Therapeutic Inhibitors: Natural Product Options through Computer-Aided Drug Design

Abstract

Drug repurposing involves reusing an active pharmaceutical ingredient that is already in the market and drugs that were unsuccessful in their clinical phases of development for a new indication. It has numerous benefits in drug development. Therapeutic inhibitors are agents that could be of synthetic or natural source with the ability to trigger the down-regulation of an enzyme or protein, thereby inducing therapeutic effect(s). Researchers have embraced synthetic methods in searching for therapeutic molecules through structural activity relationships and other means in the past and recent times. Despite these synthetic drugs, the morbidity and mortality rate of ailment and disease affecting humanity remains overwhelming. Research has shown that solutions to these challenges can be attempted through drug repurposing. In the past, natural products in raw forms have been utilized in traditional, complementary medicine to manage and treat diseases and illnesses, as there are molecules in use today as drugs, which originated from plants and other natural sources. Studies on natural products have led to diverse natural product databases that can serve as a source of repurposing agents. There are also databases for protein and enzymes of human origin, which have an enormous role in the in-silico drug repurposing approach.

1. Introduction

Repurposing of a drug is the process of reutilizing already utilized drugs for other treatment purposes. It is the use of a known drug for treating conditions other than their primary use [1]. Drug repurposing encourages disease-related drug development in a much cheaper, faster, and more accessible way for patients [2]. The drug studied for repurposing is the shelved drugs, drugs in use, discontinued drugs, and experimental drugs that either could not make it to the late phases of clinical trials or have failed in the market. Because the efficacy, safety, and toxicity of these drugs have already been established, the preliminary phases of the clinical trials can be omitted, minimizing the cost and length of the clinical trials. It takes about 15 years to deliver a new drug to the market [3]. The objective of drug repurposing is to identify new biological targets and different therapeutic uses of previously approved and/or investigational drugs, including drugs that did not meet primary therapeutic expectations. As such, a number of pre-clinical development and optimization issues, including negative toxicological profiles, can be avoided or at least minimized. Although most successful experiments in reallocating drugs are derived from coincidence, current research efforts focus on predicting opportunities for reallocating on rational grounds [4]. Interestingly, while most drug reallocation campaigns rely on chemical-based compounds, natural products can offer important opportunities. Natural products are characterized by unique and favorable properties, considerable structural diversity, and a large number of pharmacological activities [5]. Therefore, these are chemical entities preferred for the (re)discovery of medicines. Strategies that may bring to light new therapeutic uses that may not be related to their original biological space [6].

In the drug repurposing process, there are three important processes that are involved. They include (i) identification of the targets of interest for a new indication, (ii) assessment of mode of action intricate in drug or ailment of study, and (iii) establishment of the drug the usefulness in the second and third phases of a clinical trial. Of all the stages, finding a principal candidate is one of the most important. This is the stage where the most advanced and efficient techniques are required to be involved in generating new hypotheses in the reallocation of drugs. Drugs can be repurposed in multiple ways, which may be either experimentally, clinical-based, or computationally. The computational approach is an “in-silico” repurposing of drugs, which is divided into two sub-categories: centered drugs or diseases. Under the drug-based approach, we find new indications for existing drugs, while under the disease-based approach, we try new drugs for an existing disease (Figure 1) [7].

Figure 1.

Drug repurposing approaches.

Recently, natural products have seen a revival of awareness in drug discovery, with a different approach. Newer and evolving technologies, such as computational screening, proteomics, metabolomics and big data analysis, have come to the fore to drive and speed up the “repurposing” of natural compounds and, more generally speaking, of nature-inspired compounds [8].

Even though a large number of natural product formulations are available as extracts, the phytocompounds components of these extracts can be utilized in drug repurposing, with the utilization of Computer-Aided Drug Design, after isolation, purification, and structural elucidation.

Approaches for Speeding Up Drug Repurposing

• In-silico models—In-silico or bioinformatic models help to identify complex relationships between drugs, targets, and diseases necessary for reuse [9].

• Target Linkage—The use of high-throughput assessment technological skills to identify multipharmacological molecules that affect numerous targets can remedy multifactorial ailments such as cancer and diseases of neurodegeneration [10].

