Structure dictates the mechanism of ligand recognition in the histidine and maltose binding proteins.

Two mechanisms, induced fit (IF) and conformational selection (CS), have been proposed to explain ligand recognition coupled conformational changes. The histidine binding protein (HisJ) adopts the CS mechanism, in which a pre-equilibrium is established between the open and the closed states with the ligand binding to the closed state. Despite being structurally similar to HisJ, the maltose binding protein (MBP) adopts the IF mechanism, in which the ligand binds the open state and induces a transition to the closed state. To understand the molecular determinants of this difference, we performed molecular dynamics (MD) simulations of coarse-grained dual structure based models. We find that intra-protein contacts unique to the closed state are sufficient to promote the conformational transition in HisJ, indicating a CS-like mechanism. In contrast, additional ligand-mimicking contacts are required to "induce" the conformational transition in MBP suggesting an IF-like mechanism. In agreement with experiments, destabilizing modifications to two structural features, the spine helix (SH) and the balancing interface (BI), present in MBP but absent in HisJ, reduce the need for ligand-mimicking contacts indicating that SH and BI act as structural restraints that keep MBP in the open state. We introduce an SH like element into HisJ and observe that this can impede the conformational transition increasing the importance of ligand-mimicking contacts. Similarly, simultaneous mutations to BI and SH in MBP reduce the barrier to conformational transitions significantly and promote a CS-like mechanism. Together, our results show that structural restraints present in the protein structure can determine the mechanism of conformational transitions and even simple models that correctly capture such structural features can predict their positions. MD simulations of such models can thus be used, in conjunction with mutational experiments, to regulate protein ligand interactions, and modulate ligand binding affinities.

Intrinsic Disorder in a Well-Folded Globular Protein.

The folded structure of the heterodimeric sweet protein monellin mimics single-chain proteins with topology ß1-α1-ß2-ß3-ß4-ß5 (chain A: ß3-ß4-ß5; chain B: ß1-α1-ß2). Furthermore, like naturally occurring single-chain proteins of a similar size, monellin folds cooperatively with no detectable intermediates. However, the two monellin chains, A and B, are marginally structured in isolation and fold only upon binding to each other. Thus, monellin presents a unique opportunity to understand the design of intrinsically disordered proteins that fold upon binding. Here, we study the folding of a single-chain variant of monellin (scMn) using simulations of an all heavy-atom structure-based model. These simulations can explain mechanistic details derived from scMn experiments performed using several different structural probes. scMn folds cooperatively in our structure-based simulations, as is also seen in experiments. We find that structure formation near the transition-state ensemble of scMn is not uniformly distributed but is localized to a hairpin-like structure which contains one strand from each chain (ß2, ß3). Thus, the sequence and the underlying energetics of heterodimeric monellin promote the early formation of the interchain interface (ß2-ß3). By studying computational scMn mutants whose "interchain" interactions are deleted, we infer that this energy distribution allows the two protein chains to remain largely disordered when this interface is not folded. From these results, we suggest that cutting the protein backbone of a globular protein between residues which lie within its folding nucleus may be one way to construct two disordered fragments which fold upon binding.

Understanding protein domain-swapping using structure-based models of protein folding.

In domain-swapping, two or more identical protein monomers exchange structural elements and fold into dimers or multimers whose units are structurally similar to the original monomer. Domain-swapping is of biotechnological interest because inhibiting domain-swapping can reduce disease-causing fibrillar protein aggregation. To achieve such inhibition, it is important to understand both the energetics that stabilize the domain-swapped structure and the protein dynamics that enable the swapping. Structure-based models (SBMs) encode the folded structure of the protein in their potential energy functions. SBMs have been successfully used to understand diverse aspects of monomer folding. Symmetrized SBMs model interactions between two identical protein chains using only intra-monomer interactions. Molecular dynamics simulations of such symmetrized SBMs have been used to correctly predict the domain-swapped structure and to understand the mechanism of domain-swapping. Here, we review such models and illustrate that monomer topology determines key aspects of domain-swapping. However, in some proteins, specifics of local energetic interactions modulate domain-swapping and these need to be added to the symmetrized SBMs. We then summarize some general principles of the mechanism of domain-swapping that emerge from the symmetrized SBM simulations. Finally, using our own results, we explore how symmetrized SBMs could be used to design domain-swapping in proteins.

