Per-residue Energy Decomposition Analysis Research Articles

3D-QSAR, docking and molecular dynamics simulations of novel Pyrazolo-pyridazinone derivatives as covalent inhibitors of FGFR1: a scientific approach for possible anticancer agents

Developing highly potent covalent inhibitors of Fibroblast growth factor receptors 1 (FGFR1) has always been a challenging task. In the current study, various computational techniques, such as 3D-QSAR, covalent docking, fingerprinting analysis, MD simulation followed by MMGB/PBSA, and per-residue energy decomposition analysis were used to explore the binding mechanism of pyrazolo[3,4-d]pyridazinone derivatives to FGFR1. The high q2 and r2 values for the CoMFA and CoMSIA models, suggest that the constructed 3D-QSAR models could reliably predict the bioactivities of FGFR1 inhibitors. The structural requirements revealed by the model’s contour maps were strategically used to computationally create an in-house library of more than 100 new FGFR1 inhibitors using the R-group exploration technique implemented in the SparkTM software. The compounds from the in-house library were also mapped in the 3D-QSAR model that predicts comparable pIC50 values with the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to reveal the fundamentals to design potent FGFR1 covalent inhibitors. The estimated binding free energies (MMGB/PBSA) for the selected compounds were in agreement with the experimental value ranking of their binding affinities towards FGFR1. Furthermore, per-residue energy decomposition analysis has identified Arg627 and Glu531 to contribute significantly in improved binding affinity of compound W16. During ADME analysis, the majority of in-house library compounds exhibited pharmacokinetic properties superior to those of experimentally produced compounds. These new compounds may help researchers better understand FGFR1 inhibition and lead to the creation of novel, potent FGFR1 inhibitors. Communicated by Ramaswamy H. Sarma

Molecular modeling of pyrrolo-pyrimidine based analogs as potential FGFR1 inhibitors: a scientific approach for therapeutic drugs

Fibroblast growth factor receptors 1 (FGFR1) is an emerging target for the development of anticancer drugs. Uncontrolled expression of FGFR1 is strongly associated with a number of different types of cancers. Apart from a few FGFR inhibitors, the FGFR family members have not been thoroughly studied to produce clinically effective anticancer drugs. The application of proper computational techniques may aid in understanding the mechanism of protein–ligand complex formation, which may provide a better notion for developing potent FGFR1 inhibitors. In this study, a variety of computational techniques, including 3D-QSAR, flexible docking and MD simulation followed by MMGB/PBSA, H-bonds and distance analysis, have been performed to systematically explore the binding mechanism of pyrrolo-pyrimidine derivatives against FGFR1. The 3D-QSAR model was generated to deduce the structural determinants of FGFR1 inhibition. The high q2 and r2 values for the CoMFA and CoMSIA models indicated that the created 3D-QSAR models could reliably predict the bioactivities of FGFR1 inhibitors. The computed binding free energies (MMGB/PBSA) for the selected compounds were consistent with the ranking of their experimental binding affinities against FGFR1. Furthermore, per-residue energy decomposition analysis revealed that the residues Lys514 in catalytic region, Asn568, Glu571 in solvent accessible portion and Asp641 in DFG motif exhibited a strong tendency to mediate ligand–protein interactions through the hydrogen bonding and Van Der Waals interactions. These findings may benefit researchers in gaining better knowledge of FGFR1 inhibition and may serve as a guideline for the development of novel and highly effective FGFR1 inhibitors.Communicated by Ramaswamy H. Sarma

Insights Into Resveratrol as an Inhibitor Against Aβ1-42 Peptide Aggregation: A Molecular Dynamics Simulation Study