• Artificial Intelligence (AI)—AI makes records more accessible. Broad literature mining to identify possible drug interactions, adversarial effects, mode of actions, regulations of a gene can help accelerate the development of medicines [11]. The side effect of the medicine may be utilized to treat another condition. If the medications have the same adverse reactions, then they can work on the same disease [2].

Therapeutic inhibitors are agents, compounds that could be of synthetic or natural source, with the ability to trigger the down-regulation or block the expression or overexpression of an enzyme or protein, or block protein-protein interactions or block the addition of phosphates to other molecules, thereby inducing therapeutic effect(s). Therapeutic inhibitors perform their functions either directly or indirectly by affecting the catalytic properties of the active site. Inhibitors can be extraneous to the cell or normal constituents of it. Inhibitors which are a normal component of a cell, can represent a significant component of the regulation of cell metabolism. Many toxins and also pharmacologically active agents (both illegal drugs and prescription and over-the-counter medicines) act by inhibiting specific enzyme-catalyzed processes [12], which can be targeted in-silico using computer-aided drug design in the process of new therapeutic inhibitor development from natural products. There are thousands of natural products existing in natural product databases that can be utilized for this purpose. The protein and enzyme target are also readily available in protein databases in formats needed for computer simulation studies [13].

2. Classifications of therapeutic inhibitors

Based on the current mechanisms of action of already existing drugs, therapeutic inhibitors can be classified into

1. Enzyme inhibitors

2. Protease inhibitors

3. Kinase inhibitors

4. Protein synthesis inhibitors

5. Protein-protein interactions inhibitors (Figure 2).

Figure 2.

Therapeutic inhibitors.

2.1 Enzyme inhibitors

Enzyme inhibitors are compounds that interact with enzymes (either temporarily or permanently) in some way and minimize the rate of an enzyme-catalyzed reaction or stop enzymes from working in a normal manner [13]. In therapeutic, enzyme inhibitors bind to enzymes and lower their activity [14] and achieve a therapeutic benefit. Some molecules are used as drugs today because of their ability to cause correction of metabolic imbalance, the correction which is due to the effectiveness of the molecules in causing blockage of enzyme activity. Therefore, the search and discovery of molecules with inhibitory enzyme ability is an active area of research in biochemistry and pharmacology [14]. It is noteworthy to state that not all molecules that bind to enzymes are inhibitors; some could be enzyme activators; in this case, the molecules bind to enzymes and elevate their enzymatic activity [15], which can also cause therapeutic benefit. The binding of inhibitors to enzymes can either be reversible or irreversible.

A molecule is a reversible inhibitor if it binds non-covalently to the enzyme’s active site to produce an inhibition. The binding could be direct with the enzyme, the enzyme-substrate complex, or both [15].

A reversible inhibitor is described as one that, once removed from the enzyme, the enzyme returns to its normal function pre-inhibition. It exerts no permanent effects on the enzyme and does not change the shape of the active site of the enzyme [16]. There are different types of reversible inhibition. They include competitive, non-competitive and uncompetitive types, although a mixed type sometimes arises [15].

The underlying principle of competitive inhibition is that, at a single active or binding site of a drug-metabolizing enzyme, there is the mutually exclusive binding of either the substrate or the inhibitor [17]. Competitive enzyme inhibitors possess a comparable shape to that of the substrate molecule. These two drugs compete for binding to a single active site of an enzyme. Substrates are compounds or molecules upon which enzymes act. The interaction of a substrate and an enzyme occurs at the active site of the enzyme or in a binding site that can, in turn, alter the active site. This brings about competition for binding/active sites between a substrate and an inhibitor.

The second type of reversible inhibition, non-competitive reversible inhibition, utilizes inhibitors that do not have similarity with the substrate and so do not bind to the active site but rather to a separate site on the enzyme. The outcome of an interaction of a non-competitive inhibitor with an enzyme appreciably differs from an interaction with a competitive inhibitor due to the non-existence of antagonism. In the case of an antagonistic inhibition, the inhibitory effect could be minimized and subsequently overcome with escalating concentrations of substrate. With non-competitive inhibition, growing the quantity of substrate does not affect the percentage of an enzyme that is active. Indeed, in non-competitive inhibition, the percentage of enzyme inhibited remains the same through all ranges of a substrate. The implication of this is that non-competitive inhibition will efficiently diminish the concentration of enzyme by equal, fixed concentration in a typical experiment at every substrate concentration used [18].

