Structural-dynamic insights into the H. pylori cytotoxin-associated gene A (CagA) and its abrogation to interact with the tumor suppressor protein ASPP2 using decoy peptides

Identification of novel NLRP3 inhibitors as therapeutic options for epilepsy by machine learning-based virtual screening, molecular docking and biomolecular simulation studies

The NOD-Like Receptor Protein-3 (NLRP3) inflammasome is a key therapeutic target for the treatment of epilepsy and has been reported to regulate inflammation in several neurological diseases. In this study, a machine learning-based virtual screening strategy has investigated candidate active compounds that inhibit the NLRP3 inflammasome. As machine learning-based virtual screening has the potential to accurately predict protein-ligand binding and reduce false positives outcomes compared to traditional virtual screening. Briefly, classification models were created using Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) machine learning methods. To determine the most crucial features of a molecule's activity, feature selection was carried out. By utilizing 10-fold cross-validation, the created models were analyzed. Among the generated models, the RF model obtained the best results as compared to others. Therefore, the RF model was used as a screening tool against the large chemical databases. Molecular operating environment (MOE) and PyRx software's were applied for molecular docking. Also, using the Amber Tools program, molecular dynamics (MD) simulation of potent inhibitors was carried out. The results showed that the KNN, SVM, and RF accuracy was 0.911 %, 0.906 %, and 0.946 %, respectively. Moreover, the model has shown sensitivity of 0.82 %, 0.78 %, and 0.86 % and specificity of 0.95 %, 0.96 %, and 0.98 % respectively. By applying the model to the ZINC and South African databases, we identified 98 and 39 compounds, respectively, potentially possessing anti-NLRP3 activity. Also, a molecular docking analysis produced ten ZINC and seven South African compounds that has comparable binding affinities to the reference drug. Moreover, MD analysis of the two complexes revealed that the two compounds (ZINC000009601348 and SANC00225) form stable complexes with varying amounts of binding energy. The in-silico studies indicate that both compounds most likely display their inhibitory effect by inhibiting the NLRP3 protein.

In silico design of peptide inhibitors for Dengue virus to treat Dengue virus-associated infections

Dengue virus is a single positive-strand RNA virus that is composed of three structural proteins including capsid, envelope, and precursor membrane while seven non-structural proteins (NS1, NS2A, NS2B, NS3A, NS3B, NS4, and NS5). Dengue is a viral infection caused by the dengue virus (DENV). DENV infections are asymptomatic or produce only mild illness. However, DENV can occasionally cause more severe cases and even death. There is no specific treatment for dengue virus infections. Therapeutic peptides have several important advantages over proteins or antibodies: they are small in size, easy to synthesize, and have the ability to penetrate the cell membranes. They also have high activity, specificity, affinity, and less toxicity. Based on the known peptide inhibitor, the current study designs peptide inhibitors for dengue virus envelope protein using an alanine and residue scanning technique. By replacing I21 with Q21, L14 with H14, and V28 with K28, the binding affinity of the peptide inhibitors was increased. The newly designed peptide inhibitors with single residue mutation improved the binding affinity of the peptide inhibitors. The inhibitory capability of the new promising peptide inhibitors was further confirmed by the utilization of MD simulation and free binding energy calculations. The molecular dynamics simulation demonstrated that the newly engineered peptide inhibitors exhibited greater stability compared to the wild-type peptide inhibitors. According to the binding free energies MM(GB)SA of these developed peptides, the first peptide inhibitor was the most effective against the dengue virus envelope protein. All peptide derivatives had higher binding affinities for the envelope protein and have the potential to treat dengue virus-associated infections. In this study, new peptide inhibitors were developed for the dengue virus envelope protein based on the already reported peptide inhibitor.

