ff99SB Force Field Research Articles

Force Field Limitations of All-Atom Continuous Constant pH Molecular Dynamics.

All-atom constant pH molecular dynamics simulations offer a powerful tool for understanding pH-mediated and proton-coupled biological processes. As the protonation equilibria of protein sidechains are shifted by electrostatic interactions and desolvation energies, pK a values calculated from the constant pH simulations may be sensitive to the underlying protein force field and water model. Here we investigated the force field dependence of the all-atom particle mesh Ewald (PME) continuous constant pH (PME-CpHMD) simulations of a mini-protein BBL. The replica-exchange titration simulations based on the Amber ff19SB and ff14SB force fields with the respective water models showed significantly overestimated pK a downshifts for a buried histidine (His166) and for two glutamic acids (Glu141 and Glu161) that are involved in salt-bridge interactions. These errors (due to undersolvation of neutral histidines and overstabilization of salt bridges) are consistent with the previously reported pK a's based on the CHARMM c22/CMAP force field, albeit in larger magnitudes. The pK a calculations also demonstrated that ff19SB with OPC water is significantly more accurate than ff14SB with TIP3P water, and the salt-bridge related pK a downshifts can be partially alleviated by the atom-pair specific Lennard-Jones corrections (NBFIX). Together, these data suggest that the accuracies of the protonation equilibria of proteins from constant pH simulations can significantly benefit from improvements of force fields.

De novo design of covalent bonding peptides for target protein

To rapidly develop hyper-stable inhibitors that bind specifically and covalently to functional proteins is critical for diagnostics and therapeutics. Taking targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants as an example, we report a fast and low-cost de novo design strategy on covalent bonding peptides toward the SARS-CoV-2 spike protein receptor-binding domain (RBD), hence blocking its interaction with the human angiotensin-converting enzyme 2 (hACE2). As a proof-of-concept, peptide scaffolds built by ligating the hotspot residues at the hACE2-Omicron RBD interface were docked against RBD, and then the chemically modified peptides were designed by predicting their reactivity against RBD using a modified Amber ff14SB force field. Two peptides (15- and 16-mer peptides) were equipped with sulfonyl fluoride warheads bound with the conserved Y449 residue of RBD via the sulfur (VI) fluoride exchange (SuFEx) click chemistry. With permanent bonding and without dissociation, the two peptides blocked Omicron BA.2 pseudovirus infection with IC50 values of 1.07 μM and 1.56 μM, respectively. Our design approach greatly promotes the discovery of hyper-stable inhibitors against SARS-CoV-2 variants and other rapidly evolving viruses, potentially applicable to combat future viral outbreaks efficiently.

Unveiling dissociation mechanisms and binding patterns in the UHRF1-DPPA3 complex via multi-replica molecular dynamics simulations.

Ubiquitin-like with PHD and RING finger domain containing protein 1 (UHRF1) is responsible for preserving the stability of genomic methylation through the recruitment of DNA methyltransferase 1 (DNMT1). However, the interaction between Developmental pluripotency associated 3 (DPPA3) and the pre-PHD-PHD (PPHD) domain of UHRF1 hinders the nuclear localization of UHRF1. This disruption has implications for potential cancer treatment strategies. Drugs that mimic the binding pattern between DPPA3 and PPHD could offer a promising approach to cancer treatment. Our study reveals that DPPA3 undergoes dissociation from the C-terminal through three different modes of helix unfolding. Furthermore, we have identified key residue pairs involved in this dissociation process and potential drug-targeting residues. These findings offer valuable insights into the dissociation mechanism of DPPA3 from PPHD and have the potential to inform the design of novel drugs targeting UHRF1 for cancer therapy. To comprehend the dissociation process and binding patterns of PPHD-DPPA3, we employed enhanced sampling techniques, including steered molecular dynamics (SMD) and conventional molecular dynamics (cMD). Additionally, we utilized self-organizing maps (SOM) and time-resolved force distribution analysis (TRFDA) methodologies. The Gromacs software was used for performing molecular dynamics simulations, and the AMBER FF14SB force field was applied to the protein.

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R2 = 0.55), demonstrating a significant advantage over the MM/PBSA (R2 = 0.02) and MM/GBSA (R2 = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors. All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States.

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

Uncovering the interactions between PME and PMEI at the gene and protein levels: Implications for the design of specific PMEI.

