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Article ; Online: Design of a potential Sema4A-based multi-epitope vaccine to combat triple-negative breast cancer: an immunoinformatic approach.

Paranthaman, Priyanga / Veerappapillai, Shanthi

Medical oncology (Northwood, London, England)

2023 Volume 40, Issue 3, Page(s) 105

Abstract: Immunotherapy is revamping the therapeutic strategies for TNBC owing to its higher mutational burden and tumour-associated antigens. One of the most intriguing developments in cancer immunotherapy is the focus on peptide-based cancer vaccines. Thus, the ... ...

Abstract	Immunotherapy is revamping the therapeutic strategies for TNBC owing to its higher mutational burden and tumour-associated antigens. One of the most intriguing developments in cancer immunotherapy is the focus on peptide-based cancer vaccines. Thus, the current work aims to develop an efficient peptide-based vaccine against TNBC that targets Sema4A, which has recently been identified as a major regulator of TNBC progression. Initially, the antigenic peptides derived from Sema4A were determined and evaluated based on their capability to provoke immunological responses. The assessed epitopes were then linked with a suitable adjuvant (RpfB and RpfE) and appropriate linkers (AAY, GPGPG, KK and EAAAK) to preclude junctional immunogenicity. Eventually, docking and dynamics simulations are performed against TLR-2, TLR-4, TLR-7 and TLR-9 to assess the interaction between the vaccine construct and TLR receptors, as the TLR signalling pathway is critical in the host immune response. The developed vaccine was then exposed to in silico cloning and immune simulation analysis. The findings suggest that the designed vaccine could potentially evoke significant humoral and cellular immune responses in the intended organism. Considering these outcomes, the final multi-epitope vaccine could be employed to serve as an effective choice for TNBC management and may open new avenues for further studies.
MeSH term(s)	Humans ; Triple Negative Breast Neoplasms/therapy ; Epitopes, T-Lymphocyte/chemistry ; Computer Simulation ; Vaccines, Subunit/chemistry ; Peptides ; Molecular Docking Simulation ; Computational Biology ; Epitopes, B-Lymphocyte/chemistry ; Semaphorins
Chemical Substances	Epitopes, T-Lymphocyte ; Vaccines, Subunit ; Peptides ; Epitopes, B-Lymphocyte ; SEMA4A protein, human ; Semaphorins
Language	English
Publishing date	2023-02-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	1201189-7
ISSN	1559-131X ; 0736-0118 ; 1357-0560
ISSN (online)	1559-131X
ISSN	0736-0118 ; 1357-0560
DOI	10.1007/s12032-023-01970-6
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Article ; Online: Designing Novel Compounds for the Treatment and Management of RET-Positive Non-Small Cell Lung Cancer-Fragment Based Drug Design Strategy.

Ramesh, Priyanka / Veerappapillai, Shanthi

Molecules (Basel, Switzerland)

2022 Volume 27, Issue 5

Abstract: Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. ... ...

Abstract	Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.
MeSH term(s)	Carcinoma, Non-Small-Cell Lung/drug therapy ; Carcinoma, Non-Small-Cell Lung/genetics ; Drug Design ; Humans ; Lung Neoplasms/drug therapy ; Lung Neoplasms/genetics ; Molecular Docking Simulation ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/therapeutic use ; Proto-Oncogene Proteins c-ret/genetics ; Proto-Oncogene Proteins c-ret/therapeutic use
Chemical Substances	Protein Kinase Inhibitors ; Proto-Oncogene Proteins c-ret (EC 2.7.10.1) ; RET protein, human (EC 2.7.10.1)
Language	English
Publishing date	2022-02-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules27051590
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Article ; Online: Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Thirunavukkarasu, Muthu Kumar / Ramesh, Priyanka / Karuppasamy, Ramanathan / Veerappapillai, Shanthi

Journal of applied genetics

2024

Abstract: Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are ... ...

