Peptide Combination Generator: a Tool for Generating Peptide Combinations

Ali, Naseem; Shamoon, Arzoo; Yadav, Neelesh; Sharma, Tanuj

doi:10.1021/acsomega.9b03848

Cited by 5 publications

(5 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the factoradic (with 8 components) of 2021 is (0, 1, 2, 0, 4, 4, 2, 0), the permutation (of size 8) of rank 2021 is (0, 3,6,7,1,5,4,2). To obtain this permutation, we read the factoradic from right to left, and extract iteratively from the list (0, 1, .…”

Section: Link Between the Factorial Number System And Permutationsmentioning

confidence: 99%

See 1 more Smart Citation

Lexicographic Unranking of Combinations Revisited

Genitrini¹,

Pépin²

2021

Algorithms

View full text Add to dashboard Cite

In the context of combinatorial sampling, the so-called “unranking method” can be seen as a link between a total order over the objects and an effective way to construct an object of given rank. The most classical order used in this context is the lexicographic order, which corresponds to the familiar word ordering in the dictionary. In this article, we propose a comparative study of four algorithms dedicated to the lexicographic unranking of combinations, including three algorithms that were introduced decades ago. We start the paper with the introduction of our new algorithm using a new strategy of computations based on the classical factorial numeral system (or factoradics). Then, we present, in a high level, the three other algorithms. For each case, we analyze its time complexity on average, within a uniform framework, and describe its strengths and weaknesses. For about 20 years, such algorithms have been implemented using big integer arithmetic rather than bounded integer arithmetic which makes the cost of computing some coefficients higher than previously stated. We propose improvements for all implementations, which take this fact into account, and we give a detailed complexity analysis, which is validated by an experimental analysis. Finally, we show that, even if the algorithms are based on different strategies, all are doing very similar computations. Lastly, we extend our approach to the unranking of other classical combinatorial objects such as families counted by multinomial coefficients and k-permutations.

show abstract

Section: Link Between the Factorial Number System And Permutationsmentioning

confidence: 99%

“…It is also used as a basic building block in scheduling problems [3], as well as, e.g., in software testing [4]. In other contexts, it appears as the core problem for the generation of complex structures: we can for example cite phylogenetics [5] and bioinformatics [6].…”

Section: Introductionmentioning

confidence: 99%

Lexicographic Unranking of Combinations Revisited

Genitrini¹,

Pépin²

2021

Algorithms

View full text Add to dashboard Cite

show abstract

“…In particular, the role of leucine and phenylalanine residues has been the subject of other studies involving therapeutic applications of peptides [53][54][55]. In line with this, Sahoo et al (2017) demonstrated that the substitution of leucine for phenylalanine significantly increases the toxic effect of cathelicidin-5 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18) against cancer and bacterial cells [56]. Studies have also demonstrated the interaction of these amino acid residues with biomembranes, which is strongly dependent on the specific membrane components [54,57].…”

Section: Discussionmentioning

confidence: 94%

“…In the last years, more than 7% of Food and Drug Administration-approved drugs are peptide-based entities [2]. Yet, the design and refinement of these active structures are highly challenging [3], and several prediction models and tools are being proposed and have been made available in recent years [4,5]. However, despite these bioinformatics and statistical advances, the isolation of peptides from natural sources, the identification by genomic and transcriptomic investigations, or the synthesis of molecular region mimics of target proteins remain useful both to discover new structures and to understand functional aspects that are crucial for the selection of more potent and selective molecules [6,7].…”

Section: Introductionmentioning

confidence: 99%

Lessons from a Single Amino Acid Substitution: Anticancer and Antibacterial Properties of Two Phospholipase A2-Derived Peptides

Almeida

Mendes

Lancellotti

et al. 2021

CIMB

View full text Add to dashboard Cite

The membrane-active nature of phospholipase A2-derived peptides makes them potential candidates for antineoplastic and antibacterial therapies. Two short 13-mer C-terminal fragments taken from snake venom Lys49-PLA2 toxins (p-AppK and p-Acl), differing by a leucine/phenylalanine substitution, were synthesized and their bioactivity was evaluated. Their capacity to interfere with the survival of Gram-positive and Gram-negative bacteria as well as with solid and liquid tumors was assessed in vitro. Toxicity to red blood cells was investigated via in silico and in vitro techniques. The mode of action was mainly studied by molecular dynamics simulations and membrane permeabilization assays. Briefly, both peptides have dual activity, i.e., they act against both bacteria, including multidrug-resistant strains and tumor cells. All tested bacteria were susceptible to both peptides, Pseudomonas aeruginosa being the most affected. RAMOS, K562, NB4, and CEM cells were the main leukemic targets of the peptides. In general, p-Acl showed more significant activity, suggesting that phenylalanine confers advantages to the antibacterial and antitumor mechanism, particularly for osteosarcoma lines (HOS and MG63). Peptide-based treatment increased the uptake of a DNA-intercalating dye by bacteria, suggesting membrane damage. Indeed, p-AppK and p-Acl did not disrupt erythrocyte membranes, in agreement with in silico predictions. The latter revealed that the peptides deform the membrane and increase its permeability by facilitating solvent penetration. This phenomenon is expected to catalyze the permeation of solutes that otherwise could not cross the hydrophobic membrane core. In conclusion, the present study highlights the role of a single amino acid substitution present in natural sequences towards the development of dual-action agents. In other words, dissecting and fine-tuning biomembrane remodeling proteins, such as snake venom phospholipase A2 isoforms, is again demonstrated as a valuable source of therapeutic peptides.

show abstract

“…PepCoGen is also a free web server for generating peptides with a specific physicochemical profile [ 48 ]. In particular, the server generates all possible combinations of peptides by modifying the amino acids having a comparable physicochemical property profile at a given position.…”

Section: Open Resources To Expand and Describe The Chemical Spacementioning

confidence: 99%

Progress on open chemoinformatic tools for expanding and exploring the chemical space

Medina-Franco

Sánchez-Cruz

López-López

et al. 2021

J Comput Aided Mol Des

View full text Add to dashboard Cite

The concept of chemical space is a cornerstone in chemoinformatics, and it has broad conceptual and practical applicability in many areas of chemistry, including drug design and discovery. One of the most considerable impacts is in the study of structure–property relationships where the property can be a biological activity or any other characteristic of interest to a particular chemistry discipline. The chemical space is highly dependent on the molecular representation that is also a cornerstone concept in computational chemistry. Herein, we discuss the recent progress on chemoinformatic tools developed to expand and characterize the chemical space of compound data sets using different types of molecular representations, generate visual representations of such spaces, and explore structure–property relationships in the context of chemical spaces. We emphasize the development of methods and freely available tools focusing on drug discovery applications. We also comment on the general advantages and shortcomings of using freely available and easy-to-use tools and discuss the value of using such open resources for research, education, and scientific dissemination.

show abstract

Peptide Combination Generator: a Tool for Generating Peptide Combinations

Cited by 5 publications

References 28 publications

Lexicographic Unranking of Combinations Revisited

Lexicographic Unranking of Combinations Revisited

Lessons from a Single Amino Acid Substitution: Anticancer and Antibacterial Properties of Two Phospholipase A2-Derived Peptides

Progress on open chemoinformatic tools for expanding and exploring the chemical space

Contact Info

Product

Resources

About