Molecular Dynamics Free Energy Simulations Research Articles

Ab initio molecular dynamics simulation reveals the influence of entropy effect on Co@BEA zeolite-catalyzed dehydrogenation of ethane

The C–H bond activation in alkane dehydrogenation reactions is a key step in determining the reaction rate. To understand the impact of entropy, we performed ab initio static and molecular dynamics free energy simulations of ethane dehydrogenation over Co@BEA zeolite at different temperatures. AIMD simulations showed that a sharp decrease in free energy barrier as temperature increased. Our analysis of the temperature dependence of activation free energies uncovered an unusual entropic effect accompanying the reaction. The unique spatial structures around the Co active site at different temperatures influenced both the extent of charge transfer in the transition state and the arrangement of 3d orbital energy levels. We provided explanations consistent with the principles of thermodynamics and statistical physics. The insights gained at the atomic level have offered a fresh interpretation of the intricate long-range interplay between local chemical reactions and extensive chemical environments.

Comparative Assessment of Water Models in Protein-Glycan Interaction: Insights from Alchemical Free Energy Calculations and Molecular Dynamics Simulations.

Accurate computational simulations of protein-glycan dynamics are crucial for a comprehensive understanding of critical biological mechanisms, including host-pathogen interactions, immune system defenses, and intercellular communication. The accuracy of these simulations, including molecular dynamics (MD) simulation and alchemical free energy calculations, critically relies on the appropriate parameters, including the water model, because of the extensive hydrogen bonding with glycan hydroxyl groups. However, a systematic evaluation of water models' accuracy in simulating protein-glycan interaction at the molecular level is still lacking. In this study, we used full atomistic MD simulations and alchemical absolute binding free energy (ABFE) calculations to investigate the performance of five distinct water models in six protein-glycan complex systems. We evaluated water models' impact on structural dynamics and binding affinity through over 5.8 μs of simulation time per system. Our results reveal that most protein-glycan complexes are stable in the overall structural dynamics regardless of the water model used, while some show obvious fluctuations with specific water models. More importantly, we discover that the stability of the binding motif's conformation is dependent on the water model chosen when its residues form weak hydrogen bonds with the glycan. The water model also influences the conformational stability of the glycan in its bound state according to density functional theory (DFT) calculations. Using alchemical ABFE calculations, we find that the OPC water model exhibits exceptional consistency with experimental binding affinity data, whereas commonly used models such as TIP3P are less accurate. The findings demonstrate how different water models affect protein-glycan interactions and the accuracy of binding affinity calculations, which is crucial in developing therapeutic strategies targeting these interactions.

Structure-Based Discovery of Phytocompounds from Azadirachta indica as Potential Inhibitors of Thioredoxin Glutathione Reductase in Schistosoma mansoni.

Schistosomiasis, a parasitic disease caused by Schistosoma species such as S. haematobium, S. mansoni, and S. japonicum, poses a significant global health burden. The thioredoxin glutathione reductase (TGR) enzyme, crucial for maintaining the parasite's redox balance and preventing oxidative stress, has been identified as a promising target for anti-schistosomal drug development. This study aims to identify potential TGR inhibitors from Azadirachta indica phytochemicals using molecular modeling approaches. We screened 60 compounds derived from A. indica bark and leaves through molecular docking to assess their binding affinity, followed by the evaluation of binding-free energies for the most promising candidates. Drug-likeness and pharmacokinetic properties were assessed, and molecular dynamics simulations were conducted to explore the conformational stability of the protein-ligand complexes. Our findings revealed that several A. indica compounds exhibited significantly lower docking scores (up to -9.669 kcal/mol) compared to the standard drug praziquantel (-4.349 kcal/mol). Notably, Isorhamnetin, Isomargolonone, Nimbaflavone, Quercetin, and Nimbionol demonstrated strong interactions with TGR, although Isorhamnetin showed potential mutagenicity. Further binding free energy calculations and molecular dynamics simulations confirmed the stability of Isomargolonone, Nimbionol, and Quercetin as potential TGR inhibitors. In conclusion, these findings suggest that Isomargolonone, Nimbionol, and Quercetin warrant further experimental validation as promising candidates for anti-schistosomal therapy.