Background: Resveratrol (RSV), a polyphenolic compound, is reported to have anti-aggregation properties against Amyloid-beta peptides. It is, therefore, significant to understand the mechanism of inhibition of Aβ1-42 peptide aggregation by the RSV at the molecular level. We have used Molecular docking along with Molecular dynamics (MD) simulation techniques to address the role of RSV in the inhibition of Aβ1-42 pep-tide aggregation. Objective: To understand the role of Resveratrol on the Aβ1-42 peptide aggregation. Method: In this computational study, we have docked the RSV to Aβ1-42 peptide using Molecular Docking software and then performed MD simulation for the Aβ1-42 peptide monomer Aβ1-42 peptide-RSV complex using the AMBER force field. From the analysis of MD trajectories, we obtained salient structural features and determined the Binding Free Energy(BFE) and Per-residue Energy Decomposition Analysis (PRED) using MM-PBSA/GBSA method. Results: The secondary structure and the conformational analysis obtained from MD trajectories show that the binding of RSV with the Aβ1-42 peptide monomer causes an increase in the helical content in the structure of the Aβ1-42 peptide. The BFE and PRED results show a high binding affinity (GBtotal=-11.07 kcal mol-1; PBtotal= -1.82 kcal mol-1) of RSV with Aβ1-42 peptide. Also, we found the RSV to interact with cru-cial residues (Asp 23 and Lys 28) of the Aβ1-42 peptide. These residues play a signif-icant role in facilitating the formation of toxic amyloid oligomers and amyloid fibrils. The salt bridge interaction between these residues D23–K28 was found to be destabi-lized in the Aβ1-42 peptide when it is complexed with RSV. Conclusion: In summary, it can be concluded that Resveratrol greatly aids the preven-tion of Aβ1-42 peptide aggregation. Therefore, it can be considered a possible drug candidate for therapeutic strategies for Alzheimer’s disease.

In silico analysis of SOD1 aggregation inhibition modes of tertiary amine pyrazolone and pyrano coumarin ferulate as ALS drug candidates.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, the familial form (fALS) of which is often cognate to mutations in the antioxidant enzyme Cu/Zn superoxide dismutase 1 (SOD1) leading to misfolding and aggregation. Two small molecules, a tertiary amine pyrazolone (TAP) and a pyrano coumarin ferulate (PCF) were suggested to be ALS drug candidates following experimental observation of their ability to inhibit SOD1 protein misfolding and aggregation. The present work aims at computational investigation of these experimentally proposed drug candidates to gain insight into their mechanism of SOD1 misfolding and aggregation inhibition. On the basis of molecular docking, molecular dynamics simulation, MM-PBSA and per-residue energy decomposition analysis, we examined the specific interactions of TAP and PCF with three probable binding sites of SOD1, namely, dimeric interface cavity, W32 and, UMP binding sites. Results suggest that the binding of TAP at W32 and at UMP sites are least probable due to absence of any favorable interaction. The binding of TAP to dimeric cavity is also unstable due to strong unfavorable interactions. In case of PCF, binding at the UMP site is least probable while binding at dimeric cavity is accompanied by unfavorable interactions. PCF, however, exhibits stable binding with the W32 binding site of SOD1 by stabilizing the solvent accessible hydrophobic residues, which otherwise would have acted as contact points for aggregation. Thus the results imply that compound PCF functions as an inhibitior of SOD1 misfolding/aggregation through direct interaction with the protein SOD1 at the W32 binding site. However, TAP is likely to act as an inhibitor through a different mechanism rather than direct interaction with the protein SOD1. These results apart from reinforcing previous experimental findings, shed light on the probable mechanism of action of the proposed drug candidates.

Bioinformatic analysis of highly consumed phytochemicals as P-gp binders to overcome drug-resistance.

P-glycoprotein (P-gp) is an adenosine triphosphate (ATP)-dependent membrane efflux pump for protecting cells against xenobiotic compounds. Unfortunately, overexpressed P-gp in neoplastic cells prevents cell entry of numerous chemotherapeutic agents leading to multidrug resistance (MDR). MDR cells may be re-sensitized to chemotherapeutic drugs via P-gp inhibition/modulation. Side effects of synthetic P-gp inhibitors encouraged the development of natural products. Molecular docking and density functional theory (DFT) calculations were used as fast and accurate computational methods to explore a structure binding relationship of some dietary phytochemicals inside distinctive P-gp binding sites (modulatory/inhibitory). For this purpose, top-scored docked conformations were subjected to per-residue energy decomposition analysis in the B3LYP level of theory with a 6-31g (d, p) basis set by Gaussian98 package. Consecutive application of computational techniques revealed binding modes/affinities of nutritive phytochemicals within dominant binding sites of P-gp. Blind docking scores for best-ranked compounds were superior to verapamil and rhodamine-123. Pairwise amino acid decomposition of superior docked conformations revealed Tyr303 as an important P-gp binding residue. DFT-based induced polarization analysis revealed major electrostatic fluctuations at the atomistic level and confirmed larger effects for amino acids with energy-favored binding interactions. Conformational analysis exhibited that auraptene and 7,4',7'',4'''-tetra-O-methylamentoflavone might not necessarily interact to P-gp binding sites through minimum energy conformations. Although there are still many hurdles to overcome, obtained results may propose a few nutritive phytochemicals as potential P-gp binding agents. Moreover; top-scored derivatives may have the chance to exhibit tumor chemo-sensitizing effects.

