Andrzej Kloczkowski - Academia.edu (original) (raw)

Papers by Andrzej Kloczkowski

Molecules

Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the... more Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the second decade of life. It mostly occurs due to t(11;22) (q24;q12) translocation. This translocation encodes the oncogenic fusion protein EWS/FLI (Friend leukemia integration 1 transcription factor), which acts as an aberrant transcription factor to deregulate target genes essential for cancer. Traditionally, flavonoids from plants have been investigated against viral and cancerous diseases and have shown some promising results to combat these disorders. In the current study, representative flavonoid compounds from various subclasses are selected and used to disrupt the RNA-binding motif of EWS, which is required for EWS/FLI fusion. By blocking the RNA-binding motif of EWS, it might be possible to combat ES. Therefore, molecular docking experiments validated the binding interaction patterns and structural behaviors of screened flavonoid compounds within the active region of the Ewing sar...

International Journal of Molecular Sciences

To develop new alkaline phosphatase inhibitors (ALP), a series of pyrazolo-oxothiazolidine deriva... more To develop new alkaline phosphatase inhibitors (ALP), a series of pyrazolo-oxothiazolidine derivatives were synthesized and biologically assessed, and the results showed that all of the synthesized compounds significantly inhibited ALP. Specifically, compound 7g displayed the strongest inhibitory activity (IC50 = 0.045 ± 0.004 μM), which is 116-fold more active than monopotassium phosphate (IC50 = 5.242 ± 0.472 μM) as a standard reference. The most potent compound among the series (7g) was checked for its mode of binding with the enzyme and shown as non-competitively binding with the target enzyme. The antioxidant activity of these compounds was examined to investigate the radical scavenging effect. Moreover, the MTT assay method was performed to evaluate their toxic effects on the viability of MG-63 human osteosarcoma cells, and all compounds have no toxic effect on the cells at 4 μM. Computational research was also conducted to examine the binding affinity of the ligands with alka...

Nanocomposite Materials [Working Title]

Since the isolation and identification of graphene, the academic and industrial communities are u... more Since the isolation and identification of graphene, the academic and industrial communities are utilizing its superior properties. This minireview deals with the processing of graphene-based fillers/elastomer nanocomposites. The incorporation of graphene in an elastomeric matrices has significant effects on the properties of nanocomposites. The dispersion of graphene in elastomers is discussed. The processing of graphene/elastomer nanocomposites is discussed. The mechanical properties of the elastomeric matrix can be enhanced due to the presence of graphene. In this review and due to space limitations, we will present an example of improvements in the mechanical characteristics of graphene/styrene-butadiene (SBR) elastomer nanocomposites.

Distinguishing between harmful and benign genetic variations is fundamental to our understanding ... more Distinguishing between harmful and benign genetic variations is fundamental to our understanding of the relationship between genome and disease in general and for personalized medicine in particular. We investigated the relationship between predicted change in RASA and the phenotype of a missense mutation (MM). The ASAquick program was used to obtain RASA predictions for the original and mutated sequence and a parameter, δ , was introduced to assess the change in RASA for a given MM. We find that predicted RASA shows a robust, intricate signal with respect to genetic variation and that changes in RASA between variants can form a basis for a simple and quick predictor of the effect of MMs. Furthermore, we find that for hydrophobic residues, increase in the RASA corresponds to an increase in the likelihood that a MM would be harmful. For hydrophilic residues we find that a decrease in the RASA corresponds to a likelihood that a MM would be harmful. We also find that the size of the ch...

Vietnam Journal of Science and Technology, 2018

Recently single molecule force spectroscopy has become an useful tool to study protein, DNA and R... more Recently single molecule force spectroscopy has become an useful tool to study protein, DNA and RNA. However, very little attention was paid to homopolymer which plays an important role in many domains of science. In this paper we make the first attempt to decipher the free energy landscape of homopolymer using the external force as reaction coordinate. The impact of the quenched force on the free energy landscape was studied using simplified coarse-grain Go model. Similar to protein, we have obtained a clear switch from the thermal regime to force-driven regime. The distance between the denatured state and transition state in the temperature-driven regime is smaller than in the force-driven one. Having a rugged free energy landscape without a pronounced funnel the homopolymer folding is much slower than that of protein making study of homopolymer very time consuming.

