Research article Special Issues

A GraphSAGE-based model with fingerprints only to predict drug-drug interactions


  • Drugs are an effective way to treat various diseases. Some diseases are so complicated that the effect of a single drug for such diseases is limited, which has led to the emergence of combination drug therapy. The use multiple drugs to treat these diseases can improve the drug efficacy, but it can also bring adverse effects. Thus, it is essential to determine drug-drug interactions (DDIs). Recently, deep learning algorithms have become popular to design DDI prediction models. However, most deep learning-based models need several types of drug properties, inducing the application problems for drugs without these properties. In this study, a new deep learning-based model was designed to predict DDIs. For wide applications, drugs were first represented by commonly used properties, referred to as fingerprint features. Then, these features were perfectly fused with the drug interaction network by a type of graph convolutional network method, GraphSAGE, yielding high-level drug features. The inner product was adopted to score the strength of drug pairs. The model was evaluated by 10-fold cross-validation, resulting in an AUROC of 0.9704 and AUPR of 0.9727. Such performance was better than the previous model which directly used drug fingerprint features and was competitive compared with some other previous models that used more drug properties. Furthermore, the ablation tests indicated the importance of the main parts of the model, and we analyzed the strengths and limitations of a model for drugs with different degrees in the network. This model identified some novel DDIs that may bring expected benefits, such as the combination of PEA and cannabinol that may produce better effects. DDIs that may cause unexpected side effects have also been discovered, such as the combined use of WIN 55,212-2 and cannabinol. These DDIs can provide novel insights for treating complex diseases or avoiding adverse drug events.

    Citation: Bo Zhou, Bing Ran, Lei Chen. A GraphSAGE-based model with fingerprints only to predict drug-drug interactions[J]. Mathematical Biosciences and Engineering, 2024, 21(2): 2922-2942. doi: 10.3934/mbe.2024130

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  • Drugs are an effective way to treat various diseases. Some diseases are so complicated that the effect of a single drug for such diseases is limited, which has led to the emergence of combination drug therapy. The use multiple drugs to treat these diseases can improve the drug efficacy, but it can also bring adverse effects. Thus, it is essential to determine drug-drug interactions (DDIs). Recently, deep learning algorithms have become popular to design DDI prediction models. However, most deep learning-based models need several types of drug properties, inducing the application problems for drugs without these properties. In this study, a new deep learning-based model was designed to predict DDIs. For wide applications, drugs were first represented by commonly used properties, referred to as fingerprint features. Then, these features were perfectly fused with the drug interaction network by a type of graph convolutional network method, GraphSAGE, yielding high-level drug features. The inner product was adopted to score the strength of drug pairs. The model was evaluated by 10-fold cross-validation, resulting in an AUROC of 0.9704 and AUPR of 0.9727. Such performance was better than the previous model which directly used drug fingerprint features and was competitive compared with some other previous models that used more drug properties. Furthermore, the ablation tests indicated the importance of the main parts of the model, and we analyzed the strengths and limitations of a model for drugs with different degrees in the network. This model identified some novel DDIs that may bring expected benefits, such as the combination of PEA and cannabinol that may produce better effects. DDIs that may cause unexpected side effects have also been discovered, such as the combined use of WIN 55,212-2 and cannabinol. These DDIs can provide novel insights for treating complex diseases or avoiding adverse drug events.



    Fractional calculus has come out as one of the most applicable subjects of mathematics [1]. Its importance is evident from the fact that many real-world phenomena can be best interpreted and modeled using this theory. It is also a fact that many disciplines of engineering and science have been influenced by the tools and techniques of fractional calculus. Its emergence can easily be traced and linked with the famous correspondence between the two mathematicians, L'Hospital and Leibnitz, which was made on 30th September 1695. After that, many researchers tried to explore the concept of fractional calculus, which is based on the generalization of nth order derivatives or n-fold integration [2,3,4].

