An in silico approach for identification of lead compound as FtsZ inhibitor.

The remarkable conservation of the FtsZ among Gram-positive and Gram-negative bacteria, a crucial GTPase in bacterial cell division, has emerged as a promising antibacterial drug target to combat antibacterial resistance. There have been several coordinated efforts to develop inhibitors against FtsZ which can also serve as potential candidates for future antibiotics. In the present study, a natural product-like library (≈50,000 compounds) was employed to conduct HTVS against Staphylococcus aureus FtsZ protein (PDB Id: 6KVP). Additionally, molecular docking was carried out in two modes, SP and XP docking, using the Schrödinger suite. The glide scores of ligands obtained by XP docking were further summarized and compared with the control ligands (ZI1- co-crystal and PC190723-a compound undergoing clinical trial). Using the Prime-MM-GBSA approach, BFE calculations were performed on the top XP-scored ligands (≈598 compounds). These hits were also evaluated for ADMET parameters using the Qikprop algorithm, SwissADME, and in silico carcinogenicity testing using Carcinopred-El. Based on the results, ligand 4-FtsZ complex was considered for the 300 ns MDS analysis to get insights into its binding modes within the catalytic pocket of FtsZ protein. The analysis revealed that the amide linkage sandwiched between the triazole and 1-oxa-8-azaspirodecan-8-ium moiety (Val203) as well as the aminoethyl group present at 1st position on the triazole moiety (Leu209, Leu200, Asp210, and Ala202) were responsible for the FtsZ inhibitory activity, owing to their crucial interactions with key amino acid residues. Further, the complex also displayed good protein-ligand stability, ultimately predicting ligand 4 as a potent lead compound for the inhibition of FtsZ. Thus, our in silico findings will serve as a framework for in-depth in-vitro and in-vivo investigations encouraging the development of FtsZ inhibitors as a new generation of antibacterial agents.

Identification of potential JNK3 inhibitors through virtual screening, molecular docking and molecular dynamics simulation as therapeutics for Alzheimer's disease.

Alzheimer's disease (AD) is a complex neurological disorder and no effective drug is available for its treatment. Numerous pathological conditions are believed to be responsible for the initiation and development of AD including c-Jun N-terminal kinases (JNKs). The JNKs are one of the enzymes from the mitogen-activated protein kinase (MAPK) family that controls the phosphorylation of various transcription factors on serine and threonine residues, and hold significant responsibilities in tasks like gene expression, cell proliferation, differentiation, and apoptosis. Since, JNK3 is primarily expressed in the brain hence its increased levels in the brain are associated with the AD pathology promoting neurofibrillary tangles, senile plaques, neuroinflammation, and nerve cell apoptosis. The current research work is focused on the development of novel JNK inhibitors as therapeutics for AD employing a structure-based virtual screening (SBVS) approach. The ZINC database (14634052 compounds) was investigated after employing pan assay interference (PAINs), drug-likeness, and diversity picking filter to distinguish molecules interacting with JNK3 by following three docking precision criteria: High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP) & MMGBSA. Five lead molecules showed a better docking score in the range of -13.091 to -14.051 kcal/mol better than the reference compound (- 11.828 kcal/mol). The lead compounds displayed acceptable pharmacokinetic properties and were subjected to molecular dynamic simulations of 100 ns and binding free energy calculations. All the lead molecules showed stable RMSD and hydrogen bond interactions throughout the trajectory. The ∆GMM/PBSA_total score for the lead compounds ZINC220382956, ZINC147071339, ZINC207081127, ZINC205151456, ZINC1228819126, and CC-930 was calculated and found to be - 31.39, - 42.8, - 37.04, - 39.01, - 36.5, - 34.16 kcal/mol, respectively. Thus, it was concluded that the lead molecules identified in these studies have the potential to be explored as potent JNK3 inhibitors.

Identification of a novel spirocyclic Nek2 inhibitor using high throughput virtual screening.