Optimal Molecular Design: Generative Active Learning Combining REINVENT with Precise Binding Free Energy Ranking Simulations.

Active learning (AL) is a specific instance of sequential experimental design and uses machine learning to intelligently choose the next data point or batch of molecular structures to be evaluated. In this sense, it closely mimics the iterative design-make-test-analysis cycle of laboratory experiments to find optimized compounds for a given design task. Here, we describe an AL protocol which combines generative molecular AI, using REINVENT, and physics-based absolute binding free energy molecular dynamics simulation, using ESMACS, to discover new ligands for two different target proteins, 3CLpro and TNKS2. We have deployed our generative active learning (GAL) protocol on Frontier, the world's only exa-scale machine. We show that the protocol can find higher-scoring molecules compared to the baseline, a surrogate ML docking model for 3CLpro and compounds with experimentally determined binding affinities for TNKS2. The ligands found are also chemically diverse and occupy a different chemical space than the baseline. We vary the batch sizes that are put forward for free energy assessment in each GAL cycle to assess the impact on their efficiency on the GAL protocol and recommend their optimal values in different scenarios. Overall, we demonstrate a powerful capability of the combination of physics-based and AI methods which yields effective chemical space sampling at an unprecedented scale and is of immediate and direct relevance to modern, data-driven drug discovery.

Advanced sampling simulations of coupled folding and binding of phage P22 N-peptide to boxB RNA

Protein-RNA interactions are crucially important for numerous cellular processes and often involve coupled folding and binding of peptide segments upon association. The Nut-utilization site (N)-protein of bacteriophages contains an N-terminal arginine-rich motif that undergoes such a folding transition upon binding to the boxB RNA hairpin loop target structure. Molecular dynamics free energy simulations were used to calculate the absolute binding free energy of the N-peptide of bacteriophage P22 in complex with the boxB RNA hairpin motif at different salt concentrations and using two different water force field models. We obtained good agreement with experiment also at different salt concentrations for the TIP4P-D water model that has a stabilizing effect on unfolded protein structures. It allowed us to estimate the free energy contribution resulting from restricting the molecules’ spatial and conformational freedom upon binding, which makes a large opposing contribution to binding. In a second set of umbrella sampling simulations to dissociate/associate the complex along a separation coordinate, we analyzed the onset of preorientation of the N-peptide and onset of structure formation relative to the RNA and its dependence on the salt concentration. Peptide orientation and conformational transitions are significantly coupled to the first contact formation between peptide and RNA. The initial contacts are mostly formed between peptide residues and the boxB hairpin loop nucleotides. A complete transition to an α-helical bound peptide conformation occurs only at a late stage of the binding process a few angstroms before the complexed state has been reached. However, the N-peptide orients also at distances beyond the contact distance such that the sizable positive charge points toward the RNA’s center-of-mass. Our result may have important implications for understanding protein- and peptide-RNA complex formation frequently involving coupled folding and association processes.

Unveiling Therapeutic Avenues for Crohn's Disease Management: Exploring Inhibitors for Adherent-Invasive Escherichia coli Propanediol Dehydratase.

Inflammatory Bowel Disease (IBD) encompasses a group of chronic disorders distinguished by inflammation of the gastrointestinal tract. Among these, Crohn's Disease (CD) stands out as a complex and impactful condition due to challenges for both diagnosis and management, making it a cynosure of research. In CD, there is the predominance of proinflammatory bacteria, including the Adherentinvasive Escherichia coli (AIEC) with virulence-associated metabolic enzyme Propanediol Dehydratase (pduC), which has been identified as a therapeutic target for the management of CD. Herein, molecular modeling techniques, including molecular docking, Molecular Mechanics with Generalized Born and Surface Area (MMGBSA), drug-likeness, and pharmacokinetics profiling, were utilized to probe the potentials of eighty antibacterial compounds to serve as inhibitors of pduC. The results of this study led to the identification of five compounds with promising potentials; the results of the molecular docking simulation revealed the compounds as possessing better binding affinities for the target compared to the standard drug (sulfasalazine), while Lipinski's rule of five-based assessment of their drug-likeness properties revealed them as potential oral drugs. MMGBSA free energy calculation and Molecular Dynamics (MD) simulation of the complexes formed a sequel to molecular docking, revealing the compounds as stable binders in the active site of the protein. Ultimately, the results of this study have revealed five compounds to possess the potential to serve as inhibitors of pduC of AIEC. However, experimental studies are still needed to validate the findings of this study.