Biophysical Journal, 2018

cardiac dysfunction. Here, we used structural and biophysical approaches to better understand the... more cardiac dysfunction. Here, we used structural and biophysical approaches to better understand the pathogenesis of a cardiac troponin C (cTnC) C84Y mutation located in the D/E linker, first reported in a 17-year-old proband, presenting with left-ventricular hypertrophy. Despite the relevance of HCM disease, little is known concerning the function of the D/E linker and allosteric phenomena governing cTnC Ca 2þ affinity. Monitored by bis-ANS fluorescence, Ca 2þ-titrations reveal that C84Y exhibits enhanced Ca 2þ-binding affinity in both domains and conformational changes compared to WT. Although WT and C84Y display distinct Ca 2þ-binding behaviors, the overall dimensional values and molecular envelopes generated by small-angle-X-ray scattering data remains similar. Using circular-dichroism, C84Y revealed significantly lower thermostability in non-Ca 2þ-bound form compared to WT. Most of our understanding of the molecular mechanisms underlying how troponin and troponin peptides switch muscle contraction ''on'' and ''off'' has been derived using experimental NMR techniques. Currently, no experimental techniques are available that allow the understanding of protein regulatory/dynamic processes at the molecular level of large, multi-domain protein complexes. To further unravel molecular changes in C84Y, three-dimensional NMR experiments were performed for backbone assignment. The largest chemical shifts were observed in N-Helix residues and at the end of D-helix and D/E linker. NMR-derived backbone amide temperature-coefficients indicate different temperature-dependent conformational changes exist between WT and C84Y Carr-Purcell-Meiboom-Gill relaxation dispersion (CPMG-RD) and R1/R2 experiments were used to probe the population and exchanging rates of C84Y compared to WT. This work sought to elucidate: main structural components underlying this pathological mutation, novel allosteric mechanisms, and the role of D/E linker in cTnC.

Methods in Molecular Biology, 2020

We have studied the ability of three types of neural networks to predict the closeness of a given... more We have studied the ability of three types of neural networks to predict the closeness of a given protein model to the native structure associated with its sequence. We show that a partial combination of the Levenberg-Marquardt algorithm and the back-propagation algorithm produced the best results, giving the lowest error and largest Pearson correlation coefficient. We also find, as previous studies, that adding associative memory to a neural network improves its performance. Additionally, we find that the hybrid method we propose was the most robust in the sense that other configurations of it experienced less decline in comparison to the other methods. We find that the hybrid networks also undergo more fluctuations on the path to convergence. We propose that these fluctuations allow for better sampling. Overall we find it may be beneficial to treat different parts of a neural network with varied computational approaches during optimization.

Several novel techniques have been combined to improve protein structure prediction, structural r... more Several novel techniques have been combined to improve protein structure prediction, structural refinement and quality assessment of protein models. We discuss in brief the development of four-body potentials that take into account dense packing and cooperativity of interactions of proteins, and its success. We have developed a method that uses whole protein information filtered through machine learning to score protein models based on their likeness to native structure. Here we consider electrostatic interactions and residue depth, and use these for structure prediction. These potentials were tested to be successful in CASP9 and CASP10. We have also developed a Quality Assessment technique, MQAPsingle, which is a quasi-single-model MQAP, by combining advantages of both “pure” single-model MQAPs and clustering MQAPs. This technique can be used in ranking and assessing the absolute global quality of single protein models. This model (Pawlowski-Kloczkowski) was ranked 3rd in Model Qua...

