Papers by Andrzej Kloczkowski
Scientific Reports
Drug designing is high-priced and time taking process with low success rate. To overcome this obl... more Drug designing is high-priced and time taking process with low success rate. To overcome this obligation, computational drug repositioning technique is being promptly used to predict the possible therapeutic effects of FDA approved drugs against multiple diseases. In this computational study, protein modeling, shape-based screening, molecular docking, pharmacogenomics, and molecular dynamic simulation approaches have been utilized to retrieve the FDA approved drugs against AD. The predicted MADD protein structure was designed by homology modeling and characterized through different computational resources. Donepezil and galantamine were implanted as standard drugs and drugs were screened out based on structural similarities. Furthermore, these drugs were evaluated and based on binding energy (Kcal/mol) profiles against MADD through PyRx tool. Moreover, pharmacogenomics analysis showed good possible associations with AD mediated genes and confirmed through detail literature survey. T...
Polymer Solutions, Blends, and Interfaces
Abstract The materials being investigated are prepared by the following sequence of steps: (i) id... more Abstract The materials being investigated are prepared by the following sequence of steps: (i) identifying polymer chains of sufficient stiffness to give liquid-crystalline, anisotropic phases (either homopolymers, or block copolymers consisting of stiff and flexible sequences), (ii) cross linking the chains, in the presence of solvent, thus conferring sufficient solidity for the polymer to remain in a deformed state for any length of time, with the solvent preventing the premature ordering of the stiff chains or sequences, (iii) deforming the swollen network uniaxially or biaxially to induce segmental orientation, and (iv) removing the solvent, at constant length or at constant force, causing a first-order transition, and thus yielding a single-phase , homogeneous, and highly-ordered material. Although the cellulosics, starch derivatives and poly(γ-benzyl-L-glutamate) are of particular interest because of their biodegradability, experiments are also being carried out on Kevlar®, poly( n -alkyl isocyanates), poly(benzobisoxazoles), and poly(benzobisthiazoles). In the case of high-temperature polymers, this method would represent an alternative to high-temperature heat treatments, which have some disadvantages. In the case of less stable polymers, such as the cellulosics, it would be the only way to achieve this uniform ordering, and would thus represent a uniquely new processing technique.
A novel method is proposed for predicting protein secondary structure using data derived from kno... more A novel method is proposed for predicting protein secondary structure using data derived from knowledge based potentials and Neural Networks. Potential energies for amino acid sequences in proteins are calculated using protein structures. An Extreme Learning Machine classifier (ELM-PSO) is used to model and predict protein secondary structures. Classifier performance is maximized using the Particle Swarm Optimization algorithm. Preliminary results show improved results.
Biophysical Journal, 2010
IntechOpen eBooks, Nov 2, 2022
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.
Bioorganic & Medicinal Chemistry, May 1, 2023
Computers in Biology and Medicine, Oct 1, 2022
Journal of Molecular Modeling, Feb 27, 2019
We discuss the relationship between the problem of protein tertiary structure prediction from the... more We discuss the relationship between the problem of protein tertiary structure prediction from the amino acid sequence and the uncertainty analysis. The algorithm presented in this paper belongs to the category of decoy-based modeling, where different known protein models are used to establish a low dimensional space via Principal Component Analysis. The low dimensional space is utilized to perform an energy optimization via a family of very explorative Particle Swarm Optimizers to find the global minimum. The aim of this procedure is to get a representative sample of the nonlinear equivalent region, that is, protein models that have their energy lower than a certain energy bound. The posterior analysis of this family provides very valuable information about the backbone structure of the native conformation and its possible alternate states. This methodology has the advantage to be simple and fast and can help to the refinement of tertiary protein structure. We comprehensively illustrate the performance of our algorithm on one protein from the CASP-9 protein structure prediction experiment. We also provide a theoretical analysis of the energy landscape found in the tertiary structure protein inverse problem, explaining why model reduction techniques (principal component analysis in this case) serve to alleviate the ill-posed character of this high dimensional optimization problem. In addition, we expand the computational benchmark with a summary of other CASP-9 proteins in the Appendix.
BMC Bioinformatics, Aug 30, 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.
