Molecular dynamic simulations to investigate the structural impact of known drug resistance mutations on HIV-1C Integrase-Dolutegravir binding

Analysis of raltegravir analogs to enhance inhibitory efficiency against HIV integrase

This article addresses the improvement of the efficacy of anti-integrase enzyme drugs for the AIDS virus, especially using the drug Raltegravir and its 21 analogs. In this research, Hartree-Fock and Density Functional Theory methods have been employed for the design and optimization of new drug candidates. These methods are used to enhance the accuracy and reactivity of the drugs. Additionally, docking is used to investigate the interactions between the drug and the target and evaluate binding energies. Molecular dynamics simulation is utilized to validate binding results. Computational results indicate that the designed analogs exhibit higher reactivity. In molecular docking calculations, RAL5 and RAL21 show the best binding energies of -10.10 and - 10.92 kcal/mol, respectively, indicating their superior efficiency. The analysis of inhibitor potentials against the HIV-1 integrase enzyme through molecular dynamics simulation reveals that RAL5 has strong inhibitory potential for treating viral diseases. These findings contribute to the promotion of therapeutic intervention methods in this field.

The coevolutionary landscape of drug resistance in epidermal growth factor receptor: A cancer perspective

Epidermal growth factor receptor (EGFR), the first receptor tyrosine kinase, plays a critical role in neoplastic metastasis, angiogenesis, tumor invasion, and apoptosis, making it a prime target for treating non-small cell lung cancer (NSCLC). Although tyrosine kinase inhibitors (TKIs) have shown high efficacy and promise for cancer patients, resistance to these drugs often develops within a year due to alterations. The present study investigates the compensatory alterations in EGFR to understand the evolutionary process behind drug resistance. Our findings reveal that coevolutionary alterations expand the drug-binding pocket; leading to reduced drug efficacy and suggested that such changes significantly influence the structural adaptation of the EGFR against these drugs. Analysis such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), solvent accessible surface area (SASA), principal component analysis (PCA), and free energy landscape (FEL) demonstrated that structures of wild EGFR docked with gefitinib are more stable which suggests its susceptibility towards drug than coevolution dependent double mutant. The findings were supported by MM-GBSA binding affinity analysis. The insights from this study highlighted the evolution-induced structural changes which contributes to drug resistance in EGFR and may certainly aid in designing more effective drugs.

Computational approaches: atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted anti-tubercular agents

Tuberculosis (TB) has become the biggest threat to human society because of the rapid rise in resistance to the causative bacteria Mycobacterium tuberculosis (MTB) against the available anti-tubercular drugs. There is an urgent need to design new multi-targeted anti-tubercular agents to overcome the resistance species of MTB through computational design tools. With this aim in mind, we performed a combination of atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), six-point pharmacophore (AHHRRR), and molecular docking analysis on a series of fifty-eight anti-tubercular agents. The created QSAR model had a R2 value of 0.9521, a Q2 value of 0.8589, and a Pearson r-factor of 0.8988, all of which are statistically significant. This means that the model was effective at making predictions. We performed the molecular docking study for the data set of compounds with the two important anti-tubercular target proteins, Enoyl acyl carrier protein reductase (InhA) (PDBID: 2NSD) and Decaprenyl phosphoryl-β-D-Ribose 20-epimerase (DprE1) (PDBID: 4FDO). We used the similarity search principle to do virtual screening on 237 compounds from the PubChem database in order to find strong anti-tubercular agents that act against multiple targets. The screened compound, MK3, showed the highest docking score of -9.2 and -8.3 kJ/mol towards both the target proteins InhA and DprE1, which were picked for a 100 ns molecular-dynamic simulation study using GROMACS. The data showed that the compound MK3 was thermodynamically stable and effectively bound to both target proteins in their active binding pockets without much movement. The analysis of the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), and energy gap predicts the molecular reactivity and stability of the identified molecule. Based on the result of the above studies, the proposed compound MK3 can be successfully used for the development of a novel multi-targeted anti-tubercular agent with high binding affinity and favourable ADME-T properties.

