Structural dynamics and functional analysis of Saprolegnia parasitica chitin synthases 5 in a phospholipid bilayer.

Saprolegnia parasitica is an oomycete responsible for a fish disease called saprolegniosis, which poses an economic and environmental burden on aquaculture production. In Saprolegnia, CHS5 of S. parasitica (SpCHS5) contains an N-terminal domain, a catalytic domain of the glycosyltransferase -2 family containing a GT-A fold, and a C-terminal transmembrane domain. No three-dimensional structure of SpCHS5 is reported yet disclosing the structural details of this protein. We have developed a structural model of full-length SpCHS5 and validated it by molecular dynamics simulation technique. From the 1 microsecond simulations, we retrieved the stable RoseTTAFold model SpCHS5 protein to explain characteristics and structural features. Furthermore, from the analysis of the movement of chitin in the protein cavity, we assumed that ARG 482, GLN 527, PHE 529, PHE 530, LEU 540, SER 541, TYR 544, ASN 634, THR 641, TYR 645, THR 641, ASN 772 residues as a main cavity lining site. In SMD analysis, we investigated the opening of the transmembrane cavity required for chitin translocation. The pulling of chitin from the internal cavity to the extracellular region was observed through steered molecular dynamics simulations. A comparison of the initial and final structures of chitin complex showed that there's a transmembrane cavity opening in the simulations. Overall, this present work will help us understand the structural and functional basis of CHS5 and design inhibitors against SpCHS5.Communicated by Ramaswamy H. Sarma.

Antiviral peptides inhibiting the main protease of SARS-CoV-2 investigated by computational screening and in vitro protease assay.

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an important role in viral replication and transcription and received great attention as a vital target for drug/peptide development. Therapeutic agents such as small-molecule drugs or peptides that interact with the Cys-His present in the catalytic site of Mpro are an efficient way to inhibit the protease. Although several emergency-approved vaccines showed good efficacy and drastically dropped the infection rate, evolving variants are still infecting and killing millions of people globally. While a small-molecule drug (Paxlovid) received emergency approval, small-molecule drugs have low target specificity and higher toxicity. Besides small-molecule drugs, peptide therapeutics are thus gaining increasing popularity as they are easy to synthesize and highly selective and have limited side effects. In this study, we investigated the therapeutic value of 67 peptides targeting Mpro using molecular docking. Subsequently, molecular dynamics (MD) simulations were implemented on eight protein-peptide complexes to obtain molecular-level information on the interaction between these peptides and the Mpro active site, which revealed that temporin L, indolicidin, and lymphocytic choriomeningitis virus (LCMV) GP1 are the best candidates in terms of stability, interaction, and structural compactness. These peptides were synthesized using the solid-phase peptide synthesis protocol, purified by reversed-phase high-performance liquid chromatography (RP-HPLC), and authenticated by mass spectrometry (MS). The in vitro fluorometric Mpro activity assay was used to validate the computational results, where temporin L and indolicidin were observed to be very active against SARS-CoV-2 Mpro with IC50 values of 38.80 and 87.23 µM, respectively. A liquid chromatography-MS (LC-MS) assay was developed, and the IC50 value of temporin L was measured at 23.8 µM. The solution-state nuclear magnetic resonance (NMR) structure of temporin L was determined in the absence of sodium dodecyl sulfate (SDS) micelles and was compared to previous temporin structures. This combined investigation provides critical insights and assists us to further develop peptide inhibitors of SARS-CoV-2 Mpro through structural guided investigation.

Therapeutic Potential of Antiviral Peptides against the NS2B/NS3 Protease of Zika Virus.

