A comparative study of structural and conformational properties of WNK kinase isoforms bound to an inhibitor: insights from molecular dynamic simulations

An immunoinformatic approach for developing a multi-epitope subunit vaccine against Monkeypox virus

An in-silico approach was implemented to develop a multi-epitope subunit vaccine construct against the recent outbreak of the Monkeypox virus. The contribution of 10 different antigenic proteins based on their antigenicity led to the selection of 10 HTL, 9 CTL, and 6 BCL epitopes. The construct was further investigated for its allergenicity, antigenicity, and physio-chemical properties using servers such as AllerTOP and Allergen FP, VaxiJen and ANTIGENPro, and ProtParam respectively. The secondary structure of the vaccine was predicted using the SOPMA server followed by I-TASSER for the 3D structure. After refinement and validation of structural stability of the modelled vaccine, a molecular docking assay was implemented to study the interaction of the known TLR4 receptor with that of the constructed vaccine using the ClusPro server. The docked vaccine and TLR4 receptor were studied using the molecular dynamics (MD) simulation to validate the stability of the complex. After codon optimization the cDNA was constructed and in-silico cloning of the vaccine construct was carried out. The vaccine was also subjected to computational immune assay which predicted a powerful immune response against the Monkeypox virus validating that the developed multi-epitope vaccine construct can be a potent vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00220-5.

Computer-aided Affinity Enhancement of a Cross-reactive Antibody against Dengue Virus Envelope Domain III

The dengue virus (DENV), composed of four distinct but serologically related Flaviviruses, causes the most important emerging viral disease, with nearly 400 million infections yearly. Currently, there are no approved therapies. Although DENV infection induces lifelong immunity against the same serotype, the antibodies raised contribute to severe disease in heterotypic infections. Therefore, understanding the mechanism of DENV neutralization by antibodies is crucial in the design of vaccines against all serotypes. This study reports a comparative structural and energetic analysis of the monoclonal antibody (mAb) 4E11 in complex with its target domain III of the envelope protein for all four DENV serotypes. We use extensive replica molecular dynamics simulations in conjunction with the binding free energy calculations. Further single point and double mutations were designed through computational site-directed mutagenesis and observed that the re-engineered antibody exhibits high affinity to binding and broadly neutralizing activity against serotypes. Our results showed improved binding affinity by the gain of enthalpy, which could be attributed to the stabilization of salt-bridge and hydrogen bond interactions at the antigen-antibody interface. The findings provide valuable results in understanding the structural dynamics and energetic contributions that will be helpful to the design of high-affinity antibodies against dengue infections.

Molecular level investigation for identifying potential inhibitors against thymidylate kinase of monkeypox through in silico approaches

The need for more advanced and effective monkeypox (Mpox) treatments has become evident with numerous Mpox virus (MPXV) outbreaks. Over the years, interest has increased in developing targeted medicines that are efficient, safe, and precise while avoiding adverse effects. Here, we screened 32409 compounds against thymidylate kinase (TMPK), an emerging target for Mpox treatment. We studied their pharmacological characteristics and analyzed those through all-atom molecular dynamics simulations followed by molecular mechanics Poisson Boltzmann surface area (MM-PBSA) based free energy calculations. According to our findings, the leads CID40777874 and CID28960001 had the highest binding affinities towards TMPK with ΔGbind of -8.04 and -5.58 kcal/mol, respectively, which outperformed our control drug cidofovir (ΔGbind = -2.92 kcal/mol) in terms of binding favourability. Additionally, we observed crucial TMPK dynamics brought on by ligand-binding and identified key residues such as Phe68 and Tyr101 as the critical points of the protein-ligand interaction. The DCCM analysis revealed the role of ligand binding in stabilizing TMPK's binding region, as indicated by residual correlation motions. Moreover, the PSN analysis revealed that the interaction with ligand induces changes in residual network properties, enhancing the stability of complexes. We successfully identified novel compounds that may serve as potential building blocks for constructing contemporary antivirals against MPXV and highlighted the molecular mechanisms underlying their binding with TMPK. Overall, our findings will play a significant role in advancing the development of new therapies against Mpox and facilitating a comprehensive understanding of their interaction patterns.Communicated by Ramaswamy H. Sarma.