The third type of reversible inhibition, uncompetitive reversible inhibition, utilizes inhibitors that bind to the already formed enzyme-substrate complex and not to the free enzyme. In this type of reversible inhibition, the interaction of the substrate with an enzyme could trigger a conformational modification that leads to the revelation of an inhibitor binding site on the enzyme, or the inhibitor could bind and interact directly to the enzyme-bound substrate. The underlining outcome in this type of reversible inhibition is that it does not compete with the substrate for the same active site in either case and so the increasing concentration of substrate cannot overcome the effect of the inhibitor [19].

As opposed to reversible inhibition, there is irreversible inhibition. In irreversible inhibition, the inhibitor no longer separates from the enzyme after binding and interaction and the enzyme reaction is reduced. The reduction rate is dependent on the enzyme and inhibitor concentrations only and independent of the concentration of the substrate. This implies one inhibitor molecule can ideally minimize to zero the activity of one enzyme molecule [20]. Irreversible inhibition could be of two forms. The first occurs when an inhibitor is strongly bound and complex with an enzyme and fail to dissociate under physiological conditions from the enzyme. There are two types of irreversible inhibitors. The first type is so strongly complexed to the enzyme that it fails to dissociate from the enzyme under physiological conditions but can be dissociated through the method of dialysis or by chromatographic techniques [20]. The second type of irreversible inhibition is one in which the inhibitor forms a covalent bond with the enzyme; in a situation whereby the formation of the covalent bond terminates the conversion of substrate to product, then the enzyme has been irreversibly terminated. The irreversible inhibitors that function through the formation of covalent bonds are of two main types. The first type involves the reaction of an inhibitor with an essential functional group by a bimolecular process on the enzyme [21]. The biomolecular process is a reaction that involves the combination of two molecular entities. In the second type of irreversible inhibition that occurs through the formation of a covalent bond, the inhibitor which bears a leaving group forms a reversible complex with an enzyme. As this occurs, the presence of a nucleophilic group on the enzyme of the leaving group, juxtaposed within the reversible enzyme-inhibitor complex formed on the enzyme of the leaving group, could lead to a rapid neighboring group reaction within the complex in which a covalent bond is formed. Such formation of a covalent bond can be highly specific since properly positioned neighboring groups can react more rapidly than the identical bimolecular reaction [21]. A leaving group is an atom or group of atoms that dissociates from the rest of the molecule, taking with it the electron pair, which was previously the bond between the leaving group and the rest of the molecule.

2.2 Kinase inhibitors

Kinase is a type of enzyme that acts to add phosphates to other molecules, such as sugars or proteins. The addition of phosphate may cause other molecules in a cell or system to become either active, overactive, or inactive. Kinases facilitate the transmission of a phosphate moiety from a high-energy molecule to its substrate molecule. Kinases are widely utilized to convey signs and control multifaceted procedures in cells. Phosphorylation of compounds can boost or impede their effectiveness and regulate their capability to interrelate with other compounds. The presence and absence of phosphoryl groups offer the cell a means of control because various kinases can react to diverse situations or signals. There are 518 kinases encoded in the human genome are 518 kinases. These kinases are known to phosphorylate about one-third of the proteome [22, 23]. Nearly all signal transduction route occurs through a phosphotransfer process. This indicates that kinases offer several nodes for therapeutic mediation in numerous abnormally controlled biological processes [24]. Kinase function deregulation has been shown to perform an essential role in cancer immunological, inflammatory, degenerative, metabolic, cardiovascular and infectious diseases [25, 26].

Kinases are of three main categories depending on the substrate type of kinase: protein kinase, lipid kinase, carbohydrate kinase. Protein and lipid kinases represent one of the most important target classes for treating human disorders after G-protein-coupled receptors (GPCRs) and proteases. As a matter of fact, one-third of the protein targets currently undergoing investigation by pharmaceutical companies consist of protein or lipid kinases [27].