The NS2B/NS3 protease is highly conserved among various proteases of the Zika virus, making it an important therapeutic target for developing broad-spectrum antiviral drugs. The NS2B/NS3 protease is a crucial enzyme in the replication cycle of Zika virus and plays a significant role in viral maturation and assembly. Inhibiting the activity of this protease can potentially prevent viral replication, making it an attractive target for developing therapies against Zika virus infection. This work screens 429 antiviral peptides in comparison with substrate peptide against the NS2B/NS3 of Zika virus using molecular docking and molecular dynamics (MD) simulation. Based on the docking screening, MD simulation conducted for the best four peptides including AVP0239, AVP0642, AVP0660, and AVP2044, could be effective against NS2B/NS3. These results were compared with the control substrate peptide. Further analysis indicates that AVP0642 and AVP2044 are the most promising candidates. The interaction analysis showed that the catalytic site residues including His51, Asp75, Ser135 and other non-catalytic residues such as Asp129, Asp83, and Asp79 contribute substantial interactions. Hydrogen bonds (41%) and hydrophobic interactions (33%) are observed as the prominent non-covalent interaction prompting the peptide-protein complex formation. Furthermore, the structure-activity relationship (SAR) illustrates that positively charged (Lys, Arg) residues in the peptides dominate the interactions. This study provides the basis for developing novel peptide-based protease inhibitors for Zika virus.

Elucidating the Structure, Dynamics, and Interaction of a Choline Chloride and Citric Acid Based Eutectic System by Spectroscopic and Molecular Modeling Investigations.

Eutectic solvent systems are versatile solvents that have found widespread use in numerous applications. Traditional solvents are homogeneous, having only one component, and their chemistry is relatively simple, with some exceptions. On the other hand, deep eutectic solvents (DESs) comprise binary components, generally a donor and an acceptor in hydrogen bonding with varying ratios. The interaction chemistry among the donor and acceptor involved in hydrogen bonding in DESs is complicated. Although numerous research is focused on the synthesis and application of DESs, few studies are reported to elucidate the complex structure and dynamic and interaction behavior of DESs. In this study, we employed calorimetry, vibrational spectroscopy techniques including FTIR and Raman, and nuclear magnetic resonance to derive insight into the structural feature and noncovalent contact of choline chloride (ChCl) and citric acid (CA) while they formed DESs. The 1:1 ChCl/CA eutectic system showed phase transitions and melting peaks with the most pronounced peak at 156.22 °C, suggesting the DESs melting at a lower temperature than the melting temperatures of ChCl and CA. In addition to IR and Raman findings, 1H NMR investigations demonstrate hydrogen bonding intermolecular interactions between ChCl and CA, supporting the formation of 1:1 ChCl/CA DESs based on the deshielded chemical shifts of the proton for Ch. The interaction of the chloride anion with the methyl protons (H4) and methylene protons (H3) of ChCl as well as the strong hydrogen bonding interactions between the hydroxyl hydrogen (H1) of ChCl with one of CA's carbonyl oxygens both supported the formation of conformer E. In addition, molecular dynamics followed by the density functional theory (DFT) was employed to visualize the structure and interaction of DESs using the ωB97XD theory and 6-311++G (d,p) basis set. Both experimental and theoretical IR, Raman, and structural analyses provided evidence of the formation of DESs by possessing hydrogen bonds. These multifaceted experimental and computational investigations provide details of structural and intermolecular interactions of ChCl/CA DESs.

Structure and dynamics of whole-sequence homology model of ORF3a protein of SARS-CoV-2: An insight from microsecond molecular dynamics simulations.