XGBoost odor prediction model: finding the structure-odor relationship of odorant molecules using the extreme gradient boosting algorithm

Determining the structure-odor relationship has always been a very challenging task. The main challenge in investigating the correlation between the molecular structure and its associated odor is the ambiguous and obscure nature of verbally defined odor descriptors, particularly when the odorant molecules are from different sources. With the recent developments in machine learning (ML) technology, ML and data analytic techniques are significantly being used for quantitative structure-activity relationship (QSAR) in the chemistry domain toward knowledge discovery where the traditional Edisonian methods have not been useful. The smell perception of odorant molecules is one of the aforementioned tasks, as olfaction is one of the least understood senses as compared to other senses. In this study, the XGBoost odor prediction model was generated to classify smells of odorant molecules from their SMILES strings. We first collected the dataset of 1278 odorant molecules with seven basic odor descriptors, and then 1875 physicochemical properties of odorant molecules were calculated. To obtain relevant physicochemical features, a feature reduction algorithm called PCA was also employed. The ML model developed in this study was able to predict all seven basic smells with high precision (>99%) and high sensitivity (>99%) when tested on an independent test dataset. The results of the proposed study were also compared with three recently conducted studies. The results indicate that the XGBoost-PCA model performed better than the other models for predicting common odor descriptors. The methodology and ML model developed in this study may be helpful in understanding the structure-odor relationship.Communicated by Ramaswamy H. Sarma.

Finding potential inhibitors against RNA-dependent RNA polymerase (RdRp) of bovine ephemeral fever virus (BEFV): an in-silico study

The bovine ephemeral fever virus (BEFV) is an enzootic agent that affects millions of bovines and causes major economic losses. Though the virus is seasonally reported with a very high morbidity rate (80-100%) from African, Australian, and Asiatic continents, it remains a neglected pathogen in many of its endemic areas, with no proper therapeutic drugs or vaccines presently available for treatment. The RNA-dependent RNA polymerase (RdRp) catalyzes the viral RNA synthesis and is an appropriate candidate for antiviral drug developments. We utilized integrated computational tools to build the 3D model of BEFV-RdRp and then predicted its probable active binding sites. The virtual screening and optimization against these active sites, using several small-molecule inhibitors from a different category of Life Chemical database and FDA-approved drugs from the ZINC database, was performed. We found nine molecules that have docking scores varying between -6.84 to -10.43 kcal/mol. Furthermore, these complexes were analyzed for their conformational dynamics and thermodynamic stability using molecular dynamics simulations in conjunction with the molecular mechanics generalized Born surface area (MM-GBSA) scheme. The binding free energy calculations depict that the electrostatic interactions play a dominant role in the RdRp-inhibitor binding. The hot spot residues, such as Arg565, Asp631, Glu633, Asp740, and Glu707, were found to control the RdRp-inhibitor interaction. The ADMET analysis strongly suggests favorable pharmacokinetics of these compounds that may prove useful for treating the BEFV ailment. Overall, we anticipate that these findings would help explore and develop a wide range of anti-BEFV therapy.Communicated by Ramaswamy H. Sarma.

An update regarding the role of WNK kinases in cancer

Mammalian WNK kinases (WNKs) are serine/threonine kinases that contain four members, WNK1-4. They function to maintain ion homeostasis and regulate blood pressure in mammals. Recent studies have revealed that the dysregulation of WNKs contributes to tumor growth, metastasis, and angiogenesis through complex mechanisms, especially through phosphorylating kinase substrates SPS1-related proline/alanine-rich kinase (SPAK) and oxidative stress-responsive kinase 1 (OSR1). Here, we review and discuss the relationships between WNKs and several key factors/biological processes in cancer, including ion channels, cation chloride cotransporters, sodium bicarbonate cotransporters, signaling pathways, angiogenesis, autophagy, and non-coding RNAs. In addition, the potential drugs for targeting WNK-SPAK/OSR1 signaling have also been discussed. This review summarizes and discusses knowledge of the roles of WNKs in cancer, which provides a comprehensive reference for future studies.

