Molecular dynamics and MM/GBSA-integrated protocol probing the correlation between biological activities and binding free energies of HIV-1 TAR RNA inhibitors

In silico structural elucidation of Nipah virus L protein and targeting RNA-dependent RNA polymerase domain by nucleoside analogs

The large (L) protein of Mononegavirales is a multi-domain protein that performs transcription and genome replication. One of the important domains in L is the RNA-dependent RNA polymerase (RdRp), a promising target for antiviral drugs. In this work, we employed rigorous computational comparative modeling to predict the structure of L protein of Nipah virus (NiV). The RdRp domain was targeted by a panel of nucleotide analogs, previously reported to inhibit different viral RNA polymerases, using molecular docking. Best binder compounds were subjected to molecular dynamics simulation to validate their binding. Molecular mechanics/generalized-born surface area (MM/GBSA) calculations estimated the binding free energy. The predicted model of NiV L has an excellent quality as judged by physics- and knowledge-based validation tests. Galidesivir, AT-9010 and Norov-29 scored the top nucleotide analogs to bind to the RdRp. Their binding free energies obtained by MM/GBSA (-31.01 ± 3.9 to -38.37 ± 4.8 kcal/mol) ranked Norov-29 as the best potential inhibitor. Purine nucleotide analogs are expected to harbor the scaffold for an effective drug against NiV. Finally, this study is expected to provide a start point for medicinal chemistry and drug discovery campaigns toward identification of effective chemotherapeutic agent(s) against NiV.Communicated by Ramaswamy H. Sarma.

Computational identification of drug-like marine natural products as potential RNA polymerase inhibitors against Nipah virus

Nipah virus (NiV) has been an alarming threat to human populations in southern Asia for more than a decade. It is one of the most deadly viruses in the Mononegavirales order. Despite its high mortality rate and virulence, no chemotherapeutic agent or vaccine is publicly available. Hence, this work was conducted to computationally screen marine natural products database for drug-like potential inhibitors for the viral RNA-dependent RNA polymerase (RdRp). The structural model was subjected to molecular dynamics (MD) simulation to obtain the native ensemble of the protein. The CMNPDB dataset of marine natural products was filtered to retain only compounds following Lipinski's five rules. The molecules were energy minimized and docked into different conformers of the RdRp using AutoDock Vina. The best 35 molecules were rescored by GNINA, a deep learning-based docking software. The resulting nine compounds were evaluated for their pharmacokinetic profiles and medicinal chemistry properties. The best five compounds were subjected to MD simulation for 100 ns, followed by binding free energy estimation via Molecular Mechanics/ Generalized Born Surface Area (MM/GBSA) calculations. The results showed remarkable behavior of five hits as inferred by stable binding pose and orientation to block the exit channel of RNA synthesis products in the RdRp cavity. These hits are promising starting materials for in vitro validation and structural modifications to enhance the pharmacokinetic and medicinal chemistry properties for developing antiviral lead compounds.

Exploration of natural product database for the identification of potent inhibitor against IDH2 mutational variants for glioma therapy

Mutation in isocitrate dehydrogenase 2 (mIDH2) is an oncogenic driver prevalently reported in various cancer types including gliomas. To date, enasidenib is the only FDA-approved drug widely used as a mIDH2 (R140Q) inhibitor. However, dose-limiting toxicity and modest brain penetrating capability restrict its use as a plausible mIDH2 inhibitor. Furthermore, secondary site mutations (Q316E and I319M) were identified in patients with enasidenib treatments resulting in acquired therapeutic resistance. Hence, in the present investigation, we aimed to identify novel and potent drug-like compounds to overcome the existing drawbacks using an integrated in-silico strategy. A sum of 1574 natural compounds from the naturally occurring plant-based anti-cancerous compound activity target (NPACT) database was proclaimed and subjected to molecular docking. The binding affinities of the resultant natural compounds were rescored using MM-GBSA scoring functions. The resultant lead molecules were subjected to anticancer activity prediction using the machine-learning model. Furthermore, the toxicity and drug-likeliness of the lead compounds were investigated using ADMET properties. Eventually, the integrated in silico approach resulted in a lead molecule, namely squalene (NPACT00954) against mIDH2 protein. The screened compound was subjected to mutational analysis accomplishing second-site mutations. Interestingly, squalene exhibited appreciable binding affinity alongside good brain penetrating potential than enasidenib. Indeed, the reproducibility and significance of our results are examined by running 3 replicas of 100-ns simulations per system using the random initial velocities of the atoms generated by Maxwell distribution at a given temperature. Thus, we hypothesize from our results that further optimization of squalene could be beneficial for the treatment and management of glioma in the near future.