The ORF3a is a large accessory protein in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which plays an important role in virulence and viral replication; especially in inflammasome activation and apoptosis. However,, the existing cryo-EM structure of SARS-CoV-2 ORF3a is incomplete, . making it challenging to understand its structural and functional features. The aim of this study is to investigate the dynamic behaviors of the full-sequence homology model of ORF3a and compare it with the cryo-EM structure using microsecond molecular dynamics simulations. The previous studies indicated that the unresolved residues of the cryo-EM structure are not only involved in the pathogenesis of the SARS-CoV-2 but also exhibit a significant antigenicity. The dynamics scenario of homology model revealed higher RMSD, Rg, and SASA values with stable pattern when compared to the cryo-EM structure. Moreover, the RMSF analysis demonstrated higher fluctuations at specific positions (1-43, 97-110, 172-180, 219-243) in the model structure, whereas the cryo-EM structure displayed lower overall drift (except 1-43) in comparison to the model structure.Secondary structural features indicated that a significant unfolding in the transmembrane domains and ß-strand at positions 166 to 172, affecting the stability and compactness of the cryo-EM structure , whereas the model exhibited noticeable unfolding in transmembrane domains and small-coiled regions in the N-terminal. , The results from molecular docking and steered molecular dynamics investigations showed the model structure had a greater number of non-bonding interactions, leading to enhanced stability when compared to the cryo-EM structure. Consequently, higher forces were necessary for unbinding of the baricitinib and ruxolitinib inhibitors from the model structure.. Our findings can help better understanding of the significance of unresolved residues at the molecular level. Additionally, this information can guide researchers for experimental endeavors aimed at completing the full-sequence structure of the ORF3a.Communicated by Ramaswamy H. Sarma.

Unraveling the impact of ORF3a Q57H mutation on SARS-CoV-2: insights from molecular dynamics.

ORF3a is a conserved accessory protein of SARS-CoV-2, linked to viral infection and pathogenesis, with acquired mutations at various locations. Previous studies have shown that the occurrence of the Q57H mutation is higher in comparison to other positions in ORF3a. This mutation is known to induce conformational changes, yet the extent of structural alteration and its role in the viral adaptation process remain unknown. Here we performed molecular dynamics (MD) simulations of wt-ORF3a, Q57H, and Q57A mutants to analyze structural changes caused by mutations compared to the native protein. The MD analysis revealed that Q57H and Q57A mutants show significant structural changes in the dimer conformation than the wt-ORF3a. This dimer conformer narrows down the ion channel cavity, which reduces Na + or K + permeability leading to decrease the antigenic response that can help the virus to escape the host immune system. Non-bonding interaction analysis shows the Q57H mutant has more interacting residues, resulting in more stability within dimer conformation than the wt-ORF3a and Q57A. Moreover, both mutant dimers (Q57H and Q57A) form a novel salt-bridge interaction at the same position between A:Asp142 and B:Lys61, whereas such an interaction is absent in the wt-ORF3a dimer. We have also noticed that the TM3 domain's flexibility in Q57H is increased because of strong inter-domain interactions of TM1 and TM2 within the dimer conformation. These unusual interactions and flexibility of Q57H mutant can have significant impacts on the SARS-CoV-2 adaptations, virulence, transmission, and immune system evasion. Our findings are consistent with the previous experimental data and provided details information on the structural perturbation in ORF3a caused by mutations, which can help better understand the structural change at the molecular level as well as the reason for the high virulence properties of this variant.Communicated by Ramaswamy H. Sarma.

Structural and functional effects of the L84S mutant in the SARS-COV-2 ORF8 dimer based on microsecond molecular dynamics study.

The L84S mutation has been observed frequently in the ORF8 protein of SARS-CoV-2, which is an accessory protein involved in various important functions such as virus propagation, pathogenesis, and evading the immune response. However, the specific effects of this mutation on the dimeric structure of ORF8 and its impacts on interactions with host components and immune responses are not well understood. In this study, we performed one microsecond molecular dynamics (MD) simulation and analyzed the dimeric behavior of the L84S and L84A mutants in comparison to the native protein. The MD simulations revealed that both mutations caused changes in the conformation of the ORF8 dimer, influenced protein folding mechanisms, and affected the overall structural stability. In particular, the 73YIDI76 motif has found to be significantly affected by the L84S mutation, leading to structural flexibility in the region connecting the C-terminal ß4 and ß5 strands. This flexibility might be responsible for virus immune modulation.  The free energy landscape (FEL) and principle component analysis (PCA) have also supported our investigation. Overall, the L84S and L84A mutations affect the ORF8 dimeric interfaces by reducing the frequency of protein-protein interacting residues (Arg52, Lys53, Arg98, Ile104, Arg115, Val117, Asp119, Phe120, and Ile121) in the ORF8 dimer.  Our findings provide detail insights for further research in designing structure-based therapeutics against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

In silico peptide-based therapeutics against human colorectal cancer by the activation of TLR5 signaling pathways.