Molecular Mechanisms and Treatment Strategies for Helicobacter pylori-Induced Gastric Carcinogenesis and Mucosa-Associated Lymphoid Tissue (MALT) Lymphoma

Helicobacter pylori has been classified as a class I carcinogen by WHO because of its primary involvement in the development of gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma. This review focuses on understanding the molecular pathophysiological mechanisms that operate within intracellular transduction pathways and their relevance in the treatment strategies for the two main diseases caused by H. pylori. H. pylori virulence factors such as cytotoxin-associated gene A and vacuolating cytotoxin A genotypes, inflammatory mediators, H. pylori-induced microRNA deregulation, alterations in autophagy proteins and regulators, and changes in DNA methylation are some of the molecular mechanisms that play essential roles in H. pylori infection and gastric carcinogenesis. The discovery of novel treatment strategies that target the deregulated intracellular transduction pathways in gastric carcinogenesis and MALT lymphoma is critical. H. pylori eradication (HPE) is not limited to H. pylori-dependent low-grade MALT lymphoma and may be used in patients with high-grade diffuse large B-cell lymphoma (DLBCL) (de novo or DLBCL-MALT lymphoma). The loss of H. pylori dependency and high-grade transformation appear to be distinct events in the progression of gastric lymphoma. Interestingly, patients with H. pylori-positive gastric DLBCL without histological evidence of MALT lymphoma (pure gastric DLBCL) may respond to HPE therapy.

Synthesis, spectral characterisation, biocidal investigation, in-silico and molecular docking studies of 4-[(2-chloro-4-methylphenyl)carbamoyl]butanoic acid derived triorganotin(IV) compounds

Three triorganotin(IV) compounds, R3Sn(L), with R = CH3 (1), n-C4H9 (2) and C6H5 (3), and LH = 4-[(2-chloro-4-methylphenyl)carbamoyl]butanoic acid, were prepared and confirmed by various techniques. A five-coordinate, distorted trigonal-bipyramidal geometry was elucidated for tin(IV) centres both in solution and solid states. An intercalation mode was confirmed for the compound SS-DNA interaction by UV-visible, viscometric techniques and molecular docking. MD simulation revealed stable binding of LH with SS-DNA. Anti-bacterial investigation revealed 2 to be generally the most potent, especially against Sa and Ab, i.e. having the lowest MIC values (≤0.25 μg/mL) compared to the standard anti-biotics vancomycin-HCl (MIC = 1 μg/mL) and colistin-sulphate (MIC = 0.25 μg/mL). Similarly, the anti-fungal profile shows 2 exhibits 100% inhibition against Ca and Cn fungal strains and has MIC values (≤0.25 μg/mL) comparatively lower than standard drug fluconazole (0.125 and 8 μg/mL for Ca and Cn, respectively). Compound 2 has the greatest activity with CC50 ≤ 25 μg/mL and HC50 > 32 μg/mL performed against HEC239 and RBC cell lines. The anti-cancer potential was assessed against the MG-U87 cell line, using cisplatin as the standard (133 µM), indicates 2 displays the greatest activity (IC50: 5.521 µM) at a 5 µM dose. The greatest anti-leishmanial potential was observed for 2 (87.75 at 1000 μg/mL) in comparison to amphotericin B (90.67). The biological assay correlates with the observed maximum of 89% scavenging activity exhibited by 2. The Swiss-ADME data publicised the screened compounds generally follow the rule of 5 of drug-likeness and have good bioavailability potential.

Unraveling the mechanisms of Cefoxitin resistance in methicillin-resistant Staphylococcus aureus (MRSA): structural and molecular simulation-based insights

Methicillin-resistant Staphylococcus aureus (MRSA) severely affects human health, including the skin glands, nasal cavity, wound infections, bone infections, and pneumonia. Among the most effective MRSA drugs, Cefoxitin also develops resistance due to mutations in the mecA gene. Four mutations at positions E229K, E239R, G246K, and E447K are classified as high-level resistance mutations. However, the resistance mechanism of MRSA towards Cefoxitin caused by these mutations is still unclear, as there is less information available regarding the structural and functional effects of the mutations against Cefoxitin. Therefore, our present study was designed to explore the mechanisms of binding interactions between wild-type and mutated PBP2a against Cefoxitin using molecular docking and MD simulations. Subsequently, we identified that the mutant form of PBP2a affects the activity of Cefoxitin. Interestingly, the binding of Cefoxitin with G246K and E239R mutants demonstrates unstable behavior compared to E447K-Cefoxitin and E229K-Cefoxitin. In this study, we propose the resistance mechanism of Cefoxitin at the atomic level. The proposed drug-resistance mechanism will provide valuable guidance for the design of MRSA drugs. This research might provide a new framework for designing new agents against the mutated form of PBP2a.Communicated by Ramaswamy H. Sarma.