Iso-mukaadial acetate and ursolic acid acetate bind to Plasmodium Falciparum heat shock protein 70: towards targeting parasite protein folding pathway.

Plasmodium falciparum is the most lethal malaria parasite. P. falciparum Hsp70 (PfHsp70) is an essential molecular chaperone (facilitates protein folding) and is deemed a prospective antimalarial drug target. The present study investigates the binding capabilities of select plant derivatives, iso-mukaadial acetate (IMA) and ursolic acid acetate (UAA), against P. falciparum using an in silico docking approach. The interaction between the ligands and PfHsp70 was evaluated using plasmon resonance (SPR) analysis. Molecular docking, binding free energy analysis and molecular dynamics simulations were conducted towards understanding the mechanisms by which the compounds bind to PfHsp70. The molecular docking results revealed ligand flexibilities, conformations and positions of key amino acid residues and protein-ligand interactions as crucial factors accounting for selective inhibition of Hsp70. The simulation results also suggest protein-ligand van der Waals forces as the driving force guiding the interaction of these compounds with PfHsp70. Of the two compounds, UAA and IMA bound to PfHsp70 within the micromolar range based on surface plasmon resonance (SPR) based binding assay. Our findings pave way for future rational design of new selective compounds targeting PfHsp70.

Computational analysis followed by invitro studies to explore cytokines (TNF-α, IL-6 and IL-1β) inhibition potential of the new natural molecule polonilignan.

Targeting pro-inflammatory cytokines and their production is found to be of therapeutic benefit for the regulation of inflammation in various chronic autoimmune diseases. Our continued efforts to discover small molecular-weight pro-inflammatory cytokine inhibitors resulted in identifying a novel natural lignan molecule named polonilignan, isolated from the culture broth extract of an endophytic fungus Penicillium polonicum. An in silico study (molecular docking, ADME predictions, binding free energy calculation and molecular dynamics simulation) of the polonilignan over the pro-inflammatory cytokines proteins TNF-α, IL-6 and IL-1β was performed using Schrodinger LLC software to understand the binding interactions, drug-like properties, and stability of the ligand-protein complex. Further, in-vitro testing of inhibition of TNF-α, IL-6 and IL-1β by polonilignan was carried out using ELISA and RT-PCR on LPS-induced RAW 264.7 cell lines along with the testing of nitrite production effect (Griess assay) and cytotoxicity (MTT) analysis. Under the computational study, polonilignan revealed good docking scores, binding interactions, and stability under MDS and desirable in silico ADME results over the proteins TNF-α, IL-1β and IL-6. Poloniligan showed significant inhibition of IL-1β, IL-6 and TNF-α with IC50 values of 2.01 μM, 6.59 μM and 42.10 μM, respectively. Also, it reduced the translocation of the NF-κB subunit p65 to the nucleus (confocal microscopy). The mRNA expression levels of pro-inflammatory markers IL-1β, TNF-α and IL-6 levels were lowered significantly (p < .001) by the compound, and the diminution was higher with IL-1β. Further, the lignan was non-cytotoxic and effective in attenuating nitrite release (IC50 48.56 μM). Thus, polonilignan has been identified as a new pan-cytokine and NO inhibitor, it is recommended to optimise a method for the synthesis of this small molecular weight lignan and explore its pharmacokinetic characteristics, toxicity and therapeutic effect under various chronic inflammatory disease models.

Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability.

Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.

Identification of echinoderm metabolites as potential inhibitors targeting wild-type and mutant forms of Escherichia coli RNA polymerase (RpoB) for tuberculosis treatment.