    Recently, Khan and Khan [5] have discovered novel definitions of fractional integral and derivative operators. These operators enjoy interesting properties such as continuity, boundedeness, linearity etc. The integral operators, they presented, are stated as under:

    Definition 1 ([5]). Let hLθ[s,t](conformable integrable on [s,t][0,)). The left-sided and right-sided generalized conformable fractional integrals τθKνs+ and τθKνt of order ν>0 with θ(0,1], τR, θ+τ0 are defined by:

    τθKνs+h(r)=1Γ(ν)rs(rτ+θwτ+θτ+θ)ν1h(w)wτdθw,r>s, (1.1)

    and

    τθKνth(r)=1Γ(ν)tr(wτ+θrτ+θτ+θ)ν1h(w)wτdθw,t>r, (1.2)

    respectively, and τθK0s+h(r)=τθK0th(r)=h(r). Here Γ denotes the well-known Gamma function.

    Here the integral tsdθw represents the conformable integration, defined as:

    tsh(w)dθw=tsh(w)wθ1dw. (1.3)

    The operators defined in Definition 1 are in generalized form and contain few important operators in themselves. Here, only the left-sided operators are presented, the corresponding right-sided operators may be deduced in the similar way. Moreover, to understand the theory of conformable fractional calculus, one can see [5,6,7]. Also, the basic theory of fractional calculus can be found in the books [1,8,9] and for the latest research in this field one can see [3,4,10,11,12] and the references there in.

    Remark 1. 1) For θ=1 in the Definition 1, the following Katugampula fractional integral operator is obtained [13]:

    τ1Kνs+h(r)=1Γ(ν)rs(rτ+1wτ+1τ+1)ν1h(w)dw,r>s. (1.4)

    2) For τ=0 in the Definition 1, the New Riemann Liouville type conformable fractional integral operator is obtained as given below:

    0θKνs+h(r)=1Γ(ν)rs(rθwθθ)ν1h(w)dθw,r>s. (1.5)

    3) Using the definition of conformable integral given in (1.3) and L'Hospital rule, it is straightforward that when θ0 in (1.5), we get the Hadamard fractional integral operator as follows:

    00+Kνs+h(r)=1Γ(ν)rs(logrw)ν1h(w)dww,r>s. (1.6)

    4) For θ=1 in (1.5), the well-known Riemann-Liouville fractional integral operator is obtained as follows:

    01Kνs+h(r)=1Γ(ν)rs(rw)ν1h(w)dw,r>s. (1.7)

    5) For the case ν=1,τ=0 in Definition 1, we get the conformable fractional integrals. And when θ=ν=1, τ=0, we get the classical Riemann integrals.

    This subsection is devoted to start with the definition of convex function, which plays a very important role in establishment of various kinds of inequalities [14]. This definition is given as follows [15]:

    Definition 2. A function h:IRR is said to be convex on I if the inequality

    h(ηs+(1η)t)ηh(s)+(1η)h(t) (1.8)

    holds for all s,tI and 0η1. The function h is said to be concave on I if the inequality given in (1.8) holds in the reverse direction.

    Associated with the Definition 2 of convex functions the following double inequality is well-known and it has been playing a key role in various fields of science and engineering [15].

    Theorem 1. Let h:IRR be a convex function and s,tI with s<t. Then we have the following Hermite-Hadamard inequality:

    h(s+t2)1tstsh(τ)dτh(s)+h(t)2. (1.9)

    This inequality (1.9) appears in a reversed order if the function h is supposed to be concave. Also, the relation (1.9) provides upper and lower estimates for the integral mean of the convex function h. The inequality (1.9) has various versions (extensions or generalizations) corresponding to different integral operators [16,17,18,19,20,21,22,23,24,25] each version has further forms with respect to various kinds of convexities [26,27,28,29,30,31,32] or with respect to different bounds obtained for the absolute difference of the two leftmost or rightmost terms in the Hermite-Hadamard inequality.

    By using the Riemann-Liouville fractional integral operators, Sirikaye et al. have proved the following Hermite-Hadamard inequality [33].

