Predicting the effect of amino acid substitutions on protein-protein affinity (typically evaluated via the change of protein binding free energy) is important for both understanding the disease-causing mechanism of missense mutations and guiding protein engineering. In addition, researchers are also interested in understanding which energy components are mostly affected by the mutation and how the mutation affects the overall structure of the corresponding protein. Here we report a webserver, the Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) webserver, which addresses the demand for tools for predicting the change of protein binding free energy. SAAMBE is an easy to use webserver, which only requires that a coordinate file be inputted and the user is provided with various, but easy to navigate, options. The user specifies the mutation position, wild type residue and type of mutation to be made. The server predicts the binding free energy change, the changes of the corresponding energy components and provides the energy minimized 3D structure of the wild type and mutant proteins for download. The SAAMBE protocol performance was tested by benchmarking the predictions against over 1300 experimentally determined changes of binding free energy and a Pearson correlation coefficient of 0.62 was obtained. How the predictions can be used for discriminating disease-causing from harmless mutations is discussed. The webserver can be accessed via http://compbio.clemson.edu/saambe_webserver/.
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http://dx.doi.org/10.3390/ijms17040547 | DOI Listing |
J Chem Inf Model
January 2025
Cresset, New Cambridge House, Bassingbourn Road, Litlington SG8 0O5, Cambridgeshire, United Kingdom.
Recent increases in the availability of computational power have improved the accessibility of ligand-protein relative binding free energy (RBFE) calculations; however, these calculations remain resource-intensive, which can limit their practical application. RBFE calculations typically use a set of thermodynamic intermediates mediated by the transformation coordinate λ. Optimizing λ offers a way to tune the computational efforts required for a given RBFE calculation.
View Article and Find Full Text PDFMol Divers
January 2025
Department of Biotechnology, Deen Dayal, Upadhyay Gorakhpur University, Gorakhpur, India.
Chronic lymphocytic leukemia (CLL) is a malignancy caused by the overexpression of the anti-apoptotic protein B-cell lymphoma-2 (BCL-2), making it a critical therapeutic target. This study integrates computational screening, molecular docking, and molecular dynamics to identify and validate novel BCL-2 inhibitors from the ChEMBL database. Starting with 836 BCL-2 inhibitors, we performed ADME and Lipinski's Rule of Five (RO5) filtering, clustering, maximum common substructure (MCS) analysis, and machine learning models (Random Forest, SVM, and ANN), yielding a refined set of 124 compounds.
View Article and Find Full Text PDFMol Divers
January 2025
Data Science, Amity Institute of Integrative Sciences and Health, Amity University Haryana, Gurugram, India.
The ATP-binding cassette transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP-binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies.
View Article and Find Full Text PDFMol Divers
January 2025
Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal, 576104, India.
SH2 (Src Homology 2) domains play a crucial role in phosphotyrosine-mediated signaling and have emerged as promising drug targets, particularly in cancer therapy. STAT3 (Signal Transducer and Activator of Transcription 3), which contains an SH2 domain, plays a pivotal role in cancer progression and immune evasion because it facilitates the dimerization of STAT3, which is essential for their activation and subsequent nuclear translocation. SH2 domain-mediated STAT3 inhibition disrupts this binding, reduces phosphorylation of STAT3, and impairs dimerization.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Baden-Wuerttemberg, Germany.
Background: Florzolotau (APN-1607) tau-PET has shown distinct patterns of binding in patients with AD and 4-repeat tauopathies. We aimed to establish disease-specific tau covariance patterns in AD and PSP/CBS and validate them as user-independent quantitative biomarkers for reference-region-free evaluation of tau-PET in an independent clinical cohort.
Method: We analyzed Florzolotau PET data from four different cohorts.
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