High-throughput virtual screening of small-molecule inhibitors targeting immune cell checkpoints to discover new immunotherapeutics for human diseases

Identification of PLAC1 as a prognostic biomarker and molecular target in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common clinical tumor of the urinary system. The lack of effective diagnostic and treatment options poses a serious challenge to clinical treatment. Therefore, identifying effective molecular targets has become one of the potential means to treat this disease. Firstly, the analysis of the TCGA database found that PLAC1 was abnormally highly expressed in ccRCC and was negatively correlated with patient prognosis. Western blotting and immunofluorescence experiments further verified that PLAC1 was highly expressed in ccRCC patients, and knockdown of PLAC1 inhibited the development of ccRCC in vitro. Last, high-throughput virtual screening technology (HTVS) was performed to identify two molecular inhibitors ，AmB and Cana, which were able to reduce the expression of PLAC1 and inhibited the progression of ccRCC. In conclusion, the current investigation indicated that the PLAC1 could serve as a prognostic biomarker, and AmB and Cana inhibit the progression of ccRCC by reducing PLAC1, making it a potential therapeutic option for ccRCC.

Exploiting potential molecular compounds for treating testicular seminoma by targeting immune related genes

BACKGROUND

In cases of advanced seminoma, up to 30% of patients may manifest cisplatin resistance, necessitating aggressive salvage therapy, with a consequent 50% risk of mortality attributable to cancer. Nevertheless, beyond chemotherapy and radiotherapy, no further therapeutic modalities have been implemented for these patients.

METHODS

The study commenced with the identification of differentially expressed immune-related genes, which were subsequently subjected to clustering using WGCNA. Prognostic signature construction ensued through the execution of univariable Cox regression, lasso regression, and multivariable Cox regression analyses. To validate the prognostic signature, the TCGA-TGCT and GSE99420 cohorts were employed, with assessments conducted via PFS, C-index, DCA, and ROC analyses. Subsequent exploration of the immune landscape and potential immunotherapeutic applications was undertaken through Cibersort and TIDE analyses. Molecular docking and dynamics simulation techniques were then employed for screening potential molecular compounds. Validation of these findings was pursued through in vitro and vivo assays.

RESULTS

CTLA4, SNX17, and TMX1 were selected to construct the signature. Patients in the high-risk group exhibited diminished progression-free survival rates. The AUC for predicting survival at 1, 3, and 5 years was 0.802, 0.899, and 0.943, respectively, surpassing those of other risk factors, such as lymphovascular invasion and T stage. The C-index for the risk score was 0.838. Decision curve analysis (DCA) suggests that incorporating lymphovascular invasion and the risk score yields the most favorable decision-making outcomes for patients. Moreover, individuals classified as high-risk may derive greater benefit from immunotherapy. Molecular compounds including Rutin, ICG-001, and Doxorubicin can selectively target CTLA4, SNX17, and TMX1, respectively, thereby inhibiting the proliferation and invasive capabilities of seminoma tumor cells in vitro and vivo.

CONCLUSION

The signature initially constructed based on immune-related genes shows promise for predicting outcomes and assessing the efficacy of immunotherapy in seminoma patients. Rutin, ICG-001, and Doxorubicin have demonstrated potential to target these signature genes and inhibit tumor cell viability.

Identification of cholinesterases inhibitors from flavonoids derivatives for possible treatment of Alzheimer's disease: In silico and in vitro approaches

Nowadays, one of the methods to prevent the progress of Alzheimer's disease (AD) is to prescribe compounds that inhibit the acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. Researchers are actively pursuing compounds, particularly of natural origin, that exhibit enhanced efficacy and reduced side effects. The inhibition of AChE and BChE using natural flavonoids represents a promising avenue for regulating AD. This study aims to identify alternative flavonoids capable of modulating AD by down-regulating AChE and BChE activity through a molecular docking approach. Molecular docking analysis identified Ginkgetin and Kolaflavanone as potent inhibitors of AChE and BChE, respectively, among the selected flavonoids. Asn87 and Ala127 involved in the interactions of AChE-Ginkgetin complex through conventional hydrogen bonds. While in the BChE-Kolaflavanone complex, Asn83, Ser79, Gln 47, and Ser287 are involved. In vitro analysis further corroborated the inhibitory potential, with Ginkgetin exhibiting an IC50 of 3.2 mM against AChE, and Kolaflavanone displaying an IC50 of 3.6 mM against BChE. These findings underscore the potential of Ginkgetin and Kolaflavanone as candidate inhibitors for the treatment of AD through the inhibition of AChE and BChE enzymes. Nevertheless, additional in vitro and in vivo studies are imperative to validate the efficacy of these compounds.