Atomistic simulations reveal impacts of missense mutations on the structure and function of SynGAP1

De novo mutations in the synaptic GTPase activating protein (SynGAP) are associated with neurological disorders like intellectual disability, epilepsy, and autism. SynGAP is also implicated in Alzheimer's disease and cancer. Although pathogenic variants are highly penetrant in neurodevelopmental conditions, a substantial number of them are caused by missense mutations that are difficult to diagnose. Hence, in silico mutagenesis was performed for probing the missense effects within the N-terminal region of SynGAP structure. Through extensive molecular dynamics simulations, encompassing three 150-ns replicates for 211 variants, the impact of missense mutations on the protein fold was assessed. The effect of the mutations on the folding stability was also quantitatively assessed using free energy calculations. The mutations were categorized as potentially pathogenic or benign based on their structural impacts. Finally, the study introduces wild-type-SynGAP in complex with RasGTPase at the inner membrane, while considering the potential effects of mutations on these key interactions. This study provides structural perspective to the clinical assessment of SynGAP missense variants and lays the foundation for future structure-based drug discovery.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Repurposing immune boosting and anti-viral efficacy of Parkia bioactive entities as multi-target directed therapeutic approach for SARS-CoV-2: exploration of lead drugs by drug likeness, molecular docking and molecular dynamics simulation methods

The COVID-19 pandemic has caused adverse health (severe respiratory, enteric and systemic infections) and environmental impacts that have threatened public health and the economy worldwide. Drug repurposing and small molecule multi-target directed herbal medicine therapeutic approaches are the most appropriate exploration strategies for SARS-CoV-2 drug discovery. This study identified potential multi-target-directed Parkia bioactive entities against SARS-CoV-2 receptors (S-protein, ACE2, TMPRSS2, RBD/ACE2, RdRp, MPro, and PLPro) using ADMET, drug-likeness, molecular docking (AutoDock, FireDock and HDOCK), molecular dynamics simulation and MM-PBSA tools. One thousand Parkia bioactive entities were screened out by virtual screening and forty-five bioactive phytomolecules were selected based on favorable binding affinity and acceptable pharmacokinetic and pharmacodynamics properties. The binding affinity values of Parkia phyto-ligands (AutoDock: -6.00--10.40 kcal/mol; FireDock: -31.00--62.02 kcal/mol; and HDOCK: -150.0--294.93 kcal/mol) were observed to be higher than the reference antiviral drugs (AutoDock: -5.90--9.10 kcal/mol; FireDock: -35.64--59.35 kcal/mol; and HDOCK: -132.82--211.87 kcal/mol), suggesting a potent modulatory action of Parkia bioactive entities against the SARS-CoV-2. Didymin, rutin, epigallocatechin gallate, epicatechin-3-0-gallate, hyperin, ursolic acid, lupeol, stigmasta-5,24(28)-diene-3-ol, ellagic acid, apigenin, stigmasterol, and campesterol strongly bound with the multiple targets of the SARS-CoV-2 receptors, inhibiting viral entry, attachment, binding, replication, transcription, maturation, packaging and spread. Furthermore, ACE2, TMPRSS2, and MPro receptors possess significant molecular dynamic properties, including stability, compactness, flexibility and total binding energy. Residues GLU-589, and LEU-95 of ACE2, GLN-350, HIS-186, and ASP-257 of TMPRSS2, and GLU-14, MET-49, and GLN-189 of MPro receptors contributed to the formation of hydrogen bonds and binding interactions, playing vital roles in inhibiting the activity of the receptors. Promising results were achieved by developing multi-targeted antiviral Parkia bioactive entities as lead and prospective candidates under a small molecule strategy against SARS-CoV-2 pathogenesis. The antiviral activity of Parkia bioactive entities needs to be further validated by pre-clinical and clinical trials.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA.Communicated by Ramaswamy H. Sarma.