Atomistic insights into the binding of SARS-CoV-2 spike receptor binding domain with the human ACE2 receptor: The importance of residue 493

SARS-CoV-2 is a coronavirus that has created a global pandemic. The virus contains a spike protein which has been shown to bind to the ACE2 receptor on the surface of human cells. Vaccines have been developed that recognize elements of the SARS-CoV-2 spike protein and they have been successful in preventing infection. Recently, the Omicron variant of the SARS-CoV-2 virus was reported and quickly became a variant of concern due to its transmissibility. This variant contained an unusually large number (32) of point mutations, of which 15 of those mutations are in the receptor binding domain of the spike protein. While several computational and experimental investigations comparing the binding of the Omicron and wild type RBD to the human ACE2 receptor have been conducted, many of these report contradictory findings. In order to assess the differential binding ability, we conducted 2 μs of classical molecular dynamics (cMD) simulation to estimate the binding affinities and behaviors. Based upon MM-GBSA binding affinity, per-residue energy decomposition analysis, center of mass distance measurements, ensemble clustering, pairwise residue decomposition and hydrogen bonding analysis, our results suggest that a single point mutation is responsible for the enhanced binding of the Omicron mutant relative to the WT. While the 15-point mutations in the receptor binding domain contribute positively and negatively to the affinity of the spike protein for the human ACE2 receptor, it is the point mutation Q493R that confers enhanced binding while the Q493K mutation results in similar binding. The MM-GBSA binding estimations over a 2 μs trajectory, suggest that the wild type binds to ACE2 with a value of −29.69 kcal/mol while the Q493K and Q493R Omicron mutants bind with energy values of −26.67 and −34.56 kcal/mol, respectively. These values are significantly different, given the error estimates associated with the MM-GBSA method. In general, while some mutations increase binding, more mutations diminish binding, leading to an overall similar picture of binding for Q493K and enhanced binding for Q493R.

Identification of defactinib derivatives targeting focal adhesion kinase using ensemble docking, molecular dynamics simulations and binding free energy calculations

Focal adhesion kinase (FAK) belongs to the nonreceptor tyrosine kinases, which selectively phosphorylate tyrosine residues on substrate proteins. FAK is associated with bladder, esophageal, gastric, neck, breast, ovarian and lung cancers. Thus, FAK has been considered as a potential target for tumor treatment. Currently, there are six adenosine triphosphate (ATP)-competitive FAK inhibitors tested in clinical trials but no approved inhibitors targeting FAK. Defactinib (VS-6063) is a second-generation FAK inhibitor with an IC50 of 0.6 nM. The binding model of VS-6063 with FAK may provide a reference model for developing new antitumor FAK-targeting drugs. In this study, the VS-6063/FAK binding model was constructed using ensemble docking and molecular dynamics simulations. Furthermore, the molecular mechanics/generalized Born (GB) surface area (MM/GBSA) method was employed to estimate the binding free energy between VS-6063 and FAK. The key residues involved in VS-6063/FAK binding were also determined using per-residue energy decomposition analysis. Based on the binding model, VS-6063 could be separated into seven regions to enhance its binding affinity with FAK. Meanwhile, 60 novel defactinib-based compounds were designed and verified using ensemble docking. Overall, the present study improves our understanding of the binding mechanism of human FAK with VS-6063 and provides new insights into future drug designs targeting FAK. Communicated by Ramaswamy H. Sarma

Computational Insights into the Sequence-Activity Relationships of the NGF(1-14) Peptide by Molecular Dynamics Simulations.