Kinase inhibitors are molecules with the ability to alter the activities of kinases. The recognized druggability and the therapeutic safety profile of standard kinase inhibitors make kinases attractive targets for drug development. Nevertheless, there are many kinases yet to be studied effectively; this shows that the discovery of kinase inhibitors is still the majority of kinases that have been historically understudied, indicating that the field of kinase inhibitor discovery is still not fully harnessed [28, 29, 30]. There are some significant challenges in drug discovery as regard kinase inhibitors. These challenges are obstacles to the full potential of kinases as drug targets. The challenges include validating novel kinase targets, utilization of kinase inhibitors in non-oncology therapeutic areas, overcoming drug resistance, obtaining target selectivity to minimize off-target-mediated toxicity and to develop effective compound screening and profiling technologies [31]. Nevertheless, some progress has been made in towards overcoming these challenges, and also research in the field of kinase inhibitors have Over the course of the past 5 years, immense progress has been made towards these goals, and also studies the field of kinase inhibitor discovery is expanding rapidly in oncology and into different disease areas, including autoimmune and inflammatory disease as well as degenerative disorders.

The estimated current spending in research and development by pharmaceutical companies towards the development of new kinase inhibitors is about 30%. In all these, one of the most important classes of drugs targeted by pharmaceutical industrial researchers is protein kinases. To date, 89 drugs targeting protein kinases have clinically received approval. It is estimated that the current global market for kinase therapies is about US$20 billion per annum, projection to rise distinctly. Over 100 active small-molecule kinase inhibitors are currently in an advanced stage of clinical development, and many more are expected to be approved in the years ahead [32].

2.3 Protease inhibitors

Proteases, which are also known as proteinases or proteolytic enzymes, are a large class of enzymes that catalyzes the hydrolysis of peptide bonds in proteins and polypeptides. Proteases control the fortune, localization, and numerous protein actions. Proteases are important aspects in the well-being and viability of cells, participating in several procedures, such as replication, transcription, cell multiplication, differentiation, extracellular matrix remodeling, and processing of hormones and biologically active peptides. Proteases are greatly controlled (e.g. transcriptionally, post-translationally, stimulated, inhibited, and classified) [33]. Protease action has been found to play a role in the pathogenesis of vascular diseases, including atherosclerosis, thrombosis, and aneurysm. Broad diversity of proteases representing various proteolytic groups and their corresponding inhibitors are involved. These proteases play a role(s) vascular ailment through a sequence of overlapping pathways that upset the overall inflammatory status and structural integrity of the vessel wall. By triggering PARs (protease-activated receptors), these enzymes cause inflammatory signaling, cytokine production, and inflammatory cell recruitment. Furthermore, proteases can destroy components of the extracellular matrix (ECM), elastic lamina, and fibrous cap in the atheroma. The fundamental paradigm is that excessive proteolytic action is an important contributor to the start and progression of vascular disease. Recent approaches to the treatment of vascular pathologies have attempted to modulate protease activity in an effort to reduce inflammation and preserve the structural integrity of the vessel wall [34]. Proteases can be divided into six broad classes based on proteolytic mechanism: serine proteases, threonine proteases, cysteine proteases, aspartic proteases, metalloproteases, and glutamic acid proteases.

Protease inhibitors are synthetic drugs that prevent the activity of HIV-1 protease, an enzyme that cleaves two precursor proteins into smaller fragments. These fragments are essential for viral growth, infectivity, and replication. It is important to mention that proteases are not limited to HIV. Protease inhibitors interact with protease at the active site, thereby thwarting the growth and development of the freshly formed virions; this makes them stay non-infectious. Protease inhibitors are utilized in taking care of individuals with human immunodeficiency virus (HIV infection) and acquired immune deficiency syndrome (AIDS) [35]. Also, protease inhibitors are useful medically as angiotensin-converting enzyme inhibitors for blood pressure, proteasome inhibitors for myeloma, dipeptidyl peptidase IV inhibitors for type II diabetes [33]. Currently, there are many studies in progress targeting SAR-COV-2 main protease (Mpro) [36, 37, 38, 39, 40, 41]. Mpro, also termed 3CL protease, is a 33.8 kDa cysteine protease that mediates the maturation of functional polypeptides involved in the assembly of replication-transcription machinery [42]. Due to the significant role of this main protease, it is considered a promising drug target, as it is dissimilar to human proteases.

2.4 Protein synthesis inhibitors

The process of making a protein molecule using DNA, RNA, and various enzymes by cells is termed protein synthesis. In biological systems, it takes place inside the cell and involves amino acid synthesis, transcription, translation, and post-translational events. It takes place in the cytoplasm of prokaryotes, while in eukaryotes, it takes place usually in the nucleus and aids the generation of a transcript (mRNA) of the coding region of the DNA. The transcript departs the nucleus and gets to the ribosomes, where translation into a protein molecule takes place with a specific sequence of amino acids [43].