NIMA Related Kinase 2 (Nek2) kinase is an attractive target for the development of therapeutic agents for several types of highly invasive cancers. Despite this, no small molecule inhibitor has advanced to the late clinical stages thus far. In this work, we have identified a novel spirocyclic inhibitor (V8) of Nek2 kinase, utilizing a high-throughput virtual screening (HTVS) approach. Using recombinant Nek2 enzyme assays, we show that V8 can inhibit Nek2 kinase activity (IC50 = 2.4 ± 0.2 µM) by binding to the enzyme's ATP pocket. The inhibition is selective, reversible and is not time dependent. To understand the key chemotype features responsible for Nek2 inhibition, a detailed structure-activity relationships (SAR) was performed. Using molecular models of the energy-minimized structures of Nek2-inhibitory complexes, we identify key hydrogen-bonding interactions, including two from the hinge-binding region, likely responsible for the observed affinity. Finally, using cell-based studies, we show that V8 attenuates (a) pAkt/PI3 Kinase signaling in a dose-dependent manner, and (b) proliferative and migratory phenotypes of highly aggressive human MDA-MB-231 breast and A549 lung cancer cell lines. Thus, V8 is an important novel lead compound for the development of highly potent and selective Nek2 inhibitory agents.

Targeting lipid-sensing nuclear receptors PPAR (α, γ, ß/δ): HTVS and molecular docking/dynamics analysis of pharmacological ligands as potential pan-PPAR agonists.

The global prevalence of obesity-related systemic disorders, including non-alcoholic fatty liver disease (NAFLD), and cancers are rapidly rising. Several of these disorders involve peroxisome proliferator-activated receptors (PPARs) as one of the key cell signaling pathways. PPARs are nuclear receptors that play a central role in lipid metabolism and glucose homeostasis. They can activate or suppress the genes responsible for inflammation, adipogenesis, and energy balance, making them promising therapeutic targets for treating metabolic disorders. In this study, an attempt has been made to screen novel PPAR pan-agonists from the ZINC database targeting the three PPAR family of receptors (α, γ, ß/δ), using molecular docking and molecular dynamics (MD) simulations. The top scoring five ligands with strong binding affinity against all the three PPAR isoforms were eprosartan, canagliflozin, pralatrexate, sacubitril, olaparib. The ADMET analysis was performed to assess the pharmacokinetic profile of the top 5 molecules. On the basis of ADMET analysis, the top ligand was subjected to MD simulations, and compared with lanifibranor (reference PPAR pan-agonist). Comparatively, the top-scoring ligand showed better protein-ligand complex (PLC) stability with all the PPARs (α, γ, ß/δ). When experimentally tested in in vitro cell culture model of NAFLD, eprosartan showed dose dependent decrease in lipid accumulation and oxidative damage. These outcomes suggest potential PPAR pan-agonist molecules for further experimental validation and pharmacological development, towards treatment of PPAR-mediated metabolic disorders.

A short survey of dengue protease inhibitor development in the past 6 years (2015-2020) with an emphasis on similarities between DENV and SARS-CoV-2 proteases.

Dengue remains a disease of significant concern, responsible for nearly half of all arthropod-borne disease cases across the globe. Due to the lack of potent and targeted therapeutics, palliative treatment and the adoption of preventive measures remain the only available options. Compounding the problem further, the failure of the only dengue vaccine, Dengvaxia®, also delivered a significant blow to any hopes for the treatment of dengue fever. However, the success of Human Immuno-deficiency Virus (HIV) and Hepatitis C Virus (HCV) protease inhibitors in the past have continued to encourage researchers to investigate other viral protease targets. Dengue virus (DENV) NS2B-NS3 protease is an attractive target partly due to its role in polyprotein processing and also for being the most conserved domain in the viral genome. During the early days of the COVID-19 pandemic, a few cases of Dengue-COVID 19 co-infection were reported. In this review, we compared the substrate-peptide residue preferences and the residues lining the sub-pockets of the proteases of these two viruses and analyzed the significance of this similarity. Also, we attempted to abridge the developments in anti-dengue drug discovery in the last six years (2015-2020), focusing on critical discoveries that influenced the research.

In silico identification and in vivo characterization of small molecule therapeutic hypothermia mimetics.

