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Computational Approach for the Development of pH-Selective PD-1/PD-L1 Signaling Pathway Inhibition in Fight with Cancer.

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Title: Computational Approach for the Development of pH-Selective PD-1/PD-L1 Signaling Pathway Inhibition in Fight with Cancer.
Authors: McDowell, Roderick C.1 (AUTHOR) roderick.mcdowell@yahoo.com, Booth, Jordhan D.2 (AUTHOR) jdbooth@student.tougaloo.edu, McGowan, Allyson2 (AUTHOR) ajmcgowan@student.tougaloo.edu, Kolodziejczyk, Wojciech1 (AUTHOR) kolodziejczyk.wojciech@gmail.com, Hill, Glake A.1 (AUTHOR) glakeh@icnanotox.org, Banerjee, Santanu2 (AUTHOR) sbanerjee@tougaloo.edu, Feng, Manliang2 (AUTHOR) mfeng@tougaloo.edu, Kapusta, Karina2 (AUTHOR) kkapusta@tougaloo.edu
Source: Cancers. Jul2024, Vol. 16 Issue 13, p2295. 19p.
Subject Terms: *COMPUTER-assisted molecular modeling, *RESEARCH funding, *INVESTIGATIONAL drugs, *CELLULAR signal transduction, *IMMUNE checkpoint inhibitors, *CELL lines, *MOLECULAR structure, *DRUG efficacy, *TUMORS, *DRUG development, *ACID-base equilibrium, *CARCINOGENESIS, *PHARMACODYNAMICS
Abstract: Simple Summary: Despite considerable progress in cancer research and treatment, cancer continues to be a major health challenge, often requiring invasive treatments with substantial side effects. Immuno-therapy, which targets the immune system's PD-1/PD-L1 pathway, represents a promising alternative. This critical pathway allows cancer cells to avoid immune destruction by inhibiting T-cells. Our study employs computational techniques to develop inhibitors that block the PD-L1 pathway, specifically in the acidic environment of tumors. By analyzing around 10,000 natural compounds, we identified a potential pH-selective inhibitor that shows greater effectiveness in the acidic conditions typical of cancerous tissues. This research suggests a novel approach for experimental groups to explore, focusing on developing targeted, pH-dependent inhibitors that could mark a significant step in enhancing the precision and effectiveness of immunotherapy treatments, potentially revolutionizing cancer therapy. Immunotherapy, particularly targeting the PD-1/PD-L1 pathway, holds promise in cancer treatment by regulating the immune response and preventing cancer cells from evading immune destruction. Nonetheless, this approach poses a risk of unwanted immune system activation against healthy cells. To minimize this risk, our study proposes a strategy based on selective targeting of the PD-L1 pathway within the acidic microenvironment of tumors. We employed in silico methods, such as virtual screening, molecular mechanics, and molecular dynamics simulations, analyzing approximately 10,000 natural compounds from the MolPort database to find potential hits with the desired properties. The simulations were conducted under two pH conditions (pH = 7.4 and 5.5) to mimic the environments of healthy and cancerous cells. The compound MolPort-001-742-690 emerged as a promising pH-selective inhibitor, showing a significant affinity for PD-L1 in acidic conditions and lower toxicity compared to known inhibitors like BMS-202 and LP23. A detailed 1000 ns molecular dynamics simulation confirmed the stability of the inhibitor-PD-L1 complex under acidic conditions. This research highlights the potential of using in silico techniques to discover novel pH-selective inhibitors, which, after experimental validation, may enhance the precision and reduce the toxicity of immunotherapies, offering a transformative approach to cancer treatment. [ABSTRACT FROM AUTHOR]
Copyright of Cancers is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Computational Approach for the Development of pH-Selective PD-1/PD-L1 Signaling Pathway Inhibition in Fight with Cancer.
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  Data: <searchLink fieldCode="AR" term="%22McDowell%2C+Roderick+C%2E%22">McDowell, Roderick C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> roderick.mcdowell@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Booth%2C+Jordhan+D%2E%22">Booth, Jordhan D.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jdbooth@student.tougaloo.edu</i><br /><searchLink fieldCode="AR" term="%22McGowan%2C+Allyson%22">McGowan, Allyson</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> ajmcgowan@student.tougaloo.edu</i><br /><searchLink fieldCode="AR" term="%22Kolodziejczyk%2C+Wojciech%22">Kolodziejczyk, Wojciech</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> kolodziejczyk.wojciech@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Hill%2C+Glake+A%2E%22">Hill, Glake A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> glakeh@icnanotox.org</i><br /><searchLink fieldCode="AR" term="%22Banerjee%2C+Santanu%22">Banerjee, Santanu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sbanerjee@tougaloo.edu</i><br /><searchLink fieldCode="AR" term="%22Feng%2C+Manliang%22">Feng, Manliang</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> mfeng@tougaloo.edu</i><br /><searchLink fieldCode="AR" term="%22Kapusta%2C+Karina%22">Kapusta, Karina</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> kkapusta@tougaloo.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Cancers%22">Cancers</searchLink>. Jul2024, Vol. 16 Issue 13, p2295. 19p.