Abstract	Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.
Language	English
Publishing date	2024-03-05
Publishing country	England
Document type	Journal Article
ZDB-ID	1235302-4
ISSN	2190-3883 ; 1234-1983
ISSN (online)	2190-3883
ISSN	1234-1983
DOI	10.1007/s13353-024-00847-2
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Article: In-silico bioprospecting of secondary metabolites from endophytic

Antony, Ajitha / Veerappapillai, Shanthi / Karuppasamy, Ramanathan

3 Biotech

2023 Volume 14, Issue 1, Page(s) 15

Abstract: Rice blast disease, caused by : Supplementary information: The online version contains supplementary material available at 10.1007/s13205-023-03859-7. ...

Abstract	Rice blast disease, caused by Supplementary information: The online version contains supplementary material available at 10.1007/s13205-023-03859-7.
Language	English
Publishing date	2023-12-18
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2600522-0
ISSN	2190-5738 ; 2190-572X
ISSN (online)	2190-5738
ISSN	2190-572X
DOI	10.1007/s13205-023-03859-7
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Article ; Online: Sequential virtual screening collaborated with machine-learning strategies for the discovery of precise medicine against non-small cell lung cancer.

Thirunavukkarasu, Muthu Kumar / Veerappapillai, Shanthi / Karuppasamy, Ramanathan

Journal of biomolecular structure & dynamics

2023 Volume 42, Issue 2, Page(s) 615–628

Abstract: Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to ... ...

Abstract	Dysregulation of MAPK pathway receptors are crucial in causing uncontrolled cell proliferation in many cancer types including non-small cell lung cancer. Due to the complications in targeting the upstream components, MEK is an appealing target to diminish this pathway activity. Hence, we have aimed to discover potent MEK inhibitors by integrating virtual screening and machine learning-based strategies. Preliminary screening was conducted on 11,808 compounds using the cavity-based pharmacophore model AADDRRR. Further, seven ML models were accessed to predict the MEK active compounds using six molecular representations. The LGB model with morgan2 fingerprints surpasses other models ensuing 0.92 accuracy and 0.83 MCC value versus test set and 0.85 accuracy and 0.70 MCC value with external set. Further, the binding ability of screened hits were examined using glide XP docking and prime-MM/GBSA calculations. Note that we have utilized three ML-based scoring functions to predict the various biological properties of the compounds. The two hit compounds such as DB06920 and DB08010 resulted excellent binding mechanism with acceptable toxicity properties against MEK. Further, 200 ns of MD simulation combined with MM-GBSA/PBSA calculations confirms that DB06920 may have stable binding conformations with MEK thus step forwarded to the experimental studies in the near future.Communicated by Ramaswamy H. Sarma.
MeSH term(s)	Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy ; Molecular Dynamics Simulation ; Protein Binding ; Molecular Docking Simulation ; Early Detection of Cancer ; Lung Neoplasms/drug therapy ; Machine Learning ; Mitogen-Activated Protein Kinase Kinases
Chemical Substances	Mitogen-Activated Protein Kinase Kinases (EC 2.7.12.2)
Language	English
Publishing date	2023-03-30
Publishing country	England
Document type	Journal Article
ZDB-ID	49157-3
ISSN	1538-0254 ; 0739-1102
ISSN (online)	1538-0254
ISSN	0739-1102
DOI	10.1080/07391102.2023.2194994
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Article ; Online: Prediction of Micronucleus Assay Outcome Using In Vivo Activity Data and Molecular Structure Features.

Ramesh, Priyanka / Veerappapillai, Shanthi

Applied biochemistry and biotechnology

2021 Volume 193, Issue 12, Page(s) 4018–4034

Abstract: In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the in ... ...