Unleashing the power of antibodies: Engineering for tomorrow's therapy

Antibodies play a crucial role in host defense against various diseases. Antibody engineering is a multidisciplinary field that seeks to improve the quality of life of humans. In the context of disease, antibodies are highly specialized proteins that form a critical line of defense against pathogens and the disease caused by them. These infections trigger the innate arm of immunity by presenting on antigen-presenting cells such as dendritic cells. This ultimately links to the adaptive arm, where antibody production and maturation occur against that particular antigen. Upon binding with their specific antigens, antibodies trigger various immune responses to eliminate pathogens in a process called complement-dependent cytotoxicity and phagocytosis of invading microorganisms by immune cells or induce antibody-dependent cellular cytotoxicity is done by antibodies. These engineered antibodies are being used for various purposes, such as therapeutics, diagnostics, and biotechnology research. Cutting-edge techniques that include hybridoma technology, transgenic mice, display techniques like phage, yeast and ribosome displays, and next-generation sequencing are ways to engineer antibodies and mass production for the use of humankind. Considering the importance of antibodies in protecting from a diverse array of pathogens, investing in research holds great promise to develop future therapeutic targets to combat various diseases.

Technological advancements in viral vector designing and optimization for therapeutic applications

Viral vector engineering is critical to the advancement of several sectors of biotechnology, gene therapy, and vaccine development. These vectors were produced from viruses, were employed to deliver therapeutic genes or to alter biological processes. The potential for viral vectors to improve the precision, safety, and efficiency of therapeutic interventions has boosted their demand. The dynamic interplay between technological advancements and computational tools in establishing the landscape of viral vector engineering and vector optimization for therapeutic reasons is discussed in this chapter. It also emphasizes the importance of in silico techniques in maximizing vector potential for therapeutics and many phases of viral vector engineering, from genomic analysis to computer modelling and advancements to improve precise gene delivery. High-throughput screening propels the expedited process of vector selection, and computational techniques to analyze complex omics data to further enhance vector capabilities have been discussed. As in silico models reveal insights into off-target effects and integration sites, vector safety (biodistribution and toxicity) remains a crucial part and bridges the gap between preclinical and clinical investigations. Despite the limitations, this chapter depicts a future in which technology and computing merge to catapult viral vector therapy into an era of boundless possibilities.

From genome to clinic: The power of translational bioinformatics in improving human health

Translational bioinformatics (TBI) has transformed healthcare by providing personalized medicine and tailored treatment options by integrating genomic data and clinical information. In recent years, TBI has bridged the gap between genome and clinical data because of significant advances in informatics like quantum computing and utilizing state-of-the-art technologies. This chapter discusses the power of translational bioinformatics in improving human health, from uncovering disease-causing genes and variations to establishing new therapeutic techniques. We discuss key application areas of bioinformatics in clinical genomics, such as data sources and methods used in translational bioinformatics, the impact of translational bioinformatics on human health, and how machine learning and artificial intelligence are being used to mine vast amounts of data for drug development and precision medicine. We also look at the problems, constraints, and ethical concerns connected with exploiting genomic data and the future of translational bioinformatics and its potential impact on medicine and human health. Ultimately, this chapter emphasizes the great potential of translational bioinformatics to alter healthcare and enhance patient outcomes.

Inflammation, Autoimmunity and Neurodegenerative Diseases, Therapeutics and Beyond

Neurodegenerative disease (ND) incidence has recently increased due to improved life expectancy. Alzheimer's (AD) or Parkinson's disease (PD) are the most prevalent NDs. Both diseases are poly genetic, multifactorial and heterogenous. Preventive medicine, a healthy diet, exercise, and controlling comorbidities may delay the onset. After the diseases are diagnosed, therapy is needed to slow progression. Recent studies show that local, peripheral and age-related inflammation accelerates NDs' onset and progression. Patients with autoimmune disorders like inflammatory bowel disease (IBD) could be at higher risk of developing AD or PD. However, no increase in ND incidence has been reported if the patients are adequately diagnosed and treated. Autoantibodies against abnormal tau, β amyloid and α- synuclein have been encountered in AD and PD and may be protective. This discovery led to the proposal of immune-based therapies for AD and PD involving monoclonal antibodies, immunization/ vaccines, pro-inflammatory cytokine inhibition and anti-inflammatory cytokine addition. All the different approaches have been analysed here. Future perspectives on new therapeutic strategies for both disorders are concisely examined.