Identification of novel peptide inhibitors for the KRas-G12C variant to prevent oncogenic signaling

Kirsten rat sarcoma viral oncogene homolog (KRas) activating mutations are common in solid tumors, accounting for 90%, 45%, and 35% of pancreatic, colorectal, and lung cancers (LC), respectively. Each year, nearly 150k new cases (both men and women) of KRas-mutated malignancies are reported in the United States. NSCLC (non-small cell lung cancer) accounts for 80% of all LC cases. KRas mutations are found in 15% to 25% of NSCLC patients. The main cause of NSCLC is the KRas-G12C mutation. The drugs Sotorasib and Adagrasib were recently developed to treat advanced NSCLC caused by the KRas-G12C mutation. Most patients do not respond to KRas-G12C inhibitors due to cellular, molecular, and genetic resistance. Because of their safety, efficacy, and selectivity, peptide inhibitors have the potential to treat newly developing KRas mutations. Based on the KRas mutations, peptide inhibitors that are highly selective and specific to individual lung cancers can be rationally designed. The current study uses an alanine and residue scanning approach to design peptide inhibitors for KRas-G12C based on the known peptide. Our findings show that substitution of F3K, G11T, L8C, T14C, K13D, G11S, and G11P considerably enhances the binding affinity of the novel peptides, whereas F3K, G11T, L8C, and T14C peptides have higher stability and favorable binding to the altered peptides. Overall, our study paves the road for the development of potential therapeutic peptidomimetics that target the KRas-G12C complex and may inhibit the KRas and SOS complex from interacting.Communicated by Ramaswamy H. Sarma.

Structure based virtual screening and molecular simulation study of FDA-approved drugs to inhibit human HDAC6 and VISTA as dual cancer immunotherapy

Cancer immunotherapy has significantly contributed to the treatment of various types of cancers mainly by targeting immune checkpoint inhibitors (ICI). Among them, V-domain immunoglobulin suppressor of T cell activation (VISTA) has been explored as a promising therapeutic target. Besides, histone deacetylase 6 (HDAC6) has been demonstrated to be efficacious target for several cancers. The current theoretical work was performed to explore the virtual repurposing of the FDA-approved drugs as inhibitors against these two (VISTA and HDAC6) cancers therapeutic targets. The crystal structure of the two proteins were downloaded from PDB and subjected to virtual screening by DrugRep webserver while using FDA-approved drugs library as ligands database. Our study revealed that Oxymorphone and Bexarotene are the top-ranked inhibitors of VISTA and HDAC6, respectively. The docking score of Bexarotene was predicted as - 10 kcal/mol while the docking score of Oxymorphone was predicted as - 6.2 kcal/mol. Furthermore, a total of 100 ns MD simulation revealed that the two drugs Oxymorphone and Bexarotene formed stable complexes with VISTA and HDAC6 drug targets. As compared to the standard drug the two drugs Oxymorphone and Bexarotene revealed great stability during the whole 100 ns MD simulation. The binding free energy calculation further supported the Root Mean Square Deviation (RMSD) result which stated that as compared to the ref/HDAC6 (- 18.0253 ± 2.6218) the binding free energy score of the Bexarotene/HDAC6 was good (- 51.9698 ± 3.1572 kcal/mol). The binding free energy score of Oxymorphone/VISTA and Ref/VISTA were calculated as - 36.8323 ± 3.4565, and - 21.5611 ± 4.8581 respectively. In conclusion, the two drugs deserve further consideration as cancer treatment option.