In-silico discovery of dual active molecule to restore synaptic wiring against autism spectrum disorder via HDAC2 and H3R inhibition

Metal-dependent histone deacetylases (HDACs) are essential epigenetic regulators; their molecular and pharmacological roles in medically critical diseases such as neuropsychiatric disorders, neurodegeneration, and cancer are being studied globally. HDAC2’s differential expression in the central nervous system makes it an appealing therapeutic target for chronic neurological diseases like autism spectrum disorder. In this study, we identified H3R inhibitor molecules that are computationally effective at binding to the HDAC2 metal-coordinated binding site. The study highlights the importance of pitolisant in screening the potential H3R inhibitors by using a hybrid workflow of ligand and receptor-based drug discovery. The screened lead compounds with PubChem SIDs 103179850, 103185945, and 103362074 show viable binding with HDAC2 in silico. The importance of ligand contacts with the Zn²⁺ ion in the HDAC2 catalytic site is also discussed and investigated for a significant role in enzyme inhibition. The proposed H3R inhibitors 103179850, 103185945, and 103362074 are estimated as dual-active molecules to block the HDAC2-mediated deacetylation of the EAAT2 gene (SLC1A2) and H3R-mediated synaptic transmission irregularity and are, therefore, open for experimental validation.

RNA-ligand molecular docking: advances and challenges

With rapid advances in computer algorithms and hardware, fast and accurate virtual screening has led to a drastic acceleration in selecting potent small molecules as drug candidates. Computational modeling of RNA-small molecule interactions has become an indispensable tool for RNA-targeted drug discovery. The current models for RNA-ligand binding have mainly focused on the docking-and-scoring method. Accurate docking and scoring should tackle four crucial problems: (1) conformational flexibility of ligand, (2) conformational flexibility of RNA, (3) efficient sampling of binding sites and binding poses, and (4) accurate scoring of different binding modes. Moreover, compared with the problem of protein-ligand docking, predicting ligand binding to RNA, a negatively charged polymer, is further complicated by additional effects such as metal ion effects. Thermodynamic models based on physics-based and knowledge-based scoring functions have shown highly encouraging success in predicting ligand binding poses and binding affinities. Recently, kinetic models for ligand binding have further suggested that including dissociation kinetics (residence time) in ligand docking would result in improved performance in estimating in vivo drug efficacy. More recently, the rise of deep-learning approaches has led to new tools for predicting RNA-small molecule binding. In this review, we present an overview of the recently developed computational methods for RNA-ligand docking and their advantages and disadvantages.

Integrated computational approach for in silico design of new purinyl pyridine derivatives as B-Raf kinase inhibitors

B-Raf is one among the most frequently mutating proto-oncogene which is associated with the serine/threonine Raf kinase family involved in the RAS-RAF-MEK-ERK pathway, which is the most deregulated pathway in human cancers. Mutant B-Raf ^V600E got an excellent scope for investigation in cancer as a potential therapeutic target. Formerly B-Raf^V600E is considered the molecular target for numerous antitumor compounds like purinyl pyridine and pyrimidine derivatives. In the current research work using molecular docking approach of Schrodinger Glide 5.6 version, ligand docking, pharmacophore-based virtual screening, binding free energy calculations of a series of 2-amino purinyl pyridine and pyrimidine derivatives were modeled, their docking values were predicted, that were considered to be potent against B-Raf ^V600E. A five-point hypothesis accompanied by a hydrogen bond acceptor(A), two hydrogen bond donors(D), and two aromatic rings (R) was built with a justifiable R² value of 0.91 and a Q² value of 0.64. Then by using Asinex Elite Synergy database, virtual screening was performed, and identified several potential hits. Subsequently, the molecules which had interactions with the target B-Raf kinase were determined by subjecting the obtained hits for SP and XP docking processes. Finally, for the top leads obtained, binding free energies were accomplished. About 16 new purinyl pyridine molecules were also designed. Almost nine molecules manifested crucial ligand interactions and binding free energies. At the outset, this research paved the way for us in spotting new molecules with B-Raf inhibitory activity, which can further be explored to design molecules with enhanced pharmacokinetic profiles.

