Lattice simulations of cotranslational folding of single domain proteins

We use lattice protein models and Monte Carlo simulations to study cotranslational folding of small single domain proteins. We show that the assembly of native structure begins during late extrusion stages, but final formation of native state occurs during de novo folding, when all residues are extruded. There are three main results in our study. First, for the sequences displaying two-state refolding mechanism de novo cotranslational folding pathway differs from that sampled in in vitro refolding. The change in folding pathways is due to partial assembly of native interactions during extrusion that results in different starting conditions for in vitro refolding and for de novo cotranslational folding. For small single domain proteins cotranslational folding is slower than in vitro refolding, but is generally fast enough to be completed before the release from a ribosome. Second, we found that until final stages of biosynthesis cotranslational folding is essentially equilibrium. This observation is explained by low stability of structured states for partially extruded chains. Finally, our data suggest that the proteins, which refold in vitro slowly via intermediates, complete their de novo folding after the release from a ribosome. Comparison of our lattice cotranslational simulations with recent experimental and computational studies is discussed.     

Iterative cluster-NMA: A tool for generating conformational transitions in proteins

Computational models provide insight into the structure-function relationship in proteins. These approaches, especially those based on normal mode analysis, can identify the accessible motion space around a given equilibrium structure. The large magnitude, collective motions identified by these methods are often well aligned with the general direction of the expected conformational transitions. However, these motions cannot realistically be extrapolated beyond the local neighborhood of the starting conformation. In this article, the iterative cluster-NMA (icNMA) method is presented for traversing the energy landscape from a starting conformation to a desired goal conformation. This is accomplished by allowing the evolving geometry of the intermediate structures to define the local accessible motion space, and thus produce an appropriate displacement. Following the derivation of the icNMA method, a set of sample simulations are performed to probe the robustness of the model. A detailed analysis of beta1,4-galactosyltransferase-T1 is also given, to highlight many of the capabilities of icNMA. Remarkably, during the transition, a helix is seen to be extended by an additional turn, emphasizing a new unknown role for secondary structures to absorb slack during transitions. The transition pathway for adenylate kinase, which has been frequently studied in the literature, is also discussed.     

Simulating electrostatic effects on electronic transitions in proteins

Biopolymer fluorescence in biology and biochemistry is increasingly used for characterising equilibrium, dynamics and imaging. This is typically done by monitoring wavelength and intensity changes without necessarily knowing what causes such changes in detail. Simulations have been at the core of the considerable recent progress in improving the microscopic understanding of wavelength and quenching of fluorescence intensity in biopolymers. This review focuses on one of the most used intrinsic probes for protein behaviour, tryptophan (Trp), which is arguably now one of the best understood probes of internal structure and dynamics for proteins – despite its reputation to the contrary. In this review, we highlight selected classical molecular dynamics in combination with quantum mechanics simulations from our group and others during the past 20 years that support this view. The work includes simulations of time-dependent wavelength shifts in solvents and proteins, fluorescence-quenching rates, dielectric compensation by water, heterogeneity of quenching rates and applications to protein folding.     

Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: hierarchy of structural loss from all-atom Monte Carlo simulations of p27Kip1 unfolding-unbinding and structural determinants of the binding mechanism

Conformational transitions coupled to binding are studied for the p27(Kip1) protein which undergoes a functional disorder-to-order folding transition during tertiary complex formation with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) binary complex. Temperature-induced Monte Carlo simulations of p27(Kip1) unfolding-unbinding carried out from the crystal structure of the tertiary complex have revealed a systematic trend in the hierarchy of structural loss for p27(Kip1) and a considerable difference in mobility of p27(Kip1) secondary structure elements. The most persistent interactions of p27(Kip1) at the intermolecular interface during unfolding-unbinding simulations are formed by beta-hairpin and beta-strand that on average maintain their structural integrity considerably longer than other p27(Kip1) elements. We have found that the ensemble of unfolded p27(Kip1) conformations is characterized by transitions between mostly unbound, collapsed conformations and entropically favorable p27(Kip1) conformations, which are weakly bound to the cyclin A side of the binary complex. The results of this study are consistent with the experimental evidence pointing to this region of the intermolecular interface as a potential initiation docking site during binding reaction and may reconcile conflicting experimental hypotheses on the recognition of substrate recruitment motifs.     