Pectin methylesterase inhibitor (PMEI) can specifically bind and inhibit the activity of pectin methylesterase (PME), which has been widely used in fruit and vegetable juice processing. However, the limited three-dimensional structure, unclear action mechanism, low thermal stability and biological activity of PMEI severely limited its application. In this work, molecular recognition and conformational changes of PME and PMEI were analyzed by various molecular simulation methods. Then suggestions were proposed for improving thermal stability and affinity maturation of PMEI through semi-rational design. Phylogenetic trees of PME and PMEI were established using the Maximum likelihood (ML) method. The results show that PME and PMEI have good sequence and structure conservation in various plants, and the simulated data can be widely adopted. In this work, MD simulations were performed using AMBER20 package and ff14SB force field. Protein interaction analysis indicates that H-bonds, van der Waals forces, and the salt bridge formed of K224 with ID116 are the main driving forces for mutual molecular recognition of PME and PMEI. According to the analyses of free energy landscape (FEL), conformational cluster, and motion, the association with PMEI greatly disrupts PME's dispersed functional motion mode and biological function. By monitoring the changes of residue contact number and binding free energy, IG35M/ IG35R: IT93F and IT113W/ IT113W: ID116W mutations contribute to thermal stability and affinity maturation of the PME-PMEI complex system, respectively. This work reveals the interaction between PME and PMEI at the gene and protein levels and provides options for modifying specific PMEI.

Assessing the performance of docking, FEP, and MM/GBSA methods on a series of KLK6 inhibitors.

Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔGbind) for a series of 49 inhibitors of KLK6. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores obtained with rDock were in good agreement (R2 ≥ 0.5) with experimental values of ΔGbind. A similar result was obtained with MM/GBSA (using the ff14SB force field) calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68kcal/mol, respectively. Furthermore, in a simulation of a real-world drug discovery project, FEP was able to rank the most potent compounds at the top of the list. These results indicate that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.

Multi-dimensional structural footprint identification for the design of potential scaffolds targeting METTL3 in cancer treatment from natural compounds

[Formula: see text]-adenosine-methyltransferase (METTL3) is the catalytic domain of the 'writer' proteins which is involved in the post modifications of [Formula: see text]-methyladinosine ([Formula: see text]). Though its activities are essential in many biological processes, it has been implicated in several types of cancer. Thus, drug developers and researchers are relentlessly in search of small molecule inhibitors that can ameliorate the oncogenic activities of METTL3. Currently, STM2457 is a potent, highly selective inhibitor of METTL3 but is yet to be approved. In this study, we employed structure-based virtual screening through consensus docking by using AutoDock Vina in PyRx interface and Glide virtual screening workflow of Schrodinger Glide. Thermodynamics via MM-PBSA calculations was further used to rank the compounds based on their total free binding energies. All atom molecular dynamics simulations were performed using AMBER 18 package. FF14SB force fields and Antechamber were used to parameterize the protein and compounds respectively. Post analysis of generated trajectories was analyzed with CPPTRAJ and PTRAJ modules incorporated in the AMBER package while Discovery studio and UCSF Chimera were used for visualization, and origin data tool used to plot all graphs. Three compounds with total free binding energies higher than STM2457 were selected for extended molecular dynamics simulations. The compounds, SANCDB0370, SANCDB0867, and SANCDB1033, exhibited stability and deeper penetration into the hydrophobic core of the protein. They engaged in relatively stronger intermolecular interactions involving hydrogen bonds with resultant increase in stability, reduced flexibility, and decrease in the surface area of the protein available for solvent interactions suggesting an induced folding of the catalytic domain. Furthermore, in silico pharmacokinetics and physicochemical analysis of the compounds revealed good properties suggesting these compounds could serve as promising MEETL3 entry inhibitors upon modifications and optimizations as presented by natural compounds. Further biochemical testing and experimentations would aid in the discovery of effective inhibitors against the berserk activities of METTL3.

Molecular dynamics simulations of an α-synuclein NAC domain fragment with a ff14IDPSFF IDP-specific force field suggest β-sheet intermediate states of fibrillation.

