Design, Synthesis, Biological Evaluation and in Silico Studies of Curcumin Pyrrole Conjugates.

Curcumin conjugated heterocyclic compounds are potent candidates with drug likeness against various bacterial pathogens. A set of curcumin-based pyrrole conjugates (CPs) were synthesized and characterized by FT-IR, 1H and 13C NMR and HR-MS techniques. The results of free radical scavenging activity of the synthesized CPs, evaluated by FRAP and CUPRAC assays, showed the potency of these compounds as effective antioxidants. CP3 exhibits the highest antioxidant activity amongst the CPs. The bactericidal efficacy of CPs was screened against ESKAP bacterial pathogens, and CPs were found to possess better antibacterial property than curcumin, specifically against staphylococcus aureus bacteria. In addition, serum albumin (BSA and HSA) binding interaction of these CPs were determined by UV-visible and fluorescence spectrophotometric techniques. In-silico molecular docking study was performed to determine the binding patterns of molecular targets against Staphylococcus aureus tyrosyl tRNA synthetase, and serum albumin proteins. The structure-activity relationship showed that the presence of multiple phenolic hydroxyl groups, and electron withdrawing groups on the structure of CP molecule, enhances its antioxidant and antibacterial activity, respectively.

In silico design of misfolding resistant proteins: the role of structural similarity of a competing conformational ensemble in the optimization of frustration.

Most state-of-the-art in silico design methods fail due to misfolding of designed sequences to a conformation other than the target. Thus, a method to design misfolding resistant proteins will provide a better understanding of the misfolding phenomenon and will also increase the success rate of in silico design methods. In this work, we optimize the conformational ensemble to be selected for negative design purposes based on the similarity of the conformational ensemble to the target. Five ensembles with different degrees of similarity to the target are created and destabilized and the target is stabilized while designing sequences using mean field theory and Monte Carlo simulation methods. The results suggest that the degree of similarity of the non-native conformations to the target plays a prominent role in designing misfolding resistant protein sequences. The design procedures that destabilize the conformational ensemble with moderate similarity to the target have proven to be more promising. Incorporation of either highly similar or highly dissimilar conformations to the target conformation into the non-native ensemble to be destabilized may lead to sequences with a higher misfolding propensity. This will significantly reduce the conformational space to be considered in any protein design procedure. Interestingly, the results suggest that a sequence with higher frustration in the target structure does not necessarily lead to a misfold prone sequence. A successful design method may purposefully choose a frustrated sequence in the target conformation if that sequence is even more frustrated in the competing non-native conformations.

Recent advances in de novo computational design and redesign of intrinsically disordered proteins and intrinsically disordered protein regions.

In the early 2000s, the concept of "unstructured biology" has emerged to be an important field in protein science by generating various new research directions. Many novel strategies and methods have been developed that are focused on effectively identifying/predicting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs), identifying their potential functions, disorder based drug design etc. Due to the range of functions of IDPs/IDPRs and their involvement in various debilitating diseases they are of contemporary interest to the scientific community. Recent researches are focused on designing/redesigning specific IDPs/IDPRs de novo. These de novo design/redesigns of IDPs/IDPRs are carried out by altering compositional biases and specific sequence patterning parameters. The main focus of these researches is to influence specific molecular functions, phase behavior, cellular phenotypes etc. In this review, we first provide the differences of natively folded and natively unfolded or IDPs with respect to their potential energy landscapes. Here, we provide current understandings on the different computational design strategies and methods that have been utilized in de novo design and redesigns of IDPs and IDPRs. Finally, we conclude the review by discussing the challenges that have been faced during the computational design/design attempts of IDPs/IDPRs.

In silico analysis of SOD1 aggregation inhibition modes of tertiary amine pyrazolone and pyrano coumarin ferulate as ALS drug candidates.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, the familial form (fALS) of which is often cognate to mutations in the antioxidant enzyme Cu/Zn superoxide dismutase 1 (SOD1) leading to misfolding and aggregation. Two small molecules, a tertiary amine pyrazolone (TAP) and a pyrano coumarin ferulate (PCF) were suggested to be ALS drug candidates following experimental observation of their ability to inhibit SOD1 protein misfolding and aggregation. The present work aims at computational investigation of these experimentally proposed drug candidates to gain insight into their mechanism of SOD1 misfolding and aggregation inhibition. On the basis of molecular docking, molecular dynamics simulation, MM-PBSA and per-residue energy decomposition analysis, we examined the specific interactions of TAP and PCF with three probable binding sites of SOD1, namely, dimeric interface cavity, W32 and, UMP binding sites. Results suggest that the binding of TAP at W32 and at UMP sites are least probable due to absence of any favorable interaction. The binding of TAP to dimeric cavity is also unstable due to strong unfavorable interactions. In case of PCF, binding at the UMP site is least probable while binding at dimeric cavity is accompanied by unfavorable interactions. PCF, however, exhibits stable binding with the W32 binding site of SOD1 by stabilizing the solvent accessible hydrophobic residues, which otherwise would have acted as contact points for aggregation. Thus the results imply that compound PCF functions as an inhibitior of SOD1 misfolding/aggregation through direct interaction with the protein SOD1 at the W32 binding site. However, TAP is likely to act as an inhibitor through a different mechanism rather than direct interaction with the protein SOD1. These results apart from reinforcing previous experimental findings, shed light on the probable mechanism of action of the proposed drug candidates.