Characterization and prediction of linker sequences of multi-domain proteins by a neural network

In this paper, we describe a neural network analysis of sequences connecting two protein domains (domain linkers). The neural network was trained to distinguish between domain linker sequences and non-linker sequences, using a SCOP-defined domain library. The analysis indicated that a significant difference existed between domain linkers and non-linker regions, including intra-domain loop regions. Moreover, the resulting Hinton diagram showed a position-dependent amino acid preference of the domain linker sequences, and implied their non-random nature. We then applied the neural network to predict domain linkers in multi-domain protein sequences. As the result of a Jack-knife test, 58% of the predicted regions matched actual linker regions (specificity), and 36% of the SCOP-derived domain linkers were predicted (sensitivity). This prediction efficiency is superior to simpler methods derived from secondary structure prediction that assume that long loop regions are putative domain linkers. Altogether, these results suggest that domain linkers possess local characteristics different from those of loop regions.     

Frustration‐guided motion planning reveals conformational transitions in proteins

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics‐inspired motion planning procedure called dCC‐RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non‐native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC‐RRT to examine how collective, small‐scale motions of four side‐chains in the active site of cyclophilin A propagate through the protein. dCC‐RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non‐canonical capsid binding site 25 Å away, rationalizing NMR and multi‐temperature crystallography experiments. In all, dCC‐RRT can reveal detailed, all‐atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/ .     

Molecular dynamics simulations on the conformational transitions from the GA98 (GA88) to GB98 (GB88) proteins

We performed conventional and targeted molecular dynamics simulations to address the dynamic transition mechanisms of the conformational transitions from the G_A98 protein with only 1 mutation of Leu45Tyr to G_B98 and from the G_A88 protein with 7 mutations of Gly24Ala, Ile25Thr, Ile30Phe, Ile33Tyr, Leu45Tyr, Ile49Thr, and Leu50Lys to G_B88. The results show that the conformational transition mechanism from the mutated 3α G_A98 (G_A88) state to the α+4β G_B98 (G_B88) state via several intermediate conformations involves the bending of loops at the N and C termini firstly, the unfolding of αA and αC, then the traversing of αB, and the formation of the 4β layer with the conversion of the hydrophobic core. The bending of loops at the N and C termini and the formation of the crucial transition conformation with the full unfolded structure are key factors in their transition processes. The communication of the interaction network, the bending directions of loops, and the traversing site of αB in the transition of G_A98 to G_B98 are markedly different from those in G_A88 to G_B88 because of the different mutated residues. The analysis of the correlations and the calculated mass center distances between some segments further supported their conformational transition mechanisms. These results could help people to better understand the Paracelsus challenge. Copyright © 2016 John Wiley & Sons, Ltd.     

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins

Structural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered‐disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins become more ordered after ligand binding, while 40% more disordered. As protein conformational diversity is inherently connected with protein function our analysis suggests differences in structure‐function relationships related to order‐disorder transitions.     

Coarse-grained molecular dynamics simulations of membrane proteins and peptides

Molecular dynamics (MD) simulations provide a valuable approach to the dynamics, structure, and stability of membrane-protein systems. Coarse-grained (CG) models, in which small groups of atoms are treated as single particles, enable extended (>100 ns) timescales to be addressed. In this study, we explore how CG-MD methods that have been developed for detergents and lipids may be extended to membrane proteins. In particular, CG-MD simulations of a number of membrane peptides and proteins are used to characterize their interactions with lipid bilayers. CG-MD is used to simulate the insertion of synthetic model membrane peptides (WALPs and LS3) into a lipid (PC) bilayer. WALP peptides insert in a transmembrane orientation, whilst the LS3 peptide adopts an interfacial location, both in agreement with experimental biophysical data. This approach is extended to a transmembrane fragment of the Vpu protein from HIV-1, and to the coat protein from fd phage. Again, simulated protein/membrane interactions are in good agreement with solid state NMR data for these proteins. CG-MD has also been applied to an M3-M4 fragment from the CFTR protein. Simulations of CFTR M3-M4 in a detergent micelle reveal formation of an alpha-helical hairpin, consistent with a variety of biophysical data. In an I231D mutant, the M3-M4 hairpin is additionally stabilized via an inter-helix Q207/D231 interaction. Finally, CG-MD simulations are extended to a more complex membrane protein, the bacterial sugar transporter LacY. Comparison of a 200 ns CG-MD simulation of LacY in a DPPC bilayer with a 50 ns atomistic simulation of the same protein in a DMPC bilayer shows that the two methods yield comparable predictions of lipid-protein interactions. Taken together, these results demonstrate the utility of CG-MD simulations for studies of membrane/protein interactions.     