For the discovery of treatments against synucleinopathies, it is necessary to unravel and fully understand the mechanism of fibrillation of proteins involved. Among them, α-synuclein (αS) plays a key role in the development of these diseases through its aggregation into oligomers found in Lewy bodies. However, its structural disorder as an intrinsically disordered protein (IDP) makes its characterization by experimental techniques arduously difficult. Atomistic simulations aim to provide insights into this blank canvas and, fortunately, some studies have already suggested promising mechanisms. Still, it is urgent to consider the IDP features in simulations, so recently a lot of force fields designed to deal with IDPs have been developed. In this study, we have carried out a total of 12 μs simulations of an αS core fragment using a popular ff14SB AMBER force field and the ff14IDPSFF variation that includes a grid-based energy correction map (CMAP) method. The predicted chemical shifts from the simulations and those measured from the αS protein in the NMR solution indicate that ff14IDPSFF reproduces the experimental data more accurately. Moreover, structural analysis exhibits opposite trends between secondary structure propensities. The ff14SB force field preserves the α-helices found in the micelle-bound αS structure, which is used as an initial conformation, while ff14IDPSFF stands out with increased structural disorder and the formation of β-sheets, which suggests that the IDP-specific force field can capture more suitable conformations representing the possible intermediate states of the fibrillation process.

Modeling a unit cell: crystallographic refinement procedure using the biomolecular MD simulation platform Amber.

A procedure has been developed for the refinement of crystallographic protein structures based on the biomolecular simulation program Amber. The procedure constructs a model representing a crystal unit cell, which generally contains multiple protein molecules and is fully hydrated with TIP3P water. Periodic boundary conditions are applied to the cell in order to emulate the crystal lattice. The refinement is conducted in the form of a specially designed short molecular-dynamics run controlled by the Amber ff14SB force field and the maximum-likelihood potential that encodes the structure-factor-based restraints. The new Amber-based refinement procedure has been tested on a set of 84 protein structures. In most cases, the new procedure led to appreciably lower R free values compared with those reported in the original PDB depositions or obtained by means of the industry-standard phenix.refine program. In particular, the new method has the edge in refining low-accuracy scrambled models. It has also been successful in refining a number of molecular-replacement models, including one with an r.m.s.d. of 2.15 Å. In addition, Amber-refined structures consistently show superior MolProbity scores. The new approach offers a highly realistic representation of protein-protein interactions in the crystal, as well as of protein-water interactions. It also offers a realistic representation of protein crystal dynamics (akin to ensemble-refinement schemes). Importantly, the method fully utilizes the information from the available diffraction data, while relying on state-of-the-art molecular-dynamics modeling to assist with those elements of the structure that do not diffract well (for example mobile loops or side chains). Finally, it should be noted that the protocol employs no tunable parameters, and the calculations can be conducted in a matter of several hours on desktop computers equipped with graphical processing units or using a designated web service.

Introducing the effective polarizable bond (EPB) model in DNA simulations

Electrostatic polarization plays an important role in characterizing non-bonded interactions of molecule dynamics (MD) simulation of biomolecules. In this work, we extended a simple fluctuating-charge model, the effective polarizable bond (EPB) model to DNA simulations. Following the previously proposed EPB method, we re-parametrized the EPB model for DNA systems with the consideration of a realistic local electric-field environment and derived a set of DNA-specific EPB parameters. Two typical B-DNA systems, a pure DNA 1BNA and a ligand-DNA 8BNA systems were simulated respectively in the ff14SB and ff14SBEPB force fields. Results demonstrate that use of the EPB model in the DNA simulations can cause shrinking of DNA double strands along central axis and strengthen base-pair/ligand-DNA hydrogen-bond (HB) interactions. Furthermore, it stabilizes residue-level fluctuations for the 1BNA. However, it is largely different for these two DNA systems to mimic conformation changes of the minor/major grooves by the EPB model. Lastly, it is tested that approximately %9∼%9.9 CPU costs are additionally taken to execute the EPB calculations compared with the conventional ff14SB force field.

Modeling structural interconversion in Alzheimers’ amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer’s disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide’s dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42α-helix or Aβ42β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42α-helix simulations. The conformations obtained from Aβ42β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism–function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma

Proteins maintain hydration at high [KCl] concentration regardless of content in acidic amino acids