Scientific Reports, 2021

Proteins are tiny players involved in the activation and deactivation of multiple signaling casca... more Proteins are tiny players involved in the activation and deactivation of multiple signaling cascades through interactions in cells. The TNFR1 and MADD interact with each other and mediate downstream protein signaling pathways which cause neuronal cell death and Alzheimer’s disease. In the current study, a molecular docking approach was employed to explore the interactive behavior of TNFR1 and MADD proteins and their role in the activation of downstream signaling pathways. The computational sequential and structural conformational results revealed that Asp400, Arg58, Arg59 were common residues of TNFR1 and MADD which are involved in the activation of downstream signaling pathways. Aspartic acid in negatively charged residues is involved in the biosynthesis of protein. However, arginine is a positively charged residue with the potential to interact with oppositely charged amino acids. Furthermore, our molecular dynamic simulation results also ensured the stability of the backbone of T...

Frontiers in Molecular Biosciences, 2021

Two new computational approaches are described to aid in the design of new peptide-based drugs by... more Two new computational approaches are described to aid in the design of new peptide-based drugs by evaluating ensembles of protein structures from their dynamics and through the assessing of structures using empirical contact potential. These approaches build on the concept that conformational variability can aid in the binding process and, for disordered proteins, can even facilitate the binding of more diverse ligands. This latter consideration indicates that such a design process should be less restrictive so that multiple inhibitors might be effective. The example chosen here focuses on proteins/peptides that bind to hemagglutinin (HA) to block the large-scale conformational change for activation. Variability in the conformations is considered from sets of experimental structures, or as an alternative, from their simple computed dynamics; the set of designe peptides/small proteins from the David Baker lab designed to bind to hemagglutinin, is the large set considered and is asses...

Biophysical Journal, 2018

Entropy, 2019

Entropy should directly reflect the extent of disorder in proteins. By clustering structurally re... more Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of fluctuations at a given MSA site and used these as representative of the sequence and structure entropy at that site. In general, we found a tendency for negative correlations between disorder and structure, and significant positive correlations between disorder and the fluctuations in the system. We also found evidence for residue-type conservation for those residues proximate to potentially disordered sites. Mutation at the disorder site itself appear to be allowed. In addition, we found positive correlation for disorder and accessible surface area, validating that disordered residues occur in exposed regions of proteins. Finally, we also found that fluctuations in the ...

The Journal of Chemical Physics, 2018

Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neuro... more Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Despite much progress in the understanding of the protein aggregation process, the factors governing fibril formation rates and fibril stability have not been fully understood. Using lattice models, we have shown that the fibril formation time is controlled by the kinetic stability of the fibril state but not by its energy. Having performed all-atom explicit solvent molecular dynamics simulations with the GROMOS43a1 force field for full-length amyloid beta peptides Aβ40 and Aβ42 and truncated peptides, we demonstrated that kinetic stability can be accessed via mechanical stability in such a way that the higher the mechanical stability or the kinetic stability, the faster the fibril formation. This result opens up a new way for predicting fibril formation rates based on mechanical stability that may be easily estimated by...

Biophysical Journal, 2019

Biophysical Journal, 2019

Protein-peptide interactions play essential roles in many cellular processes and their structural... more Protein-peptide interactions play essential roles in many cellular processes and their structural characterization is the major focus of current experimental and theoretical research. Two decades ago, it was proposed to employ the steered molecular dynamics to assess the strength of protein-peptide interactions 1. The idea behind using steered molecular dynamics simulations is that the mechanical stability can be used as an efficient alternative to computationally highly demanding estimation of binding affinity and aggregation rate 2,3. However, mechanical stability defined as a peak in force-extension profile depends on the choice of the pulling direction. Here we propose an uncommon choice of the pulling direction along resultant dipole moment vector, which has not been explored in simulations so far. Using explicit solvent all-atom MD simulations, we apply steered molecular dynamics technique to probe mechanical resistance of protein-peptide system pulled along two different vectors 4. A novel pulling direction, along the resultant dipole moment vector, results in stronger forces compared to commonly used peptide unbinding along center of masses vector. Our results demonstrate that resultant dipole moment is one of the factors influencing the mechanical stability of protein-peptide complex.