Nanobody-peptide-conjugate (NPC) for passive immunotherapy against SARS-CoV-2 variants of concern (VoC): a prospective pan-coronavirus therapeutics

The COVID-19 crisis, incited by the zoonotic SARS-CoV-2 virus, has quickly escalated into a catastrophic public health issue and a grave threat to humankind owing to the advent of mutant viruses. Multiple pharmaceutical therapies or biologics envision stopping the virus from spreading further; however, WHO has voiced concerns about the variants of concern (VoCs) inability to respond. Nanobodies are a new class of antibody mimics with binding affinity and specificity similar to classical mAbs, as well as the privileges of a small molecular weight, ease of entry into solid tissues, and binding cryptic epitopes of the antigen. Herein, we investigated multiple putative anti-SARS-CoV-2 nanobodies targeting the Receptor binding domain of the WHO-listed SARS-CoV-2 variants of concern using a comprehensive computational immunoinformatics methodology. With affinity maturation via alanine scanning mutagenesis, we remodeled an ultrapotent nanobody with substantial breadth and potency, exhibiting pico-molar binding affinities against all the VoCs. An antiviral peptide with specificity for ACE-2 receptors was affixed to make it multispecific and discourage viral entry. Collectively, we constructed a broad-spectrum therapeutic biparatopic nanobody-peptide conjugate (NPC) extending coverage to SARS-CoV-2 VoCs RBDs. We PEGylated the biparatopic construct with 20kD maleimide-terminated PEG (MAL-(PEG)n-OMe) to improve its clinical efficacy limiting rapid renal clearance, and performed in silico cloning to facilitate future experimental studies. Our findings suggest that combining biparatopic nanobody conjugate with standard treatment may be a promising bivariate tool for combating viral entry during COVID-19 illness.

Structure-based virtual screening and fragment replacement to design novel inhibitors of Coxsackievirus A16 (CVA16)

Numerous studies have shown that hand, foot and mouth disease (HFMD) pathogen Coxsackievirus A16 (CVA16) can also cause severe neurological complications and even death. Currently, there is no effective drugs and vaccines for CVA16. Therefore, developing a drug against CVA16 has become critical. In this study, we conducted two strategies-virtual screening (VS) and fragment replacement to obtain better candidates than the known drug GPP3. Through VS, 37 candidate drugs were screened (exhibiting a lower binding energy than GPP3). After toxicity evaluations, we obtained five candidates, analysed their binding modes and found that four candidates could enter the binding pocket of the GPP3. In another strategy, we analysed the four positions in GPP3 structures by the FragRep webserver and obtained a large number of candidates after replacing different functional groups, we obtained eight candidates (that target the four positions above) with the combined binding score and synthetic accessibility evaluations. AMDock software was uniformly utilized to perform molecular docking evaluation of the candidates with binding activity superior to that of GPP3. Finally, the selected top three molecules (Lapatinib, B001 and C001) and its interaction with CAV16 were validated by molecular dynamics (MD) simulation. The results indicated that all three molecules retain inside the pocket of CAV16 receptor throughout the simulation process, and he binding energy calculated from the MD simulation trajectories also support the strong affinity of the top three molecules towards the CVA16. These results will provide new ideas and technical guidance for designing and applying CVA16 therapeutics.Communicated by Ramaswamy H. Sarma.

Multi-pathogen based chimeric vaccine to fight against COVID-19 and concomitant coinfections

BACKGROUND

COVID-19 has proved to be a fatal disease of the year 2020, due to which thousands of people globally have lost their lives, and still, the infection cases are at a high rate. Experimental studies suggested that SARS-CoV-2 interacts with various microorganisms, and this coinfection is accountable for the augmentation of infection severity.

METHODS AND RESULTS

In this study, we have designed a multi-pathogen vaccine by involving the immunogenic proteins from S. pneumonia, H. influenza, and M. tuberculosis, as they are dominantly associated with SARS-CoV-2. A total of 8 antigenic protein sequences were selected to predict B-cell, HTL, and CTL epitopes restricted to the most prevalent HLA alleles. The selected epitopes were antigenic, non-allergenic, and non-toxic and were linked with adjuvant and linkers to make the vaccine protein more immunogenic, stable, and flexible. The tertiary structure, Ramachandran plot, and discontinuous B-cell epitopes were predicted. Docking and MD simulation study has shown efficient binding of the chimeric vaccine with the TLR4 receptor.

