scholarly journals Physical epistatic landscape of antibody binding affinity

2017 ◽  
Author(s):  
Rhys M. Adams ◽  
Justin B. Kinney ◽  
Aleksandra M. Walczak ◽  
Thierry Mora
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Evolutionary Process ◽  
Null Model ◽  
High Specificity ◽  
Affinity Maturation ◽  
High Affinity ◽  
Antibody Sequence ◽  
Negative Epistasis ◽  
Insight Into

Affinity maturation produces antibodies that bind antigens with high specificity by accumulating mutations in the antibody sequence. Mapping out the antibody-antigen affinity landscape can give us insight into the accessible paths during this rapid evolutionary process. By developing a carefully controlled null model for noninteracting mutations, we characterized epistasis in affinity measurements of a large library of antibody variants obtained by Tite-Seq, a recently introduced Deep Mutational Scan method yielding physical values of the binding constant. We show that representing affinity as the binding free energy minimizes epistasis. Yet, we find that epistatically interacting sites contribute substantially to binding. In addition to negative epistasis, we report a large amount of beneficial epistasis, enlarging the space of high-affinity antibodies as well as their mutational accessibility. These properties suggest that the degeneracy of antibody sequences that can bind a given antigen is enhanced by epistasis — an important property for vaccine design.

Insight into the adsorption profiles of the Saprolegnia monoica chitin synthase MIT domain on POPA and POPC membranes by molecular dynamics simulation studies

2016 ◽  
Vol 18 (7) ◽  
pp. 5281-5290 ◽  
Author(s):  
Guanglin Kuang ◽  
Lijun Liang ◽  
Christian Brown ◽  
Qi Wang ◽  
Vincent Bulone ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulation ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Chitin Synthase ◽  
Dynamics Simulation ◽  
Simulation Methods ◽  
Simulation Studies ◽  
Insight Into

The binding mode and binding free energy of the Saprolegnia monoica chitin synthase MIT domain with the POPA membrane have been studied by molecular simulation methods.

Computational insight into the anticholinesterase activities and electronic properties of physostigmine analogs

2019 ◽  
Vol 11 (15) ◽  
pp. 1907-1928 ◽  
Author(s):  
Adebayo A Adeniyi ◽  
Jeanet Conradie
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Quantum Mechanics ◽  
Structural Properties ◽  
Conformational Changes ◽  
Energy Surface ◽  
Binding Free Energy ◽  
The Elderly ◽  
Free Energy Surface ◽  
Insight Into

Aim: Alzheimer's disease (AD) is known to be themajor cause of dementia among the elderly. The structural properties and binding interactions of the AD drug physostigmine (-)-phy, and its analogues (-)-hex and (-)-phe and (+)-phe, were examined, as well as their impact on the conformational changes of two different AD target enzymes AChE and BChE. Materials & methods: The conformational changes were studied using molecular dynamics and structural properties using Quantum mechanics. Results & conclusions: The binding free energy (ΔGbind) and the change in the free energy surface (FES) computed from the funnel metadynamics (FMD) simulation, both support the idea that inhibitors (-)-phe and (-)-hex have better binding activities toward enzyme AChE, and that (-)-phe is stronger in binding than the present AD drug (-)-phy.

scholarly journals Investigation of Molecular Details of Keap1-Nrf2 Inhibitors Using Molecular Dynamics and Umbrella Sampling Techniques

Molecules ◽  
2019 ◽  
Vol 24 (22) ◽  
pp. 4085 ◽  
Author(s):  
Ashwini Machhindra Londhe ◽  
Changdev Gorakshnath Gadhe ◽  
Sang Min Lim ◽  
Ae Nim Pae
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Binding Pocket ◽  
Umbrella Sampling ◽  
Valuable Insight ◽  
Protein Protein Interaction ◽  
Kelch Domain ◽  
Insight Into

