In silico modeling of PAX8–PPARγ fusion protein in thyroid carcinoma: influence of structural perturbation by fusion on ligand-binding affinity

2021 ◽  
Author(s):  
Kaori Sakaguchi ◽  
Yoshio Okiyama ◽  
Shigenori Tanaka
Keyword(s):  
Thyroid Carcinoma ◽  
Fusion Protein ◽  
Ligand Binding ◽  
Binding Affinity ◽  
In Silico ◽  
Structural Perturbation ◽  
In Silico Modeling

Automated, Accurate, and Scalable Relative Protein-Ligand Binding Free Energy Calculations using Lambda Dynamics

2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Computational Cost ◽  
Combinatorial Libraries ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Efficient Estimation ◽  
Lead Compound

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>

Distinct Modulation of Wild-Type and Selective Gene Mutated Vitamin D Receptor by Essential Poly Unsaturated Fatty Acids

2021 ◽  
Vol 21 ◽  
Author(s):  
Hari Balaji ◽  
Selvaraj Ayyamperuma ◽  
Niladri Saha ◽  
Shyam Sundar Pottabathula ◽  
Jubie Selvaraj ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Vitamin D ◽  
Ligand Binding ◽  
Vitamin D Deficiency ◽  
Binding Affinity ◽  
Unsaturated Fatty Acids ◽  
Binding Domain ◽  
Ligand Binding Domain ◽  
Binding Energies ◽  
Wild Type

: Vitamin-D deficiency is a global concern. Gene mutations in the vitamin D receptor’s (VDR) ligand binding domain (LBD) variously alter the ligand binding affinity, heterodimerization with retinoid X receptor (RXR) and inhibit coactivator interactions. These LBD mutations may result in partial or total hormone unresponsiveness. A plethora of evidence report that selective long chain polyunsaturated fatty acids (PUFAs) including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and arachidonic acid (AA) bind to the ligand-binding domain of VDR and lead to transcriptional activation. We therefore hypothesize that selective PUFAs would modulate the dynamics and kinetics of VDRs, irrespective bioactive of vitamin-D binding. The spatial arrangements of the selected PUFAs in VDR active site were examined by in-silico docking studies. The docking results revealed that PUFAs have fatty acid structure-specific binding affinity towards VDR. The calculated EPA, DHA & AA binding energies (Cdocker energy) were lesser compared to vitamin-D in wild type of VDR (PDB id: 2ZLC). Of note, the DHA has higher binding interactions to the mutated VDR (PDB id: 3VT7) when compared to the standard Vitamin-D. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding of DHA with mutated VDR complex. These findings suggest the unique roles of PUFAs in VDR activation and may offer alternate strategy to circumvent vitamin-D deficiency.

In silico approach for designing a novel recombinant fusion protein as a Candidate Vaccine against HPV

2020 ◽  
Vol 17 ◽  
Author(s):  
Mohsen Sisakht ◽  
Amir Mahmoodzadeh ◽  
Mohammadsaeid Zahedi ◽  
Davood Rostamzadeh ◽  
Amin Moradi Hasan-Abad ◽  
...  
Keyword(s):  
Immune Responses ◽  
Fusion Protein ◽  
In Silico ◽  
Precancerous Lesions ◽  
Candidate Vaccine ◽  
T Cell Epitopes ◽  
Binding Interaction ◽  
Hpv16 E6 ◽  
E7 Proteins

Background: Human papillomavirus (HPV) is the main biological agent causing sexually transmitted diseases (STDs), including precancerous lesions and several types of prevalent cancers. To date, numerous types of vaccines are designed to prevent high-risk HPV. However, their prophylactic effect is not the same and does not clear previous infections. Therefore, there is an urgent need for developing therapeutic vaccines that trigger cell-mediated immune responses for the treatment of HPV. The HPV16 E6 and E7 proteins are ideal targets for vaccine therapy against HPV. Fusion protein vaccines, which include both immunogenic interest protein and an adjuvant for augmenting the immunogenicity effects, are theoretically capable of guarantee the power of the immune system against HPV. Method: A vaccine construct, including HPV16 E6/E7 proteins along with a heat shock protein GP96 (E6/E7-NTGP96 construct), was designed using in silico methods. By the aid of the SWISS-MODEL server, the optimal 3D model of the designed vaccine was selected, followed by physicochemical and molecular parameters were performed using bioinformatics tools. Docking studies were done to evaluate the binding interaction of the vaccine. Allergenicity, immunogenicity, B, and T cell epitopes of the designed construct were predicted. Results: Immunological and structural computational results illustrated that our designed construct is potentially proper for stimulation of cellular and humoral immune responses against HPV. Conclusion: Computational studies showed that the E6/E7-NTGP96 construct is a promising candidate vaccine that needs further in vitro and in vivo evaluations.

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