Protegrin-2, a potential inhibitor for targeting SARS-CoV-2 main protease Mpro

Background

SARS-CoV-2 variants continue to spread throughout the world and cause waves of COVID-19 infections. It is important to find effective antiviral drugs to combat SARS-CoV-2 and its variants. The main protease (Mpro) of SARS-CoV-2 is a promising therapeutic target due to its crucial role in viral replication and its conservation in all the variants. Therefore, the aim of this work was to identify an effective inhibitor of Mpro.

Methods

We studied around 200 antimicrobial peptides using in silico methods including molecular docking and allergenicity and toxicity prediction. One selected antiviral peptide was studied experimentally using a Bioluminescence Resonance Energy Transfer (BRET)-based Mpro biosensor, which reports Mpro activity through a decrease in energy transfer.

Results

Molecular docking identified one natural antimicrobial peptide, Protegrin-2, with high binding affinity and stable interactions with Mpro allosteric residues. Furthermore, free energy calculations and molecular dynamics simulation illustrated a high affinity interaction between the two. We also determined the impact of the binding of Protegrin-2 to Mpro using a BRET-based assay, showing that it inhibits the proteolytic cleavage activity of Mpro.

Conclusions

Our in silico and experimental studies identified Protegrin-2 as a potent inhibitor of Mpro that could be pursued further towards drug development against COVID-19 infection.

Laterosporulin25: A probiotically produced, novel defensin-like bacteriocin and its immunogenic properties

Although multiple vaccines have been developed against infectious diseases, the rapid emergence of new pathogens develops an urgent need for novel strategies to combat infectious diseases. Antimicrobial peptides (AMPs) are excellent agents to fight against infectious diseases having unique multiple mechanisms of action against various pathogens. Apart from the direct applications, AMPs can also be developed as subunit vaccines or could be used as a highly immunogenic carrier protein with highly antigenic but non-immunogenic antigens. Here in the present study, we have identified a novel defensin-like bacteriocin, laterosporulin25 (LS25) upon genome mining of Brevibacillus laterosporus DSM25, a probiotic bacterial strain. By using immunoinformatic tools, we have studied the immunogenic and physiochemical properties of LS25. LS25 is characterized as defensin-like bacteriocin, having 51 amino acids and a molecular weight of 5862.7 Da. The modeled tertiary structure of LS25 is docked with TLR3 and TLR4-MD2 complex to confirm the facilitation of induced immune response that is further validated using molecular dynamics simulations and In-silico immune stimulations. Overall, detailed immunoinformatics analysis suggested LS25 as a potential candidate to be used as an adjuvant or carrier protein for subunit vaccine development, however, further in-vitro and in-vivo experiments are essential to validate its potential.

A computational overview of integrase strand transfer inhibitors (INSTIs) against emerging and evolving drug-resistant HIV-1 integrase mutants

AIDS (Acquired immunodeficiency syndrome) is one of the chronic and potentially life-threatening epidemics across the world. Hitherto, the non-existence of definitive drugs that could completely cure the Human immunodeficiency virus (HIV) implies an urgent necessity for the discovery of novel anti-HIV agents. Since integration is the most crucial stage in retroviral replication, hindering it can inhibit overall viral transmission. The 5 FDA-approved integrase inhibitors were computationally investigated, especially owing to the rising multiple mutations against their susceptibility. This comparative study will open new possibilities to guide the rational design of novel lead compounds for antiretroviral therapies (ARTs), more specifically the structure-based design of novel Integrase strand transfer inhibitors (INSTIs) that may possess a better resistance profile than present drugs. Further, we have discussed potent anti-HIV natural compounds and their interactions as an alternative approach, recommending the urgent need to tap into the rich vein of indigenous knowledge for reverse pharmacology. Moreover, herein, we discuss existing evidence that might change in the near future.