Advances in the understanding of protein misfolding and aggregation through molecular dynamics simulation.

Aberrant protein folding known as protein misfolding is counted as one of the striking factors of neurodegenerative diseases. The extensive range of pathologies caused by protein misfolding, aggregation and subsequent accumulation are mainly classified into either gain of function diseases or loss of function diseases. In order to seek for novel strategies for treatment and diagnosis of neurodegenerative diseases, insights into the mechanism of misfolding and aggregation is essential. A comprehensive knowledge on the factors influencing misfolding and aggregation is required as well. An extensive experimental study on protein aggregation is somewhat challenging due to the insoluble and noncrystalline nature of amyloid fibrils. Thus there has been a growing use of computational approaches including Monte Carlo simulation, docking simulation, molecular dynamics simulation in the study of protein misfolding and aggregation. The review presents a discussion on molecular dynamics simulation alone as to how it has emerged as a promising tool in the understanding of protein misfolding and aggregation in general, detailing upon three different aspects considering four misfold prone proteins in particular. It is noticeable that all four proteins considered in this review i.e prion, superoxide dismutase1, huntingtin and amyloid ß are linked to chronic neurodegenerative diseases with debilitating effects. Initially the review elaborates on the factors influencing the misfolding and aggregation. Next, it addresses our current understanding of the amyloid structures and the associated aggregation mechanisms, finally, summarizing the contribution of this computational tool in the search for therapeutic strategies against the respective protein-deposition diseases.

Identification of an optimal foldability criterion to design misfolding resistant protein.

Proteins achieve their functional, active, and operative three dimensional native structures by overcoming the possibility of being trapped in non-native energy minima present in the energy landscape. The enormous and intricate interactions that play an important role in protein folding also determine the stability of the proteins. The large number of stabilizing/destabilizing interactions makes proteins to be only marginally stable as compared to the other competing structures. Therefore, there are some possibilities that they become trapped in the non-native conformations and thus get misfolded. These misfolded proteins lead to several debilitating diseases. This work performs a comparative study of some existing foldability criteria in the computational design of misfold resistant protein sequences based on self-consistent mean field theory. The foldability criteria selected for this study are Ef, Δ, and Φ that are commonly used in protein design procedures to determine the most efficient foldability criterion for the design of misfolding resistant proteins. The results suggest that the foldability criterion Δ is significantly better in designing a funnel energy landscape stabilizing the target state. The results also suggest that inclusion of negative design features is important for designing misfolding resistant proteins, but more information about the non-native conformations in terms of Φ leads to worse results compared to even simple positive design. The sequences designed using Δ show better resistance to misfolding in the Monte Carlo simulations performed in the study.

Role of local and nonlocal interactions in folding and misfolding of globular proteins.

A Monte Carlo simulation based sequence design method is proposed to study the role of the local and the nonlocal interactions with varying secondary structure content in protein folding, misfolding and unfolding. A statistical potential is developed from the compilation of a data set of proteins, which accounts for the respective contribution of local and the nonlocal interactions. Sequences are designed through a combination of positive and negative design by a Monte Carlo simulation in the sequence space. The weights of the local and the nonlocal interactions are tuned appropriately to study the role of the local and the nonlocal interactions in the folding, unfolding and misfolding of the designed sequences. Results suggest that the nonlocal interactions are the primary determinant of protein folding while the local interactions may be required but not always necessary. The nonlocal interactions mainly guide the polypeptide chain to form compact structures but do not differentiate between the native-like conformations, while the local interactions stabilize the target conformation against the native-like competing conformations. The study concludes that the local interactions govern the fold-misfold transition, while the nonlocal interactions regulate the fold-unfold transition of proteins. However, for proteins with predominantly ß-sheet content, the nonlocal interactions control both fold-misfold and fold-unfold transitions.

Globular-disorder transition in proteins: a compromise between hydrophobic and electrostatic interactions?

The charge-hydrophobicity correlation of globular and disordered proteins is explored using a generalized self-consistent field theoretical method combined with Monte Carlo simulations. Globular and disordered protein sequences with varied mean net charge and mean hydrophobicity are designed by theory, while Metropolis Monte Carlo generates a suitable ensemble of conformations. Results imply a transition of the dominant interactions between globular and disordered proteins across the charge-hydrophobicity boundary. It is observed that the charge-hydrophobicity boundary actually represents a trade-off between the repulsive and attractive interactions in a protein sequence. The attractive interactions predominate on the globular side of the boundary, while the repulsive interactions prevail on the disordered side. For globular proteins, core forming hydrophobic interactions are dominant leading to a minimally frustrated native conformation. For disordered proteins, the repulsive electrostatic interactions prevail yielding a minimally frustrated region comprising of an expanded, dynamic conformational ensemble. Thus, protein disorder, like protein folding, satisfies the principle of minimal frustration. All results are compared to real globular and disordered proteins. Thus this algorithm may be useful to probe the conformational characteristics of disordered proteins.