Hypothermia has been proved to have a beneficial effect on several pathologies. CIRBP is one of the so termed cold-shock proteins involved in this process. In this work, we have detected small molecules capable of modulating the activity of CIRBP in the absence of a cold stimulus, by High Throughput Virtual Screening (HTVS) of the Diversity Set IV of the NCI and 15 compounds of our in-house data base. Fifteen compounds were selected from the HTVS to carry out a second screening through a cell-based Western blot assay. This assay, together with molecular modeling studies allowed us to select compound zr17-2 for an in vivo experiment, which showed an interesting increase of CIRBP expression in several organs of experimental animals. Therefore, we have demonstrated that the effect of hypothermia can be mimicked by small molecules, which can be developed as first-in-class new drugs for the treatment of several diseases.

3D QSAR, pharmacophore and molecular docking studies of known inhibitors and designing of novel inhibitors for M18 aspartyl aminopeptidase of Plasmodium falciparum.

BACKGROUND: The Plasmodium falciparum M18 Aspartyl Aminopeptidase (PfM18AAP) is only aspartyl aminopeptidase which is found in the genome of P. falciparum and is essential for its survival. The PfM18AAP enzyme performs various functions in the parasite and the erythrocytic host such as hemoglobin digestion, erythrocyte invasion, parasite growth and parasite escape from the host cell. It is a valid target to develop antimalarial drugs. In the present work, we employed 3D QSAR modeling, pharmacophore modeling, and molecular docking to identify novel potent inhibitors that bind with M18AAP of P. falciparum. RESULTS: The PLSR QSAR model showed highest value for correlation coefficient r(2) (88 %) and predictive correlation coefficient (pred_r2) =0.6101 for external test set among all QSAR models. The pharmacophore modeling identified DHRR (one hydrogen donor, one hydrophobic group, and two aromatic rings) as an essential feature of PfM18AAP inhibitors. The combined approach of 3D QSAR, pharmacophore, and structure-based molecular docking yielded 10 novel PfM18AAP inhibitors from ChEMBL antimalarial library, 2 novel inhibitors from each derivative of quinine, chloroquine, 8-aminoquinoline and 10 novel inhibitors from WHO antimalarial drugs. Additionally, high throughput virtual screening identified top 10 compounds as antimalarial leads showing G-scores -12.50 to -10.45 (in kcal/mol), compared with control compounds(G-scores -7.80 to -4.70) which are known antimalarial M18AAP inhibitors (AID743024). This result indicates these novel compounds have the best binding affinity for PfM18AAP. CONCLUSION: The 3D QSAR models of PfM18AAP inhibitors provided useful information about the structural characteristics of inhibitors which are contributors of the inhibitory potency. Interestingly, In this studies, we extrapolate that the derivatives of quinine, chloroquine, and 8-aminoquinoline, for which there is no specific target has been identified till date, might show the antimalarial effect by interacting with PfM18AAP.

Identification of Triazolopyrimidinyl Scaffold SARS-CoV-2 Papain-Like Protease (PLpro) Inhibitor.

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its companion disease, COVID-19, has reminded us of the importance of basic coronaviral research. In this study, a comprehensive approach using molecular docking, in vitro assays, and molecular dynamics simulations was applied to identify potential inhibitors for SARS-CoV-2 papain-like protease (PLpro), a key and underexplored viral enzyme target. A focused protease inhibitor library was initially created and molecular docking was performed using CmDock software (v0.2.0), resulting in the selection of hit compounds for in vitro testing on the isolated enzyme. Among them, compound 372 exhibited promising inhibitory properties against PLpro, with an IC50 value of 82 ± 34 µM. The compound also displayed a new triazolopyrimidinyl scaffold not yet represented within protease inhibitors. Molecular dynamics simulations demonstrated the favorable binding properties of compound 372. Structural analysis highlighted its key interactions with PLpro, and we stress its potential for further optimization. Moreover, besides compound 372 as a candidate for PLpro inhibitor development, this study elaborates on the PLpro binding site dynamics and provides a valuable contribution for further efforts in pan-coronaviral PLpro inhibitor development.

Identification of novel natural product inhibitors of BRD4 using high throughput virtual screening and MD simulation.