Journal of Biomolecular Structure and Dynamics, 2017

Disordered protein chains and segments are fast becoming a major pathway for our understanding of... more Disordered protein chains and segments are fast becoming a major pathway for our understanding of biological function, especially in more evolved species. However, the standard definition of disordered residues: the inability to constrain them in X-ray derived structures, is not easily applied to NMR derived structures. We carry out a statistical comparison between proteins whose structure was resolved using NMR and using X-ray protocols. We start by establishing a connection between these two protocols for obtaining protein structure. We find a close statistical correspondence between NMR and X-ray structures if fluctuations inherent to the NMR protocol are taken into account. Intuitively this tends to lend support to the validity of both NMR and X-ray protocols in deriving biomolecular models that correspond to in-vivo conditions. We then establish Lindemann-like parameters for NMR derived structures and examine what order/disorder cutoffs for these parameters are most consistent with X-ray data and how consistent are they. Finally, we find critical value of L = 4 for the best correspondence between X-ray and NMR derived order/disorder assignment, judged by maximizing the Matthews correlation, and a critical value L = 1.5 if a balance between false positive and false negative prediction is sought. We examine a few non-conforming cases, and examine the origin of the structure derived in X-ray. This study could help in assigning meaningful disorder from NMR experiments.

BMC Bioinformatics, 2016

Background: Sequence matching is extremely important for applications throughout biology, particu... more Background: Sequence matching is extremely important for applications throughout biology, particularly for discovering information such as functional and evolutionary relationships, and also for discriminating between unimportant and disease mutants. At present the functions of a large fraction of genes are unknown; improvements in sequence matching will improve gene annotations. Universal amino acid substitution matrices such as Blosum62 are used to measure sequence similarities and to identify distant homologues, regardless of the structure class. However, such single matrices do not take into account important structural information evident within the different topologies of proteins and treats substitutions within all protein folds identically. Others have suggested that the use of structural information can lead to significant improvements in sequence matching but this has not yet been very effective. Here we develop novel substitution matrices that include not only general sequence information but also have a topology specific component that is unique for each CATH topology. This novel feature of using a combination of sequence and structure information for each protein topology significantly improves the sequence matching scores for the sequence pairs tested. We have used a novel multi-structure alignment method for each homology level of CATH in order to extract topological information. Results: We obtain statistically significant improved sequence matching scores for 73 % of the alpha helical test cases. On average, 61 % of the test cases showed improvements in homology detection when structure information was incorporated into the substitution matrices. On average z-scores for homology detection are improved by more than 54 % for all cases, and some individual cases have z-scores more than twice those obtained using generic matrices. Our topology specific similarity matrices also outperform other traditional similarity matrices and single matrix based structure methods. When default amino acid substitution matrix in the Psi-blast algorithm is replaced by our structure-based matrices, the structure matching is significantly improved over conventional Psi-blast. It also outperforms results obtained for the corresponding HMM profiles generated for each topology. Conclusions: We show that by incorporating topology-specific structure information in addition to sequence information into specific amino acid substitution matrices, the sequence matching scores and homology detection are significantly improved. Our topology specific similarity matrices outperform other traditional similarity matrices, single matrix based structure methods, also show improvement over conventional Psi-blast and HMM profile based methods in sequence matching. The results support the discriminatory ability of the new amino acid similarity matrices to distinguish between distant homologs and structurally dissimilar pairs.

Physical Chemistry Chemical Physics, 2017

This paper explores how and why FVFLM peptides can be used as model systems to inhibit beta-amylo... more This paper explores how and why FVFLM peptides can be used as model systems to inhibit beta-amyloid aggregation.

Biophysical Journal, 2017

results identify large-scale structural burial of four key hydrophobic residues toward its C-term... more results identify large-scale structural burial of four key hydrophobic residues toward its C-terminal end and provide a molecular view of its dynamic structure-ensemble at the TMAO-induced folded state of this intrinsically disordered transactivation domain of ERa.