A protein synthesis inhibitor is a molecule with the ability to terminate or reduce the growth rate of cells by interrupting the progressions that directly leads to the production of new proteins [44]. Even though a wide description of this definition could be utilized in closely describing any compound depending on the amount present, in reality, it classically denotes compounds that exert their molecular effect level on translational machinery. Protein synthesis inhibitors are another major group of therapeutically useful antibacterials, such as erythromycin, tetracycline, chloramphenicol, and aminoglycosides. They specifically interact with the 70S bacterial ribosome and spare the 80S eukaryotic ribosome particle. Macrolide, lincosamide, and streptogramins (MLS) antibiotics represent three classes of structurally diverse protein biosynthesis inhibitors used clinically [45]. Generally, protein synthesis inhibitors work at different stages of bacterial mRNA translation into proteins, like initiation, elongation (including aminoacyl tRNA entry, proofreading, peptidyl transfer, and bacterial translocation) and termination.

2.5 Protein-protein interactions inhibitors

The protein-protein interaction (PPI) can be described as a substantial network linking a protein and its partner(s) [46, 47, 48]. These networks may exhibit a variety of heterogeneities and complexities in large molecular structures, leading to the formation of protein dimers, multi-constituent complexes, or lengthy chains [49]. The contact between subunits of protein can be transitory or constant, similar or dissimilar, and precise or imprecise [48, 50, 51]. There are closely 650,000 protein-protein interactions in humans, and this figure keeps on increasing as additional interaction networks are being discovered [48, 52]. Protein-protein interactions (PPIs) play pivotal roles in biological processes [53]. Mutations or compromised regulation of PPIs affect cellular networks and have a role to play in the development of diseases. The discovery and development of new PPI inhibitors with the intention to control abnormal pathways have therefore aroused substantial interest from the pharmaceutical industry [54]. Almost half of the dry mass of a cell is composed of proteins, and disorder in PPIs often causes diseases, including cancer [55, 56]. Hence, research and studies on PPI play a vital role in advancing our understanding of molecular biology and human diseases, as well as for developing new therapeutic agents in drug discovery [51, 57, 58].

Generally, protein-protein interactions were used to being seen as a non-druggable target. This standing is likely due to the lack of or limited knowledge on high-throughput assessment assays, as well as the consideration that most protein-protein interactions are held to by big, chemically noncomplex surfaces with a deficiency of easily druggable pockets [59]. While such tough protein-protein interaction targets indisputably exist, it is now understood that many protein-protein interactions use minimal interfaces for their interaction, regularly consisting of an unstructured peptide bound to a distinct groove [54]. Additionally, mutagenesis analyses of numerous PPIs have shown that surfaces causing the affinity of a given PPI are not steadily spread across the whole interface. Rather, there tends to be a “hot spot” or a small number of important residues that anchor two proteins together [60]. This implies that a putative inhibitor would not need to dislodge the entirety of a given PPI but rather only occupy the hot spot, a more tractable problem.

Currently, researches in the area of SARS-COV-2 also include inhibition of Spike-ACE2 interaction, which is a protein-protein interaction [61, 62].

3. Natural products option

Plants as a source of medicine Nature, as old as mans’ existence, have been a provider of medicines and agents used for the development of medicine. There are other natural sources of medicinal products like marine, but the most prevalent source is a plant [63]. An enormous number of the medications in use today was obtained from a plant. Some medications in use also were developed from a compound originally gotten from a plant. The development of most of these medicines gotten from a plant started from the study of the utilization of the plant in traditional medicinal practice, which gave an insight into the type of pharmacological property or likely pharmacological effect for which the molecules from plants could be developed for.

The system of traditional medicinal practice keeps on being a very indispensable target in the world’s healthcare system because of the dependence of the 80% of the world population on traditional medicinal practice system for their elementary healthcare needs, according to World Health Organization. The remaining 20% of the population who are residents of developed countries also use plant products for healthcare needs or substances developed from plant products [64]. Research has it that between 1959 and 1980 in the United States that about 25% of the dispensed prescription drugs from community pharmacies were products of plant extracts or contained active ingredients obtained from higher plants [65].