Design, Synthesis, Anticancer Evaluation, and Molecular Docking Studies of Novel Benzoxazole Linked 1,3,4-Oxadiazoles

BACKGROUND

Cancer disease is making a serious concern globally. Global cancer occurrence is steadily increasing every year. There is always a persistent need to develop new anticancer drugs with reduced side effects or act synergistically with the existing chemotherapeutics.

OBJECTIVE

Benzoxazoles are fused bicyclic nitrogen and oxygen-containing heterocyclic compounds and are considered biologically privileged scaffolds. We designed a synthetic route to link the benzoxazoles with oxadiazoles resulting in a better pharmacophore for anticancer activity.

METHODS

A series of novel amide derivatives of benzoxazole linked 1,3,4-oxadiazoles (10a-j) were synthesized and characterized by ¹H NMR, ¹³C NMR, and mass spectroscopic techniques. The biological properties of the compounds were screened in vitro against four different tumor cell lines.

RESULTS

The results suggest that the compound 10b having 3,4,5-trimethoxy substitution on the phenyl ring exhibited potent anticancer activity in three cell lines (A549 = 0.13 ± 0.014 µM, MCF-7 = 0.10 ± 0.013 µM and HT-29 = 0.22 ± 0.017 µM). Notably, among the synthesized derivatives, compounds 10b, 10c, 10f, 10g, and 10i exhibited potent anticancer activity than the control IC₅₀ in the range of 0.11 ± 0.02 to 0.93 ± 0.034 µM. Molecular docking simulation results showed compounds were stabilized by hydrogen bond and π-π interactions with the protein.

CONCLUSION

The molecules showed comparable binding affinities with standard Combretastatin-A4. The present research work is preliminary and needs further studies to take the synthesized compounds to the next level in the cancer research field.

Discovery of novel dual adenosine A1/A2A receptor antagonists using deep learning, pharmacophore modeling and molecular docking

Adenosine receptors (ARs) have been demonstrated to be potential therapeutic targets against Parkinson's disease (PD). In the present study, we describe a multistage virtual screening approach that identifies dual adenosine A1 and A2A receptor antagonists using deep learning, pharmacophore models, and molecular docking methods. Nineteen hits from the ChemDiv library containing 1,178,506 compounds were selected and further tested by in vitro assays (cAMP functional assay and radioligand binding assay); of these hits, two compounds (C8 and C9) with 1,2,4-triazole scaffolds possessing the most potent binding affinity and antagonistic activity for A1/A2A ARs at the nanomolar level (pKi of 7.16-7.49 and pIC50 of 6.31-6.78) were identified. Further molecular dynamics (MD) simulations suggested similarly strong binding interactions of the complexes between the A1/A2A ARs and two compounds (C8 and C9). Notably, the 1,2,4-triazole derivatives (compounds C8 and C9) were identified as the most potent dual A1/A2A AR antagonists in our study and could serve as a basis for further development. The effective multistage screening approach developed in this study can be utilized to identify potent ligands for other drug targets.

Phenothiazine as novel human superoxide dismutase modulators: discovery, optimization, and biological evaluation