Identification of novel peptide inhibitors for oncogenic KRAS G12D as therapeutic options using mutagenesis-based remodeling and MD simulations

The Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) serves as a molecular switch, cycling between guanosine triphosphate (GTP)-bound and inactive guanosine diphosphate (GDP)-bound states. KRAS modulates numerous signal transduction pathways including the conventional RAF-MEK-ERK pathway. Mutations in the RAS genes have been linked to the formation of malignant tumors. Human malignancies typically show mutations in the Ras gene including HRAS, KRAS, and NRAS. Among all the mutations in exon 12 and exon 13 of the KRAS gene, the G12D mutation is more prevalent in pancreatic and lung cancer and accounts for around 41% of all G12 mutations, making them potential anticancer therapeutic targets. The present study is aimed at repurposing the peptide inhibitor KD2 of the KRAS G12D mutant. We employed an in-silico mutagenesis approach to design novel peptide inhibitors from the experimentally reported peptide inhibitor, and it was found that substitutions (N8W, N8I, and N8Y) might enhance the peptide's binding affinity toward the KRAS. Molecular dynamics simulations and binding energy calculations confirmed that the newly designed peptide inhibitors are stable and that their binding affinities are stronger as compared to the wild-type peptide. The detailed analysis revealed that newly designed peptides have the potential to inhibit KRAS/Raf interaction and the oncogenic signal of the KRAS G12D mutant. Our findings strongly suggest that these peptides should be tested and clinically validated to combat the oncogenic activity of KRAS.Communicated by Ramaswamy H. Sarma.

Identification of novel inhibitors for SARS-CoV-2 as therapeutic options using machine learning-based virtual screening, molecular docking and MD simulation

The new coronavirus SARS-COV-2, which emerged in late 2019 from Wuhan city of China was regarded as causing agent of the COVID-19 pandemic. The primary protease which is also known by various synonymous i.e., main protease, 3-Chymotrypsin-like protease (3CL^PRO) has a vital role in the replication of the virus, which can be used as a potential drug target. The current study aimed to identify novel phytochemical therapeutics for 3CL^PRO by machine learning-based virtual screening. A total of 4,000 phytochemicals were collected from deep literature surveys and various other sources. The 2D structures of these phytochemicals were retrieved from the PubChem database, and with the use of a molecular operating environment, 2D descriptors were calculated. Machine learning-based virtual screening was performed to predict the active phytochemicals against the SARS-CoV-2 3CL^PRO. Random forest achieved 98% accuracy on the train and test set among the different machine learning algorithms. Random forest model was used to screen 4,000 phytochemicals which leads to the identification of 26 inhibitors against the 3CL^PRO. These hits were then docked into the active site of 3CL^PRO. Based on docking scores and protein-ligand interactions, MD simulations have been performed using 100 ns for the top 5 novel inhibitors, ivermectin, and the APO state of 3CL^PRO. The post-dynamic analysis i.e,. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis reveal that our newly identified phytochemicals form significant interactions in the binding pocket of 3CL^PRO and form stable complexes, indicating that these phytochemicals could be used as potential antagonists for SARS-COV-2.

Perspectives from recent advances of Helicobacter pylori vaccines research

BACKGROUND

Helicobacter pylori (H. pylori) infection is the main factor leading to some gastric diseases. Currently, H. pylori infection is primarily treated with antibiotics. However, with the widespread application of antibiotics, H. pylori resistance to antibiotics has also gradually increased year by year. Vaccines may be an alternative solution to clear H. pylori.

AIMS

By reviewing the recent progress on H. pylori vaccines, we expected it to lead to more research efforts to accelerate breakthroughs in this field.

MATERIALS & METHODS

We searched the research on H. pylori vaccine in recent years through PubMed®, and then classified and summarized these studies.

RESULTS

The study of the pathogenic mechanism of H. pylori has led to the development of vaccines using some antigens, such as urease, catalase, and heat shock protein (Hsp). Based on these antigens, whole-cell, subunit, nucleic acid, vector, and H. pylori exosome vaccines have been tested.