Conformational Entropy of Intrinsically Disordered Proteins from Amino Acid Triads.

This work quantitatively characterizes intrinsic disorder in proteins in terms of sequence composition and backbone conformational entropy. Analysis of the normalized relative composition of the amino acid triads highlights a distinct boundary between globular and disordered proteins. The conformational entropy is calculated from the dihedral angles of the middle amino acid in the amino acid triad for the conformational ensemble of the globular, partially and completely disordered proteins relative to the non-redundant database. Both Monte Carlo (MC) and Molecular Dynamics (MD) simulations are used to characterize the conformational ensemble of the representative proteins of each group. The results show that the globular proteins span approximately half of the allowed conformational states in the Ramachandran space, while the amino acid triads in disordered proteins sample the entire range of the allowed dihedral angle space following Flory's isolated-pair hypothesis. Therefore, only the sequence information in terms of the relative amino acid triad composition may be sufficient to predict protein disorder and the backbone conformational entropy, even in the absence of well-defined structure. The predicted entropies are found to agree with those calculated using mutual information expansion and the histogram method.

Designing pH induced fold switch in proteins.

This work investigates the computational design of a pH induced protein fold switch based on a self-consistent mean-field approach by identifying the ensemble averaged characteristics of sequences that encode a fold switch. The primary challenge to balance the alternative sets of interactions present in both target structures is overcome by simultaneously optimizing two foldability criteria corresponding to two target structures. The change in pH is modeled by altering the residual charge on the amino acids. The energy landscape of the fold switch protein is found to be double funneled. The fold switch sequences stabilize the interactions of the sites with similar relative surface accessibility in both target structures. Fold switch sequences have low sequence complexity and hence lower sequence entropy. The pH induced fold switch is mediated by attractive electrostatic interactions rather than hydrophobic-hydrophobic contacts. This study may provide valuable insights to the design of fold switch proteins.

Does lack of secondary structure imply intrinsic disorder in proteins? A sequence analysis.

Intrinsically disordered proteins (IDPs)/protein regions (IDPRs) lack unique three-dimensional structure at the level of secondary and/or tertiary structure and are represented as an ensemble of interchanging conformations. To investigate the role of presence/absence of secondary structures in promoting intrinsic disorder in proteins, a comparative sequence analysis of IDPs, IDPRs and proteins with minimal secondary structures (less than 5%) is required. A sequence analysis reveals proteins with minimal secondary structure content have high mean net positive charge, low mean net hydrophobicity and low sequence complexity. Interestingly, analysis of the relative local electrostatic interactions reveal that an increase in the relative repulsive interactions between amino acids separated by three or four residues lead to either loss of secondary structure or intrinsic disorder. IDPRs show increase in both local negative-negative and positive-positive repulsive interactions. While IDPs show a marked increase in the local negative-negative interactions, proteins with minimal secondary structure depict an increase in the local positive-positive interactions. IDPs and IDPRs are enriched in D, E and Q residues, while proteins with minimal secondary structure are depleted of these residues. Proteins with minimal secondary structures have higher content of G and C, while IDPs and IDPRs are depleted of these residues. These results confirm that proteins with minimal secondary structure have a distinctly different propensity for charge, hydrophobicity, specific amino acids and local electrostatic interactions as compared to IDPs/IDPRs. Thus we conclude that lack of secondary structure may be a necessary but not a sufficient condition for intrinsic disorder in proteins.

The role of site-directed point mutations in protein misfolding.

A self-consistent mean-field based model is presented to explore the role of site-directed point mutations in designing folded and/or misfolded sequences with a reduced hydrophobic-polar (HP) patterning of amino acids. This site-directed point mutation procedure is developed and applied to both real and lattice proteins to generate a diverse set of sequences. The respective roles of core and surface residues are analyzed with respect to the optimum hydrophobicity required for the structural stability of the protein. The core sites are found to have a critical number of hydrophobic residues, below which a protein may misfold, while the surface sites show a clear preference for the polar residues with the ability to tolerate some hydrophobic residues. Although core sites play an important role in the structural stability of proteins, some specific surface sites are also found to be equally important. A clash and match calculation procedure is proposed, which may be used to predict the number of residue pairs in a sequence with unfavorable and favorable interactions, respectively, due to site-directed point mutations. The number of clashing and matching residue pairs may indicate whether the mutated sequence would be folded or misfolded. The results are independent of the secondary structure topology of the protein. This model may provide new insights into the effect of point mutations on protein stability and may introduce a new method to predict the outcome of a mutation in terms of its probability to fold or misfold.