On the application of Good-Turing statistics to quantify convergence of biomolecular simulations

Understanding a point mutation signature D54K in the caspase activation recruitment domain of NOD1 capitulating concerted immunity via atomistic simulation

Point mutation D54K in the human N-terminal caspase recruitment domain (CARD) of nucleotide-binding oligomerization domain -1 (NOD1) abrogates an imperative downstream interaction with receptor-interacting protein kinase (RIPK2) that entails combating bacterial infections and inflammatory dysfunction. Here, we addressed the molecular details concerning conformational changes and interaction patterns (monomeric-dimeric states) of D54K by signature-based molecular dynamics simulation. Initially, the sequence analysis prioritized D54K as a pathogenic mutation, among other variants, based on a sequence signature. Since the mutation is highly conserved, we derived the distant ortholog to predict the sequence and structural similarity between native and mutant. This analysis showed the utility of 33 communal core residues associated with structural-functional preservation and variations, concurrently served to infer the cryptic hotspots Cys39, Glu53, Asp54, Glu56, Ile57, Leu74, and Lys78 determining the inter helical fold forming homodimers for putative receptor interaction. Subsequently, the atomistic simulations with free energy (MM/PB(GB)SA) calculations predicted structural alteration that takes place in the N-terminal mutant CARD where coils changed to helices (45 α3- L4-α4-L6- α683) in contrast to native (45T2-L4-α4-L6-T483). Likewise, the C-terminal helices 93T1-α7105 connected to the loops distorted compared to native 93α6-L7105 may result in conformational misfolding that promotes functional regulation and activation. These structural perturbations of D54K possibly destabilize the flexible adaptation of critical homotypic NOD1CARD-CARDRIPK2 interactions (α4Asp42-Arg488α5 and α6Phe86-Lys471α4) is consistent with earlier experimental reports. Altogether, our findings unveil the conformational plasticity of mutation-dependent immunomodulatory response and may aid in functional validation exploring clinical investigation on CARD-regulated immunotherapies to prevent systemic infection and inflammation.Communicated by Ramaswamy H. Sarma.

A proof-of-concept study of the secondary structure of influenza A, B M2 and MERS- and SARS-CoV E transmembrane peptides using folding molecular dynamics simulations in a membrane mimetic solvent

Here, we have carried out a proof-of-concept molecular dynamics (MD) simulation with adaptive tempering in a membrane mimetic environment to study the folding of single-pass membrane peptides. We tested the influenza A M2 viroporin, influenza B M2 viroporin, and protein E from coronaviruses MERS-Cov-2 and SARS-CoV-2 peptides with known experimental secondary structures in membrane bilayers. The two influenza-derived peptides are significantly different in the peptide sequence and secondary structure and more polar than the two coronavirus-derived peptides. Through a total of more than 50 μs of simulation time that could be accomplished in trifluoroethanol (TFE), as a membrane model, we characterized comparatively the folding behavior, helical stability, and helical propensity of these transmembrane peptides that match perfectly their experimental secondary structures, and we identified common motifs that reflect their quaternary organization and known (or not) biochemical function. We showed that BM2 is organized into two structurally distinct parts: a significantly more stable N-terminal half, and a fast-converting C-terminal half that continuously folds and unfolds between α-helical structures and non-canonical structures, which are mostly turns. In AM2, both the N-terminal half and C-terminal half are very flexible. In contrast, the two coronavirus-derived transmembrane peptides are much more stable and fast helix-formers when compared with the influenza ones. In particular, the SARS-derived peptide E appears to be the fastest and most stable helix-former of all the four viral peptides studied, with a helical structure that persists almost without disruption for the whole of its 10 μs simulation. By comparing the results with experimental observations, we benchmarked TFE in studying the conformation of membrane and hydrophobic peptides. This work provided accurate results suggesting a methodology to run long MD simulations and predict structural properties of biologically important membrane peptides.