The Nerve Growth Factor (NGF) belongs to the neurothrophins protein family involved in the survival of neurons in the nervous system. The interaction of NGF with its high-affinity receptor TrkA mediates different cellular pathways related to Alzheimer’s disease, pain, ocular dysfunction, and cancer. Therefore, targeting NGF-TrkA interaction represents a valuable strategy for the development of new therapeutic agents. In recent years, experimental studies have revealed that peptides belonging to the N-terminal domain of NGF are able to partly mimic the biological activity of the whole protein paving the way towards the development of small peptides that can selectively target specific signaling pathways. Hence, understanding the molecular basis of the interaction between the N-terminal segment of NGF and TrkA is fundamental for the rational design of new peptides mimicking the NGF N-terminal domain. In this study, molecular dynamics simulation, binding free energy calculations and per-residue energy decomposition analysis were combined in order to explore the molecular recognition pattern between the experimentally active NGF(1–14) peptide and TrkA. The results highlighted the importance of His4, Arg9 and Glu11 as crucial residues for the stabilization of NGF(1–14)-TrkA interaction, thus suggesting useful insights for the structure-based design of new therapeutic peptides able to modulate NGF-TrkA interaction.

FastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation.

Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein-ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein-ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.

Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

In Silico Mutagenesis-Based Remodelling of SARS-CoV-1 Peptide (ATLQAIAS) to Inhibit SARS-CoV-2: Structural-Dynamics and Free Energy Calculations.

The prolific spread of COVID-19 caused by a novel coronavirus (SARS-CoV-2) from its epicenter in Wuhan, China, to every nook and cranny of the world after December 2019, jeopardize the prevailing health system in the world and has raised serious concerns about human safety. Multi-directional efforts are made to design small molecule inhibitors, and vaccines and many other therapeutic options are practiced, but their final therapeutic potential is still to be tested. Using the old drug or vaccine or peptides could aid this process to avoid such long experimental procedures. Hence, here, we have repurposed a small peptide (ATLQAIAS) from the previous study, which reported the inhibitory effects of this peptide. We used in silico mutagenesis approach to design more peptides from the native wild peptide, which revealed that substitutions (T2W, T2Y, L3R, and A5W) could increase the binding affinity of the peptide towards the 3CLpro. Furthermore, using MD simulation and free energy calculation confirmed its dynamics stability and stronger binding affinities. Per-residue energy decomposition analysis revealed that the specified substitution significantly increased the binding affinity at the residue level. Our wide-ranging analyses of binding affinities disclosed that our designed peptide owns the potential to hinder the SARS-CoV-2 and will reduce the progression of SARS-CoV-2-borne pneumonia. Our research strongly suggests the experimental and clinical validation of these peptides to curtail the recent corona outbreak.Graphic abstract

Identification of 13 Guanidinobenzoyl- or Aminidinobenzoyl-Containing Drugs to Potentially Inhibit TMPRSS2 for COVID-19 Treatment.

Positively charged groups that mimic arginine or lysine in a natural substrate of trypsin are necessary for drugs to inhibit the trypsin-like serine protease TMPRSS2 that is involved in the viral entry and spread of coronaviruses, including SARS-CoV-2. Based on this assumption, we identified a set of 13 approved or clinically investigational drugs with positively charged guanidinobenzoyl and/or aminidinobenzoyl groups, including the experimentally verified TMPRSS2 inhibitors Camostat and Nafamostat. Molecular docking using the C-I-TASSER-predicted TMPRSS2 catalytic domain model suggested that the guanidinobenzoyl or aminidinobenzoyl group in all the drugs could form putative salt bridge interactions with the side-chain carboxyl group of Asp435 located in the S1 pocket of TMPRSS2. Molecular dynamics simulations further revealed the high stability of the putative salt bridge interactions over long-time (100 ns) simulations. The molecular mechanics/generalized Born surface area-binding free energy assessment and per-residue energy decomposition analysis also supported the strong binding interactions between TMPRSS2 and the proposed drugs. These results suggest that the proposed compounds, in addition to Camostat and Nafamostat, could be effective TMPRSS2 inhibitors for COVID-19 treatment by occupying the S1 pocket with the hallmark positively charged groups.