Molecular dynamics study of tropical calcific pancreatitis (TCP) associated calcium-sensing receptor single nucleotide variation

Tropical Calcific Pancreatitis (TCP) is a chronic non-alcoholic pancreatitis characterised by extensive calcification. The disease usually appears at a younger age and is more common in tropical regions. This disease’s progression can lead to pancreatic diabetes, which can subsequently lead to pancreatic cancer. The CASR gene encodes a calcium-sensing receptor (CaSR), which is a GPCR protein of class C. It is expressed in the islets of Langerhans, the parathyroid gland, and other tissues. It primarily detects small gradients in circulating calcium concentrations and couples this information to intracellular signalling, which helps to regulate PTH (parathyroid hormone) secretion and mineral ion homeostasis. From co-leading insulin release, CaSR modulates ductal HCO₃₋ secretion, Ca²⁺ concentration, cell-cell communication, β-cell proliferation, and intracellular Ca²⁺ release. In pancreatic cancer, the CaSR limits cell proliferation. TCP-related four novel missense mutations P163R, I427S, D433H and V477A, found in CaSR extracellular domain (ECD) protein, which were reported in the mutTCPdb Database (https://lms.snu.edu.in/mutTCPDB/index.php). P163R mutation occurs in ligand-binding domain 1 (LBD-1) of the CaSR ECD. To investigate the influence of these variations on protein function and structural activity multiple in-silico prediction techniques such as SIFT, PolyPhen, CADD scores, and other methods have been utilized. A 500 ns molecular dynamic simulation was performed on the CaSR ECD crystal structure and the corresponding mutated models. Furthermore, Principal Component Analysis (PCA) and Essential Dynamics analysis were used to forecast collective motions, thermodynamic stabilities, and the critical subspace crucial to CaSR functions. The results of molecular dynamic simulations showed that the mutations P163R, I427S, D433H, and V477A caused conformational changes and decreased the stability of protein structures. This study also demonstrates the significance of TCP associated mutations. As a result of our findings, we hypothesised that the investigated mutations may have an effect on the protein’s structure and ability to interact with other molecules, which may be related to the protein’s functional impairment.

Recent Advances in Computer-aided Antiviral Drug Design Targeting HIV-1 Integrase and Reverse Transcriptase Associated Ribonuclease H

Acquired immunodeficiency syndrome (AIDS) has been a chronic, life-threatening disease for a long time. However, a broad range of antiretroviral drug regimens are applicable for the successful suppression of virus replication in human immunodeficiency virus type 1 (HIV-1) infected people. The mutation-induced drug resistance problems during the treatment of AIDS forced people to continuously look for new antiviral agents. HIV-1 integrase (IN) and reverse transcriptase associated ribonuclease (RT-RNase H), two pivotal enzymes in HIV-1 replication progress, has gain popularity as drug-able targets for designing novel HIV-1 antiviral drugs. During the development of HIV-1 IN and/or RT-RNase H inhibitors, computer-aided drug design (CADD), including homology modeling, pharmacophore, docking, molecular dynamics (MD) simulation, and binding free energy calculation, represents a significant tool to accelerate the discovery of new drug candidates and reduce costs in antiviral drug development. In this review, we summarized the recent advances in the design of single-and dual-target inhibitors against HIV-1 IN or/and RT-RNase H as well as the prediction of mutation-induced drug resistance based on computational methods. We highlighted the results of the reported literature and proposed some perspectives on the design of novel and more effective antiviral drugs in the future.

Interaction analysis of statistically enriched mutations identified in Cameroon recombinant subtype CRF02_AG that can influence the development of Dolutegravir drug resistance mutations

BACKGROUND

The Integrase (IN) strand transfer inhibitor (INSTI), Dolutegravir (DTG), has been given the green light to form part of first-line combination antiretroviral therapy (cART) by the World Health Organization (WHO). DTG containing regimens have shown a high genetic barrier against HIV-1 isolates carrying specific resistance mutations when compared with other class of regimens.