Functional Loop Dynamics and Characterization of the Inactive State of the NS2B-NS3 Dengue Protease due to Allosteric Inhibitor Binding

Dengue virus, a flavivirus that causes dengue shock syndrome and dengue hemorrhagic fever, is currently prevalent worldwide. A two-component protease (NS2B-NS3) is essential for maturation, representing an important target for designing anti-flavivirus drugs. Previously, consideration has been centered on developing active-site inhibitors of NS2B-NS3pro. However, the flat and charged nature of its active site renders difficulties in developing inhibitors, suggesting an alternative strategy for identifying allosteric inhibitors. The allosterically sensitive site of the dengue protease is located near Ala125, between the 120s loop and 150s loop. Using atomistic molecular dynamics simulations, we have explored the protease's conformational dynamics upon binding of an allosteric inhibitor. Furthermore, characterization of the inherent flexible loops (71-75s loop, 120s loop, and 150s loop) is carried out for allosteric-inhibitor-bound wild-type and mutant A125C variants and a comparison is performed with its unbound state to extract the structural changes describing the inactive state of the protease. Our study reveals that compared to the unliganded system, the inhibitor-bound system shows large structural changes in the 120s loop and 150s loop in contrast to the rigid 71-75s loop. The unliganded system shows a closed-state pocket in contrast to the open state for the wild-type complex that locks the protease into the open and inactive-state conformations. However, the mutant complex fluctuates between open and closed states. Also, we tried to see how mutation and binding of an allosteric inhibitor perturb the connectivity in a protein structure network (PSN) at contact levels. Altogether, our study reveals the mechanism of conformational rearrangements of loops at the molecular level, locking the protein in an inactive conformation, which may be useful for developing allosteric inhibitors.

Unraveling the Molecular Mechanism of Recognition of Selected Next-Generation Antirheumatoid Arthritis Inhibitors by Janus Kinase 1

Rheumatoid arthritis (RA) is a chronic immune-related condition, primarily of joints, and is highly disabling and painful. The inhibition of Janus kinase (JAK)-related cytokine signaling pathways using small molecules is prevalent nowadays. The JAK family belongs to nonreceptor cytoplasmic protein tyrosine kinases (PTKs), including JAK1, JAK2, JAK3, and TYK2 (tyrosine kinase 2). JAK1 has received significant attention after being identified as a promising target for developing anti-RA therapeutics. Currently, no crystal structure is available for JAK1 in complex with the next-generation anti-RA drugs. In the current study, we investigated the mechanism of binding of baricitinib, filgotinib, itacitinib, and upadacitinib to JAK1 using a combined method of molecular docking, molecular dynamics simulation, and binding free energy calculation via the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) scheme. We found that the calculated binding affinity decreases in the order upadacitinib > itacitinib > filgotinib > baricitinib. Due to the increased favorable intermolecular electrostatic contribution, upadacitinib is more selective to JAK1 compared to the other three inhibitors. The cross-correlation and principal component analyses showed that different inhibitor bindings significantly affect the binding site dynamics of JAK1. Furthermore, our studies indicated that the hydrophobic residues and hydrogen bonds from the hinge region (Glu⁹⁵⁷ and Leu⁹⁵⁹) of JAK1 played an essential role in stabilizing the inhibitors. Protein structural network analysis reveals that the total number of links and hubs in JAK1/baricitinib (354, 48) is more significant than those in apo (328, 40) and the other three complexes. The JAK1/baricitinib complex shows the highest probability of the highest-ranked community, indicating a compact network of the JAK1/baricitinib complex, consistent with its higher stability than the rest of the four systems. Overall, our study may be crucial for the rational design of JAK1-selective inhibitors with better affinity.

Discovery of potential competitive inhibitors against With-No-Lysine kinase 1 for treating hypertension by virtual screening, inverse pharmacophore-based lead optimization, and molecular dynamics simulations

The With-No-Lysine (WNK) has received attention because of its involvement in hypertension. Genetic mutation in the genes of WNK, leading to its overexpression, has been reported in Familial Hyperkalaemic Hypertension, and thus WNK is considered a potential drug target. Herein, we have performed a high-throughput virtual screening of ~11,000 compounds, mainly the natural phytochemical compounds and kinase inhibitory libraries, to find potential competitive inhibitors against WNK1. Initially, candidates with a docking score of ~ -10.0 kcal/mol or less were selected to further screen their good pharmacological properties by applying absorption, distribution, metabolism, excretion, and toxicity (ADMET). Finally, six docked compounds bearing appreciable binding affinities and WNK1 selectivity were complimented with 500 ns long all-atom molecular dynamic simulations. Subsequently, the MMPBSA scheme (Molecular Mechanics Poisson Boltzmann Surface Area) suggested three phytochemical compounds, C00000947, C00020451, and C00005031, with favourable binding affinity against WNK1. Among them, C00000947 acts as the most potent competitive inhibitor of WNK1. Further, inverse pharmacophore-based lead optimization of the C00000947 leads to one potential compound, meciadanol, which shows better binding affinity and specificity than C00000947 towards WNK1, which may be further exploited to develop effective therapeutics against WNK1-associated hypertension after in vitro and in vivo validation.