In silico identification of prolyl hydroxylase inhibitor by per-residue energy decomposition-based pharmacophore approach.

Hypoxia is an effective preconditioning stimulus and many cellular responses to hypoxia are mediated through a transcription control complex termed the hypoxia-inducible factor (HIF). The stability and activation of HIF are governed by HIF prolyl-4-hydroxylases 2 (PHD2). Hence, the development of a small molecule inhibitor for prolyl hydroxylase has been suggested as a potentially useful therapeutic strategy for the treatment of oxidative/ischemic stress conditions. Thus, to unveil a novel human PHD2 inhibitor, a custom-based virtual screening was carried out to identify the potential inhibitors against PHD2 based on; (1) the per-residue energy decomposition (PRED)-based pharmacophore model, (2) molecular docking, and(3) MD approaches. The PREDanalysis was performed to identify the common interaction pattern of HIF fragment (5L9B) and crystallized ligand (4JZR) to develop a relevant accurate allosteric pharmacophore model. The custom pharmacophore model (AAARR) was developed and further used to screen multiple databases. The docking was performed as a secondary strategy for screening the pharmacophore hits. Furthermore, the docked complexes were screened by molecular dynamics (MD) simulation and molecular mechanics/generalized Born surface area (MM-GBSA) based binding free energy calculations to determine the binding energy of the inhibitors and to identify crucial interaction energy fingerprint. One hit has demonstrated good binding free energy and a better binding affinity for PHD2 compared to the other four selected ligands. Thus, the results obtained from pharmacophore, docking, and MD simulations depicted that linker length and metal binding in the scaffold could be effectively used as a potent inhibitor toward human PHD2 in AD therapeutics.

Comparative Study of Interactions between Human cGAS and Inhibitors: Insights from Molecular Dynamics and MM/PBSA Studies.

Recent studies have identified cyclic GMP-AMP synthase (cGAS) as an important target for treating autoimmune diseases, and several inhibitors of human cGAS (hcGAS) and their structures in complexation with hcGAS have been reported. However, the mechanisms via which these inhibitors interact with hcGAS are not completely understood. Here, we aimed to assess the performance of molecular mechanics/Poisson–Boltzmann solvent-accessible surface area (MM/PBSA) in evaluating the binding affinity of various hcGAS inhibitors and to elucidate their detailed interactions with hcGAS from an energetic viewpoint. Using molecular dynamics (MD) simulation and MM/PBSA approaches, the estimated free energies were in good agreement with the experimental ones, with a Pearson’s correlation coefficient and Spearman’s rank coefficient of 0.67 and 0.46, respectively. In per-residue energy decomposition analysis, four residues, K362, R376, Y436, and K439 in hcGAS were found to contribute significantly to the binding with inhibitors via hydrogen bonding, salt bridges, and various π interactions, such as π· · ·π stacking, cation· · ·π, hydroxyl· · ·π, and alkyl· · ·π interactions. In addition, we discussed other key interactions between specific residues and ligands, in particular, between H363 and JUJ, F379 and 9BY, and H437 and 8ZM. The sandwiched structures of the inhibitor bound to the guanidinium group of R376 and the phenyl ring of Y436 were also consistent with the experimental data. The results indicated that MM/PBSA in combination with other virtual screening methods, could be a reliable approach to discover new hcGAS inhibitors and thus is valuable for potential treatments of cGAS-dependent inflammatory diseases.

A recursive molecular docking coupled with energy-based pose-rescoring and MD simulations to identify hsGC βH-NOX allosteric modulators for cardiovascular dysfunctions