METHODS

We evaluated the HIV-1 CRF02_AG IN gene sequences from Cameroon for the presence of resistance-associated mutations (RAMs) against INSTIs and naturally occurring polymorphisms (NOPs), using study sequences (n = 20) and (n = 287) sequences data derived from HIV Los Alamos National Laboratory database. The possible impact of NOPs on protein structure caused by HIV-1 CRF02_AG variations was addressed within the context of a 3D model of the HIV-1 IN complex and interaction analysis was performed using PyMol to validate DTG binding to the Wild type and seven mutant structures.

RESULTS

We observed 12.8% (37/287) sequences to contain RAMs, with only 1.0% (3/287) of the sequences having major INSTI RAMs: T66A, Q148H, R263K and N155H. Of these,11.8% (34/287) of the sequences contained five different IN accessory mutations; namely Q95K, T97A, G149A, E157Q and D232N. NOPs occurred at a frequency of 66% on the central core domain (CCD) position, 44% on the C-terminal domain (CTD) position and 35% of the N-terminal domain (NTD) position. The interaction analysis revealed that DTG bound to DNA, 2MG ions and DDE motif residues for T66A, T97A, Q148H, N155H and R263K comparable to the WT structure. Except for accessory mutant structure E157Q, only one MG contact was made with DTG, while DTG had no MG ion contacts and no DDE motif residue contacts for structure D232N.

CONCLUSIONS

Our analysis indicated that all RAM's that resulted in a change in the number of interactions with encompassing residues does not affect DTG binding, while accessory mutations E157Q and D232N could affect DTG binding leading to possible DTG resistance. However, further experimental validation is required to validate the in silico findings of our study.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

Pyrazinamide resistance of novel mutations in pncA and their dynamic behavior

Pyrazinamide (PZA) is one of the essential anti-mycobacterium drugs, active against non-replicating Mycobacterium tuberculosis (MTB) isolates. PZA is converted into its active state, called pyrazinoic acid (POA), by action of pncA encoding pyrazinamidase (PZase). In the majority of PZA-resistance isolates, pncA harbored mutations in the coding region. In our recent report, we detected a number of novel variants in PZA-resistance (PZAR) MTB isolates, whose resistance mechanisms were yet to be determined. Here we performed several analyses to unveil the PZAR mechanism of R123P, T76P, G150A, and H71R mutants (MTs) through molecular dynamics (MD) simulations. In brief, culture positive MTB isolates were subjected to PZA susceptibility tests using the WHO recommended concentration of PZA (100 μg ml-1). The PZAR samples were screened for mutations in pncA along sensitive isolates through polymerase chain reactions and sequencing. A large number of variants (GeneBank accession no. MH461111), including R123P, T76P, G150A, and H71R, have been spotted in more than 70% of isolates. However, the mechanism of PZAR for mutants (MTs) R123P, T76P, G150A, and H71R was unknown. For the MTs and native PZase structures (WT), thermodynamic properties were compared using molecular dynamics simulations for 100 ns. The MTs structural activity was compared to the WT. Folding effect and pocket volume variations have been detected when comparing between WT and MTs. Geometric matching further confirmed the effect of R123P, T76P, G150A, and H71R mutations on PZase dynamics, making them vulnerable for activating the pro-drug into POA. This study offers a better understanding for management of PZAR TB. The results may be used as alternative diagnostic tools to infer PZA resistance at a structural dynamics level.

Structural Comparison of Diverse HIV-1 Subtypes using Molecular Modelling and Docking Analyses of Integrase Inhibitors

The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral integrase (IN) enzyme catalyzes integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of integrase strand transfer inhibitors (INSTIs). We applied computational methods of molecular modelling and docking to analyze the effect of NOPs on the full-length IN structure and INSTI binding. We identified 13 NOPs within the Cameroonian-derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any differences in INSTI binding affinity. However, linear regression analysis revealed a positive correlation between the Ki and EC50 values for DTG and BIC as strong inhibitors of HIV-1 IN subtypes. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment-naïve populations. This study supports the use of second-generation INSTIs such as DTG and BIC as part of first-line combination antiretroviral therapy (cART) regimens, due to a stronger genetic barrier to the emergence of drug resistance.