DISCUSSION

At present, researchers have developed many types of vaccines, such as whole cell vaccines, subunit vaccines, vector vaccines, etc. However, although some of these vaccines induced protective immunity in mouse models, only a few were able to move into human trials. We propose that mRNA vaccine may play an important role in preventing or treating H. pylori infection. The current study shows that we have developed various types of vaccines based on the virulence factors of H. pylori. However, only a few vaccines have entered human clinical trials. In order to improve the efficacy of vaccines, it is necessary to enhance T-cell immunity.

CONCLUSION

We should fully understand the pathogenic mechanism of H. pylori and find its core antigen as a vaccine target.

In Silico Strategies for Designing of Peptide Inhibitors of Oncogenic K-Ras G12V Mutant: Inhibiting Cancer Growth and Proliferation

Ras plays a pivotal function in cell proliferation and is an important protein in signal transduction pathways. Mutations in genes encoding the Ras protein drive the signaling cascades essential for malignant transformation, tumour angiogenesis, and metastasis and are responsible for above 30% of all human cancers. There is evidence that N-Ras, K-Ras, and H-Ras play significant roles in human cancer. The mutated K-Ras protein is typically observed in malignant growths. Mutant K-Ras is the most common in lung, colon, and pancreatic cancers. The purpose of this research was to create peptides that inhibit K-Ras G12V. The crystal structure of the mutant K-Ras G12V-H-REV107 complex was obtained from a protein data bank. Further, we used a residue scan approach to create unique peptides from the reference peptide (H-REV107). AMBER molecular dynamics simulations were used to test the stability of the top four proposed peptides (based on binding free energies). Our findings showed that the top four selected peptides had stronger interactions with K-Ras than the reference peptide and have the ability to block the activation function of K-Ras. Our extensive analyses of binding affinities showed that our designed peptide possesses the potential to inhibit K-Ras and to reduce the progression of cancer.

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

Repositioning of experimentally validated anti-breast cancer peptides to target FAK-PAX complex to halt the breast cancer progression: a biomolecular simulation approach

FAK (focal adhesin kinase), a tyrosine kinase, plays an imperative role in cell-cell communication, particularly in cell signaling systems. It is a multi-functional signaling protein, which integrates and transduces signals into cancer cells through growth factor receptors or integrin and its interaction with Paxillin (PAX). The molecular processes by which FAK promotes the development and progression of cancer have progressively established the possible relationship between FAK-PAX complex in many types of cancer. The interaction of FAX and PAX is very important in breast cancer and thus acts as an essential biomarker for drugs, vaccines or peptide inhibitor designing. In this regard, computational approaches, particularly peptide designing to target the binding interface of the interacting partners, would greatly assist the design of peptide inhibitors against various cancer. Accordingly, in this present study, we screened 236 experimentally validated anti-breast cancer peptides using computational drugs repositioning approach to design peptides targeting the FAK-PAX complex. Using protein-peptide docking the binding site for the HP1 was confirmed and a total of 236 anti-breast cancer peptides were screened. Among the 236, only 12 peptides reported a docking score better than the control. From these 12, Magainin with the docking score - 103.8 ± 10.3 kcal/mol, NRC-07 with the docking score - 100.8 ± 16.5 kcal/mol, and Indolicidin with the docking score - 101.7 ± 3.9 kcal/mol, peptides potentially inhibit the FAX-PAX binding. Calculation of protein's motion and FEL revealed the binding and inhibitory behavior. Moreover, binding free energy (MM/GBSA) confirmed that Magainin exhibited the total binding energy - 53.28 kcal/mol, NRC-07 possessed the TBE - 44.16 kcal/mol, and Indolicidin reported the TBE of - 40.48 kcal/mol, thus explaining the inhibitory potential of these peptides. In conclusion, these peptides exhibit strong inhibitory potential and could abrogate the FAK-PAX complex in in vitro models and thus may relieve the burden of breast cancer.