OBJECTIVE: Colorectal cancer (CRC) is the third leading cause of cancer-related deaths in both men and women. Toll-like receptor 5 (TLR5), an autoimmune signaling receptor that plays a role in cancer, can be exploited for the suppression of human colon cancer. Salmonella flagellin protein, a novel agonist of TLR5 activating downstream signaling, could be a basis for designing anticancer peptides. METHODS: The three-dimensional crystal structure of TLR5 (PDB ID: 3J0A, Resolution = 26.0 Å) was optimized using the AMBER force field in the YASARA suit. In silico enzymatic digestion tool, PeptideCutter, was used to identify peptides from Salmonella flagellin, an agonist against human TLR5. The 3D structure of the peptides was generated using PEP-FOLD3. These peptides were screened against human TLR5 using shape complementarity principles based on the binding affinity and interactions with the active residue of TLR5 monomer, and the selected peptides were further validated by molecular dynamic (MD) simulation. RESULTS: In this study, we generated 42 peptides from Salmonella flagellin protein by in silico protein digestion. Then, based on a new hidden Markov model sub-optimal conformation sampling approach as well as the size of the fragments, we select 38 effective peptides from these 42 cleavages. These peptides were screened against the monomeric Xray structure of human TLR5 using shape complementarity principles. Based on the binding affinity and interactions with the active residue of TLR5 monomer (residues 294 and 366 of TLR5), nine top-scored peptides were selected for the initial molecular dynamic (MD) simulation. Among these peptides, Clv10, Clv17, and Clv28 showed high stability and less flexibility during MD simulation. A 1 µs MD simulation was performed on TLR5-Clv10, TLR-Clv17, and TLR5-Clv28 complexes to further analyze the stability, conformational changes, and binding mode (Clv10, Clv17, and Clv28). During this MD study, the peptides showed high salt bridges and ionic interactions with residue ASP294 and residue ASP366 throughout the simulation and remained in the concave of the human TLR5 monomer. The RMSD and Rg values showed that the peptide-protein complexes become stable after 200 ns of contraction and extraction. CONCLUSION: These findings can facilitate the rational design of selected peptides as an agonist of TLR5, which have antitumor activity, suppress colorectal cancer tumors, and can be used as promising candidates and novel agonists of TLR5.

Potential antiviral peptides against the nucleoprotein of SARS-CoV-2.

Nucleoprotein is a conserved structural protein of SARS-CoV-2, which is involved in several functions, including replication, packaging, and transcription. In this research, 21 antiviral peptides that are known to have inhibitory function against nucleoprotein in several other viruses, were screened computationally against the nucleoprotein of SARS-CoV-2. The complexes of five best performing peptides (AVP1142, AVP1145, AVP1148, AVP1150, AVP1155) with nucleoprotein were selected for subsequent screening via 5 ns molecular dynamics (MD) simulation. Two peptides, namely AVP1145 and AVP1155, came out as promising candidates and hence were selected for 200 ns MD simulation for further validation, incorporating a DMPC-based membrane environment. In the long MD simulation, both AVP1155 and AVP1145 utilized multiple residues-mainly aromatic, acidic, and nonpolar residues-as interacting points to remain in contact with the nucleoprotein and formed predominantly hydrogen bonds along with hydrophobic and electrostatic interactions. However, AVP1155 proved to be superior to AVP1145 when its complex with nucleoprotein was analyzed in terms of root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessible surface area and free energy landscape. In a nutshell, the findings of this research may guide future studies in the development of selective peptide inhibitors of SARS-CoV-2 nucleoprotein. Supplementary Information: The online version contains supplementary material available at 10.1007/s11696-022-02514-4.

