Mini Review - Pharmaceutical Bioprocessing (2023) Volume 11, Issue 3

Pharmaceutical Formulation Based on Disintegrate Particle Breakdown

Chris Jordan*

Department of Pharmaceutics, University of Dundee, Scotland

*Corresponding Author:
Chris Jordan
Department of Pharmaceutics, University of Dundee, Scotland
E-mail: chrisjor@edu.co.in

Received: 02-May-2023, Manuscript No. FMBP-23-99910; Editor assigned: 04-May-2023, PreQC No. FMBP-23-99910 (PQ); Reviewed: 18-May-2023, QC No FMBP-23-99910; Revised: 23-May-2023, Manuscript No. FMBP-23-99910 (R); Published: 30-May-2023, DOI: 10.37532/2048- 9145.2023.11(3).59-61

Abstract

The breakdown of tiny molecules into fragments is a regular step in the drug design process. There are numerous strategies and techniques for dissolving molecules into smaller pieces. In this work, we introduce a novel straightforward method for the decomposition of molecules called MedChemFrag. This method enables the decomposition of molecules into non-overlapping pieces and is significant in terms of medicinal chemistry. It tries to disassemble drug-like compounds into a collection of rings and linkers that are similar to what medical chemists refer to as “fragments.” Our technique seeks to maintain the functional groups, which may reveal the specific interaction pattern, such as the amide groups, in contrast to most other attempts that sought to break molecules using retrosynthetic viable rules [1].

Keywords

Drug design • Molecules decomposition • Chemo-informatics

Introduction

Breaking small molecules into fragments is a common task in drug development. One area where this task has gained widespread popularity is fragment-based drug discovery (FBDD), which has gained considerable momentum in the last few decades.

Similar requirements arise in our recently proposed reverse fragment-based drug discovery (R-FBDD). R-FBDD proposes a simple and useful method that uses a scoring function to derive the contribution of a specific fragment to the interaction energy of the ligand as a whole and its target. Note that this approach itself is not limited to any particular ligand removal scheme and the utility of this approach has been demonstrated using manual ligand removal. However, to optimize the cheminformatics application of the R-FBDD approach, it is more convenient to combine the analysis provided by R-FBDD with an automated method to split the ligand into fragments. We initially decided to use one of the existing methods for breaking organic molecules into fragments. To achieve this objective, a number of requirements were imposed on the anticipated breakdown plan. First, fragments should not overlap, as it is important to assign more or less unambiguously the contribution of individual fragments to the binding energy. If the fragments overlap, additional work will be required to study the contribution of each part of the ligand. The second requirement, though partly intuitive, is the ability to use the resulting fragments naturally in medicinal chemistry practice, based on frequently shared and enduring perceptions in the medicinal chemist community. This requirement is not easily captured by a rigorous definition, but it is certainly relevant when interpreting the results obtained in terms of actionable insight. This means that medicinal chemists usually have to agree with the dissection in terms of the importance and novelty (in terms of intellectual property) of the resulting fragment. The importance of ligand fragment contributions is known to differ, and this difference in particular underlies his FBDD approach itself, which (despite the low absolute value) needs to form the first hit interaction energies, energetically dense interactions characterized by different ligand efficiency indices. Efficient interactions are only possible when the majority of ligands make complementary interactions with the receptor. Different fragments provoke different types of intermolecular interactions, which have proven useful in numerous drug discovery practices and have yielded theoretically relevant physicochemical interpretations [2-4]. For example, units containing amide bonds can act as hydrogen bond donors, hydrogen bond acceptors and as planar conjugated systems that can interact with aromatic systems known as ‘amide stacking’. The phenyl moiety is involved in both hydrophobic interactions and π-π stacking. In drug design, the pharmacophore concept is used to create spatial models in which the mutual arrangement of features responsible for specific favorable interactions is directly related to ligand activity. From the pharmacophore point of view, the nitrogen atoms of amines, aromatic amines and amide fragments are different atoms. Therefore, from a practical point of view, functional groups were added that reflect the most important contributions of neighboring atoms (such as conjugation), and the resulting fragments formed appropriately capturing the most important kinds of intermolecular interactions. You will be able to require a set of equipped fragments between each fragment of the entire ligand and the receptor. We think that from the perspective of medicinal chemistry, fragments having the aforementioned characteristics will be significant. The next thing was to determine whether or not the programmes and procedures already in use satisfied the criteria I had established for the final segment [5-8].