Immmunoinformatics-based design of a multi-epitope vaccine with CTLA-4 extracellular domain to combat Helicobacter pylori

In view of the high infection rate of Helicobacter pylori, a safe and effective vaccine is urgently needed. Recent trends in vaccine design have shifted toward safe and specific epitope-based vaccines. In this study, by using different immunoinformatics approaches, a total of eight linear B cell epitopes, four HTL and three CTL epitopes of FlaA and UreB proteins of H. pylori G27 strain were screened out, we also predicted the conformational epitopes of the two proteins. Then, the dominant epitopes were sequentially linked by appropriate linkers, and the cytotoxic T lymphocyte-associated antigen 4 extracellular domain was attached to the N-terminal of the epitope sequence. Meanwhile, molecular docking, molecular dynamics simulations and principal component analysis were performed to show that the multi-epitope vaccine structure had strong interactions with B7 (B7-1, B7-2) and Toll-like receptors (TLR-2, -4). Eventually, the effectiveness of the vaccine was validated using in silico cloning. These analyses suggested that the designed vaccine could target antigen-presenting cells and had high potency against H. pylori, which could provide a reference for the future development of efficient H. pylori vaccines.

Oncological drug discovery: AI meets structure-based computational research

The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the diversity of neoplastic diseases portrayed by the different hallmarks of cancer. Here, we review six use case scenarios for integrated computational methods, namely driver prediction, computational mutagenesis, (off)-target prediction, binding site prediction, virtual screening, and allosteric modulation analysis. We address the heterogeneity of integration approaches and individual methods, while acknowledging their current limitations and highlighting their potential to bring drugs for personalized oncological therapies to the market faster.

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.

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.

Structural and Biophysical Investigation of the Key Hotspots on the Surface of Epstein-Barr Nuclear Antigen 1 Essential for DNA Recognition and Pathogenesis

Epstein-Barr Virus (EBV) is considered the most important human pathogen due to its role in infections and cellular malignancies. It has been reported that this Oncolytic virus infects 90% world’s population. EBNA1 is required for DNA binding and survival of the virus and is considered an essential drug target. The biochemical and structural properties of this protein are known, but it is still unclear which residues impart a critical role in the recognition of dsDNA. Intending to disclose only the essential residues in recognition of dsDNA, this study used a computational pipeline to generate an alanine mutant of each interacting residue and determine the impact on the binding. Our analysis revealed that R469A, K514A, Y518A, R521A and R522A are the key hotspots for the recognition of dsDNA by the EBNA1. The dynamics properties, i.e. stability, flexibility, structural compactness, hydrogen bonding frequency, binding affinity, are altered by disrupting the protein-DNA contacts, thereby decreases the binding affinity. In particular, the two arginine substitution, R521A and R522A, significantly affected the total binding energy. Thus, we hypothesize that these residues impart a critical role in the dsDNA recognition and pathogenesis. This study would help to design structure-based drugs against the EBV infections.

Targeting the N-terminal domain of the RNA-binding protein of the SARS-CoV-2 with high affinity natural compounds to abrogate the protein-RNA interaction: a molecular dynamics study

The emergence of COVID-19 took the world by shock in December 2019, starting from Wuhan, China and swiftly spreading across the globe. The number of COVID-19 cases continues to rise which is a global burden on the health care system worldwide. Efforts are continuing to come up with a solution either to develop a small molecular inhibitor or vaccine, but still no success. In the fight against SARS-CoV-2, targeting a different protein of the SARS-CoV-2 is the need of the hour to impede and relinquish the current pandemic. Therefore, in this study, computational modelling and simulation approaches are used to target the N-terminal domain of the phosphor-nucleoprotein (RNA binding protein), which is primarily responsible for binding and packing the viral genome to get ribonucleoprotein complex (RNP). Our multi-step drug screening approach shortlisted potential drugs. These top hits were confirmed by re-docking which revealed that the interacting molecules block the key residues i.e. Thr57, His59, Ser105, Arg107, and Arg177 and thus ultimately block the NTD from RNA recognition. Furthermore, the activity of the top four hits was also confirmed by using molecular dynamics simulation and free energy calculation. Our analysis suggests that these top hits possess strong inhibitory properties and should be tested experimentally. In conclusion, we hope these top hits would abrogate the binding of RNA and the NTD of the SARS-CoV-2, which might be helpful to combat COVID-19.Communicated by Ramaswamy H. Sarma.