Superoxide dismutases (SODs) are regarded as important antioxidants for protecting cells against damage arising from oxidative stress. Much research is focused on finding new chemicals with an ability to boost human SOD activity. In the research described herein a structure-based approach was used to identify new human Cu-Zn superoxide dismutase (SOD1) modulators based on previously reported plasmodium falciparum iron SOD inhibitors using induced fit docking and molecular dynamic (MD) protocols. The compound with the highest docking binding energy was selected for further structure simplification followed by structural similarity and MD in order to find a new activator/inhibitor scaffold of the SOD1 enzyme. According to the docking survey of the mentioned series, 1,4-bis(3-(1,4,8-trichloro-10Hphenothiazin-10-yl) propyl) piperazine (DS88) was the top scoring compound interacting with the SOD1 active site channel. Following structure simplification and similarity search, the most promising scaffold which is closely related to the phenothiazine antipsychotic class, was identified. Compared with the normal blood SOD1 activity, the percent of O₂ production increased with trifluoperazine, while it decreased with the chlorpromazine. The molecular dynamic investigation shows that trifluoperazine exerts its SOD1 activating effect by stabilizing electrostatic loop while chlorpromazine employs SOD1 inhibition activity through repositioning of the electrostatic loop and increasing its distance from the catalytic metal site which diminished substrate specificity and catalytic activity of the SOD1 enzyme. The results identified the preferred region, orientation, and types of interaction for each activator or inhibitor compound.

DNA-binding mechanisms of human and mouse cGAS: a comparative MD and MM/GBSA study

Cyclic GMP-AMP synthase (cGAS) can detect the presence of cytoplasmic DNA and activate the innate immune system via the cGAS-STING pathway. Although several structures of cGAS-DNA complexes were resolved recently, the molecular mechanism of cGAS in its recognition of DNA has not yet been fully understood. In order to reveal the subtle differences between human and mouse cGAS in terms of their DNA-binding mechanisms, four systems, both human and mouse cGAS in complex with two different DNA sequences of equal length, were studied by molecular dynamics simulations and molecular mechanics/generalized Born surface area analysis. Several residues, including ARG176/ARG161, ARG195/ARG180, ASN210/ASN196, LYS384/LYS372, CYM397/CYM385, LYS403/LYS391, LYS407/LYS395, and LYS411/LYS399, were identified to be the common key residues in the recognition of DNA for cGAS in both humans and mice. In addition, four residue pairs LYS173/ARG158, ASP177/LYS162, CYS199/LYS184, and GLU398/SER387 were suggested to be the major residues that make human cGAS and mouse cGAS different in terms of their binding to DNA. Besides the well-known zinc-thumb domain, two residues at the kink of the spine helix were also proposed for the first time to be the major binding motifs in cGAS-DNA interaction.

In Silico Structure-Based Repositioning of Approved Drugs for Spike Glycoprotein S2 Domain Fusion Peptide of SARS-CoV-2: Rationale from Molecular Dynamics and Binding Free Energy Calculations

The membrane-anchored spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a pivotal role in directing the fusion of the virus particle mediated by the host cell receptor angiotensin-converting enzyme 2 (ACE-2). The fusion peptide region of the S protein S2 domain provides SARS-CoV-2 with the biological machinery needed for direct fusion to the host lipid membrane. In our present study, computer-aided drug design strategies were used for the identification of FDA-approved small molecules using the optimal structure of the S2 domain, which exhibits optimal interaction ratios, structural features, and energy variables, which were evaluated based on their performances in molecular docking, molecular dynamics simulations, molecular mechanics/generalized Born model and solvent accessibility binding free energy calculations of molecular dynamics trajectories, and statistical inferences. Among the 2,625 FDA-approved small molecules, chloramphenicol succinate, imipenem, and imidurea turned out to be the molecules that bound the best at the fusion peptide hydrophobic pocket. The principal interactions of the selected molecules suggest that the potential binding site at the fusion peptide region is centralized amid the Lys790, Thr791, Lys795, Asp808, and Gln872 residues.IMPORTANCE The present study provides the structural identification of the viable binding residues of the SARS-CoV-2 S2 fusion peptide region, which holds prime importance in the virus's host cell fusion and entry mechanism. The classical molecular mechanics simulations were set on values that mimic physiological standards for a good approximation of the dynamic behavior of selected drugs in biological systems. The drug molecules screened and analyzed here have relevant antiviral properties, which are reported here and which might hint toward their utilization in the coronavirus disease 2019 (COVID-19) pandemic owing to their attributes of binding to the fusion protein binding region shown in this study.