Molecules

Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the... more Ewing sarcoma (ES) is a highly malignant carcinoma prevalent in children and most frequent in the second decade of life. It mostly occurs due to t(11;22) (q24;q12) translocation. This translocation encodes the oncogenic fusion protein EWS/FLI (Friend leukemia integration 1 transcription factor), which acts as an aberrant transcription factor to deregulate target genes essential for cancer. Traditionally, flavonoids from plants have been investigated against viral and cancerous diseases and have shown some promising results to combat these disorders. In the current study, representative flavonoid compounds from various subclasses are selected and used to disrupt the RNA-binding motif of EWS, which is required for EWS/FLI fusion. By blocking the RNA-binding motif of EWS, it might be possible to combat ES. Therefore, molecular docking experiments validated the binding interaction patterns and structural behaviors of screened flavonoid compounds within the active region of the Ewing sar...

International Journal of Molecular Sciences

To develop new alkaline phosphatase inhibitors (ALP), a series of pyrazolo-oxothiazolidine deriva... more To develop new alkaline phosphatase inhibitors (ALP), a series of pyrazolo-oxothiazolidine derivatives were synthesized and biologically assessed, and the results showed that all of the synthesized compounds significantly inhibited ALP. Specifically, compound 7g displayed the strongest inhibitory activity (IC50 = 0.045 ± 0.004 μM), which is 116-fold more active than monopotassium phosphate (IC50 = 5.242 ± 0.472 μM) as a standard reference. The most potent compound among the series (7g) was checked for its mode of binding with the enzyme and shown as non-competitively binding with the target enzyme. The antioxidant activity of these compounds was examined to investigate the radical scavenging effect. Moreover, the MTT assay method was performed to evaluate their toxic effects on the viability of MG-63 human osteosarcoma cells, and all compounds have no toxic effect on the cells at 4 μM. Computational research was also conducted to examine the binding affinity of the ligands with alka...

Nanocomposite Materials [Working Title]

Since the isolation and identification of graphene, the academic and industrial communities are u... more Since the isolation and identification of graphene, the academic and industrial communities are utilizing its superior properties. This minireview deals with the processing of graphene-based fillers/elastomer nanocomposites. The incorporation of graphene in an elastomeric matrices has significant effects on the properties of nanocomposites. The dispersion of graphene in elastomers is discussed. The processing of graphene/elastomer nanocomposites is discussed. The mechanical properties of the elastomeric matrix can be enhanced due to the presence of graphene. In this review and due to space limitations, we will present an example of improvements in the mechanical characteristics of graphene/styrene-butadiene (SBR) elastomer nanocomposites.

Distinguishing between harmful and benign genetic variations is fundamental to our understanding ... more Distinguishing between harmful and benign genetic variations is fundamental to our understanding of the relationship between genome and disease in general and for personalized medicine in particular. We investigated the relationship between predicted change in RASA and the phenotype of a missense mutation (MM). The ASAquick program was used to obtain RASA predictions for the original and mutated sequence and a parameter, δ , was introduced to assess the change in RASA for a given MM. We find that predicted RASA shows a robust, intricate signal with respect to genetic variation and that changes in RASA between variants can form a basis for a simple and quick predictor of the effect of MMs. Furthermore, we find that for hydrophobic residues, increase in the RASA corresponds to an increase in the likelihood that a MM would be harmful. For hydrophilic residues we find that a decrease in the RASA corresponds to a likelihood that a MM would be harmful. We also find that the size of the ch...

Vietnam Journal of Science and Technology, 2018

Recently single molecule force spectroscopy has become an useful tool to study protein, DNA and R... more Recently single molecule force spectroscopy has become an useful tool to study protein, DNA and RNA. However, very little attention was paid to homopolymer which plays an important role in many domains of science. In this paper we make the first attempt to decipher the free energy landscape of homopolymer using the external force as reaction coordinate. The impact of the quenched force on the free energy landscape was studied using simplified coarse-grain Go model. Similar to protein, we have obtained a clear switch from the thermal regime to force-driven regime. The distance between the denatured state and transition state in the temperature-driven regime is smaller than in the force-driven one. Having a rugged free energy landscape without a pronounced funnel the homopolymer folding is much slower than that of protein making study of homopolymer very time consuming.