Folding molecular dynamics simulation of T-peptide, a HIV viral entry inhibitor: Structure, dynamics, and comparison with the experimental data

Peptide T is a synthetic octapeptide fragment, which corresponds to the region 185-192 of the gp120 HIV coat protein and functions as a viral entry inhibitor. In this work, a folding molecular dynamics simulation of peptide T in a membrane-mimicking (DMSO) solution was performed with the aim of characterizing the peptide's structural and dynamical properties. We show that peptide T is highly flexible and dynamic. The main structural characteristics observed were rapidly interconverting short helical stretches and turns, with a notable preference for the formation of β-turns. The simulation also indicated that the C-terminal part appears to be more stable than the rest of the peptide, with the most preferred conformation for residues 5-8 being a β-turn. In order to validate the accuracy of the simulations, we compared our results with the experimental NMR data obtained for the T-peptide in the same solvent. In agreement with the simulation, the NMR data indicated the presence of a preferred structure in solution that was consistent with a β-turn comprising the four C-terminal residues. An additional comparison between the experimental and simulation-derived chemical shifts also showed a reasonable agreement between experiment and simulation, further validating the simulation-derived structural characterization of the T-peptide. We conclude that peptide folding simulations produce physically relevant results even when performed with organic solvents that were not part of the force field parameterization procedure.

A molecular dynamics simulation study on the propensity of Asn-Gly-containing heptapeptides towards β-turn structures: Comparison with ab initio quantum mechanical calculations

Both molecular mechanical and quantum mechanical calculations play an important role in describing the behavior and structure of molecules. In this work, we compare for the same peptide systems the results obtained from folding molecular dynamics simulations with previously reported results from quantum mechanical calculations. More specifically, three molecular dynamics simulations of 5 μs each in explicit water solvent were carried out for three Asn-Gly-containing heptapeptides, in order to study their folding and dynamics. Previous data, based on quantum mechanical calculations within the DFT framework have shown that these peptides adopt β-turn structures in aqueous solution, with type I’ β-turn being the most preferred motif. The results from our analyses indicate that at least for the given systems, force field and simulation protocol, the two methods diverge in their predictions. The possibility of a force field-dependent deficiency is examined as a possible source of the observed discrepancy.

Feature vector clustering molecular pairs in computer simulations

A clustering framework is introduced to analyze the microscopic structural organization of molecular pairs in liquids and solutions. A molecular pair is represented by a representative vector (RV). To obtain RV, intermolecular atom distances in the pair are extracted from simulation trajectory as components of the key feature vector (KFV). A specific scheme is then suggested to transform KFV to RV by removing the influence of permutational molecular symmetry on the KFV as the predicted clusters should be independent of possible permutations of identical atoms in the pair. After RVs of pairs are obtained, a clustering analysis technique is finally used to classify all the RVs of molecular pairs into the clusters. The framework is applied to analyze trajectory from molecular dynamics simulations of an ionic liquid (trihexyltetradecylphosphonium bis(oxalato)borate ([P_6,6,6,14 ][BOB])). The molecular pairs are successfully categorized into physically meaningful clusters, and their effectiveness is evaluated by computing the product moment correlation coefficient (PMCC). (Willett, Winterman, and Bawden, J. Chem. Inf. Comput. Sci. 1986, 26, 109-118; Downs, Willett, and Fisanick, J. Chem. Inf. Comput. Sci. 1994, 34, 1094-1102) It is observed that representative configurations of two clusters are related to two energy local minimum structures optimized by density functional theory (DFT) calculation, respectively. Several widely used clustering analysis techniques of both nonhierarchical (k-means) and hierarchical clustering algorithms are also evaluated and compared with each other. The proposed KFV technique efficiently reveals local molecular pair structures in the simulated complex liquid. It is a method, which is highly useful for liquids and solutions in particular with strong intermolecular interactions. © 2019 Wiley Periodicals, Inc.

How To Design Selective Ligands for Highly Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System

A model system of two related enzymes with conserved binding sites, namely N-myristoyltransferase from two different organisms, was studied to decipher the driving forces that lead to selective inhibition in such cases. Using a combination of computational and experimental tools, two different selectivity-determining features were identified. For some ligands, a change in side-chain flexibility appears to be responsible for selective inhibition. Remarkably, this was observed for residues orienting their side chains away from the ligands. For other ligands, selectivity is caused by interfering with a water molecule that binds more strongly to the off-target than to the target. On the basis of this finding, a virtual screen for selective compounds was conducted, resulting in three hit compounds with the desired selectivity profile. This study delivers a guideline on how to assess selectivity-determining features in proteins with conserved binding sites and to translate this knowledge into the design of selective inhibitors.