Tuberculosis (TB) remains a critical global health challenge, with the emergence of drug-resistant strains heightening concerns. The development of effective drugs targeting both wild-type (WT) and mutant Escherichia coli RNA polymerase β subunit (RpoB) is crucial for global TB control, aiming to alleviate TB incidence, mortality, and transmission. This study employs molecular docking and ADMET analyses to screen echinoderm metabolites for their potential inhibition of Escherichia coli RNA polymerase, focusing on wild-type and mutant RpoB variants associated with TB drug resistance. The evaluation of docking results using the glide gscore led to the selection of the top 10 compounds for each protein receptor. Notably, CMNPD2176 demonstrated the highest binding affinity against wild-type RpoB, CMNPD13873 against RpoB D516V mutant, CMNPD2177 against RpoB H526Y mutant, and CMNPD11620 against RpoB S531L mutant. ADMET screening confirmed the therapeutic potential of these selected compounds. Additionally, MM-GBSA binding free energy calculations and molecular dynamics simulations provided further support for the docking investigations. While the results suggest these compounds could be viable for tuberculosis treatment, it is crucial to note that further in-vitro research is essential for the transition from prospective inhibitors to clinical drugs.

Binding Modes of Xanthine-Derived Selective Allosteric Site Inhibitors of MTHFD2.

Methylenetetrahydrofolate dehydrogenase (MTHFD2) is a mitochondrial enzyme involved in 1 C metabolism that is upregulated in various cancer cells, but absent in normal proliferating cells. Xanthine derivatives are the first selective inhibitors of MTHFD2 which bind to its allosteric site. Xanthine derivatives (including the co-crystallized inhibitors) were herein interrogated by molecular/induced-fit docking, MM-GBSA binding free energy calculations and molecular dynamics simulations in both MTHFD2 and MTHFD1 (a close homolog expressed in healthy cells). The gained insights from our in silico protocol allowed us to study binding mode, key protein-ligand interactions and dynamic movement of the allosteric inhibitors, correlating with their experimental binding affinities, biological activities and selectivity for MTHFD2. The reported conformational changes with MTHFD2 upon binding of xanthine derivatives were furthermore evaluated and confirmed by RMSF analyses of the MD simulation trajectories. The results reported herein are expected to benefit in the rational design of selective MTHFD2 allosteric inhibitors.

Identification of novel potential hepatitis E virus inhibitors as seen from molecular docking, free energy landscape and molecular dynamics simulation studies

ABSTRACT Hepatitis E virus (HEV), a non-enveloped and globular protein, is the primary cause of acute hepatitis. The structural capsid protein encoded by HEV is the open-reading frame 2 gene. However, there are presently no efficient and targeted therapies for HEV infections. This research aims to screen out the effective bioactive compounds from Paederia foetida, which may be novel potential inhibitors of Hepatitis E. Despite various research in recent decades, the molecular picture of the interaction between the Hepatitis E virus and iridoid glycosides from Paederia foetida remains vague. We performed in silico ADMET predictions of the phytochemicals of Paederia foetida, and the findings revealed a reasonably good ADMET profile for the twenty chosen phytochemicals. Herein, the twenty phytochemicals were submitted to an analysis of molecular docking studies with the HEV protein and the analysis suggested that asperuloside, ellagic acid, friedlin, lupeol and paederoside as the most potential HEV inhibitors among the selected phytochemicals. Subsequently, the stability of these phytochemical complexes was studied by using molecular dynamic (MD) simulation of 100 ns. Based on our computational study, lupeol and paederoside phytochemicals obtained from the paederia foetida plant may be used as potential drug candidates for the inhibition of hepatitis E.

In silico molecular modeling and simulations of black tea theaflavins revealed theaflavin-3’-gallate as putative liver X receptor-beta agonist