Biophysical Journal, 2018

cardiac dysfunction. Here, we used structural and biophysical approaches to better understand the... more cardiac dysfunction. Here, we used structural and biophysical approaches to better understand the pathogenesis of a cardiac troponin C (cTnC) C84Y mutation located in the D/E linker, first reported in a 17-year-old proband, presenting with left-ventricular hypertrophy. Despite the relevance of HCM disease, little is known concerning the function of the D/E linker and allosteric phenomena governing cTnC Ca 2þ affinity. Monitored by bis-ANS fluorescence, Ca 2þ-titrations reveal that C84Y exhibits enhanced Ca 2þ-binding affinity in both domains and conformational changes compared to WT. Although WT and C84Y display distinct Ca 2þ-binding behaviors, the overall dimensional values and molecular envelopes generated by small-angle-X-ray scattering data remains similar. Using circular-dichroism, C84Y revealed significantly lower thermostability in non-Ca 2þ-bound form compared to WT. Most of our understanding of the molecular mechanisms underlying how troponin and troponin peptides switch muscle contraction ''on'' and ''off'' has been derived using experimental NMR techniques. Currently, no experimental techniques are available that allow the understanding of protein regulatory/dynamic processes at the molecular level of large, multi-domain protein complexes. To further unravel molecular changes in C84Y, three-dimensional NMR experiments were performed for backbone assignment. The largest chemical shifts were observed in N-Helix residues and at the end of D-helix and D/E linker. NMR-derived backbone amide temperature-coefficients indicate different temperature-dependent conformational changes exist between WT and C84Y Carr-Purcell-Meiboom-Gill relaxation dispersion (CPMG-RD) and R1/R2 experiments were used to probe the population and exchanging rates of C84Y compared to WT. This work sought to elucidate: main structural components underlying this pathological mutation, novel allosteric mechanisms, and the role of D/E linker in cTnC.

Methods in Molecular Biology, 2020

We have studied the ability of three types of neural networks to predict the closeness of a given... more We have studied the ability of three types of neural networks to predict the closeness of a given protein model to the native structure associated with its sequence. We show that a partial combination of the Levenberg-Marquardt algorithm and the back-propagation algorithm produced the best results, giving the lowest error and largest Pearson correlation coefficient. We also find, as previous studies, that adding associative memory to a neural network improves its performance. Additionally, we find that the hybrid method we propose was the most robust in the sense that other configurations of it experienced less decline in comparison to the other methods. We find that the hybrid networks also undergo more fluctuations on the path to convergence. We propose that these fluctuations allow for better sampling. Overall we find it may be beneficial to treat different parts of a neural network with varied computational approaches during optimization.

Several novel techniques have been combined to improve protein structure prediction, structural r... more Several novel techniques have been combined to improve protein structure prediction, structural refinement and quality assessment of protein models. We discuss in brief the development of four-body potentials that take into account dense packing and cooperativity of interactions of proteins, and its success. We have developed a method that uses whole protein information filtered through machine learning to score protein models based on their likeness to native structure. Here we consider electrostatic interactions and residue depth, and use these for structure prediction. These potentials were tested to be successful in CASP9 and CASP10. We have also developed a Quality Assessment technique, MQAPsingle, which is a quasi-single-model MQAP, by combining advantages of both “pure” single-model MQAPs and clustering MQAPs. This technique can be used in ranking and assessing the absolute global quality of single protein models. This model (Pawlowski-Kloczkowski) was ranked 3rd in Model Qua...