Microbes in Tumoral In Situ Tissues and in Tumorigenesis

Cancerous tumors are severe diseases affecting human health that have a complicated etiology and pathogenesis. Microbes have been considered to be related to the development and progression of numerous tumors through various pathogenic mechanisms in recent studies. Bacteria, which have so far remained the most studied microbes worldwide, have four major possible special pathogenic mechanisms (modulation of inflammation, immunity, DNA damage, and metabolism) that are related to carcinogenesis. This review aims to macroscopically summarize and verify the relationships between microbes and tumoral in situ tissues from cancers of four major different systems (urinary, respiratory, digestive, and reproductive); the abovementioned four microbial pathogenic mechanisms, as well as some synergistic pathogenic mechanisms, are also discussed. Once the etiologic role of microbes and their precise pathogenic mechanisms in carcinogenesis are known, the early prevention, diagnosis, and treatment of cancers would progress significantly.

Phylogenetic Analysis and Structural Perspectives of RNA-Dependent RNA-Polymerase Inhibition from SARs-CoV-2 with Natural Products

Abstract

Most recently, an outbreak of severe pneumonia caused by the infection of SARS-CoV-2, a novel coronavirus first identified in Wuhan, China, imposes serious threats to public health. Upon infecting host cells, coronaviruses assemble a multi-subunit RNA-synthesis complex of viral non-structural proteins (nsp) responsible for the replication and transcription of the viral genome. Therefore, the role and inhibition of nsp12 are indispensable. A cryo-EM structure of RdRp from SARs-CoV-2 was used to identify novel drugs from Northern South African medicinal compounds database (NANPDB) by using computational virtual screening and molecular docking approaches. Considering Remdesivir as the control, 42 compounds were shortlisted to have docking score better than Remdesivir. The top 5 hits were validated by using molecular dynamics simulation approach and free energy calculations possess strong inhibitory properties than the Remdesivir. Thus, this study paved a way for designing novel drugs by decoding the architecture of an important enzyme and its inhibition with compounds from natural resources. This disclosing of necessary knowledge regarding the screening and the identification of top hits could help to design effective therapeutic candidates against the coronaviruses and design robust preventive measurements.

Graphic abstract

Pan-Cancer Analysis and Drug Formulation for GPR139 and GPR142

GPR (G protein receptor) 139 and 142 are novel foundling GPCRs (G protein-coupled receptors) in the class "A" of the GPCRs family and are suitable targets for various biological conditions. To engage these targets, validated pharmacophores and 3D QSAR (Quantitative structure-activity relationship) models are widely used because of their direct fingerprinting capability of the target and an overall accuracy. The current work initially analyzes GPR139 and GPR142 for its genomic alteration via tumor samples. Next to that, the pharmacophore is developed to scan the 3D database for such compounds that can lead to potential agonists. As a result, several compounds have been considered, showing satisfactory performance and a strong association with the target. Additionally, it is gripping to know that the obtained compounds were observed to be responsible for triggering pan-cancer. This suggests the possible role of novel GPR139 and GPR142 as the substances for initiating a physiological response to handle the condition incurred as a result of cancer.

Molecular anatomy and pathogenic actions of Helicobacter pylori CagA that underpin gastric carcinogenesis