Structural transitions and oligomerization along polyalanine fibril formation pathways from computer simulations

The results of a computer simulation study of the aggregation kinetics of a large system of model peptides with particular focus on the formation of intermediates are presented. Discontinuous molecular dynamic simulations were used in combination with our intermediate-resolution protein model, PRIME, to simulate the aggregation of a system of 192 polyalanine (KA(14) K) peptides at a concentration of 5 mM and a reduced temperature of T* = 0.13 starting from a random configuration and ending in the assembly of a fibrillar structure. The population of various structures, including free monomers, beta sheets, amorphous aggregates, hybrid aggregates, and fibrils, and the transitions between the structures were tracked over the course of 30 independent simulations and averaged together. The aggregation pathway for this system starts with the association of free monomers into small amorphous aggregates that then grow to moderate size by incorporating other free monomers or merging with other small amorphous aggregates. These then rearrange into either small beta sheets or hybrid aggregates formed by association between unstructured chains and beta sheets, both of which grow in size by adding free monomer chains or other small aggregates, one at a time. Fibrillar structures are formed initially either by the stacking of beta sheets, rearrangement of hybrid aggregates or association between beta sheets and hybrid aggregates. They grow by the addition of beta sheets, hybrid aggregates, and other small fibrillar structures. The rearrangement of amorphous aggregates into beta sheets is a critical and necessary step in the fibril formation pathway.     

CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background

The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better.

Results

Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions.Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family.

Conclusions

CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.     

Modeling bond correlations in denatured proteins and polypeptides

Bond‐orientational correlations for finite‐length homopolypeptides and a selected group of denatured proteins are obtained by numerical simulations using a polypeptide model with a potential of mean force. These correlations characterize the stiffness of the polypeptide backbone and are generally described by either an exponential or a power‐law decay in the asymptotic limit. However, for finite length polypeptides and unfolded proteins the correlations significantly deviate from either single exponential or power‐law behavior. A heuristic model is developed to analyze the correlations of homopolypeptides, which depends on the chain length and the side‐chain properties. The model contains power‐law and multi‐exponential terms, the latter which could be interpreted as local persistence lengths. In the asymptotic limit, the model reduces to the expected power‐law behavior. Simulations of denatured proteins show that the power‐law behavior of the correlations is significantly suppressed and only the multi‐exponential term is needed to model the correlations. In addition, average persistence lengths (ranging from 2.0 to 2.5 nm) are obtained from the correlations by fitting single exponentials and shown to be in general agreement with experiments, which also assume single exponential decay. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 312–323, 2016.     

Structural disorder: a tool for housekeeping proteins performing tissue-specific interactions

An interaction between a pair of proteins unique for a particular tissue is denoted as a tissue-specific interaction (TSI). Tissue-specific (TS) proteins always perform TSIs with a limited number of interacting partners. However, it has been claimed that housekeeping (HK) proteins frequently take part in TSIs. This is actually an unusual phenomenon. How a single HK protein mediates TSIs – remains an interesting yet an unsolved question. We have hypothesized that HK proteins have attained a high degree of structural flexibility to modulate TSIs efficiently. We have observed that HK proteins are selected to be intrinsically disordered compared to TS proteins. Therefore, the purposeful adaptation of structural disorder brings out special advantages for HK proteins compared to TS proteins. We have demonstrated that TSIs may play vital roles in shaping the molecular adaptation of disordered regions within HK proteins. We also have noticed that HK proteins, mediating a huge number of TSIs, have a greater portion of their interacting interfaces overlapped with the adjacent disordered segment. Moreover, these HK proteins, mediating TSIs, preferably adapt single domain (SD). We have concluded that HK proteins adapt a high degree of structural flexibility to mediate TSIs. Besides, having a SD along with structural flexibility is more economic than maintaining multiple domains with a rigid structure. This assists them in attaining various structural conformations upon binding to their partners, thereby designing an economically optimum molecular system.     

Molecular dynamics simulations of Factor Xa: insight into conformational transition of its binding subsites

Protein flexibility and conformational diversity is well known to be a key characteristic of the function of many proteins. Human blood coagulation proteins have multiple substrates, and various protein-protein interactions are required for the smooth functioning of the coagulation cascade to maintain blood hemostasis. To address how a protein may cope with multiple interactions with its structurally diverse substrates and the accompanied structural changes that may drive these changes, we studied human Factor X. We employed 20 ns of molecular dynamics (MD) and steered molecular dynamics (SMD) simulations on two different conformational forms of Factor X, open and closed, and observed an interchangeable conformational transition from one to another. This work also demonstrates the roles of various aromatic residues involved in aromatic-aromatic interactions, which make this dynamic transition possible.     