Scientific Reports, 2021

Proteins are tiny players involved in the activation and deactivation of multiple signaling casca... more Proteins are tiny players involved in the activation and deactivation of multiple signaling cascades through interactions in cells. The TNFR1 and MADD interact with each other and mediate downstream protein signaling pathways which cause neuronal cell death and Alzheimer’s disease. In the current study, a molecular docking approach was employed to explore the interactive behavior of TNFR1 and MADD proteins and their role in the activation of downstream signaling pathways. The computational sequential and structural conformational results revealed that Asp400, Arg58, Arg59 were common residues of TNFR1 and MADD which are involved in the activation of downstream signaling pathways. Aspartic acid in negatively charged residues is involved in the biosynthesis of protein. However, arginine is a positively charged residue with the potential to interact with oppositely charged amino acids. Furthermore, our molecular dynamic simulation results also ensured the stability of the backbone of T...

Frontiers in Molecular Biosciences, 2021

Two new computational approaches are described to aid in the design of new peptide-based drugs by... more Two new computational approaches are described to aid in the design of new peptide-based drugs by evaluating ensembles of protein structures from their dynamics and through the assessing of structures using empirical contact potential. These approaches build on the concept that conformational variability can aid in the binding process and, for disordered proteins, can even facilitate the binding of more diverse ligands. This latter consideration indicates that such a design process should be less restrictive so that multiple inhibitors might be effective. The example chosen here focuses on proteins/peptides that bind to hemagglutinin (HA) to block the large-scale conformational change for activation. Variability in the conformations is considered from sets of experimental structures, or as an alternative, from their simple computed dynamics; the set of designe peptides/small proteins from the David Baker lab designed to bind to hemagglutinin, is the large set considered and is asses...

Biophysical Journal, 2018

Entropy, 2019

Entropy should directly reflect the extent of disorder in proteins. By clustering structurally re... more Entropy should directly reflect the extent of disorder in proteins. By clustering structurally related proteins and studying the multiple-sequence-alignment of the sequences of these clusters, we were able to link between sequence, structure, and disorder information. We introduced several parameters as measures of fluctuations at a given MSA site and used these as representative of the sequence and structure entropy at that site. In general, we found a tendency for negative correlations between disorder and structure, and significant positive correlations between disorder and the fluctuations in the system. We also found evidence for residue-type conservation for those residues proximate to potentially disordered sites. Mutation at the disorder site itself appear to be allowed. In addition, we found positive correlation for disorder and accessible surface area, validating that disordered residues occur in exposed regions of proteins. Finally, we also found that fluctuations in the ...

The Journal of Chemical Physics, 2018

Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neuro... more Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Despite much progress in the understanding of the protein aggregation process, the factors governing fibril formation rates and fibril stability have not been fully understood. Using lattice models, we have shown that the fibril formation time is controlled by the kinetic stability of the fibril state but not by its energy. Having performed all-atom explicit solvent molecular dynamics simulations with the GROMOS43a1 force field for full-length amyloid beta peptides Aβ40 and Aβ42 and truncated peptides, we demonstrated that kinetic stability can be accessed via mechanical stability in such a way that the higher the mechanical stability or the kinetic stability, the faster the fibril formation. This result opens up a new way for predicting fibril formation rates based on mechanical stability that may be easily estimated by...

Biophysical Journal, 2019

Biophysical Journal, 2019

Protein-peptide interactions play essential roles in many cellular processes and their structural... more Protein-peptide interactions play essential roles in many cellular processes and their structural characterization is the major focus of current experimental and theoretical research. Two decades ago, it was proposed to employ the steered molecular dynamics to assess the strength of protein-peptide interactions 1. The idea behind using steered molecular dynamics simulations is that the mechanical stability can be used as an efficient alternative to computationally highly demanding estimation of binding affinity and aggregation rate 2,3. However, mechanical stability defined as a peak in force-extension profile depends on the choice of the pulling direction. Here we propose an uncommon choice of the pulling direction along resultant dipole moment vector, which has not been explored in simulations so far. Using explicit solvent all-atom MD simulations, we apply steered molecular dynamics technique to probe mechanical resistance of protein-peptide system pulled along two different vectors 4. A novel pulling direction, along the resultant dipole moment vector, results in stronger forces compared to commonly used peptide unbinding along center of masses vector. Our results demonstrate that resultant dipole moment is one of the factors influencing the mechanical stability of protein-peptide complex.

