and JAK1), galangin with 2 targets (IRAK1 and JAK1), and kaempferol (IRAK1) with one target of RA. Moreover, the presence of these three flavonoids was confirmed in the A. calcarata rhizome extract using LC-MS analysis. The computational study suggests that flavonoids present in A. calcarata rhizome may be responsible for RA modulatory activity. Particularly, quercetin and galangin could be potential development candidates for the treatment of RA. Investigation of Alpinia calcarata constituent interactions with molecular targets of rheumatoid arthritis: docking, molecular dynamics, and network approach.

Current computer-aided drug design methodologies in discovery of novel drug candidates for neuropsychiatric and inflammatory diseases

Drug discovery and development is a very challenging, expensive and time-consuming process. Impressive technological advances in computer sciences and molecular biology have made it possible to use computer-aided drug design (CADD) methods in various stages of the drug discovery and development pipeline. Nowadays, CADD presents an efficacious and indispensable tool, widely used in medicinal chemistry, to lead rational drug design and synthesis of novel compounds. In this article, an overview of commonly used CADD approaches from hit identification to lead optimization was presented. Moreover, different aspects of design of multitarget ligands for neuropsychiatric and anti-inflammatory diseases were summarized. Apparently, designing multi-target directed ligands for treatment of various complex diseases may offer better efficacy, and fewer side effects. Antipsychotics that act through aminergic G protein-coupled receptors (GPCRs), especially Dopamine D2 and serotonin 5-HT2A receptors, are the best option for treatment of various symptoms associated with neuropsychiatric disorders. Furthermore, multi-target directed cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors are also a successful approach to aid the discovery of new anti-inflammatory drugs with fewer side effects. Overall, employing CADD approaches in the process of rational drug design provides a great opportunity for future development, allowing rapid identification of compounds with the optimal polypharmacological profile.

Carfilzomib as a potential inhibitor of NADH-dependent enoyl-acyl carrier protein reductases of Klebsiella pneumoniae and Mycobacterium tuberculosis as a drug target enzyme: insights from molecular docking and molecular dynamics

Multiple antibiotic-resistant strains of Klebsiella pneumoniae can cause life-threatening infections. Bacterial enoyl-acyl carrier protein (ACP) reductases (ENRs) are considered critical targets for developing antibiotics. Our current study aims to identify inhibitors of K. pneumoniae ENRs (FabI and FabV). Due to the unavailability of experimental structures, protein models of FabI and FabV were predicted and validated in this study. Virtual screening of the 1930 FDA-approved drug database was conducted against the active site of the FabI protein with the help of the LEA3D server, and carfilzomib was chosen among the screened drugs for further docking studies. Carfilzomib, a proteasome inhibitor used in the treatment of multiple myeloma, was among the best-suited compounds obtained from the virtual screening and was found to be bactericidal in the in vitro experiment. Carfilzomib was docked against the active sites of the FabI and FabV proteins, and the ENR of Mycobacterium tuberculosis, InhA. Carfilzomib showed a high binding affinity with all three proteins. Molecular dynamics (MD) simulations were conducted following the docking studies. MD simulations revealed that carfilzomib binds strongly to the active sites of the above mentioned ENRs. Our study found that carfilzomib is a potential inhibitor of the ENRs of K. pneumoniae and M. tuberculosis. This is a possible mechanism of its bactericidal property against M. tuberculosis observed in vitro in addition to its predicted actions on zinc-dependent metalloprotease-1 and peptide deformylase, two other drug target enzymes of M. tuberculosis. Our study suggests that this drug could be used as a lead compound to develop antibiotics that can selectively act against ENRs of bacteria, without interfering with the activities of human proteasome. Communicated by Ramaswamy H. Sarma.

Evaluation of the potency of FDA-approved drugs on wild type and mutant SARS-CoV-2 helicase (Nsp13)

SARS-CoV-2 has caused COVID-19 outbreak with nearly 2 M infected people and over 100K death worldwide, until middle of April 2020. There is no confirmed drug for the treatment of COVID-19 yet. As the disease spread fast and threaten human life, repositioning of FDA approved drugs may provide fast options for treatment. In this aspect, structure-based drug design could be applied as a powerful approach in distinguishing the viral drug target regions from the host. Evaluation of variations in SARS-CoV-2 genome may ease finding specific drug targets in the viral genome. In this study, 3458 SARS-CoV-2 genome sequences isolated from all around the world were analyzed. Incidence of C17747T and A17858G mutations were observed to be much higher than others and they were on Nsp13, a vital enzyme of SARS-CoV-2. Effect of these mutations was evaluated on protein-drug interactions using in silico methods. The most potent drugs were found to interact with the key and neighbor residues of the active site responsible from ATP hydrolysis. As result, cangrelor, fludarabine, folic acid and polydatin were determined to be the most potent drugs which have potency to inhibit both the wild type and mutant SARS-CoV-2 helicase. Clinical data supporting these findings would be important towards overcoming COVID-19.