In this study, we investigate the atomistic details of Keap1-Nrf2 inhibitors by in-depth modeling techniques, including molecular dynamics (MD) simulations, and the path-based free energy method of umbrella sampling (US). The protein–protein interaction (PPI) of Keap1-Nrf2 is implicated in several neurodegenerative diseases like cancer, diabetes, and cardiomyopathy. A better understanding of the five sub-pocket binding sites for Nrf2 (ETGE and DLG motifs) inside the Kelch domain would expedite the inhibitor design process. We selected four protein–ligand complexes with distinct co-crystal ligands and binding occupancies inside the Nrf2 binding site. We performed 100 ns of MD simulation for each complex and analyzed the trajectories. From the results, it is evident that one ligand (1VV) has flipped inside the binding pocket, whereas the remaining three were stable. We found that Coulombic (Arg483, Arg415, Ser363, Ser508, and Ser602) and Lennard–Jones (Tyr525, Tyr334, and Tyr572) interactions played a significant role in complex stability. The obtained binding free energy values from US simulations were consistent with the potencies of simulated ligands. US simulation highlight the importance of basic and aromatic residues in the binding pocket. A detailed description of the dissociation process brings valuable insight into the interaction of the four selected protein–ligand complexes, which could help in the future to design more potent PPI inhibitors.

scholarly journals Molecular Interactions and Binding Free Energy of Polydopamine and Methylene Blue: A DFT Study

2020 ◽  
Vol 17 (7) ◽  
pp. 719-725
Author(s):  
Kunlanat SRIPHUMRAT ◽  
Phattaraporn THONGSAMAI ◽  
Montra CHAIRAT ◽  
Pilan SAENSUK ◽  
Nawee KUNGWAN ◽  
...  
Keyword(s):  
Methylene Blue ◽  
Free Energy ◽  
Complex Formation ◽  
Intermolecular Interactions ◽  
Binding Free Energy ◽  
Autodock Vina ◽  
Net Charge ◽  
Basic Solutions ◽  
Ph Range ◽  
Insight Into

Polydopamine (PDA) is a kind of mussel-inspired material. It has been applied as a coating and an adsorbent material. As an adsorbent, the PDA microspheres were used to remove methylene blue (MB) in aqueous solution. It was reported that the efficiency of the PDA adsorbent depends on the pH of the solution. Furthermore, in a pH range of 3 - 10, the hydroxyl and amine functional groups of PDA can be either protonated or deprotonated. The change of the net charge of PDA can affect the intermolecular interactions between PDA and MB. It was proposed that both of the electrostatic and p-p interactions should be dominant in the acidic and basic solutions. Therefore, the structural properties and intermolecular interactions of the PDA-MB complex should be investigated. Such an investigation can be useful for the improvement of the PDA microspheres for the other dyes. To get insight into the roles of PDA structure and its role as an interesting adsorbent for MB, the PDA-MB complex formation was carried out at pH 7. The PDA dimers which have six possible structures were selected. The optimization of all PDA dimers and MB was performed in the gas phase at the B3LYP/6-311++G(d,p) calculations. After that, the complex formation of the optimized PDA dimers and MB was performed using the AutoDock Vina V1.1.2. The binding free energy of the PDA dimers and MB was in a range of -3.2 to -3.7 kcal/mol, which indicated that the binding of PDA dimer and MB is spontaneous. The results showed that the p-p interaction between PDA dimer and MB plays a crucial role in the complex formation. Likewise, the sandwich-like structures of the complexes are more stable than the twisted structures.

Insight into the key interactions of bromodomain inhibitors based on molecular docking, interaction fingerprinting, molecular dynamics and binding free energy calculation

2015 ◽  
Vol 11 (5) ◽  
pp. 1295-1304 ◽  
Author(s):  
Ting Ran ◽  
Zhimin Zhang ◽  
Kejun Liu ◽  
Yi Lu ◽  
Huifang Li ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Docking ◽  
Binding Free Energy ◽  
Interaction Mechanism ◽  
Free Energy Calculation ◽  
Energy Calculation ◽  
Binding Free Energy Calculation ◽  
Docking Interaction ◽  
Insight Into

The interaction mechanism of bromodomain inhibitors was investigated using interaction fingerprinting and binding free energy based methods.

Large-Scale Assessment of Binding Free Energy Calculations in Active Drug Discovery Projects

2020 ◽  
Author(s):  
Christina Schindler ◽  
Hannah Baumann ◽  
Andreas Blum ◽  
Dietrich Böse ◽  
Hans-Peter Buchstaller ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Large Scale ◽  
Active Drug ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Energy Calculation ◽  
Large Scale Assessment ◽  
New Public ◽  
Binding Free Energy Calculations

Here we present an evaluation of the binding affinity prediction accuracy of the free energy calculation method FEP+ on internal active drug discovery projects and on a large new public benchmark set.<br>

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>

Sign in / Sign up

Export Citation Format

Share Document