Source of oseltamivir resistance due to single E119D and double E119D/H274Y mutations in pdm09H1N1 influenza neuraminidase

Influenza epidemics are responsible for an average of 3-5 millions of severe cases and up to 500,000 deaths around the world. One of flu pandemic types is influenza A(H1N1)pdm09 virus (pdm09H1N1). Oseltamivir is the antiviral drug used to treat influenza targeting at neuraminidase (NA) located on the viral surface. Influenza virus undergoes high mutation rates and leads to drug resistance, and thus the development of more efficient drugs is required. In the present study, all-atom molecular dynamics simulations were applied to understand the oseltamivir resistance caused by the single E119D and double E119D/H274Y mutations on NA. The obtained results in terms of binding free energy and intermolecular interactions in the ligand-protein interface showed that the oseltamivir could not be well accommodated in the binding pocket of both NA mutants and the 150-loop moves out from oseltamivir as an "open" state. A greater number of water molecules accessible to the binding pocket could disrupt the oseltamivir binding with NA target as seen be high mobility of oseltamivir at the active site. Additionally, our finding could guide to the design and development of novel NA inhibitor drugs.

Modeling caspase-1 inhibition: Implications for catalytic mechanism and drug design

The metabolic product of caspase-1, IL-1β, is an important mediator in inflammation and pyroptosis cell death process. Alzheimer's disease, septic shock and rheumatoid arthritis are IL-1β mediated diseases, making the caspase-1 an interesting target of pharmacological value. Many inhibitors have been developed until now, most of them are peptidomimetic with improved potency. In the present study, all-atom molecular dynamics simulations and the MM/GBSA method were employed to reproduce and interpret the results obtained by in vitro experiments for a series of inhibitors. The analysis shows that the tautomeric state of the catalytic His237 impact significantly the performance of the prediction protocol, providing evidence for a His237 tautomeric state different to the proposed in the putative mechanism. Additionally, analysis of inhibitor-enzyme interactions indicates that the differences in the inhibitory potency of the tested ligands can be explained mainly by the interaction of the inhibitors with the S2-S4 protein region. These results provide guidelines for subsequent studies of caspase-1 catalytic reaction mechanism and for the design of novel inhibitors.

Probing the "fingers" domain binding pocket of Hepatitis C virus NS5B RdRp and D559G resistance mutation via molecular docking, molecular dynamics simulation and binding free energy calculations

The NS5B RdRp polymerase is a prominent enzyme for the replication of Hepatitis C virus (HCV). During the HCV replication, the template RNA binding takes place in the "fingers" sub-domain of NS5B. The "fingers" domain is a new emerging allosteric site for the HCV drug development. The inhibitors of the "fingers" sub-domain adopt a new antiviral mechanism called RNA intervention. The details of essential amino acid residues, binding mode of the ligand, and the active site intermolecular interactions of RNA intervention reflect that this mechanism is ambiguous in the experimental study. To elucidate these details, we performed molecular docking analysis of the fingers domain inhibitor quercetagetin (QGN) with NS5B polymerase. The detailed analysis of QGN-NS5B intermolecular interactions was carried out and found that QGN interacts with the binding pocket amino acid residues Ala97, Ala140, Ile160, Phe162, Gly283, Gly557, and Asp559; and also forms π⋯π stacking interaction with Phe162 and hydrogen bonding interaction with Gly283. These are found to be the essential interactions for the RNA intervention mechanism. Among the strong hydrogen bonding interactions, the QGN⋯Ala140 is a newly identified important hydrogen bonding interaction by the present work and this interaction was not resolved by the previously reported crystal structure. Since D559G mutation at the fingers domain was reported for reducing the inhibition percentage of QGN to sevenfold, we carried out molecular dynamics (MD) simulation for wild and D559G mutated complexes to study the stability of protein conformation and intermolecular interactions. At the end of 50 ns MD simulation, the π⋯π stacking interaction of Phe162 with QGN found in the wild-type complex is altered into T-shaped π stacking interaction, which reduces the inhibition strength. The origin of the D559G resistance mutation was studied using combined MD simulation, binding free energy calculations and principal component analysis. The results were compared with the wild-type complex. The mutation D559G reduces the binding affinity of the QGN molecule to the fingers domain. The free energy decomposition analysis of each residue of wild-type and mutated complexes revealed that the loss of non-polar energy contribution is the origin of the resistance. Communicated by Ramaswamy H. Sarma.