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  Data: *<searchLink fieldCode="DE" term="%22COMPUTER-assisted+molecular+modeling%22">COMPUTER-assisted molecular modeling</searchLink><br />*<searchLink fieldCode="DE" term="%22RESEARCH+funding%22">RESEARCH funding</searchLink><br />*<searchLink fieldCode="DE" term="%22INVESTIGATIONAL+drugs%22">INVESTIGATIONAL drugs</searchLink><br />*<searchLink fieldCode="DE" term="%22CELLULAR+signal+transduction%22">CELLULAR signal transduction</searchLink><br />*<searchLink fieldCode="DE" term="%22IMMUNE+checkpoint+inhibitors%22">IMMUNE checkpoint inhibitors</searchLink><br />*<searchLink fieldCode="DE" term="%22CELL+lines%22">CELL lines</searchLink><br />*<searchLink fieldCode="DE" term="%22MOLECULAR+structure%22">MOLECULAR structure</searchLink><br />*<searchLink fieldCode="DE" term="%22DRUG+efficacy%22">DRUG efficacy</searchLink><br />*<searchLink fieldCode="DE" term="%22TUMORS%22">TUMORS</searchLink><br />*<searchLink fieldCode="DE" term="%22DRUG+development%22">DRUG development</searchLink><br />*<searchLink fieldCode="DE" term="%22ACID-base+equilibrium%22">ACID-base equilibrium</searchLink><br />*<searchLink fieldCode="DE" term="%22CARCINOGENESIS%22">CARCINOGENESIS</searchLink><br />*<searchLink fieldCode="DE" term="%22PHARMACODYNAMICS%22">PHARMACODYNAMICS</searchLink>
– Name: Abstract
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  Data: Simple Summary: Despite considerable progress in cancer research and treatment, cancer continues to be a major health challenge, often requiring invasive treatments with substantial side effects. Immuno-therapy, which targets the immune system's PD-1/PD-L1 pathway, represents a promising alternative. This critical pathway allows cancer cells to avoid immune destruction by inhibiting T-cells. Our study employs computational techniques to develop inhibitors that block the PD-L1 pathway, specifically in the acidic environment of tumors. By analyzing around 10,000 natural compounds, we identified a potential pH-selective inhibitor that shows greater effectiveness in the acidic conditions typical of cancerous tissues. This research suggests a novel approach for experimental groups to explore, focusing on developing targeted, pH-dependent inhibitors that could mark a significant step in enhancing the precision and effectiveness of immunotherapy treatments, potentially revolutionizing cancer therapy. Immunotherapy, particularly targeting the PD-1/PD-L1 pathway, holds promise in cancer treatment by regulating the immune response and preventing cancer cells from evading immune destruction. Nonetheless, this approach poses a risk of unwanted immune system activation against healthy cells. To minimize this risk, our study proposes a strategy based on selective targeting of the PD-L1 pathway within the acidic microenvironment of tumors. We employed in silico methods, such as virtual screening, molecular mechanics, and molecular dynamics simulations, analyzing approximately 10,000 natural compounds from the MolPort database to find potential hits with the desired properties. The simulations were conducted under two pH conditions (pH = 7.4 and 5.5) to mimic the environments of healthy and cancerous cells. The compound MolPort-001-742-690 emerged as a promising pH-selective inhibitor, showing a significant affinity for PD-L1 in acidic conditions and lower toxicity compared to known inhibitors like BMS-202 and LP23. A detailed 1000 ns molecular dynamics simulation confirmed the stability of the inhibitor-PD-L1 complex under acidic conditions. This research highlights the potential of using in silico techniques to discover novel pH-selective inhibitors, which, after experimental validation, may enhance the precision and reduce the toxicity of immunotherapies, offering a transformative approach to cancer treatment. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Cancers is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/cancers16132295
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 19
        StartPage: 2295
    Subjects:
      – SubjectFull: COMPUTER-assisted molecular modeling
        Type: general
      – SubjectFull: RESEARCH funding
        Type: general
      – SubjectFull: INVESTIGATIONAL drugs
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      – SubjectFull: CELLULAR signal transduction
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      – SubjectFull: IMMUNE checkpoint inhibitors
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      – SubjectFull: MOLECULAR structure
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      – SubjectFull: DRUG efficacy
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      – SubjectFull: DRUG development
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      – SubjectFull: ACID-base equilibrium
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      – SubjectFull: CARCINOGENESIS
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      – SubjectFull: PHARMACODYNAMICS
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              Text: Jul2024
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