    Theorem 2. ([33]). Let h:[s,t]R be a function such that 0s<t and hL[s,t]. If h is convex on [s,t], then the following double inequality holds:

    h(s+t2)Γ(ν+1)2(ts)ν[01Kνs+h(t)+01Kνth(s)]h(s)+h(t)2. (1.10)

    For more recent research related to generalized Hermite-Hadamard inequality one can see [34,35,36,37,38,39,40,41,42] and the references therein.

    Motivated from the Riemann-Liouville version of Hermite-Hadamard inequality (given above in (1.10)), we prove the same inequality for newly introduced generalized conformable fractional operators. As a result we get a more generalized inequality, containing different versions of Hermite-Hadamard inequality in single form. We also prove an identity for generalized conformable fractional operators and establish a bound for the absolute difference of two rightmost terms in the newly obtained Hermite-Hadamard inequality. We point out some relations of our results with those of other results from the past. At the end we present conclusion, where directions for future research are also mentioned.

    In the following theorem the well-known Hermite-Hadamard inequality for the newly defined integral operators is proved.

    Theorem 3. Let ν>0 and τR,θ(0,1] such that τ+θ>0. Let h:[s,t][0,)R be a function such that hLθ[s,t](conformal integrable on [s, t]). If h is also a convex function on [s,t], then the following Hermite-Hadamard inequality for generalized conformable fractional Integrals τθKνs+ and τθKνt holds:

    h(s+t2)(τ+θ)νΓ(ν+1)4(tτ+θsτ+θ)ν[τθKνs+H(t)+τθKνtH(s)]h(s)+h(t)2, (2.1)

    where H(x)=h(x)+˜h(x), ˜h(x)=h(s+tx).

    Proof. Let η[0,1]. Consider x,y[s,t], defined by x=ηs+(1η)t,y=(1η)s+ηt. Since h is a convex function on [s,t], we have

    h(s+t2)=h(x+y2)h(x)+h(y)2=h(ηs+(1η)t)+h((1η)s+ηt)2. (2.2)

    Multiplying both sides of (2.2) by

    (ts)(τ+θ)1ν((1η)s+ηt)τ+θ1Γ(ν)[tτ+θ((1η)s+ηt)τ+θ]1ν,

    and integrating with respect to η, we get

    (ts)(τ+θ)1νΓ(ν)h(s+t2)10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νdη(ts)(τ+θ)1νΓ(ν)12{10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh(ηs+(1η)t)dη+10(1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh((1η)s+ηt)dη}. (2.3)

    Note that we have

    10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νdη=1ν(τ+θ)(ts)(tτ+θsτ+θ)ν.

    Also, by using the identity ˜h((1η)s+ηt)=h(ηs+(1η)t), and making substitution (1η)s+ηt=w, we get

    (ts)(τ+θ)1νΓ(ν)10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh(ηs+(1η)t)dη=(τ+θ)1νΓ(ν)tswτ+θ1[tτ+θwτ+θ]1ν˜h(w)dw=(τ+θ)1νΓ(ν)tswτ[tτ+θwτ+θ]1ν˜h(w)dθw=τθKνs+˜h(t). (2.4)

    Similarly

    (ts)(τ+θ)1νΓ(ν)10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh(ηt+(1η)s)dη=τθKνs+h(t). (2.5)

    By substituting these values in (2.3), we get

    (tτ+θsτ+θ)νΓ(ν+1)(τ+θ)νh(s+t2)τθKνs+H(t)2. (2.6)

    Again, by multiplying both sides of (2.2) by

    (ts)(τ+θ)1ν((1η)s+ηt)τ+θ1Γ(ν)[((1η)s+ηt)τ+θsτ+θ]1ν,

    and then integrating with respect to η and by using the same techniques used above, we can obtain:

    (tτ+θsτ+θ)νΓ(ν+1)(τ+θ)νh(s+t2)τθKνtH(s)2. (2.7)

    Adding (2.7) and (2.6), we get:

    h(s+t2)Γ(ν+1)(τ+θ)ν4(tτ+θsτ+θ)ν[τθKνs+H(t)+τθKνtH(s)]. (2.8)

    Hence the left-hand side of the inequality (2.1) is established.