CONCLUSION

The in silico immune simulation analysis has shown a high level of cytokines and IgG after a three-dose injection. Hence, this strategy could be a better way to decrease the disease's severity and could be used as a weapon to prevent this pandemic.

Translational vaccinomics and structural filtration algorithm to device multiepitope vaccine for catastrophic monkeypox virus

Recent outbreak of monkeypox disease commenced in April 2022, and on May 7, the first confirmed case was reported. The world health organization then designated monkeypox disease as a public health emergency of international outrage on July 23, after it spread to 70 non-endemic nations in less than 15 days. This catastrophic viral infection encourages the development of antiviral therapeutics due to the lack of specific treatments with negligible adverse effects. This analysis developed a highly immunogenic multiepitope subunit vaccine against the monkeypox virus using an in silico translational vaccinomics technique. Highly antigenic B cell and T cell (HTL and CTL) epitopes were predicted and conjugated with the help of unique linkers. An adjuvant (β-defensin) and a pan-HLA DR sequence were attached at the vaccine construct's N-terminal to invoke a robust immunological response. Additionally, physiochemical, allergic, toxic, and antigenic properties were anticipated. Interactions between the vaccine candidate and the TLR3 demonstrated that the vaccine candidate triggers a robust immunological response. Finally, the stability is confirmed by the molecular dynamics study. In contrast, the modified vaccine candidate's ability to produce a protective immune response were verified by an immune dynamics simulation study conducted via C-ImmSim server. This study validates the generation of B cell, Th cell, and Tc cell populations as well as the production of IFN-γ.

Identification of multi-targeting natural antiviral peptides to impede SARS-CoV-2 infection

SARS-CoV-2 and its variants cause serious health concerns throughout the world. The alarming increase in the daily number of cases has become a nightmare in many low-income countries; although some vaccines are available, their high cost and low vaccine production make them unreachable to ordinary people in developing countries. Other treatment strategies are required for novel therapeutic options. The peptide-based drug is one of the alternatives with low toxicity, more specificity, and ease of synthesis. Herein, we have applied structure-based virtual screening to identify potential peptides targeting the critical proteins of SARS-CoV-2. Non-toxic natural antiviral peptides were selected from the enormous number of peptides. Comparative modeling was applied to prepare a 3D structure of selected peptides. 3D models of the peptides were docked using the ClusPro docking server to determine their binding affinity and peptide-protein interaction. The high-scoring peptides were docked with other crucial proteins to analyze multiple targeting peptides. The two best peptides were subjected to MD simulations to validate the structure stability and evaluated RMSD, RMSF, Rg, SASA, and H-bonding from the trajectory analysis of 100 ns. The proposed lead peptides can be used as a broad-spectrum drug and potentially develop as a therapeutic to combat SARS-CoV-2, positively impacting the current pandemic.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11224-022-02113-9.

Exploring actinomycetes natural products to identify potential multi-target inhibitors against Leishmania donovani

Visceral leishmaniasis (VL) is a neglected tropical disease that mainly affects the poor population of the Indian, African, and South American subcontinent. The increasing resistance to antimonial and miltefosine and frequent toxicity of amphotericin B drives an urgent need to develop an anti-leishmanial drug with excellent efficacy and safety profile. In this study, three sequential docking protocols (HTVS, SP, and XP) were performed to screen the secondary metabolites (n = 6519) from the actinomycetes source against five key proteins involved in the metabolic pathway of Leishmania donovani. Those proteins were adenine phosphoribosyltransferase (PDB ID: 1QB7), trypanothione reductase (PDB ID: 2JK6), N-myristoyl transferase (PDB ID: 2WUU), pteridine reductase (PDB ID: 2XOX), and MAP kinase (PDB ID: 4QNY). Although the binding energy of top ligands was predicted using the MM-GBSA module of the Schrödinger suite. SP and XP docking mode resulted in 55 multi-targeted ligands against L donovani. MM-GBSA analysis selected the top 18 ligands with good-binding affinity and the binding-free energy for four proteins, as mentioned earlier, when compared with the miltefosine, paromomycin, and a reference ligand selected for each target. Finally, molecular dynamics simulation, post-MD-binding-free energy (MM-PBSA), and principal component analysis (PCA) proposed three best ligands (Adenosine pentaphosphate, Atetra P, and GDP-4-keto-6-deoxymannose) qualifying the above screening parameters and confirmed as a potential drug candidate to fight against Leishmania donovani parasites.