Protein Domain-Swapping Can Be a Consequence of Functional Residues.

Monomer topology has been implicated in domain-swapping, a potential first step on the route to disease-causing protein aggregation. Despite having the same topology (ß1-α1-ß2-ß3-ß4-ß5), the cysteine protease inhibitor stefin-B domain swaps more readily than a single-chain variant of the heterodimeric sweet protein monellin (scMn). Here, we computationally study the folding of stefin-B and scMn in order to understand the molecular basis for the difference in their domain-swapping propensities. In agreement with experiments, our structure-based simulations show that scMn folds cooperatively without the population of an intermediate while stefin-B populates an equilibrium intermediate state. Since the simulation intermediate has only one domain structured (ß3-ß4-ß5), it can directly lead to domain-swapping. Using computational variants of stefin-B, we show that the population of this intermediate is caused by regions of stefin-B that have been implicated in protease inhibition. We also find that the protease-binding regions are located on two structural elements and localized in space. In contrast, the residues that contribute to the sweetness of monellin are not localized to a few structural elements but are distributed over the protein fold. We conclude that the distributed functional residues of monellin do not induce large local perturbations in the protein structure, eliminating the formation of folding intermediates and in turn domain-swapping. On the other hand, the localized protease-binding regions of stefin-B promote the formation of a folding intermediate which can lead to domain-swapping. Thus, domain-swapping can be a direct consequence of the constraints that function imposes on the protein structure.

How maltose influences structural changes to bind to maltose-binding protein: results from umbrella sampling simulation.

A well-studied periplasmic-binding protein involved in the abstraction of maltose is maltose-binding protein (MBP), which undergoes a ligand-induced conformational transition from an open (ligand-free) to a closed (ligand-bound) state. Umbrella sampling simulations have been us to estimate the free energy of binding of maltose to MBP and to trace the potential of mean force of the unbinding event using the center-of-mass distance between the protein and ligand as the reaction coordinate. The free energy thus obtained compares nicely with the experimentally measured value justifying our theoretical basis. Measurement of the domain angle (N-terminal-domain - hinge - C-terminal-domain) along the unbinding pathway established the existence of three different states. Starting from a closed state, the protein shifts to an open conformation during the initial unbinding event of the ligand then resides in a semi-open conformation and later resides predominantly in an open-state. These transitions along the ligand unbinding pathway have been captured in greater depth using principal component analysis. It is proposed that in mixed-model, both conformational selection and an induced-fit mechanism combine to the ligand recognition process in MBP.

Are different stoichiometries feasible for complexes between lymphotoxin-alpha and tumor necrosis factor receptor 1?

BACKGROUND: Tumor necrosis factors, TNF and lymphotoxin-α (LT), are cytokines that bind to two receptors, TNFR1 and TNFR2 (TNF-receptor 1 and 2) to trigger their signaling cascades. The exact mechanism of ligand-induced receptor activation is still unclear. It is generally assumed that three receptors bind to the homotrimeric ligand to trigger a signaling event. Recent evidence, though, has raised doubts if the ligand:receptor stoichiometry should indeed be 3:3 for ligand-induced cellular response. We used molecular dynamics simulations, elastic network models, as well as MM/PBSA to analyze this question. RESULTS: Applying MM/PBSA methodology to different stoichiometric complexes of human LT-(TNFR1)n=1,2,3 the free energy of binding in these complexes has been estimated by single-trajectory and separate-trajectory methods. Simulation studies rationalized the favorable binding energy in the LT-(TNFR1)1 complex, as evaluated from single-trajectory analysis to be an outcome of the interaction of cysteine-rich domain 4 (CRD4) and the ligand. Elastic network models (ENMs) help to associate the difference in the global fluctuation of the receptors in these complexes. Functionally relevant transformation associated with these complexes reveal the difference in the dynamics of the receptor when free and in complex with LT. CONCLUSIONS: MM/PBSA predicts complexes with a ligand-receptor molar ratio of 3:1 and 3:2 to be energetically favorable. The high affinity associated with LT-(TNFR1)1 is due to the interaction between the CRD4 domain with LT. The global dynamics ascertained from ENMs have highlighted the differential dynamics of the receptor in different states.