Bromodomains are evolutionarily conserved structural motifs that recognize acetylated lysine residues on histone tails. They play a crucial role in shaping chromatin architecture and regulating gene expression in various biological processes. Mutations in bromodomains containing proteins lead to multiple human diseases, which makes them attractive target for therapeutic intervention. Extensive studies have been done on BRD4 as a target for several cancers, such as Acute Myeloid Leukemia (AML) and Burkitt Lymphoma. Several potential inhibitors have been identified against the BRD4 bromodomain. However, most of these inhibitors have drawbacks such as non-specificity and toxicity, decreasing their appeal and necessitating the search for novel non-toxic inhibitors. This study aims to address this need by virtually screening natural compounds from the NPASS database against the Kac binding site of BRD4-BD1 using high throughput molecular docking followed by similarity clustering, pharmacokinetic screening, MD simulation and MM-PBSA binding free energy calculations. Using this approach, we identified five natural product inhibitors having a similar or better binding affinity to the BRD4 bromodomain compared to JQ1 (previously reported inhibitor of BRD4). Further systematic analysis of these inhibitors resulted in the top three hits: NPC268484 (Palodesangren-B), NPC295021 (Candidine) and NPC313112 (Buxifoliadine-D). Collectively, our in silico results identified some promising natural products that have the potential to act as potent BRD4-BD1 inhibitors and can be considered for further validation through future in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

A high-throughput structural dynamics approach for identification of potential agonists of FFAR4 for type 2 diabetes mellitus therapy.

Diabetes mellitus is a metabolic disorder that persists as a global threat to the world. A G-protein coupled receptor (GPCR), free fatty acid receptor 4 (FFAR4), has emerged as a potential target for type 2 diabetes mellitus (T2DM) and obesity-related disorders. The current study has investigated the FFAR4, deploying 3-dimensional structure modeling, molecular docking, machine learning, and high-throughput virtual screening methods to unravel the receptor's crucial and non-crucial binding site residues. We screened four lakh compounds and shortlisted them based on binding energy, stereochemical considerations, non-bonded interactions, and pharmacokinetic profiling. Out of the screened compounds, four compounds were selected for ligand-bound simulations. The molecular dynamic simulations were carried out for 1µs for native FFAR4 and 500 ns each for complexes of FFAR4 with compound 1, compound 2, compound 3, and compound 4. Our findings showed that in addition to reported binding site residues ARG99, ARG183, and VAL98 in known agonists like TUG-891, the amino acids ARG22, ARG24, THR23, TRP305, and GLU43 were also critical binding site residues. These amino acids impart stability to the FFAR4 complexes and contribute to the stronger binding affinity of the compounds. The study also indicated that aromatic residues like PHE211 are crucial for recognizing the active site's pi-pi and C-C double bonds. Since FFAR4 is a membrane protein, the simulation studies give an insight into the mechanisms of the crucial protein-lipid and lipid-water interactions. The analysis of the molecular dynamics trajectories showed all four compounds as potential hit molecules that can be developed further into potential agonists for T2DM therapy. Amongst the four compounds, compound 4 showed relatively better binding affinity, stronger non-bonded interactions, and a stable complex.Communicated by Ramaswamy H. Sarma.

Atomic level and structural understanding of natural ligands inhibiting Helicobacter pylori peptide deformylase through ligand and receptor based screening, SIFT, molecular dynamics and DFT - a structural computational approach.

Helicobacter pylori is a Gram-negative microaerophilic gastric pathogen, responsible for the cause of peptic ulcer around half of the global population. Although several antibiotics and combination therapies have been employed for H. pylori-related gastric ulcer and cancer regiments, identifying potent inhibitors for specific targets of this bacterium will help assessing better treatment periodicity and methods to eradicate H. pylori. Herein, 1,000,000 natural compounds were virtually screened against Helicobacter pylori Peptide deformylase (HpPDF). Pharmacophore hypotheses were created using ligand and receptor-based pharmacophore modeling of GLIDE. Stringent HTVS and IFD docking protocol of GLIDE predicted leads with stable intermolecular bonds and scores. Molecular dynamics simulation of HpPDF was carried out for 100 ns using GROMACS. Hits ZINC00225109 and ZINC44896875 came up with a glide score of -9.967 kcal/mol and -12.114 kcal/mol whereas; reference compound actinonin produced a glide score of -9.730 kcal/mol. Binding energy values of these hits revealed the involvement of significant Van der Waals and Coulomb forces and the deduction of lipophilic forces that portray the deep hydrophobic residues in the S1pocket of H. pylori. The DFT analysis established the electron density-based features of the molecules and observed that the results correlate with intermolecular docking interactions. Analysis of the MD trajectories revealed the crucial residues involved in HpPDF - ligand binding and the conformational changes in the receptor. We have identified and deciphered the crucial features necessary for the potent ligand binding at catalytic site of HpPDF. The resulting ZINC natural compound hits from the study could be further employed for potent drug development.Communicated by Ramaswamy H. Sarma.