BMC Bioinformatics, Sep 13, 2016
Background: Protein secondary structure prediction (SSP) has been an area of intense research int... more Background: Protein secondary structure prediction (SSP) has been an area of intense research interest. Despite advances in recent methods conducted on large datasets, the estimated upper limit accuracy is yet to be reached. Since the predictions of SSP methods are applied as input to higher-level structure prediction pipelines, even small errors may have large perturbations in final models. Previous works relied on cross validation as an estimate of classifier accuracy. However, training on large numbers of protein chains compromises the classifier ability to generalize to new sequences. This prompts a novel approach to training and an investigation into the possible structural factors that lead to poor predictions. Here, a small group of 55 proteins termed the compact model is selected from the CB513 dataset using a heuristics-based approach. In a prior work, all sequences were represented as probability matrices of residues adopting each of Helix, Sheet and Coil states, based on energy calculations using the C-Alpha, C-Beta, Side-chain (CABS) algorithm. The functional relationship between the conformational energies computed with CABS force-field and residue states is approximated using a classifier termed the Fully Complex-valued Relaxation Network (FCRN). The FCRN is trained with the compact model proteins. Results: The performance of the compact model is compared with traditional cross-validated accuracies and blind-tested on a dataset of G Switch proteins, obtaining accuracies of ∼81 %. The model demonstrates better results when compared to several techniques in the literature. A comparative case study of the worst performing chain identifies hydrogen bond contacts that lead to Coil ↔ Sheet misclassifications. Overall, mispredicted Coil residues have a higher propensity to participate in backbone hydrogen bonding than correctly predicted Coils. Conclusions: The implications of these findings are: (i) the choice of training proteins is important in preserving the generalization of a classifier to predict new sequences accurately and (ii) SSP techniques sensitive in distinguishing between backbone hydrogen bonding and side-chain or water-mediated hydrogen bonding might be needed in the reduction of Coil ↔ Sheet misclassifications.
Physical Chemistry Chemical Physics, 2017
Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with prot... more Preeclampsia, a pregnancy-specific disorder, shares typical pathophysiological features with protein misfolding disorders including Alzheimer's disease. Characteristic for preeclampsia is the involvement of multiple proteins of which fragments of SERPINA1 and β-amyloid co-aggregate in urine and placenta of preeclamptic women. To explore the biophysical basis of this interaction, we investigated the multidimensional efficacy of the FVFLM sequence in SERPINA1, as a model inhibitory agent of β-amyloid aggregation. After studying the oligomerization of FVFLM peptides using all-atom molecular dynamics simulations with the GROMOS43a1 force field and explicit water, we report that FVFLM can aggregate and its aggregation is spontaneous with a remarkably faster rate than that recorded for KLVFF (aggregation "hot-spot" from β-amyloid). The fast kinetics of FVFLM aggregation was found to be driven primarily by core-like aromatic interactions originating from the anti-parallel orientation of complementarily uncharged strands. The conspicuously stable aggregation mechanism observed for FVFLM peptides is found not to conform to the popular 'dock-lock' scheme. We also found high propensity of FVFLM for KLVFF binding. When present, FVFLM disrupts the β-amyloid aggregation pathway and we propose that FVFLM-like peptides might be used to prevent the assembly of full-length Aβ or other proamyloidogenic peptides into amyloid fibrils
Biophysical Journal, 2013
Proceedings of the National Academy of Sciences of the United States of America, Dec 29, 2022
Lecture Notes in Computer Science, 2023
Lecture Notes in Computer Science, 2023
arXiv (Cornell University), Feb 27, 2018
Considering all the PDB annotated allosteric proteins (from ASD-AlloSteric Database) belonging to... more Considering all the PDB annotated allosteric proteins (from ASD-AlloSteric Database) belonging to four different classes (kinases, nuclear receptors, peptidases and transcription factors), this work has attempted to decipher certain consistent patterns present in the residues constituting the allosteric communication subsystem (ACSS). The thermal fluctuations of hydrophobic residues in ACSSs were found to be significantly higher than those present in the non-ACSS part of the same proteins, while polar residues showed the opposite trend. The basic residues and hydroxyl residues were found to be slightly more predominant than the acidic residues and amide residues in ACSSs, hydrophobic residues were found extremely frequently in kinase ACSSs. Despite having different sequences and different lengths of ACSS, they were found to be structurally quite similar to each other-suggesting a preferred structural template for communication. ACSS structures recorded low RMSD and high Akaike Information Criterion(AIC) scores among themselves. While the ACSS networks for all the groups of allosteric proteins showed low degree centrality and closeness centrality, the betweenness centrality magnitudes revealed nonuniform behavior. Though cliques and communities could be identified within the ACSS, maximal-common-subgraph considering all the ACSS could not be generated, primarily due to the diversity in the dataset. Barring one particular case, the entire ACSS for any class of allosteric proteins did not demonstrate "small world" behavior, though the sub-graphs of the ACSSs, in certain cases, were found to form small-world networks.
Biophysical Journal, Feb 1, 2020
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 dihedral angles at the original mutated residue and disorder are positively correlated while dihedral angle fluctuations in spatially proximal residues are negatively correlated with disorder. Our results seem to indicate permissible variability in the disordered site, but greater rigidity in the parts of the protein with which the disordered site interacts. This is another indication that disordered residues are involved in protein function.
Biophysical Journal, Feb 1, 2019
Biophysical Journal, Feb 1, 2016
Formation of transient encounter complexes during the early steps of protein binding is known to ... more Formation of transient encounter complexes during the early steps of protein binding is known to play an important role in the specific-complex formation by enhancing the association rate. The cellular medium is crowded with an
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Papers by Andrzej Kloczkowski