Tripleurin XIIc: Peptide Folding Dynamics in Aqueous and Hydrophobic Environment Mimic Using Accelerated Molecular Dynamics

Peptaibols are a special class of fungal peptides with an acetylated N-terminus and a C-terminal 1,2-amino alcohol along with non-standard amino acid residues. New peptaibols named tripleurins were recently identified from a strain of the filamentous fungal species Trichoderma pleuroti, which is known to cause green mould disease on cultivated oyster mushrooms. To understand the mode of action of these peptaibols, the three-dimensional structure of tripleurin (TPN) XIIc, an 18-mer peptide, was elucidated using an enhanced sampling method, accelerated MD, in water and chloroform solvents. Non-standard residues were parameterized by the Restrained Electrostatic Potential (RESP) charge fitting method. The dihedral distribution indicated towards a right-handed helical formation for TPN XIIc in both solvents. Dihedral angle based principal component analysis revealed a propensity for a slightly bent, helical folded conformation in water solvent, while two distinct conformations were revealed in chloroform: One that folds into highly bent helical structure that resembles a beta-hairpin and another with an almost straight peptide backbone appearing as a rare energy barrier crossing event. The hinge-like movement of the terminals was also observed and is speculated to be functionally relevant. The convergence and efficient sampling is addressed using Cartesian PCA and Kullback-Leibler divergence methods.

Folding Molecular Dynamics Simulation of a gp41-Derived Peptide Reconcile Divergent Structure Determinations

T-20 peptide is the first FDA-approved fusion inhibitor against AIDS/HIV-1 gp41 protein. Part of it, the gp41[659-671] peptide, that contains the complete epitope for the neutralizing 2F5 monoclonal antibody, has been found experimentally in a number of divergent structures. Herein, we attempt to reconcile them by using unbiased large-scale all-atom molecular dynamics folding simulations. We show that our approach can successfully capture the peptide's heterogeneity and reach each and every experimentally determined conformation in sub-angstrom accuracy, whilst preserving the peptide's disordered nature. Our analysis also unveils that the minor refinements within the AMBER99SB family of force fields can lead to appreciable differences in the predicted conformational stability arising from subtle differences in the helical- and β-region of the Ramachandran plot. Our work underlines the contribution of molecular dynamics simulation in structurally characterizing pharmacologically important peptides of ambiguous structure.

Identification of new inhibitors against human Great wall kinase using in silico approaches

Microtubule associated serine/threonine kinase (MASTL) is an important Ser/Thr kinase belonging to the family of AGC kinases. It is the human orthologue of Greatwall kinase (Gwl) that plays a significant role in mitotic progression and cell cycle regulation. Upregulation of MASTL in various cancers and its association with poor patient survival establishes it as an important drug target in cancer therapy. Nevertheless, the target remains unexplored with the paucity of studies focused on identification of inhibitors against MASTL, which emphasizes the relevance of our present study. We explored various drug databases and performed virtual screening of compounds from both natural and synthetic sources. A list of promising compounds displaying high binding characteristics towards MASTL protein is reported. Among the natural compounds, we found a 6-hydroxynaphthalene derivative ZINC85597499 to display best binding energy value of −9.32 kcal/mol. While among synthetic compounds, a thieno-pyrimidinone based tricyclic derivative ZINC53845290 compound exhibited best binding affinity of value −7.85 kcal/mol. MASTL interactions with these two compounds were further explored using molecular dynamics simulations. Altogether, this study identifies potential inhibitors of human Gwl kinase from both natural and synthetic origin and calls for studying these compounds as potential drugs for cancer therapy.

Dynamical footprint of cross-reactivity in a human autoimmune T-cell receptor

The present work focuses on the dynamical aspects of cross-reactivity between myelin based protein (MBP) self-peptide and two microbial peptides (UL15, PMM) for Hy.1B11 T-cell receptor (TCR). This same TCR was isolated from a patient suffering from multiple sclerosis (MS). The study aims at highlighting the chemical interactions underlying recognition mechanisms between TCR and the peptides presented by Major Histocompatibility Complex (MHC) proteins, which form a crucial component in adaptive immune response against foreign antigens. Since the ability of a TCR to recognize different peptide antigens presented by MHC depends on its cross-reactivity, we used molecular dynamics methods to obtain atomistic detail on TCR-peptide-MHC complexes. Our results show how the dynamical basis of Hy.1B11 TCR’s cross-reactivity is rooted in a similar bridging interaction pattern across the TCR-peptide-MHC interface. Our simulations confirm the importance of TCR CDR3α E98 residue interaction with MHC and a predominant role of P6 peptide residue in MHC binding affinity. Altogether, our study provides energetic and dynamical insights into factors governing peptide recognition by the cross-reactive Hy.1B11 TCR, found in MS patient.