Currently in use as medications are at least 119 chemical entities obtained from 90 different plant species. Of all these 119 drug entities, 74% were obtained from plants through direct isolation of active substances from plants that are already in use in traditional medicinal practice systems [66]. It is on record that in all sales made by the leading pharmaceutical industries in the year 1991, most of the sales were made on products derived from natural sources or containing a substance or substances that are natural product-based [67]. It is also on record that in 1993, a total of 57% of the top 150 brand-name products that were prescribed had at least one major active compound from a natural source or derived from a natural source or patterned after substances reflecting biological diversity [68].

Many researchers have taken an interest in discussing and accessing different medicinal plants as a reservoir for new therapeutic agents [63], and some others have persuasively converged their research on the use of specific chemical classes like flavonoids, alkaloids, glycosides, etc. in drug discovery. Recent research has continued to demonstrate and validate the ethnomedicinal drug discovery approach to the initial discovery approaches of pharmaceuticals [69]. Still, some other researchers have estimated that out of about 375 total compounds of pharmaceutical importance in the rain forests, only about one-eight have been explored. Assessing and observing the roles these natural product base medications have played in humanity, there are possibilities that more efficient ones are still in the forest unexplored [70].

This forms the basis for the need for more exploration and research on traditional medicinal plants for the emerging healthcare challenges of humans. Researchers in the field of medicinal plants are no longer only interested in testing plant extracts for pharmacological activities but are also undertaking the isolation of molecules from plant extracts and identifying these molecules. Some has gone further to establish the pharmacological effect of these isolated molecules. For example, in previous research on Vernonia amygdalina, we were able to establish the antidiabetic and antihelminthic effectiveness of methanolic extract Vernonia amygdalina [71, 72], and we went further to isolate six pure molecules from the methanolic extract [73] and then tested the isolated molecules for the antidiabetic and antihelminthic property. From the study, we were able to identify the molecules responsible for the antidiabetic and antihelminthic effects observed in the extract [74].

Likewise, there are thousands of isolated molecules from plants yet to be studied for any pharmacological activity. These molecules form plants are usually deposited in natural product databases from where their structures can be downloaded for studies using Computer-Aided Drug Design. Some of them are also available for purchase for in-vitro and in-vivo studies. Some of the natural product databases include;

• ColleCtion of Open NatUral producTs (COCONUT) [75], containing 406,747 phytocompounds

• African Natural Products Database (ANPDB) [76, 77], containing 6515 phytocompounds

• Comprehensive Marine Natural Products Database (CMNPD) [78], containing 32,000 compounds

These isolated and identified natural products can also serve as a primary source for new molecule development through in-silico structural modification and synthesis. The existence of these natural products and these databases has provided a vast background for targeted natural product drug design and development. To be able to utilize these natural compounds in receptor/protein/enzyme targeted drug design and development in-silico, the receptor/protein/enzyme need to be available in a portable format that will enable its utilization in-silico, which is provided in protein databases.

4. Protein databases

A protein database is a body of data derived from physical, chemical and biological information about the sequence, domain structure, function, three-dimensional structure, and protein-protein interactions. Together, protein databases can serve as a database of protein sequences. Therefore, it is significant to utilize suitable protein databases that can analyze and store data relating to protein science and also expedite the utilization of analytical software accessible to the scientific community. Protein databases can be broadly grouped into two types. The first is a universal type, a set of proteins found in all identified biological species. The second kind of protein database is a specialized database that deals with proteins belonging to a specific group or family of certain species. In addition, each protein database can be further categorized according to the type of information required [79].

4.1 Categories of a protein database

Since protein datasets are being developed from different experimental groups, it would be necessary to provide suitable databases to meet their needs. Presently there are several types of protein databases accessible to the public, which can be further classified into more specialized categories based on the type of information sought [79].

4.1.1 Protein sequence database

Protein sequences consist of 20 different amino acids; this sequence is known as the primary structure of a protein. This type of protein database, which collects amino acid sequences of proteins and related information, is termed a protein sequence database. Examples of this type of database include; Swiss-Prot [80], TrEMBL [80], PIR [81], DDBJ [82], etc.