Proteins of halophilic organisms, which accumulate molar concentrations of KCl in their cytoplasm, have a much higher content in acidic amino acids than proteins of mesophilic organisms. It has been proposed that this excess is necessary to maintain proteins hydrated in an environment with low water activity, either via direct interactions between water and the carboxylate groups of acidic amino acids or via cooperative interactions between acidic amino acids and hydrated cations. Our simulation study of five halophilic proteins and five mesophilic counterparts does not support either possibility. The simulations use the AMBER ff14SB force field with newly optimized Lennard-Jones parameters for the interactions between carboxylate groups and potassium ions. We find that proteins with a larger fraction of acidic amino acids indeed have higher hydration levels, as measured by the concentration of water in their hydration shell and the number of water/protein hydrogen bonds. However, the hydration level of each protein is identical at low (bKCl = 0.15 mol/kg) and high (bKCl = 2 mol/kg) KCl concentrations; excess acidic amino acids are clearly not necessary to maintain proteins hydrated at high salt concentration. It has also been proposed that cooperative interactions between acidic amino acids in halophilic proteins and hydrated cations stabilize the folded protein structure and would lead to slower dynamics of the solvation shell. We find that the translational dynamics of the solvation shell is barely distinguishable between halophilic and mesophilic proteins; if such a cooperative effect exists, it does not have that entropic signature.

Abstract P-19: 15-Microsecond Molecular Dynamics Simulations of Nucleosome Show Structural Heterogeneity and Plasticity

Background: Nucleosomes are basic units of chromatin organization, resembling spools with ~150 base pairs of DNA wrapped around the octamer of histone proteins. They play a crucial role in chromatin compactization and gene expression. Currently, there are more than 340 structures of nucleosomes and their complexes with proteins in the protein data bank, 159 of them are made with cryoEM, 60 of those in 2020 and later. It is clear that cryoEM will soon yield even more structures of nucleosomes with different histone variants, mutations, DNA sequences, and interacting proteins. Despite the variety, the majority of the aforementioned structures look very similar. This is due to the fact that most of the models are built on the basis of very similar crystal structures. However, the dynamics of nucleosomes are crucial for understanding the mechanisms that govern the chromatin functions. Computational methods can supplement experimental approaches and recreate the dynamic conformational landscape of nucleosomes from initial static structures. We present an all-atom molecular dynamics simulation of nucleosome core particles at a record timescale of 15 microseconds. Methods: All-atom MD simulations were performed using GROMACS 2018 with AMBER ff14SB force field with parmbsc1 DNA and CUFIX ion parameters. Crystal structures with PDB IDs 1KX5 and 3LZ0 were used. Analysis was performed with custom-developed python scripts based on MDAnalysis and 3DNA. Models of chromatin fibers were built by connecting random snapshots from MD trajectories with straight linker segments of B-DNA of different lengths. Results: We observed the inner dynamics of histone octamer, which covers the conformational space of the most deformed structures reported by cryoEM. We showed that histone dynamics play important role in DNA mobility, allowing for twist-defects propagation. Conclusion: We observed unprecedented unwrapping of nucleosomal DNA with truncated histone tails. Through multi-scale modeling, we showed that such unwrapping alone is crucial for nucleosomal fibers geometry and elastic properties.

Abstract 16069: Molecular Dynamics Simulations Reveal the Functional Impact of Pathogenic Variants in the LDL Receptor LA 4-6 Repeats

Introduction: Functional annotation of rare variants is key to the implementation of genomic medicine. We used molecular dynamics (MD) simulations to assess functional consequences of putative pathogenic variants (PVs) in the low-density lipoprotein receptor gene ( LDLR ). LDLR has a multidomain structure with seven LA repeats and local interactions between these repeats influence ligand binding. However, binding and recycling of the receptor-ligand complex require global changes in conformation. Using MD, we investigated the effects of PVs on long-range dynamics and LDL binding. Methods: An LA 4-6 repeat structure was created from a crystal structure of the extracellular domain (PDB: 1N7D). Structures were solvated with a water box containing TIP3P water molecules and simulated using the AMBER software package with the ff14SB forcefield. The wild type (WT) structure was first relaxed using MD; and subsequently PVs D245Y, F181Y and F181G were modeled. Dynamics were simulated for approximately one microsecond. Values for LDL binding for each PV were obtained from a prior study which used a radioisotope uptake assay. Results: WT domains demonstrated a stable conformation based on root mean square deviation. PVs disrupted the normal distribution in all domains significantly (p < 0.0001), broadening it and introducing multiple peaks. Projection along the top principal components (PCs) showed global destabilization with all PVs. The variant with the greatest impact on LDL binding, F181G, adopted a distinct alternate conformation. Comparison between PV and WT subspaces from PCA correlated with LDL binding (R 2 = 0.99, exponential regression). Structural analysis revealed that the LA5 calcium cage is involved in inter-domain salt bridges, which are disrupted in simulations of PVs. Conclusion: MD simulation of LA4-6 repeats in LDLR suggests PVs alter long-range conformational dynamics, and that such dynamics correlate with LDL binding. The impact of PVs on conformational dynamics and binding may be through disruption of interdomain salt bridges that are mediated by the acidic calcium cage. This study demonstrates the potential utility of MD simulations to functionally characterize LDLR variants.