Investigating potency of TMC-126 against wild-type and mutant variants of HIV-1 protease: a molecular dynamics and free energy study

A detailed computational study was performed to investigate the conformational changes of flap region and the mechanism underlying the binding of the inhibitor TMC-126 to HIV-1 protease (PR1) and its mutant variants through molecular dynamics simulations in conjunction with the molecular mechanics Poisson-Boltzmann (MM-PBSA) free energy calculation. Further, we have studied the effectiveness of the inhibitor against HIV-2 protease (PR2). The MM-PBSA calculation suggests that TMC-126 loses its potency against mutant variants and PR2 compared to wild-type PR1 mainly due to the loss in intermolecular electrostatic interactions. The potency of the inhibitor decreases in the order: wild type PR1 > M46L > MDR20 > I50V > PR2 > V32I > A28S. Our study reveals that the flap of PR1 adopts a semi-open conformation due to the mutation I50V or MDR20. The dissimilar nature of the movement of the flap tip of both monomers is evident from the dynamic cross-correlation map. The protein structural network analysis displays that mutation causes structural rearrangements and changes the communication path between residues. Overall, we believe our study may help explore and accelerate the development of novel HIV-1/HIV-2 protease inhibitors with better potency.

Molecular Mechanism of Inhibiting WNK Binding to OSR1 by Targeting the Allosteric Pocket of the OSR1-CCT Domain with Potential Antihypertensive Inhibitors: An In Silico Study

The oxidative-stress-responsive kinase 1 (OSR1) and the STE20/SPS1-related proline-alanine-rich kinase (SPAK) are physiological substrates of the with-no-lysine (WNK) kinase. They are the master regulators of cation Cl^- cotransporters that could be targeted for discovering novel antihypertensive agents. Both kinases have a conserved carboxy-terminal (CCT) domain that recognizes a unique peptide motif (Arg-Phe-Xaa-Val) present in their upstream kinases and downstream substrates. Here, we have combined molecular docking with molecular dynamics simulations and free-energy calculations to identify potential inhibitors that can bind to the allosteric pocket of the OSR1-CCT domain and impede its interaction with the WNK peptide. Our study revealed that STOCK1S-14279 and Closantel bound strongly to the allosteric pocket of OSR1 and displaced the WNK peptide from the primary pocket of OSR1. We showed that primarily Arg1004 and Gln1006 of the WNK4-peptide motif were involved in strong H-bond interactions with Glu453 and Arg451 of OSR1. Besides, our study revealed that atoms of Arg1004 were solvent-exposed in cases of STOCK1S-14279 and Closantel, implying that the WNK4 peptide was moved out of the pocket. Overall, the predicted potential inhibitors altogether abolish the OSR1-WNK4-peptide interaction, suggesting their potency as a prospective allosteric inhibitor against OSR1.

Identification of Potential Inhibitors against Epstein-Barr Virus Nuclear Antigen 1 (EBNA1): An Insight from Docking and Molecular Dynamic Simulations

Epstein-Barr virus (EBV), a known tumorigenic virus, is associated with various neuropathies, including multiple sclerosis (MS). However, there is no anti-EBV FDA-approved drug available in the market. Our study targeted EBV protein EBV nuclear antigen 1 (EBNA1), crucial in virus replication and expressed in all the stages of viral latencies. This dimeric protein binds to an 18 bp palindromic DNA sequence and initiates the process of viral replication. We chose phytochemicals and FDA-approved MS drugs based on literature survey followed by their evaluation efficacies as anti-EBNA1 molecules. Molecular docking revealed FDA drugs ozanimod, siponimod, teriflunomide, and phytochemicals; emodin; protoapigenone; and EGCG bound to EBNA1 with high affinities. ADMET and Lipinski's rule analysis of the phytochemicals predicted favorable druggability. We supported our assessments of pocket druggability with molecular dynamics simulations and binding affinity predictions by the molecular mechanics generalized Born surface area (MM/GBSA) method. Our results establish a stable binding for siponimod and ozanimod with EBNA1 mainly via van der Waals interactions. We identified hot spot residues like I481', K477', L582', and K586' in the binding of ligands. In particular, K477' at the amino terminal of EBNA1 is known to establish interaction with two bases at the major groove of the DNA. Siponimod bound to EBNA1 engaging K477', thus plausibly making it unavailable for DNA interaction. Computational alanine scanning further supported the significant roles of K477', I481', and K586' in the binding of ligands with EBNA1. Conclusively, the compounds showed promising results to be used against EBNA1.