GlmU Inhibitors as Promising Antibacterial Agents: A Review.

Bacterial infections are a major cause of mortality and morbidity in humans throughout the world. Infections due to resistant bacterial strains such as methicillin-resistant Staphyloccocusaureus vancomycin, resistant Enterococci, Klebsiella pneumoniae, Staphylococcus aureus, and Mycobacterium are alarming. Hence the development of new antibacterial agents, which act via a novel mechanism of action, became a priority in antibacterial research. One such approach to overcome bacterial resistance is to target novel protein and develop antibacterial agents that act via different mechanisms of action. Bacterial GlmU is one such bifunctional enzyme that catalyzes the two consecutive reactions during the biosynthesis of uridine 5'-diphospho-Nacetylglucosamine, an essential precursor for the biosynthesis of bacterial cell wall peptidoglycan. This enzyme comprises two distinct active sites; acetyltransferase and uridyltransferase and both these active sites act independently during catalytic reactions. GlmU is considered an attractive target for the design and development of newer antibacterial agents due to its important role in bacterial cell wall synthesis and the absence of comparable enzymes in humans. Availability of three dimensions X-crystallographic structures of GlmU and their known catalytic mechanism from different bacterial strains have instigated research efforts for the development of novel antibacterial agents. Several GlmU inhibitors belonging to different chemical classes like 2- phenylbenzofuran derivative, quinazolines, aminoquinazolines, sulfonamides, arylsulfonamide, D-glucopyranoside 6-phosphates, terreic acid, iodoacetamide, N-ethyl maleimide, and Nethylmaleimide etc., have been reported in the literature. In the present review, we present an update on GlmU inhibitors and their associated antibacterial activities. This review may be useful for the design and development of novel GlmU inhibitors with potent antibacterial activity.

Identification of potential inhibitors against Escherichia coli Mur D enzyme to combat rising drug resistance: an in-silico approach.

Indiscriminate use of anti-microbial agents has resulted in the inception, frequency, and spread of antibiotic resistance among targeted bacterial pathogens and the commensal flora. Mur enzymes, playing a crucial role in cell-wall synthesis, are one of the most appropriate targets for developing novel inhibitors against antibiotic-resistant bacterial pathogens. In the present study, in-silico high-throughput virtual (HTVS) and Standard-Precision (SP) screening was carried out with 0.3 million compounds from several small-molecule libraries against the E. coli Mur D enzyme (PDB ID 2UUP). The docked complexes were further subjected to extra-precision (XP) docking calculations, and highest Glide-score compound was further subjected to molecular simulation studies. The top six virtual hits (S1-S6) displayed a glide score (G-score) within the range of -9.013 to -7.126 kcal/mol and compound S1 was found to have the highest stable interactions with the Mur D enzyme (2UUP) of E. coli. The stability of compound S1 with the Mur D (2UUP) complex was validated by a 100-ns molecular dynamics simulation. Binding free energy calculation by the MM-GBSA strategy of the S1-2UUP (Mur D) complex established van der Waals, hydrogen bonding, lipophilic, and Coulomb energy terms as significant favorable contributors for ligand binding. The final lead molecules were subjected to ADMET predictions to study their pharmacokinetic properties and displayed promising results, except for certain modifications required to improve QPlogHERG values. So, the compounds screened against the Mur D enzyme can be further studied as preparatory points for in-vivo studies to develop potential drugs. HIGHLIGHTSE.coli is a common cause of urinary tract infections.E.coli MurD enzyme is a suitable target for drug development.Novel inhibitors against E.coli MurD enzyme were identified.Molecular dynamics studies identified in-silico potential of identified compound.ADMET predictions and Lipinski's rule of five studies showed promising results.Communicated by Ramaswamy H. Sarma.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach.