Journal of Biomolecular Structure and Dynamics, 2017

Disordered protein chains and segments are fast becoming a major pathway for our understanding of... more Disordered protein chains and segments are fast becoming a major pathway for our understanding of biological function, especially in more evolved species. However, the standard definition of disordered residues: the inability to constrain them in X-ray derived structures, is not easily applied to NMR derived structures. We carry out a statistical comparison between proteins whose structure was resolved using NMR and using X-ray protocols. We start by establishing a connection between these two protocols for obtaining protein structure. We find a close statistical correspondence between NMR and X-ray structures if fluctuations inherent to the NMR protocol are taken into account. Intuitively this tends to lend support to the validity of both NMR and X-ray protocols in deriving biomolecular models that correspond to in-vivo conditions. We then establish Lindemann-like parameters for NMR derived structures and examine what order/disorder cutoffs for these parameters are most consistent with X-ray data and how consistent are they. Finally, we find critical value of L = 4 for the best correspondence between X-ray and NMR derived order/disorder assignment, judged by maximizing the Matthews correlation, and a critical value L = 1.5 if a balance between false positive and false negative prediction is sought. We examine a few non-conforming cases, and examine the origin of the structure derived in X-ray. This study could help in assigning meaningful disorder from NMR experiments.

BMC Bioinformatics, 2016

Background: Sequence matching is extremely important for applications throughout biology, particu... more Background: Sequence matching is extremely important for applications throughout biology, particularly for discovering information such as functional and evolutionary relationships, and also for discriminating between unimportant and disease mutants. At present the functions of a large fraction of genes are unknown; improvements in sequence matching will improve gene annotations. Universal amino acid substitution matrices such as Blosum62 are used to measure sequence similarities and to identify distant homologues, regardless of the structure class. However, such single matrices do not take into account important structural information evident within the different topologies of proteins and treats substitutions within all protein folds identically. Others have suggested that the use of structural information can lead to significant improvements in sequence matching but this has not yet been very effective. Here we develop novel substitution matrices that include not only general sequence information but also have a topology specific component that is unique for each CATH topology. This novel feature of using a combination of sequence and structure information for each protein topology significantly improves the sequence matching scores for the sequence pairs tested. We have used a novel multi-structure alignment method for each homology level of CATH in order to extract topological information. Results: We obtain statistically significant improved sequence matching scores for 73 % of the alpha helical test cases. On average, 61 % of the test cases showed improvements in homology detection when structure information was incorporated into the substitution matrices. On average z-scores for homology detection are improved by more than 54 % for all cases, and some individual cases have z-scores more than twice those obtained using generic matrices. Our topology specific similarity matrices also outperform other traditional similarity matrices and single matrix based structure methods. When default amino acid substitution matrix in the Psi-blast algorithm is replaced by our structure-based matrices, the structure matching is significantly improved over conventional Psi-blast. It also outperforms results obtained for the corresponding HMM profiles generated for each topology. Conclusions: We show that by incorporating topology-specific structure information in addition to sequence information into specific amino acid substitution matrices, the sequence matching scores and homology detection are significantly improved. Our topology specific similarity matrices outperform other traditional similarity matrices, single matrix based structure methods, also show improvement over conventional Psi-blast and HMM profile based methods in sequence matching. The results support the discriminatory ability of the new amino acid similarity matrices to distinguish between distant homologs and structurally dissimilar pairs.

Physical Chemistry Chemical Physics, 2017

This paper explores how and why FVFLM peptides can be used as model systems to inhibit beta-amylo... more This paper explores how and why FVFLM peptides can be used as model systems to inhibit beta-amyloid aggregation.

Biophysical Journal, 2017

results identify large-scale structural burial of four key hydrophobic residues toward its C-term... more results identify large-scale structural burial of four key hydrophobic residues toward its C-terminal end and provide a molecular view of its dynamic structure-ensemble at the TMAO-induced folded state of this intrinsically disordered transactivation domain of ERa.