    Also since h is convex, we have:

    h(ηs+(1η)t)+h((1η)s+ηt)h(s)+h(t). (2.9)

    Multiplying both sides

    (ts)(τ+θ)1ν((1η)s+ηt)τ+θ1Γ(ν)[tτ+θ((1η)s+ηt)τ+θ]1ν,

    and integrating with respect to η we get

    (ts)(τ+θ)1νΓ(ν)10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh(ηs+(1η)t)dη+(ts)(τ+θ)1νΓ(ν)10((1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νh(ηt+(1η)s)dη(ts)(τ+θ)1νΓ(ν)[h(s)+h(t)]10(1η)s+ηt)τ+θ1[tτ+θ((1η)s+ηt)τ+θ]1νdη, (2.10)

    that is,

    τθKνs+H(t)(tτ+θsτ+θ)νΓ(ν+1)(τ+θ)ν[h(s)+h(t)]. (2.11)

    Similarly multiplying both sides of (2.9) by

    (ts)(τ+θ)1ν((1η)s+ηt)τ+θ1Γ(ν)[((1η)s+ηt)τ+θsτ+θ]1ν,

    and integrating with respect to η, we can obtain

    τθKνtH(s)(tτ+θsτ+θ)νΓ(ν+1)(τ+θ)ν[h(s)+h(t)]. (2.12)

    Adding the inequalities (2.11) and (2.12), we get:

    Γ(ν+1)(τ+θ)ν4(tτ+θsτ+θ)ν[τθKνtH(s)+τθKνs+H(t)]h(s)+h(t)2. (2.13)

    Combining (2.8) and (2.13), we get the required result.

    The inequality in (2.1) is in compact form containing few inequalities for different integrals in it. The following remark tells us about that fact.

    Remark 2. 1) For θ=1 in (2.1), we get Hermite-Hadamard inequality for Katugampola fractional integral operators, as follows [38]:

    h(s+t2)(τ+1)νΓ(ν+1)4(tτ+1sτ+1)ν[τ1Kνs+H(t)+τ1KνtH(s)]h(s)+h(t)2, (2.14)

    where H(x)=h(x)+˜h(x), ˜h(x)=h(s+tx).

    2) For τ=0 in (2.1), we get Hermite-Hadamard inequality for newly obtained Riemann Liouville type conformable fractional integral operators, as follows:

    h(s+t2)θνΓ(ν+1)4(tθsθ)ν[0θKνs+H(t)+0θKνtH(s)]h(s)+h(t)2, (2.15)

    where H(x)=h(x)+˜h(x), ˜h(x)=h(s+tx).

    3) For τ+θ0, in (2.1), applying L'Hospital rule and the relation (1.3), we get Hermite-Hadamard inequality for Hadamard fractional integral operators, as follows:

    h(s+t2)Γ(ν+1)2(lnts)ν[00+Kνs+h(t)+00+Kνth(s)]h(s)+h(t)2. (2.16)

    4) For τ+θ=1 in (2.1), the Hermite-Hadamard inequality is obtained for Riemann-Liouville fractional integrals [33]:

    h(s+t2)Γ(ν+1)2(ts)ν[01Kνs+h(t)+01Kνth(s)]h(s)+h(t)2. (2.17)

    5) For the case ν=1,τ=0 in (2.1), the Hermite-Hadamard inequality is obtained for the conformable fractional integrals as follows:

    h(s+t2)θ2(tθsθ)tsH(w)dθwh(s)+h(t)2. (2.18)

    6) When θ=ν=1, τ=0 the Hermite-Hadamard inequality is obtained for classical Riemann integrals [15]:

    h(s+t2)1tstsh(w)dwh(s)+h(t)2. (2.19)

    To bound the difference of two rightmost terms in the main inequality (2.1), we need to establish the following Lemma.