Abstract	In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the in vivo experiments and the expenses, we intended to develop novel machine learning-based tools to predict the toxicity of the compounds with high precision. A total of 372 compounds with known toxicity information were retrieved from the PubChem Bioassay database and literature. The fingerprints and descriptors of the compounds were generated using PaDEL and ChemSAR, respectively, for the analysis. The performance of the models was assessed using the three tires of evaluation strategies such as fivefold, tenfold, and validation by external dataset. Further, structural alerts causing genotoxicity of the compounds were identified using SARpy method. Of note, fingerprint-based random forest model built in our analysis is able to demonstrate the highest accuracy of about 0.97 during tenfold cross-validation. In essence, our study highlights that structural alerts such as chlorocyclohexane and trimethylamine are likely to be the leading cause of toxicity in humans. Indeed, we believe that random forest model generated in this study is appropriate for reduction of test animals and should be considered in the future for the good practice of animal welfare.
MeSH term(s)	Animals ; Biological Assay ; Computer Simulation ; Databases, Factual ; Humans ; Machine Learning ; Micronucleus Tests ; Models, Biological ; Molecular Structure
Language	English
Publishing date	2021-10-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	392344-7
ISSN	1559-0291 ; 0273-2289
ISSN (online)	1559-0291
ISSN	0273-2289
DOI	10.1007/s12010-021-03720-8
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Article: Prediction of Micronucleus Assay Outcome Using In Vivo Activity Data and Molecular Structure Features

Ramesh, Priyanka / Veerappapillai, Shanthi

Applied biochemistry and biotechnology. 2021 Dec., v. 193, no. 12

2021

Abstract	In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the in vivo experiments and the expenses, we intended to develop novel machine learning-based tools to predict the toxicity of the compounds with high precision. A total of 372 compounds with known toxicity information were retrieved from the PubChem Bioassay database and literature. The fingerprints and descriptors of the compounds were generated using PaDEL and ChemSAR, respectively, for the analysis. The performance of the models was assessed using the three tires of evaluation strategies such as fivefold, tenfold, and validation by external dataset. Further, structural alerts causing genotoxicity of the compounds were identified using SARpy method. Of note, fingerprint-based random forest model built in our analysis is able to demonstrate the highest accuracy of about 0.97 during tenfold cross-validation. In essence, our study highlights that structural alerts such as chlorocyclohexane and trimethylamine are likely to be the leading cause of toxicity in humans. Indeed, we believe that random forest model generated in this study is appropriate for reduction of test animals and should be considered in the future for the good practice of animal welfare.
Keywords	algorithms ; animal welfare ; bioassays ; biotechnology ; chemical structure ; data collection ; databases ; drugs ; genotoxicity ; humans ; micronucleus tests ; mutagens ; prediction ; trimethylamine
Language	English
Dates of publication	2021-12
Size	p. 4018-4034.
Publishing place	Springer US
Document type	Article
ZDB-ID	392344-7
ISSN	0273-2289
ISSN	0273-2289
DOI	10.1007/s12010-021-03720-8
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Exploring the potential of

Pant, Rajat / Kumar, Ravi / Sharma, Shilpa / Karuppasamy, Ramanathan / Veerappapillai, Shanthi

Journal of biomolecular structure & dynamics

2023 , Page(s) 1–15

Abstract: Pesticides are widely used in agriculture but at the same time, a majority of them are known to cause serious harm to health and the environment. In the recent past, laccases have been reported as key enzymes having the ability to degrade pollutants by ... ...

Abstract	Pesticides are widely used in agriculture but at the same time, a majority of them are known to cause serious harm to health and the environment. In the recent past, laccases have been reported as key enzymes having the ability to degrade pollutants by converting them into less toxic forms. In this investigation, laccase from polyextremophilic bacterium
Language	English
Publishing date	2023-11-21
Publishing country	England
Document type	Journal Article
ZDB-ID	49157-3
ISSN	1538-0254 ; 0739-1102
ISSN (online)	1538-0254
ISSN	0739-1102
DOI	10.1080/07391102.2023.2283165
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Article ; Online: Computational biophysics approach towards the discovery of multi-kinase blockers for the management of MAPK pathway dysregulation.