Large scale peptide screening against main protease of SARS CoV-2.

The COVID-19 pandemic has been a public health emergency, with deadly forms constantly emerging around the world, highlighting the dire need for highly effective antiviral therapeutics. Peptide therapeutics show significant potential for this viral disease due to their efficiency, safety, and specificity. Here, two thousand seven hundred eight antibacterial peptides were screened computationally targeting the Main protease (Mpro) of SARS CoV-2. Six top-ranked peptides according to their binding scores, binding pose were investigated by molecular dynamics to explore the interaction and binding behavior of peptide-Mpro complexes. The structural and energetic characteristics of Mpro-DRAMP01760 and Mpro-DRAMP01808 complexes fluctuated less during a 250 ns MD simulation. In addition, three peptides (DRAMP01760, DRAMP01808, and DRAMP01342) bind strongly to Mpro protein, according to the free energy landscape and principal component analysis. Peptide helicity and secondary structure analysis are in agreement with our findings. Interaction analysis of protein-peptide complexes demonstrated that Mpro's residue CYS145, HIS41, PRO168, GLU166, GLN189, ASN142, MET49, and THR26 play significant contributions in peptide-protein attachment. Binding free energy analysis (MM-PBSA) demonstrated the energy profile of interacting residues of Mpro in peptide-Mpro complexes. To summarize, the peptides DRAMP01808 and DRAMP01760 may be highly Mpro specific, resulting disruption in a viral replication and transcription. The results of this research are expected to assist future research toward the development of antiviral peptide-based therapeutics for Covid-19 treatment.

Phytochemicals-based targeting RdRp and main protease of SARS-CoV-2 using docking and steered molecular dynamic simulation: A promising therapeutic approach for Tackling COVID-19.

The ongoing COVID-19 pandemic has affected millions of people worldwide and caused substantial socio-economic losses. Few successful vaccine candidates have been approved against SARS-CoV-2; however, their therapeutic efficacy against the mutated strains of the virus remains questionable. Furthermore, the limited supply of vaccines and promising antiviral drugs have created havoc in the present scenario. Plant-based phytochemicals (bioactive molecules) are promising because of their low side effects and high therapeutic value. In this study, we aimed to screen for suitable phytochemicals with higher therapeutic value using the two most crucial proteins of SARS-CoV-2, the RNA-dependent RNA polymerase (RdRp) and main protease (Mpro). We used computational tools such as molecular docking and steered molecular dynamics simulations to gain insights into the different types of interactions and estimated the relative binding forces between the phytochemicals and their respective targets. To the best of our knowledge, this is the first report that not only involves a search for a therapeutic bioactive molecule but also sheds light on the mechanisms underlying target inhibition in terms of calculations of force and work needed to extractthe ligand from the pocket of its target. The complexes showing higher binding forces were subjected to 200 ns molecular dynamic simulations to check the stability of the ligand inside the binding pocket. Our results suggested that isoskimmiwallin and terflavin A are potential inhibitors of RdRp, whereas isoquercitrin and isoorientin are the lead molecules against Mpro. Collectively, our findings could potentially aid in the development of novel therapeutics against COVID-19.

Cysteine focused covalent inhibitors against the main protease of SARS-CoV-2.