Cysteine-3 and cysteine-4 are essential for the thioredoxin-like oxidoreductase and antioxidant activities of Plasmodium falciparum macrophage migration inhibitory factor.

Plasmodium falciparum macrophage migration inhibitory factor (PfMIF) exhibits thioredoxin (Trx)-like oxidoreductase activity but the active site for this activity and its function have not been evaluated. A bioinformatics search revealed that the conserved CXXC motif, which is responsible for Trx-like oxidoreductase activity, is absent from PfMIF. In contrast, the adjacent N-terminal Cys-3 and Cys-4 are conserved in MIF across species of malarial parasites. Mutation of either vicinal Cys-3 or Cys-4 of PfMIF abolished the Trx-like activity, whereas the mutation of the remaining Cys-59 or Cys-103 did not affect it. PfMIF has an antioxidant function. It prevents reactive oxygen species-mediated lipid peroxidation and oxidative damage of DNA as evident from DNA nicking assay. Interestingly, chemical modification of the vicinal cysteines by phenylarsine oxide (PAO), a specific vicinal thiol modifier, significantly prevented this antioxidant activity. Modification of Cys-3 and Cys-4 was confirmed by MALDI-TOF mass spectroscopy of peptide fragments obtained after cyanogen bromide digestion of PAO-modified PfMIF. Furthermore, mutation of either Cys-3 or Cys-4 of PfMIF resulted in the loss of both Trx-like oxidoreductase and antioxidant activities of PfMIF. Altogether, our results suggest that the vicinal Cys-3 and Cys-4 play a critical role in the Trx-like oxidoreductase activity and antioxidant property of PfMIF.

Deciphering the Structural Requirements of Nucleoside Bisubstrate Analogues for Inhibition of MbtA in Mycobacterium tuberculosis: A FB-QSAR Study and Combinatorial Library Generation for Identifying Potential Hits.

The re-emergence of tuberculosis infections, which are resistant to conventional drug therapy, has steadily risen in the last decade. Inhibitors of aryl acid adenylating enzyme known as MbtA, involved in siderophore biosynthesis in Mycobacterium tuberculosis, are being explored as potential antitubercular agents. The ability to identify fragments that interact with a biological target is a key step in fragment based drug design (FBDD). To expand the boundaries of quantitative structure activity relationship (QSAR) paradigm, we have proposed a Fragment Based QSAR methodology, referred here in as FB-QSAR, for deciphering the structural requirements of a series of nucleoside bisubstrate analogs for inhibition of MbtA, a key enzyme involved in siderophore biosynthetic pathway. For the development of FB-QSAR models, statistical techniques such as stepwise multiple linear regression (SMLR), genetic function approximation (GFA) and GFAspline were used. The predictive ability of the generated models was validated using different statistical metrics, and similarity-based coverage estimation was carried out to define applicability boundaries. To aid the creation of novel antituberculosis compounds, a bioisosteric database was enumerated using the combichem approach endorsed mining in a lead-like chemical space. The generated library was screened using an integrated in-silico approach and potential hits identified.

Why pyridine containing pyrido[2,3-d]pyrimidin-7-ones selectively inhibit CDK4 than CDK2: insights from molecular dynamics simulation.