The low constitutive activation of Liver X receptor, an endogenous nuclear receptor with two subtypes (α and β), is a condition lying at the crossroad of cancer and cardiovascular disease. Both natural and synthetic Liver X receptor agonists have reportedly shown remarkable antiproliferative and atheroprotective effects but the repeated doses of its synthetic ones are also paradoxically associated with hyperlipidaemic effects and neurotoxicity, though attributed to the alpha subtype. This highlights the need for novel, safe, and potent LXR-beta-selective agonists. Hypocholesterolaemic effects of black theaflavins have been widely reported, but data on the exact theaflavin compound (s) responsible for these effects is currently lacking. Neither is information on the possible modulatory effects of the compound (s) on LXR-beta nor its possible implications in the context of drug development for cardiovascular diseases and cancers is explored. On this account, we investigated the potential interaction of four main theaflavin monomers (TF1, TF2A, TF2B & TF3) with human LXR-beta through robust computational modelling that entails molecular docking, free energy calculations and molecular dynamics simulations. The ligands were further profiled (in silico) for absorption, distribution, metabolism, excretion, and toxicological properties. Our result revealed theaflavin TF2B as a putative LXR-beta agonist, possibly responsible for the widely observed hypocholesterolaemic effect in black tea. This finding, while encouraging, needs to be experimentally verified in wet studies. Communicated by Ramaswamy H. Sarma

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

BackgroundSARS-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. MethodsWe 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. ResultsMolecular 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. ConclusionsOur 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.

Evolutionary divergence in the conformational landscapes of tyrosine vs serine/threonine kinases.

Inactive conformations of protein kinase catalytic domains where the DFG motif has a "DFG-out" orientation and the activation loop is folded present a druggable binding pocket that is targeted by FDA-approved 'type-II inhibitors' in the treatment of cancers. Tyrosine kinases (TKs) typically show strong binding affinity with a wide spectrum of type-II inhibitors while serine/threonine kinases (STKs) usually bind more weakly which we suggest here is due to differences in the folded to extended conformational equilibrium of the activation loop between TKs vs. STKs. To investigate this, we use sequence covariation analysis with a Potts Hamiltonian statistical energy model to guide absolute binding free-energy molecular dynamics simulations of 74 protein-ligand complexes. Using the calculated binding free energies together with experimental values, we estimated free-energy costs for the large-scale (~17-20 Å) conformational change of the activation loop by an indirect approach, circumventing the very challenging problem of simulating the conformational change directly. We also used the Potts statistical potential to thread large sequence ensembles over active and inactive kinase states. The structure-based and sequence-based analyses are consistent; together they suggest TKs evolved to have free-energy penalties for the classical 'folded activation loop' DFG-out conformation relative to the active conformation, that is, on average, 4-6 kcal/mol smaller than the corresponding values for STKs. Potts statistical energy analysis suggests a molecular basis for this observation, wherein the activation loops of TKs are more weakly 'anchored' against the catalytic loop motif in the active conformation and form more stable substrate-mimicking interactions in the inactive conformation. These results provide insights into the molecular basis for the divergent functional properties of TKs and STKs, and have pharmacological implications for the target selectivity of type-II inhibitors.

Computational Predictions of the Hydrolysis of 2,4,6-Trinitrotoluene (TNT) and 2,4-Dinitroanisole (DNAN).

Hydrolysis is a common transformation reaction that can affect the environmental fate of many organic compounds. In this study, three proposed mechanisms of alkaline hydrolysis of 2,4,6-trinitrotoluene (TNT) and 2,4-dinitroaniline (DNAN) were investigated with plane-wave density functional theory (DFT) combined with ab initio and classical molecular dynamics (AIMD/MM) free energy simulations, Gaussian basis set DFT calculations, and correlated molecular orbital theory calculations. Most of the computations in this study were carried out using the Arrows web-based tools. For each mechanism, Meisenheimer complex formation, nucleophilic aromatic substitution, and proton abstraction reaction energies and activation barriers were calculated for the reaction at each relevant site. For TNT, it was found that the most kinetically favorable first hydrolysis steps involve Meisenheimer complex formation by attachment of OH- at the C1 and C3 arene carbons and proton abstraction from the methyl group. The nucleophilic aromatic substitution reactions at the C2 and C4 arene carbons were found to be thermodynamically favorable. However, the calculated activation barriers were slightly lower than in previous studies, but still found to be ΔG‡ ≈ 18 kcal/mol using PBE0 AIMD/MM free energy simulations, suggesting that the reactions are not kinetically significant. For DNAN, the barriers of nucleophilic aromatic substitution were even greater (ΔG‡ > 29 kcal/mol PBE0 AIMD/MM). The most favorable hydrolysis reaction for DNAN was found to be a two-step process in which the hydroxyl first attacks the C1 carbon to form a Meisenheimer complex at the C1 arene carbon C1-(OCH3)OH-, and subsequently, the methoxy anion (-OCH3) at the C1 arene carbon dissociates and the proton shuttles from the C1-OH to the dissociated methoxy group, resulting in methanol and an aryloxy anion.