    Lemma 1. Let τ+θ>0 and ν>0. If hLθ[s,t], then

    h(s)+h(t)2(τ+θ)νΓ(ν+1)4(tτ+θsτ+θ)ν[τθKνs+H(t)+τθKνtH(s)]=ts4(tτ+θsτ+θ)ν10Δντ+θ(η)h(ηs+(1η)t)dη, (2.20)

    where

    Δντ+θ(η)=[(ηs+(1η)t)τ+θsτ+θ]ν[(ηt+(1η)s)τ+θsτ+θ]ν+[tτ+θ((1η)s+ηt)τ+θ]ν[tτ+θ((1η)t+ηs)τ+θ]ν.

    Proof. With the help of integration by parts, we have

    τθKνs+H(t)=(tτ+θsτ+θ)ν(τ+θ)νΓ(ν+1)H(s)+(ts)ν(τ+θ)νΓ(ν+1)10[tτ+θ((1η)s+ηt)τ+θ]νH(ηt+(1η)s)dη. (2.21)

    Similarly, we have

    τθKνtH(s)=(tτ+θsτ+θ)ν(τ+θ)νΓ(ν+1)H(t)(ts)ν(τ+θ)νΓ(ν+1)10[((1η)s+ηt)τ+θsτ+θ]νH(ηt+(1η)s)dη. (2.22)

    Using (2.21) and (2.22) we have

    4(tτ+θsτ+θ)νts(h(s)+h(t)2(τ+θ)νΓ(ν+1)4(tτ+θsτ+θ)ν[τθKνtH(s)+τθKνs+H(t)])=10([((1η)s+ηt)τ+θsτ+θ]ν[(tτ+θ((1η)s+ηt)τ+θ]ν)H(ηt+(1η)s)dη. (2.23)

    Also, we have

    H(ηt+(1η)s)=h(ηt+(1η)s)h(ηs+(1η)t),η[0,1]. (2.24)

    And

    10[((1η)s+ηt)τ+θsτ+θ]νH(ηt+(1η)s)dη=10[((1η)t+ηs)τ+θsτ+θ]νh(ηs+(1η)t)dη10[((1η)s+ηt)τ+θsτ+θ]νh(ηs+(1η)t)dη. (2.25)

    Also, we have

    10[tτ+θ((1η)s+ηt)τ+θ]νH(ηt+(1η)s)dη=10[tτ+θ((1η)t+ηs)τ+θ]νh(ηs+(1η)t)dη10[tτ+θ((1η)s+ηt)τ+θ]νh(ηs+(1η)t)dη. (2.26)

    Using (2.23), (2.25) and (2.26) we get the required result.

    Remark 3. When τ+θ=1 in Lemma 1, we get the Lemma 2 in [33].

    Definition 3. For ν>0, we define the operators

    Ων1(x,y,τ+θ)=s+t2s|xw||yτ+θwτ+θ|νdwts+t2|xw||yτ+θwτ+θ|νdw, (2.27)

    and

    Ων2(x,y,τ+θ)=s+t2s|xw||wτ+θyτ+θ|νdwts+t2|xw||wτ+θyτ+θ|νdw, (2.28)

    where x,y[s,t][0,) and τ+θ>0.

    Theorem 4. Let h be a conformable integrable function over [s,t] such that |h| is convex function. Then for ν>0 and τ+θ>0 we have:

    |h(s)+h(t)2(τ+θ)νΓ(ν+1)4(tτ+θsτ+θ)ν[τθKνs+H(t)+τθKνtH(s)]|Kντ+θ(s,t)4(ts)(tτ+θsτ+θ)ν(|h(s)|+|h(t)|), (2.29)

    where Kντ+θ(s,t)=Ων1(t,t,τ+θ)+Ων2(s,s,τ+θ)Ων2(t,s,τ+θ)Ων1(s,t,τ+θ).

    Proof. Using Lemma 1 and convexity of |h|, we have:

    |h(s)+h(t)2(τ+θ)νΓ(ν+1)4(tτ+θsτ+θ)ν[τθKνs+H(t)+τθKνtH(s)]|ts4(tτ+θsτ+θ)ν10|Δντ+θ(η)||h(ηs+(1η)t)|dηts4(tτ+θsτ+θ)ν(|h(s)|10η|Δντ+θ(η)|dη+|h(t)|10(1η)|Δντ+θ(η)|dη). (2.30)

    Here 10η|Δντ+θ(η)|dη=1(ts)2ts|ψ(u)|(tu)du,

    and ψ(u)=(uτ+θsτ+θ)ν((t+su)τ+θsτ+θ)ν+(tτ+θ(s+tu)τ+θ)ν(tτ+θuτ+θ)ν.