Mining of Ebola virus genome for the construction of multi-epitope vaccine to combat its infection

Ebola virus is the primary causative agent of viral hemorrhagic fever that is an epidemic disease and responsible for the massive premature deaths in humans. Despite knowing the molecular mechanism of its pathogenesis, to date, no commercial or FDA approved multiepitope vaccine is available against Ebola infection. The current study focuses on designing a multi-epitope subunit vaccine for Ebola using a novel immunoinformatic approach. The best predicted antigenic epitopes of Cytotoxic-T cell (CTL), Helper-T cells (HTL), and B-cell epitopes (BCL) joined by various linkers were selected for the multi-epitope vaccine designing. For the enhanced immune response, two adjuvants were also added to the construct. Further analysis showed the vaccine to be immunogenic and non-allergenic, forming a stable and energetically favorable structure. The stability of the unbound vaccine construct and vaccine/TLR4 was elucidated via atomistic molecular dynamics simulations. The binding free energy analysis (ΔG_Bind = -194.2 ± 0.5 kcal/mol) via the molecular mechanics Poisson-Boltzmann docking scheme revealed a strong association and thus can initiate the maximal immune response. Next, for the optimal expression of the vaccine construct, its gene construct was cloned in the pET28a + vector system. In summary, the Ebola viral proteome was screened to identify the most potential HTLs, CTLs, and BCL epitopes. Along with various linkers and adjuvants, a multi-epitope vaccine is constructed that showed a high binding affinity with the immune receptor, TLR4. Thus, the current study provides a highly immunogenic multi-epitope subunit vaccine construct that may induce humoral and cellular immune responses against the Ebola infection.Communicated by Ramaswamy H. Sarma.

Characterizing an allosteric inhibitor-induced inactive state in with-no-lysine kinase 1 using Gaussian accelerated molecular dynamics simulations

The binding of an allosteric inhibitor in WNK1 leads to the inactive state.

Computational Investigation of Structural Dynamics of SARS-CoV-2 Methyltransferase-Stimulatory Factor Heterodimer nsp16/nsp10 Bound to the Cofactor SAM

Recently, a highly contagious novel coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has emerged, posing a global threat to public health. Identifying a potential target and developing vaccines or antiviral drugs is an urgent demand in the absence of approved therapeutic agents. The 5'-capping mechanism of eukaryotic mRNA and some viruses such as coronaviruses (CoVs) are essential for maintaining the RNA stability and protein translation in the virus. SARS-CoV-2 encodes S-adenosyl-L-methionine (SAM) dependent methyltransferase (MTase) enzyme characterized by nsp16 (2'-O-MTase) for generating the capped structure. The present study highlights the binding mechanism of nsp16 and nsp10 to identify the role of nsp10 in MTase activity. Furthermore, we investigated the conformational dynamics and energetics behind the binding of SAM to nsp16 and nsp16/nsp10 heterodimer by employing molecular dynamics simulations in conjunction with the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) method. We observed from our simulations that the presence of nsp10 increases the favorable van der Waals and electrostatic interactions between SAM and nsp16. Thus, nsp10 acts as a stimulator for the strong binding of SAM to nsp16. The hydrophobic interactions were predominately identified for the nsp16-nsp10 interactions. Also, the stable hydrogen bonds between Ala83 (nsp16) and Tyr96 (nsp10), and between Gln87 (nsp16) and Leu45 (nsp10) play a vital role in the dimerization of nsp16 and nsp10. Besides, Computational Alanine Scanning (CAS) mutagenesis was performed, which revealed hotspot mutants, namely I40A, V104A, and R86A for the dimer association. Hence, the dimer interface of nsp16/nsp10 could also be a potential target in retarding the 2'-O-MTase activity in SARS-CoV-2. Overall, our study provides a comprehensive understanding of the dynamic and thermodynamic process of binding nsp16 and nsp10 that will contribute to the novel design of peptide inhibitors based on nsp16.