Materials and Methods

Implementation of decomposition

The SMARTS expressions used to implement the rules of molecular fragmentation. A script was created for the decomposition using Python3 and the RDKit module. The supporting information explains how to use the script. It is possible to download the script. The original set of rules offered (v. 1.0) can readily be expanded to accommodate a wider range of organic chemicals and molecules that are similar to drugs. It will then be expanded by looking at more breakdowns of pertinent drug-like ligands.

Algorithm

The following is implemented by the script: SMARTS finds fragment-containing atoms first. The atom pairs in the discovered fragments that have bonds that must be broken are indicated for further bond breaking. Second, using the RDKit library method Fragment On Bonds, the ligand is broken into fragments by severing the bonds established by the atom pairs. Fragments are presented on top of the entire ligand structure in an image or written to files with hydrogen atom caps.

Discussion

This is consistent with the concept of fragmentlike compounds, as most fragments contain up to 15 atoms and have molecular weights below 300 Da. Most molecules were degraded into a significant number of fragments, up to 5. This figure could be rationalized by considering drug research practices. First, dealing with large numbers of fragments is difficult and tedious. Second, in the fragment approach, the structure is continuously extended with several iterations by adding new fragments to the drug, but usually the number of iterations rarely exceeds. Large fragments with masses up to 300 Da (of medical and chemical importance) and 2-3 smaller fragments containing linkers. Be expected. In summary, the molecular weights of these fragments should meet the requirements of modern pharmaceuticals. Therefore, a maximum of 5 explicit fragments in the structure is considered reasonable [9].

Note that applying the third rule may violate the basic principle in some cases. When applying the breakdown rules, we found a structure where the application of the rules is not clear. Conventionally, single-atom or multi-atom fragments with broken conjugate bonds are obtained. Examples of such violations are the presence of small linkers such as ether oxygen atoms (single atom fragments) or diazo fragments between two aromatic ring systems. Since we cannot unambiguously decide which ring to leave in the fragment, we chose to break both bonds. According to decomposition requirements, the resulting fragments must make sense and must not overlap. Given the fact that it is practically impossible to establish a priori the relative preference rules for such intercooled systems, we deviate from the principle and in such cases all these couplings we decided to split the molecule along. This decision helps to completely avoid such uncertainties in molecular decomposition. In this case, the covalent bond is broken to eliminate ambiguity, leaving it up to the medicinal chemist to decide which fragment remains at the end. There may be several such fragments in the structure, thus increasing the number of possible variants of the set of fragments. Thus, the disruption of connectivity in such cases is offset by the increased convenience and flexibility of fragment dissection, which is becoming increasingly popular [10].

Conclusion

In this study, we formulated the requirements of a method for cleaving molecules into fragments. This may be relevant in terms of the type of intermolecular interactions these fragments can form at the target binding site. An analysis performed on the existing distribution methods found them to be unsatisfactory due to the different objectives on which these methods are based. In general, existing methods can retro synthetically cleave specific monolithic fragments or generate sets of overlapping fragments. For this reason, we proposed a new method, MedChemFrag, to split molecules into fragments that better meet the above requirements.

The method of splitting the ligand into fragments makes it possible to obtain nonoverlapping fragments while preserving their steric and electronic features. This is because it is important when interpreting interactions from a medicinal chemistry perspective. This method was tested and showed major differences from existing decomposition methods. We believe that this method has broad applications in chemo informatics.

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