Pair Potentials as Machine Learning Features.

Atom pairwise potential functions make up an essential part of many scoring functions for protein decoy detection. With the development of machine learning (ML) tools, there are multiple ways to combine potential functions to create novel ML models and methods. Potential function parameters can be easily extracted; however, it is usually hard to directly obtain the calculated atom pairwise energies from scoring functions. Amber, as one of the most popular suites of modeling programs, has an extensive history and library of force field potential functions. In this work, we directly used the force field parameters in ff94 and ff14SB from Amber and encoded them to calculate atom pairwise energies for different interactions. Two sets of structures (single amino acid set and a dipeptide set) were used to evaluate the performance of our encoded Amber potentials. From the comparison results between energy terms obtained from our encoding and Amber, we find energy difference within ±0.06 kcal/mol for all tested structures. Previously we have shown that the Random Forest (RF) model can help to emphasize more important atom pairwise interactions and ignore insignificant ones [Pei, J.; Zheng, Z.; Merz, K. M. J. Chem. Inf. Model. 2019, 59, 1919-1929]. Here, as an example of combining ML methods with traditional potential functions, we followed the same work flow to combine the RF models with force field potential functions from Amber. To determine the performance of our RF models with force field potential functions, 224 different protein native-decoy systems were used as our training and testing sets We find that the RF models with ff94 and ff14SB force field parameters outperformed all other scoring functions (RF models with KECSA2, RWplus, DFIRE, dDFIRE, and GOAP) considered in this work for native structure detection, and they performed similarly in detecting the best decoy. Through inclusion of best decoy to decoy comparisons in building our RF models, we were able to generate models that outperformed the score functions tested herein both on accuracy and best decoy detection, again showing the performance and flexibility of our RF models to tackle this problem. Finally, the importance of the RF algorithm and force field parameters were also tested and the comparison results suggest that both the RF algorithm and force field potentials are important with the ML scoring function achieving its best performance only by combining them together. All code and data used in this work are available at https://github.com/JunPei000/FFENCODER_for_Protein_Folding_Pose_Selection.

Exploiting a Mechanical Perturbation of a Titin Domain to Identify How Force Field Parameterization Affects Protein Refolding Pathways.

Molecular mechanics force fields have been shown to differ in their predictions of biomolecular processes such as protein folding. To test how force field differences affect predicted polypeptide behavior, we created a mechanically perturbed model of the β-stranded I91 titin domain based on atomic force spectroscopy data and examined its refolding behavior using six different force fields. We found that different force fields varied significantly in their ability to refold the mechanically perturbed I91 domain. Examination of the perturbed I91 unfolded state revealed that all five Amber force fields oversample a specific region of the Ramachandran plot, thereby creating unfolded state intermediates which are not predicted by the Charmm 22* force field. Simulations of perturbed I91 refolding with Amber FB15 revealed that Amber FB15 destabilizes stable portions of I91, thereby contradicting experimental stability analyses. Finally, inspection of the perturbed I91 unfolded state along with equilibration simulations of the Ac-(AAQAA)3-NH2 peptide suggest that high dihedral torsional barriers cause the Amber ff14SB force field to predict higher helical lifetimes relative to other force fields. These results suggest that using mechanically perturbed models can provide a controlled method to gain insights into how force fields affect polypeptide behavior.