4.1.2 Protein structure databases

Protein structure regulates function, given that the specificity of active sites and binding sites hinges on the exact three-dimensional conformation. Protein structure databases contain information related to three-dimensional protein structure and secondary structure obtained from analyses by X-ray crystallography, electron microscopy and NMR. Examples include Protein Data Bank (PDB) [83], etc.

4.1.3 Protein-protein interaction databases

A protein-protein interaction database is developed on the basis of protein-protein interaction information gotten from yeast two-hybrid, co-purification, affinity column chromatography, in vitro binding and IP/coIP (protein immunoprecipitation (IP)/ co-immunoprecipitation (Co-IP) methods. Examples include; BIND (biomolecular interaction network database) [84], DIP (database of interacting proteins) [85], MINT (molecular interactions database) [86], etc.

4.1.4 Protein pattern and profile databases

Motifs can be identified in protein, DNA, and RNA sequences, but the most familiar use of motif-based analysis is the identification of sequence motifs conforming to structural or functional features in proteins. One of the essential instruments for sequence analysis is the utilization of protein sequences or profiles to establish protein function [87, 88]. Example, Interpro [89], etc.

4.1.5 2-D PAGE databases

These 2-D PAGE databases comprise gel image data acquired by examining the 2-DE and documented data on gel spots about molecular mass (M.W.), isoelectric point (pI), a status report on the identified location, and cross-reference links [90].

4.1.6 Metabolic pathway databases

Metabolic databases offer descriptive data on enzymes, biochemical reactions and metabolic pathways. Examples are BioCyc [91], MetaCyc [92], etc.

4.1.7 Signaling pathway databases

This signaling pathway database is to inspire complementary investigation in individual laboratories and to enable access to essential information on biological signaling pathways. This database can be classified into the following areas, depending on the format, for it contains both graph and tree-type data structures.

Examples are TRANSPATH [93], etc.

With these receptor/protein/enzyme databases and natural product databases, more in-silico research aiming towards the discovery and development of more therapeutic inhibitors from natural products can be initiated. At the present time, in-silico approaches have become an essential aspect of the drug discovery procedure. The use of in-silico/ computational approaches to discover, develop, and analyze drugs and similar biologically active molecules is referred to as Computer-Aided Drug Design.

5. Computer-aided drug design/repurposing

Computer-aided drug design, which commenced in about the early 1970s, is a process where new drug molecules are designed/identified, redesigned or repurposed to bind with a biological target of known or predictable 3D structure and express substantial affinity/specificity [94]. The core purpose of drug design methods is to utilize the receptor/ligand tertiary structures for accelerating the drug discovery process and also repurposing or enhancing the inhibition properties of a ligand, which could act as a therapeutic inhibitor. In performing computer-aided drug design, two approaches can be implemented. The first is structure-based (target-based), while the second is ligand-based (analogue-based) [95].

Methods by which the 3D structure of a protein can be generated include X-ray crystallography, NMR, electron microscopy, or prediction based on homology in silico. Once the 3D structure has been resolved, the protein’s binding site or active site is identified. Structural-based drug design methods recognize/design an inhibitor having functional properties complementary to the protein binding site. These include molecular docking and the design of de novo molecules. Molecular docking techniques assess a molecule’s most viable binding geometries at the binding site of a target protein in the 3D space. These binding geometries are termed binding poses, which include both configurations, which are the molecule’s position in the target or the receptor-binding site and conformational sampling. These binding geometries are recorded using molecular mechanics and calibrated according to the intensity of the interaction with the receptor. This process can be performed on large high-speed databases (virtual screening), allowing rapid molecular screening to recognize the right inhibitors. De novo design approaches form ligands that have not been synthesized before. In this approach, the functional groups responsible for interactions with the target receptor are positioned in the additional 3D space of the protein binding site and are linked to the binding scaffolding. This technique assumes that only the functional groups of a molecule are responsible for their activity and not the scaffold [96].

Ligand-based drug design approaches like quantitative structure-activity relationship (QSAR) and pharmacophore modeling have established their effectiveness in designing/envisaging the action of new molecules and in searching chemical databases to detect novel lead scaffolds in the absence of target receptor 3D structure [97, 98, 99]. QSAR and quantitative structure-property relationship approach developed a mathematical model for biological activity employing numerous structural and functional properties [100, 101, 102]. This activity (dependent quantity) and property (independent quantity) model can be used to contemplate the activity of novel molecules as inhibitors without knowing the structure of the 3D receptor. These relations can be obtained using statistical measurements such as regression approach, neural networks, main component analysis (PCA), partial least squares (PLS).