Potential dual inhibition of SE and CYP51 by eugenol conferring inhibition of Candida albicans: Computationally curated study with experimental validation

Ergosterol is the key sterol component in the cell membrane of fungi including moulds and yeasts. Any decrease in the levels of ergosterol in the cell membrane of fungi render them venerable to cell membrane damage and even its death. Majority of antifungal drug targets the key enzymes involved in ergosterol biosynthesis pathway. The biochemical pathway for the synthesis of Ergosterol is a complex one, though the reactions carried by Squalene Epoxidase (SE) and 14α-demethylase (CYP51- a member of Cytochrome P450 family) serves to the key rate limiting reactions that can impact the overall production of Ergosterol. Allylamines class of antifungal drug target SE while Azoles target the CYP51. Currently advancement in the drug development is focused to introduce newer drugs that can simultaneously inhibit both this rate limiting enzymes. However, natural compounds established to possess antifungal activity but the major loophole about their understanding lies in the fact that their mode of action are severely unstudied. One such well-established antifungal natural phytochemical is Eugenol, and in current manuscript we investigated its efficacy to interact with both, SE and CYP51 of Candida albicans using molecular Docking, Free energy change calculations and Molecular Dynamics (MD) simulation, showing promising outcomes. For experimental studies, terbinafine, clotrimazole and eugenol showed 4 μg/ml, 2 μg/ml, and 512 μg/ml MIC90 values, respectively against C. albicans and also showed reduction in Ergosterol production at sub-MIC levels. The obtained result indicates the involvement of eugenol in the inhibition of enzymes require in the ergosterol biosynthesis pathway.

Discovery of Novel HIV Protease Inhibitors Using Modern Computational Techniques.

The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern. With the new HIV incidence, the emergence of multi-drug resistance and the untoward side effects of currently used anti-HIV drugs, there is an urgent need to discover more efficient anti-HIV drugs. Modern computational tools have played vital roles in facilitating the drug discovery process. This research focuses on a pharmacophore-based similarity search to screen 111,566,735 unique compounds in the PubChem database to discover novel HIV-1 protease inhibitors (PIs). We used an in silico approach involving a 3D-similarity search, physicochemical and ADMET evaluations, HIV protease-inhibitor prediction (IC50/percent inhibition), rigid receptor–molecular docking studies, binding free energy calculations and molecular dynamics (MD) simulations. The 10 FDA-approved HIV PIs (saquinavir, lopinavir, ritonavir, amprenavir, fosamprenavir, atazanavir, nelfinavir, darunavir, tipranavir and indinavir) were used as reference. The in silico analysis revealed that fourteen out of the twenty-eight selected optimized hit molecules were within the acceptable range of all the parameters investigated. The hit molecules demonstrated significant binding affinity to the HIV protease (PR) when compared to the reference drugs. The important amino acid residues involved in hydrogen bonding and п-п stacked interactions include ASP25, GLY27, ASP29, ASP30 and ILE50. These interactions help to stabilize the optimized hit molecules in the active binding site of the HIV-1 PR (PDB ID: 2Q5K). HPS/002 and HPS/004 have been found to be most promising in terms of IC50/percent inhibition (90.15%) of HIV-1 PR, in addition to their drug metabolism and safety profile. These hit candidates should be investigated further as possible HIV-1 PIs with improved efficacy and low toxicity through in vitro experiments and clinical trial investigations.