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

Physicochemical parameters for design and development of lead herbicide molecules: Is 'Lipinski's rule of 5' appropriate for herbicide discovery?

BACKGROUND: Herbicide use has been a great add-on in agriculture, aiding weed management in crop fields, thereby escalating crop production. However, the development of resistance in weeds against the existing herbicides is a setback. The development of herbicide resistance has compelled the agrochemical industries to replace existing herbicides with novel agrochemicals. Developing new herbicide molecules through traditional methods is time-consuming and cost-prohibitive. The use of high-throughput virtual screening (HTVS) through physicochemical properties, de novo design and combinatorial design of molecules with cutting-edge computational methods is an alternative to the traditional techniques in lead molecule discovery. The lack of optimal physicochemical criteria for screening herbicide-like molecules has become a hindrance in the process. RESULTS: In this study, physicochemical parameters [molecular weight, aromatic atoms, rotatable bonds, hydrogen-bonding capacity, topological polar surface area (TPSA), polarity and solubility] of known herbicide molecules have been studied and evaluated, and optimal criteria have been proposed for target-specific herbicides. Properties including molecular weight and hydrogen (H)-bond acceptor atoms tend to have higher values, but the range of H-bond donor atoms is relatively lower. These are distinguishable characteristics in herbicides when compared with oral drugs. Significant variations in optimal physicochemical parameters between herbicides of different groups (targeting weeds with different modes of action) have been observed. CONCLUSION: The proposed parameters for respective target sites could be used as filters for in silico screening, designing and developing of target-specific lead herbicide molecules. © 2023 Society of Chemical Industry.

Virtual screening and multilevel precision-based prioritisation of natural inhibitors targeting the ATPase domain of human DNA topoisomerase II alpha.

Human DNA topoisomerase II alpha (hTopIIα) is a classic chemotherapeutic drug target. The existing hTopIIα poisons cause numerous side effects such as the development of cardiotoxicity, secondary malignancies, and multidrug resistance. The use of catalytic inhibitors targeting the ATP-binding cavity of the enzyme is considered a safer alternative due to the less deleterious mechanism of action. Hence, in this study, we carried out high throughput structure-based virtual screening of the NPASS natural product database against the ATPase domain of hTopIIα and identified the five best ligand hits. This was followed by comprehensive validation through molecular dynamics simulations, binding free energy calculation and ADMET analysis. On stringent multilevel prioritization, we identified promising natural product catalytic inhibitors that showed high binding affinity and stability within the ligand-binding cavity and may serve as ideal hits for anticancer drug development.Communicated by Ramaswamy H. Sarma.

Optimal decision-making in high-throughput virtual screening pipelines.

The need for efficient computational screening of molecular candidates that possess desired properties frequently arises in various scientific and engineering problems, including drug discovery and materials design. However, the enormous search space containing the candidates and the substantial computational cost of high-fidelity property prediction models make screening practically challenging. In this work, we propose a general framework for constructing and optimizing a high-throughput virtual screening (HTVS) pipeline that consists of multi-fidelity models. The central idea is to optimally allocate the computational resources to models with varying costs and accuracy to optimize the return on computational investment. Based on both simulated and real-world data, we demonstrate that the proposed optimal HTVS framework can significantly accelerate virtual screening without any degradation in terms of accuracy. Furthermore, it enables an adaptive operational strategy for HTVS, where one can trade accuracy for efficiency.

Atosiban and Rutin exhibit anti-mycobacterial activity - An integrated computational and biophysical insight toward drug repurposing strategy against Mycobacterium tuberculosis targeting its essential enzyme HemD.