The evolutionary relationship of the domain architectures in the RhoGEF-containing proteins

Domain insertions and deletions lead to variations in the domain architectures of the proteins from their common ancestor. In this work, we investigated four groups of the RhoGEF-containing proteins from different organisms with domain architectures RhoGEF-PH-SH3, SH3-RhoGEF-PH, RhoGEF-PH, and SH3-RhoGEF defined in the Pfam database. The phylogenetic trees were constructed using each individual domain and/or the combinations of all the domains. The phylogenetic analysis suggests that RhoGEF-PH-SH3 and SH3-RhoGEF-PH might have evolved from RhoGEF-PH through the insertion of SH3 independently, while SH3- RhoGEF of proteins in fruit fly might have evolved from SH3-RhoGEF-PH by the degeneration of PH domain.     

Amaranthus caudatus lectin with polyproline II fold: conformational and functional transitions and molecular dynamics

Polyproline II (PPII) fold, a peculiar structural element was detected in the Amaranthus caudatus seed lectin (ACL) based on far UV circular dichroism spectrum, conformational transitions of the lectin, and a distinct isodichroic point in thermal denaturation. It was confirmed using PolyprOnline database to estimate the percentage of amino acids contributing to PPII fold and showed the values as 13.5 and 13.9% for PROSS and XTLSSTR, respectively. Investigations of the functional and conformational transitions of ACL during thermal-, pH-, and guanidine hydrochloride (GdnHCl)-induced denaturation were carried out using biochemical and biophysical techniques and molecular dynamics (MD) simulations approach. The lectin got aggregated at 60°C with instantaneous structural alterations. The aggregation-prone regions in ACL were predicted using online servers viz. AGGRESCAN, AmylPred, FoldAmyloid, and Waltz that were represented by Visual Molecular Dynamics tools. Nine conserved regions were identified by these softwares as being ‘hot-spots’ for aggregation. MD simulation studies of the lectin at 60°C revealed increase in radius of gyration. The loss of PPII fold in 2.0 M GdnHCl was reversible. The partially unfolded intermediate of ACL with diminished PPII fold formed at pH 1.0 was stable up to 90°C. The polyproline II fold has been rarely detected in lectins, ACL being the second after the potato lectin.     

Dynamic conformational changes due to the ATP hydrolysis in the motor domain of myosin: 10-ns molecular dynamics simulations

Muscle contraction is caused by directed movement of myosin heads along actin filaments. This movement is triggered by ATP hydrolysis, which occurs within the motor domain of myosin. The mechanism for this intramolecular process remains unknown owing to a lack of ways to observe the detailed motions of each atom in the myosin molecule. We carried out 10-ns all-atom molecular dynamics simulations to investigate the types of dynamic conformational changes produced in the motor domain by the energy released from ATP hydrolysis. The results revealed that the thermal fluctuations modulated by perturbation of ATP hydrolysis are biased in one direction that is relevant to directed movement of the myosin head along the actin filament.     

Coarse‐grained modeling of the intrinsically disordered protein Histatin 5 in solution: Monte Carlo simulations in combination with SAXS

Monte Carlo simulations and coarse‐grained modeling have been used to analyze Histatin 5, an unstructured short cationic salivary peptide known to have anticandidical properties. The calculated scattering functions have been compared with intensity curves and the distance distribution function P(r) obtained from small angle X‐ray scattering (SAXS), at both high and low salt concentrations. The aim was to achieve a molecular understanding and a physico‐chemical insight of the obtained SAXS results and to gain information of the conformational changes of Histatin 5 due to altering salt content, charge distribution, and net charge. From a modeling perspective, the accuracy of the electrostatic interactions are of special interest. The used coarse‐grained model was based on the primitive model in which charged hard spheres differing in charge and in size represent the ionic particles, and the solvent only enters the model through its relative permittivity. The Hamiltonian of the model comprises three different contributions: (i) excluded volumes, (ii) electrostatic, and (iii) van der Waals interactions. Even though the model can be considered as gross omitting all atomistic details, a great correspondence is obtained with the experimental results. Proteins 2016; 84:777–791. © 2016 Wiley Periodicals, Inc.