    We observe that ψ is a nondecreasing function on [s,t]. Moreover, we have:

    ψ(s)=2(tτ+θsτ+θ)ν<0,

    and also ψ(s+t2)=0. As a consequence, we have

    {ψ(u)0,if sus+t2,ψ(u)>0,if s+t2<ut.

    Thus we get

    10η|Δντ+θ(η)|dη=1(ts)2ts|ψ(u)|(tu)du=1(ts)2[s+t2sψ(u)(tu)du+ts+t2ψ(u)(tu)du]=1(ts)2[K1+K2+K3+K4], (2.31)

    where

    K1=s+t2s(tu)(uτ+θsτ+θ)νdu+ts+t2(tu)(uτ+θsτ+θ)νdu, (2.32)
    K2=s+t2s(tu)((t+su)τ+θsτ+θ)νduts+t2(tu)((t+su)τ+θsτ+θ)νdu, (2.33)
    K3=s+t2s(tu)(tτ+θ(s+tu)τ+θ)νdu+ts+t2(tu)(tτ+θ(s+tu)τ+θ)νdu, (2.34)

    and

    K4=s+t2s(tu)(tτ+θuτ+θ)νduts+t2(tu)(tτ+θuτ+θ)νdu. (2.35)

    We can see here that K1=Ων2(t,s,τ+θ), K4=Ων1(t,t,τ+θ).

    Also, by using of change of the variables v=s+tu, we get

    K2=Ων2(s,s,τ+θ),K3=Ων1(s,t,τ+θ). (2.36)

    By substituting these values in (2.31), we get

    10ηΔντ+θ(η)dη=Ων2(t,s,τ+θ)+Ων1(t,t,τ+θ)+Ων2(s,s,τ+θ)Ων1(s,t,τ+θ)(ts)2. (2.37)

    Similarly, we can find

    10(1η)Δντ+θ(η)dη=Ων2(s,s,τ+θ)Ων2(t,s,τ+θ)+Ων1(t,t,τ+θ)Ων1(s,t,τ+θ)(ts)2. (2.38)

    Finally, by using (2.30), (2.37) and (2.38) we get the required result.

    Remark 4. when τ+θ=1 in (2.29), we obtain

    |h(s)+h(t)2Γ(ν+1)2(ts)ν[01Kνth(s)+01Kνs+h(t)]|(ts)2(ν+1)(112ν)[h(s)+h(t)],

    which is Theorem 3 in [33].

    A generalized version of Hermite-Hadamard inequality via newly introduced GC fractional operators has been acquired successfully. This result combines several versions (new and old) of the Hermite-Hadamard inequality into a single form, each one has been discussed by fixing parameters in the newly established version of the Hermite-Hadamard inequality. Moreover, an identity containing the GC fractional integral operators has been proved. By using this identity, a bound for the absolute of the difference between the two rightmost terms in the newly established Hermite-Hadamard inequality has been presented. Also, some relations of our results with those of already existing results have been pointed out. Since this is a fact that there exist more than one definitions for fractional derivatives [2] which makes it difficult to choose a convenient operator for solving a given problem. Thus, in the present paper, the GC fractional operators (containing various previously defined fractional operators into a single form) have been used in order to overcome the problem of choosing a suitable fractional operator and to provide a unique platform for researchers working with different operators in this field. Also, by making use of GC fractional operators one can follow the research work which has been performed for the two versions (1.9) and (1.10) of Hermite-Hadamard inequality.

    This work was supported by the Natural Science Foundation of China (Grant Nos. 61673169, 11301127, 11701176, 11626101, 11601485).

    The authors declare that there are no conflicts of interest regarding the publication of this paper.



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