Modulating the activity of human soluble guanylate cyclase (hsGC) through allosteric regulation of the βH-NOX domain has been considered as an immediate treatment for cardiovascular disorder (CVDs). Currently available βH-NOX domain-specific agonists including cinaciguat are unable to deal with the conundrum raised due to oxidative stress in the case of CVDs and their associated comorbidities. Therefore, the idea of investigating novel compounds for allosteric regulation of hsGC activation has been rekindled to circumvent CVDs. Current study aims to identify novel βH-NOX domain-specific compounds that can selectively turn on sGC functions by modulating the conformational dynamics of the target protein. Through a comprehensive computational drug-discovery approach, we first executed a target-based performance assessment of multiple docking (PLANTS, QVina, LeDock, Vinardo, Smina) scoring functions based on multiple performance metrices. QVina showed the highest capability of selecting true-positive ligands over false positives thus, used to screen 4.8 million ZINC15 compounds against βH-NOX domain. The docked ligands were further probed in terms of contact footprint and pose reassessment through clustering analysis and PLANTS docking, respectively. Subsequently, energy-based AMBER rescoring of top 100 low-energy complexes, per-residue energy decomposition analysis, and ADME-Tox analysis yielded the top three compounds i.e. ZINC000098973660, ZINC001354120371, and ZINC000096022607. The impact of three selected ligands on the internal structural dynamics of the βH-NOX domain was also investigated through molecular dynamics simulations. The study revealed potential electrostatic interactions for better conformational dialogue between βH-NOX domain and allosteric ligands that are critical for the activation of hsGC as compared to the reference compound.

Drug similarity and structure-based screening of medicinal compounds to target macrodomain-I from SARS-CoV-2 to rescue the host immune system: a molecular dynamics study

The outbreak of the recent coronavirus (SARS-CoV-2), which causes a severe pneumonia infection, first identified in Wuhan, China, imposes significant risks to public health. Around the world, researchers are continuously trying to identify small molecule inhibitors or vaccine candidates by targeting different drug targets. The SARs-CoV-2 macrodomain-I, which helps in viral replication and hijacking the host immune system, is also a potential drug target. Hence, this study targeted viral macrodomain-I by using drug similarity, virtual screening, docking and re-docking approaches. A total of 64,043 compounds were screened, and potential hits were identified based on the docking score and interactions with the key residues. The top six hits were subjected to molecular dynamics simulation and Free energy calculations and repeated three times each. The per-residue energy decomposition analysis reported that these compounds significantly interact with Asp22, Ala38, Asn40, Val44, Phe144, Gly46, Gly47, Leu127, Ser128, Gly130, Ile131, Phe132 and Ala155 which are the critical active site residues. Here, we also used ADPr as a positive control to compare our results. Our results suggest that our identified hits by using such a complicated computational pipeline could inhibit the SARs-CoV-2 by targeting the macrodomain-1. We strongly recommend the experimental testing of these compounds, which could rescue the host immune system and could help to contain the disease caused by SARs-CoV-2. Communicated by Ramaswamy H. Sarma

Structural insights into the mechanism of RNA recognition by the N-terminal RNA-binding domain of the SARS-CoV-2 nucleocapsid phosphoprotein

The emergence of recent SARS-CoV-2 has become a global health issue. This single-stranded positive-sense RNA virus is continuously spreading with increasing morbidities and mortalities. The proteome of this virus contains four structural and sixteen nonstructural proteins that ensure the replication of the virus in the host cell. However, the role of phosphoprotein (N) in RNA recognition, replicating, transcribing the viral genome, and modulating the host immune response is indispensable. Recently, the NMR structure of the N-terminal domain of the Nucleocapsid Phosphoprotein has been reported, but its precise structural mechanism of how the ssRNA interacts with it is not reported yet. Therefore, here, we have used an integrated computational pipeline to identify the key residues, which play an essential role in RNA recognition. We generated multiple variants by using an alanine scanning strategy and performed an extensive simulation for each system to signify the role of each interfacial residue. Our analyses suggest that residues T57A, H59A, S105A, R107A, F171A, and Y172A significantly affected the dynamics and binding of RNA. Furthermore, per-residue energy decomposition analysis suggests that residues T57, H59, S105 and R107 are the key hotspots for drug discovery. Thus, these residues may be useful as potential pharmacophores in drug designing.

Unveiling a New Era in Malaria Therapeutics: A Tailored Molecular Approach Towards the Design of Plasmepsin IX Inhibitors.