With the advancements of high throughput computational screening procedures, drug repurposing became the privileged framework for drug discovery. The structure-based drug discovery is the widely used method of drug repurposing, consisting of computational screening of compounds and testing them in-vitro. This current method of repurposing leaves room for mechanistic insights into how these screened hits interact with and influence their targets. We addressed this gap in the current study by integrating highly sensitive biophysical methods into existing computational repurposing methods. We also corroborated our computational and biophysical findings on H37Rv for the anti-mycobacterial action of selected drugs in-vitro and ex-vivo conditions. Atosiban and Rutin were screened as highly interacting hits against HemD through multi-stage docking and were cross-validated in biophysical studies. The affinity of these drugs (K ~ 106 M-1) was quantified using fluorescence quenching studies. Differential Scanning Fluorimetry (DSF) and urea-based chemical denaturation studies revealed a destabilizing effect of these drugs on target which was further validated using MD simulations. Conformational rearrangements of secondary structures were established using CD spectra and intrinsic fluorescence. Furthermore, Atosiban and Rutin inhibited M.tb growth in-vitro and ex-vivo while remaining non-toxic to mice peritoneal macrophages.

An in-silico investigation of potential natural polyphenols for the targeting of COVID main protease inhibitor.

The deadliest recent pandemic outbreak of COVID-19 disease has severely damaged the socio-economic health of the people globally. Due to unavailability of any effective vaccine or treatment the human beings are still struggling to overcome the pandemic condition. In an attempt to discover anti-COVID molecule, we used in-silico approach and reported 160 natural polyphenols to identify the most promising druggable HITs that can further used for drug discovery process. The co-crystallized structure COVID protease enzyme (PDB id 6LU7) was used. HTVS, MD simulation, binding energy calculations and in-silico ADME calculation were done and analyzed. Depending upon the scores three compounds galangin, nalsudaldain and rhamnezine were identified and the docking score were found to be -7.704, -6.51, -4.212 respectively. These docked complexes were further subjected to MD simulation runs over a 100 ns time and the RMSD and RMSF values were determined. The RMSD values of three compounds were found to be 2.9 Å, 7.6 Å & 9.5 Å respectively and the lowest RMSF values suggested the steady stability of ligand-protein complexes. The binding free energies (ΔG) of compounds with protein were found to be -49.8, -56.45, -62.87 kJ/mole. Moreover, in-silico ADME calculations indicated the drug likeliness properties of these molecules. By considering all these in-silico results the identified HITs would be the most probable anti-COVID drug molecules that can be further taken in wet lab and can act as lead for development of newer inhibitor of COVID-19 main protease enzyme.

Rational designing of peptide-ligand conjugates-based immunotherapy for the treatment of complicated malaria.

AIMS: Malaria deaths occur primarily due to complicated malaria associated with the sequestration of Plasmodium falciparum-infected erythrocyte (PfIE) in the capillary microvasculature. This study aims to design peptide ligand conjugates (PLCs) for treating complicated malaria using various in silico techniques. The PLC includes a natural ligand for the Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1): expressed explicitly on the surface of PfIE, and a highly immunogenic peptide derived from the commonly used peptide vaccines in malaria-endemic countries. The ligand is predicted to prevent the sequestration of PfIE, and the peptide is predicted to eliminate PfIE from circulation by the pre-existing vaccine-induced immunity. MAIN METHODS: The epitope identification from the vaccines and the analysis of physicochemical properties, antigenicity, allergenicity, and toxicity were performed using SVMTriP, ProtParam, VaxiJen, AllerTop, and ToxinPred servers, respectively. The high throughput virtual screening (HTVS) and drug-like properties analysis of natural compound ligands were carried out by Schrodinger-2021 software. The molecular dynamics simulations were performed through the WebGro server. KEY FINDINGS: HTVS revealed three bioactive natural ligands for PfEMP1 from (NPASS) database. Three super immunogenic peptides were identified from malaria-endemic countries' commonly used peptide vaccines. Finally, Nine PLCs were designed with different combinations of peptides and ligands with the suitable non-cleavable triazole linker. SIGNIFICANCE: Antimalarials have been losing efficacy in a time when malaria deaths in 2020 significantly increased than in 2019. In this scenario, further research on the designed PLCs may offer some innovative immune therapeutics for complicated malaria with minimum possibilities of drug resistance.