Designing selective cyclin-dependent kinase 4 (CDK4) inhibitors is an area of intense research to develop potential anticancer drugs. The molecular basis governing the selective inhibition of CDK4 by lig17 (6-bromo-8-cyclopentyl-2-(5-piperazin-1-yl-pyridin-2-ylamino)-8H-pyrido[2,3-d]pyrimidin-7-one) has been investigated using molecular dynamics simulation. The positive charge on the ligand was determined to be an important contributor for CDK4 selectivity due to the electronegative nature of its active site. Similar studies on CDK2 indicated that Lys89 intrudes into the active site displacing the positive charge on lig17 away from the active center. This intrusion was observed to propel a drastic conformational change in lig17, weakening its binding interactions with the protein. The pyridine nitrogen (N(AR)) of lig17 was capable of interacting with His95 (CDK4) through hydrogen bonding. N(AR) also showed a strong tendency to mediate protein-ligand interactions through a bridged water molecule, only when bound to CDK4. The G-loop of CDK4 was observed to fluctuate extensively when complexed with lig17 and a novel "flipping-out" mechanism exhibited by Tyr17(CDK4/CDK4-17) is reported in this study. Although these proteins have similar folds, the results from principal component analysis (PCA) indicate that CDK4 and CDK2 follow an anti-correlated behavior towards the accessibility of the active site.

Hybrid structure-based virtual screening protocol for the identification of novel BACE1 inhibitors.

BACE1, also called beta-secretase or memapsin 2, is an extensively studied aspartic protease, involved in etiopathogenesis and progression of Alzheimer's disease (AD). We report herein a modified structure-based virtual screening protocol that augments the lead identification process against BACE1 during virtual screening endeavors. A hybrid structure-based virtual screening protocol that incorporates elements from both ligand-based and structure-based techniques was used for the identification of prospective small molecule inhibitors. Virtual screening, using an active-site-derived pharmacophore, followed by ROCS (rapid overlay of chemical structures)-based GOLD (genetic optimization in ligand docking) docking was used to identify a library of focused candidates. The efficacy of the ROCS-based GOLD docking method together with our customized weighted consensus scoring function was evaluated against conventional docking methods for its ability to discern true positives from a screening library. An in-depth structural analysis of the binding mode of the top-ranking molecules reveals that emulation of the curial interaction patterns deemed necessary for BACE1 inhibition. The results obtained from our validation study ensure the superiority of our docking methodology over conventional docking methods in yielding higher enrichment rates.

Combined ligand and structure based approaches for narrowing on the essential physicochemical characteristics for CDK4 inhibition.

In the absence of an experimentally determined 3D structure of CDK4 (Cyclin-Dependent Kinase 4), QSARs (Quantitative Structure Activity Relationship) have been explored to rationalize binding affinity in terms of physicochemical and structural parameters. Further, docking on a homology model of CDK4 validated the derived QSARs and predicted the binding mode of this series of inhibitors. Relevant parameters and leave-one-out (LOO) cross-validation (q (2)) as well as an external test set validation (r (2) pred) judged the statistical significance and predictive ability of the models. Docking enabled a better understanding of protein-ligand interaction and provided a mechanistic interpretation in terms of physicochemical characteristics. It identified a unique hydrogen bonding between the imidazole of His-95 and the pyridine nitrogen in the ligand. It rationalized the need for R 2 substituents to be bulky and polar, while the substituent at R 8 to be hydrophobic and comparatively less steric. It also explained why at R 6 a variety of substituents are tolerated and how the presence of methyl at R 5 enhances binding affinity.

An efficient tool for identifying inhibitors based on 3D-QSAR and docking using feature-shape pharmacophore of biologically active conformation--a case study with CDK2/cyclinA.

This study proposes a fast and efficient approach for identifying novel inhibitors when the biologically active conformation of an inhibitor is known. The present study was carried out with CDK2/CyclinA inhibitors. The co-crystal structure of the most active ligand with CDK2/CyclinA was converted into a feature-shape query. This query served three purposes (i) alignment of molecules to generate 3D-QSAR model, (ii) rigid docking to the active site using GOLD, (iii) extracting hits from databases. A statistically valid 3D-QSAR (r(2)=0.867, q(2)=0.887) with good external set prediction (r(pred)(2)=0.890) was obtained. The docked poses were analyzed based on their interaction with hinge region (Glu81-Leu83) of CDK2. A reasonably good consensus score was generated using 11 scoring functions. The developed model was then successfully used to identify potential leads for CDK2/CyclinA inhibitors.