In viral replication and transcription, the main protease (Mpro) of SARS-CoV-2 plays an important role and appears to be a vital target for drug design. In Mpro, there is a Cys-His catalytic dyad, and ligands that interact with the Cys145 assumed to be an effective approach to inhibit the Mpro. In this study, approximately 1400 cysteine-focused ligands were screened to identify the best candidates that can act as potent inhibitors against Mpro. Our results show that the selected ligands strongly interact with the key Cys145 and His41 residues. Covalent docking was performed for the selected candidates containing the acrylonitrile group, which can form a covalent bond with Cys145. All atoms molecular dynamics (MD) simulation was performed on the selected four inhibitors including L1, L2, L3 and L4 to validate the docking interactions. Our results were also compared with a control ligand, α-ketoamide (11r). Principal component analysis on structural and energy data obtained from the MD trajectories shows that L1, L3, L4 and α-ketoamide (11r) have structural similarity with the apo-form of the Mpro. Quantitative structure-activity relationship method was employed for pattern recognition of the best ligands, which discloses that ligands containing acrylonitrile and amide warheads can show better performance. ADMET analysis displays that our selected candidates appear to be safer inhibitors. Our combined studies suggest that the best cysteine focused ligands can help to design an effective lead drug for COVID-19 treatment. Communicated by Ramaswamy H. Sarma.

Identification of potent inhibitors against transmembrane serine protease 2 for developing therapeutics against SARS-CoV-2.

In viral binding and entry, the Spike(S) protein of SARS-CoV-2 uses transmembrane serine protease 2 (TMPRSS2) for priming to cleavage themselves. In this study, we have screened 'drug-like' 7476 ligands and found that over thirty ligands can effectively inhibit the TMPRSS-2 better than the control ligand. Finally, the three best drug agents L1, L2, and L6 were selected according to their average binding affinities and fitting score. These ligands interact with Asp435, Cys437, Ser436, Trp461, and Cys465 amino acid residues. The three best candidates and a reported drug Nafamostat mesylate (NAM) were selected to run 250 ns molecular dynamics (MD) simulations. Various properties of ligand-protein interactions obtained from MD simulation such as bonds, angle, dihedral, planarity, coulomb, and van der Waals (VdW) were used for principal component analysis (PCA) calculation. PCA discloses the evidence of the structural similarities to the corresponding complexes of L1, L2, and L6 with the complex of TMPRSS2(TM) and Nafamostat mesylate (TM-NAM). Moreover, Quantitative structure-activity relationship (QSAR) pattern recognition was generated using PCA for the investigation of structural similarities among the selected ligands. Multiple Linear Regression (MLR) model was built to predict the binding energy compared to the binding energy obtained from molecular docking. The MLR regression model reveals an accuracy of 80% for the prediction of the binding energy of ligands. ADMET analysis demonstrates that these drug agents are appeared to be safer inhibitors. These three ligands can be used as potential inhibitors against the TMPRSS2.Communicated by Ramaswamy H. Sarma.

A student led computational screening of peptide inhibitors against main protease of SARS-CoV-2.

The main protease of SARS-CoV-2 is a promising drug target due to its functional role as a catalytic dyad in mediating proteolysis during the viral life cycle. In this study, experimentally proven 14 HIV protease peptides were screened against the main protease of SARS-CoV-2. Fourteen middle and high school "student researchers" were trained on relevant computational tools, provided with necessary biological and chemical background and scientific article writing. They performed the primary screening via molecular docking and the best performing complexes were subjected to molecular dynamics simulations. Molecular docking revealed that HIP82 and HIP1079 can bind with the catalytic residues, however after molecular dynamics simulation only HIP1079 retained its interaction with the catalytic sites. The student researchers were also trained to write scientific article and were involved with drafting of the manuscript. This project provided the student researchers an insight into multi-disciplinary research in biology and chemistry, inspired them about practical approaches of computational chemistry in solving a real-world problem like a global pandemic. This project also serves as an example to introduce scientific inquiry, research methodology, critical thinking, scientific writing, and communication for high school students.

Remdesivir analogs against SARS-CoV-2 RNA-dependent RNA polymerase.