These days in-silico drug repurposing is attracting global awareness as a result of the accessibility of a huge amount of data on protein structures, pharmacophores, disease data, clinical investigations, or gene expression profiles of medicines. As well, increased public social networking technologies and computational access to genetic information have greatly helped computational approaches predict new indications. As a result, most pharmaceutical companies use bioinformatics or modern computing resources to reposition drugs from various chemical spaces. The ultimate desire of each pharmaceutical company is to be able to put medication into the market with increased speed and at the same time lower the cost of design and development. The powerful in-silico technology can provide these benefits. With the increase of drug-related data available, new computational approaches with improved recall and precision for targeted profiling of small compounds have been developed. These approaches enhance the repurposing procedure by including chemoinformatics, bioinformatics, network biology, systems biology or genomic information to uncover unidentified targets and mechanisms for approved drugs with accelerated timeframes.

6. New therapeutic inhibitors and natural products

In utilizing existing drugs in drug repurposing and natural molecules in the discovery and development of new therapeutic inhibitors, all we have discussed above: classification of therapeutic inhibitors, protein database, natural product database and Computer-Aided Drug design, have essential roles to play.

Before one can aim at targeted drug design, there must be a disease of interest at heart. Then, understanding the pathophysiology and pathogenesis of the disease. A good understanding of these processes to identify the protein and enzymes involved in the pathophysiology and pathogenesis and also the role(s) each of these proteins and enzymes plays. Apart from the role the proteins and enzymes play in the diseases of interest development, there might also be other positive roles (s) these proteins and enzymes play in the system. With all these, a proper decision can be made on the possibility of achieving a beneficial therapeutic effect without causing a chronic negative outcome to the system.

Protein databases already described above ensure the availability of proteins and enzymes in a format that can be downloaded and utilized for in-silico studies. These databases contain proteins and enzymes from humans, animals and different levels of organisms. Some of the databases can be accessed for free, making them open for any interested researcher to access. An interesting feature of most of these proteins available on protein databases like protein data banks is that their active sites are specified, with a ligand molecule attached, making it easier for a specific study to be carried out using the proteins and enzymes.

The natural product databases described above and existing drugs library like drug bank provide the ligands (molecules) which can be utilized or from which new therapeutic inhibitors can be sourced for the purpose of drug repurposing. Because of the number of these natural products as contained in the databases, handling such an enormous amount of data might be challenging, but with the advances in in-silico high throughput screening, there are drug design applications that can be deployed in minimizing the number of ligands that could lead to hit molecule(s).

With the advances in computer-aided drug design and bioinformatics, certain steps can be undertaken using natural products towards the discovery and development of better therapeutic inhibitors and also repurposing already existing drugs for the discovery and development of better therapeutic inhibitors. So many studies are already in progress using these steps. There are so many applications that can utilize in the in-silico study for the discovery and development of new therapeutic inhibitors. With these applications, drug-likeness and ADMET of thousands of natural compounds can be predicted, protein active site can be established, molecular docking can be simulated, molecular dynamic simulation can be carried out, and in-silico that is of the essence in determining which molecule(s) has the lowest chance of failure if taken to in-vitro experiments.

7. Conclusion

Search for discovery and development of new therapeutic inhibitors is an inexhaustible area of research because, even though there are already existing therapeutic inhibitors for different disease conditions, there is always a need for a better option than what is currently available through drug repurposing of already existing drugs or natural products. The abundance of unutilized natural product molecules provides us with a wide range of options from which new and better option therapeutic inhibitors can be sourced. It is well known that the search for the better option is time-consuming and also expensive; there is the need to ensure that the process of discovery and development of new therapeutic inhibitors is undertaken in a manner that minimizes the chances of failure of the process. With the information currently available regarding protein and metabolic pathway databases, ligand and natural product databases, Computer-Aided Drug Design can be utilized by researchers to initiate steps that will ensure that the most suitable drug repurposing candidates are identified earlier in the process of discovery and development of new therapeutic inhibitor.

Acknowledgments

The authors are grateful to the members of our research group, the CURIES, who have been a source of encouragement to the authors.