Molecular basis of Toxoplasma gondii oryzalin resistance from a novel α-tubulin binding site model

Oryzalin (ORY) is a dinitroaniline derivative that inhibits the microtubule polymerization in plants and parasitic protozoa by selectively binding to the α-tubulin subunit. This herbicidal agent exhibits good antiprotozoal activity against major human parasites, such as Toxoplasma gondii (toxoplasmosis), Leishmania mexicana (leishmaniasis), and Plasmodium falciparum (malaria). Previous chemical mutagenesis assays on T. gondii α-tubulin (TgAT) have identified key mutations that lead to ORY resistance. Herein, we employed alchemical free energy methods and molecular dynamics simulations to determine if the ORY resistance mutations either decrease the TgAT's affinity of the compound or increase the protein stability. Our results here suggest that L136F and V202F mutations significantly decrease the affinity of ORY to TgAT, while T239I and V252L mutations diminish TgAT's flexibility. On the other hand, protein stability predictors determined that R243S mutation reduces TgAT stability due to the loss of its salt bridge interaction with E27. Interestingly, molecular dynamics simulations confirm that the loss of this key interaction leads to ORY binding site closure. Our study provides a better insight into the TgAT-ORY interaction, further supporting our recently proposed ORY-binding site.

Effect of Leu/Val Mutation on the Energetics of Antimicrobial Peptide:Micelle Binding.

Recently, we had reported a synthetic positively charged leucine-rich 14-residue-long antimicrobial peptide (AMP, LL-14: NH3+-LKWLKKLLKWLKKL-CONH2), which was highly active and cytotoxic relative to its valine analogue (VV-14). However, the thermodynamics underlying this differential toxicity and antimicrobial activity was unclear. Understanding the energetics of peptide binding to micelles (simplest membrane mimic, viz., SDS as a bacterial membrane and DPC as a eukaryotic membrane) and the effect of Leu → Val peptide mutations on the stability of the peptide:micelle complexes are of great academic interest and relevant for the rational design of potent and selective AMPs for therapeutic use. Here, we have reported the molecular dynamics free energy simulations that allowed us to quantitatively estimate the strength of peptide discrimination (based on single- or multiple-site Leu/Val mutations in LL-14) by membrane mimetic micelles (SDS and DPC) and decipher the energetics underlying peptide selectivity by micelles. The Leu-containing peptide (LL-14) was found to be preferred for micelle (SDS and DPC) binding relative to its Val analogues (single or multiple Val mutants). The strength of the preference depended on the position of the Leu/Val mutation in the peptide. Surprisingly, the N-terminal LL-14 single mutation (Leu → Val: L1V) was found to fine-tune the electrostatic interactions, resulting in the highest peptide selectivity (ΔΔG ∼ 8 kcal/mol for both SDS and DPC). However, the mechanism of L1V peptide selectivity was distinctly different for SDS and DPC micelles. SDS ensured high selectivity by disrupting the peptide:micelle salt bridge, whereas DPC desolvated the broken-peptide-backbone hydrogen bond in the V1 peptide:micelle complex. Mutations (Leu → Val) in the middle positions of the LL-14 (4th, 7th, 8th, and 11th) were disfavored by the micelles primarily due to the loss of peptide:micelle hydrophobic interactions. Peptides differing at the C-terminal (i.e., L14V) were recognized by SDS micelles (ΔΔG ∼ 4 kcal/mol) by altering peptide:micelle interactions. L14V mutation, on the other hand, did not play any role in the peptide:DPC binding, as no direct interactions between the C-terminal and DPC micelle were observed due to obvious electrostatic reasons. The strength of selectivity favoring LL-14 binding against VV-14 was found to be much higher for DPC micelles (ΔΔG ∼ 25 kcal/mol) relative to SDS micelles (ΔΔG ∼ 19 kcal/mol). The loss of the peptide:micelle hydrophobic contact in response to LL-14 → VV-14 mutation was found to be significantly larger for DPC relative to SDS micelles, resulting in higher discriminatory power for the former. Peptide:SDS salt bridges seemed to prevent the loss of peptide:micelle hydrophobic contact to some extent, leading to weaker selectivity for SDS micelles. High selectivity of DPC micelles provided an efficient mechanism for VV-14 dissociation from DPC micelles, whereas low-selectivity of SDS micelles ensured binding of both LL-14 and VV-14. To the best of our knowledge, this is the first study in which the experimental observations (antimicrobial activity and toxicity) between leucine-rich and valine-rich peptides have been explained by establishing a direct link between the energetics and structures.