The COVID-19 pandemic has already taken many lives but is still continuing its spread and exerting jeopardizing effects. This study is aimed to find the most potent ligands from 703 analogs of remdesivir against RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus . RdRp is a major part of a multi-subunit transcription complex of the virus, which is essential for viral replication. In clinical trials, it has been found that remdesivir is effective to inhibit viral replication in Ebola and in primary human lung cell cultures; it effectively impedes replication of a broad-spectrum pre-pandemic bat coronaviruses and epidemic human coronaviruses. After virtual screening, 30 most potent ligands and remdesivir were modified with triphosphate. Quantum mechanics-based quantitative structure-activity relationship envisages the binding energy for ligands applying partial least square (PLS) regression. PLS regression remarkably predicts the binding energy of the effective ligands with an accuracy of 80% compared to the value attained from molecular docking. Two ligands (L4:58059550 and L28:126719083), which have more interactions with the target protein than the other ligands including standard remdesivir triphosphate, were selected for further analysis. Molecular dynamics simulation is done to assess the stability and dynamic nature of the drug-protein complex. Binding-free energy results via PRODIGY server and molecular mechanics/Poisson-Boltzmann surface area method depict that the potential and solvation energies play a crucial role. Considering all computational analysis, we recommend the best remdesivir analogs can be utilized for efficacy test through in vitro and in vivo trials against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Designing potent inhibitors against the multidrug resistance P-glycoprotein.

The multidrug transporter P-glycoprotein is an ATP binding cassette (ABC) exporter responsible for resistance to tumor cells during chemotherapy. This study was designed with computational approaches aimed at identifying the best potent inhibitors of P-glycoprotein. Although many compounds have been suggested to inhibit P-glycoprotein, however, their information on bioavailability, selectivity, ADMET properties, and molecular interactions has not been revealed. Molecular docking, ADMET analysis, molecular dynamics, Principal component analysis (PCA), and binding free energy calculations were performed. Two compounds D1 and D2 showed the best docking score against P-glycoprotein and both compounds have 4-thiazolidinone derivatives containing indolin-3 one moiety are novel anti-tumor compounds. ADMET calculation analysis predicted D1 and D2 to have acceptable pharmacokinetic properties. The MD simulation discloses that D1-P-glycoprotein and D2-P-glycoprotein complexes are in stable conformation as apo-form. Hydrophobic amino acid such as phenylalanine plays significant on the interactions of inhibitors. Principal component analysis shows that both complexes are relatively similar variables as apo-form except planarity and Columbo energy profile. In addition, Quantitative Structural Activity Relationship (QSAR) of the ligand candidates were subjected to the principal component analysis (PCA) for pattern recognition. Partial-least-square (PLS) regression analysis was further utilized to model drug candidates' QSAR for subsequent prediction of the binding energy of validated drug candidates. PCA revealed groupings of the drug candidates based on the similarity or differences in drug candidates QSAR. Moreover, the developed PLS regression accurately predicted the values of the binding energy of drug candidates, with low residual error of prediction.Communicated by Ramaswamy H. Sarma.

Structure and dynamics of membrane protein in SARS-CoV-2.

SARS-CoV-2 membrane (M) protein performs a variety of critical functions in virus infection cycle. However, the expression and purification of membrane protein structure is difficult despite tremendous progress. In this study, the 3 D structure is modeled followed by intensive validation and molecular dynamics simulation. The lack of suitable homologous templates (>30% sequence identities) leads us to construct the membrane protein models using template-free modeling (de novo or ab initio) approach with Robetta and trRosetta servers. Comparing with other model structures, it is evident that trRosetta (TM-score: 0.64; TM region RMSD: 2 Å) can provide the best model than Robetta (TM-score: 0.61; TM region RMSD: 3.3 Å) and I-TASSER (TM-score: 0.45; TM region RMSD: 6.5 Å). 100 ns molecular dynamics simulations are performed on the model structures by incorporating membrane environment. Moreover, secondary structure elements and principal component analysis (PCA) have also been performed on MD simulation data. Finally, trRosetta model is utilized for interpretation and visualization of interacting residues during protein-protein interactions. The common interacting residues including Phe103, Arg107, Met109, Trp110, Arg131, and Glu135 in the C-terminal domain of M protein are identified in membrane-spike and membrane-nucleocapsid protein complexes. The active site residues are also predicted for potential drug and peptide binding. Overall, this study might be helpful to design drugs and peptides against the modeled membrane protein of SARS-CoV-2 to accelerate further investigation. Communicated by Ramaswamy H. Sarma.