The NS4A Cofactor Dependent Enhancement of HCV NS3 Protease Activity Correlates with a 4D Geometrical Measure of the Catalytic Triad Region

We are developing a 4D computational methodology, based on 3D structure modeling and molecular dynamics simulation, to analyze the active site of HCV NS3 proteases, in relation to their catalytic activity. In our previous work, the 4D analyses of the interactions between the catalytic triad residues (His57, Asp81, and Ser139) yielded divergent, gradual and genotype-dependent, 4D conformational instability measures, which strongly correlate with the known disparate catalytic activities among genotypes. Here, the correlation of our 4D geometrical measure is extended to intra-genotypic alterations in NS3 protease activity, due to sequence variations in the NS4A activating cofactor. The correlation between the 4D measure and the enzymatic activity is qualitatively evident, which further validates our methodology, leading to the development of an accurate quantitative metric to predict protease activity in silico. The results suggest plausible “communication” pathways for conformational propagation from the activation subunit (the NS4A cofactor binding site) to the catalytic subunit (the catalytic triad). The results also strongly suggest that the well-sampled (via convergence quantification) structural dynamics are more connected to the divergent catalytic activity observed in HCV NS3 proteases than to rigid structures. The method could also be applicable to predict patients’ responses to interferon therapy and better understand the innate interferon activation pathway.

Sensitivity of Folding Molecular Dynamics Simulations to Even Minor Force Field Changes

We examine the sensitivity of folding molecular dynamics simulations on the choice between three variants of the same force field (the AMBER99SB force field and its ILDN, NMR-ILDN, and STAR-ILDN variants). Using two different peptide systems (a marginally stable helical peptide and a β-hairpin) and a grand total of more than 20 μs of simulation time we show that even relatively minor force field changes can lead to appreciable differences in the peptide folding behavior.

Characterizing a partially ordered miniprotein through folding molecular dynamics simulations: Comparison with the experimental data

The villin headpiece helical subdomain (HP36) is one of the best known model systems for computational studies of fast-folding all-α miniproteins. HP21 is a peptide fragment-derived from HP36-comprising only the first and second helices of the full domain. Experimental studies showed that although HP21 is mostly unfolded in solution, it does maintain some persistent native-like structure as indicated by the analysis of NMR-derived chemical shifts. Here we compare the experimental data for HP21 with the results obtained from a 15-μs long folding molecular dynamics simulation performed in explicit water and with full electrostatics. We find that the simulation is in good agreement with the experiment and faithfully reproduces the major experimental findings, namely that (a) HP21 is disordered in solution with <10% of the trajectory corresponding to transiently stable structures, (b) the most highly populated conformer is a native-like structure with an RMSD from the corresponding portion of the HP36 crystal structure of <1 Å, (c) the simulation-derived chemical shifts-over the whole length of the trajectory-are in reasonable agreement with the experiment giving reduced χ(2) values of 1.6, 1.4, and 0.8 for the Δδ(13) C(α) , Δδ(13) CO, and Δδ(13) C(β) secondary shifts, respectively (becoming 0.8, 0.7, and 0.3 when only the major peptide conformer is considered), and finally, (d) the secondary structure propensity scores are in very good agreement with the experiment and clearly indicate the higher stability of the first helix. We conclude that folding molecular dynamics simulations can be a useful tool for the structural characterization of even marginally stable peptides.

Dynamical insights into the differential characteristics of Mycobacterium avium subsp. paratuberculosis peptide binding to HLA-DRB1 proteins associated with multiple sclerosis

Differential properties of MAP binding to HLA proteins in Sardinian MS patients.

Sampling Assessment for Molecular Simulations Using Conformational Entropy Calculations

The extent and significance of conformational sampling is a major factor determining the reliability of long-scale molecular simulations of large and flexible biomolecules. Although several methods have been proposed to quantify the effective sample size of molecular simulations by transforming root mean squared distances between pairs of configurations into statistical/probabilistic quantities, there is still no standard technique for measuring the size of sampling. In this work, we study conformational entropy (Sconform) as a purely informational and probabilistic measure of sampling that does not require the adoption of any clustering protocol or distance metric between configurations. In addition Sconform, which is calculated from the probability mass functions associated with discretized dihedral angles, offers other potential advantages for sampling assessment (e.g., global character, thermodynamic significance, relationship with internal degrees of freedom, etc.). The utility of Sconform in sampling assessment is illustrated by carrying out test calculations on configurations produced by two extended molecular dynamics simulations, namely, a 2.0 μs trajectory of a highly flexible 17-residue peptide and the trajectory data set of the 1.0 ms bovine pancreatic trypsin inhibitor simulation provided by the D. E. Shaw research group.