Thirunavukkarasu, Muthu Kumar / Veerappapillai, Shanthi / Karuppasamy, Ramanathan

Molecular diversity

2022 Volume 27, Issue 5, Page(s) 2093–2110

Abstract: The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. ... ...

Abstract	The MAPK pathway is important in human lung cancer and is improperly activated in a substantial proportion through number of ways. Strategies on dual-targeting RAF and MEK are an alternative option to diminish the limitations in this pathway inhibition. Hence, we implemented parallel pharmacophore screening of 11,808 DrugBank compounds against RAF and MEK. ADHRR and DHHRR were modeled as a pharmacophore hypothesis for RAF and MEK respectively. Importantly, these hypotheses resulted an AUC value of > 0.90 with the external data set. As a result of phase screening, glide docking, and prime-MM/GBSA scoring, it is determined that DB08424 and DB08907 have the best chances of acting as multi-kinase inhibitors. The pi-cation interaction with key amino acid residues of both target receptors may responsible for the stronger binding with these kinases. Cumulative 600 ns MD simulation studies validate the binding ability of these compounds. Significantly, the hit compounds resulted higher number of stable conformational state with less atomic movements than the reference compound against both targets. The anti-cancer efficacy of the lead compounds was validated through machine learning-based approaches. These findings suggest that DB08424 and DB08907 might be novel molecules to be explored further experimentally to block the MAPK signaling in lung cancer patients.
MeSH term(s)	Humans ; Molecular Dynamics Simulation ; Molecular Docking Simulation ; Protein Binding ; Lung Neoplasms ; Mitogen-Activated Protein Kinase Kinases
Chemical Substances	Mitogen-Activated Protein Kinase Kinases (EC 2.7.12.2)
Language	English
Publishing date	2022-10-19
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1376507-3
ISSN	1573-501X ; 1381-1991
ISSN (online)	1573-501X
ISSN	1381-1991
DOI	10.1007/s11030-022-10545-y
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Article: Discovery of a Potent Candidate for RET-Specific Non-Small-Cell Lung Cancer-A Combined In Silico and In Vitro Strategy.

Ramesh, Priyanka / Shin, Woong-Hee / Veerappapillai, Shanthi

Pharmaceutics

2021 Volume 13, Issue 11

Abstract: Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET- ... ...

Abstract	Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET-positive NSCLC. However, specificity, toxicity, and reduced efficacy limit the usage of multiple kinase inhibitors in targeting RET protein. Thus, in the present investigation, we aimed to figure out novel and potent candidates for the inhibition of RET protein using combined in silico and in vitro strategies. In the present study, screening of 11,808 compounds from the DrugBank repository was accomplished by different hypotheses such as pharmacophore, e-pharmacophore, and receptor cavity-based models in the initial stage. The results from the different hypotheses were then integrated to eliminate the false positive prediction. The inhibitory activities of the screened compounds were tested by the glide docking algorithm. Moreover, RF score, Tanimoto coefficient, prime-MM/GBSA, and density functional theory calculations were utilized to re-score the binding free energy of the docked complexes with high precision. This procedure resulted in three lead molecules, namely DB07194, DB03496, and DB11982, against the RET protein. The screened lead molecules together with reference compounds were then subjected to a long molecular dynamics simulation with a 200 ns time duration to validate the inhibitory activity. Further analysis of compounds using MM-PBSA and mutation studies resulted in the identification of potent compound DB07194. In essence, a cell viability assay with RET-specific lung cancer cell line LC-2/ad was also carried out to confirm the in vitro biological activity of the resultant compound, DB07194. Indeed, the results from our study conclude that DB07194 can be effectively translated for this new therapeutic purpose, in contrast to the properties for which it was originally designed and synthesized.
Language	English
Publishing date	2021-10-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527217-2
ISSN	1999-4923
ISSN	1999-4923
DOI	10.3390/pharmaceutics13111775
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