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools.

Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

Repurposing fusion inhibitor peptide against SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving. Although several vaccines were approved, this pandemic is still a major threat to public life. Till date, no established therapies are available against SARS-CoV-2. Peptide inhibitors hold great promise for this viral pathogen due to their efficacy, safety, and specificity. In this study, seventeen antiviral peptides which were known to inhibit SARS-CoV-1 are collected and computationally screened against heptad repeat 1 (HR1) of the SARS-CoV-2 spike protein (S2). Out of 17 peptides, Fp13 and Fp14 showed better binding affinity toward HR1 compared to a control peptide EK1 (a modified pan-coronavirus fusion inhibitor) in molecular docking. To explore the time-dependent interactions of the fusion peptide with HR1, molecular dynamics simulation was performed incorporating lipid membrane. During 100 ns MD simulation, structural and energy parameters of Fp13-HR1 and Fp14-HR1 complexes demonstrated lower fluctuations compared to the control EK1-HR1 complex. Furthermore, principal component analysis and free energy landscape study revealed that these two peptides (Fp13 and Fp14) strongly bind to the HR1 with higher affinity than that of control EK1. Tyr917, Asn919, Gln926, lys933, and Gln949 residues in HR1 protein were found to be crucial residues for peptide interaction. Notably, Fp13, Fp14 showed reasonably better binding free energy and hydrogen bond contribution than that of EK1. Taken together, Fp13 and Fp14 peptides may be highly specific for HR1 which can potentially prevent the formation of the fusion core and could be further developed as therapeutics for treatment or prophylaxis of SARS-CoV-2 infection.

A comprehensive computational and principal component analysis on various choline chloride-based deep eutectic solvents to reveal their structural and spectroscopic properties.

In this study, the quantum chemical properties, nonbonding interactions, and spectroscopic insights of a wide variety of choline chloride (ChCl)-based deep eutectic solvents were investigated employing molecular dynamics (MD), density functional theory, and spectroscopic analyses. Nine experimentally reported ChCl-based deep eutectic solvents (DESs) were selected for this study where ChCl was common in all the DESs and the hydrogen bond donors (HBDs) were varied. The most energetically favorable cluster was selected using MD simulation followed by density functional theory calculation. The most stable cluster structures were fully optimized, and their quantum chemical properties and IR spectra were computed at the ωB97XD/6-31G++(d,p) level of theory. Principal component analysis was performed to distinguish their behavioral differences and to find out if any correlation exists among the 1:1 and 1:2 clusters. The atom-atom radial distribution functions based on MD simulations revealed that several hydrogen bonds were formed among the donor and acceptor molecules. However, the most prominent hydrogen bonds were found to be N-HHBD⋯Cl- for ChCl:U, ChCl:TU, and ChCl:Ace and O-HHBD⋯Cl- for ChCl:Glu, ChCl:Ma, ChCl:Ox, ChCl:Gly, and ChCl:Phe. Both N-HHBD⋯Cl- and O-HHBD⋯Cl- were major interactions for ChCl:Pro, where Cl- worked as a bridge between Ch+ and the respective donors. In addition, the -OH of Ch+ showed strong intermolecular interactions with the acceptor groups of the donor molecules, such as C=O and O-H. This study has tried to extract a pattern of the contributions of HBDs by comparing the structural, spectroscopic, and thermodynamic properties of ChCl-based DESs, which have also been successfully correlated with the intermolecular interactions.