Chronic infection with Helicobacter pylori cagA-positive strains is the strongest risk factor for gastric cancer. The cagA gene product, CagA, is delivered into gastric epithelial cells via the bacterial type IV secretion system. Delivered CagA then undergoes tyrosine phosphorylation at the Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs in its C-terminal region and acts as an oncogenic scaffold protein that physically interacts with multiple host signaling proteins in both tyrosine phosphorylation-dependent and -independent manners. Analysis of CagA using in vitro cultured gastric epithelial cells has indicated that the nonphysiological scaffolding actions of CagA cell-autonomously promote the malignant transformation of the cells by endowing the cells with multiple phenotypic cancer hallmarks: sustained proliferation, evasion of growth suppressors, invasiveness, resistance to cell death, and genomic instability. Transgenic expression of CagA in mice leads to in vivo oncogenic action of CagA without any overt inflammation. The in vivo oncogenic activity of CagA is further potentiated in the presence of chronic inflammation. Since Helicobacter pylori infection triggers a proinflammatory response in host cells, a feedforward stimulation loop that augments the oncogenic actions of CagA and inflammation is created in CagA-injected gastric mucosa. Given that Helicobacter pylori is no longer colonized in established gastric cancer lesions, the multistep nature of gastric cancer development should include a “hit-and-run” process of CagA action. Thus, acquisition of genetic and epigenetic alterations that compensate for CagA-directed cancer hallmarks may be required for completion of the “hit-and-run” process of gastric carcinogenesis.

Extraction of molecular features for the drug discovery targeting protein-protein interaction of Helicobacter pylori CagA and tumor suppressor protein ASSP2

Half of the world population is infected by the Gram-negative bacterium Helicobacter pylori (H. pylori). It colonizes in the stomach and is associated with severe gastric pathologies including gastric cancer and peptic ulceration. The most virulent factor of H. pylori is the cytotoxin-associated gene A (CagA) that is injected into the host cell. CagA interacts with several host proteins and alters their function, thereby causing several diseases. The most well-known target of CagA is the tumor suppressor protein ASPP2. The subdomain I at the N-terminus of CagA interacts with the proline-rich motif of ASPP2. Here, in this study, we carried out alanine scanning mutagenesis and an extensive molecular dynamics simulation summing up to 3.8 μs to find out hot spot residues and discovered some new protein-protein interaction (PPI)-modulating molecules. Our findings are in line with previous biochemical studies and further suggested new residues that are crucial for binding. The alanine scanning showed that mutation of Y207 and T211 residues to alanine decreased the binding affinity. Likewise, dynamics simulation and molecular mechanics with generalized Born surface area (MMGBSA) analysis also showed the importance of these two residues at the interface. A four-feature pharmacophore model was developed based on these two residues, and top 10 molecules were filtered from ZINC, NCI, and ChEMBL databases. The good binding affinity of the CHEMBL17319 and CHEMBL1183979 molecules shows the reliability of our adopted protocol for binding hot spot residues. We believe that our study provides a new insight for using CagA as the therapeutic target for gastric cancer treatment and provides a platform for a future experimental study.

Molecular dynamics simulation revealed the intrinsic conformational change of cellular inhibitor of apoptosis protein-1

Inhibitor of apoptosis proteins (IAPs) are important regulators of apoptosis, and protein targets for the development of anti-cancer drugs. Cellular inhibitor of apoptosis protein-1 (cIAP1) is an important member of IAPs. Peptides or small-molecular antagonists can induce the dimerization, auto-ubiquitination, and proteasomal degradation of the cellular inhibitor of apoptosis protein-1 (cIAP1). While in the absence of antagonists, several mutations of the cIAP1 protein also lead to its dimerization and auto-ubiquitination. Even though the crystal structure of cIAP1 protein has been determined, the intrinsic mechanism of its dimerization remains unexplored. Accumulating evidence indicated that intrinsic conformational change existed during the binding of antagonists with cIAP1 protein, or introduction of mutations. To reveal this intrinsic conformational change, molecular dynamics simulations at microsecond scale were applied for the wild-type and mutant-type cIAP1 proteins. Compared to the crystal structure, significant conformational change was observed during the simulations, which could explain the importance of previously identified key mutations. To validate these findings revealed by our simulations, a new mutation D303A was constructed and the following native polyacrylamide gel electrophoresis (native-PAGE) assay observed a proportion of spontaneous dimerization, in comparison with the wild-type control. Taken together, these computational and experimental results revealed the intrinsic conformational change of cIAP1, which could not only explain previously identified key mutations, but also be exploited for further design and development of anti-tumor compounds that target the cIAP1 protein.Communicated by Ramaswamy H. Sarma.