Development of a theoretical model for the inhibition of nsP3 protease of Chikungunya virus using pyranooxazoles

Chikungunya virus (CHIKV) causes Chikungunya fever (CHIKF) and till date no effective medicine for its cure is available in market. Different research groups find various possible interactions between small molecules and non-structural proteins, viz. nsP3, one of the most important viral elements in CHIKV. In this work, authors have studied the interactions of nsP3 protease of CHIKV with pyranooxazoles. Initially, a one-pot three-component reaction was designed using oxazolidine-2,4-dione, benzaldehyde and cyanoethylacetate to get a proposed biological active molecule, i.e. based on pyranooxazoles. The mechanism for the synthesis of the product based on pyranooxazole was studied through density functional theory (DFT) using Gaussian. Then, a library of the obtained pyranooxazole was created through computational tools by varying the substituents. Further, virtual screening of the designed library of pyranooxazoles (200 compounds) against nsP3 protease of CHIKV was performed. Herein, CMPD 104 showed strongest binding affinity toward the targeted nsP3 protease of CHIKV, based on the least binding energy obtained from docking. Based on docking results, the pharmacological, toxicity, biological score and Lipinski’s filters were studied. Further, DFT studies of top five compounds were done using Gaussian. Molecular dynamics (MD) simulation of nsP3 protease of CHIKV with and without 104 was performed using AMBER18 utilizing ff14SB force field in three steps (minimization, equilibration and production). This work is emphasized to designing of one-pot three-component synthesis and to develop a theoretical model to inhibit the nsP3 protease of CHIKV.AbbreviationsCHIKFChikungunya feverCHIKVChikungunya virusDFTdensity functional theoryDSDiscovery StudioMDmolecular dynamicsMM-GBSAmolecular mechanics-generalized born surface areaMMVMolegro molecular viewerCommunicated by Ramaswamy H. Sarma

A Hierarchical Approach to Predict Conformation-Dependent Histidine Protonation States in Stable and Flexible Proteins.

Solution acidity measured by pH is an important environmental factor that affects protein structure. It influences the protonation state of protein residues, which in turn may be coupled to protein conformational changes, unfolding, and ligand binding. It remains difficult to compute and measure the p Ka of individual residues, as well as to relate them to pH-dependent protein transitions. This paper presents a hierarchical approach to compute the p Ka of individual protonatable residues, specifically histidines, coupled with underlying structural changes of a protein. A fast and efficient free energy perturbation (FEP) algorithm has also been developed utilizing a fast implementation of standard molecular dynamics (MD) algorithms. Specifically, a CUDA version of the AMBER MD engine is used in this paper. Eight histidine p Ka's are computed in a diverse set of pH stable proteins to demonstrate the proposed approach's utility and assess the predictive quality of the AMBER FF99SB force field. A reference molecule is carefully selected and tested for convergence. A hierarchical approach is used to model p Ka's of the six histidine residues of the diphtheria toxin translocation domain (DTT), which exhibits a diverse ensemble of individual conformations and pH-dependent unfolding. The hierarchical approach consists of first sampling equilibrium conformational ensembles of a protein with protonated and neutral histidine residues via long equilibrium MD simulations (Flores-Canales, J. C.; et al. bioRxiv, 2019, 572040). A clustering method is then used to identify sampled protein conformations, and p Ka's of histidines in each protein conformation are computed. Finally, an ensemble averaging formalism is developed to compute weighted average histidine p Ka's. These can be compared with an apparent experimentally measured p Ka of the DTT protein and thus allows us to propose a mechanism of pH-dependent unfolding of the DTT protein.

The Role of the Active Site Flap in Streptavidin/Biotin Complex Formation.

Obtaining a detailed description of how active site flap motion affects substrate or ligand binding will advance structure-based drug design (SBDD) efforts on systems including the kinases, HSP90, HIV protease, ureases, etc. Through this understanding, we will be able to design better inhibitors and better proteins that have desired functions. Herein we address this issue by generating the relevant configurational states of a protein flap on the molecular energy landscape using an approach we call MTFlex-b and then following this with a procedure to estimate the free energy associated with the motion of the flap region. To illustrate our overall workflow, we explored the free energy changes in the streptavidin/biotin system upon introducing conformational flexibility in loop3-4 in the biotin unbound ( apo) and bound ( holo) state. The free energy surfaces were created using the Movable Type free energy method, and for further validation, we compared them to potential of mean force (PMF) generated free energy surfaces using MD simulations employing the FF99SBILDN and FF14SB force fields. We also estimated the free energy thermodynamic cycle using an ensemble of closed-like and open-like end states for the ligand unbound and bound states and estimated the binding free energy to be approximately -16.2 kcal/mol (experimental -18.3 kcal/mol). The good agreement between MTFlex-b in combination with the MT method with experiment and MD simulations supports the effectiveness of our strategy in obtaining unique insights into the motions in proteins that can then be used in a range of biological and biomedical applications.