The invasive tactics employed by the malarial parasite renders malaria a global health threat, further impeding the effective treatment of the mosquito borne-parasitic disease. Although there have been countless efforts directed towards the development of effective therapeutics, factors such as emerging strains of drug resistance, enhanced toxicity and poor pharmacokinetic properties of current therapeutics has hampered the drug discovery process resulting in the spread of this parasitic disease. A promising target of the most lethal strain of the Plasmodium species that plays a predicted role in erythrocyte invasion of the virulent malarial parasite is aspartic protease IX commonly referred to Plasmepsin IX. The integration of computer aided-drug design platforms has revolutionized the 21st century and has opened avenues to render a final "knock out" in the elimination and eradication of this parasitic disease Hitherto, this is the first attempt directed towards the design of therapeutics tailored explicitly to Plasmepsin IX. A potent peptidomimetic inhibitor referred to as 49c which is a known inhibitor of Plasmepsin II, has recently exhibited potent inhibitory activity against Plasmepsin IX. In-silico structural and physicochemical inspection of 49c displayed poor pharmacokinetic properties thus paving the way for the development of tailored inhibitors with desirable therapeutic properties against Plasmepsin IX. In this study we implement the pharmacophore model approach in combination with per-residue energy decomposition analysis to serve as a powerful cornerstone, that may assist medicinal experts in the composition of multifunctional therapeutics that may predispose factors such as cross-resistance and toxicity, with enhanced pharmacokinetic properties.

Prediction and validation of HIV-1 gp41 ecto-transmembrane domain post-fusion trimeric structure using molecular modeling

The glycoproteins on the surface of human immunodeficiency virus (HIV) undergoes cascade of conformational transitions to evade the human immune system. The virus replicates inside the host and infects the T-cells instigating acquired immunodeficiency syndrome (AIDS). The glycoprotein 41 (gp41) of HIV helps to mediate the fusion of virus and host membranes. The detailed mechanism of host cell invasion by virus remains obscure due to the unavailability of experimental structure of complete gp41. In the current study, the post-fusion (PoF) trimeric structure of ecto-domain including transmembrane domain of gp41 was modeled using multiple homologous templates of Simian immunodeficiency virus (SIV) and HIV-1. In order to validate the gp41 model, interactions of three peptide inhibitors: T20, C37 and C34; were studied using all-atom molecular dynamics (MD) simulations, binding free-energy calculation and per-residue energy decomposition analysis. The binding free energy calculated using MM-PBSA (Molecular Mechanics Poisson-Boltzmann surface area) method predicts maximum affinity for C34 and minimum by T20 for gp41, which is in good agreement with the available computational and experimental studies. The van der Waals interaction is a dominant contributor for the peptide-gp41 complexes. The per-residue decomposition of energy confirmed the role of Trp117, Trp120 and Ile124, present in C34 and C37, for the strong hydrophobic interactions with the deep pocket localized around the N-terminal of gp41, which is lacking in T20. The HIV-1 gp41 structure developed in this work can be used in future study to gain insight into the mechanism of virus invasion and probing potent inhibitor to eliminate AIDS.Communicated by Ramaswamy H. Sarma

A Synergistic Combination Against Chronic Myeloid Leukemia: An Intra-molecular Mechanism of Communication in BCR-ABL1 Resistance.

The constitutive BCR-ABL1 active protein fusion has been identified as the main cause of chronic myeloid leukemia. The emergence of T334I and D381N point mutations in BCR-ABL1 confer drug resistance. Recent experimental studies show a synergistic effect in suppressing this resistance when Nilotinib and Asciminib are co-administered to target both the catalytic and allosteric binding site of BCR-ABL1 oncoprotein, respectively. However, the structural mechanism by which this synergistic effect occurs has not been clearly elucidated. To obtain insight into the observed synergistic effect, molecular dynamics simulations have been employed to investigate the inhibitory mechanism as well as the structural dynamics that characterize this effect. Structural dynamic analyses indicate that the synergistic binding effect results in a more compact and stable protein conformation. In addition, binding free energy calculation suggests a dominant energy effect of nilotinib during co-administration. van der Waals energy interactions were observed to be the main energy component driving this synergistic effect. Furthermore, per-residue energy decomposition analysis identified Glu481, Ser453, Ala452, Tyr454, Phe401, Asp400, Met337, Phe336, Ile334, And Val275 as key residues that contribute largely to the synergistic effect. The findings highlighted in this study provide a molecular understanding of the dynamics and mechanisms that mediate the synergistic inhibition in BCR-ABL1 protein in chronic myeloid leukemia treatment.